TRAVEL INDUSTRY ECONOMICS a guide for financial analysis. [4 ed.] 9783030633516, 3030633519

Table of contents :
Preface
Contents
About the Author
Part I: Introduction
Chapter 1: Economic Perspectives
1.1 Time Concepts
1.1.1 Alternatives
1.1.2 Availabilities
1.2 Supply and Demand Factors
1.2.1 Productivity
1.2.2 Demand for Leisure
1.2.3 Expected Utility Comparisons
1.2.4 Demographics and Debts
1.2.5 Barriers to Entry
1.3 Primary Principles
1.3.1 Marginal Matters
1.3.2 Price Discrimination
1.3.3 Public-Good Characteristics
1.3.4 Power Laws28
1.4 Personal-Consumption Expenditure Relationships
1.5 Price Effects
1.6 Industry Structures and Segments
1.6.1 Structures
1.6.2 Segments
1.6.3 Advertising and Promotion
1.7 Valuation Variables
1.7.1 Discounted Cash Flows
1.7.2 Comparison Methods
1.7.3 Options
1.7.4 Business Model Aspects
1.8 Macro Trend Disruptors
1.8.1 Oil
1.8.2 Health Issues
1.8.3 Wars and Politics
1.9 Big Data and Artificial Intelligence (AI) Aspects
1.10 Concluding Remarks
References
Further Reading
Part II: Getting There
Chapter 2: Wings
2.1 Onward and Upward
2.1.1 Technology and Early History
2.1.2 Regulation and Deregulation
2.2 Operational Characteristics
2.2.1 Structural Features
2.2.2 Basics
2.2.3 Marketing Features
2.2.4 Airport Management
2.3 Economic Characteristics
2.3.1 Macroeconomic Sensitivities
2.3.2 Microeconomic Matters
2.4 Financing and Accounting Issues
2.4.1 Financial Features
2.4.2 Financing
2.4.3 Accounting
2.5 Valuing Airline Properties
2.6 Concluding Remarks
References
Further Reading
Chapter 3: Water and Wheels
3.1 Wetting the Whistle
3.1.1 Fantasy Islands
3.1.2 Operational Aspects
3.1.3 Economic Aspects
3.2 Automobiles
3.2.1 Jamming
3.2.2 Car Rentals
3.3 Kings of the Road
3.4 Iron and Steel
3.5 Finance and Accounting
3.6 Concluding Remarks
References
Further Reading
Part III: Being There
Chapter 4: Hotels
4.1 Rooms at the inn
4.2 Basics
4.2.1 Structural Features
4.2.2 Operating Features
4.2.3 Marketing Matters
4.3 Financial and Economic Aspects
4.3.1 Financing Frameworks
4.3.2 Accounting Issues
4.3.3 Economic Sensitivities
4.4 Valuing Hotel Assets
4.5 Concluding Remarks
References
Further Reading
Part IV: Doing Things There
Chapter 5: Casinos
5.1 From Ancient History
5.1.1 At First
5.1.2 Gaming in America
5.1.3 Asia´s Jackpot
5.2 Money Talks
5.2.1 Macroeconomic Matters
5.2.2 Funding Functions
5.2.3 Regulation
5.2.4 Financial Performance and Valuation
5.3 Underlying Profit Principles and Terminology
5.3.1 Principles
5.3.2 Terminology and Performance Standards
5.4 Casino Management and Accounting Policies
5.4.1 Marketing Matters
5.4.2 Cash and Credit
5.4.3 Procedural Paradigms
5.5 Gambling and Economics
5.6 Concluding Remarks
References
Further Reading
Chapter 6: Amusement/Theme Parks and Resorts
6.1 Flower Power
6.1.1 Gardens and Groves
6.1.2 Modern Times
6.2 Financial Operating Characteristics
6.3 Recreational Resorts
6.4 Economic Sensitivities
6.5 Valuing Theme-Park Properties
6.6 Concluding Remarks
References
Further Reading
Chapter 7: Tourism
7.1 Don´t Leave Home Without It
7.2 Economic Aspects
7.2.1 Demand Models
7.2.2 Multipliers
7.2.3 Balance of Trade
7.2.4 Input-Output Analysis
7.3 Travel Laws and Regulation
7.4 Concluding Remarks
References
Further Reading
Part V: Roundup
Chapter 8: Performance and Policy
8.1 Common Elements
8.2 Public Policy Issues
8.3 Guidelines for Evaluation
8.4 Final Remarks
References
Appendix A: Sources of Information
Appendix B: Valuation Concepts
Glossary
References
Index

Citation preview

Harold L. Vogel

Travel Industry Economics A Guide for Financial Analysis Fourth Edition

Travel Industry Economics

Harold L. Vogel

Travel Industry Economics A Guide for Financial Analysis Fourth Edition

Harold L. Vogel Vogel Capital Management New York, NY, USA

ISBN 978-3-030-63350-9 ISBN 978-3-030-63351-6 https://doi.org/10.1007/978-3-030-63351-6

(eBook)

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

To my beautiful mom, whose love and spirit knew no bounds

Preface

trav
el—involves a trip, a journey, a transmission, and a movement from one place or time to another; in
dus
try—a specific branch of a craft, art, business, or trade that involves a division of labor and that requires significant investment capital and employs many people in organizations with similar technological and organizational structures used to provide goods and services that are largely substitutable; ec
o
nom
ics—a social science that studies how wealth is created, distributed, used, and consumed and that considers costs and returns. We are, it seems, all born with a natural curiosity—with an urge to travel. What normal infant, confined to crib or playpen, doesn’t soon want to explore the world beyond? What active teenager doesn’t want to scope out a new neighborhood or city or country? And what person hasn’t ever dreamt of how it would feel to travel across the boundaries of space or time? The urge to travel is universal. And this makes travel, as broadly defined, a big business indeed. In the United States, for example, travel and tourism is estimated to account for approximately 5% of gross domestic product and to be the third largest retail industry after automobile dealers and food stores. Clearly, in getting from here to there and back again, we need lots of goods and services. In fact, including everything, the travel industry turns out to be one of the world’s largest in terms of numbers of people employed and in total direct and indirect revenues generated. Three hundred million people—one of every ten employees worldwide—and more than US$4.0 trillion out of a total world economic output of around US$80 trillion are probably reasonable estimates for early in the third decade of the twenty-first century. With an industry so large it is difficult even to know where to begin. There are texts relating to hotel or restaurant or casino management procedures and strategies. There are tomes and stock brokerage house reports and consultants’ papers providing forecasts for the various travel-related business segments. Statistics of all types abound.

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Yet what seems to be missing is a concise treatment that ties together all the major industry segments from the perspective of a potential investor and financial economist. The mission is to thus broadly cover—for anyone who analyzes or manages or writes about travel-related investments—the financial and economic dynamics of the businesses that service the needs of people who, whether for pleasure (tourism) or commerce, require physical transportation: travel, in other words. In contrast, the underlying concept of my related work, Entertainment Industry Economics: A Guide for Financial Analysis, involves a different kind of transportation—that of people’s emotions. The style of that work as well as the chapters providing an economic overview and coverage of casinos and theme parks has been largely carried over. As in that volume, only those industry segments that have clearly defined borders and reliable data histories are examined Travel Industry Economics is primarily a text for graduate or advanced undergraduate students. The minimum requirement, supported by the appended glossary, is for the reader to have some familiarity with general economics and financial terminology. However, the present work is also intended to be of interest to general readers and should prove to be a handy reference for executives, financial analysts and investors, agents and legal advisors, accountants, economists, legislators, regulators, and journalists. The approach is holistic: The global travel ecosystem is always highly interdependent.and managers and analysts concentrating in any one sector increasingly need to also understand how related and adjacent sectors function, rely on, and connect to each other (e.g., airlines and hotels; casinos, theme parks, and tourism; airlines, airports, hotels, and cruises).. Instructors should find it easy to design one-semester courses centered on one or two areas. A minimal grasp of what travel industry economics is all about would require that virtually all students read at least Chapter 1 and, at the end of the course, the first section of Chap. 8. But different modules can be readily assembled and tailored. Among the most popular might be a concentration on transportation modes, mainly airlines (Chap. 2). Another would be a course covering hotels, gaming and resorts, theme parks, cruise ships, and tourism (Chaps. 3–7). To stay focused, however, the larger aspects of transportation industries—that might further include studies of airport planning and urban public transit—have been omitted. Analyses of tourism-related subjects that would take the text into areas such as trade and regional development are also merely sketched, as giving those topics the full treatments that they deserve would only distract from the primary purpose. For much the same reason, there is only tangential coverage of subjects that are commonly discussed in transport economics—externalities, infrastructure investment criteria, peak-load pricing, regulation, and social cost-benefit analysis, to name a few. This fourth edition updates, refreshes and extends coverage of tourism economics and adds sections on travel law and applications of big data and artificial intelligence technologies as well as new material on demographic spending patterns, the online travel agency business, and pandemic effects and affects. As in the previous edition, end-of-chapter further readings items that can conveniently form the basis for case studies and class discussions are indicated in boldface type.

Preface

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I am indebted to the transportation and travel industry economists upon whose academic shoulders this work rests. Particularly noteworthy for making the task of exposition a lot easier than it would have otherwise been are Kenneth Button’s Transport Economics; Kenneth Boyer’s Principles of Transportation Economics; Adrian Bull’s The Economics of Travel and Tourism; Rigas Doganis’s airline economics masterpiece, Flying Off Coursel and J. P. (Pat) Hanlon’s Global Airlines. Also proving invaluable were Morrell’s text on airline finance, Graham’s on managing airports, Block’s on REITs, Dickinson and Vladimir’s on cruise ships, Meyer and Oster’s on intercity passenger travel, Hayes and Ninemeier’s Hotel Operations Management, and the pioneering works in the casino gaming field by Friedman, Greenlees, and Scarne. In tourism, both Vanhove’s Economics of Tourism Destinations, Candela and Figini’s Economics of Tourism Destinations (same title) and Tisdell's Handbook of Tourism Economics provided a strong foundation for the expanded exposition here. In addition, the book has substantially benefited from data made available by the various industry trade groups including the Airline Transport Associations (ATA and IATA) and the International Civil Aviation Organization (ICAO). Similar benefit was derived from data of the Cruise Lines International Association (CLIA), the United Nations World Tourism Organization (WTO), and the International Association of Amusement Parks and Attractions (IAAPA). For the previous first edition, I thank Michael Lenz, Director of Investor Relations at American Airlines, for taking time to review a draft of the airline chapter and Erin Williams, Manager of Investor Relations at Royal Caribbean, who reviewed the cruise ship section. Thanks similarly to Laura Paugh, Vice President for Investor Relations at Marriott International, for appraising the hotel chapter. I am further indebted to Bobby Bowers of Smith Travel Research (STR) who kindly guided my quest for essential aggregate hotel industry data. Additional acknowledgements are also due to Arthur Gruen for time-use data, veteran gaming industry expert, Howard J. Klein, Vance Gulliksen, head of Public Relations at Carnival Cruise, to Robert Mandelbaum of PKF Hospitality Research, and to Pablo Alonso of Hotstats.com. This project and several earlier ones also benefited enormously from the support of Scott Parris, former longtime economics editor at Cambridge University Press, and for Springer editions Executive Editor Christian Rauscher and Associate Editor Barbara Bethke. Even with such impressive backup, however, the responsibility for any for any errors that may inadvertently remain is mine alone. In all, I hope and expect that readers will find Travel Industry Economics to be a truly enjoyable and moving experience. As Danish storyteller Hans Christian Andersen wrote, “to travel is to live.” All aboard! New York, NY March 2021

Harold L. Vogel

Contents

Part I 1

Introduction

Economic Perspectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Time Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.1 Alternatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.2 Availabilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Supply and Demand Factors . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.1 Productivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.2 Demand for Leisure . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2.3 Expected Utility Comparisons . . . . . . . . . . . . . . . . . . 1.2.4 Demographics and Debts . . . . . . . . . . . . . . . . . . . . . . 1.2.5 Barriers to Entry . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Primary Principles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3.1 Marginal Matters . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3.2 Price Discrimination . . . . . . . . . . . . . . . . . . . . . . . . . 1.3.3 Public-Good Characteristics . . . . . . . . . . . . . . . . . . . . 1.3.4 Power Laws . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4 Personal-Consumption Expenditure Relationships . . . . . . . . . . 1.5 Price Effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.6 Industry Structures and Segments . . . . . . . . . . . . . . . . . . . . . 1.6.1 Structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.6.2 Segments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.6.3 Advertising and Promotion . . . . . . . . . . . . . . . . . . . . . 1.7 Valuation Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.7.1 Discounted Cash Flows . . . . . . . . . . . . . . . . . . . . . . . 1.7.2 Comparison Methods . . . . . . . . . . . . . . . . . . . . . . . . . 1.7.3 Options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.7.4 Business Model Aspects . . . . . . . . . . . . . . . . . . . . . . . 1.8 Macro Trend Disruptors . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.8.1 Oil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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3 3 3 4 9 9 10 12 13 15 15 15 18 20 20 22 25 26 26 27 31 32 32 33 34 34 35 35 xi

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1.8.2 Health Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.8.3 Wars and Politics . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.9 Big Data and Artificial Intelligence (AI) Aspects . . . . . . . . . . 1.10 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Further Reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Part II

. . . . . .

37 38 38 39 48 52

Getting There

2

Wings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Onward and Upward . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1.1 Technology and Early History . . . . . . . . . . . . . . . . . . 2.1.2 Regulation and Deregulation . . . . . . . . . . . . . . . . . . . 2.2 Operational Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.1 Structural Features . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.2 Basics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.3 Marketing Features . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.4 Airport Management . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Economic Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.1 Macroeconomic Sensitivities . . . . . . . . . . . . . . . . . . . 2.3.2 Microeconomic Matters . . . . . . . . . . . . . . . . . . . . . . . 2.4 Financing and Accounting Issues . . . . . . . . . . . . . . . . . . . . . . 2.4.1 Financial Features . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.2 Financing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.3 Accounting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.5 Valuing Airline Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Further Reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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57 58 58 63 66 66 68 71 76 78 78 79 96 96 98 102 106 109 139 151

3

Water and Wheels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Wetting the Whistle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.1 Fantasy Islands . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.2 Operational Aspects . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1.3 Economic Aspects . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Automobiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.1 Jamming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2.2 Car Rentals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Kings of the Road . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Iron and Steel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5 Finance and Accounting . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Further Reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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161 161 161 166 168 170 170 171 174 176 178 178 184 186

Contents

Part III 4

xiii

Being There

Hotels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Rooms at the inn . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Basics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.1 Structural Features . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.2 Operating Features . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2.3 Marketing Matters . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Financial and Economic Aspects . . . . . . . . . . . . . . . . . . . . . . 4.3.1 Financing Frameworks . . . . . . . . . . . . . . . . . . . . . . . . 4.3.2 Accounting Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.3 Economic Sensitivities . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Valuing Hotel Assets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Further Reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Part IV

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191 191 196 196 197 208 212 212 214 215 219 225 238 241

Doing Things There

5

Casinos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 From Ancient History . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.1 At First . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.2 Gaming in America . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1.3 Asia’s Jackpot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Money Talks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2.1 Macroeconomic Matters . . . . . . . . . . . . . . . . . . . . . . . 5.2.2 Funding Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2.3 Regulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2.4 Financial Performance and Valuation . . . . . . . . . . . . . 5.3 Underlying Profit Principles and Terminology . . . . . . . . . . . . 5.3.1 Principles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3.2 Terminology and Performance Standards . . . . . . . . . . . 5.4 Casino Management and Accounting Policies . . . . . . . . . . . . . 5.4.1 Marketing Matters . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4.2 Cash and Credit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4.3 Procedural Paradigms . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 Gambling and Economics . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.6 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Further Reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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245 245 245 246 252 255 255 256 258 259 260 260 262 265 265 266 268 269 272 281 285

6

Amusement/Theme Parks and Resorts . . . . . . . . . . . . . . . . . . . . . 6.1 Flower Power . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1.1 Gardens and Groves . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1.2 Modern Times . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Financial Operating Characteristics . . . . . . . . . . . . . . . . . . . .

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6.3 Recreational Resorts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4 Economic Sensitivities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.5 Valuing Theme-Park Properties . . . . . . . . . . . . . . . . . . . . . . . 6.6 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Further Reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . .

298 299 301 301 305 305

Tourism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1 Don’t Leave Home Without It . . . . . . . . . . . . . . . . . . . . . . . . 7.2 Economic Aspects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.1 Demand Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.2 Multipliers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.3 Balance of Trade . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2.4 Input-Output Analysis . . . . . . . . . . . . . . . . . . . . . . . . 7.3 Travel Laws and Regulation . . . . . . . . . . . . . . . . . . . . . . . . . 7.4 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Further Reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . .

309 310 318 321 322 325 327 328 329 335 338

. . . . . .

343 343 344 345 348 348

Appendix A: Sources of Information . . . . . . . . . . . . . . . . . . . . . . . . . .

351

Appendix B: Valuation Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

353

Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

355

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

369

Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

399

7

Part V 8

Roundup

Performance and Policy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.1 Common Elements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2 Public Policy Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3 Guidelines for Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4 Final Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

About the Author

Harold (Hal) L. Vogel, PhD, CFA was the senior entertainment and media analyst at Merrill Lynch & Co., Inc. and has taught at the Columbia Business School in New York and the Cass Business School in London. His books include Entertainment Industry Economics: A Guide for Financial Analysis, 10th edition (2020), and Financial Market Bubbles and Crashes: Features, Causes, and Effects, 2nd edition (2018, 3rd edition forthcoming, 2022).

xv

Part I

Introduction

Abstract This chapter provides the economic framework and context in which all travel businesses operate. It covers basic economic concepts, hours of work, growth rates, population, productivity, and price effects, industry structures, valuation variables, advertising and promotion, and big data and artificial intelligence tehnological aspects. The importance of time and disposable income for travel and productivity enhancements are emphasized, and the financial performance of major travel industry subsectors are compared.

Chapter 1

Economic Perspectives

Travel broadens the mind.—Proverb, early twentieth century.

It also costs money and takes up time. This chapter examines the fundamental economic factors that affect all aspects of the travel and tourism business. The perspectives provided by this approach will provide a framework for understanding how travel industries are defined and fit into the larger economic picture and will also highlight the financial features that guide investments in this field.

1.1 1.1.1

Time Concepts Alternatives

You need time to get from here to there. And given that time-transport machines are still to be seen only in science fiction films, it is worth spending a little time to understand the economic value of time. Time for leisure or business travel comes out of a budget that includes time for work, time for play, and time for taking care of the necessities of life. However, the boundaries between these categories have become increasingly blurred. For instance, what is loosely known as “leisure time” is widely considered as being time in which people are free from having any sense of obligation or compulsion to do anything.1 The term leisure might as easily be characterized as time not spent at work. Yet no matter what the definitional preference, the essential economic fact is that time has a cost in terms of alternative opportunities foregone. Because time is needed to use or to consume goods and services, as well as to produce them, economists have attempted to develop theories that treat time as a commodity with varying qualitative and quantitative cost features. However, as Sharp (1981) has noted, economists have been only partially successful in this attempt: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 H. L. Vogel, Travel Industry Economics, https://doi.org/10.1007/978-3-030-63351-6_1

3

4

1 Economic Perspectives “Although time is commonly described as a scarce resource in economic literature, it is still often treated rather differently from the more familiar inputs of labor and materials and outputs of goods and services. The problems of its allocation have not yet been fully or consistently integrated into economic analysis.” (p. 210)

Investigations into the economics of time, including those of Becker (1965) and DeSerpa (1971) have, however, suggested that the demand for leisure is affected in a complicated way by the consumption-cost of time. For instance, according to Becker (1965) [see also Ghez and Becker (1975)]: The two determinants of the importance of forgone earnings are the amount of time used per dollar of goods and the cost per unit of time. Reading a book, taking a haircut or commuting use more time per dollar of goods than eating dinner, frequenting a night-club or sending children to private summer camps. Other things the same, foregone earnings would be more important for the former set than the latter. The importance of forgone earnings would be determined solely by time intensity only if the cost of time was the same for all commodities. Presumably, however, it varies considerably among commodities and at different periods. For example, the cost of time is often less on weekends and in the evenings. (Becker 1965, p. 503). In all, “Time is what remains scarce when all else becomes abundant.”2 Time indeed is money.

1.1.2

Availabilities

Most of us are not normally subject to sharp changes in our availability of leisure time (except on retirement or loss of job). Yet there is a fairly widespread impression that leisure time has been trending steadily higher ever since the Industrial Revolution of more than a century ago. The evidence on this is mixed. Figure 1.1 shows that in the United States the largest increases in leisure time—workweek reductions—for agricultural and nonagricultural industries were achieved prior to 1940. More recently, however, the lengths of average workweeks adjusted for increases in holidays and vacations have scarcely changed for the manufacturing sector and have also stopped declining in the services sector (Table 1.1 and Fig. 1.2). By comparison, average hours worked in other major countries, as illustrated in Fig. 1.3, have declined markedly since 1970.3 Although this suggests that there has been little, if any, expansion of leisure time in the United States, what has apparently happened instead is that work schedules now provide greater diversity. As noted by Smith (1986), “A larger percentage of people worked under 35 h or over 49 h a week in 1985 than in 1973, yet the mean and median hours (38.4 and 40.4 respectively, in 1985) remained virtually unchanged.”4 If findings from public-opinion surveys on Americans and the arts are to be believed, the number of hours available for leisure may actually at best be holding

1.1 Time Concepts

5

Fig. 1.1 Estimated average weekly hours for all persons employed in agricultural and nonagricultural industries, 1850–1940 (10-year intervals) and 1941–56 (annual averages for all employed persons, including the self-employed and unpaid family workers.) Source: Zeisel (1958) Table 1.1 Average weekly hours at work, 1948–2018a and median weekly hours at work for selected years Average hours at work Year Unadjusted 1948 42.7 1956 43.0 1962 43.1 1969 43.5 1975 42.2 1986 42.8

Adjustedb 41.6 41.8 41.7 42.0 40.9

Median hours at work Year Hours 1975 43.1 1980 46.9 1987 46.8 1995 50.6 2004 50.0 2008 46.0 2018 43.5c

Sources: Owen (1976, 1988), and Harris (1995), http://www.harrisinteractive.com/Insights/ HarrisVault.aspx for median hours worked and preliminary estimate for 2018 a Nonstudent men in nonagricultural industries. Source: Owen (1976, 1988) b Adjusted for growth in vacations and holidays

steady.5 But the view that Americans are actually working more hours than previously has been occasionally expressed.6 Aguiar and Hurst (2007) argue the opposite. And as shown in Table 1.2, McGrattan and Rogerson (2004) find that since World War II, the number of weekly

6

1 Economic Perspectives

Fig. 1.2 Average weekly hours worked by production workers in manufacturing and services, 1965–2019. Source: U.S. Department of Commerce

Weekly hours

43 40 Manufacturing

37 34

Serv ices

31 65 Fig. 1.3 Average annual hours worked in the United States versus other countries, 1970–2018. Source: OECD Employment Outlook

75

85

95

05

15

2,300 Japan

2,050

U.S.

1,800 France

U.K.

1,550 Germany

1,300 70

80

90

00

10

Table 1.2 Aggregate weekly hours worked per person (+15), 1950–2000 Year 1950 1960 1970 1980 1990 2000 % change, 1950–2000

Aver. weekly hours worked Per person 22.34 21.55 21.15 22.07 23.86 23.94 7.18

Per worker 42.40 40.24 38.83 39.01 39.74 40.46
4.56

Employment-to Population ratio (%) 52.69 53.55 54.47 56.59 60.04 59.17 12.30

Source: McGratten and Rogerson (2004), U.S. Dept. of Commerce, Bureau of the Census

hours of market work in the United States has remained roughly constant, even though there have been dramatic shifts in various subgroups. Robinson (1989, p. 34) also measured free time by age categories and found that “most gains in free time have occurred between 1965 and 1975 [but] since then, the amount of free time people have has remained fairly stable.” By adjusting for age

1.1 Time Concepts

7

categories, the case for an increase in total leisure hours available becomes much more persuasive.7 In addition, Roberts and Rupert (1995) found that total hours of annual work have not changed by much but that the composition of labor has shifted from home work to market work with nearly all the difference attributable to changes in the total hours worked by women.8 A similar conclusion as to average annual hours worked was also reached by Rones et al. (1997).9 Yet, according to Jacobs and Gerson (1998, p. 457), “even though the average work week has not changed dramatically in the U.S. over the last several decades, a growing group of Americans are clearly and strongly pressed for time.” And this fully reflects the income-time paradox wherein the young and elderly have lots of time but relatively little income available as compared to the middle-aged, who have income but no time. In all, it seems safe to say that for most middle-aged and middle-income Americans—and recently for Europeans too—leisure time is not expanding.10 Indeed, the comprehensive compilation of research by Ramey and Francis (2009) suggests that “per capita leisure and average annual lifetime leisure increased by only four or five hours per week during the last 100 years. . .leisure has increased by 10 percent since 1900.” Still, whatever the actual rate of expansion or contraction may be, there has been a natural evolution toward repackaging the time set aside for leisure into longer holiday weekends and extra vacation days rather than in reducing the minutes worked each and every week.11 And this is all advantageous to the travel business. Particularly for those in the higher-income categories—conspicuous consumers, as Veblen (1899) would say—the result is that personal-consumption expenditures (PCEs) for leisure activities (including those for tourism and travel) are likely to be intense, frenzied, and compressed instead of evenly metered throughout the year. In Veblen’s view, leisure was a symbol of social class, with status emulation as a driver of demand. And this is as valid an observation today as it was in Veblen’s time: Even allowing for cultural differences, wherever large middle-class populations emerge, status emulation will drive demand for the type of conspicuous consumption that is well represented by travel and tourism. Estimated apportionment of leisure hours among various activities, and the changes in such apportionments between 1970 and 2017, are indicated in Table 1.3.12 In addition, many of the time and cost concepts that apply specifically to travel and tourism can be tied together in what has been dubbed a distance-decay function as shown in Fig. 1.4. The function captures the fact that while traveling, an opportunity cost of time rather spent doing something else is incurred. As Bull (1995, p. 45) suggests, a proxy for physical distance is a composite variable that includes the opportunity cost of time and of the money cost for a trip. Such a variable is inversely related to demand for tourist travel. It can also be understood, though, that “[T]ransportation is a friction—a cost in both money and time—that must be incurred by individuals and firms to complete almost any market transaction. An efficient and extensive transportation system

8

1 Economic Perspectives

Table 1.3 Time spent by U. S. adults on selected leisure activities, 2018 estimates Medium Televisiona Network Affiliates Independent Stations Basic Cable Programs Pay Cable Programs Radio Home Out of Home Internetb Newspapersc Recorded Musicd Magazinese Leisure Booksf Movies: Theaters Home Videog Spectator Sports Video Games: Home Cultural Events Total Hours Per Adult Per Week Hours Per Adult Per Day

Hours per per person year

% of Total time

1350 452 3 868 57 685 205 480 1758 64 159 52 71 9 17 17 134 6 4352 83.7 11.9

31.7 10.4 0.1 19.9 1.3 15.7 4.7 11.0 40.4 1.5 3.7 1.2 1.6 0.2 0.4 0.4 3.1 0.1 100.0

Source: Wilkofsky Gruen Associates Does not include over-the-top viewing, part of the Internet category b Includes mobile access c Includes free dailies but not online reading, part of the Internet category d Includes licensed digital music e Does not include online reading, part of the Internet category f Includes electronic and audio books g Does not include OTT viewing, part of the Internet category a

Fig. 1.4 Distance-decay function for tourist travel

Frequency of tourist demand

60

weekend trip

40

2-week trip

20

0 1

6

11

16

21

Time/cost of travel

1.2 Supply and Demand Factors

9

greatly enriches the standard of living in modern society by reducing the cost of nearly everything. . .“13.

1.2 1.2.1

Supply and Demand Factors Productivity

Ultimately, more leisure time availability is not a function of government decrees, labor union activity, or factory owner altruism. It is a function of the rising trend in output per person-hour—in brief, the rising productivity of the economy. Quite simply, technological advances embodied in new capital equipment and in the training of a more skilled labor pool allow more goods and services to be produced in less time or by fewer workers. Long-term growth in leisure-related and travel industries thus depends on the rate of technological development throughout a nation’s economy. Information concerning trends in productivity as well as other aspects of economic activity is provided the National Income and Product Accounting (NIPA) figures and data from the Bureau of Labor Statistics. From these sources it can be seen (Fig. 1.5) that overall productivity between 1979 and 1990 rose at an average annual rate of approximately 1.5%, then jumped to a rate of 2.7% between 2000–07 before falling back to a rate of 1.3% between 2007 and 2018. This suggests that the potential for leisure-time expansion remained fairly steady in the last quarter of the twentieth century and into the early 2000s. Meanwhile, the % change 3.0 2.8 2.8

2.5

2.6

2.3 2.2

2.0 1.8 1.5 1.5

1.3 1.2

1.2

1.0

1947-73

1973-79

1979-90

1990-'00

2000-07

2007-17

Fig. 1.5 Average annual percent change in nonfarm business productivity in the United States, 1947–2018, selected periods. Source: U.S. Department of Labor and St. Louis Federal Reserve Bank FRED, available at stlouisfed.org

10

1 Economic Perspectives

gap between European and U.S. labor productivity had continued to narrow until the early 1990s.14 Since then productivity growth rates for the U.S. and other already developed countries have diminished but are still rising from a relatively low base in emerging markets (EMs). The potential for growth of leisure-time and spending on entertainment, media, and travel is thus relatively much higher in EM countries.

1.2.2

Demand for Leisure

All of us can choose either to fully use our free time for recreational purposes (defined here as being inclusive of entertainment and leisure-travel activities) or to use some of this time to generate additional income. How we allocate free time between the conflicting desires for more leisure and for additional income then becomes a subject that economists investigate with standard analytical tools.15 In effect, economists can treat demand for leisure as if it were, say, demand for gold, or for wheat, or for housing. And they often estimate and depict the schedules for supply and demand with curves of the type shown in Fig. 1.6. In simplified form, it can be seen that, as the price of a unit rises, the supply of it will normally increase and the demand for it decrease so that, over time and in an openly competitive market an approximate equilibrium at the intersection of the curves will be reached—though in reality such equilibrium is fictional and is a narrative that primarily applies best to tangible manufactured assets and agricultural produce.16 Consumers typically tend to substitute less expensive close-equivalent goods and services for more expensive ones and the total amounts they can spend—their budgets—are limited or constrained by income. The effects of such substitutions and changes in income as related to demand for leisure have been extensively studied by Owen (1970), who observed:

$7 Price (P) per unit

Fig. 1.6 Supply and demand schedules

P

6

Demand

5 Supply

4 3 2 1 0 1

2

3 4 5 6 7 8 9 10 Quantity (Q) of units per time

11

Q

12

1.2 Supply and Demand Factors Fig. 1.7 Backwardbending labor-supply curve

11 Wage Rate

Bo

o

A

Hours Worked

An increase in property income will, if we assume leisure is a superior good, reduce hours of work. A higher wage rate also brings higher income which, in itself, may incline the individual to increase his leisure. But at the same time the higher wage rate makes leisure time more expensive in terms of forgone goods and services, so that the individual may decide instead to purchase less leisure. The net effect will depend then on the relative strengths of the income and price elasticities . . . It would seem that for the average worker the income effect of a rise in the wage rate is in fact stronger than the substitution effect. (p. 18)

In other words, as wage rates continue to rise up to point A in Fig. 1.7, people will choose to work more hours to increase their income (income effect). Eventually, however, they will begin to favor more leisure over more income (substitution effect, between points A and B), resulting in a backward-bending labor-supply curve.17 And the net (of taxes) hourly wage thus becomes the opportunity cost of an hour of leisure! Although renowned economists, including Adam Smith, Alfred Marshall, Frank Knight, A. C. Pigou, and Lionel Robbins, have substantially differed in their assessments of the net effect of wage-rate changes on the demand for leisure, it is clear that “leisure does have a price, and changes in its price will affect the demand for it” (Owen 1970, p. 19). Results from a Bureau of Labor Statistics survey of some 60,000 households in 1986 indeed suggest that about two-thirds of those surveyed did not want to work fewer hours if it means earning less money.18 As Owen (1970) has demonstrated, estimation of the demand for leisure requires consideration of many complex issues, including the nature of “working conditions,” the effects of increasing worker fatigue on production rates as work hours lengthen, the greater availability of educational opportunities that affect the desirability of certain kinds of work, government taxation and spending policies, and market unemployment rates.19

12

1.2.3

1 Economic Perspectives

Expected Utility Comparisons

Individuals differ in terms of emotional gratification derived from consumption of different goods and services. It is thus difficult to measure and compare the degrees of satisfaction derived from, say, eating dinner as opposed to buying a new car. To facilitate comparability, economists have adapted an old philosophical yet vague concept known as utility (which is essentially pleasure).30 Utility “is not a measure of usefulness or need but a measure of the desirability of a commodity from the psychological viewpoint of the consumer.”21 It is often the consumption characteristics and qualities associated with goods rather than the possession of goods themselves that matters most. Rational individuals try to maximize utility—in other words, make decisions that provide them with the most satisfaction. But they are hampered in this regard because decisions are typically made under conditions of uncertainty, with incomplete information, and therefore with the risk of an undesired outcome. People thus tend implicitly to include a probabilistic component in their decision-making processes—and they end up maximizing expected utility rather than utility itself. The notion of expected utility is especially well applied to thinking about demand for travel goods and services. It explains, for example, why people may be attracted to gambling or why they are sometimes willing to pay premiums for certain hotel and restaurant accommodations. Expected utility also sheds light on how various travel and entertainment activities compete for the limited time and funds of consumers. To illustrate, assume for a moment that the cost of an activity per unit of time is somewhat representative of its expected utility. If the admission price to a 2-hour movie is $12, and if the purchase of video-game software for $25 provides six hours of play before the onset of boredom, then the cost per minute for the movie is 10 cents whereas that for the game is 6.9 cents. Now, obviously, no one decides to see a movie or buy a game on the basis of explicit comparisons of cost per minute. For an individual, many qualitative (nonmonetary) factors, especially fashions and fads, may affect the perception of an item’s expected utility. However, in the aggregate and over time, such implicit comparisons do have a significant cumulative influence on relative demand for travel (and other) products and services. In the case of the distance-decay function of Fig. 1.4, for example, expected utility thinking is what makes travelers behave as they do in terms of balancing the opportunity cost of time and money (distance) against frequency of travel. Finally, it is helpful to view travel service companies as being in the business of supplying customers with “experiences” as channeled through entertainment, educational, aesthetic, and escapist activities.22 Especially in travel, such experiences have deep-seated and long-lasting effects on emotions and psychology.23 People, it seems, are often happier after purchasing experiences (like those related to travel) than material goods.

1.2 Supply and Demand Factors

1.2.4

13

Demographics and Debts

Over the longer term, the demand for leisure goods and services can also be significantly affected by changes in the relative growth of different age cohorts. Teenagers, for example, tend to be important purchasers of recorded music; people under the age of thirty are the most avid moviegoers. A large increase in births following World War II accordingly created, in the 1960s and 1970s, a market highly receptive to movie and music products. In terms of travel and tourism, this generation is currently into or just past its years of family formation and peak earnings power and it would be natural to expect a rising demand for visits to places of historical interest, to casinos, and to resort destinations. The expansive demographic shifts most important to travel industry prospects in the United States include (1) a projected increase in the number of 5 to 17-year-olds by 4.7 million from 2010 to 2020 and another 4.8 million from 2020 to 2030, and (2) a major expansion of the population over age 65 (Table 1.4). By 2030, the over 65 group will account for an estimated 19.3% of the population, as compared to 12.4% in 2000. This upcoming rapid expansion of the 65+ generation presages a large increase in demand for tourism and resort-destination trips designed for retired people, who are more likely to have the time and money to indulge in travel and tourism. The marked departure from the years between 2000 and 2010 is that the number of people in the 45-to-64 age group will not be increasing in proportion to the Table 1.4 Components of population change, 2000–2030 Percent distribution 2000 2010 2020 under 5 6.8 6.8 6.7 5–17 18.8 17.4 17.2 18–34 23.8 23.4 22.5 35–64 38.1 39.4 37.5 65+ 12.4 13.0 16.1 total 100.0 100.0 100.0 Population trends by life stage (millions) 0–13 56.2 14–24 43.4 25–34 39.8 35–44 45.1 45–54 38.0 55–64 24.4 65+ 35.1 Total 282.2

2030 6.5 17.0 21.7 35.5 19.3 100.0 58.2 47.7 41.8 41.3 44.7 36.3 40.2 310.2

2000–2010 1.9 1.0 5.4 14.7 5.1 28.1

Change (millions) 2010–2020 1.7 4.7 4.3 5.8 14.6 31.2 63.6 48.9 46.1 43.7 41.4 43.0 54.8 341.4

2020–2030 1.3 4.8 4.2 4.5 17.3 32.1 68.0 53.9 47.0 48.2 44.0 40.3 72.1 373.5

14

1 Economic Perspectives 2.2

Fig. 1.8 Ratio of spenders to savers, 1960–2030

Ratio

1.8 1.4 1.0 Ages 20 to 34 versus 45 to 59

0.6 60

80

00

20

number of people in the 25-to-44 group. This is of particular importance given that those in the younger category are generally apt to spend much of their income when they enter the labor force and form households, whereas those in the older category are already established and are thus more likely to be in a savings mode, perhaps to finance college education for their children or to prepare for retirement, when earnings are lower. The ratio of people in the younger group to those in the older group—in effect, the spenders versus the savers—is illustrated in Fig. 1.8. A related metric involves the ratio of consumer debt to personal income, which later appears in Fig. 6.3. This aggregate ratio will be affected by a society’s demographic composition and also at any time reflect the availability of jobs and economic growth opportunities. A high and rising consumer debt to personal income ratio will, however, always suggest that potential spending in the future is being shifted into the present and that further increases in spending will likely be constrained or limited. Although it depends on the specific industry component to be analyzed, proper interpretation of long-term changes in population characteristics may also require that consideration be given to several additional factors, which include dependency ratios, fertility rates, number of first births, number of families with two earners, and trends in labor force participation rates for women, which had climbed steadily from 45% in 1975 to around 60% by 2005.24 Elements of consumer debt (Fig. 6.3), weighted by the aforementioned demographic factors, probably explain why leisure hours per week seem to have declined noticeably (Table 1.2) since the early 1970s. As the median age rises, however, these very same elements may combine and begin to abate pressures on time availability. As can be seen from Fig. 1.9, aggregate spending on transportation is concentrated in the middle-age groups—the ages at which incomes and career demands usually peak even though free time may be relatively scarce. This again is the aforementioned paradox, wherein the middle-aged, have the income but not the time to spend it.

1.3 Primary Principles

15 age

Fig. 1.9 Average annual spending on total and public transportation (black bar) per person by age category, 2018. Source: U.S. Department of Commerce survey

75+ 65-74 55-64 45-54 35-44 25-34 under 25 0

1.2.5

2

4

6

8

10

12

Barriers to Entry

The supply of travel and tourism products and services offered would also depend on how readily prospective new businesses can overcome barriers to entry (i.e., competitive advantages) and thereby contest the market. Barriers to entry—which can be structural (economies of scale), strategic (price reductions), or institutional (tariffs and licenses)—restrict supply and fit mainly into the following categories, listed in order of importance to the travel service industries: Capital Know-how Regulations25 Price competition A decision to begin operating an airline, hotel, railroad, bus company, cruise line, or travel agency cannot be made without considerable planning and expertise. To compete effectively, even large corporations must invest considerable time and capital to acquire technical knowledge and experience. Government regulations such as those applying to the airline and casino businesses often present additional obstacles for potential new entrants to surmount. Furthermore, in most industries, established firms ordinarily have some ability to protect their positions through price competition.

1.3 1.3.1

Primary Principles Marginal Matters

Microeconomics provides a descriptive framework in which to analyze the effects of incremental changes in the quantities of goods and services supplied or demanded over time. A standard diagram of this type, Fig. 1.10, shows an idealized version of a firm that maximizes its profits by pricing its products at the point where marginal

16

1 Economic Perspectives

(a)

(b)

P

P

p

p MC

MC

AC

c

D

AC c

MR

MR

q

q

Q

D Q

(c) P

A

p1

C

p2

D B q1

q2

Q

Fig. 1.10 Marginal costs and revenues

revenue (MR)—the extra revenue gained by selling an additional unit—equals marginal cost (MC), the cost of supplying an extra unit. Here, the average cost (AC), which includes both fixed and variable components, first declines and is then pulled up by rising marginal cost. Profit for the firm is represented by the shaded rectangle (price [p] times quantity [q] minus cost [c] times quantity [q]). In analyzing the pricing of airline tickets, for example, the so-called competitivemonopolistic model of Fig. 1.10a in which many firms produce slightly differentiated products is not far-fetched. The objective for such profit-maximizing firms is to both rightward-shift and to also steepen the demand schedule idealized by line D. By thus making the schedule of demand more vertical—that is, quantity demanded becomes less sensitive to change in price (i.e., more price-inelastic) through promotional and advertising efforts—a firm would be able to reap a potentially large proportionate increase in profits as long as marginal costs are held relatively flat

1.3 Primary Principles

17

(Fig. 1.10b). In all, the more substitutes that are available, the greater is the price elasticity (i.e., responsiveness) of demand. Nonetheless, no matter what the elasticities or the ultimate demand functions turn out to be, the costs of building airports and airplanes and hotels, which are large compared with other, later costs, are mostly borne upfront. Come what may, the costs here are sunk (i.e., the money is already spent and probably unrecoverable) and irrelevant for the purposes of making ongoing strategic decisions. In travel and tourism, the cost of generating an incremental unit is usually quite small as compared to other operating (and also sunk) costs. It often accordingly makes sense for a travel service distributor to take a chance on spending a little more on marketing and promotion in an attempt to shift the demand schedule into a more price-inelastic and rightward position. Such inelastic demand is characteristic of products and services that. • • • • •

are considered to be necessities have few substitutes are a small part of the budget are consumed over a relatively brief time, or are not used often.

Economists use estimates of elasticity to indicate the expected percentage change in demand if there is a one-percent change—either up or down—in price or income (or some other factor such as journey time). In the case of price, this can be stated as εp ¼

% change in quantity demanded , % change in unit price

All other things being equal, quantity demanded would normally be expected to rise with an increase in income and decline with an increase in price.26 For example, if quantity demanded declined 8% when price rose 4%, the price elasticity of demand would be
2.0. In theory, cross-elasticities of demand between goods and services that are close substitutes for each other (a trip to Venice versus a trip to Florence), or complements to each other (a trip and a travel bag), might also be estimated. Such notions of elasticity suggest that it makes sense for firms to first increase the price markup on goods with the most inelastic demand (known as the Ramsey, or inverse elasticity pricing rule). In sum, when elasticity is greater than 1, price increases lead to decreases in revenue and vice versa. When elasticity is less than 1 (inelastic), increases in price lead to increases in revenues. And when elasticity equals 1, changes in price lead to no changes in revenues. Elasticity When prices are raised, revenues are. . . >1 x] ~ x-k). In simple terms, this says that of the many products and services offered by companies, only a few stand out and generate the bulk of the revenues and earnings. This is seen in that 25% of flyers will typically account for 70% of an airline’s revenues, that 40% of tour operator earnings might be generated by only 10% of the tours provided,

1.3 Primary Principles

21 log (freq)

log (rank)

Fig. 1.12 An idealized Pareto (power) lawa

% of top rank 100

80 airport passengers 60

casino sq. ft.

40

city visitors park attendance

20

hotel properties hotel rooms

0 2

4

6

8

10

12

14

16

18

20

22

24

Rank Fig. 1.13 Power laws in action: Airport arrivals, origin-destination, theme park attendance, and hotel rooms operated, 2019

and that 70% of a hotel chain’s revenues might be derived from 20% of its properties. Rankings by size and value also exhibit power law features. This can be seen in rankings of airline or hotel industry profits by company, origin-destination traffic patterns by city pairs, theme park attendance rankings, and number of airport arrivals. A selected sample of these, taken from actual data, is presented in Fig. 1.13. Indexed global rankings for airport traffic, casino size, hotel rooms, number of hotels, major city visitors, and theme park attendance, 2019, with x-axis direction from previous Fig. 1.12 directionally reversed. Various industry ranking sources.

22

1.4

1 Economic Perspectives

Personal-Consumption Expenditure Relationships

There is a close relationship between demand for leisure and demand for recreational products and services that would include those provided to the tourist and leisure traveler. Demand for business travel services would be similarly related to overall business conditions as measured through growth of the economy and corporate profits. For either consumers or businesses, though, demand for travel is derived largely from the needs and desires of people to do other things. As Button (2010, p. 416) explains, travel is “one of a whole range of complementary and competitive activities operating in a sequence of events in time and space. . .people trade time to move location.” National Income and Product Account (NIPA) data classify spending on transportation and on recreation as subsets of total personal-consumption expenditures (PCEs) and are shown in Table 1.5. This table is particularly important because it allows comparison of the amount of transportation and leisure-related spending to the amount of spending for shelter, food, clothing and other items.29 A summary of the approximate (and slow-to-change) percentages of all PCEs allocated to selected main categories in 2019 were: However, if indirect spending for restaurant meals, private-car gasoline, and other related items are also to be included, total spending on travel as a percentage of personal consumption expenditures is actually much larger than what appears in these categories. Total expenditures for travel and tourism including such items has indeed been estimated by the United States Bureau of Economic Analysis to amount to approximately 5% of United States gross domestic product (GDP) and 3.3% of employment.30 In other developed countries, these percentages are apt to be proportionally similar. Another way to visualize the longer term shifts in spending preferences is provided in Fig. 1.14 in which it can be seen that spending for transportation services as compared to some other categories has held to a fairly stable percentage of all PCEs, whereas the percentages spent on medical services clearly has risen and that on clothing and food have declined. Yet because travel is a composite activity involving elements of both transportation and recreation, the close-up view provided in Fig. 1.15 is, in some respects, more revealing. It is interesting to also see that the percent of PCEs spent on intercity

Table 1.5 PCEs for travel and transportation, selected categories, in billions of current dollars, 2019

Housing Health care Food (excl. Alcohol bev.) Clothing Transportation services Casinos Hotels & motels Airlines

18.3% 17.0 7.1 2.7 3.3 0.8 0.8 0.7

1.4 Personal-Consumption Expenditure Relationships Fig. 1.14 Trends in percent of total personal consumption expenditures in selected categories, 1980–2019

23

18 % Medical serv ices Food

12

All recreation

6

Clothing

Transportation serv ices

80

Fig. 1.15 Transportation services (total and intercity) and recreation services as a percent of total PCEs, 1960–2019

90

00

10

%

4.5

Total transportation

3.0 Recreation serv ices

1.5 Intercity

60

Fig. 1.16 Real per capita PCE on transportation services and recreation services, 1960–2019

70

80

90

00

10

$ $ 750

600 450

Transportation

300 Recreation

150 0 60

70

80

90

00

10

transportation—the component of total transport services that practically defines travel—has recently declined slightly. Measurement of real (adjusted for inflation) per capita spending on total transportation and recreation services provides another long-term view of how Americans have allocated their travel-related dollars. Figure 1.16 illustrates the start around 1980 of a steeper uptrend in spending for travel and recreation services, both of

24

1 Economic Perspectives

Fig. 1.17 Miles traveled per capita, 1940–2019. Sources: Transportation in America, 1999 and Census Bureau updates

Miles per capita

14,000

Total

10,500

7,000 Public carriers ex-auto

3,500

0 40

50

60

70

80

90

00

10

which have mostly moved similarly.31 That year appears to be pivotal for recreation spending while also reflecting the price-lowering effects of global airline deregulation, declining oil prices, and the introduction of wide-bodied planes (i.e., new technologies). Still, various travel industry sectors will have markedly different responses to changing conditions: Travel-sector time series comparisons against components of gross domestic product (GDP) accounts are fairly limited in what they can convey about the degree of recession resistance or cyclicity of travel relative to that of the economy at large.32 What can be asserted with virtual certainty, however, is that the positive relation between income and travel is seen globally. As Schafer and Victor (1997) note: throughout the world, personal income and traffic volume grow in tandem. As average income increases, the annual distance traveled per capita by car, bus, train or aircraft. . .rises by roughly the same proportion. The average North American earned $9,600 and traveled 12,000 kilometers (7,460 miles) in 1960; by 1990 both per capita income and traffic volume had approximately doubled.33

In addition to a budget for income there is also a budget for time, and at the aggregate level, as Button (1993, p. 40) suggests, “time expenditure on travel per head increases roughly proportionally to income budgeted for travel.” Figure 1.17 indicates that since 1950, growth of per-capita passenger-miles—a measure of the quantity of transportation services demanded—has risen at a compound annual rate of approximately 2.2%. In other words, the average American of the early 2000s each year traveled more than 10,000 miles by air, rail, bus, and private automobile as compared to 3000 miles a half a century ago. Of this recent total, however, only around 1800 miles were by public carriers. Americans now not only drive a lot more than they used to but each person is also on the average taking more trips and longer trips. An international perspective is later provided by Fig. 2.4 with respect to airline travel.

1.5 Price Effects

1.5

25

Price Effects

Prices are largely dependent on supply and demand factors specifically related to the particular good or service. And economic policies and strategies implemented by governments and their central banks—which have the power to create or extinguish money and credit—often also have an important influence on whether overall prices are moving upward (inflation) or downward (deflation). Although notable episodes of inflation and deflation have occurred in many nations at many times in history, the tendency and preference is normally to allow prices to rise gradually (i.e., creep higher). Yet by dint of compound interest effects, even small annual increments in the wholesale (producer or PPI) and consumer price (CPI) indexes will over time significantly erode the purchasing power of a country’s currency, both internally and externally. As a result, a dollar as reported today in average airline ticket or hotel room prices is not the same as one of yesterday or of ten years ago. In fact, in the United States, today’s dollar has the purchasing power of and is equivalent to perhaps only two or three cents of 100 years ago (see also Fig. 1.22). And prices that are rising merely at a compound rate of around 3% a year will approximately double in a little more than 20 years.34 It is therefore important to be aware of such price effects when comparing data that are generated relatively far apart in time and to be careful when interpreting numbers that are stated as being “record-setting.” Indexes of this kind are also criticized as being misleading because they are frequently revised (in data and methodology) and poorly capture changes in quality and technology (i.e., so-called hedonic factors).35 Price trends as reported by the U.S. Bureau of Labor Statistics using the CPI and GDP deflator series are shown in Fig. 1.18. The main take-away from the heavy dark line (CPI-U) is that overall prices have more than tripled since 1980 (from around 72 to 250 in 2019). Fig. 1.18 Price inflation indexes

Index

300

CPIU - public

225

150

CPIU-all

75 GDP deflator

0 70

80

90

00

10

26

1.6 1.6.1

1 Economic Perspectives

Industry Structures and Segments Structures

Microeconomic theory suggests that industries can be categorized according to how firms make price and output decisions in response to prevailing market conditions. In perfect competition, all firms make identical products and each firm is so small in relation to total industry output that its operations have a negligible effect on price or on quantity supplied. At the other idealized extreme is monopoly, in which there are no close substitutes for the single firm’s output, the firm sets prices, and there are barriers that prevent potential competitors from entering. A natural monopoly, moreover, occurs when it is impossible for potential competitors to “contest” a market because high fixed or sunk entry costs cannot be recouped (as prices converge to equal marginal costs and the monopolist’s economies of scale are large). Utility providers such as those distributing electricity, water, and cable television programming are typical examples. In the real world, the structure of most industries cannot be characterized as being perfectly competitive or as monopolistic but as somewhere in between. One of those in-between structures is monopolistic competition, in which there are many sellers of somewhat differentiated products and in which some control of pricing and competition through advertising and branding is seen. An oligopoly structure is similar, except that in oligopolies there are only a few sellers of products that are close substitutes and pricing decisions may affect the pricing and output decisions of other firms in the industry. Although the distinction between monopolistic competition and oligopoly is often blurred, it is clear that when firms must take a rival’s reaction to changes of price into account, the structure is oligopolistic. In travel, industry segments fall broadly into the following somewhat overlapping structural categories: Monopoly Major airports Some intercity routes

Oligopoly Airlines Car rental agencies Cruise ships Major hotel chains Major gaming chains Theme parks

Monopolistic Competition Buses Hotels and motels Restaurants Travel agencies Local casinos

These categories can then be further analyzed in terms of the degree to which there is a concentration of power among rival firms. A measure that is sensitive to both differences in the number of firms in an industry and differences in relative market shares—the Herfindahl-Hirschman Index—is frequently used by economists to measure the concentration of markets.36

1.6 Industry Structures and Segments

1.6.2

27

Segments

The relative economic importance of selected industry segments is illustrated in Fig. 1.19, in which the trend lines provide long-range macroeconomic perspectives of travel industry growth patterns relative to personal-consumption expenditures. These patterns then translate into short-run financial operating performance, which is revealed in Table 1.6 showing revenues, pretax operating incomes, assets, and cash flows for a selected sample of major public companies. This sample includes an estimated 75% of the domestic transactions volume in travel-related industries and provides a means of comparing efficiencies and growth rates in various segments.37 One such comparison, showing the relative sizes of PCEs for travel-related categories appears in Fig. 1.20. Meanwhile, Fig. 1.21 illustrates how airlines have come to account for the largest share of intercity travel at the expense of travel by cars, buses, and rail. The percent of PCEs going toward foreign travel by U.S. citizens is then seen in Fig. 1.22. More immediately, it can be estimated from Table 1.6 that major travel industry sample segments generated revenues of more than $400 billion in 2019 and that annual growth between 2015 and 2019—a period following the deep economic recession of 2008–09—was at least 6.0%. It can also be seen that over the same span total operating income growth was 15%, even as assets and operating cash flows grew more slowly at 2.3% and 9.5% respectively.

(a)

(b)

1.00

%

%

0.80

hotels & m otels

airlines 0.75 0.60 0.50 0.40 0.25 0.20

59

(c) 1.00

69

79

89

99

59

09

69

79

89

99

09

(d)

%

6.2 6.0

casinos

Purchasefoodbev (restaurants)

0.75 5.8

am usement/theme parks

0.50

5.6 5.4

0.25

5.2 59

69

79

89

99

09

5.0

60

70

80

90

00

10

Fig. 1.19 PCEs of selected travel categories as percentages of total PCEs for (a) airlines, (b) hotels and motels, (c) casinos and theme parks, and restaurants, 1959–2019

28

1 Economic Perspectives

Table 1.6 Travel industry composite sample, 2015–2019 a

Revenues Operating Margin incomea %

2019 2018 2017 2016 2015

439,017 416,851 400,077 183,785 179,790

61,872 63,364 62,832 25,635 26,190

14.1 15.2 15.7 13.9 14.6

Assetsa

Operating Cash Flowa

727,390 717,477 671,849 418,559 396,100

87,073 89,836 87,240 41,541 39,081

Operating Income

Assets

Compound annual growth rates (%): 2015-2019 No. companies in sample Revenues

Industry segment Airlines Car rental Cruise lines Gaming (casinos) Hotels Travel Agencies Theme parks

10 3 5

16 16 4

6 60

Total

4.4 3.3 8.2 4.8 5.1 12.6 8.7

(5.5) 12.3 12.1 10.4 3.9 11.7 10.5

7.9 6.0 6.4 3.8 3.5 0.8 6.5

Operating Cash Flow (0.6) 1.6 10.9 9.8 2.3 15.4 (12.0) Avg margin

Avg, op Margin (%) 12.5 1.7 17.1 16.3 11.0 20.2 18.1 12.1

Total Composite Pretax return(%) on Revenues 2019 14.1 2018 15.2 2017 15.7 2016 13.9 2015 14.6

Revenues Assets 8.5 8.8 9.4 6.1 6.6

b

CAGR : a b

439,017 416,851 400,077 183,785 179,790 25.0

Operating Income ($ millions) 61,872 63,364 62,832 25,635 26,190 24.0

Assets

Operating Cash Flow

727,390 717,477 671,849 418,559 396,100

87,073 89,836 87,240 41,541 39,081

16.4

22.2

$ millions. Compound annual growth rate (%).

Cash flow is so important because it can be used to service debt, acquire assets, or pay dividends. Representing the difference between cash receipts from the sale of goods or services and cash outlays required in their production, operating cash flow is usually understood to be operating income before deductions for interest, depreciation, and amortization (EBITDA) and, more recently and alternatively, operating income before depreciation and amortization (OIBDA).38 Although it has lost some analytical favor, cash flow (EBITDA) so defined is often used as a valuation metric for all kinds of hotel, airline, media, and entertainment assets because the distortional effects of differing tax and financial structure

1.6 Industry Structures and Segments

29

Fig. 1.20 Relative percent of PCEs for selected categories, 2019

cruise ships 8.2% casinos 27.6%

theme parks 16.2% car rentals 4.6%

hotels 28.0%

Fig. 1.21 Shares of PCEs for travel by air, bus, and rail, 1959–2019

airlines 16.2%

%

0.9 Air

0.6

0.3

Rail Bus

59

69

79

89

99

09

considerations are stripped away. A business property can thus be more easily evaluated from the standpoint of what it might be worth to potential buyers.39 Also, a trend of declining EBIT margins (i.e., EBIT/revenues) always has stockprice forecasting implications because it suggests that companies are finding it more difficult to convert revenues into cash—a situation that if sustained leads ultimately to lower share valuations. By and large, the weak growth of cash flows relative to earlier periods suggests that it will be more difficult and costly for travel firms to finance new asset additions and equipment and infrastructure replacements through borrowings and/or sales of equity (i.e., shares of stock). Further consolidation through heightened merger and acquisition activity ought to be expected if overall growth were to remain subdued over an extended period (e.g., as in a pandemic). Nevertheless, a thorough analysis of the composites shown in Table 1.6 would require consideration of many features of the business environment, including interest rates, antitrust policy attitudes, the trend of dollar exchange rates, and

30 Fig. 1.22 Percent of PCE’s for foreign travel by U.S. citizens, 1959–2019

1 Economic Perspectives %

1.5

1.1

0.7

Foreign travel by U.S. Citizens

0.3 59

Fig. 1.23 Consumer Price Index inflation-rate comparisons for all urban consumers (CPI-U) and selected industry segments, 1980–2019. Source: Bureau of Labor Statistics

69

79

89

99

09

375 Air

300 225 150

CPI-U

75 0 80

90

00

10

relative pricing power. This last factor is illustrated by Fig. 1.22 which compares the rise of airfares and lodging prices against the average of all items for all urban consumers (CPI-U). From this, it can be seen that since the early 1980s, prices in both segments have been rising faster than the average rate of inflation. Finally, an indexed comparison of the percentage of personal-consumption expenditures going to different segments reveals the effects of changes in technology and in spending preferences. Two such trends are reflected in Fig. 1.23 in which the indexed percentage of total PCEs going to airlines and hotels is illustrated. Interestingly, the effects of airline price-deregulation of around 1980 can be seen, with the airline index losing altitude relative to the hotels segment index. At the time, hotels benefited from relatively improved pricing power as a result of the increased demand that was stimulated by newly deregulated airfares. Meanwhile, a similar index of spending on casinos (not shown) is now approximately fifteen times the level of 1959 (Fig. 1.24).

1.6 Industry Structures and Segments Fig. 1.24 Indexed personal consumption expenditures on airlines and hotels as a percent of total PCEs, (1959 ¼ 1.0), 1959–2019

31

index

5.0

Airlines

4.0

3.0 Hotels

2.0

1.0 59

Table 1.7 Top ten ad spending categories in the United States, 2018

69

79

89

Retail Automotive Medicine & remedies Financial services Telecom, Internet Food, beverages. & candy Travel & tourism (airlines, hotels, etc.) Restaurants Personal care Insurance

99

09

$ billions 17.8 14.3 9.4 8.6 8.5 7.3 7.0 6.8 5.9 5.3

Source: Advertising Age and Kantar media, December 2018 and author’s estimates

1.6.3

Advertising and Promotion

The industrial structure that most commonly appears in all of the important travelrelated segments leads inevitably to a great need for advertising and promotional services. Such services often provide the only timely and efficient means to make widely dispersed and diverse consumers aware of constantly changing products, prices, and availabilities. Inormation—about airline schedules and routes, hotel amenities, new features and attractions, or changes in hours of operation—is vital to smooth operational performance and branding. Especially within an oligopolistic or competitive-monopolistic framework, advertising and promotion is often one of the few ways for companies to differentiate themselves. All of this makes advertising an important expense category for airlines, hotels, car rental and travel agencies, casinos, theme parks, and restaurants. As may be seen from the compilation in Table 1.7, annual expenditures for advertising in these categories (including restaurants, casinos, and theme parks) added up to almost $14 billion in 2018.

32

1.7

1 Economic Perspectives

Valuation Variables

Important as it is to understand the economic perspectives, it is ultimately the role of the financial analyst to condense this information into an asset valuation estimate. The key question for investors is whether the market is correctly pricing the assets of an industry or of a company. In attempting to arrive at an answer, analysts find that valuation of assets often involves as much art as it does science. Valuation methods fall into three broad categories of approaches, using discounted cash flows, comparison methods, and option-pricing models. Sometimes all three approaches are suitable and the results are compared. At other times, the characteristics of the asset to be valued are such that only one approach is used. In most cases, however, the central concept is discounted cash flow, which takes account of both the time value of money and risk. The assessment of risk then leads to probability concepts—often applied to investments and gambling—that are somewhat simplistically expressed via calculations of expected values (EVs). This notion appears as: EV ¼

X

PðX i Þ  X i ,

in which each possible outcome, Xi, is multiplied by the likelihood (i.e., probability) that it will occur, P(Xi). These are then all added together. For instance, if the probability of a film earning $100 million is estimated to be 60% and the probability of it generating $200 million is 40%, EV ¼ 0:6 x 100 þ 0:4 x 200 ¼ 60 þ 80 ¼ 140: Such calculations are readily applied to games of chance but usually are not suitable and misleading when the range of probable outcomes is not completely known. Another valuation metric, popularized especially by technology stock investors, is that of the total addressable (or potentially available) market (TAM) that a company might eventually be able to grow into. Companies with large perceived and/or estimated TAM’s are most often accorded relatively higher than average price-to-earnings or price-to-sales ratios.

1.7.1

Discounted Cash Flows

Given that the primary assets of travel industry companies are composed of both tangible assets such as buildings and equipment and intangible assets embodied in the form of brand names and reservation systems, it is reasonable to base valuations on the expected future profits that the control of such assets might be expected to convey over time. Although it is not a flawless measure, estimated cash flow

1.7 Valuation Variables

33

(or perhaps EBITDA) discounted back to a present value will usually well-reflect such profit potential as long as a reasonable discount rate is ascribed and the time horizon is relatively brief: Cash flow to equity (i.e., after interest expenses and principal payments) must use a cost of equity capital discount rate, whereas cash flow to the firm (i.e., prior to interest expenses and principal payments) would use a weighted average cost of capital (WACC) discount rate. The discounted cash flow approach takes the value of any asset as the net present value (NPV) of the sum of expected future cash flows, as represented by the following formula: NPV ¼

t¼n X

CF t =ð1 þ rÞt ,

t¼1

where r is the risk-adjusted required rate of return (tied to current interest rates), CFt is the projected cash flow in period t, and n is the number of future periods over which the cash stream is to be received. To illustrate most simply, assume that the required rate of return is 9%; that the projected net cash flows of a new theme-park attraction in each of the next three years are $3 million, $2 million, and $1 million; and that the attraction has no value beyond the third year. The NPV of the attraction would then be 3/(1.0 + 0.09) + 2/(1.0 + 0.09)2 + 1/ (1.0 + 0.09)3 ¼ 2.75 + 1.683 + 0.7722 ¼ $5.205 million. Discount rates are normally the most important decisional variable in proposed capital-intensive investments for all tourism and travel-related projects that would include but are not limited to airplane or ship purchases, airport, rail, and road infrastructure, and hotels.40 These rates are, in turn, significantly influenced by a nation’s central bank monetary policies as typically expressed and influenced through changes in short-term interest rates, changes in bond purchases or sales, and foreign exchange rate considerations.

1.7.2

Comparison Methods

Comparisons of various company financial ratios and characteristics will also typically provide important valuation insights. These comparisons will often include current price multiples of cash flows and estimates of earnings, shareholders’ equity, and revenue growth rates relative to those of similar properties. And one of the best yardsticks for comparing global companies that report with different accounting standards is a ratio of enterprise value (EV) to EBITDA. Enterprise value, subject to adjustment for preferred shares and other off-balance-sheet items, equals total common shares outstanding times share price (i.e., equity capitalization) plus debt minus cash.

34

1 Economic Perspectives

Of course, a ratio of price to cash flow, earnings, revenues, or some other financial feature should—but opportunistically may not—already reflect inherently the estimated discounted cash flow and/or salvage (terminal) values of an asset or class of assets. If hotels are thus being traded at prices that suggest multiples of ten times next year’s projected cash flow, it is likely that most other hotels with similar characteristics will also be priced at a multiple near ten. This comparative-multiple approach is often used in valuations of travel industry properties even though it is not particularly good in capturing what economists call externalities—those factors that would make a hotel property, for example, especially valuable, say, as a “trophy” to a specific buyer. Prestige, potential for political or moral influence, and access to certain markets are all externalities that ordinarily affect transaction prices.

1.7.3

Options

For assets that have option-like characteristics or that are traded infrequently, neither the discounted cash flow nor the price and ratio comparison approaches can be readily applied. Instead, option-pricing models (e.g., the Black-Scholes model) that use contingent claim valuation estimates (of assets that pay off only under certain contingencies) are usually employed. This approach, however, is not used in travel industry practice unless the asset to be valued is an option contract (e.g., a warrant, call, or put) or is a contract for marketing or distribution rights or for some form of intellectual property right (e.g., a patent). Some other variations on these valuation concepts are discussed in Appendix B.

1.7.4

Business Model Aspects

The coronavirus pandemic of 2020 damaged the global travel and tourism buinesses to an extent not ever before experienced. At the nadir in the spring of that year, airline boardings fell by 97 per cent, cruise ships stopped cruising, hotels hosted no guests, casinos and theme parks were shuttered, and many companies were fighting for their very survival. Even the largest could only be saved through a combination of special government-authorized subsidies, loans, and bailouts. This event completely upended the business model assumptions and efficiency concepts—i.e., ever quicker turnaround times and crowd density increases—that had been an integral part of the operating philosophies and growth strategies of all travel and tourism segments. For instance, in airlines, where profit margins have often been very thin or lacking, the operating objective prior to the pandemic was always to keep the equipment (i.e., planes) in the air for as many hours a day as possible and to fill

1.8 Macro Trend Disruptors

35

the cabins to the brim, clustering seats and passengers ever closer together. In theme parks and casinos, the larger the crowd crammed into the facility the merrier in terms of profitability, excitement, and “atmosphere.” In restaurants, the goal is to fit as many tables as possible into a space and to then have the guests start and finish their meals quickly. But responses to the pandemic required crowd density reductions, slower turnaround times, and incursion of additional costs related to maintenance, cleaning, and health issues. Efficiencies involving time useage and density will, in one form or another, always be sought because they are fundamental to all travel and tourism sectors. Hence, once a crisis passes into history, growth strategies will out of necessity again revert to their previous methods, goals, and aspirations. The turmoil of 2020 clearly exposed and highlighted important and often hidden financial risk aspects.

1.8

Macro Trend Disruptors

Most travel industry sectors tend to grow in response to increasing global populations, productivity enhancements made possible by new technological advances that ultimateyl allow for more leisure and vacation time, and overall rising incomes and wealth. But every so often, the long term trend is distorted and disrupted by external factors that wreak havoc on the financial performance of even the best of companies and sectors. Among the most important pertain to energy costs, health issues, wars and political instabilities and upheavals. Relatively large changes in each of these areas have in the past affected the livelihoods of tens of millions of people and with many firms struggling to survive. Such macro trend disruptors are not unusual occurrences in the long history of travel and tourism industry growth and they are certain to appear again in the future. No perspective on travel and tourism economics would thus be complete without some historical context on major macro trend disruptors.

1.8.1

Oil

For the economy as a whole, but especially for travel and tourism industries, there is no single thing that is more important than oil. It has been estimated, for example, that for every $10 per barrel rise in the price of crude, U.S. GDP declines by around 0.3%. Each 1% rise in the global growth rate adds around 500,000 barrels a day to demand. For the U.S., each $1 change in the price per barrel, translates within a few weeks to a change in retail pump prices of around 2.5 cents a gallon. And global jet-fuel demand will normally account for around 7.5% of petroleum production.

36

1 Economic Perspectives

Without oil or an inexpensive and readily available substitute for it—something that does not yet exist—there is no driving, no flying, and no cruising: There are no profitable theme parks, casinos, or hotels. This direct dependence of travel and tourism industries on the prices and availabilities of petroleum-based products and services suggests that no financial analysis of travel and tourism would be complete without some reference to the availability and pricing of oil. It is, therefore, sensible to assume that the relatively inexpensive price of oil has over the last seventy years supported, if not actually directly subsidized, travel prices and thus also the demand for hotel, lodging and affiliated industry services. All other things then being equal, relatively low energy prices will generally add to global travel demand (and vice versa). Except for the brief pricing and availability problems in the 1970s and 2007–08, oil has been generally so plentiful and cheap that there has been no need for worry or concern: A gallon (~4 liters) of gasoline in the United States was and is still less expensive than a gallon of milk or sometimes even of bottled water. By the late 1990s, however, it has been recognized that many large fields, including the vast ones in the Middle Eastern countries, might be approaching exhaustion.41 World annual consumption as of 2019 was at a rate of around 36 billion barrels a year and rising and an estimate that perhaps only 1500 billion barrels of proven and probable global reserves remain to be recovered suggests that—at current rates of consumption and of new-field discovery—world supplies might not last more than another forty years! If so, and in the absence of further large discoveries and/or of technological substitutes, the price in real terms can only rise substantially. Under such conditions, people will be inevitably forced to re-allocate their budget priorities—spending more for energy (e.g., heating and air-conditioning as well as for driving and flying) and less on other items.42 Although rising prices ($145 a barrel at the peak in 2008) appear to have signaled that world production is already becoming insufficient to match the new demands spurred by rapidly modernizing nations such as India, China, and Brazil, such a pessimistic view is not totally convincing in view of the steep drop to under $45 a barrel in 2015.43 Implementation of modern oil shale and natural gas extraction technologies (including horizontal drilling and “fracking”) suggest that the U.S. has already become largely energy-independent. And alternatives to petroleum will be ultimately developed and already include tar-sand, hydrogen, algae cultivation, and solar power sources. Meanwhile, new petroleum and gas reserves continue to be found in many places outside of the Middle East.44 The challenge for travel-related industries, though, is to survive and prosper through often difficult periods of highly volatile energy prices and government policies.45 The travel and tourism sector benefits greatly from the fact that a price decline of $10 a barrel corresponds roughly to a 0.25 percentage point gain in GDP growth over the following year. Even so, given that travel-related industries all require substantial energy inputs for operations, imposition of taxes imposed for the purposes of reducing carbon

1.8 Macro Trend Disruptors Fig. 1.25 World crude oil production (consumption closely tracks production), 1960–2018. Sources: International Energy Annual, EIA.gov

37 $ price

Billions bbl/year

125

42

100

35 World Consum ption

28

75

21

50 25

14 real price/bbl

-

7 60

Fig. 1.26 Crude oil production and consumption in the United States, 1950–2018. Source: Annual Energy Review, DOE/EIA. gov

8

70

80

90

00

10

Billions bbl/year

6 U.S Consumption

4 U.S. Production

2 0 50

60

70

80

90

00

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emissions and slowing climate changes have the potential to significantly impair the investment characteristics of travel companies. World oil production and consumption rates and the inflation-adjusted annual average prices per barrel are illustrated in Fig. 1.25. Production and consumption rates for the United States appear in Fig. 1.26.

1.8.2

Health Issues

The global Covide-19 (coronavirus) pandemic appears to have originated in or near a biological research laboratory in Wuhan, China. And within a few weeks after its identification in late 2019, it had spread to every part of the world and by Spring 2021, infecting at least 100 million people and leading to 2 million deaths. There have over history been many other dangerous virus infections with much higher mortality rates. The numerous previous pandemics include Malaria, referenced in Chinese documents of around 2700 BC, the Plague of Athens in

38

1 Economic Perspectives

163 A.D, the Black Death Bubonic Plague of 1665, and Cholera in 1817. All occurred in a time when global air travel and shipping didn’t exist. In the early 2000s episodes included SARS, MERS, Ebola, and H1NI (aka “swine flu”). But none of these were as contagious and as financially and economically devastating to the global travel and tourism and entertainment-related sectors as Covid-19. The United Nations World Tourism Organization estimated that lost revenues in 2020 globally totaled US$1.3 trillion and that international tourism arrivals fell by one billion or 7.4%.46 To contain the contagion, in the first half of 2020, entire cities and countries and industries needed to be closed, locked-down, and shuttered. Quarantines and travel bans were commonly mandated in many countries. And people were advised to “shelter-at-home” and to avoid close contact with others. Even more confounding was that some virus-carriers experienced no symptoms yet could transmit it to the population at large. As a result, the survival of airlines, hotels, casinos, cruise ships, restaurants, museums, and concert and sports arenas soon everywhere required massive government handouts, bailouts, and loans. The data that appear in most of the book’s tables and figures thus cannot be linearly extrapolated even though the business, financial, accounting, and operational features and aspects remain largely the same as they long have been.

1.8.3

Wars and Politics

Warfare and political conflict appear throughout human history and have always diminished and disrupted the otherwise long upward macroeconomic trends that, for both business and pleasure, will normally favor travel and tourism activities. The same applies to violent political disputes and protests that have often occurred in many different societies and cultures. Proper financial analysis must always take these issues into account. An example is provided by the large and lengthy freedom protests in Hong Kong (circa 2018–2019) that noticeably reduced tourism spending and casino business in nearby Macau.

1.9

Big Data and Artificial Intelligence (AI) Aspects

The rise of social networks operating on mobile devices and transmitted through increasingly fast and sophisticated technologies (e.g., 5G) has drastically reconfigured the media and entertainment landscape for consumers and companies. “Big Data” refers to massive and complex data-sets that are captured, stored, mined, sliced and diced, and statistically analyzed so as to expose potentially valuable behavioral insights and predictions that can theoretically lead to greater sales, higher profitability, and more direct interaction with end consumers.

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Concluding Remarks

39

For example, purchases of a plane ticket or hotel room from online sites had previously provided the carrier or hotel company with little or no information about the purchaser. But application of artificial intelligence to big data bases provide immensely more information for the purposes of targeting, advertising, and strategic planning. Airlines, theme parks, and casinos can more readily determine their staffing needs with respect to local weather and seasonal factors and tourism destinations can now adjust their capital spending budgests and promotional plans with far greater accuracy than ever before. As the data flow in, artificial intelligence systems are able to automatically and constantly “learn” to better discern and anticipate what the customer will likely want, need, or do in the future. In brief, AI enables connection and analysis of previously unobservable patterns of behavior, prices, and markets.

1.10

Concluding Remarks

Travel may be characterized as: • Largely a derived demand as people for the most part travel for business, leisure, and/or visiting friends and family. Few people ride trains or airplanes just for the ride experience alone. • Dependent on prices of energy and capital inputs and costs in terms of ticket prices and total time spent in transit. • Dependent on the rate of economic and productivity growth. More productivity allows for more leisure time and travel options. Technological developments lead to both. This chapter has sketched the economic landscape in which all travel industries operate. It has indicated how hours at work, productivity trends, expected utility functions, demographics, and other factors can affect the amounts of time and money spent on goods and services that include travel. That time is money translates directly into the cost and benefit analysis that always goes into decisions of travelers in choosing when, where, and how to travel and also to the scheduling, pricing, and capital investments companies make in providing the services. Benchmarks against which the relative growth rates and sizes of different industry segments or composites can be measured have also been presented. Technological development has obviously played an important role too. It underlies the growth of productivity and thus of the relative supply of leisure time. But just as significantly, technological advances have changed the way in which we think of travel and leisure services. Figure 1.27 provides an overview of travel industry milestones. Greater detail appears in the milestone illustrations in each of the industry chapters that follow.

1910

1930

1970

First Holiday Inns

Travel Industry Milestones

1950

CAB formed

Motor Carrier Act regulates buses with ICC

Commercial flight service popularized

Railway Labor Act

Five-day workweek introduced at Ford

First national hotel chains evolve

1990

2010

Gulf War disrupts world travel ICC Termination Act Microsoft starts Expedia Internet allows price comparison shopping Terrorists attack U.S., Aviation & Transport Security Act First commercial maglev train service (Shanghai) Carnival & Princess cruise lines merge ($5.4 bn) Iraq War Oil price peak @ $147/barrel Great Recession New airline fees for bags and food Costa Corcordia cruise shipwreck Expedia buys Travelocity, Orbitz Coronavirus halts global travel

Mirage opens first Las Vegas mega-resort

Yield management and frequent flyer programs introduced

Bus Regulatory Reform Act

International Air Transportation Competition Act National Tourism Policy Act

Airline Deregulation Act

Helsinki International Travel Accord

OPEC's first oil price shock

Modern Cruise industry sets sail

Disney World opens

First commercial jets Amtrak (National Rail Passenger Corp.) formed by Congress

Federal Aviation Act forms FAA

Interstate Highway Act

Disneyland opens

Transportation Act returns rails to private sector

Passports introduced

Fig. 1.27 Travel industry milestones, 1890–2020

1890

Thomas Cook, first travel agent, 1841

Passenger Vessel Act, 1886

Interstate Commerce Act, 1887, creates Interstate Commerce Commission (ICC)

First scheduled intercity bus service

Hepburn Act give ICC power to set rail rate ceilings

Automobile era begins

Passenger Shipping Act

First American Express travelers checks

40 1 Economic Perspectives

1.10

Concluding Remarks

41

“Travel,” says Thomas (2020) “can change the way we feel about our home places.” And, “it can make us wiser as well as better-informed.” These notions ring true for all travelers at all times. Notes 1. De Grazia (1962, p. 13) notes that it is obvious that “time on one’s hands is not enough to make leisure,” and free time accompanied by fear and anxiety is not leisure. As Torkildsen (1999, p. 93) also notes, the concept of leisure can also be defined as an activity, experience, state of being, a way of life, and so on, and it can encompass play and recreation activity. Kaplan (1960) defines leisure as a composite that includes creation of pleasant expectations and recollections, requires minimal social-role obligations, involves a psychological perception of free, and is often characterized by play. See also Henig (2008), Pieper (2009), Rojek (2010), and Surdam (2015). 2. Gilder (2018, p. 47). See also Hamermesh (2019). 3. Annual vacation and holiday time also varies greatly. In the late 1990s, the number of days off in the United States averaged twenty-five; in Canada, twenty-nine; in Germany, forty; and in Japan, forty-four. See Grimsley (1998) and Landler (2004). 4. As Smith (1986, p. 8) has further noted, surveys indicate that for full-time, day-shift plant workers, the average workweek decreased by 0.8 h between 1973 and 1985 but that over the same period, “the schedule of full-time office workers in the private sector rose by 0.2 h, with the result that the workweek of these two large groups converged markedly.” Hedges and Taylor (1980) show that hours for full-time service workers declined faster than for white-collar and blue-collar employees between 1968 and 1979. In addition, the Bureau of Labor Statistics estimated that the percentage of nonagricultural salaried jobs in which the workweek exceeded 49 h rose to 18.5% in 1993 as compared to 14.2% in 1973. Through World War I Americans regularly worked 6 days a week and it was not until after passage of the Fair Labor Standards Act in 1938 that overtime pay and a 40-h workweek became the norm. 5. The Harris nationwide cross-section sample survey of 1501 adults found that the estimated hours available for leisure have been steadily decreasing from 26.2 h per week in 1973 to 16.6 h per week in 1987. Since 1989 this has stabilized at around 20 h. Harris argues that an apparent combination of economic necessities and choices by women who want to work has increased the number of families in which both husbands and wives hold jobs. Also see Gibbs (1989). 6. Schor (1991, p. 29) wrote that between 1969 and 1987, “the average employed person is now on the job an additional 163 h, or the equivalent of an extra month a year. . .and that hours have risen across a wide spectrum of Americans and in all income categories.” These estimated changes in hours worked appear strikingly high. It seems that, although the analysis could have been correct in catching the direction of change, it might have mistakenly estimated its magnitude. Schor’s book is so politically imbued with an anticapitalist theme that the

42

7.

8.

9.

10.

11.

1 Economic Perspectives

methodology and the objectivity of its findings are suspect. See also Robinson and Godbey (1997) and The Economist, December 23, 1995, p. 12. Effects on work hours during the 2007–09 recession are discussed in Kroll (2011). Robinson (1989, p. 35) found, for example, that “people aged 51 to 64 have gained the most free time since 1965, mainly because they are working less. Among people in this age group, the proportion of men opting for early retirement increased considerably between 1965 and 1985.” Also, Robinson and Godbey (1997) suggest that Americans, in the aggregate, have more time for leisure because of broad trends toward younger retirements and smaller families. Except for parents of young children, or those with more than four children under age eighteen, everyone else, they say, has gained at least one hour per week since 1965. Hammermesh (2019) provides time spending details. Roberts and Rupert (1995) state that the presumption of declining leisure is a fallacy. “Previous studies purporting to have uncovered such a fact have not adequately disentangled time spent in home production-activities . . . from time spent enjoying leisure activities. [W]hile hours of market work and home work have remained fairly constant for men since the mid-1970s, market hours have been rising and home production hours have been declining for women . . . Possible reasons include an increase in market versus nonmarket productivity or labor-saving technological advancements in the home.” Rones, Ilg, and Gardner (1997) concluded that, between 1976 and 1993, “after removing the effect of the shifting age distribution, average weekly hours for men showed virtually no change (edging up from 41.0 to 41.2 hours), and the average workweek for women increased by only a single hour [but] . . . a growing proportion of workers are putting in very long workweeks . . . This increase is pervasive across occupations, and the long workweek itself seems to be associated with high earnings and certain types of occupations.” Note that the U.S. Federal Government approved funding in December 2000 for an American Time Use Survey of Activity. See Shelley (2005). Divergence of results in studying hours of work may be caused by differences in how government data are used. For example, such data generally are based on hours paid rather than hours worked. This means that a worker on paid vacation would be counted as working, even though he or she was not. Also, hours per job, rather than hours per worker are used. The shift in work-hour trends in Europe is a function of competition from low-wage countries and is discussed in Landler (2004). Rybczynski (1991) provides a detailed history of the evolution of the weekend, and Spring (1993) provides a study of the popularity of spare-time activities classified by day of the week. Television viewing, consuming one-third of free time on weekdays and one-fourth on weekends, leads the list by far on every day of the week. Veal (2007) provides a broad survey of the economics of leisure and Cameron (2011) collects studies on the economics of leisure. A history of leisure time, spending preferences, and elasticities for 1890–1940 appear in Bakker (2011).

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Concluding Remarks

43

12. In addition, studies comparing time allocation in different countries can be found in Juster and Stafford (1991), where, for example, it can be seen that both men and women allocate more time to leisure in the United States than in Japan or Sweden. Bell and Freeman (2000), however, explain that the differences in hours worked in different countries are related less to cultural values than to a greater diversity of wages, the effects of number of hours worked on future compensation, and less job security in the United States than elsewhere. They find that an American working 2000 h per year who increases that by 10% to 2200 h can generally expect a “1 percent increase in future wages.” 13. The quote is from Winston (2013). Economists such as Hensher (2013) have also studied what is known as valuation of travel time savings. 14. The apparently reduced rate of improvement between 1973 and 1990 may have been caused by unexpected sharp cost increases for energy and capital (interest rates), by high corporate debt levels, or perhaps by the burgeoning “underground’” (off-the-books) economy not directly reflected in (and therefore distorting) the NIPA numbers. As McTague (2005) suggests, growth of the underground economy still creates important distortions, especially in the measurement of productivity. McKinsey (2010) speculates that the gap in European productivity is a result of a greater preference for leisure time and also relative underperformance of service sectors. As of 2010, the per capita gross domestic product (GDP) gap was estimated to be $11,250. 15. There are many fine texts providing full descriptions of these tools. 16. In most mathematical presentations, the independent variable or the “cause” of change is presented along the horizontal x-axis and the dependent variable on the vertical y-axis. Economists, however, have generally found it more convenient to depict prices (the independent variable) and quantities by switching the axes. Thus, prices are usually seen on the vertical axis and quantities on the horizontal one. Werner (2005, p. 326) importantly notes that “the variable that produces the equilibrium in this model is price. However, to achieve this outcome, perfect information is required. If there is imperfect information, there is no guarantee that equilibrium will ever be obtained. It would be pure chance if demand equaled supply.” 17. In Linder (1970), standard indifference-curve/budget-line analysis is used to show how the supply of labor is a function of income and substitution effects. The standard consumers’ utility function is V ¼ f(Q, Tc), where Q is the number of units of consumption goods, and Tc is the number of hours devoted to consumption purposes. Two constraints are Q ¼ pTw, and T ¼ Tw + Tc, where p is a productivity index measuring the number of consumption goods earned per hour of work (Tw), and T is the total number of hours available per time period. To maximize utility, V now takes the Lagrange multiplier function: L ¼ f(Q, Tc) + λ[Q
p(T
Tc)], which is then differentiated with respect to Q, Tc, and the multiplier λ. 18. See Trost (1986) and Monthly Labor Review, U.S. Department of Commerce, Bureau of Labor Statistics, November 1986, No. 11, November 1986.

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19. Owen’s (1970) exhaustive study of these issues leads to a model supporting the hypothesis of a backward-bending labor-supply curve and suggesting that demand for leisure activity has positive income and negative price elasticities, consistent with economic theory. 20. Utility can often be visualized in the form of a mathematical curve or function. For instance, the utility a person derives from the purchase of good x might vary with the square root of the amount of x (i.e., U(x) ¼ square root of x). See Levy and Sarnat (1972). 21. The quotation is from Barrett (1974, p. 79). Taking this a step further, one finds that a marginal rate of substitution (MRS) between good x and good y can then be presented in the form of indifference curves that are a ratio of the marginal utility (MU) of x to the marginal utility of y, and along which utility is constant. The underlying assumption is that of diminishing marginal utility, which means that the curves never intersect and are negatively sloped and generally convex to the origin. 22. This first appeared in Pine and Gilmore (1998, p. 102) in the form of a circle divided into four parts or “realms” rotating clockwise from entertainment (upper left) to educational, esthetic, and escapist and centered on a vertical axis ranging (top to bottom) from absorption to immersion and a horizontal axis ranging (left to right) from passive to active participation. See also Blackman (2014). 23. A 2016 study commissioned by Booking.com and appearing in HNN Newswire 29 November 2016 questioned 17.00 people from 17 countries found among other things that 77% of people book a holiday to cheer themselves up. The planning (anticipatory and visualization) stages provide the most immediate boost. See also Van Boven and Gilovich (2003) and Carter and Gilovich (2010), and Blackman (2014). Lancaster (1966, 1971) developed the consumption characteristics approach. Pine and Gilmore (1998) first wrote about the experience economy and explain that “experiences are a distinct economic offering, as different from services as services are from goods. . . An experience occurs when a company intentionally uses services as the stage, and goods as props, to engage individual customers in a way that creates a memorable event.” Scitovsky (1976) wrote on the psychology of happiness and satisfaction. 24. A dependency ratio is the number of people who are net consumers (children and senior citizens) divided by the number of net producers; see, for example, Burton and Toth (1974). See also Gladwell (2006). 25. Regulation is often deemed politically necessary to offset alleged imperfections in the market economy. At times there have been movements to contain monopoly power, to control excessive competition, to provide public goods, and to regulate externalities. In travel-related industries, such regulatory influence can be seen in the 1997 Vail Resorts and Ralston Resorts proposed merger in which the Justice Department adopted a narrow definition of the ski market and similarly by the Federal Trade Commission with regard to the cruise vacation market when Royal Caribbean Cruises and Carnival Corporation fought to acquire P&O Princess Cruises in 2003. Sorkin (2004) discusses the

1.10

26.

27.

28. 29. 30.

31.

32.

Concluding Remarks

45

regulatory approach to the proposed MGM Mirage acquisition of Mandalay Resort Group. Price or other elasticities are also often taken at a point and expressed in the calculus as ε p ¼
( p/q) x (dq/dp), where q is a measure of quantity of units demanded and p is price per unit. Historical comparisons studied by Costa (1997) show that from 1888 to 1991 expenditure elasticities have fallen from around two around one currently. The decline is attributed to rising incomes, falling prices of recreation, and investment in public recreational goods. Cox and Alm (2007) show that as incomes rise, elasticities also generally tend to rise for services, medicine and health care, education, and communications and transportation. For “Giffen goods” in which people consume more as the price rises, the income effect is stronger than the substitution effect. These relationships are consistent with the notion of utility maximization and are often expressed in what are known as Engel curves which show how the quantity demanded of a good or service changes as the consumer’s income level changes. However, estimates typically have low explanatory power. Gabaix (2009) reviews the important presence of power laws in finance and economics. The complete PCE tables include much greater detail than is shown here. The estimate of 4.6% to 5.3% for 1992 appears in Okubo and Planting (1998, p. 9). It was also found that value added in travel and tourism represented 1.9% to 2.2% of GDP, with hotels and lodging generating the highest value added. However, the entertainment services series as a percentage of total recreation spending has demonstrated considerable volatility since 1929. This series hit a peak of nearly 50% in the early 1940s, when there were relatively few consumer durables available. Then, for a dozen or so years ending in the late 1970s, the percentage had been confined to a fairly narrow band of 33% to 36%. GNP measures output belonging to U.S. citizens and corporations wherever that output is created, whereas GDP measures the value of all goods and services produced in a country no matter whether that output belongs to natives or foreigners. In actuality, in the United States the differences between the values of the two series have been slight. Critics of National Income Accounting, for example Cobb, Halstead, and Row (1995), argue that GDP measurements allow activities in the household and volunteer sectors to go entirely unreckoned. As a result, GDP measurements mask the breakdown of the social structure and are grossly misleading. As they put it, “GDP does not distinguish between costs and benefits, between productive and destructive activities, or between sustainable and unsustainable ones. The nation’s central measure of well-being works like a calculating machine that adds but cannot subtract . . . The GDP treats leisure time and time with family the way it treats air and water: as having no value at all.” (pp. 64–67) See also Uichitelle (2006) and Zencey (2009), who say that the “basic problem is that gross domestic product measures activity, not benefit.” Stiglitz, Sen, and Fitoussi (2010) discuss additional problems in viewing economic activity through GDP metrics.

46

1 Economic Perspectives

33. Schafer (2000) also found through analysis of cross-sectional and longitudinal studies, confirmation of earlier work in which strong regularities in time and monetary expenditure shares for passenger travel are seen for many countries. See also Jorgenson and Preston (2007). 34. In finance, a handy shortcut is known as the “rule of 72” which allows approximation of the time it takes for an amount to double. Thus, a compound rate of growth of 3% divided into 72 suggests that the initial amount would double in 24 periods. 35. Price indexes comes in several versions; CPI-U for all items and urban consumers, CPI-W for wage earners, and a GDP deflator series. The GDP deflator series does not generally rise as fast as those measuring CPIs. An illustration of hedonic effects is that a desktop computer of 1980 was primitive to those of today yet it cost a lot more in inflation-adjusted terms. 36. The Herfindahl–Hirschman Index (HHI)—used by the Department of Justice in determining whether proposed mergers ought to be permitted—is calculated as the sum of the squared market shares of competitors in the relevant product and geographic markets: n P HHI ¼ S2i i¼1

where S is the market share of the ith firm in the industry and n equals the number of firms in the industry. Generally, near-monopolies would have an HHI approaching 10,000; modest concentrations would fall between 1000 and 1800; and low concentration would be under 1000. For airlines, Hanlon (1996, p. 62) notes that, “[E]ven where increasing concentration is simply the result of efficient firms becoming more dominant, once they achieve this greater dominance they will enjoy a greater degree of monopoly market power, which they may then use to raise prices.“Williamson (1968) had earlier shown how the balance between market power and efficiency depends on the price elasticity of demand for the particular goods or services, with the degree of monopoly market power of a firm represented by its pricecost margin, which is (price minus marginal cost)/price. Firms with no monopoly power (i.e., operating under textbook definitions of perfect competition) would have a ratio of zero. The Gini coefficient or Gin index, originated by sociologist Corrado Gini in 1912 to measure income inequality, is also used to express concentration in markets. When everyone has the same income or share, the coefficient is zero. And when there is maximal inequality, the coefficient is one (or 100%). On a graph, using income distribution, the cumulative share of people from lowest to highest incomes goes from left to right on the x-axis and the cumulative share of income earned appears on the y-axis. A 45-degree straight line indicates perfect equality. 37. For example, airline segment operating income had grown nearly twice as fast as hotel segment operating income between 1993 and 1998 (not shown) and also faster than for hotels between 2010 and 2014.

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Concluding Remarks

47

38. OIBDA eliminates the uneven effect across company business segments of non-cash depreciation of tangible assets and amortization of certain intangible assets that are recognized in business combinations. The limitation of this measure, however, is that it does not reflect periodic costs of certain capitalized tangible and intangible assets used in generating revenues. OIBDA also does not reflect the diminution in value of goodwill and intangible assets or gains and losses on asset sales. In contrast, free cash flow (FCF) is defined as cash from operations less cash provided by discontinued operations, capital expenditures and product development costs, principal payments on capital leases, dividends paid, and partnership distributions, if any. More emphasis is also being placed on return on invested capital (ROIC), defined as EBIT(1- tax rate)/[(Debt +Equity) – (Cash + Equivalents)]. See Benoit (2016). 39. Enthusiasm for the use of EBITDA as an important metric of comparison has waned in light of the accounting scandals of the early 2000s. Increasingly, investors appear to favor measures of free cash flow and net earnings, especially now that the rules for writing down goodwill have been changed (see Chap. 4) and given that EBITDA does not indicate the detrimental effects of high and rising debt obligations on balance sheets and rising interest expenses on net earnings. 40. Cochrane (2011) provides a rigorous analysis of the importance of discount rates. 41. A possible peak in production was first noted by M. King Hubbert, a Shell Oil geologist who predicted in 1956 that production in the contiguous United States would peak in the 1970s. Peak oil is discussed in Simmons (2005) and Hubbert’s Peak in Campell (2004), Goodstein (2004), Deffeyes (2003, 2005), Maxwell (2004). Gold and Davis (2007) suggested that the peak global production ceiling is probably around 100 million barrels a day. A downgrade of supply projections by the International Energy Agency appears in King and Fritsch (2008). See also Maass (2005). Corsi and Smith (2005) and Mills (2008) show that hydrocarbon materials are continually seeping upward from deep below the earth’s surface and that oil and gas are abiotic—i.e., do not require decay of dinosaurs or plants or photosynthesis—and also are renewable. Mann (2013) discusses fracking and methane hydrate and the possibility that reserve supplies are still ample. Mills (2017) write on low-cost fracking and Epstein (2014) makes the moral case for use of fossil fuels. 42. In the United States, which absorbs around 20% of world production (with China around 21% in 2016), approximately two-thirds of consumption goes to fuel cars, trucks, and planes. As economic development in China, India, and Brazil proceeds, the demand for fuel in those populous countries will likely be of similar proportion. Appenzeller (2004) notes since 1970, the total miles traveled annually by cars and trucks in the United States has doubled and thus far outstripped population growth. Schwartz (2008) briefly reviews the history of how the United States came to be so dependent on oil. See also Graham and Glaister (2002).

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1 Economic Perspectives

43. Huber and Mills argue that, as of 2005, the global average cost of lifting a barrel is under $15 ($5 in the Middle East and about $15 to melt it out of Alberta sands). Also, reserves are at least 3.5 trillion barrels, at three times conventional estimates and enough to last another one hundred years. Ball (2004), Huber and Mills (2005), Radetzki (2010), Luskin and Warren (2015), and Aguilera and Radetzki (2016) are optimistic about the availability of oil resources. See also “The Oil Sands of Alberta,” 60 Minutes, CBS News, January 22, 2006, Energy’s Future beyond Carbon,” Scientific American, September 2006, and Saleri (2008), Increasing energy efficiency is another mitigating factor given that real U.S. economic output, using about the same amount of crude, was 25% higher in 2011 than it had been a dozen years prior. 44. See McKillop (2005) and Broad (2010) explain the formation of oil. Fallows (2012) writes about algae facilities. The question remains whether it requires more energy to produce this algae oil than that contained in the oil itself. See Helman (2013). 45. See also Tertzakian (2006); Bryce (2008); and Hicks and Nelder (2008); “The Future of Energy” in The Economist, June 21, 2008; and Helman (2009). A broad overview appears in El-Gamal and Jaffe (2010). The pessimistic view, which incorporates accounting for costs of ecological damage, is presented in Hallett and Wright (2011). A more optimistic view is presented in Corsi and Smith (2005), Huber and Mills (2005), Reed (2010), Yergin (2020, 2011, 2012), and Lynch (2015). Button (2013) writes about transport and energy. 46. See McKay and Dvorak (2020) and Rickards (2021).

References Aguiar, M., and Hurst, E. (2007). “Measuring Trends in Leisure: The Allocation of Time over Five Decades,” Quarterly Journal of Economics, 233)(August). Aguilera, R. F., and Radetzki, M. (2016). The Price of Oil. New York: Cambridge University Press. Appenzeller, T. (2004). “The End of Cheap Oil,” National Geographic, June. Bakker, G. (2011). “Leisure Time, Cinema, and the Structure of Household Entertainment Expenditure,” 1890–1940,” in S. Cameron, ed. Handbook on the Economics of Leisure. Cheltenham, UK: Edward Elgar. Ball, J. (2004). “As Prices Soar, Doomsayers Provoke Debate on Oil’s Future,” Wall Street Journal, September 21. Barrett, N. S. (1974). The Theory of Microeconomics Policy. Lexington, MA: Heath. Becker, G. S. (1965). “A Theory of the Allocation of Time,” Economic Journal LXXV(299) (September):493–517. Bell, L. A., and Freeman, R. B. (2000). “The Incentive for Working Hard: Explaining Hours Worked Differences in the U.S. and Germany,” NBER Working Paper 8051 (December). New York: National Bureau of Economic Research (www.nber.org). Benoit, D. (2016). “Finance’s Hot New Metric: ROIC,” Wall Street Journal, May 4. Blackman, A. (2014). “Can Money Buy You Happiness?,” Wall Street Journal, November 10. Broad, W. J. (2010). “Tracing Oil Reserves to Their Tiny Origins,” New York Times, August 3. Bryce, R. (2008). Gusher of Lies: The Dangerous Delusions of “Energy Independence.” New York: Public Affairs.

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Bull, A. O. (1995). The Economics of Travel and Tourism, 2nd ed. Melbourne: Longman Australia. Button, K. J. (2013). “Transport and Energy,” in De Palma et al., eds. (2013). Button, K. J. (2010). Transport Economics, 3rd ed. Cheltenham, UK and Northampton, MA: E. Elgar. Button, K. J. (1993). Transport Economics, 2nd ed. Cheltenham, UK and Northampton, MA: E. Elgar. Cameron, D., Spector, M., and Nicas, J. (2011). “American Lands in Bankruptcy,” Wall Street Journal, November 30. Corsi, J. R., and Smith, C. R. (2005). Black Gold Stranglehold: The Myth of Scarcity and the Politics of Oil. Nashville, TN: WND Books (Cumberland House). Carter, T. J., and Gilovich, T. (2010). “The Relative Relativity of Material and Experiential Purchases,” Journal of Personality and Social Psychology, 98(1). Cochrane, J. H. (2011). “Discount Rates,” Journal of Finance, 66(4) (August). Cox, W. M., and Alm, R. (2007). “Opportunity Knocks,” 2007 Annual Report, Federal Reserve Bank of Dallas. Costa, D. L. (1997). “Less of a Luxury: The Rise of Recreation Since 1888,” NBER Working Paper 6054 (June). Deffeyes, K. S. (2005). Beyond Oil: the View from Hubbert’s Peak. New York: Farrar, Strauss, Geroux (Hill and Wang). Deffeyes, K. S. (2003). Hubbert’s Peak: The Impending World Oil Shortage. Princeton (N.J.): Princeton University. De Grazia, S. (1962). Of Time, Work and Leisure. New York: Twentieth Century Fund. DeSerpa, A. C. (1971). “A Theory of the Economics of Time,” Economic Journal (December):828–46. El-Gamal, M. A. and Jaffe, A. M. (2010). Oil, Dollars, Debt, and Crises: the Global Curse of Black Gold. New York: Cambridge University Press. Epstein, A. (2014). The Moral Case for Fossil Fuels. New York: Portfolio/Penguin. Fallows, J. (2012). “China Takes Off,” Popular Science, May. Gabaix, X. (2009). “Power Laws in Economics and Finance,” Annual Review of Economics, 1255–93. Ghez, G. R., and Becker, G. S. (1975). The Allocation of Time and Goods Over the Life Cycle. New York: National Bureau of Economic Research. Gibbs, N. (1989). “How America Has Run Out of Time,” Time, 133(17)(April 24). Gilder, G. (2018). Life After Google: The Fall of Big Data and the Rise of the Blockchain Economy. Washington, DC. Regenery. Gladwell, M. (2006). “The Risk Pool,” The New Yorker, August 28. Gold, R., and Davis, A. (2007). “Oil Officials See Limit Looming on Production,” Wall Street Journal, November 19. Goodstein, D. (2004). Out of Gas: The End of the Age of Oil. New York: W. W. Norton. Graham, D. J., and Glaister, S. (2002). “The Demand for Automobile Fuel: A Survey of Elasticities,” Journal of Transport Economics and Policy, 36(1)(January). Grimsley, K. D. (1998). “An Ocean of Difference in Vacation Time,” The Washington Post, June 30. Hallett, S., and Wright, J. (2011). Life Without Oil: Why We Must Shift to a New Energy Future. Amherst, NY: Prometheus. Hamermesh, D. S. (2019). Spending Time: The Most Valuable Resource. New York: Oxford University Press. Hanlon, P. (1996, 1999 2nd ed., 3rd ed. 2007). Global Airlines: Competition in a Transnational Industry. Oxford, UK: Butterworth-Heinemann. Harris, L. (1995). The Harris Poll 1995, # 68. New York: Louis Harris & Associates, Inc. Hedges, J. N., and Taylor, D. E. (1980). “Recent Trends in Worktime: Hours Edge Downward,” Monthly Labor Review, 103(3)(March).

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Helman, C. (2013). “Green Oil: Scientists Turn Algae Into Petroleum in 30 Minutes,” Forbes, December 23. Helman, C. (2009). “Crude Cassandra,” Forbes, 183(4)(March 2). Henig, R. M. (2008). “Taking Play Seriously,” New York Times, February 17. Hensher, D. A. (2013). “Valuation of Travel Time Savings,” in De Palma et al., eds. (2013). Hicks, B, and Nelder, C. (2008). Profit From the Peak: The End of Oil and the Greatest Investment Event of the Century. Hoboken, NJ: John Wiley & Sons (Angel). Huber, P. and Mills, M. (2005). “Oil, Oil, Everywhere. . .,” Wall Street Journal, January 27, and The Bottomless Well: The Twilight of Fuel, The Virtue of Waste, and Why we Will Never Run Out of Energy. New York: Basic Books. Jacobs, J. A., and Gerson, K. (1998). “Who Are the Overworked Americans?” Review of Social Economy, vol LVI (4)(Winter). Jorgenson, F., and Preston, J. (2007). “The Relationship Between Fare and Travel Distance,” Journal of Transport Economics and Policy, 41(3)(September). Juster, F. T., and Stafford, F. P. (1991). “The Allocation of Time: Empirical Findings, Behavioral Models, and Problems of Measurement,” Journal of Economic Literature, June, vol. 29. Kaplan, M. (1960). Leisure in America: A Social Inquiry. New York: John Wiley & Sons. Kroll, S. (2011). “The Decline in Work Hours During the 2007–09 Recession,” Monthly Labor Review, 134(4)(April). Lancaster, K. J. (1971). Consumer Demand: A New Approach. New York: Columbia University Press. Lancaster, K. J. (1966). “A New Approach to Consumer Theory,” Journal of Political Economy, 84. Landler, M. (2004). “Europe Reluctantly Deciding it Has Less Time for Time Off,” New York Times, July 7. Levy, H., and Sarnat, M. (1972). Investment and Portfolio Analysis. New York: Wiley. Linder, S. B. (1970). The Harried Leisure Class. New York: Columbia University Press. Luskin, D. L., and Warren, M. (2015). “The Shale Boom Shifts Into Higher Gear,” Wall Street Journal, June 1. Lynch, M. C. (2015). The “Peak Oil” Scare and the Coming Oil Flood. Santa Barbra, CA: Praeger (ABC-Clio). Maass, P. (2005). “The Breaking Point,” New York Times, August 21. Mann, C. C. (2013). “What if We Never Run Out of Oil?,” The Atlantic, May. Maxwell, C. T. (2004). “The Gathering Storm,” Barron’s, November 15. McGrattan, E. R., and Rogerson, R. (2004). “Changes in Hours Worked, 1950–2000,” Quarterly Review, Federal Reserve Bank of Minneapolis, 28(1)(July). McKay, B, and Dvorak, P. (2020). “A Pandemic Was Inevitable, Why Was No One Ready,” Wall Street Journal, August 14. McKillop, A., ed. (2005). The Final Energy Crisis. Ann Arbor, MI: Pluto Press. McTague, J. (2005). “Going Underground,” Barron’s, January 3. Mills, M. P. (2017). “Saudi Arabia Puts U.S. Energy Producers to a Test – and They Ace It,” Wall Street Journal, March 28. Mills, R. M. (2008). The Myth of the Oil Crisis: Overcoming the Challenges of Depletion, Geopolitics, and Global Warming. Westport, CT: Praeger. Okubo, S., and Planting, M. A. (1998). “U.S. Travel and Tourism Satellite Accounts for 1992” Survey of Current Business. Washington, DC: U.S. Department of Commerce, Bureau of Economic Analysis, (July). Owen, J. D. (1988). “Work-Time Reduction in the U.S. and Western Europe,” Monthly Labor Review, 111(12)(December). Owen, J. D. (1976). “Workweeks and Leisure: An Analysis of Trends, 1948–75,” Monthly Labor Review, 99(8)(August). Owen, J. D. (1970). The Price of Leisure. Montreal: McGill-Queen’s University Press.

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Pieper, J. (2009). Leisure: The Basis of Culture. San Francisco: Ignatius Press (original ed. Random House 1963). Pine, B. J., and Gilmore, J. H. (1998). “Welcome to the Experience Economy,” Harvard Business Review, July–August. Radetzki, M. (2010). “Peak Oil and Other Threatening Peaks – Chimeras Without Substance,” Energy Policy, 38(11). Ramey, V. A., and Francis, N. (2009). “A Century of Work and Leisure,” American Economic Journal: Macroeconomics, 1(2)(July). Reed, S. (2010). “Endless Oil,” BusinessWeek, January 7. Rickards, J. (2021). The New Great Depression: Winners and Losers in a Post-Pandemic World. New York: Portfolio/Penguin. Roberts, K., and Rupert, P. (1995). “The Myth of the Overworked American,” Economic Commentary. Cleveland: Federal Reserve Bank of Cleveland, January 15. Robinson, J. P. (1989). “Time’s Up,” American Demographics, 11(7)(July). Robinson, J. P., and Godbey, G. (1997). Time for Life: The Surprising Ways Americans Use Their Time. University Park, PA: Penn State Press. Rojek, C. (2010). The Labour of Leisure: The Culture of Free Time. London: Sage. Rones, P.L., Ilg, R. E., and Gardner, J. M. (1997). “Trends in Hours of Work Since the Mid-1970s,” Monthly Labor Review, BLS, April. Rybczynski, W. (1991). “Waiting for the Weekend,” The Atlantic Monthly, 268(2)(August), and Waiting for the Weekend (New York: Viking). Saleri, N. G. (2008). “The World Has Plenty of Oil,” Wall Street Journal, March 4. Schafer, A. (2000). “Regularities in Travel Demand: An International Perspective,” Journal of Transportation and Statistics, (December). Washington, DC: U.S. Department of Transportation, Bureau of Transportation Statistics. Schafer, A., and Victor, D. (1997). “The Past and Future of Global Mobility,” Scientific American, 277(4) (October). Schor, J. B. (1991). The Overworked American: The Unexpected Decline of Leisure. New York: Basic Books. Schwartz, N. D. (2008). “American Energy Policy, Asleep at the Spigot,” New York Times, July 6. Scitovsky, T. (1976). The Joyless Economy. New York: Oxford University Press. Sharp, C. H. (1981). The Economics of Time. Oxford, UK: Martin Robertson. Shelley, K. J. (2005). “Developing the American Time Use Survey Activity Classification System,” Monthly Labor Review, (June), U. S. Department of Labor. Simmons, M. R. (2005). Twilight in the Desert: The Coming Saudi Oil Shock. Hoboken, N.J.: John Wiley & Sons. Smith, S. J. (1986). “The Growing Diversity of Work Schedules,” Monthly Labor Review, November, 109(11). Sorkin, A. R. (2004). “Regulators Will Decide Fate of Bid for Mandalay,” New York Times, June 15. Spring, J. (1993). “Seven Days of Play,” American Demographics, 15(3), March. Surdam, D. S. (2015). Century of the Leisured Masses: The Rise of Leisure in Twentieth-Century America. New York: Oxford University Press. Tertzakian, P. (2006). A Thousand Barrels a Second: The Coming Oil Break Point and the Challenges Facing an Energy Dependent World. New York: McGraw-Hill. Thomas, E. (2020). The Meaning of Travel: Philosophers Abroad. Oxford: Oxford University Press. Torkildsen, G. (1999). Leisure and Recreation Management, 4th ed. London and New York: SPON Press and Routledge. Trost, C. (1986). “All Work and No Play? New Study Shows How Americans View Jobs,” Wall Street Journal, December 30. Uichitelle, L. (2006). “Seizing Intangibles for the G.D.P.,” New York Times, April 9.

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Van Boven, L., and Gilovich, T. (2003). “To Do or to Have: That Is the Question,” Journal of Personality and Social Psychology, 85. Veal, A. J. (2007). “Economics of Leisure,” in C. Rojek et al. (2007). Veblen, T. (1899). The Theory of the Leisure Class. New York: Macmillan (paperback, New American Library, 1953). Werner, R. A. (2005). New Paradigm in Macroeconomics: Solving the Riddle of Japanese Macroeconomic Performance. Houndmills, U.K.: Palgrave Macmillan. Williamson, O. E. (1968). “Economies as an Antitrust Defense,” American Economic Review, 58 (1) (March). Winston, C. (2013). “On the Performance of the U.S. Transportation System: Caution Ahead,” Journal of Economic Literature, 51(3)(September). Yergin, D. (2020). “The New Geopolitics of Energy,” Wall Street Journal, September 12. Zeisel, J. S. (1958). “The Workweek in American Industry 1850–1956,” in Mass Leisure, Larrabee, E., and Meyerson, R., eds. Glencoe, IL: The Free Press. Zencey, E. (2009). “G.D.P. R.I.P.,” New York Times, August 10.

Further Reading Aeppel, T. (2015). “U.S. Productivity: Missing or in Hinding?” Wall Street Journal, July 17. Aguiar, M., Hurst, E., and Karababounis, L. (2013). “Time Use During the Great Recession,” American Economic Review, 103(5)(August). Aron, C. S. (1999). Working at Play: A History of Vacations in the United States. New York: Oxford University Press. Athavaley, A. (2007). “Vacation Deflation: Breaks Get Shorter,” Wall Street Journal, August 15. Burton, J. S., and Toth, J. R. (1974). “Forecasting Long-Term Interest Rates,” Financial Analysts Journal, 30(5)(September/October):73–87. Button, K. (2005). “The Economics of Cost Recovery in Transport,” Journal of Transport Economics and Policy, 39(3)(September). Clemence, S. (2013). “Bringing Back the No-Stigma Extended Vacation,” Wall Street Journal, June 29. Cooke, A. (1994). The Economics of Leisure and Sport. London: International Thomson Publishing Company. Elliott, J. (1997). Tourism: Politics and Public Sector Management. London and New York: Routledge. Han, X., and Fang, B. (1998). “Measuring Transportation in the U.S. Economy,” Journal of Transportation Statistics (June). Washington, DC: U.S. Department of Transportation, Bureau of Transportation Statistics. King, N. Jr. (2007). “Saudi Industrial Drive Strains Oil-Export Role,” Wall Street Journal, December 12. Kirkland, K. (2000). “On the Decline in Average Weekly Hours Worked,” Monthly Labor Review, 123(7)(July). Lundberg, D. E., Stavenca, M. H., and Krishnamoorthy, M. (1995). Tourism Economics. New York: John Wiley & Sons. Marano, H. E. (1999). “The Power of Play,” Psychology Today, 32(4)(August). Mason, J. (2012). “AMR and the Return of the Bare-Knuckled Bankruptcy,” The Deal Magazine, February 6. McCarthy, P. S. (2001). Transportation Economics. Theory and Practice: A Case Study Approach. Oxford, UK: Blackwell. McDowell, E. (1997). “The Abbreviated Tourist: Americans Are So Busy with So Many Places to Go,” New York Times, July 31.

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Miller, C. C. (2020). “The Five-Day Office Week May be Over,” New York Times July 6. Naisbitt, J. (1994). Global Paradox. New York: Morrow. Owen, J. D. (1971). “The Demand for Leisure,” Journal of Political Economy, 79(1)(January/ February). Paulin, G. D. (2015). “Travel Expenditures, 2005–2013: Domestic and International Patterns in Recession and Recovery,” Monthly Labor Review, March. Reilly, R. F., and Schweihs, R. P. (1999). Valuing Intangible Assets. New York: McGraw-Hill. Rhoads, C. (2002). “Short Work Hours Undercut Europe in Economic Drive,” Wall Street Journal, August 8. Roberts, P. (2004). The End of Oil: On the Edge of a Perilous New World. Boston: Houghton Mifflin. Robinson, J. P., Martin, S., Glorieux, I., and Minnen, J. (2011). “The Overestimated Workweek Revisited,” Monthly Labor Review, 134(6)(June). Scott, J. (1999). “Working Hard, More or Less,” New York Times, July 10. Smith, G. V., and Parr, R. L. (1994). Valuation of Intellectual Property and Intangible Assets, second ed. New York: John Wiley & Sons. Stopher, P., and Stanley, J. (2014). Introduction to Transport Policy. Cheltenham, UK: Edward Elgar. “Study of Travel and Tourism,” The Economist, January 10, 1998 and, March 21, 1991. Thomas, E. (2020). The Meaning of Travel: Philosophers Abroad. Oxford: Oxford University Press. Tribe, J. (2011). The Economics of Recreation, Leisure and Tourism. Oxford: ButterworthHeinemann/Elsevier. Toossi, M. (2012). “Labor Force Projections to 2020: A More Slowly Growing Workforce,” Monthly Labor Review, 135(1)(January). Tungate, M. (2018). The Escape Industry: How Iconic and Innovative Brands Built the Travel Business. New York: Kogan Page. Varchaver, N. (2004). “How to Kick the Oil Habit,” Fortune, 150(4)(August 24). Vitello, P. (2008). “More Americans Are Giving Up Golf,” New York Times, February 21. Whaples, R. M. (1990). “The Shortening of the American Work Week: An Economic and Historical Analysis of Its Context, Causes, and Consequences,” https://repository.upenn.edu/dissertations/ AAI9026669/ Winston, C. (1985). “Conceptual Developments in the Economics of Transportation: An Interpretive Survey,” Journal of Economic Literature, 23.

Part II

Getting There

Abstract All travel, going from here to there, requires that large-capital investments in machinery, infrastructure, systems, and technology are efficient and affordable. Part II reviews the major modes, including airlines, cruise ships, rail, and automobiles. The coverage includes historical developments, long-term trends, operaional and marketing methods and metrics, and accounting treatments.

Chapter 2

Wings

I’ll teach you how to jump on the wind’s back, and then away we go.—Peter Pan by J. M. Barrie.

The dream has always been to fly. That famous flyer of Greek mythology, Icarus, flew too close to the Sun and his wax wings melted. The Wright Brothers of North Carolina managed in 1903 to fly their Kitty Hawk a few hundred feet across a field and just barely above the ground. Nowadays—in non-pandemic-affected times—travel by air is so common that, on a global basis, 3.3 billion passengers a year take 33 million scheduled flights over more than 1.5 billion miles (2.5 billion km) on more than 23,000 commercial aircraft that provide service via 1000 commercial airlines to 3700 airports. More than 18,000 city pairs are connected. This volume of traffic, growing globally at an estimated annual rate of 3%, makes the airline business one of the largest of any in the world economy. At this rate the number of aircraft will approximately double to 43,000 by 2030, with the percentage share of total traffic continuing to shift to Asian, Latin American, and African markets. It has been forecasted (by the ICAO and IATA) that sometime in the 2030s, China will likely become the largest market, with 1.6 billion passengers (versus 1.3 billion in the U.S.) per year and mostly carried by the largest state-run companies (Air China, China Eastern, and China Southern). Table 2.1 compares estimated regional airline passenger traffic flow growth rates into the early 2030s. Despite its enormity, the increasingly complex and technologically sophisticated airline industry is guided by relatively simple and readily analyzed economic principles. Its history of development can be roughly divided into five distinct phases: (a) the early era of technological and regulatory implementation lasting from 1900 to 1930; (b) air travel and transportation becoming an ingrained component of the overall economy in both war and peace, 1930 to 1960; (c) the era of jets and jumbos, 1960 to 1980; (d) the era of deregulation, 1980 to 2000; and (e) the current period of financially forced restructuring and rationalization and technologies that allow passengers to book trips and compare prices online. A sixth era, that of higher-trending but more volatile oil prices, arguably began in 2008, when the price spiked to around $145 a barrel, then fell steeply, rebounded back to more than $110 a barrel by 2011, and then declined again to below $50 a barrel by 2015. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 H. L. Vogel, Travel Industry Economics, https://doi.org/10.1007/978-3-030-63351-6_2

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Table 2.1 Airline passenger traffic flow growth rate estimates (RPKs in billions) in percent by region, 2019–2038 RPKs in percentagesa China North America Europe Middle East Oceana South America Africa

China 6.2

North America 4.9 3.3

Europe 5.2 2.9 3.6

Middle East 9.4 6.3b 4.3 4.7

Oceana 4.7

4.2 3.7

Sputh America 8.8b 5.4 4.9b – 6.7

Africa 7.1b 5.4 4.5 7.3 8.0b 6.6

Source: Boeing Current Market Outlook, 2019–38 available at Boeing.com/cmo Revenue passenger kilometers (RPKs) b Based on previous year estimates a

Unbundling of services previously provided for free (e.g., food, checked baggage, seat selection) also have come to characterize this sixth era.

2.1

Onward and Upward

The principles of flight had, by the late 1800s, already been demonstrated (Fig. 2.1). However, it required another one hundred years or so before the oligopolistic structure of the global airline industry had been solidified through a spate of mergers and acquisitions. That the industry should evolve in this way should come as no surprise given the tremendous amounts of capital investment required to launch and maintain airline equipment and services.

2.1.1

Technology and Early History

Twelve seconds. That’s how long the Kitty Hawk, the first powered airplane designed by the Wright brothers, stayed aloft on its first flight in December 1903. And it was only a few years later, in July 1909, that history was again made as Frenchman Louis Blériot piloted the first flying machine across the English Channel. Civilian commercial flights followed soon thereafter, first from Blackpool (August 1910) England and then in 1914 in Florida, where the first scheduled air service began (in a noisy flying boat, with its pilot and one passenger sitting on a small windexposed wooden bench).1 Ever since, technological progress and growth of passenger volume has been onward and upward. Still, commercial aviation was slow to catch on with the general public. In those early days people could travel as fast and more comfortably by rail and perceived flight as dangerous. But the value for military purposes quickly became clear in

1910

Fig. 2.1 Airline industry milestones, 1890–2020

1890

Interstate Commerce Act, 1887

Lilienthal gliders prove principles of flight

First flight (Wright Bros. ``Kitty Hawk")

First scheduled flights

First airmail

Paris Convention – sovereignty over air space

British (Imperial) Airways begins

Contract Air Mail Act

Air Commerce Act

First trans-Atlantic flight (Lindbergh)

1930

Big Four (American, Eastern, United, and TWA) emerge

Continental Airlines founded

DC-3 introduced by American Airlines

Civil Aeronautics Act passed

1950

1970

Bermuda - bilateral agreement (U.S. & U.K.)

Piedmont Airlines begins

American Airlines Sabre sustem introduced

Eastern Air-Shuttle begins

First turbo-jets

Federal Aviation Act forms FAA

2010

2030

1990

2010

Delta & Northwest merge

Airbus A380s begins New Open Skies deal for US & EU

Air France and KLM merge US Airways & America West merge ($1.5 bn) Delta, Northwest bankruptcy

People Express fails USAir buys Piedmont for $1.6 billion Eastern bankrupt after machinists' strike American buys Eastern's L. American routes for $300 mm United & American buy Heathrow rights ($400-$445 million) Pan Am bankruptcy Delta buys Pan Am Atlantic rights ($1.3 billion) United buys Pan Am Latin American routes ($135 mm) European de-regulation Northwest buys Continental stake Marketing alliances (Star, OneWorld, Wings) begin to form UAL bids $4.3 billion for US Airways, then cancels American buys bankrupt TWA ($742 million) Terrorists attack U.S., Aviation and Transportation Security Act US Airways bankruptcy (and again in Sept. '04) Start-ups (Legend, JetBlue, National) appear United bankruptcy

American introduces 'yield mgmt

United pilots strike, Delta buys Western Airlines for $860 mm United and BA begin code-share

Pandemic collapses Global air travel demand

Boeing 787- Max crashes

Alaska buys Virgin Amer.

BA parent buys Aer Lingus

DOJ probes collusion Terrorists attack Paris

Iceland volcano disrupts traffic United and Continental merge US Airways & American merge Southwest buys Airtran

American introduces first 'frequent-flyer' Braniff fails Continental declares bankruptcy Virgin Atlantic begins CAB ends United buys Pan Am Asia routes for $750 mm

Pan Am buys National Airlines for $374 mm People Express begins PATCO (air controllers) fired

Southwest Airlines begins service First fuel crisis Supersonic service (Concorde) begins Second fuel crisis Laker Airways low fares over North Atlantic Airline Deregulation Act

Widebody Boeing 747 and DC-10 and L-1011 begin

First commercial flights over North Pole by SAS

Airline Industry Milestones

Heathrow opens

Chicago Convention - International tariffs & rights

2.1 Onward and Upward 59

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Wings

World War I, especially as evolution of more powerful motors enabled aircraft to reach higher speeds and altitudes. In that war, Britain, France, and Germany each produced more than 48,000 planes and, in all countries, civil air transport development grew out of the military use of aircraft. The German all-metal Junkers F13 monoplane is considered to be the world’s first practical civilian transport airplane. Airmail came next. Using a large number of war-surplus planes, the U. S. Post Office began airmail service in 1917 and by 1919 had begun to provide segments of transcontinental shipment by air. The government then moved to transfer airmail service to the private sector through the 1925 Contract Air Mail Act (Kelly Act), which provided the impetus for creation of a private U.S. airline industry. The core of several major carriers, including United Airlines, American Airlines, and TWA (as well as the ultimately defunct Pan Am and Eastern), grew from the roots of the winners of the initial five contracts. Also in 1925, the predecessor of the Federal Aviation Administration (FAA), the Morrow Board, was established to recommend national civil aviation standards. Congress adopted the Morrow Board recommendations in passing the Air Commerce Act of 1926. With this, the government began to pay private mail carriers according to the weight carried rather than a percentage of the postage paid. Development in Britain followed a similar path. In 1917 the Royal Flying Corps ferried mail across the channel and, by 1918, the services run by the Royal Air Force (RAF) had established the framework for what ultimately became an extensive international network of civilian air carriers led by the companies Air Transport & Travel and Handley Page. Then there was the famous Sopwith Camel, a British single-seat biplane fighter with powerful rotary engines and twin synchronized machine guns that was introduced in 1917 and credited with shooting down more enemy aircraft than any other fighter of the war. French companies, with the help of government subsidies, also sprang into competition around this time, connecting Paris and London. By the early 1920s, Brussels and Amsterdam were also becoming routine destinations. And in Germany, Junkers and another company were merged in 1926 and provided with annual subsidies in support of what became Lufthansa. Because of its near-monopoly position and government support, the early Lufthansa, unlike many other European carriers, was highly profitable. As a result, it was able to open the first air service to China in 1930, even though China at that time had no aerial maps, repair stations or airports, and only primitive landing strips. By 1938 Lufthansa had pioneered nonstop trans-Atlantic flights, going via four-engine propeller plane from Berlin to eastern Long Island’s Floyd Bennett Field in around 25 hours. As in the United States and Germany, however, the government was soon enmeshed in the affairs of the British civilian industry, especially through efforts of the Civil Air Transport Subsidies Committee, otherwise known as the Hambling Committee. This committee decided on the need for a British national flag-carrier, named Imperial Airways Limited, to be formed via merger of several smaller companies that would receive subsidies and that would purchase British-made aircraft and engines. Yet subsidies notwithstanding, Imperial ultimately failed to adequately service connections to Europe and it was eventually absorbed through a

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forced merger in 1938 with British Airways, a company that had originated in 1935. It was not until the 1974 merger of British Overseas Airways Corporation (BOAC) with British European Airlines, that the modern British Airways was formed with a critical mass of equipment, routes, and service. Charles Lindbergh’s historic first nonstop flight from New York to Paris across the Atlantic Ocean in 1927 was most significant in that it fully captured the public’s imagination and began to attract to this industry many millions of dollars of private investment on both sides of the Atlantic. (The first transatlatinc flight, including several stops, had been flown in 1919.) 2 With capital now being injected more rapidly, technological development of aircraft and aviation systems accelerated. Airlines began to attract more passengers away from the railroads, engines and cockpit instruments improved, and better radio communications equipment made it possible to fly at night or in poor weather conditions. Radio beacons became operational in 1932 and the first air traffic control tower was constructed at Newark International Airport in 1935. Development of Britain’s Heathrow Airport—opened in 1946 on the site of a former World War I grassrunway airstrip (with the first terminal building constructed in 1955)—was also notable as Heathrow quickly became (because of location, time zones, etc.) the leading international airport with few rivals until 1990. The 1930s also brought political scandal in the form of the Watres Act passed by Congress in 1930 and the subsequent “spoils conference” based on this act. In the spoils conference, smaller airlines were purposely shut out of bidding for government airmail contracts in the expectation that promotion of larger, stronger airlines would be in the national interest. But the issue of unfairness to the smaller lines raised political pressure that led to the Air Mail Act of 1934 and a more competitive structure for the private carriage of mail. In Canada, Trans-Canada Air was legislated into existence in 1936 as a subsidiary of CN Rail, whose shares were owned by the Canadian government. Modern passenger aircraft also advanced rapidly at this time, with United Airlines in 1933 buying sixty Boeing 247 s, each of which could accommodate ten passengers and cruise at 155 miles per hour. Not to be outdone, TWA bought an alternative model from Douglas aircraft, the DC-1, which was equipped with the first efficient wing flaps and autopilot. Rapid improvements on the initial model then led to the DC-3, which American Airlines introduced in 1936 and which—being the first aircraft that enabled airlines to make money carrying passengers—became the workhorse of the industry. The DC-3 had twenty-one seats, was equipped with hydraulic landing gear, and could go coast-to-coast in sixteen hours, an impressive speed for that time. By 1940 the Boeing Stratoliner, a derivative of the B-17 bomber, provided another technological leap with its pressurized cabins allowing flights to go as high as 20,000 feet and at speeds of 200 miles per hour. Things also began to move faster on the regulatory front with the establishment of the Civil Aeronautics Authority (CAA) by way of the Civil Aeronautics Act of 1938. The act was unusual from today’s perspective in that the airlines actually wanted greater government regulation through an agency empowered to regulate airline

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tariffs, airmail rates, mergers, and routes while sheltering them from unbridled competition. Congress then also in 1940 created a separate agency, the Air Safety Board, which was later combined with the CAA to form the Civil Aeronautics Board (CAB). Aviation also played an important role in World War II, a time of especially rapid technological progress in systems and equipment. The fighter and bomber planes and radar designs that came out of the war were soon applied to the civilian segment, with jet engines being the most important of these innovations. These engines for the first time made it possible to visit and/or view the earth’s entire surface. and their introduction forever redefined and changed commerce, leisure, arts, and culture (as well as war and peace). An early-model British-made passenger jet, the Comet, flying from London to Johannesburg in 1952 could now fly at speeds up to 500 miles per hour. This also enabled formation of Japan Airlines which, in recovering from the war, then had pressing need for trade and travel over long oceanic distances.3 The true coming of the passenger-jet age (surveyed by Verhovek 2010), however, did not appear until 1958, when Boeing introduced its 707 model with a capacity of 181 passengers and a speed of up to 550 miles per hour. A Pan Am 707 then became the first transatlantic (New York to Brussels) non-stop commercial jet flight. But with airlines concentrating on passenger carriage and not at all equipped to efficiently handle freight, the way was clear for a young man by the name of Fred Smith—starting in 1969 with two small jets—to build a delivery system that bypassed crowded passenger hubs and congested daytime flying times to move packages and parts overnight. Today, FedEx along with competitor UPS are the world’s largest freight airlines each annually generating more than $70 billion in revenues. Jets became dominant because they could fly at heights that are usually above turbulent weather and at speeds about three times faster than aircraft powered by piston-driven gasoline engines. Later, the Boeing 737 became the best-selling aircraft in history, with more than 5000 put into service. And more than 100 years after the Kitty Hawk’s first wobbly flight, the Airbus A380 (no longer in production and replaced by more efficient smaller planes with better range and economics) had become the largest commercial plane—capable of holding up to 800 passengers, flying faster than 600 miles per hour (960 kph), and going 8500 nautical miles without refueling.4 Yet it also ought not to be forgotten that aviation was tragically brought to a practical standstill by terrorist attacks (on September 11, 2001) using hijacked civilian commercial aircraft against the World Trade Center in New York and the Pentagon in Washington, D.C.: Three thousand innocent people were murdered. Global airline passenger traffic and tourism then subsequently declined so steeply that many airline companies required extensive government guarantees and subsidies of various types so that services could be resumed.5 The coronavirus pandemic of 2020—in which passenger demand briefly collapsed by 90% or more from the year before—then had an even deeper and longerlasting affect on the industry and required similar guarantees, loans, and subsidies to rescue, restore, and support infrastructure.

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63

Regulation and Deregulation

With travel by air becoming more popular and the skies too crowded for existing systems to properly handle, Congress also saw, in 1958, the need to pass the Federal Aviation Act. This Act created the predecessor to the current FAA, which is now contained within the Department of Transportation. The FAA is responsible for sustenance of safe operating conditions for all commercial aircraft through all phases of flight within the air traffic control system: It assumes jurisdiction over aviation safety matters including certification of aircraft designs, airline training, and maintenance programs. Introduction of wide-bodied aircraft such as the Boeing 747 in 1969 and the Douglas DC-10 and Lockheed L-1011 in 1970 further revolutionized the economics of civilian aviation. The planes could seat as many as 450 passengers and as such had the potential to significantly lower the cost of carrying each passenger per mile of service. But it was not until after 1978, when the CAB was disbanded and competitive air travel pricing strategies could be implemented, that the public could truly reap the benefits of relatively low-cost travel by air. The Airline Deregulation Act of 1978 made all the difference; passenger demand soon afterward began rising quickly as flying became a common mode of transportation for the public at large (with similar deregulation implemented in Europe beginning in 1997). Only the supersonic Concorde—introduced in 1969 and flown in scheduled service by British Air and Air France for more than twenty-five years (until 2003)—had remained limited to those few who could afford the steep price of a ticket. It wasn’t until the mid-2020s that commercial supersonic passenger jet service again became available.6 The one thing that the traffic growth and deregulation of this era could not easily offset was the adverse effect on airline profits that came from formation of the OPEC oil cartel in the 1970s. Two large hikes in the price of jet fuel (oil)—always a significant component of total operating cost and at the time comprising 20% of the total—suppressed nascent industry profitability and gave airline investors an especially bumpy ride.7 Profitability was briefly restored after the economic recessions of the early 1980s (Fig. 2.2a). Then another recession beginning in mid-1990, the Gulf War of early 1991, and a highly competitive pricing environment once again depressed profits (Fig. 2.2b) until the record-long economic expansion and technological advances of the 1990s finally took hold. Airlines became a major beneficiary of the rising demand thereby created. Over this decade, such demand was further sustained by the continuing long-term decline by about one-third of the average real price (including extra baggage and other new fees) that passengers paid to fly a mile. Since then, this real price per mile has not varied much. Although the public-utility style regulation that characterized the airline business until the late 1970s no longer exists, there remain numerous restrictions and regulations concerning the award of landing rights, customer service reporting

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requirements (e.g., on-time arrivals, frequency of overbooking, etc.), and the power to grant privileges to carriers of foreign countries. The comment that “It’s the most regulated deregulated industry in the world” thus rings true.8 International landing agreements and privileges are still, however, negotiated bilaterally between nations and specify which cities can be serviced, how many flights each airline may operate, and the prices that each carrier may charge. Bilateral negotiations involving the United States are led by the State Department, with active participation from the Department of Transportation (formed in 1967).9 The International Air Transport Association (IATA), founded in 1945, represents the interests of the airlines and operates a clearing house for inter-airline debts arising from interairline traffic.10 Trends in passenger enplanements and average miles per flight are displayed in Fig. 2.3a.

2.1 Onward and Upward

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Operational Characteristics Structural Features

The industry has evolved to the point where several large carriers in the United States and a few large national carriers elsewhere capture an estimated 75% of all revenues generated. This structure takes advantage of available economies of scale in which purchases of everything from aircraft equipment to fuel, food, maintenance, insurance, financing, and advertising and marketing are less per mile flown and passenger served than if the industry operated with many smaller independent companies unable to pare down average unit costs. Majors The industry defines major airlines, also known as trunk carriers, as those companies generating revenues of more than $1 billion annually from provision of scheduled nationwide or worldwide services. Although the number seems bound to shrink as the industry consolidates into an oligopoly dominated by a few megacarriers, as of 2021, there were more than a dozen major U.S. airlines including: Alaska, Allegiant, American (merged with US Airways), Delta (merged with Northwest), ExpressJet, Federal Express, Frontier, Hawaiian, JetBlue, Southwest (bought AirTran), Spirit, United (merged with Continental), UPS, and Virgin.11 Except for the parcel-delivery companies, these (Group III) majors generate more than 90% of aggregated revenues from passenger traffic and less than 10% from cargo carriage, with approximately 75% of the flights being between domestic destinations. All of the majors are required to hold two certificates issued by the federal government. The Department of Transportation (DOT) under Section 401 of the Federal Aviation Act issues the first, a fitness certificate. It establishes that the carrier has the financial and management wherewithal in place to provide scheduled service with large aircraft, those with sixty-one or more seats and a payload of more than 18,000 pounds. The second, an operating certificate, is issued by the FAA under Section 121 of the Federal Aviation Regulations and specifies for aircraft with ten or more seats numerous requirements including those pertaining to the training of flight crews and to aircraft maintenance programs. Nationals and Regionals National carriers (in DOT Group II) are defined as scheduled airlines generating annual revenues between $100 million and $1 billion but they may sometimes provide long-haul and even international service. Like the majors, nationals operate mostly medium-and large-size jets and are thus subject to the same certification requirements as the majors. As of 2020, the Group IIs included Express Jet, Horizon, Mesa, and Sun Country. Regionals account for the majority of flights in the U.S. and had until recently been among the fastest growing companies. As the name implies, these carriers (RJs, in brief) for the most part provide service to only one region of the country and generate revenues of under $100 million (Group I). The largest regionals, with revenues of more than $20 million, must also comply with FAA and DOT

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certification requirements, although smaller, so-called commuter airlines are only required to file certain annual reports according to DOT’s Section 298 regulations. These small carriers are exempt from Section 401 fitness certificate requirements because their aircraft have fewer than thirty seats. Among the largest regionals are major-carrier affiliates that operate on fixed departure fees per flight.12 The major carriers set RJ schedules and establish fares but also absorb operational risks related to costs of fuel and revenue targets of their contract carrier affiliates. Charters, Taxis, and Fractional-Ownership Carriers Nonscheduled airline operators, known as charter airlines, are more frequently found serving the European than the U.S. tourism markets (see Chap. 7). Such airlines organize their operations by chartering aircraft equipment, often on a temporary basis, for the purpose of flying to specific tourist locations in season. However, Section 401 certification regulations for any aircraft operating within the United States are largely the same as for the major scheduled carriers. Development of new technologies (including, for example, complex planning algorithms) has also enabled charter air taxi-like companies to begin providing services on shorter routes. These online services allow passengers to instantly obtain prices on flight plans of their own design.13 And fractional-jet ownership programs, comparable in structure to vacation time-share plans used by the hotel industry, divert high-paying business customers from the major commercial airlines by offering the convenience and speed that major carriers are no longer able to provide. Such plans account for around 15% of all U.S. business-aviation flights.14 Labor Relations Labor accounts for a significant part of an airline’s total operating costs, typically ranging from at least 20% to sometimes as high as 40%. Discount airlines such as JetBlue and Southwest—in all accounting for around 20% of domestic U.S. air-carrier capacity as of the early 2000s—have enjoyed competitive advantages in that their labor cost percentages have tended to be near the lower end of the range as compared to the upper end of the range at legacy carriers. The actual percentage is influenced by a variety of factors that include average length of routes, average hours of flight per plane per day (e.g., around nine hours for Southwest and perhaps six hours for United and Delta); union and government agreements; and corporate history. Given that operating margins are already narrow to begin with, it has always been important to contain labor costs, as even small savings in this area may often translate into the difference between profit and loss. As a consequence, the industry has had a long history of labor strife, with work slowdowns or strikes being not all that uncommon (and with strikes occasionally averted in airline and railroad disputes through presidential intervention under the Railway Labor Act of 1926). This history of labor dissent, expressed in frequent union/management clashes, has extended across the board from pilots (e.g., the Airline Pilot’s Association, ALPA) to machinists (e.g., the International Association of Machinists and Aerospace Workers, IAM) and to flight attendants (e.g., the Association of Flight Attendants, AFA).15

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In attempts to relieve tensions and to combine the interests of labor and management, several airlines have—through union governance and in lieu of larger pay raises—sometimes given their workers equity stakes in the companies.16 To date, however, experiences with such arrangements have not proven viable over the long term. Whether or not they are, though, does not change the fact that labor unions are significant participants within the airline industry’s operating structure.

2.2.2

Basics

The airline industry long ago developed its own descriptive terminology of operational features. For instance, it is important for airlines as well as other types of public carriers to be able to compare revenues and costs per mile that are respectively earned and incurred in carrying each passenger (or cargo) unit. The standard measurements are thus stated in terms of revenue passenger-miles (RPM)—the number of revenue-paying passengers multiplied by the number of miles flown. In economic terms, RPMs are a measure of an airline’s or the industry’s output. Similarly, in freight and mail carriage, the analogous units on scheduled routes would be ton-miles or ton-kilometers (defined by the International Civil Aviation Organization [ICAO] as a combined measure of passenger, freight, and mail traffic which also takes into account distances flown). From this it may be inferred that on a worldwide basis the cargo-hauling (freight) aspects of airline operations account for roughly one-fourth of total airline output (i.e., compare the two right-hand columns) and perhaps up to an eighth of total operating revenues (Table 2.2).17 This means that for many airlines, especially those with international routes, cargo carriage will contribute significantly to profitability.18 By region, ICAO data indicate that in 2018, the percentages of total world traffic in terms of passengers carried was: Africa: Asia-Pacific: Europe: Middle East: Latin America and Carribean: North America: Total

2.2 37.1 26.0 5.3 6.8 22.6 100.0

From these definitions, it is then a simple step to calculate what is known as the yield, which is total revenue divided by the total number of passenger-miles flown (or in the case of cargo, tons flown). Yield, which can also be calculated as average revenue per passenger, is thus an arithmetic mean that indicates on the average how much revenue is generated per unit of output. It is usually stated in terms of cents per passenger-mile.

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Table 2.2 Airline scheduled-service carriages of passengers, freight domestic and international routes, top six countries + France and Japan, 2018a

Type of service ICAO total Domestic International United States Domestic International China + HK, Macau United Arab Emir. United Kingdom Germany Rep. of Korea Japan France

Passengers carriedb (millions) 4322 2558 1764 889.0 778.3c 236.2c 611.4

Passenger-km performed (millions) 8,257,635 3,055,799 5,201,856 1,627,875 1,360,537 467,338 1,234,065

Freight tonne-km performed (millions) 230.967 30,315 200,652 42,985 17,120 25,865 37,965

Total revenue tonne-km (millions) 1,004,763 367,691 697,072 192,408 123,381 69,027 149,424

95.5

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6198

39,308

109.8 88.2 126.4 70.2

242,054 178,239 197,830 201,955

7970 11,930 9421 4444

31,852 29,157 26,391 25,041

Other Sources: https://www.icao.int/annual-report-2018/Documents/Annual.Report.2018_Air% 20Transport%20Statistics.pdf a Ranked by total tonne-kilometres performed, which includes passengers, freight, with right-hand column including mail. Data for 2019 delayed by Covid virus b World Bank data for 2019 available at: https://data.worldbank.org/indicator/IS.AIR.PSGR c Approximate, from www.airlines.org

The industry also finds it competitively important to closely track another yieldlike metric—passenger revenue per available seat-mile (PRASM). Passenger trips per day each way (PDEW) would, however, be additionally useful as a measure of demand in an origin to destination (O-D) market.19 Carriers will further manage revenues through use of price discrimination features (see Chap. 1) or “fences,” which are barriers that make discounted fares available only to price-sensitive passengers. Such barriers include advance purchase requirements and restrictions, ticket refundability limitations and change fees, weekend stay conditions, and passenger loyalty programs. As such, in the determination of profits, yield is usually more important than the actual passenger fares charged. But yield also tends to vary widely over time from one route to another and from one airline to another because of differences in average sector length flown, geographic territory covered, currency fluctuations, and other factors. Yield is thus a price index rather than a price, and it is sensitive to changes in the composition of traffic. As an index, it does not directly reflect demand because it does not reference the variation of quantity along with a variation of price; it is instead a derived statistic.

70 Table 2.3 Comparative yields (per rpm) and realized load percentages, selected sample of major airlines, 2000, 2010, and 2019

2

Alaska American Delta JetBlue Southwest United

Yield (cents) 2000 2010 13.50 12.75 14.06 13.36 13.86 14.11 10.12 12.07 12.95 14.72 13.30 14.37

2019 14.45 17.41 17.79 14.52 15.82 16.55

Realized LF% 2000 2010 69.2 83.3 72.4 81.9 72.9 83.0 73.2 82.4 70.5 79.3 72.3 83.8

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Source: Company reports

It is also important to know how much of a system’s total potential capacity for carriage is being used at any given time. Capacity would be determined by multiplying the number of seats by the distances flown. Load factors (LF) are a way of expressing the amount of potential capacity that is being sold. For most airlines on most routes, passenger load factors, taken as a percentage of total seats available, would generally have to average above 60% for the flight to be profitable (Table 2.3). For a whole system of routes, such load factors could also be arithmetically expressed in terms of available seat-miles (ASM) (i.e., the number of available seats times the number of miles flown on designated routes). In other words, LF ¼ RPM/ASM. Again, a similar measure for cargo operations would be the weight load factor— ton-kilometers sold as a percentage of available ton-kilometers. Unit costs, unit revenues (yield), and load factors—all of which will immediately reflect competitive conditions on a local, if not a global basis—are the principal determinants of profits. Projected yields on routes are usually used to calculate breakeven load factors, although an airline might still find a route to be profitable if its low yield is in practice offset by a relatively high load factor. However, it is usually not practical to regularly raise load factors above 85% without the risk of turning away (spilling) too much demand to other flights and other carriers.20 As compared to their competitors, efficient carriers will by definition transport more passengers per employee, be profitable at lower load factors, and also find that increasing the load factor percentage by much beyond 80% is counterproductive. All of these aforementioned elements are then used to arrive at a basic airline profit equation which takes revenues and subtracts operating expenses as follows: Operating Profit ¼ (RPM x Yield) – (ASM x Unit Cost) The implication is that high yield is not desirable if the average load factor is too low and that a high average load factor may be the result of selling too many seats at relatively low fares. Along with yield management (basically inventory control), airlines also increasingly employ mathematically sophisticated dynamic fleet management strategies, which enable capacity (i.e., the type of aircraft) to be quickly adjusted to demand so as to maximize load factors and to minimize spill either on a route or network basis.

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These goals will sometimes lead to antitrust complaints about predation, which includes attempts to gain market share by lowering prices to below costs.21 An important macroeconomic constraint in fleet management, however, is that as of 2020 there were globally around 22,500 planes—many rather fuel-inefficient and ready for retirement—and only around 1000 new ones built each year. In times of economic expansion, the cost of implementing fleet management strategies through buying or leasing will, of course, rise accordingly. Other often-used terms in the industry are fairly obvious in meaning. Point-topoint (or city pairing) services are those with dedicated flights directly serving origin and destination (O&D) markets. Round-robin (triangular) flights fly in one direction, first to one point, then another, and finally back to the origin. Hubs are the centers of the hub-and-spoke route networks that airlines operate out of a few important regional cities—e.g., United uses Chicago and San Francisco as hubs, American uses Dallas-Ft. Worth, Charlotte, and Washington, D.C, and Delta, Atlanta. The hubs generate above average pre-tax profit margins: American’s hubs combined showed margins at 13.1% versus 7.5% for the airline overall. Fare class categories are referred to as “buckets.” And through code-sharing arrangements flights on one line use the same airline code-designation as that of another to feed passengers into the other line’s routes. A domestically based line might, for example, share its code with an international line to the presumed benefit of both.

2.2.3

Marketing Features

Airlines can largely control supply (or output as measured by ton-kilometers or seatmiles produced) but can only influence, not control, demand. Marketing is thus a key tool in attempting to align supply and demand as closely as possible against a backdrop that usually includes fierce competition, high financial leverage and pricing instability, sharp economic cyclicity, rapid technological evolution, and dynamic feedback effects from even small changes in supply and demand on each other. Indeed, even the types of aircraft flown reflect an airline’s strategic marketing viewpoints.22 Airlines must fight their relentless battles on many different fields and at many different levels: market-by-market, price-by-price, and sometimes even down to flight-by-flight. In so doing they must protect brand image and maintain good relations with their primary customer and local-community constituencies, all while minimizing costs. Marketing efforts are implemented through advertising campaigns, reservation systems, frequent-flyer programs, travel agencies, yield management/price discrimination strategies (that could conceivably include selling spare off-peak capacity en bloc to charter or tour market operators), and clustered alliances between domestic and foreign carriers (e.g., Star Alliance, oneworld, and SkyTeam).23 Such codesharing alliances (expanded in the 1990s) increase each airline’s network spread,

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marketing power, and geographical reach with little extra cost and help the top twenty airlines in the world to command more than 70% of total traffic as measured by passenger-kilometers. Yet, even so, there is not yet a single global airline. Advertising and Reservation Systems To succeed over the long run, airlines need to be sharp on many fronts: equipment and fuel purchasing, bidding for routes, labor and government relations, safety maintenance procedures, and flight scheduling. All other things being equal, however, none of these things matters unless customers can be convinced to fly the same route on one line instead of another. Given the competitive-monopolistic nature of most (but not all) route operations, advertising plays a frontline role used both offensively and defensively. Many airlines will in the normal course of business have to allocate at least 2% of revenues toward advertising; however, they will need to spend much more if launching a new service, entering a new market, or trying to gain share against entrenched competitors. Economists call this measure of advertising to revenues the advertising intensity ratio. More formally, it can be expressed as: advertising intensity ¼ (advertising expenditure)/(sales revenue) ¼ kA/ (P x Q) ¼ εa/εp, where A is advertising expenditure, k is a constant, P is price, Q is quantity, εp is the price elasticity of demand, and εa is the advertising elasticity of demand. The notions of elasticity here are similar in concept to those discussed in Sect. 1.3 (Primary principles) and below in Sect. 2.3 (Economic characteristics).24 Because a reservation system is one of the first things that a prospective passenger comes into contact with, the reservation system is now as much a powerful advertising and marketing medium as it is a data bank. American Airlines most visibly demonstrated this through shrewd use of its SABRE reservation system (versus United’s APOLLO), which, in the 1980s, notably boosted share of market through the simple expedient of listing American’s scheduled flights ahead of competing flights on every reservation screen.25 Modern reservation systems can sift data banks of mind-boggling size and complexity as they keep constant track of billions of pieces of information— everything from flight schedules, passenger names, and seat assignments to fares that change almost by the minute (and that are funneled through the Airline Tariff Publishing Co. [ATPCO], a clearinghouse for all airlines’ fares that is owned jointly and funded by thirty U. S. and foreign carriers). But such systems can do much more when used to improve predictions of passenger bookings and price and departure-time sensitivities. Airlines have come to depend on these systems to manage the yield that they derive from every flight. In the post-1978 deregulated environment, yield management has become an essential price-setting tool without which most airlines would likely be perennially unprofitable. Yield-management (segmentation) strategies are what make it possible for carriers to earn more by selling 100 seats at 100 different prices than all seats at the same price.26 By some estimates business-class and first-class passengers respectively

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produce five and ten times the profits of economy/coach passengers. And for the large carriers, roughly 15% of flyers are estimated to generate 45% of revenue. Because most business travelers—accounting for around half the customer base of major U.S. carriers—usually care more about convenient departure times than about ticket prices and they also book closer to departure time than leisure travelers, airlines can maximize yield based on forecasted booking patterns. Such patterns run pretty close to those formed for the same day of the week and time of the year as in prior years and allow operators to engage price discrimination strategies (as described in Chap. 1) to the utmost.27 In other words, prices can be set just high enough to fill a flight with a maximum number of high-paying passengers. Frequent-Flyer (Loyalty) Programs These major marketing tools, along with the advent of sophisticated reservation systems, came into prominence in the early 1980s. Frequent flyers, those making more than ten trips a year, are worthy customers who account for only 8% of passengers but 45% of trips flown. In offering free flights to passengers, the operators may be arguably providing a special type of quantity discount to their best customers. But in the process, they also hope to build brand loyalty and (as in Chap. 1) to shift the demand curve to the right and make it more price-inelastic (i.e., vertical). The programs have succeeded to the extent that people have been known to fly far out of the way and to spend much more time in transit than necessary just to qualify for additional mileage credits. This loyalty aspect has financial impact because it costs far more in marketing expenditures to attract new customers than to retain existing ones.28 It would initially seem that the cumulative cost to the industry of revenues foregone has been enormous—an estimated 8% to 10% of revenue-passenger miles are being provided free of charge to travelers and the number of unredeemed miles is estimated at around 10 trillion. Yet because many of these miles will ultimately expire unclaimed, the true liability is thus much below the undiscounted face value. In fact, frequent-flyer programs have actually evolved into a very good and relatively non-cyclical business because of the numerous ways that billions of dollars of revenues may now be generated by selling miles (at between 1.5 and 2.5 cents per) to credit card issuers, hotel chains, charities, and others who use them in turn to attract and retain their own clients. Air carriers thereby collect cash years in advance of mileage redemptions and incur little extra expense if and when such redemptions occur: A frequent-flyer ticket may be worth several hundred dollars to a passenger yet the airline’s marginal cost of giving away an otherwise empty seat might be no more than $25 per domestic round trip (which covers the extra cost of ticketing, fuel, and food).29 Carriers now increasingly also tie rewards to dollars spent rather than miles traveled and have begun to auction various perks such as late seating upgrades.30 The result is that loyalty programs have created a distinct and financially significant business that goes far beyond that of moving people and cargo. By selling miles (at estimated margins of ~50%+) to large banks and companies such as car

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rental firms and hotel chains, the programs can contribute up to half of an airline’s profits! 31 Travel Agencies With the implementation of yield management practices and deregulation, passengers in the 1980s began to face a vast array of ever-changing prices and scheduling choices. Travel agencies, long functioning both as an indirect marketing arm of the airlines (and the other modal carriers) and as product and service rationalizers, helped to turn chaos into order. The number of agencies in the United States more than doubled to 27,000 between 1975 and 1995, a period that included a large increase in demand related to airline deregulation and the Civil Aeronautics Board’s (CAB) lifting of restrictions on travel agency commissions. Travel agencies are a primary point of contact between tourists and providers of tourism services and, because of their significantly lower information search costs, have a comparative advantage relative to tourists. The great volume of business transacted through agencies should not be surprising in view of the long history of development between airlines and these independently owned distributors who, in a plan devised by the Air Traffic Conference (ATC) of 1945, were originally required to be officially accredited. However, throughout the postwar period leading up to the early 1980s, the travel agency business was inherently fraught with various potential or actual conflicts of interest that did not begin to be addressed until the CAB voted in 1980 to eliminate fixed commissions. After that, relations between agencies and airlines were never quite as cozy, with United and then other carriers in 1997 reducing their commission rates from 10% to 8% (and then to 5% in 1999), and with commission caps being placed on both domestic and international flights. In contrast, cruise package commissions can range as high as 15%.32 Although air carriers still derive perhaps 40% of their bookings through tickets sold by traditional travel agents, the agencies are seeing their roles diminished through a disintermediation effect as price-comparison information and discounts have become available on Internet meta-search sites (e.g., TripAdvisor, Booking Holdings aka Priceline, Priceline-owned Kayak, and Hipmunk) and other sources.33 Carriers have also become less dependent on agents as they have themselves employed electronic ticketing technology and direct marketing campaigns tied to frequent-flyer programs. Meanwhile, online travel discounters such as Expedia and Travelocity have gained traction in facilitating corporate travel and wholesale packaging of both airline seats and hotel rooms. Agencies might also be affiliated with or act as passenger consolidators who book the seats and inclusive tour (IT) packages for charter airlines at fares below those of scheduled flights on similar routes. Even with their low fare schedules, charters can be profitable because unit costs are well below those at scheduled airlines. Charter flights have high load factors; fly equipment more hours per day (i.e., more rotations or round-trips); use secondary airports at off hours; have tight seating configurations, use fewer cabin attendants; offer fewer in-flight amenities; have significantly lower general and administrative costs; subcontract out baggage handling; have little or no

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Table 2.4 U.S travel agency and tour operator industry number of establishments, total receipts, payrolls, and employees, 2007, 2012, 2017 Payroll No. of Receipts (annual) Estabs ($1000) ($1000) Travel agencies (NAICS 561510) 2017 15,726 30,407,244 6,163,150 2012 13,458 13,731,899 3,933,267 2007 15,804 17,289,135 6,377,269 Tour operators (NAICS 561520 2017 2936 10,489,987 1,567,752 2012 2786 6,372,644 1,022,782 2007 2993 4,396,677 1,193,824

Employees (paid)

Receipts per Employ ($)

Payroll as % of receipts

96,008 94,611 121,694

316,716 145,141 142,071

20.27 28.64 36.89

31,378 25,721 32,125

334,310 247,760 136,862

14.95 19.04 36.89

Source: U.S. Economics Census, 2012, Accommodation and Food Services, U.S. Census Bureau, Available at: http://www.census.gov/econ/susb/index.html on U.S. all industries selection. Data for years prior to 2017 may not be fully comparable because of classification changes and revisions https://www.census.gov/data/tables/2017/econ/susb/2017-susb-annual.html

responsibility for connecting passengers; and save on ticketing, sales, promotions, fixed station operations, and reservation systems. As seen in Table 2.4 (similar to Table 4.4), both the number of people emplyed by travel agencies and tour operators and the number of establishments has declined since 2007. But with receipts per employee rising and payroll as a percent of receipts relatively stable or falling, agencies and tour operators have generally become more efficient. For charter companies, commissions that are paid to travel and tour operators (some of which are owned by the same or closely related entities) are minimal, as are selling and promotion costs that might at most involve negotiations with a few holiday packagers and buyers of charter capacity. Best of all, though, is that unlike the situation with scheduled services in which costs per flight are largely incurred before actual revenues are known (or received), charter operators basically lock in revenues early on through far-in-advance bookings and then have considerable flexibility to accordingly adjust costs so as to ensure a profit. Agencies remain an important link to the carriers in that they create value to travelers in customizing vacation tours and developing fly/drive/cruise packages, often in conjunction with charter airline operators. Agencies are also still relatively more important in arranging international as compared to domestic trips. But it seems inevitable that agency profits will grow more slowly, if at all, and that a wave of consolidation into a few large national and international agencies will not soon be ending.

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Airport Management

Airports of any size are essential elements of the air-transportation system that provide infrastructure that most of the time enables passengers, baggage, and freight to be readily transferred. And major airports have evolved into mini-cities, with the attendant operating procedures and problems that all big cities face. Traffic control, security and fire protection, shopping, restaurant, lodging, parking, trash collection, and fueling are among the many functions performed: All functions have an environmental as well as economic impact on the surrounding region. In a major hub like Atlanta, for instance, more than a thousand flights a day with around 128 planes landing every hour on five parallel runways are operated. Airports are, in brief, the nodes of a physical Internet—energized by global considerations of time and cost rather than space—through which one-third of all the goods traded in the world ($3.8 trillion in 2019) travels via airfreight.34 As such, their geographical and financial destinies are deeply entwined with those of the nearby cities that they serve and sometimes spawn: The positive effects on regional economic development are usually significant.35 Because of these characteristics, airports are operated and financed through many different private and public ownership and management configurations. In the United States, which has the largest and most extensive aviation system, there are more than 3000 national system airports that qualify for federal assistance, 400 primary airports, and 2700 general aviation facilities. Whereas airports in most other countries are owned and operated by national governments, commercial airports in the U.S. are publicly owned by a municipality or public agency and are usually financed by issuance of tax-exempt general airport revenue bonds (GARBs) supported by a varying mix of aviation revenues, user-specific taxes, and passenger facility charges (PFC). The various fees paid by airlines would typically account for 40% to 60% of total airport revenues. On an operational basis, revenues are usually categorized as either aeronautical (i.e., fees for passenger arrivals, landing, aircraft parking, etc.) or non-aeronautical (i.e., terminal concessions, rents, shopping, car parking, etc.). Landing and passenger fees are overall by far the most important sources within the first category and concessions and rents are the most important in the second.36 A 2015 ACI Airport Economics Survey covering more than 652 airports carrying around 70% of the world’s passenger traffic, for instance, found that charges as a percent of total revenues of US$130.9 billion could be categorized as: Passengers 42% Landing 21 Terminal rentals 12 Ground handling 4 Other 13 Source: Airport World, April 2015 available at: http://issuu.com/airportworldmagazine/docs/aw12015

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Meanwhile, total operating costs amounted to US$106.5 billion (operating 62%/ capital 38%), with the distribution of non-aeronautical income being 27% from retail concessions, 20% from car parking, and 18% from real estate income or rent. Another more pragmatic categorization, however, breaks revenues into three main opportunities: aviation services for airlines: retailing for passengers, and realestate. The steadiness of retail and real-estate revenues will often offset the volatility from aviation service income. Among the factors that most affect the level and structure of costs and revenues, but over which airport managers have the least control, are the volume and nature of traffic. These elements, in turn, depend on location (i.e., mountains, plains, usual weather conditions, etc.), environmental restrictions (i.e., night-flight and noise limitations); peak-to-trough traffic differentials if the facility is a hub; and the mix of international versus domestic passenger loads. Domestic traffic, of course, does not require additional space for customs and immigration and for the larger number of bags usually carried by international passengers.37 In 2019, the world’s top twenty-five busiest airports handled more than 50% of global traffic. Three important trends in airport management have become evident: commercialization, privatization, and globalization. Each of these trends has been driven by traffic growth and the ongoing needs for large-scale capital investments.38 Commercialization is a means of capturing additional revenues from the passengers and freight that pass through an airport’s facilities. By providing convenient shopping, maintenance, and other services to airlines and their customers, an airport is also able to build a brand that can be used to build share of market and be extended to other managed or owned airports in other cities or other countries. Such standardization leads to globalization from which administrative and financing as well as operating costs can be reduced on a per unit basis. Training of personnel, bulk buying of insurance, joint vehicle purchases, and centralized accounting may all be consolidated to achieve cost savings; economic risk is meanwhile reduced by diversification to other country or regional environments where business cycle and political conditions may be different and offsetting. In addition, development of other local business enterprises is supported by such efforts and airports also have an incentive to compete for carriers, luring them with special discounted fee arrangements (that might include lower taxes and reduced landing fees, servicing, and parking charges).39 Yet, even so, around 67% of the world’s airports operated at a net loss, according to a 2013 Airports Council International report. These losses are primarily concentrated in the 80% of airports handling less than one million passengers a year: Size and traffic flows and geography clearly matter. Still, globalization often further leads to airport privatizations of which there are five basic types: issuance of shares to the public (i.e., flotations), trade-sales; concessions; management contracts; and project financings. With issuance of public shares, the original owner, usually a governmental body, relinquishes most if not all operating control to managers selected by the new private owners. This differs considerably from the situation in a so-called trade-sale in which some or all of an

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airport’s assets are sold to a trade partner or consortium of strategic investors with operational as well as financial capabilities. Concession purchases, in contrast, provide a lease to operate airport facilities over a long period, say twenty to thirty years, and require payment of a large initial fee followed by annual fees based on a percentage of airport revenues and/or profits. Such arrangements are, in effect, long term management contracts, the least radical and perhaps most common of the privatization options. Project finance privatizations that would be used to build or redevelop existing facilities will also often play important roles in airport management planning. Although there might not be any upfront payment requirements in a project finance deal structure, the builder-operator would usually bear all costs and retain most, if not all, revenues for an extended period of time. Such arrangements are generically denoted as build, operate, and transfer (BOT) deals, although several variants exist.40 The attraction to private investors is that competition from other airports and other modes of transportation is usually limited, there are significant barriers to entry, and airports have potential to benefit from long-term growth of air travel.

2.3 2.3.1

Economic Characteristics Macroeconomic Sensitivities

Derived demand for travel services depends on factors such as the purpose for which a trip is made, the distance traveled, and the cost of the service. Implicit are the value of time and the cost of opportunities foregone. Business travelers would, for example, presumably value their time more highly than leisure travelers and would therefore be more likely to travel by air, the usually faster means of transportation. A traveler’s valuation of time savings would also appear to be roughly correlated with income.41 All other things being equal, rising real incomes ought to thus increase demand for the most rapid means of transportation, which in most cases would be by air. In fact, studies suggest that the income elasticity of demand for travel by air (a concept explained in the following section) is usually in the range of 1.5 to 2.5.42 These elasticities also suggests that the fastest modes can justifiably charge significant fare premiums. The number of flights per capita (log scale) as compared to GDP per capita for 2013 are illustrated in Fig. 2.4. Near the origin of the plot are countries such as Egypt, Pakistan, and Brazil, whereas near the upper right end of the curve are countries such as the United States, Canada, England, and France where the annual average is around 2.0. Air-travel demand is always responsive to changes in business cycle conditions, rising easily when the economy is growing and falling when it is not. In fact, great sensitivity to recessionary economic cycles was demonstrated in 2001, when highly profitable business travel declined along with bursting of the technology and telecom

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Fig. 2.4 Flights per capita versus GDP per capita, 2013. Source: IATA/Tourism Economics’ Air Passenger Forecasts, http://www.iata.org/whatwedo/Documents/economics/20yearsForecastGAD2014-Athens-Nov2014-BP.pdf

investment bubble of the late 1990s and also in the much larger and longer recession that began in December 2007. Yet the global pandemic of 2020 caused a far greater collapse of demand than in any of the earlier episodes. Annual global passenger boardings in 2020 fell by 60% from the year before and to numbers (1.795 billion) not seen since the 1980s. Historically, passenger and freight traffic growth has been 1.5 to 2 times the rate of GDP growth (Fig. 2.5). Demand for air transport has, in addition, a significant multiplier effect on the overall economy. Studies by the ICAO (viz., Fischer 2003), for instance, estimated that every $100 produced by civil aviation industries generate another $469 of output in a broad swath of industries that include finance, education, food service, and lodging.

2.3.2

Microeconomic Matters

Cost Categories Airline managements have considerable leeway in the supply of services, whether passenger or cargo, that they offer. And fleet selection and flight scheduling are principal determinants of costs. Fleet selection, for example, is the main component of capital costs as well as fuel burn rates and many maintenance items, while scheduling is a significant determinant of labor-staffing cost structure.

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% change 20 World GDP Constant $ 15

10

5

0 RPMs -5 terrorists attack America -10 80

85

90

95

00

05

10

15

Fig. 2.5 The correlation between percent changes in real World GDP and percent changes in U.S. carrier revenue passenger-miles (RPMs) traveled. By this measure, RPMs broadly suggest an income elasticity of around +0.75)

Airlines have considerably less control over demand. They can advertise and promote and cut fares and offer new frequent-flyer programs. But in view of the industry’s consolidation into just a few mega-carriers, so can their competitors. Because of this, airline managements can have the greatest effects on prospective profitability through their attempts to control costs, about half of which are variable (and dependent on definition). It is thus imperative in deregulated markets to operate with average costs per passenger-mile or ton-kilometer as low as possible. Otherwise, long-run survival becomes an open question. In fact, studies such as those by Straszheim (1969) and White (1979) suggest that—except in marketing and perhaps in terms of the mix of fleet equipment—there is a point beyond which the industry does not tend widely toward significant further cost economies of scale. Airlines nevertheless tend to benefit from what are known as economies of density (i.e., economies of scale along a given route) that appear when passenger traffic through hub airports is aggregated. By establishing hub-and-spoke traffic networks that combine passengers from different origination points, airlines derive important advantages: In filling larger aircraft average cost per seat-mile is lowered, load factors are raised, and profitability is enhanced. The economies of density occur because, as traffic increases, not all input factors (e.g., vehicles or fixed facilities) need be scaled proportionally upward. However, such networks require that more miles be flown. And hub costs are higher than otherwise because passengers making connections increase their use of hub-airport facilities, with arrivals and departures are unevenly scheduled in waves

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of activity (i.e., within narrow windows of time called banks).43 In addition, crews and other personnel remain idle while awaiting arrivals. Also, in economic downturns, removal of even a few flights feeding into hubs may be greatly disruptive, depriving the remaining flights of the marginal revenue generated by the boarding of perhaps only a couple of extra connecting passengers on whom profits hinge. Hubs, therefore, may not always necessarily lower total operating costs or boost profitability, although they do tend to keep ticket prices high.44 With sufficiently high traffic, direct service between two cities may sometimes be less expensive to operate than a hub-and-spoke arrangement. From a larger systemic point of view, though, it is also important to recognize that hub-and-spoke systems exhibit behavior consistent with the Law of Connectivity, the basis of the Internet’s exponential growth.45 This law states that the utility (value) of a network rises by at least the number of users (or nodes) squared. More formally, the relationship can be stated as: V ¼ aN2 + bN + c, where V is the value, N is the number of nodes, and the other terms are constants. In network industries, including those of software development, banking, broadcasting, cable, and airlines, the huge upfront sunk cost (i.e., cost that cannot be recovered) of developing the first unit of a product or service “together with almost negligible marginal cost implies that the average cost function declines sharply” as the number of product or service units sold increases. “This means that a competitive equilibrium does not exist and that markets of this type will often be characterized by dominant leaders that capture most of the market.”46 Once an airline is able to fly twice the number of departures out of a hub as compared to its next largest competitor, it is usually able to win the majority of the highest-paying business travelers. There is, nevertheless, is a wide variation of unit costs among airlines, especially those of the international foreign-flag carriers, which are also often established to serve social and political purposes.47 In the early 1990s, for example, Lufthansa and Swiss Air had unit costs (as shown in Fig. 2.6) twice that of Singapore Airlines and Quantas, both of which predominantly fly what are known as “long, thin” routes.48 When defined by the degree to which these costs can be affected by management decisions, costs can be categorized into three groups. In the first category are costs such as those for fuel, prevailing wages, landing, navigation, and other user fees and taxes. In the second category are costs over which an airline has somewhat greater, but limited, control. Costs of this type are to a degree determined by the geographic location and predominant conditions (mountainous, flat, foggy, sunny, snowy, etc.) at the carrier’s home base; by the average length of routes (stages or sectors, i.e., the distance between two airports) flown; by bilateral agreements reached with other lines; and by decisions concerning the class of aircraft to be used and the frequency of schedules on which the equipment is to be operated. In the third category, however, are the costs over which management has potentially the greatest amount of control. Such costs might include those for marketing, financial leverage, aircraft ownership, and acquisitions and expansions.

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Fig. 2.6 Unit operating costs as a function of stage length. Source: Comité des Sages (1994). Expanding Horizons, Civil Aviation in Europe: An Action Programme for the Future. Brussels: European Commission. (See also, Hanlon 1996, p. 20, 1999 ed., p. 23) http://aei.pitt.edu/8690/1/ 8690.pdf

CASM (cents) 14 13

Delta

12

American

United

Southwest 11

Hawaiian short-haul

10

JetBlue Alaskan

9 8

Allegiant Spirit

7 0

400

800

1,200

1,600

2,000

Stage-length (miles)

Fig. 2.7 Average Stage-Length vs. Cost per Available Seat-Mile, Major U.S. Carriers, mainline operations, 2016. Note that Hawaiian Airlines dot shows only short-haul for islands, as long-haul stage length is 3000+ miles. Source: Company reports

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Table 2.5 Operating cost per average ton-kilometer (ATK) by item, 1998, 2003, and 2011 estimated for IATA International Scheduled Servicesa

Direct operating costs (DOC) Cockpit crew Fuel and oil Flight equipment, insurance, depreciation, rentals Maintenance and overhaul Airport (landing) and En route charges Total DOC Indirect Operating Costs (IOC) Station and ground costs Cabin crew and passenger service Ticketing, sales, and promotion General and administrative Total IOC Total DOC and IOC

US cents 1998

% of total 1998

% of total 2003

% of total 2011

2.8 4.9 5.0

7.2% 12.5 12.7

6.2% 16.5 14.0

4.9% 30.0 15.0

3.9 3.9 20.5

10.0 10.0 52.4%

10.4 9.3 56.4%

10.5 9.2 69.6%

4.7 5.3 6.4 2.2 18.6 39.1

12.0 13.6 16.4 5.6 47.6% 100.0%

9.8 12.8 14.5 6.5 43.6% 100.0%

8.5 7.3 9.5 5.1 30.4% 100.0%

Sources: https://www.iata.org/contentassets/a686ff624550453e8bf0c9b3f7f0ab26/wats-2019mediakit.pdf, IATA Annual Report, 1999, IATA Airline Economic Results and Prospects 2004. See also http://www.iata.org/whatwedo/Documents/economics/IATA-Economic-Performance-ofthe-Industry-mid-year-2015-report.pdf a Estimated from industry sources and company reports

The comparative average cost per available seat-miles versus stage-lengths is displayed in Fig. 2.7. As is apparent from the long history of airline-business failures, cumulative errors in judgment on short run escapable variable costs can be just as debilitating as errors in judgment on fixed costs, which do not vary over the short run if a particular flight or series of flights were to be canceled. The most important and largely inescapable influence on variable cost, however, is the price of fuel, which traces a long run uptrend that is often laced by unpredictably extreme short run fluctuations. Such fluctuations heighten the potential for tactical and strategic errors to be made and greatly disrupt the industry’s presumed cost allocation structure. The immediate reduction of profitability that occurs when fuel prices rise rapidly cannot be readily mitigated through hedging and surcharges on fares: Hedging is expensive (and sometimes ineffective and/or incorrectly placed) and extensive application of surcharges is counterproductive because it reduces demand. More specifically, for international scheduled services, Table 2.5 shows that as of 2011 spending for fuel and oil (see also Fig. 1.24) accounted for around 30% of total costs and amounted to around $200 billion a year.49 With fuel, passenger service, en route, and landing costs being primarily variable or semi-variable, perhaps as much

84 Fig. 2.8 Costs as a percent total operating expenses, selected major cost categories for major airlines, 1971–2019. Source: ATA, A4A. DOT

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% Labor

40 30 20

Fuel

10 0 75

85

95

05

15

as 55% of all costs (exclusive of network and/or opportunity costs) may be considered as being of a variable nature.60 This basic cost-allocation structure remains even though every years’ data will obviously differ. Trends in major costs (fuel and labor) as a percentage of total operating expenses for Airlines for America (A4A)— formerly known as Air Transport Association of America (ATA)—member airline are shown in Fig. 2.8. Productivity Factors In analyzing the determinants of profitability there are, in addition, a few that are not quite as obvious as the price of fuel and wages. With around half of transportation workers unionized and covered by collective bargaining agreements (CBAs), unions play an important role in determining productivity and profitability. In periods when industry profits are relatively high demands for wage premiums normally rise, whereas in periods of losses and bankruptcies, contract concessions will likely be made. And because workers such as mechanics, pilots, and flight attendants cannot be replaced quickly or easily, unions gain considerable bargaining power via their potential threats of strikes or “slowdowns.” Although different representative unions will have dissimilar and divergent agendas, demands, and contract durations, work-rule and wage concessions granted to one group will be often used to obtain similar benefits when the next round of contract negotiations come due. The size of aircraft and their cruising speed and range also significantly affect the airline’s average hourly productivity—with payload times average speed determining the average output per hour.51 Generally, the larger the aircraft, the less it will cost to operate per unit of output, whether it be a passenger-mile or a ton-kilometer. However, the higher trip costs of flying large aircraft can potentially offset any lower average cost per passenger-mile or ton-kilometer produced. Any analysis of productivity would also not be complete without considering the effect of aircraft speed, which is also a measure of output per hour. A faster plane will by definition be able to transport more passengers or tons per hour than a slower one even though landing fees, flight crew, and other costs might be almost the same

2.3 Economic Characteristics Fig. 2.9 Hourly productivity versus stage length. Source: Adapted from Holloway (1997, p. 90)

85 ATKs/hour declining payload

rising average speed

Stage length

for each aircraft. In this regard, additional cost considerations such as engine performance (fuel burn rates) at different average flight speeds, stage length—the typical length of route between airports over which a particular aircraft is flown—as well as frequency of service and airspace overflight fees will come into play.52 Of these factors, stage length has the greatest impact on relative productivity. Indeed, it was the matching of stage-length to airport and airplane size that led to development of hub-and-spoke networks (such as American’s Dallas-Ft. Worth hub). Airlines feed shorter stage-length flights from smaller cities using smaller planes into their hubs and then fly the longer stage-length (and more filled) flights from such hubs.53 An idealized representation of potential hourly productivity in terms of available tonne-kilometers (ATKs/hour as a function of payload capacity and block speed as related to stage length) is shown in Fig. 2.9. ATK is a measure of an airline’s total capacity for lifting both passengers and cargo and is derived by multiplying capacity in tonnes by kilometers flown. For an airline thinking of buying new equipment or changing that already being used on a particular route, potential market demand growth is always a key consideration. However, the range capability of the aircraft being used (or to be used) on that route (and also the aircraft ownership hourly lease rate ascribed to the route) will ultimately affect the buy or change decision. Obviously, the less time spent on the ground loading and unloading relative to distance covered, the greater the productivity per hour. Productivity should also be further measured in terms of the many costs associated with ticket sales, reservations, and baggage handling, which are related to the number of passengers hauled, rather than distances covered. For example, because the unit costs of ticketing and baggage handling are the same no matter what the distance flown, on a total cost per flight basis, the carrier would be better off hauling fewer passengers on longer flights than more passengers on shorter ones. Last but not least are the productivity considerations of fleet size.54 The larger the fleet, generally, the greater the efficiency and flexibility in the scheduling of crews and aircraft and the greater the likelihood that the type of aircraft and size of crew

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Table 2.6 Air transportation multifactor productivity, average annual percent change, 1972–2001 1972–2001 1990–2000

Output per hour 2.4 2.4

Output 4.8 4.2

Hours 2.3 1.8

Multifactor productivity 2.0 1.9

Source: Duke and Torres (2005)

will be properly matched to the needs of a particular market. Although most areas of airline operations have constant returns to scale (i.e., they provide no important cost economies as size increases), fleets that are standardized using the same type of aircraft will typically have lower maintenance and training costs for mechanics and crews and higher productivity than if the fleet were a mongrel lot.55 Since the 1970s, air carriers have encountered great business turbulence—everything from labor strikes, bankruptcies, bloated pension costs, a global pandemic, and a steep rise in the cost of fuel. Yet, as indicated in Table 2.6, the industry has been able to survive in large part because of above average multifactor (i.e., labor and capital) productivity gains of 2.0% as compared with a 0.7% average annual gain for the entire private business sector. Adoption of new technology (e.g., self-serve kiosks, marketing through social media) and the change in equipment ownership structure—with a much higher percentage of the fleet leased rather than owned— have at least partially alleviated the cost pressures arising elsewhere. Carriers have thus to a large extent become “virtual” service packagers of services and equipment owned by others.56 At the Margin At its core, microeconomic analysis describes what happens to costs and prices when an extra unit is bought or sold at the margin. Economists will look for responses to small changes in terms of what are known as price or income elasticities. For airlines and also other travel-related segments such as hotels and theme parks, these elasticities practically become defining characteristics of the underlying businesses. Once the air network or hotel or theme park is up and running, it costs next to nothing to allow an extra traveler onto the flight or a guest into the hotel or theme park. Estimates of elasticities in relation to changes in prices and incomes are thus central not only to the care and feeding of economists on the whole but also to an understanding of how the travel industries intrinsically operate. As noted in the previous chapter, the basic idea is to estimate how much a change of income or a change in price—either up or down—will change demand for air travel. In the case of income, this can be stated as: income elasticity ¼ εi ¼ %

change in quantity demanded : % change in income

Therefore, if a 4% increase in personal income results in an 8% increase in demand for airline tickets, the elasticity is +2.0; for every 1% increase in income, the industry should expect to see a 2% rise in ticket sales. The same type of calculation for price elasticity, εp, was earlier shown in Sect. 1.3. With prices, a negative elasticity would be expected because price increases are normally likely to lower demand (and vice versa).

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What are known as cross-elasticities of demand are also important considerations in travel industry economics. Assuming all else remains constant, such crosselasticities measure the change in demand for one service or product when the price of another substitutable or complementary service or product changes. A cross-elasticity greater than zero—meaning that a price rise in one mode of travel causes the other mode’s traffic to rise—indicates that the modes are substitutes for each other (e.g., car rentals and taxis). Conversely, a negative cross elasticity— wherein a rise in the price of one mode causes the other mode’s traffic to decline— indicates that the modes are complementary (e.g., air travel and airport buses).57 In all, the main determinants of travel income or price elasticity (Button 2010, pp. 84–96) can be stated as the following: • Competition, where the more competition, the greater the demand elasticity • Distance, where long-haul flights tend to be more demand-elastic than those for the short haul • Business versus pleasure (i.e., trip purpose), where business flyers tend to be less responsive to price changes than are individuals on personal trips or vacations • Time, where the more time available for a trip to be planned in advance, the greater the elasticity • Absolute level of price change in which a 10% increase on a $5 fare has a different elasticity than the same percentage increase on a $500 fare • Income levels, where those with higher incomes have more alternatives to choose from • Changes in tastes and in prices of alternative modes and transport services, for example travel by air versus by car Unfortunately, the theory is easier to state than the practice is to apply because, when making estimates, many other variables will come into play and the relevant economic data on incomes or prices may not be so obviously isolated. Is the relevant income that of the nation, of a region, or of a city? For estimates of demand for a single route out of a small Midwestern city to another small city the choice may be relatively unambiguous. For an estimate of routes out of New York, Los Angeles, or London or Atlanta (major transfer hubs), the possible income-data set choices are overwhelming. Moreover, it is usually not clear which of the myriad and constantly changing prices are the ones that should be used as a basis for estimates of elasticity. Per capita income series are also imperfect because income is never evenly distributed over populations and traveler age profiles might not be taken into account. Moreover, the elasticities for business travelers are surely different than those for leisure travelers, even when both are of the same age, live in the same cities, and earn the same incomes. Problems in the estimation of price elasticities also abound, in part, because there are so many different fares for the same routes on the same days. In addition, people react differently to price changes over the long run than over the short run; over time they can altogether adjust by moving their homes or business locations. The moral of the story is that both income and price elasticity estimates, whether made in terms of airlines or any other travel-related industry segments, are, in and of

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Table 2.7 Demand elasticity estimate ranges for selected modes of transportation a Mode Air passenger Leisure travel Business travel Mixed or unknown Intercity rail Business travel Mixed travel Urban transit

Automobile usage United States Australia

Time series

Cross-section

Other

0.40–1.92 0.65 0.82–1.81

1.52 1.15 0.76–4.51

1.40–4.60 0.9 0.53–1.90

0.67–1.00 0.37–1.54

0.70 1.4

0.15 0.12–1.50

0.01–1.32 Short run

0.05–0.34 Long run

0.06–0.70 Unspecified

0.23 0.09–0.24

0.28 0.22–0.31

0.13–0.45 0.22–0.34

Source: Oum, Waters, and Yong (1992) a All elasticity estimates are in negative values

themselves, imprecise and changeable over time. Most income elasticity estimates for airlines suggest that such elasticities generally range between 1.2 and 2.3, with short-haul leisure being near the upper end of the range and long-haul business near the lower end. As for price elasticities, it should come as no surprise that business travelers, who generally do not pay for their own travel expenses, are less sensitive to price changes than are leisure travelers, who do mostly pay their own way. As compared to those in the leisure segment, business travelers would thus be expected to have lower price elasticities of demand—especially during economic boom times (the late 1990s or 2005) when business might account for 40% of the flyers but 60% of domestic revenues.58 From the carriers’ standpoint, it will always be understood that once a flight departs, any empty seats can never be sold again. And although it is impossible in most situations to estimate elasticity precisely, it is possible to get a sense of whether a certain class of potential travelers’ demand is elastic or inelastic with respect to prices and/or incomes.59 Generally, long-haul and business flights are less price sensitive than those involving shorter distances—where ground travel options are competitive in terms of time expenditure—and leisure-sector travelers. The estimates are important because proper implementation can make a significant difference in an airline’s (or hotel’s or theme park’s) profitability. Elasticity estimates provide the basis for price-discrimination strategies from which (as shown in Chap. 1) revenues can be maximized by charging different market segments markedly different prices. Comparisons of estimated elasticities for different modes of transportation are shown in Table 2.7. Given that most airlines (and hotels too) operate in structural environments that can be characterized as being either monopolistic competitive or oligopolistic, the

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Fig. 2.10 Unit Cost Changes ranked by aircraft seat count. Source: Delta Airlines, 2017

Fig. 2.11 (a) Monopolistic competition and short-run equilibrium, and (b) classical profit maximization in an oligopoly

standard microeconomic diagrams can be applied as in Fig. 2.10a. As in all such idealized representations, the short-run equilibrium price, P*, is the one at which marginal revenue (MR) equals marginal cost (MC); a rising MC intersects the longrun average cost (LAC) curve at its low and the perceived firm demand schedule is represented by line D. Under the classical model of oligopoly, shown in Fig. 2.11b), maximum industry profit is attained under the assumption that all firms work together toward such maximization and where costs are held constant, as indicated by rectangle P*ABC. The cost effect of congestion—as measured by traffic flow rates (vehicles per unit time), densities (concentrations of vehicles on a length of roadway, runway, or flight path), and average speeds—applicable to the economics of all modes of transportation, is illustrated in Fig. 2.12.60 Obviously, whether in the air or on the ground or at sea, as density approaches a maximum, the flow rate approaches zero. And, over the long run, congestion is likely to continue as a major concern for all parts of the industry, with airports, airlines, and passengers all bearing the costs.

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Cost per passenger-mile

8 MC

6 4 2 AC

0 1

3

5

7

9

11

13

Traffic v olume (passenger-miles)

Fig. 2.12 Congestion: Marginal and average costs per passenger-mile versus traffic volume

As neat and clean as this all seems, though, it is often difficult in practice to make as sharp a distinction between short-run and long-run costs or between fixed and semifixed variable costs as the theory would have us believe is possible: A degree of arbitrariness of definition in an accounting and economic sense is inevitable.61 Also, as relative input factor prices change, it is in fact especially difficult in transport operations to readily substitute one factor input for another. Only over the long run can demand schedules—and therefore long-run marginal revenues—react to developments in travel service technologies used by other modes of transportation.62 Pricing Considerations In the pricing of transportation and travel services, the concept of economic efficiency is paramount. That is because economic efficiency requires that producers make the best use of the available resources: Airlines or hotels that do not set their prices correctly will find, if they price too low, that they incur the costs of congestion shown in the idealized representation of Fig. 2.12. Or, if they price too high, their assets will be underutilized. From the standpoint of economic efficiency, the price charged for any transportation service should under all conditions be equal to the opportunity cost of producing it. Opportunity costs are the costs of foregoing doing something else. In other words, the cost of an action is the value of other opportunities that are not taken. For example, a sales person could decide to make a presentation in Denver, foregoing the possibility of making the same presentation in London. The sales person has foregone the opportunity to make the pitch in London and must view this as a cost, a fact that becomes especially evident if the pitch fails in Denver when it might have succeeded in London. In the case of tourists, the opportunity cost of vacationing in Italy might be foregoing a trip to Spain. The cost becomes more evident if it rains every vacation day in Italy, while the sun shines every day in Spain. As translated into economics terminology, this means that the opportunity cost of an individual making a single trip is the short-run marginal cost, which for purposes of economic efficiency ought to be the price charged for the trip.

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A related concept is that of subsidy-free pricing, which begins with the idea that users of transportation facilities must collectively cover all of the costs of the facilities that they use. Otherwise, someone else is subsidizing the users. The economic efficiency criteria is most helpful in the setting of prices (fees or tolls) for the use of infrastructure (fixed facilities) under congestion (peak-load) conditions, which is when marginal costs rise sharply.63 In the airline business this would apply to takeoff and landing slots at the busiest times of the day.64 Subsidyfree pricing considerations would, however, be mostly used in determining which users or user groups should pay for particular fixed system facilities such as airports.65 Pricing in airlines or other public transportation modes should optimally guide new investments in capital equipment and technology. But more often than not pricing is used as an instrument to pick up share of market, fill empty seats, attract new customers, and achieve a wide variety of additional short and long run objectives. Given that barriers to entry on routes are relatively low and that seat bookings are a highly perishable product, there is ever the temptation to fill seats for any fare that covers the cost of a bag of peanuts and a couple gallons of fuel.66 As a result, airlines tend to sell seats for prices that are far below their long-run costs, some of which may include costs related to environmental damage.67 Two philosophically different but not necessarily exclusive approaches are to either set prices by relating them to cost of service, or, to demand. It all depends on the primary objectives to be met. An airline might use one approach in one market or part of its network and the other elsewhere. As a result, carriers now try to offset the often extreme consumer price sensitivity to ticket price increases by unbundling services and charging extra in their lowest fare brackets for things like checked baggage, pillows, aisle seats, and food.68 Such unbundling of so-called ancillaries will always make it more difficult to compare prices, as incremental fees for checked luggage, ticket changes, or meals vary greatly from one carrier to another.69 U.S. airlines basically now cover their costs via ticket sales and generate profits from baggage, seating preference, reservation-change, cancellation, extra legroom, early boarding, and other fees (earning perhaps $20 per passenger on an average one-way fare of $180).70 For a specific route, the four most important factors that determine prices are • • • •

type of competition, budget or premium; intensity of competition, light or fierce; type of passenger, leisure or business; operating costs, which include terminal rents and landing fees.71

The success of the various pricing strategies will to a great degree depend on how effectively the services that are offered can be segregated (i.e., “fenced”) by various imposed fare rules, conditions, and restrictions so that traffic that is willing and able to pay a high tariff (e.g., on routes serving many business travelers and/or relatively wealthy communities) does not slip into lower tariff categories. For an international carrier, this is expedited by yield management models that might allocate fares on each route into as many as twenty reservation or booking

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100%

Market Share

0%

0%

Frequency Share

100%

Fig. 2.13 Idealized S-curve of market share versus departure frequency share. Source: Belobaba et al. (2009, p. 69. The Global Airline Industry, John Wiley & Sons, Ltd., 2009, p. 69. See also Belobaba and Cheung (2004)

classifications. Given that the marginal cost of carrying an additional passenger is always relatively low, the temptation to fill an empty seat is always high because any extra fare then contributes to at least covering some fixed costs and likely all of the marginal ones as well. Fixed costs will include those related to airport gates and terminal leases along with equipment (aircraft ownership arrangements) and buildings. Average fixed costs are calculated by dividing total fixed costs by output (perhaps measured by RPMs, total daily hours of flying time, or some other metric). Market share—which can be variously measured in terms of number of passengers, seats, or flights between cities—is also always a function of frequency of departures, as frequent departures will tend to capture all passengers wishing to fly during periods when only a single carrier offers a flight. The theoretical tradeoff between market share and frequency share can be depicted as an elongated forwardslanted “S”-curve with market share on the y-axis and frequency share on the x-axis as shown in idealized Fig. 2.13.72 Higher frequency always tends to be associated with higher market shares. Many structurally complex (but nonbinding) tariff guidelines for international routes are set in IATA conferences. The carriers adhere to the guidelines in some, but not necessarily all markets or parts of their networks, with the degree of compliance being a function of specific strategic objectives and competitive conditions. In contrast, low-cost and charter airlines generally operate on a model that differs from the major carriers; they have simple fare policies, they do not transfer passengers between lines, and their pricing is determined independently. Antitrust and Predation Concerns about monopolization and considerations about applicability of antitrust laws to specific markets, routes, and carriers are closely related to the pricing of services. Predation is the term economists would use to describe deliberate pricing below short-run marginal (or average variable) cost—with subsequent rapid return to

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93

monopoly pricing (i.e., recoupment) once the challenger has exited the market or been vanquished. It may be seen in the situation wherein a full-service airline (FSA), the incumbent, significantly decreases prices or changes route capacities or competitive strategies to respectively deter or dissuade another carrier—usually a low-cost carrier (LCC)—from either entering or remaining in a market. In addition to the classic form of pricing below costs, such predatory (anticompetitive) behavior might also include adding to capacity (“capacity dumping”) or setting up a new LCC carrier by the FSA itself. In many countries and many instances, this situation may result in legal, regulative, and/or other retaliatory or punitive actions that are designed with the presumption that such interference is needed to restore fair play and balance. In actuality, however, the underlying economic theory is often questionable, the accounting definitions of marginal or variable costs are elusive and imprecise, application of regulation is arbitrary and capricious, and the time required to process claims through the courts is long and torturous. In part, this is because alleged predators must possess a substantial degree of market power, the boundaries and definitions of which are difficult to pin down. But this is also because operating and marketing barriers in the airline industry include: • network size and breadth; • flight frequency; • access to airport facilities including gates, ticket counters, baggage handling, and take-off and landing slots; • frequent-flyer programs • travel agent commission overrides;73 • brand and reputation. Even so, low-cost carriers have (much to the detriment of the FSAs) been generally able to carve out significant niches in markets all around the world—a fact that in a broader sense starkly calls into question the effectiveness, value of, or need for stringent anticompetitive regulation and enforcement efforts.74 Whatever the restrictions that might be imposed, city pair markets will everywhere tend toward becoming natural monopolies (i.e., the number of carriers in a market will be unaffected by market size). In this, airport presence is the competitive weapon with which such a monopoly is formed.75 After all, this is a risky and complex business for participants of any size. It is often difficult to distinguish predation from normal commercial behavior. Government subsidies (i.e., pricing below cost) for other modes of transportation (e.g., buses, rail, highways) are often present. And this implies that the government itself may be a “predator.” Incumbent FSAs, moreover, have the right (as well as the obligation to shareholders) to maximize profits and to defend their own financial viability. Traffic Forecasting Except perhaps for specific purposes in the course of touring (e.g., a nostalgic train trip), people usually do not directly demand to be transported from one point to another just for the sake of riding in a plane, bus, car, or train. The

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demand is instead for a bundle of transport services that is derived from other needs and objectives such as to engage in business, to vacation, or to visit friends and relatives (VFR). Given the difficulties of estimating the derived demand for intercity business and leisure travel—each of which is driven by different passenger objectives—economists have sought other approaches that might provide a logical basis for forecasting traffic. Time-series (i.e., noncausal) estimation using traffic as the dependent variable and time as the independent one is the approach that most readily comes to mind. As usual, equations of this type can be couched in either linear or exponential forms. In the linear version, traffic (i.e., the anticipated number of passengers carried) increases by a constant absolute amount with each unit of time and is simply traffic ( y) ¼ a + bt, where a and b are constants and t is time. Although increments per period are the same in number, the percentage change declines as time progresses. The comparable exponential form, where b is the growth rate, is. traffic (y) ¼ a(1 + b)t In this situation, it is the percentage change that remains steady, while the traffic per period increases. For example, if traffic on the New York-Baltimore route in 2020 was 200,000 passengers and the average annual expected growth rate is 5%, then the exponential form would predict 2025 traffic as 200,000 X (1.05)5 ¼ 255,256. The basic problem with such simplistic models, however, is the assumption that traffic growth is merely a function of time. As Witt and Witt (1992, p. 7) note, “a great problem with forecasting by extrapolation is that it presupposes that the factors which were the main cause of growth in the past will continue to be the main cause in the future.” Yet many other factors might affect traffic growth, including changes in local industry prospects, demographics, regional incomes and existing number of flights per capita, and potential airport congestion problems. To make sense of all this most economists would then resort to standard regression (i.e., causal) forecasting or other econometric techniques (e.g., GARCH models) that give weight to many different variables, and that also, in effect, estimate factor elasticities. The basic form of one such simple regression equation might be as follows: T ¼ f (F, Y, t) where traffic, T, is the number of passengers on a route taken as a function of average real fares, F; Y is a measure of real personal consumption expenditures per capita and t is the time trend. As usual, many additional variables (including the cost of travel time and even local hotel prices) can be added to this type of model. With all other things being equal, most forecasting models of this kind would probably include at least the following variables (and would also be applicable in studies of other modes of transportation):

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• Population, wherein the higher the number of people resident in a country, the larger the number of trips likely to be taken • Income, which is measured as real per capita income in the originating region affects demand • Own price of service, which is the cost of travel to the destination • Prices of substitutes, which would obviously affect demand Nevertheless, neither types of models are useful when trying to forecast traffic on new routes, for which most, if not all input data do not yet exist. This is an important consideration because the number of unique city pair services has globally risen from 6000 in 1980 to more than 15,000 in 2020. An approach that to a degree solves this problem uses what is known as the gravity model, which was suggested as early as 1885 and tends to be used more outside of the air travel industry. As discussed by Kanafani (1983, p. 165) and by Boyar (1997, p. 84), the gravity model is analogous to the one used in physics to describe the attraction between two objects. In the case of travel, this type of spatialequilibrium model predicts that the number of trips between any two origins and destinations will be distributed according to the formula: tij ¼ α Ai Bj cijσ where tij ¼ the number of trips taken between origin i and destination j. Ai ¼ number of total trips taken from origin i Bj ¼ number of total trips taken to destination j cij ¼ distance between i and j or a measure of cost of transportation between them α and σ ¼ parameters whose values are estimated for each particular city pair The underlying concept in this model is that the number of people moving between cities—the traffic density—be proportional to the sizes of the cities and inversely proportional to the distance between them. Some empirical estimates have found that values of σ are approximately 2.0 (i.e., the same value of σ as found in physics), which suggests “that trips between any pair of localities will increase with the product of the trips generated at those places and decline with the square of the distance between them.”76 In addition to the gravity model, economists have also adapted from physics models based on statistical mechanics (entropy) and electrical systems. However, for large, capital-intensive infrastructure projects, there has been a recent shift of preference toward use of what are known as activity-based approaches to predictions of demand for travel facilities and services.77 All such models may, of course, be applied not only to the study of airlines and their potential demand for aircraft of various sizes and capabilities but also to demand estimation for intercity travel by rail, bus, and private car. To be useful such models must somehow incorporate the fundamental characteristics of transportation service demand, which is derived, tends to fluctuate on daily and seasonal as well as long-term macroeconomic cycles, and is sensitive not only to the fare charged but also to the cost of time over which the transport service is used.78

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Financing and Accounting Issues Financial Features

At first glance, one would think that it should be relatively easy to directly compare the profitability parameters of different airlines. Yet, because of substantially different policies regarding asset depreciation, mix of leased versus owned equipment, and degree of government subsidy (if any), it is difficult to derive an independent, internally consistent estimate of something even as simple as a return on assets for the industry as a whole. Operating (pretax) and net income (after tax) data—compiled by the ATA for U.S. carriers and the ICAO for most of the world’s airlines organized by country of operation—however, provides a useful approximation. Such data for the ATA are illustrated in Fig. 2.2a from which it can be seen that over most of the time since 1938, when operating statistics were first compiled, the domestic industry produced cumulative losses. ICAO data of Fig. 2.13 are the most globally inclusive and comparable, with volatility of results (huge swings from up to down to up) again being the most salient feature. Additional ICAO operating statistics are then displayed in Fig. 2.14. (See also domestic financial operating performance in Table 1.6.) With support from a booming economy, relatively low fuel prices and firm ticket prices (with the average spread between business and leisure fares widening to two times as compared to an earlier average of 1.5 times), the industry moved into a cumulative profit position in the 1990s.79 However, by the early 2000s, the industry fell quickly into near insolvency when faced with a sluggish economy and slackening of travel demand (in part as a result of terrorist attacks). In effect, revenues in such situations fall far faster than (largely fixed) costs can be cut. Shifts in the typically narrow spread between average

Fig. 2.14 ICAO-member profits (ex-USSR), 1947– 2019. Source: ICAO

80

$ billions

64 48 32 16 0 -16 47

57

67

77

87

97

07

17

2.4 Financing and Accounting Issues

97

(a)

(b) flights

passengers

4,500

39

3,000

26

billions

12,000 10,000

flights

6,000 13

1,500

4,000 2,000

passengers

passenger-km

0

-

0

60

70

80

available seat-km

8,000

90

00

10

50

20

60

70

80

90

00

10

20

(c) % 85 78

Load factor

71 64 57 50 50

60

70

80

90

00

10

20

Fig. 2.15 ICAO-member (a) flights and passengers (in millions), (b) available seat-kilometers (in billions), and (c) load factors, 1950–2019. Source: ICAO

breakeven and realized load factor percentages (Table 2.3) can thus be seen as being pivotal in the determination of airline profits and profitability. Another important feature is reflected in the industry’s collective balance sheet which relative to other industries has been high on the proportion of debt relative to equity. The relative burden of debt, or financial leverage (Fig. 2.15), would be reflected in a leverage ratio defined as debt to cash flow (earnings before interest, taxes, depreciation, and amortization, EBITDA): leverage ratio = total net debt (long 2 term debt minus cash)/EBITDA. The similar operating ratio would show how well covered by cash flows are gross interest payment expenses (i.e., including capitalized interest and not net of interest income): operating ratio = EBITDA/interest cost. Both ratios are often subject to definitional refinements (e.g., sometimes EBITDA is measured before subtracting rental and/or lease payments, which is EBITDAR), but the basic features are retained. Companies with a leverage ratio of, say, more than 5.0 to 1 would be rather financially risky as even a small downturn in cash flow due to an economic recession, rising fuel costs, or more competition would likely put the company on the road to bankruptcy—something that has happened to more than one hundred airlines since 1975.80 In the case of the operating ratio, however, the higher is the better. Any company that can barely cover its interest costs with operating cash flow (EBITDA)—that is, showing a ratio close to 1:1—is risking ruin.81

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Direction of rising risk

Debt/EBITDA "

EBITDA/Interest #

Wings

Debt/Revenue "

A third related measure of a company’s debt burden is the debt-to-revenue ratio, taken as net (of cash) balance-sheet debt including capitalized aircraft operating leases, airport lease commitments, and retiree obligations (i.e., pension liabilities) as compared against revenues: debt ratio = Net debt/revenues This ratio is generally most useful at times of financial distress for comparing companies against others in the same industry. A revenue ratio above 70% or so (excluding off-balance sheet lease and other obligations) suggests that a company is functioning at the outer limits of financial viability.82 The tremendous negative financial impact of the global virus pandemic of 2020 on selected travel sector ratios can be illustrated by the yearend 2019 panels of Fig. 2.16, wherein all the bars moved far into financial danger zones in the first half of 2020. Another aspect of financial risk, as linked to the already described ratios, is also often revealed through estimates of the sensitivity of EBITDA—which is a rough measure of cash flow (cf)—to changes in GDP or other such metrics. This provides another angle from which to view riskiness, but this time through an elasticity indicator (see Chap. 1), which is: in EBITDA εcf ¼ % %change change in GDP

Major U.S. airline profits had been strong enough in the late 1990s (but not in the early 2000s) to restore the industry’s financial health; the industry’s leverage ratio declined and the operating ratio rose. However, as this period covers the change from an economic low point (the recession of 1990–91) through a decade of the longest U.S. economic expansion, it is probably atypical.83 The terrorist attacks of September 2001 and the fuel price spike in 2008 temporarily moved the ratios into abnormal positions. Then came the economically devastating pandemic of early 2020, which pushed these ratios for all travel sectors into extremely risky positions and a struggle for survival. All countries with a large airline sector ended up bailing out the largest companies through loans or partial ownership positioning or a combination of both. The German government, for instance, injected around 9.5 billion euros in return for 20% ownership (i.e., a “nationalization” of sorts). Figure 2.16a,b,c Pandemic’s Financial Affect, selected travel sectors.

2.4.2

Financing

Airlines finance their operations in ways similar to those of other capital-intensive companies. Capital budgeting will rely on cash flow projections, net present value

2.4 Financing and Accounting Issues Fig. 2.16 Yearend 2019 ratios by sector: (a) leverage, (b) operating, (c) revenue. Soource: SEC 10-K filings. (a) Leverage ratio. (b) Operating atio: EBITDA/Interest. (c) Revenue ratio, Debt/ Revenues

99 Debt/EBITDA

4.0 3.5 3.0 2.5 2.0 1.5 1.0 A ir lin e s

C a s in o s

C r u is e s

H o t e ls

P arks

O T As

a) EBIT DA/Interest 28 24 20 16 12 8 4 0

Airlin e s C asin o s C ru ise s

H o te ls

P arks

O T As

b) Debt/Revenues 1.4 1.2 1.0 0.8 0.6 0.4 0.2 A ir li n e s

c)

C a s in o s

C r u is e s

H o t e ls

P arks

O T As

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(NPV) calculations, and internal rate of return (IRR) analysis methods commonly used for making long-run investment decisions (see Appendix B). In all such instances, a key indicator is the rate of return on invested capital (ROIC, or alternatively, on assets employed). Estimated comparisons of ROIC for the individual companies are affected by often widely differing depreciation policies, proportions of leased versus owned equipment, and direct and indirect forms of government subsidies. But the most important characteristic for the industry as a whole is the sensitivity to world economic growth, which ROIC tracks closely in time and magnitude.84 The six major sources of financing for aircraft are:85 • • • • • •

Internally generated cash Operating leases Commercial bank debt Export credit agencies (ECA) Tax leases Debt capital markets

Each of these sources contains various degrees of advantage depending on the financial condition and present needs of an airline. Internally generated cash (equity, in effect) provides complete control over funding but is nevertheless a high-cost source of funds as compared to debt, which enjoys tax advantages. Export credit agencies, established by governments, provide support for exports but lack the financing flexibility and relative ease of bank financing. However, bank financing is rarely longer than twelve years, which is much shorter than an aircraft’s useful life. Tax leases, which are used to lower the cost of financing by transferring the tax benefits of owning an airplane to companies that find such benefits even more valuable, require complex arrangements. And operating leases, which are regularly used as a source of funds, have their own distinct intricacies. U.S. carriers in particular have come to rely on the debt capital markets as a major source of funding. They finance aggressively through debt issuance when interest rates are low and they sell equity or convertible debt when the equity markets favor the company’s shares with a high price-to-earnings or price-to-cash flow valuation. The goal is to find a mix wherein the weighted average cost of capital (WACC), including debt and equity components (or variants), is as low as possible. Without going into greater detail, the province of pure texts on finance, WACC can be stated as WACC ¼ rd x debt/(debt + equity) + re x equity/(debt + equity), where rd is the cost of debt expressed as an interest rate, and re is the cost of equity, as estimated using risk premiums and risk adjustment factors (known as betas). Capital-intensive transport industries also use other means of equipment finance to shift debt off their balance sheets and to gain further potential tax advantages. Airlines or railroads, for example, often sell their equipment or have other parties buy their equipment for them in a sale-leaseback type of arrangement (the

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accounting implications of which are discussed in a later section). By shifting some of the equipment-related debts and assets off the balance sheet, not only do the companies appear less financially risky to potential investors, but also they provide financial companies specializing in these areas with annuity income and tax advantages that might otherwise go unused. Issuance of plain-vanilla common and preferred shares would be as typical a way for this industry to finance itself as it would be for any other. The same holds for convertible bonds of various flavors. But companies that have a need to finance large and expensive pieces of movable equipment (for instance, airplanes, ocean tankers, rail cars and locomotives, and trucks) have found that equipment trust certificates (ETC) are especially adaptable. Such certificates first evolved in the rail industry and are a form of secured debt, which means that the trustee, as the formal owner of the equipment, can upon default immediately repossess the equipment that has been pledged as collateral. In this structure, legal ownership is vested in the trustee (who leases the equipment to the company) and in an investor who has a claim rather than a mortgage lien. The advantage to the company using the equipment is that it can conserve cash over the near term, making only a down payment in the range of 10 to 25% of the cost of the equipment and paying the balance on a scale of maturities that could be between one and fifteen years. Moreover, debt-ratings agencies such as Moody’s will often rate the trust certificate debt one grade higher than the company’s other debts, thereby making comparative financing through issuance of such debt certificates a little less costly.86 ETCs are often also created as much for tax reasons as for spreading risk and lowering of borrowing costs. A modified version of the ETC, introduced by Northwest Airlines in 1994, is the enhanced equipment trust certificate (E-ETC). Such certificates are a type of debt securitization in which the plain ETC is divided up into several readily tradable pieces, each with a different risk/reward profile in terms of security and access to lease rental cash flows. As Morrell (1997, p. 186) notes, “a structure of this type will give the senior (lower risk) certificates a much higher credit rating than under the ETC.”87 Table 2.8 Major airline operating cost categories

Direct operating costs Flight operations Maintenance and overhaul Depreciation and amortization Indirect operating costs Station and ground expenses Passenger services Ticketing, sales and promotion General and administrative Other Source: ICAO and Doganis (2002, p. 79). Accounting treatments that depart from the standard are primarily in the flight operations category and pertain to airport and en route charges and to depreciation of rental leases of equipment and crews

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Accounting

Operating Items In all accounting systems there is a need to separate financial statement items into operating and nonoperating categories. For airlines, general categorization of this kind, shown in Table 2.8 (and also in Table 2.4), has been provided by the ICAO, which identifies nonoperating items as: • • • • •

gains and losses derived from sale of retired property and equipment, interest paid on loans, all profits or losses arising from an airline’s affiliated companies, gains or losses arising from foreign exchange or securities transactions, direct government subsidies.

As in other complex businesses, definitions in this industry differ to some degree from those in others but the basic accounting questions always relate to treatments of operating revenues and costs. Direct operating cost (DOC) should in theory include all costs associated with and dependent on the operation of aircraft, which would include fuel, flight crew salaries, maintenance and overhaul, and depreciation expenses. Other costs, including those for ticketing, administration, passenger service, administration, and ground costs, would be indirect. In practice, though, the distinction is not as clear, with some companies categorizing costs of administration or for cabin crews as direct whereas others assign them as indirect.88 In all, it is typical for direct operating cost to be around half of total cost, but with long haul and also low-cost no-frills carriers likely to see a much higher percentage (given that most no-frills cost-savings are in the indirect categories). If generally categorized, the relative percentages of total costs will vary from country to country, carrier to carrier, and year to year. But by and large fuel tends to account for at least 25% of the total, labor 20%, operations 20%, aircraft ownership or leasing 20%, airport fees 7%, ticket distribution 5%, and passenger services 3%. The different treatments illustrate the characteristics of managerial accounting, which provides the internal metrics needed to guide operations and facilitate planning and control, and financial accounting, which allows those external of management to assess the financial condition of a company. Managerial accounting here provides information to assess the impact of equipment changes and the costs of flying different routes, to calculate breakeven load factors, and to make competitive benchmark comparisons, for examples. Like most other large businesses, the industry uses accrual accounting in which revenues are recognized when services are rendered. The IATA Clearing House (ICH) provides the means of settling airline-to-airline financial transactions that arise when a passenger books trip sectors on different carriers (i.e., interlining). The Airlines Reporting Corp. is the clearinghouse for ticket transactions with travel agents. Although classifications into direct and indirect components are obviously of great usefulness and simplicity, the drawback is that the approach has limited ability to guide a carrier on decisions pertaining to pricing or overall economic viability of providing services on specific routes. To make such evaluations, analysts must turn,

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as Doganis (2002, p. 92) suggests, to the concept of escapability of costs. Some costs can be escaped over the short run whereas others only over the long run.89 Also, calculation of accounting profits using the cost categories in Table 2.7 does not encompass the notion of economic profit which equals accounting profit less opportunity cost. Economic profit is not typically stated because opportunity costs are difficult to explicitly estimate.90 Leases. For companies that have already encumbered much of their free cash flow, leasing allows the company to hold onto more cash over the near term than would otherwise be possible.91 And because some 85% of airlines presently lease all or part of their fleets and much of the related equipment, leasing another area in which there may be accounting ramifications that are of analytical importance. According to long-standing U.S. generally accepted accounting principles (GAAP), leases are classified as being either of the operating or of the capital (finance) type. Both types had been governed by rules spelled out in Financial Accounting Standards Board (FASB) statement 13. The finance lease gives priority to the concept of economic ownership of the lease asset, accounting for it on the balance sheet as if it were purchased. In contrast, the operating lease prioritizes the concept of legal ownership of the asset. The difference between the two types may have a substantial impact on reported earnings. For example, in the case of an operating lease, as lease payments become payable by the lessee, they are charged as a period expense over the term of the lease. Following FASB 13, “if rental payments are not made on a straight-line basis, rental expense nevertheless shall be recognized on a straight-line basis unless another systematic and rational basis is more representative of the time pattern in which use benefit is derived from the leased property.” Critics and regulators had, however, long complained that such operating lease accounting—in which some airlines show no airplane assets or liabilities for money they are committed to pay in the future—presents a distorted picture of a carrier’s financial health because the actual leverage is hidden: Companies have been generally able to classify almost all leases as operating and to thereby keep them off balance sheets. As a result, effective 2018, new standardized rules were approved by the International Accounting Standards Board (and in the U. S., by the FASB). Under the FASB’s revised comprehensive lease recognition Accounting Standard Update (ASU 2016–02), lessees must recognize most leases on their balance sheets as liabilities, with corresponding “right-of-use” assets. For income statement recognition purposes, leases are to be classified as either the operating or finance lease types.92 This generally results in straight-line expnse recognition for operating leases and accelerated expense recognition for financing leases (which is similar to previous capital lease procedures). These changes not only enlarge balance sheets but also make the accounting similar to the way it would be if the company had directly borrowed money to buy the plane.93 Operating leases longer than a year must now be placed on the balance sheet (instead of appearing in footnotes) and be treated as debt. But so-called variable leases—such as those involving airport terminals—wherein future

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payments change according to circumstances are excluded from the balance sheet. That’s because such payments may never be required and are thus not directly definable as assets or liabilities even though airlines are most certainly and ultimately still on the hook to possibly make them. Airlines have thus generally benefited because under the new rules leases for airport gates are not counted and interest rates on debt can be used to discount the future value of leases.94 One last complication—as if there aren’t enough already—is that international treatments for leases may differ from those in the United States even though the finance/capital lease approach, based on a concept of economic ownership of the asset, is the treatment suggested by International Accounting Standard—Accounting for Leases (IAS 17). In Europe and Japan “finance leases were often excluded from the balance sheet because the airline did not have legal title or ownership. In the U.K. and U.S., however, these leases are capitalized and placed on the balance sheet.”95 Aside from the financial accounting implications, operating leases permit the carrier to respond rapidly to changes in market conditions, are of relatively short term (averaging five years), and give the carrier use of the equipment without incurring an obligation to pay off the aircraft at full cost. However, finance leases (also called full-payout leases) that are used for about half of the fleets in North American carriers often extend over an average of ten to twelve years and involve a relatively large amount of debt and smaller amounts of equity (20 to 40% of the equipment’s value). Such leases are somewhat varied and depend to an extent on the country in which the lease originates and the aircraft is predominantly operated.96 Even though lease valuations are approached in many different ways they will, nevertheless, be always grounded in Net Present Value (NPV), Internal Rate of Return (IRR), and the associated discounted cash-flow (DCF) concepts. Monte Carlo (i.e., probabilistic) analyses of risks are also sometimes applied to DCFs. And the average expected cost of debt and equity financing—the Weighted Average Cost of Capital (WACC)—is also inherently included in operating lease valuations, which always include the capital cost of the depreciating aircraft, the implicit interest charge, and the cost of risk transfer. Sale-Leasebacks The sale and subsequent leaseback of aircraft is a frequently used airline financing strategy that can generate cash, realize economic gains, and increase fleet flexibility. According to the International Accounting Standards statement 17 (see IATA Airline Accounting Guide No. 6), if a sale-leaseback transaction results in a capital (finance) lease, any profit or loss should not be recognized immediately through income but should be deferred and amortized over the lease term. However, if such a transaction results in an operating lease and it is clear that the transaction is established at fair value, any profit or loss should be recognized immediately. And this treatment is not consistent with U.S. GAAP which requires that all gains arising on operating leasebacks be deferred and amortized over the minimum lease term in proportion to the gross rental charged as an expense. Notably, GAAP methods also differ from International Financial Reporting

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Standards (IFRS) in some important ways and the two approaches are not entirely compatible.97 In summary, the advantages of leasing (which may, in part, also be derived from outsourcing of other major equipment assets and services) are as follows: • Volume discounts for aircraft purchases can be obtained and passed on to the airline. • The airline conserves working capital and credit capacity. • Up to 100% of the equipment is financed with no deposits or pre-payments required. • The airline shifts the burden of risk of obsolescence to the lessor. • It may be possible to exclude leasing finance commitments from the balance sheet. • The tax status might become more favorable. The disadvantages of leases are as follows: • The cost may be higher than for straight-debt financing. • The profit from eventual sales of the equipment accrues to the lessor, not the airline. • Higher debt-equity (gearing) ratios may result. • Aircraft equipment specifications may not be fully compatible with the airline’s needs. Other Elements Given that modern airline companies must finance large capital equipment purchases by incurring significant debts, it is not unusual to find that they may attempt to shunt as much debt as possible to off-balance sheet affiliates called special-purpose entities (SPE). A parent company (under the accounting rules of the early 2000s) can own up to 97% of the investment in the SPE without having to consolidate the affiliate’s balance sheet into its own accounts. By this means, large debt obligations for plane leases will not appear on the airline’s balance sheet even though the parent company remains financially exposed and responsible for service of such obligations.98 Other elements specific to the airline industry include accounting for frequentflyer programs and acquired gates, routes, and airport landing slots. Airlines will generally record, under an accrual approach (also known as the incremental cost method) an estimated liability for the incremental cost associated with providing the related free transportation at the time a free travel award is earned. The liability will then be periodically adjusted for awards redeemed and earned or for changes in program requirements.99 Most airlines utilize the incremental cost method. However, as noted in IATA Airline Accounting Guideline No. 2, a deferred revenue approach may also be used. Under this procedure a proportion of passenger revenue generated from the sale of tickets conferring frequent-flyer benefits is deferred until such time as a ticket associated with the use of the frequent-flyer award is granted and used.100 The same approach pertains to revenues generated from mileage credits that have been sold to other companies participating in such programs; the deferred revenue is amortized as transportation is provided.

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Airlines will usually amortize routes on a straight-line basis over forty years, gates over the stated term of the related leases, and slots over twenty years. As for airports, some international airport management companies may adopt government accounting methods, while others will follow commercial practices. If the government methods are used it is possible that the airport’s real estate assets will not appear on the balance sheet. Moreover, some airport operators depreciate their systems over as many as one hundred years and others over only thirty to forty years. Then there are tax considerations. As with cruise lines (Chap. 3), foreignregistered corporate income from aircraft operation is exempt from U.S. federal taxation if the country in which the firm is registered offers equivalent exemptions to American firms. Under these provisions, major airlines such as British Airways or Lufthansa thus do not pay U.S. taxes but pay substantial taxes in their home countries. Taxation regimes for airports also differ widely, with those in the United States being largely exempt from most taxes as they are largely financed through issuance of municipal bonds. Hedging of risk is also part-and-parcel of the industry’s standard financial management routine. Such hedging would commonly involve use of forward and futures contracts, swaps, and options trading. Such hedges will regularly be applied to jet fuel needs, but might also be tied to equipment purchases, to leases, and to minimization of exposure to changes in interest and foreign-exchange rate conditions. Last, but far from least in the greater scheme of airline financial economics, is the need to recognize that the entire industry is globally subsidized through numerous government-directed programs that act in support of national flag carriers (e.g., stateowned Air India) or plane manufacturers such as Boeing and Airbus. Numerous agencies in Europe, in the Middle East, and in Asia, as well as the U.S. ExportImport Bank, essentially function as indirect loan guarantors largely at the expense of local taxpayers. Without such “too big to fail” types of supports, there would undoubtedly be fewer carriers and also a greater likelihood that average ticket prices would be high enough to fully recover unsubsidized capital costs.101 The result would be more consistent and real profitability across the industry. But as it stands now and into the foreseeable future, consolidation of the global industry into more financially efficient service providers will likely be politically untenable and slow to materialize almost everywhere.

2.5

Valuing Airline Properties

In the valuation of airline assets, projected cash flow forecasts provide only a starting point. The difference between what the shares of the company are selling for on the open market and what they might fetch in a takeover may be a function of the following factors, which are not all necessarily well captured in discounted cash flow projections:

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economic forecasts on a regional, national, or global basis brand-name value prospective reservation-system and frequent-flyer program capabilities amount of prospective competition age of equipment and facilities demographic and income profiles of business and leisure travelers in territories covered current and prospective rights to fly routes number and quality of gates at airports served number and time of day for current and prospective acquisitions of landing slot rights102 eventual size of potential carbon-emissions fee charges.103 For the financial analyst, the objective is to take all of these factors into account and to then compare such private market acquisition-value estimates to public share price valuations. In this regard, computation of the enterprise value (EV) of a company is a related and helpful concept. EV ¼ (number of shares outstanding x price of the shares) + outstanding value of net debt where net debt ¼ long term debt + current liabilities minus cash and cash equivalents This EV is often further modified by deducting the estimated value of off-balance sheet, nonoperating, assets to arrive at an adjusted enterprise value (AEV); AEV ¼ EV minus off balance sheet assets These AEV estimates, which reflect public market prices, are then in turn used to compute a ratio to cash flow (or EBITDA, that might further add in a term for aircraft rental) and that allows for relatively clean and simple comparisons to be made among similar firms in an industry (be it airlines, hotels, or media): AEV valuation ratio ¼ EBITDA

In the airline industry, for example, such valuation ratios will often cluster around five to six times EBITDA. But private market values, which include an implicit control premium, are usually much higher than are seen in public market trading of shares. The securities of a company would become attractive for purchase when the public share price is at a sizable discount (perhaps 20% or more) to such private value estimates.104 For many such assets, private market multiples would typically range between eight and fifteen times the cash flow that is projected for the next year (Table 2.9). This multiple could also be more precisely determined by comparing to cash-flow multiples on similar, recently traded, airline properties and to estimates of the potential for generating new revenue streams—economic value added (EVA)—on already invested capital. In such EVA models, share valuations key off of the difference between the weighted-average cost of debt and equity capital (WACC) and the returns in excess of the WACC.105

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Table 2.9 Public and private market valuation methods: Examples

Public market values Price per share Shares outstanding Total market value of equitya plus Total long-term debt Total less Cash Other off–balance sheet assets Adjusted enterprise value (AEV) EBITDA Cash flow multiple (AEV/EBITDA) Private market values EBITDA Times assumed multipleb Unadjusted value plus Cash Other off–balance sheet assets less Long-term debt Net asset value Shares outstanding Net private market asset value per share

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$11.50 $60 690 1200 1890 150 250 1490 165 9.0 165 10 1650 150 250 1200 850 60 $14.17

a

Preferred stock market value must also be included Derived by comparison with recent transfer-price multiples for similar assets

b

Table 2.10 Major selected airline deals since 1999 Surviving name Alaska Airlines IAG (British Air et al.) American Airlines LATAM Group Southwest United Delta US Airways Groupe Air Francea AMR/American Airlines a

Combined with Date Virgin America Aer Lingus US Airways TAM AirTran Continental Northwest America West KLM Royal Dutch Airlines Trans World Airlines

Date Dec. 2016 Aug 2015 Feb 2013 Jun 2012 Mar 2012 May 2010 Jan 2008 Jun 2005 Sep 2003 Jan 2001

Value in $ billions 2.6 1.5 11.0 2.7 1.4 3.2 3.1 1.5 5.1 4.2

History of deal in Michaels (2006). See also Clark (2015)

Major selected airline company mergers are shown in Table 2.10 which suggests that antitrust regulation in the U. S. has shifted from concern about a merged carrier’s overall market share to emphasis on whether a combination would decrease competition on specific routes.106

2.6 Concluding Remarks

2.6

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Concluding Remarks

Not so long ago, in 1895, Lord Kelvin, president of the prestigious Royal Society in London, declared that “[H]eavier-than-air flying machines are impossible.” Wouldn’t he be surprised! Travel by air has forever changed the way we think about the size of the world and the way we conduct our business and leisure activities. The systems that have been developed are complex and could not operate without the important advances in computing technology that have come out of the twentieth century. Many of the financing and operating methods are tailored to the specific needs of this industry in which technological obsolescence is much more of a factor than it is perhaps in rails or buses. This can be seen in the industry’s early adoption of blockchain procedures as applied to customer loyalty programs, parts tracking, parts leasing, airport slot management, and interline revenue tracking. The analytical methods used to study economic sensitivities here are, however, also generally applicable to other travel-related segments, all of which face the same essential problem in matching capacity with demand and having to make large capital investments far in advance of knowing what the demand will ultimately be. As such, the deregulated airline industry operates within a relatively unstable boom-and-bust cyclical swing in capital investments and profits and in which bankruptcies have been quite common. Bankruptcies provide relief from debts, which then allow the bankrupt operators to use a lower cost base to undercut the prices of other carriers, which then will often lead to more bankruptcies.107 From a microeconomic standpoint, the rules of airline operations basically boil down to what Petzinger (1995) has described as • every additional passenger is almost pure profit • whoever has the most flights from a city gets a disproportionate share of passengers • you can (and should) fill some, but not all, of the seats at low fares.108 Airlines must constantly battle pressures on margins and will always be affected to a notable extent by the ups and downs of the overall economy. “[A]irlines are not like other businesses, where competition breeds variety and choice for consumers and profits for business. They are more like flying utilities.”109 It is an endogenous sunk costs industry and a business that has become deregulated only on one side, with free competition for revenue but with costs largely immovable. Airlines are thus, in effect, merely “cash accumulators for other constituencies”—the various government entities that tax it, the cartel that sells it equipment and the industry’s bankers.110 Indeed, the IATA 2018 (pre-pandemic) profit estimate of $38 billion, as aggregated over more than 200 carriers, on average amounts only to about $9 per passenger in good-economy years! Accprdomg tp IATA data, North America generated the highest net post-tax profit per passenger of around $15, with Europe, $8, and Asia, $5. For sure, it is a high volume but low margin industry.

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Although opportunities to further realize significant cost economies of scale are limited, airlines will continue to combine and to consolidate operations—if not through outright acquisitions then through sharing of flight codes and frequentflyer programs and other such arrangements. Pricing power, market share, and brand dominance are often more the motivating elements than are potential cost savings. Still, despite the challenges involved in starting new companies or in combining older ones, new systems and carriers can and do emerge.109 That’s the nature of the business. Notes 1. See Carey (2013a) for more details. Hussey (2015) explains that the first flight might not have been by the Wright Brothers. 2. See Barron (2019). 3. The Japanese flagship carrier, Japan Airlines (JAL), was formed in 1951. Its first aircraft, a DC-4, entered service in September 1952 on a Tokyo-OsakaFukuoka route. Shortly thereafter, in 1953, the Japan Airlines Law was enacted. 4. See McCartney (2020). 5. Within two weeks of the attack, for example, Congress overwhelmingly passed a $15 billion aid package and agreed to set up an open-ended federal fund to compensate victims. The decline in global tourism (Chap. 7) was the first in twenty years. See also Alvarez and Labaton (2001), a overview of aviation history in Gunston (2002), and about the importance of air transport for tourism in Papatheodorou and Zenelis (2013). 6. See Varadarajan (2019) on small supersonics in development and Vance (2020) on Boom Technology and its Overture plane. 7. OPEC, the Organization of Petroleum Exporting Countries, was established in 1960 for the purpose of stabilizing oil prices. In the 1970s, however, in response to political pressures and the need of the member countries for more income, OPEC was able to significantly raise the price of oil in two large steps. 8. Quote from former Continental CEO Gordon Bethune cited in McGee (2012, p. 50). 9. Many bilateral agreements follow along the lines of the U.S. and British agreement that was a compromise signed in Bermuda in 1946. Both countries then undertook to model other future agreements on the Bermuda pattern. As Doganis (1991, p. 29) notes, a significant clause of the Bermuda agreement was that “while both governments maintained their ultimate right to approve or disapprove the tariffs proposed by the airlines, they agreed that where possible such tariffs should be arrived at using the procedures of the International Air Transport Association.” The other significant clause involved so-called fifth freedom rights. In bilateral negotiations, the freedoms are as follows: First Freedom: The right to fly over another country without landing.

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Second Freedom: The right to make a landing for technical reasons (e.g., refueling) in another country without picking up or setting down revenue traffic. Third Freedom: The right to carry revenue traffic from your own country (A) to the country (B) of your treaty partner. Fourth Freedom: The right to carry traffic from country B back to your own country A. Fifth Freedom: The right of an airline from country A to carry revenue traffic between country B and other countries such as C or D. Sixth Freedom: The right of an airline, registered in country A, to carry traffic to a gateway—a point in A—and then abroad to a third country C. The traffic has neither its origin nor ultimate destination in country A. Seventh Freedom: The right of an airline, registered in country A, to operate entirely outside of country A, in carrying traffic between two other countries. Eighth Freedom: The right of an international airline, registered in country A, to carry traffic between any two points of country B (often referred to as cabotage). In the Bermuda-style agreement, fifth freedom rights are relatively unrestricted in terms of allowing airlines to set the frequency and capacity on routes between two countries without regulatory interference as long as the other airline doesn’t complain. Freedoms of the sixth to eighth degrees are rarely accepted. See also Meller (2003) about proposed changes in European bilateral agreements and the Wall Street Journal editorial, “The Free Blue Yonder,” October 18, 2005. In 2007, the United States and the European Union (EU) signed a comprehensive Open Skies agreement which authorizes every U.S. and EU airline to fly directly between every city in the EU and the U.S.; to operate without restriction on the number of flights, aircraft, and routes; to set fares according to market demand; and to enter into codesharing, franchising, and leasing arrangements. This means that a U.S. passenger could fly to Paris on British Airways without changing planes in London, or that Air France can fly between Los Angeles and London. EU investors may hold up to 49.9% of the total equity in a U.S. airline. In Europe the Open Aviation Area agreement of 2008 was comparable to Open Skies. See Palmer (2007), Michaels (2007), Michaels (2008b), and Carey and Michaels (2013) in which problems for U.S. and European carriers created by Open Skies is discussed with respect to the massively governmentsubsidized expansions (including airports, terminals, and jumbo jet purchases) of the large Gulf State airlines (Emirates, Qatar Airways, and Etihad Airways). These carriers do not necessarily need to be profitable to survive and are thus strong and fit competitors against largely unsubsidized legacy companies but might be facing difficulties as discussed in Campbell (2017). See also Becker (2013, Chap. 6), McCartney (2014a, b), Carey (2015b), Dow (2015), Gapper (2015), Mouawad (2015), Parker and Wilson (2015), and Wall and Parasie (2018) on Emirates strategy.

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10. The spirit of deregulation along with support for growth of international travel was manifest in the Helsinki Accord of 1975 and the International Air Transportation Competition Act of 1979 (passed by Congress in early 1980). The Helsinki Accord established principles of operation that simplified and harmonized the administration of international travel, especially across national frontiers. The Air Transportation Act, however, was also designed to strengthen the competitive position of U.S. international air carriers, provide more freedom for carriers to set rates and establish routes, eliminate operational and marketing regulations with respect to capacity and flight frequency, integrate domestic and international operations, increase the number of U.S. gateway cities, provide foreign lines with increased access to U.S. cities, eliminate discrimination against U.S. carriers, and promote and develop civil aeronautics. See also Gee et al. (1997, p. 311), Wensveen (2007), and Belobaba et al. (2009). 11. American acquired TWA in 2001. 12. After 1995, all scheduled carriers operating aircraft with ten or more seats were required to comply with FAA Part 121 certification procedures. Among the largest contract carriers have been Atlantic Coast (now Independence Air), Skywest, ExpressJet, and Pinnacle. Both Atlantic Coast and Skywest had either been or are still partnered, respectively, with United and Delta, and ExpressJet with United/Continental. Carey (2009) notes that relationships between the regionals and their partners are sometimes strained. According to federal aviation rules and legal precedent, commuter airlines are considered to be distinct legal entities even though their planes usually bear the logo of the mainline carriers. See Mouawad (2012c) and McCartney (2013b). On industry vertical integration, see Forbes and Lederman (2009). 13. Fallows (2005) describes brief history and discusses SATSair and DayJet. See also Meckler and Johnson (2006), about light business jets and Sharkey (2008). Krupnick (2015) writes about start-ups such as Magellan Jets, which offers a subscription whereby passengers buy blocks of flight times and are then matched to planes via an iPhone app. Another start-up is BlackJet, which matches passengers with empty seats on nearby private aircraft. In 2016, JetBlue bought a stake in JetSuite, the fourth largest charter operator in the United States. This company makes private jet travel on four and six seat aircraft affordable with service to small airports that can be booked online. On the more luxurious JetSuiteX, the company uses 30-seat aircraft that flies between private airport terminals. 14. A typical five-year contract with NetJets (Executive Jet Inc.) and smaller competitors, (e.g., Flight Operations, Inc.) involves the sale of one-sixteenth ownership share of a plane to a buyer who gets fifty hours of flight per year after paying further specified monthly and hourly operating fees. Fractional-jet ownership programs, pioneered by Executive Jet in the mid-1980s, are described more fully in Carey (2002b), who notes that the cost of a one-sixteenth share of a small Citation Excel, twin-engine, seven-seat jet requires an upfront investment of $620,000, a monthly fee of nearly $8000,

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and an hourly flight fee of almost $1700 for a plane that sells new for about $9.8 million. Comparably, a one-fourth share of a Gulfstream V, which can carry thirteen passengers, has an upfront fee of $10.1 million, a monthly fee of $56,516, and an hourly fee of $3118 for 200 hours per year. One of the significant advantages of such jets is that they can land at 5000 U. S. airports rather than only the 500 or so available to larger commercial carriers. A major challenge in running the business is that an estimated 25% or more of the average time a plane spends in the air it is empty, en route to passenger pickups. Fabrikant (2008) writes that the annual estimated corporate operating cost in 2008 for a plane like the Gulfstream G550 was around $1.3 million, including $500,000 for property tax and $400,000 for pilots and stewards. Typical operating costs are more than $2000 an hour in the air. Another experimental concept, discussed in the November 2012 issue of Inc. involves Surf Air, a company that allows unlimited monthly flights to regional airports for a fee of $1110 a month. See also Witz (2013b) and Zipkin (2015a). As of 2002, Executive Jet Inc., owned by Warren Buffett’s Berkshire Hathaway, Inc. had held around 50% share of market. See also Carey (2002a), Johnson (2005), Jackson (2006), and Palmer (2004) in which growth of air charter through companies such as Blue Star Jet, small air taxis (Pogo), and Jet Cards (that operate like a prepaid phone card) are discussed. Airport congestion concerns related to such taxis is discussed in McCartney (2006c). See also Sharkey (2007); BusinessWeek January 29, 2007; Burger (2011) and Kesmodel (2012). 15. These unions are the largest for each labor group, but there are others. For example, American Airlines employees are represented by different unions. At American, the ratio of the number of pilots to planes is around 10:1. 16. As of 1999, at United Airlines (UAL) 55% of the holding company’s UAL shares had been employee owned and at TWA, 45%. Subsequently, both airlines failed within this structure. UAL’s Employee Stock Ownership Program (ESOP) was born out of the financial woes of the early 1990s, when United needed to cut costs. In exchange for $4.8 billion in pay cuts and workrule changes, in 1994 all United employees with the exception of flight attendants received a collective stake of 55%. See also Zuckerman (2001b), Wall Street Journal, December 6, 2002, and Carey and McCartney (2003) for a discussion of UAL’s ponderous labor rules such as rigs which are contractual formulas that pay pilots and flight attendants for the time the spend sitting at airports or in hotel rooms. More recent pilot-pay issues are discussed in Nicas and Carey (2014b). As of 2016, Southwest had the highest airline employee share ownership at 13%. 17. Doganis (1991, p. 23).

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18. It is difficult to determine the precise profit contribution from carriage of freight and mail because, in most instances of scheduled services, the operating costs of the flight and the fixed costs of the terminal, service equipment, and so forth are combined with costs related to serving passengers. Calculation of cargocarriage contributions to profits would thus require somewhat arbitrary allocation of costs among the different categories. 19. According to IATA 2018 data, the largest O-D markets by far were U.S. domestic and China domestic, respectively carriying 587 million and 515 million passengers. And in terms of passenter-kilometers (domestic and international) flown, the top three carriers were American, Delta, and United at around 330,000 million RPKs, followed by Emirates with roughly 10% fewer RPKs. 20. Spill is the difference between nominal demand from passengers who want to fly on a segment and the load (i.e., passengers who actually fly the segment). Spill has both an economic and opportunity cost, but it is not an accounting cost that is shown on an income statement. The greater the reliance on connecting traffic, the greater the probability of increased network spill costs. Load factors can sometimes be adjusted by upgauging, i.e., using a plane with more seats. See also McGee (2012, p. 26) 21. On an industry-wide basis, experience has shown that in almost any year it is difficult to increase available seat capacity by more than 5% without having to cut prices. Carriers with a larger-than-average capacity-share in a given market will often gain a greater-than-proportional share of the available revenue in that market and conversely, carriers with a smaller than average capacity-share will earn a smaller-than-proportional share of the total revenue in that market. This notion is known as the S-curve effect, where the S-curve is a plot of revenue share, the independent variable, against market share, the dependent variable and where the S-curve portrays the effect of dominance at a hub. As Berdy (2002) notes, in this context, a “share gap is the difference between traffic or revenue share compared to service share.” Data for such curves appear to indicate that high-fare passengers are attracted to those carriers providing the most service in a market. For more detail see Butler and Keller (1999, p. 32 and p. 39), an article about dynamic fleet management by Skinner et al. (1999); Spill in Clark (2002); and Mouawad (2010). Operational problems from the consumer perspective are discussed in McGee (2012). On predation see Pinto (2009) and Sciaudone et al. (2020). 22. As noted in Wayne (2006), Boeing’s 787 Dreamliner, introduced into service in 2011, was designed to be marketed to airlines and their customers who prefer direct flights (city pairs) versus the Airbus A-380, introduced into service in late 2006, which would be more likely to fly between hubs. By 2020, however, lighter and more efficient smaller planes, which filled faster and thus reduced ticket price discounting and fuel consumption were favored. For example, Wall (2018a) explains that in 2017, United Continental spent around $17,750 an hour to operate its latest 747 as compared to $10,125 per hour for the more technologically advanced 787.

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23. Regression analyses by Oum et al. (2000, p. 196) showed that “major” alliances that included deep and wide interfirm cooperation enabled partner airlines to improve productivity, to price their services more aggressively, and to thereby raise profitability. The benefits extend to introduction of new technology and global brand building as well as increased traffic flow. The five major alliances as of the early 2000s are Oneworld (including American, British Airways, Cathay Pacific, Finnair, Iberia, Japan Airlines, JetBlue, LATAM, Qatar, and Quantas); Star Alliance (including Air Canada, Air China, Air India, Air New Zealand, Avianca, Aerolinas, Lufthansa, Saudi, Singapore Airlines, United, and Varig); and SkyTeam (including Air FranceKLM, AeroMexico, Delta, and Korean Air). Cooperation in these alliances can result in cost savings through joint purchasing and adoption of common information-technology platforms. Most nations, however, place restrictions on outright foreign ownerships. For instance, foreigners may own up to 49% of equity and 25% of voting rights in Unites States carrier companies. See also Doganis (2001, p. 75), Michaels (2006, 2007), Maynard (2009b), Cameron (2012b), and McCartney (2018d). One way to measure the effectiveness of such marketing in a particular market or within a network is to compare actual percent market share of revenues (or total passengers’ boardings), Sr, with the percent share of scheduled service, Sss If the resulting “marketing power” ratio, MPR ¼ Sr/Sss is above 1.0 or moving to above 1.0, the airline’s marketing is effective. The ratio is similar to that of the same name that is used in broadcasting. Code-sharing also provide carriers, especially on international routes, to engage price-discrimination strategies. See McCartney (2004a). Bilotkach (2017, Chap. 6) covers the history of code-sharing. 24. The advertising intensity ratio is discussed further in Hanlon (1996) and in Bagwell (2003, pp. 55–62). It is based on theory, developed by Dorfman and Steiner (1954) for optimal monopoly advertising. This model shows that it makes sense to increase spending on advertising as long as the sales gain from doing this is greater than the sales to be gained if such spending were to instead be used for price reductions 25. In response to many complaints about this, the CAB in 1984 ordered that vendors must offer primary terminal displays that rank flights based on fares and service factors rather than on carrier identities and that connecting flights must be listed according to objective criteria. Nevertheless, the reservation systems remained inherently biased in favor of online connections over interline connections. Until 2004, DOT rules did not permit such bias; instead it was ordered that flights be listed by schedule, yet allowing agents to install their own screen preferences. After the DOT rules expired in 2004, bias was again seen creeping into travel agency bookings sites because Travelocity, Expedia, and Orbitz began cutting special deals with airlines and hotels, paying to have flights or rooms listed ahead of those of competitors. As noted in the Wall Street Journal of November 9, 2004, the result is that travel sites sometimes list hotels as sold out or unavailable when they really are not. The four global

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reservation distribution systems in use as of the early 2000s were SABRE, Amadeus (created by several European airlines), Galileo, and Worldspan. By 2012, Lutfhansa, Air France, Iberia, had sold interests in Amadeus, American Airlines had sold SABRE, and British Air and KLM had sold Galileo. Orbitz (acquired by Expedia in 2015 for $1.34 billion) and Hotwire (part of Expedia as of 2005) are discussed in Barrett (2000). Trottman and Power (2002) discuss antitrust concerns about Orbitz, which had been owned by the five largest U.S. airlines (United, American, Delta, Northwest, and Continental). Orbitz quickly became the No. 3 online player competing against the Web sites of Expedia and Travelocity.com, which in 2015 merged when SABRE sold its interest. As of 2005, Galileo International (also a part of the Travelport unit of Cendant that was sold to Blackstone) had been the second-largest travel reservation system after SABRE. Galileo’s consumer leisure-travel site, Trip. com, is described in the Wall Street Journal, April 29, 2002. As of 2019, OTAs accounted for an estimated 15% of $1.8 trillion in worldwide bookings. Commissions on airline tickets may be as low as 2% to 3%, with rental-car commissions somewhat higher (around 8%), and hotels potentially the highest at up to 30% (but usually in the range of 15% to 20% of room rate). Google is leading the way toward turning browsers into bookers and thus competing with the legacy OTAs. See also Sect. 4.2 on OTA sector operations related to hotels and www.asta.org. In 2002, Orbitz was only beginning to enter so-called “merchant” discounting in which Expedia (and also competitor Priceline.com, now Booking Holdings, Inc.) negotiates discount prices for large blocks of hotel rooms or vacation packages and then profits from selling at higher prices to consumers. In this “merchant” model, margins are higher and Expedia controls the pricing. This differs from the traditional agency model, where online companies give customer reservations to the service supplier in return for a commission, and on top of which are added segment fees from global distribution systems and service fees from travelers. A brief history of Orbitz and its effect on pricing is in Hansell (2002). In 2002 SABRE sold around $80 billion of tickets and retained 2 percent as revenue. See also Hansell (2003), Deutsch (2006), and FitzGerald (2016). American Airlines pulled out of Orbitz in favor of its own system in late 2010 but was then ordered by the Illinois Circuit Court to return in 2011. Data from PhoCusWright shown in Esterl (2011) indicates that in 2010, U.S. Airline booking revenue was $110 billion, with 32% derived from airline websites, 45% from travel agents, 16% from online travel agencies, and 7% from airline call centers. Travel sites like Expedia and Orbitz, and Galileo and Worldspan (owned by Travelport) get fees of $8 to $10 (and often up to $12) for each roundtrip airline ticket they sell, with around $3 to $5 coming from airlines and $5 from global distribution systems (GDS). This translates into around $7 billion in annual cost for the world’s airlines. In return, online travel agents (OTAs)—the largest of which include Booking/Priceline, Expedia, MakeMyTrip Limited (India), and Orbitz Worldwide—receive reservation

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flows and computing capability from the GDS systems. However, around 2012, airlines and hotels began to seriously incentivize travelers to book directly on company sites (e.g., RoomKey.com for hotels), and thus circumventing the OTAs. Direct booking on hotel sites in 2016 was around 30% of all U.S. room-nights. On this, see White (2015), Edelson (2016), and Kirkham (2017). See also Rich and Angwin (2002), BusinessWeek (July 8, 2002), Levere (2011), “The Ineluctable Middleman,” about Global Distribution Systems in The Economist of August 25, 2012, FitzGerald (2013), and Salzman (2013). TripAdvisor was spun-off from Expedia in 2013. 26. On a global basis, business and first class long-haul cabins are estimated to account for 10% to 15% of all seats but for up to half of revenues for carriers such as British Airways and Lufthansa (Mouawad 2013a). According to Garvett and Avery (1998, p. 181), an airline’s profitability is most closely related to yield management effectiveness, ownership structure (i.e., government versus private) and/or tenure of airline, and unit revenue. Stage length (i.e., an airport-to-airport segment) and customer satisfaction were also significant. Yield and load factors are not necessarily correlated with profits. And profits require both high load factors and high yields at the same time (i.e., high revenue per available seat-kilometer). Homan (1999, p. 508) suggests “that for every 1 percent decrease in yield, quantity demanded (by RPMs) increases by about 0.7 percent. Additionally, for every 1 percent increase in real GDP, demand increases by over 0.9 percent.” Doganis (2002, p. 283) indicates, however, that maximization of total passenger revenue per flight “is not the same as ensuring the highest load factor or the highest average yield.” And Fallows (2005) suggests that yield management has led to arrays of special fares and conditions that have made travel confusing but that kept planes full. Yet introductions of Orbitz/ Travelocity type systems have begun to wreak havoc on yield management attempts and have led to the demise of high-cost operators. A new pricepredictive service (farecast.com) that uses algorithms to help passengers forecast ticket price changes is discussed in Darlin (2006) and Tedeschi (2007). But Contracts of Carriage (CoCs), printed on tickets, specify that airlines have fewer obligations (e.g., destinations and arrival times) to passengers than is generally understood. See also Belobaba (1998a, b) and Noyes (2014) on use of big data. 27. Such price discrimination tactics for dividing business from leisure travelers include overnight stay requirements that force business travelers to pay much higher fares if they want flexibility and to be home on weekends. See McCartney (2008c) and Thompson (2013). 28. Although the programs have turned out to be essential in supporting a brand, McCartney (2004b) notes that the loyalty benefits have been diluted over time as the companies have joined in marketing alliances, added corporate discount contracts, and begun to tilt such programs in favor of more profitable customers who pay higher prices. Brand loyalty has done little to slow the rise of low-fare

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carriers. Another tactic discussed in McCartney (2006a) is to issue prepaid passes that allow customers to lock in relatively reasonable fares, while the airline transfers some of the risk of empty seats to customers, gets cash in advance, and retains the traffic. See also McCartney (2012a). Sharkey (2002) discusses the growing frequent-flyer liabilities being incurred by the major lines, noting that they have been accounting for free trips for years at rates that have typically averaged 7 to 8% of the total paid miles flown. As an example, Delta had ten million awards each representing 25,000 miles on its books at the end of 2002. The liability to cover the cost was $228 million, or around $23 per award. In 2014, United earned $2.9 billion from sales of mile equivalents to other companies. In implementing the programs, airlines incur administrative expenses that amount to perhaps 1% of total costs. For major carriers, this might amount to 10% to 13% of total current liabilities. Brand-building effects and potentially firmer pricing structures may, arguably, provide an offset as passengers have demonstrated a degree of loyalty to one line in preference to another flying the same route at the same or at perhaps even lower prices and more convenient departure times. Also, incremental revenues from affiliated consumer merchandising partners such as hotel, car rental, credit card issuer, and telephone companies have historically paid the airlines an average of 2 cents per milepoint, although current value (see McCartney 2008a) is probably approaching 1 cent per mile-point. In all, such compensation may actually add up to more than the price of a discounted-fare ticket on the typical route flown. For example, 25,000 redemption mile-points sold to marketing partners might provide the airline with $500. McCartney (2010c) indicates that most airlines charge passengers between 2.5 and 3 cents per mile and that some add processing charges of $25. See also Lieber (2004), Maynard and Dash (2005), McCartney (2012b), Weed (2014), and The Economist, “Funny Money,” December 24, 2005. Passengers determine the buying power of miles earned by dividing the cash price of a ticket by the miles required. On this basis, business-class upgrades might have a buying power of 4 to 5 cents a mile as compared to 1 to 1.5 cents a mile for coach seats. By 2012, airlines had accumulated on their books an estimated 10 trillion frequent flyer miles. According to Morrell (2007, pp. 47–8), the miles are most often accounted for using the incremental cost method, which recognizes liability for potential future costs incurred in carrying such passengers. A passenger would need to have accumulated a minimum threshold of points to be entered as an accrued liability on the balance sheet. An alternative accounting treatment is the deferred revenue method, which was standardized by the FAST effective 2018. This method increases the value for mileage credits but otherwise has no impact on miles sold under co-brand cards or to other partners. 29. As many as 30% of the mileage liabilities may go unredeemed and airlines may value a mile on their books at a fraction of a cent. Also, flyer programs have

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31. 32.

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increasingly evolved away from rewarding customer loyalty to instead qualifying passengers for avoidance of common inconveniences. In aiming to appeal to the more profitable customer segments Delta in 2014 began awarding for prices instead of miles, with passengers earning between five and ten miles per dollar spent. See also Lieber (2014, 2015) and Wall (2017a). On perk auctions, see McCartney (2016b). However, as noted in McCartney (2017c), even elite flyers are finding fewer perks. See Bachman (2017). For the airlines in particular, tickets written by agencies at the mid-1990s peak had come to account for approximately three-fourths of air carrier revenues. The spread of Internet services has, however, reduced agency activity to less than 50% of airline tickets sold even though agencies still handle around 85% of cruises, 70% of tours and packages, 30% of all hotels, and 25% of all car rentals. In 1995, airlines began to cap commissions for round-trip domestic flights costing more than $500 at $50 and for one-way flights at $25. In 1997, commission rates dropped from 10%, to 8% for domestic and international travel originating in the U.S. and Canada. And in 1998 a $100 cap on roundtrip international flights was first imposed. Commissions were further reduced to $20 for round-trip domestic flights in 2001. For flights booked on the Internet, commissions are $10 a ticket. Also, in 2001, Carnival Corp., the largest cruise operator said it would cut in half travel-agent commissions on the air-travel portion of cruise bookings. By 2002, after the severe earnings declines of the prior year, Delta announced that it would eliminate all domestic travel commissions. Delta had paid about $540 million to agents in 2001. See Zuckerman (2002). Agents must also have what are known as Airline Reporting Corporation (ARC) appointments, without which they cannot sell any tickets. These appointments require everything from the employment of a manager with at least two years of ARC-appointed agency experience to the need for a safe in which to store blank ticket stock. Airlines keep close track of tickets sold and monies owed by agents, and they require prompt remittances. Agents, in contrast, must usually wait longer than a week or two to be paid by their travel customers. Airlines see agents in the domestic market as being good at issuing tickets but not at marketing. Sovich (2017) writes of a trend toward more personal travel experience planning. Services such as those provided by Booking/Priceline.com enable travelers to name the price they are willing to pay for a ticket and to presumably reap significant discounts. Airlines have been somewhat (see Morton et al. 2015) willing to cooperate because they can sell otherwise empty seats close to departure time without subverting their higher-price structure. OTAs such as Booking.com might earn a flat booking fee 15% of each hotel transaction, but meta-search companies such as Kayak are instead paid per click and thus earn a

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lower margin of perhaps 7%. See also Siemers and Harris (1999), Elkind (1999), and especially Salzman (2013). Cameron (2012a) interviews the CEO of Travel Leaders Group, the largest U.S. travel agency operator as measured by number of agents. The company was formed by a 2008 buyout of Carlson’s Wagonlit unit. Many of the company’s 28,000 agents work at home. Online agency companies and their major brands as of 2015 are shown in Sect. 4.2.3. For Lindsay (2011) and Kasarda and Lindsay (2011), the largest of such airport cities, formed over the last decade for the specific purpose of becoming important international long-haul transport hubs, is an aerotropolis. Creation of on-site hotel complexes, as described in Zipkin (2015b), have accordingly become necessities. An early prototype was Dallas/Fort Worth International Airport, designed in the 1970s to be a planned city, hub, and office park that would generate economic growth. Measurement of economic and environmental impacts are typically approached through use of input-output (I/O) tables and economic multipliers relating to employment, incomes, etc. and are often stated, for example, in terms of jobs (or whatever) per million passengers per annum (mppa). Multiplier and I/O analysis are discussed in Chap. 7 in relation to tourism impacts. The importance of time, cost, and accessibility and the $3 trillion airfreight estimate appear in Kasarda and Lindsay (2011, pp. 10–7). See also Carey (2011b), Gillen (2013), and Mouawad (2014b). Sheard (2015) found that airport size has a positive effect on local employment with an elasticity of 0.03. Green (2007) used various measures of airport activity such as boardings, hub status, and cargo volume and found that passenger activity predicts growth but cargo activity doesn’t. According to a 1999 survey by the Airport Council International (ACI), just under half of all airport revenues were aeronautical, with the highest non-aeronautical percentages of total revenues in the wealthier North America and Europe markets and the lowest in Africa, Central, and South America. Wayne (2009) writes that in the U.S. two-thirds of all airport revenue comes from nonairline sources such as retail concession-fees, car rental surcharges, and facilities charges. See Cohen (2006), in which the privatization and fee-structure battles at Charles De Gaulle Airport in Paris are reviewed. Also see Michaels (2008c) about the benefits of British Airway’s move to new Heathrow Terminal 5, Michaels (2005), and McCartney (2006b, 2008b). McCartney (2010d) discusses more efficient takeoff reservations. Hammer (2015) writes about the problems in opening Berlin’s new Brandenburg Airport. The Airports Council International (www.aci-na.org) represents more than 1700 airports in 170 countries and provides research and data on various airport management topics. See also McCartney (2016a) on costs at LAX, McCartney (2017a), and Berger (2018) on JFK terminal overhauls. To measure and compare efficiency, airport managers will generate metrics related to the number of passengers or tons of freight loaded and aircraft moved but may also use a unit cost measure known as a work load unit (WLU),

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defined as carriage of one passenger or 1 kg of freight. Airport throughput units (APU) are then equal to WLUs divided by air transport movements (ATM), that is, APU ¼ WLU/ATM. For purposes of financial analysis, it is also often useful to make airport efficiency comparisons for labor productivity in terms of WLU per employee, capital productivity in terms of WLU per total assets, and revenues per WLU, cash flow (Ebitda) per WLU, or enterprise value (EV) per WLU. See Graham (2001, 2003), Wells and Young (2003), Ashford, Stanton, and Moore (1996), and Forsyth et al. (2004) on regulation of airports and McCartney (2006b) about air taxi congestion concerns. Mouawad (2012e) notes that departure delays are related to the number of slots and proximity of other major airports. See also Donohue and Shaver (2008), Clark (2012b, c), Mouawad (2012a), and Orr (2017). Noted by Graham (2001, 2003). See also McCartney (2017b), Bednarek (2016), Jorge-Calderón (2014) and Ashford and Moore (1992). See Negroni (2017). Important variants include build-transfer (BT), build-rent-transfer (BRT), and design-construct-manage-finance (DCMF). Unlike elsewhere, in the United States airports and airlines enter into unique binding contracts known as airport use and lease agreements which detail the fees and rental rates that airlines are obligated to pay for use of airfields and terminals. Such agreements may further relate to allocations of landing slots and whether runway fees are based on maximum takeoff weight (MTOW) or are fixed per landing, no matter what the type of aircraft. The reason for this structure in the U.S. is that private bondholders require detailed information concerning such formal arrangements. See also Ashford and Moore (1992), Pitt and Norsworthy (1999), Schoenberger (2003), Williams (2006), Carey and Nicas (2013a), and Carey (2014b). Michaels and Merrick (2009) discuss airport debt problems. Barboza (2013) writes about China’s airport building spree, Moss (2016) on China’s route expansion plans, and Feng (2016) on China’s airports. Witz (2013a) is about problems at Ontario, California and Cameron and McGroarty (2018) on airport expansion programs in the U.S. A 1977 National Transportation Survey showed that the percent of trips made by air in 1977 was 52.8% for travelers with household incomes above $50,000 and only 25.3% for those with household income of $15,000 to $25,000. See also Meyer and Oster (1987, p. 185). These studies include those by the British Airports Authority (BAA 1978). See also Doganis (1991, p. 222). Hubs have traditionally involved flying fifty to sixty airplanes at a time for arrival within twenty minutes of each other. As arrivals become more dispersed and connecting passengers must wait longer, the hub, in industry jargon, is then called a “rolling hub.” Clusters of arrivals and departures are also called complexes. In a large hub such as American’s base in Dallas, there might be between six and eight such complexes per day. Mouawad (2011b, c) writes that

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the ability to fly more direct routes and land along smoother glide paths, thus saving time and fuel and minimizing congestion, is the goal of the FAA’s new NextGen air traffic control system, which replaces ground radar with satellite positioning technology at an estimated cost of up to $42 billion. See also Antoniou (1991), Fujii et al. (1992), Trottman and McCartney (2002), McCartney (2005a, 2010a, 2014c, 2018b), Mouawad (2012c), Carey (2013b), Carey and Pasztor (2014), Pasztor (2014), Carey (2015a), Carey and Pasztor (2017). Bamberger and Carlton (2002) found that average local fares increase as airport hub activity increases (more passengers use an airport as a connecting point) but that the number of flights available to local passengers (i.e., service quality) increases as well. Maynard (2004) suggests that the whole industry is undergoing a major shift in structure, moving toward fewer hubs and dividing into three layers of competition. The top tier would include premium-fare service, primarily served by legacy airlines on long-distance international routes where discount-carriers cannot easily compete. At the opposite end of pricing and service would be markets served by discount-fare carriers providing minimal services and earning minimal profits. In the vast middle market, the battle would be waged in terms of degree of predominance at hubs and provision of more service amenities than available on pure discount-priced flights. Olson (2009) and Millman and Esterl (2009) report on how smaller-city airports are trying to retain service and hub status by reducing fees (waiving landing fees and sharing of marketing expenses, etc.) and even paying cash to airlines. Stellin (2010b) discusses the impact of rising airfare taxes. See also Borenstein (1989), Ramsey (2011), Levere (2012), Carey and Nicas (2013a, b) and Nicas (2015). This evolving business model differs greatly from the post-deregulation model that had been supported by customers willing to pay a premium for convenience and wide availability of flights. McCartney (2005a) cites a 2001 U.S. Department of Transportation study that found that ticket prices for hub-market travelers such as in Charlotte, Cincinnati, Minneapolis and Pittsburgh were 41% higher than in competitive markets. The Law of Connectivity is also called Metcalfe’s Law, named after Robert Metcalfe, one of the Internet and Ethernet engineering pioneers. The law is usually applied to electronic networks such as the Internet. It becomes operative once the number of nodes surpasses a critical mass. Otherwise, the network fails. See also Mayer and Sinai (2003). Quote from Shy (2001, p. 5). Using game theory concepts, Shy (2001, pp. 218–29) further explains how and why airlines find it beneficial to establish hub-spoke and code-sharing systems. Button (2002) discusses airline network economics. Doganis (1991, p. 129).

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48. Ng (2012) writes that as of 2013, long, thin routes were gradually being eliminated as a result of slower global economic growth and the sheer weight of the increasingly expensive fuel needed to fly for more than 15 hours. On these, aircraft burn more fuel per mile than on shorter routes without a commensurate increase in ticket prices. Rising competition from budget airlines (carrying one-fourth of the traffic) in the Asia-Pacific region has also been a factor. But by 2018, lower-to-stable fuel prices, new and more lightweight technology, and faster global economic growth prompted resumption of such long thin flights, the first one being a 17-hour nonstop from Perth to London (9010 miles). By the early 2020s, 19-to-22-hour journeys, say from Sydney to New York or Singapore to New York (9535 miles) are being flown. See Raghuvanshi (2014, 2016), Moss (2017), McCartney (2018a, 2019a), and Wall (2018b). 49. Each $1 per barrel price change is estimated to be equivalent to around a $425 million a year change in total expenses for U.S.-based carriers. Each pennyper-gallon increase in jet fuel prices is estimated to cost the industry $180 million. Michaels (2008a) describes how airlines are reducing their long nonstops as the cost of flying “18 hours in one hop could double the cost of flying the same route with three stops. To fly far, a plane needs lots of fuel onboard, and to carry all that fuel, it needs even more fuel.” Still, airplanes are relatively efficient: A Boeing 747, for example, burns about one gallon of fuel every second, or 36,000 gallons on a ten-hour flight. With 500 passengers on board, it is transporting 500 people one mile using 5 gallons of fuel, or 0.01 gallons per person per mile, or 100 miles per gallon per person, as compared to a car carrying one person at perhaps 30 miles per gallon. See “How Higher Fuel Prices Affect Aviation” available at wwwlabacuspub.com and McCartney (2012d). Fuel burned per passenger for U.S. airlines was 28.6 gallons in 2000 and 22.5 gallons in 2011. 50. Although network costs and opportunities are relatively difficult to estimate, they ought not to be ignored when looking at an overall profitability profile, which is explored in Borenstein (2011). For instance, Significant capital may be tied to routes that are locally unprofitable but that contribute strongly to network profitability because they feed the network with a high percentage of connecting short-haul passengers. See Baldanza (2002) and also Belobaba (2002), in which the latest embellishments to network revenue maximization models are discussed. In part, the complexity of such network optimization models arises from the fact that two relatively low-fare local itinerary flight legs might contribute more revenue than one high-fare connecting passenger traveling on both legs. Earlier versions of yield management models simply analyzed pricing strategies on single origin to destination (O & D) legs without regard for network profitability effects. Modern O & D systems are designed to counter the number of inexpensive and unprofitable fares that can be found on the Internet. A carrier would rather book a short-haul low fare to a passenger who continues on to a more expensive long-haul segment than to a passenger

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just on the short-haul. See Perez and Trotman (2006) and Sengupta and Wiggins (2014). Holloway (1997, p. 91) notes, “[B]lock speed (i.e., average speed chock to chock) is more important than average cruising speed on short-haul routes, but the two correspond more closely as stage length increases because a greater portion of longer journeys is spent at cruise rather than maneuvering. . .on the ground.” As an example of average hourly productivity, a plane flying at an average speed of 600 km per hour and carrying a 20-ton payload produces 12,000 ton-km per hour. Passenger weights, including free and excess baggage, are conventionally assumed at either 90 kg or sometimes 95 kg (209 lbs) each. Wei and Hansen (2003) found that “for any given stage length there is an optimal size, which increases with stage length.” See also Hirsch and Macpherson (2000) on labor market premiums. Fee schedules for airspace overflight rights vary by country and may be computed using maximum takeoff weight, distance, use of traffic control services, and other factors. As described in Carey (2007), overflight fees are balanced against additional fuel costs, weather and runway conditions, average speed, and other variables as computed with sophisticated software. At overcrowded hubs, the ratio of block-hours to air-hours rises. As Pearson and Strahler (1995, p. 426) note, every 0.01-point increase in the annual ratio collectively costs the nine largest U.S. airlines $150 million in additional operating expenses. This datum is found in U.S. DOT Form 41. Despite such costs, however, even overcrowded hubs help protect traditional regional strongholds even while making it difficult for lines to naturally expand into new geographic markets. Mergers then appear to be the best and sometimes only way to expand and strengthen a service network. See also Murphy (2001), and McCartney (2002, 2013a). Nesbitt (2002) notes that productivity (or output measured as RPMs per airplane day) for each type of aircraft is governed by seats, load factors, utilization (hours flown per day), and speed expressed as: RPM/airplane day ¼ number of seats times passenger load factor times block utilization times block speed. This means that, all other things held constant, a 5% increase in speed will have the same affect on RPMs as a 5% increase in load factor. An example of the trade-offs involved is that schedule planners will often have an airplane wait for a desirable departure time so as to increase the load factor, but this reduces utilization, one of the four basic productivity elements. Point-to-point carriers will thus typically have higher aircraft utilization rates than hub carriers. On a global basis, as of 2003, there were 13, 593 aircraft in commercial fleets. See Tatge (2003) and McCartney (2012c). Dresner (2002) and Windle and Dresner (1992) note that airline performance metrics are actually much more complicated than this formula suggests. Productivity, which is affected by average stage length, percentage of cargo carriage, and other factors, should be further analyzed in terms of labor, flight equipment, or other inputs such as revenue ton-kilometers per gallon of fuel.

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55.

56.

57.

58.

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The only way to compare productivity across firms or over time is by taking total factor productivity (TFP) into account. To calculate TFP, overall input and output indices are created by weighing the individual inputs and outputs, with each input weighed by its share of total (or variable) cost and each output weighed by its share of revenue. TFP is then calculated by dividing total output by total input. See also O’Connor (2001). Productivity depends greatly on the number of hours per day that equipment is used. Southwest has been especially effective with its short-haul operations but as the 2020 bankruptcy of Norwegian suggested this strategy does not work well on long-haul operations. See Lunsford (2008). Michaels (2012) notes that price discounts for new planes vary between 20% and 60% off listed prices. The reason prices are difficult to determine is that contracts, which run to hundreds of pages, are complex and usually cover financing structures, inflation escalation formulas, engines, cabin interiors, training programs, and spare parts. Also, large early buyers of new models can negotiate better deals. Carey (2012), however, writes that Delta maintains a complex mix of older jets which burn more fuel and require more rigorous frequent inspections and a large inventory of spare parts but are less expensive to acquire and can save money when acting as replacements for smaller 50-seat regional jets. A CBS 60-Minutes broadcast of April 15, 2018, “Flying Under the Radar,” exposed maintenance problems on discount carrier Allegiant. On sluggish sales of the Airbus A380 see Mouawad (2014a) and Wall (2019). Button (2010, p. 244) writes that another reason for survival is that the structure of the business has changed: “[A]ircraft are now seldom owned by the carriers but are leased . . . the airlines are increasingly becoming ‘virtual carriers’ that act to bring together packages of services owned by others and that are encumbered with few fixed costs themselves in the traditional economic sense.” An example in transportation would be the cross-elasticity of demand for airline service versus rail service between New York and Washington, D.C. Given that the travel time from center city to center city is probably on the average about the same using either rail or air, any noticeable change in the price of rail or air service would likely have a measurable effect on demand for the competing service. Note also that the journey time elasticity of demand, which applies to all transportation modes, is especially important to the business travel segment. Doganis (1991, p. 225) explains: “An examination of price elasticities in some studies shows this to be true. Whereas nonbusiness travel tends to have price elasticities greater than minus 1.0, the price elasticity of business travel is less than minus 1.0 and in the case of first-class travel on the North Atlantic it was as low as minus 0.65.” According to the Global Business Travel Association, business travelers in 2015 spent about $1.25 trillion for airfares, accommodations, and other related items. Dargay (1993, p. 87) suggests that demand elasticities vary widely and are often influenced by the type of model and data used, the functional

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specification, degree of aggregation, and several other factors. However, there is also the possibility of “nonsymmetric” or “irreversible” price effects or “hysteresis” in the demand relationships. In other words, “consumers may not respond similarly to rising and falling prices, as it is traditionally assumed, but instead react in a more complex fashion dependent not only on the direction and magnitude of the price change, but also on previous price history. If this were the case, the elasticity itself would be dependent on the evolution of prices so that empirical estimates would be sensitive to the time period used for the analysis.” Klophaus (2009, p. 89) studied fuel price elasticities for trips between cities. The average price elasticity for business travelers was .07 and for leisure travelers 1.52. A related demand aspect is flight overbooking, which is discussed in Belobaba et al. (2009, pp. 93–5). A model for overbooking would include a variable for maximum physical capacity (CAP); authorized capacity (AU) which is the maximum boarding that the airline will accept; an overbooking factor (OV) where OV >1.0, is to be determined such that AU¼CAP x OV; a no-show rate (NSR); and a confirmed booking number (BKD) that is counted just prior to check-in. In a simple deterministic model, AU¼CAP/(1-NSR). To illustrate, if CAP ¼ 100, NSR ¼ 0.20 then AU ¼ 125. Probablility estimates will then be applied to the AU. 60. Stopher and Stanley (2014, pp. 97–101) explain that speed, v, can be measured in several ways including instantaneously (at the moment); by an average of the speed of all vehicles moving through a length of the network over a period of time, which is the time mean; and by the average speed of all vehicles in the length of a network at a particular moment, which is the space mean speed. 61. Boyar (1997, p. 288) notes that several methods have been proposed for dealing with problems of allocating nonunique fixed costs. “One way of eliminating the arbitrariness of the residual fixed cost allocation is to accept some inefficiency and to use a second best pricing scheme .... Second best cost allocation, also called Ramsey pricing, recovers fixed costs by marking up the variable costs of different user groups by different amounts determined by the elasticities of demand. Under Ramsey pricing all user groups pay something toward the fixed costs of the system, but those who have the lowest elasticity of demand are given the highest markups over marginal cost. That is, those groups with fewest alternatives will have prices raised over marginal cost by the largest amount.” Application of this is seen, for example, in the computergenerated rankings of flight cancellations due to bad weather, as explained in Sapporito (2014). 62. In sophisticated models, such changes would then have to be reflected in estimated technical change coefficients. See also Janić (2000). Former Southwest Airlines CEO, Herb Kelleher, in Reingold (2013), says that even ignoring capital costs and everything else, high fuel prices alone can make flying a route unprofitable and that the great competitiveness of the industry comes from the ready ability to move the proportionately large capital investment embodied in planes to any place in the world.

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63. According to Eurocontrol, which tries to coordinate European air-traffic control, if capacity stays constant, every 1% rise in traffic produces a 5% increase in delays. See The Economist, February 5, 2000, Michaels (2011b), and Clark (2012a) who writes of the difficulties of implementing a master plan known as the Single European Sky. Middle East carriers also face increasing airspace limitations which are a brake to growth as explained in Jones and Michaels (2013). 64. Wald (2000) writes that landing slots at New York’s La Guardia were worth about $two million as of the year 2000. Such fees had been historically based on weight (at La Guardia, $5 per thousand pounds or $2000 for a Boeing 767) but may in the future be based on other criteria. In relation to this, see also a law known as AIR 21 and Kolker (2001). As of 2008, British airlines began to take account of slot values on their balance sheets. As noted in the Wall Street Journal of May 16, 2008, a pair of peak time slots at Heathrow are valued, for example, at between £25 and £30 million. And in a 2011 auction, JetBlue paid $32 million for eight takeoff and landing slot pairs at New York’s LaGuardia. See also Peters (2008) on proposed auctioning of landing and departure slots at New York airports, Morrison and Winston (2007), Nicas (2013), Molnar (2013), Mann et al. (2015), and Cameron (2019) on allocations of slots and the IATA‘s Worldwide Slot Guidelines system. Button (2010, Chap. 9) provides reviews the economic issues that enter into slot allocations and valuations. Probably the most valuable landing slots are at Heathrow Airport, where Continental Airlines paid $209 million for four pairs in 2008. As of 2011, Virgin Atlantic controlled 288 takeoff and landing slots, 3% of the total. Evans (2013) writes that Heathrow is at a breaking point (98% of capacity), unable to further process the tremendous demand to handle more traffic. See also Dresner et al. (2002), Bernadino (2009), Brown and Jones (2013), Carey and Nicas (2013b), and Michaels and Cauchi (2013). 65. In thinking about the peak-load pricing problem Glaister (1981, p. 68) suggests, “in the absence of queues, the service is obtained by those who value it most relative to other things. If cheap fares are provided at times of severe peaks then the cost to society of building the capacity to cope with these peaks may be very much higher than the values placed on the service even by those who value it most. . .Long run marginal cost pricing (i.e., peak pricing) together with a suitable system of compensation could make everybody at least as well off as under constant pricing.” As Ingersoll (1999) suggests, passenger facility charges (PFCs) are often politically contentious. See also Williamson (1966) Bishop and Thompson (1992), and Carey (2017). 66. McDonald (2005) indicates that JetBlue’s pricing strategy is simple: Take the number of seats in an aircraft and multiply by flight length in miles to derive ASM. Then multiply by the estimated cost per ASM, which gives a cost per flight. For example, the flight is 1000 miles, the plane has 150 seats, the cost per ASM is 8 cents, and an average load factor of 80%. The cost of the flight would be $12,000 ($150,000 x 0.08). Divide the average cost by the expected number of passengers (150 x 80% ¼ 120). This gives a cost per passenger of

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$100 ($12,000/120). Now add a target operating margin of 10 percent and then a 7.5% excise tax to find the final ticket price of $118.25. See also Jiang and Hansman (2006) concerning industry profit cycles and Carey (2013c) on JetBlue’s change in marketing strategy. 67. Jenkins (2004) further notes that “the airline industry produces an irresistible urge for activity in politicians . . . Airlines are not incompatible with capitalism so much as incompatible with modern antitrust policy, which assumes that ‘more competitors’ is the same thing as ‘more efficiency.’” Environmental costs will also include those for noise and air pollution. Who bears the cost is an entire economic topic in itself and is covered in Button (2010, Chap. 8). Nobel economist Ronald Coase noted that either the polluters or those adversely affected might theoretically allocate environmental property rights. Economist Arthur Pigou’s approach is that the polluter ought to pay for any such damages via taxes and fees. Coase’s approach involves tradable rights. 68. Mouawad (2012d) discusses the complexities of food service provision and associated costs. Airline catering is a $13 billion-a-year business, with LSG Sky Chefs the largest caterer. In 2010, LSG provided 460 million meals for 300 airlines operating kitchens in 50 countries, while GateGourmet, the second-largest caterer, served 9700 flights in 28 countries. A decision to trim an ounce from its steaks saved Delta $250,000 a year, removing a strawberry from salads served in first class on domestic routes saved $210,000 a year. But a one-cent increase in peanut prices adds $610,000 to costs given that Delta passengers consume 61 million bags of peanuts each year. Similarly, according to a Wall Street Journal article (June 17, 2013) about United, a switch from whole to split cashews in the heated nut cocktail served in first class saved $200,000 a year and Mouawad (2013b) notes that reduction of 2.2 pounds (~1 kg) of the weight of a seat saves as much as $800 a year on fuel cost per seat. This is seen, as Wall (2014) explains, in British Airways‘using lighterweight seats to shed 1000 pounds per plane and experiencing annual fuel-cost savings of as much as $56,000 per jet. On average, planes might burn five gallons of fuel per mile, even on empty flights. 69. Airlines arguably promote the notion that ancillary fees allow customers to improve aspects of the flying experience that they most value—flexibility, time, comfort, and entertainment. This differs from the historical approach in which prices included all services for all customers and price differentiation was mainly by cabin and time of purchase. Maynard (2010) and Sharkey (2011) note that most fee revenue is not subject to the 7.5% excise tax fee levied on fares. For passengers, ancillary fees for reservation changes and checked bags can account for an additional 20% of a ticket’s cost. For airlines checked bag and reservation change fees are now many multiples of what they were in the early 2000s, i.e., in 2009, $2.7 billion and $2.4 billion, respectively. According to the U.S. Department of Transportation, passenger ticket prices in 2011 accounted for only 71% of U.S. airlines’ total passenger revenue as compared to 88% in 1990. See also Carey (2011a), Clark (2013a), Mouawad

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71. 72. 73.

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(2011a, 2013c), and White (2013). Ancillary fees now also extend to food and beverages, seat upgrades, duty-free, lounge access, vacation packages, and in-flight connectivity. McCartney (2018c) writes that in 2017 reservation-change and cancellation penalties accounted for more than half of net airline profits. U.S. airline fee earnings of around $20 are about twice what international airlines earn. McCartney (2010b) uses these points to illustrate why long-distance trip prices are often much less per mile than prices for short-distance trips. See Belobaba et al. (2009, p. 69) and Belobaba and Cheung (2004). A U.S. General Accounting Office (GAO 2001) report (cited in Forsyth et al.) lists these operating and marketing barriers. Much of the literature also discusses a related concept developed by Areeda and Turner (1975)—the AreedaTurner test—which as Lall (2005, p. 39) notes, “suggests that under perfect competition prices must equal marginal costs and under imperfect competition they must exceed marginal cost. So any price below short-run marginal costs must be deemed predatory.” A similar test involves avoidable costs and is attributed to Baumol (1996). Knorr and Arndt (2005) conclude that “the effectiveness of strategic barriers to entry has long been overestimated . . . infrastructure bottlenecks—which, in turn, are overwhelmingly caused or at least amplified by ill-designed allocation rules and access regulations—must be seen as the only true barrier to entry . . . Not only do these rules and regulations shield inefficient incumbents . . . but . . . established carriers can only erect meaningful strategic entry barriers upon this base.” Lall (2005, p. 37) quotes William Landes speaking about Nobel laureate Ronald Coase, who “said he had gotten tired of antitrust because when the prices went up the judges said it was monopoly, when the prices went down they said it was predatory pricing, and when they stayed the same they said it was tacit collusion.” This view is largely consistent with what is known as the Chicago School, which is skeptical about government intervention in competitive processes. Some economists would indeed contend that the incumbent predator may harm itself as much or more than the upstart LCC because losses during the period of rivalry may never be recouped afterward and resources that are better used elsewhere are diverted. See also Tan (2016). The relevant body of economic theory and law, known as antitrust, that has been historically developed in the United States beginning in the 1890s goes by several other names and has different legal underpinnings in other countries. In the European Community, regulation of competition is governed by the EC Treaty, also called the Treaty of Rome of 1957. Articles in this treaty prohibit direct or indirect imposition of unfair selling prices and also abuse of dominant position by a carrier. In the United Kingdom, the counterpart is the Competition Act of 1998, and in Australia, the Trade Practices Act of 1974 serve the same goal of attempting to discourage the lessening or elimination of competition. Canada has continually amended its one federal antitrust statute, The Competition Act. See also Peoples (2012, 2014), Zhang et al. (2013), and Nicas et al. (2015) on a collusion probe by the DOJ. Tabacco (2017) suggests that the

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77.

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79.

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industry ought to be seen a a natural oligopoly, with each market being dominated by one to three carriers regardless of market size. See Tabacco (2017), Shaken and Sutton (1983), and Aguirregabiria and ChunYu (2010). A simple formulation of this model would be Tij ¼ kPiPj/Dij, where Tij is the traffic between points i and j, Dij is the distance, k is a constant, and Pi and Pj represent the populations of the two cities. A variation of the same concept, discussed in West (2017, pp. 347–50), is that the number of visitors to any attraction scales inversely as the square of both the distance traveled and the frequency of visitation. See also Boyar (1997, p. 84) and Abdelghany (2009). Nicas and Carey (2012) write that in the decade up to 2012 airlines added 10,000 new routes, a 37% increase. Early forecast methodology used to evaluate the input of capital-intensive infrastructure investments were known as four-step models that understood and accepted, yet did not reflect, the derived demand aspect of travel. As discussed in Hensher and Button (2000) and Hall (1999), newer activitybased approaches provide richer and more holistic frameworks in which travel is analyzed as a pattern of behavior related to and derived from differences in lifestyles and activity participation. Such models reflect the scheduling of activities in time and space. Suryani et al. (2010) present a system dynamics approach to forecasting passenger demand and terminal capacity expansions. When all is said and done, and following Holloway (1997, 2003), the preceding concepts of productivity and profitability, may be handily summarized in the following expression: Output X Unit cost > < Traffic X Yield ¼ operating performance (i.e., loss or profit). Even in the boom years of the late 1990s, the domestic industry’s return on capital was a relatively meager 8%, below that for autos and computers. Zuckerman (2001a) writes that since deregulation in 1978 the industry has not earned a return exceeding its cost of capital and that some 200 or so airlines have disappeared. See also Pearce (2013) which is an in-depth study of why since 1970 “air travel has expanded ten-fold and air cargo 14-fold, compared to a three to four fold rise in world GDP. Yet over this period airlines have only been able to generate sufficient revenues and profit to pay their suppliers and service their debt. There has been nothing left to pay investors for providing equity capital. . . .Air transport. . .destroys value for its airline equity investors.” Werner (1999, p. 189) notes “that there are three commonly used measures of the amount, or ‘degree’ of leverage in a company. All three are economic elasticities, the percentage change in one variable in response to the percentage change in another. They may be calculated from an income statement organized to identify fixed and variable costs.” The degree of operating leverage (DOL) indicates the percentage change in earnings before interest and taxes (EBIT) for a given percentage change in revenues. The degree of financial leverage (DFL) is the percentage change in earnings per share (EPS) for a

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81.

82.

83.

84.

85. 86.

87.

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given percentage change in EBIT. And the degree of total leverage (DTL) is the percentage change in EPS for a given percentage change in revenues. Baggaley (1999, p. 319) observes that the median interest coverage in 1997 for passenger airlines rated investment grade by Standard & Poor’s was 4.6x, but for those rated in the BB category, it was 3.8x, and for those in the B of CCC categories, the median was 2.4x. Net debt to revenues for domestic system majors has ranged from a low of 10.9% in 2010 to a high of 34.4% in 2002. Carey (2003) observes that the ten largest airlines in the U.S. increased their balance-sheet debt to $56 billion at the end of 2002 as compared to $27 billion at the end of 1999 and that when off-balance sheet aircraft leases and airport rental payments are included the industry’s adjusted debt load amounted to $125 billion. Cross-sectional studies such as those by Garvett and Hilton (2002) suggest that three factors in combination relate well to an airline’s profitability: (a) yield management effectiveness; (b) ownership/length of tenure; and (c) unit revenue. Stage length and customer satisfaction are also somewhat important. However, on a cross-sectional basis, other factors such as costs and productivity are not good predictors of airline profitability because data includes both profitable and unprofitable high-cost and low-cost carriers. Depreciation is a complicated subject, with most companies needing to prepare two sets of financial statements. For external use, the depreciation method of choice might be used, but for tax reporting purposes, the IRS requires that all U.S. companies adhere to the standardized depreciation method known as the Modified Accelerated Cost Recovery System (MACRS). MACRS does not take salvage values into account. See also Vasigh et al. (2015, pp. 182–93), Doganis (2002, p. 4), and https://www.iata.org/en/iata-repository/publications/ economic-reports/why-it-matters-that-the-airline-industry-stays-value-creating-for-its-investors/ See Baseler (2002). Insurers, banks, and other financial institutions may invest in equipment trust obligations or certificates adequately secured and evidencing an interest in transportation equipment, wholly or in part within the United States, if the obligations or certificates carry the right to receive determined portions of rental, purchase, or other fixed obligatory payments to be made for the use or purchase of the transportation equipment. An E-ETC prospectus will provide a description of the numbers and types of planes to be financed, projections of annual depreciation rates, and loan-tovalue ratios obtained from independent appraisals. Such ratios are used to subdivide the bonds into credit tranches, with Class A certificates having the most conservative ratios of generally 40% to 45% of debt relative to appraised value as compared, say, to Class C certificates with ratios of 60% to 70%. Additional variations would include callability and sinking fund features. Lunsford and Carey (2003) explain that leveraged leases using E-ETC financing structures became popular in the 1990s. “. . . an equity provider puts up 20% of the cost of the airplane, enabling it to have ownership of the

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airplane. As owner, the equity provider can get the tax benefits of depreciating the aircraft over a seven-year period . . .The remaining 80% of the loan—the debt portion—is borne by the airline, which finances all or part of it by borrowing from investors.” Also, E-ETCs are usually issued on a pool of around twenty or so airplanes and the A tranche of the notes carry lower interest rates than the B or subsequent tranches because the A tranche is the least risky debt as it is the most likely to be repaid. Of course, when the market sours, as it did after September 11, 2001, the 20% equity holders would be the last to be repaid and the first to be wiped out. Many of the certificates issued in the 1990s were priced at interest rates of 1.25% to 5% above comparablelength Treasury bonds for periods ranging from five to twenty years. Lunsford et al. (2004) write that bankruptcy filings have been used by airlines to negotiate more favorable lease terms or to convert long-term leveraged leases into shorter-term operating leases. Lunsford (2004) further describes the so-called Cape Town convention that makes “it easier for creditors to call in the repo man, even when the plane is located in some countries where that is an impossibility.” Prior to this treaty, large financial institutions had avoided airplane loans because of the risk that the collateral asset could be flown to countries with laws that shielded the asset from creditors. The reasons bankruptcies and losses have not reduced the number of major carriers is discussed in Wessel and Carey (2005). The 2011 bankruptcy filing for American Airlines is discussed in Cameron (2011) in which it is shown that American’s labor expense in cents per available seat mile was 4.1, as compared to 3.6 for Southwest, 3.4 for United/Continental, 3.3 for Delta, 3.0 for US Airways, and 2.5 for JetBlue. According to Morrell (1997, p. 187), the first international securitization of aircraft was offered by Guinness Peat Aviation (GPA) in 1992. Fourteen aircraft valued at $380 million were leased. Equity investors in this would get a 10% to 12% return in annual dividends plus a share in any residual value from the aircraft at maturity. Until GPA ran into financial difficulties (from inadequate capitalization and overleveraging), along with International Lease Finance Corporation (ILFC) it was one of the two dominant firms in the aircraft leasing business. GPA’s assets were acquired by General Electric Capital Asset Services (GECAS) and, with a fleet of 1300 aircraft as of 2018, GECAS became one of the two major leasing firms. ILFC was acquired by American insurance giant AIG in 1990 and was sold to AerCap Holdings of the Netherlands in late 2013. ILFC added nearly 1000 aircraft to AerCap’s 373. The story of ILFC’s founder, Steven Udvar-Hazy, is described in Wayne (2007) and in Lubove and Rothman (2012). Zimmerman (2009) discusses the firm’s financing problems, and Cameron (2011), the company’s revival. Steven UdvarHazy subsequently went on to found Air Lease Corp. As of 2011, IFLC had 933 aircraft and 23% share of market. See Ng and Michaels (2011), Bryant and Sutherland (2018) and Gryta and Gottfried (2019) on GECAS, Fletcher and Wall (2018), and Sindreu (2019b). In March 2021 GECAS was sold to AerCap for $30 billion.

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According to Lunsford (2002), ILFC “makes the bulk of its money by renting out airplanes for the first five to seven years of their life at rates of between 9% and 12% of their value annually. At around five to seven years, the companies either re-lease the airplanes or sell them on the secondary market. Meanwhile, the value of the airplanes can be written down quickly, reaping big tax benefits for the leasing company.” Such lessors receive discounts on large orders for planes and make money by renting them to carriers for various lengths of time (a few months to several years) at rates that more than cover the discount. Carriers can thereby obtain strategic flexibility and use of equipment that they might otherwise not be able to afford. Used aircraft can be sold for as much as 85% of original sticker prices, and with a $100 million plane, for example, “a leasing company can bring in as much as $84 million over the life of a seven-year lease. If the airplane is sold used for $85 million, the total cash generated would be $169 million, leaving the company with a $69 million profit on the aircraft before accounting for the cost of capital over time.” Michaels (2010a) indicates that as of 2011, lessors “own one of every three jetliners flying, but Boeing expects that to reach one of every two within ten years.” This compares to 23% in 1990. Smaller public companies in this area include Aercap Holdings, Aircastle, Atlas Air, FLY Leasing, and Willis Lease Finance. Atlas is the largest wet-lease (ACMI) provider, explained in note 89. Other competitors include AWAS, Aviation Capital Group, and Doric GmbH in Germany. The entire leasing business structure changed when bank lending capacity diminished after 2008 and U.S. capital markets became the key funding source based on E-ETCs and Export Credit Agency (ECA) bonds. Bisserbe (2013) notes that credit export agencies and capital markets respectively accounted for 23% and 14% of deliveries in 2013, with the remainder covered by airlines’ cash. See also Airfinance Journal (2007), Stone et al. (1999), Lintott (1999), Gawlicki (2000), Jenkins (2010), Michaels (2010b, c, 2011a), Murphy and Desai (2011), and Cameron (2013) about jet-leasing for large aircraft deliveries. Mouawad and Clark (2010) discuss export credit financing. 88. Holloway (2003, p. 273) breaks down direct operating costs as (a) capacity costs that include aircraft-related fixed costs such as insurance and flight specific costs without payload such as airport charges and per cycle maintenance costs, and (b) traffic costs that are payload-specific and include fuel, catering, handling charges and travel agencies’ commissions and overrides. 89. Escapability of the first type can be done by, say, reducing the number of weekly departures from an existing base station, while escapability of the second type can be achieved through reduction of fleet size or changing of equipment financing strategies depending on changes in long-term interest rates. All such decisions are facilitated in an accounting sense by classifying costs more specifically into variable (immediately escapable) and fixed components (which are direct operating costs that do not vary over the short run with particular flights or series of flights). 90. See Vasigh et al. (2015, pp. 20–1).

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91. The lease versus purchase decision is discussed in more mathematical detail in Stonier (1998). 92. Another type of operating lease is known in the industry as the wet lease, which includes aircraft, crew, maintenance and insurance (ACMI) as opposed to a dry lease, which only includes leasing of the aircraft. Wet lease is similar to the chartering of aircraft except that the lesee would have the necessary operating licenses and permits and would operate the wet-lease flights with its own flight designation. Although ACMI transactions are more complex, the margins tend to also be higher because of the greater tailoring of the contracts. Leasing is extensively covered in Vasigh et al. (2015, pp. 496–534). See also Wall and Michaels (2019). Although the criteria for classifying leases appear in theory to be unambiguous, in practice, there can be different interpretations. Over the years, the FASB had attempted through the issuance of several additional statements to clarify certain aspects of FASB statement 13. In the case of a capital lease, however, FASB 13 says that “the lessee shall record a capital lease as an asset and an obligation at an amount equal to the present value at the beginning of the lease term . . . [and] . . . the asset shall be amortized in a manner consistent with the lessee’s normal depreciation policy except that the period of amortization shall be the lease term.” To be classified as a capital lease, the lease must meet one or more of the following criteria. Otherwise, it is an operating lease. Also, sale-leaseback transactions may be of either type depending on the criteria met by the lease. • A capital lease transfers ownership of the property to the lessee by the end of the lease term. • It contains a bargain purchase option • The lease term is equal to 75% or more of the estimated economic life of the leased property. • The present value of the minimum lease payments, including certain adjustments, is 90% or more of the fair value of the leased property at the inception of the lease. A capital lease will thus transfer substantially all the benefits and risks inherent in the ownership of a property and will directly appear as an asset and a related liability on the balance sheet and with financial statement footnotes providing details on minimum obligations. In contrast, with an operating lease, which is cancelable and requires the regular payment of rent, equipment assets and liabilities do not appear on the balance sheet (although information about minimal obligations would appear in financial statement footnotes). Lease rentals are charged evenly to the income statement over the lease term. This difference may materially affect the comparability of transportation service company balance sheets and financial ratios. For example, in the first year, expenses for a lessee under a capital lease (i.e., interest expense and depreciation) are greater than expenses under an operating lease (i.e., rent expense). In later years, however, as the interest component on a capital

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93.

94. 95.

96.

97.

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lease diminishes, annual expense becomes greater with operating leases. Reported period net earnings would, all other things equal, then depend on a company’s mix of leasing versus asset-purchasing strategies. An important implication for lenders is that airlines in bankruptcy are able to reject their aircraft leases and return planes to their owners without financial penalty. See Weil (2004) In the proposed changes, this accounting would differ from most real estate leases, in which the value would be based on the expected size of lease payments over the life of the lease. See Norris (2013) and the Wall Street Journal, November 11, 2015. The new lease accounting will boost reported leverage for airlines and restaurant chains. See Eaglesham (2019). Quote is from Morrell (1997, p. 49), who further notes that U.K. rules for accounting for leases define a financial/capital lease—also known as full pay-out lease—requiring placement on the balance sheet as: “a lease that transfers substantially all the risks and rewards of ownership of an asset to the lessee. It should be presumed that such a transfer of risks and rewards occurs if at the inception of a lease the present value of the minimum lease payments amounts to substantially all (normally 90% or more) of the fair value of the leased asset.” In addition, “a more difficult problem occurs with extendible operating leases, which usually have a lease term that covers the economic life of the aircraft, but give the lessee airline the opportunity to break the lease at no penalty . . . at various intervals over the term. British Airways have a number of aircraft leased in this way, and originally left them off balance sheet.” U.S. GAAP and International Financial Reporting Standards (IFRS) have begun to converge but some differences remain. Both GAAP and IFRS recognize the economic substance of leases for both the lessor and lessee. But IFRS terminology refers to leases as finance leases; GAAP as capital leases. Under GAAP, leased assets consist only of property, plant and equipment, whereas under IFRS, other types of assets, including leases to explore mineral resources and to exploit other licensed property agreements (including movies and manuscripts) may be included. Also, GAAP is more rules based as compared to IFRS. Other differences for lease accounting are discussed in Siegel and Shim (2010). As Morrell (2001, p. 200) notes, in the Japanese Leveraged Lease (JLL), 20% to 30% of the financing comes from Japanese institutions, with the remainder from banks, whereas leveraged leases in the U.S. provide maximum benefits for aircraft based and registered in the United States. Non-U.S. carriers may also be able to make lease deals similar in structure to that of the JLL variety by implementing the provisions of the U.S. Foreign Sales Corp. (FSC). As explained in Vasigh et al. (2015, p. 147), IFRS and GAAP differences involve: • last in, first out (LIFO) inventory costing, which is precluded in IFRS

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• IFRS uses a single-step method for impairment writedowns whereas GAAP uses a two-step method. • There are different probability thresholds for contingencies and curing of debt covenant violations after year-end. It is expected that both methods will gradually converge. See also AICPA (2008). 98. For example, see “Who Else Is Hiding Debt,” Business Week, January 28, 2002. 99. Technically, this is done on the income statement by increasing passenger services expenses by the incremental costs (including food, fuel, taxes, etc.) of carrying the award passengers at a future date while the same amount is recorded on the balance sheet as an accrued liability. Then, when the award passenger is carried, the incremental cost is deducted from expenses and the liability on the balance sheet is extinguished. Using this method, the operating profit in each year is not distorted by the award. Since 1999, the methods follow Securities and Exchange Commission Staff Accounting Bulletin 101, which requires that revenue from sale of mileage credits is deferred and recognized when transportation is provided. Such frequent flyer/traveler award programs began in the early 1980s and were originally patterned on the “green stamps” that food retailers used in the 1950s and 1960s to encourage customer loyalty. By 2008, airlines had given away many more miles than could be accommodated by increases in capacity. The programs had become an important source of profits, in some cases up to $1 billion a year, but also had evolved from being an airline’s loyalty program to a currency program for the customers of other companies in other industries. Generally, these other companies can purchase the miles at prices of between one to three cents. The number of unused miles has also become staggering. Delta had 488 billion miles, and American 613 billion by the end of 2007. AMR’s American Airlines unit awarded 200 billion miles, while only 150 billion were redeemed. See also Garvett and Avery (1998), Business Week, March 5, 2000; Elliott (2004); Trottman and Carey (2007); Sidel and Carey (2008); Stellin (2008); Maynard (2009a), and especially Vasigh et al. (2015, pp. 154–73) for detailed explanation. 100. Calculation of the level of deferred revenue depends on assumptions concerning the proportion of points to be redeemed and the mix of awards to be taken up and also on the yield assigned to the mileage or points attributed to the expected take-up of free travel awards. As noted in the IATA Accounting Guide, the redemption rate is affected by the threshold of points required before a member can redeem a reward, the time until award expiration, and the award redemption experience of the airline. Many airlines estimate the likelihood of redemption using algorithms based on historical patterns. For example, according to the Alaska Air SEC financial statement report for 2010, the company had 117 billion miles outstanding, resulting in an aggregate

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liability and deferred revenue balance of $673.9 million. The assumptions in accounting for the Mileage Plan include the following: the rate at which sales proceeds from sold miles are deferred the number of miles that will not be redeemed for travel (breakage) the number of miles used per award (i.e., free ticket) the number of awards redeemed for travel on our airlines versus other airlines: the costs that will be incurred to provide award travel 101. Export Credit Agency (ECA) financing accounted for nearly one-third of new aircraft deliveries in 2012. Much of this comes under the Aviation Sector Understanding (ASU) which significantly changed the economics of ECA guarantees. See also Jenkins (2011). 102. The value of gates, routes (especially long-haul), and landing slots (such as those at London’s Heathrow) has increased enormously as airlines have tried to increase the frequency and reach of their services. As of 2008, according to Michaels (2008c), a pair of takeoff and landing slots at Heathrow had cost more than $50 million, at least double the price ten years earlier. Control of a large percentage of gates and slots at an airport can give the airline a predominant, almost monopolistic, position that would usually translate into greater pricing power and therefore higher valuation. In the early 1990s United bought Pan Am’s Heathrow landing rights for $400 million and American bought TWA’s for $445 million. At around the same time, Delta bought Pan Am’s Atlantic routes for $1.3 billion. And in the mid-1980s, United bought Pan Am’s Asia routes for $750 million. However, as Murphy (2001) notes, federal legislation (AIR-21) requires airports to submit competition plans; airports that are found by the DOT to operate in an anticompetitive manner may lose improvement grants. Strategic importance of the control of gates is discussed in McCartney (2005b). 103. The amount of environmental impact from aircraft engines releasing heat and particles at high-altitudes is debatable but there’s no doubt that there is some affect. Scheduled flights in the U.S. burned around 17 billion barrels of fuel in 2019. In Mouawad and Davenport (2015, 2016) the estimate is that aviation contributes 2% of global emissions. Aviation activity releases of carbon dioxide may—depending on future political, economic, and scientific assessments of climate change—result in various new taxes and fees being imposed on the industry. See Lee (2009) in Gössling and Upham (2009), Davenport and Mouawad (2015), European Parliament (November 2015), “Emission Reduction Targets for International Aviation and Shipping,” IP/A/ENVI2015–11, Sivak (2015), Mouawad and Cardwell (2015), Johnson (2021), and Phillip (2021) on biomass fuel, Ryan and Mathis (2020) cover Airbus’ plans to use hydrogen fuel. Fountain (2016b,c), Mouawad and Davenport (2016), Fountain (2016a), Wall (2016), McCartney (2019b), and Sindreau (2019a). A 2017 study also showed that climate change is likely to increase turbulence in flight as mentioned in Wichter (2017). Ives (2017) and Pattani (2017) write of

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105. 106.

107.

108.

109.

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the costs to the industry and airports of global warming that include need for lighter loads, flight delays, and potential flood prevention. Anything less than a 20% discount to estimated value typically does not provide enough leeway for the uncertainty of a transaction occurring and for the possibility that costs of mounting an acquisition campaign could be quite high. Great detail on value investing asset and earnings accounting adjustments appear in Greenwald et al. (2021). Availability of pooling versus purchase accounting and additional tax-related issues had also often had a bearing on the size of the trading discount. See Sect. 2.4. See Mouawad (2013e), Lubben (2013), Porter (2013), and Crandall (2013). As of 2020, some major airlines and/or airline groups (including recent merger partners) by region are as follows: North America: American (US Airways), Delta (Northwest), United (Continental), Southwest (AirTran). Europe: Air France (KLM), British Air (Iberia), Lufthansa (Austrian, Brussels, Swiss) Other (Aer Lingus, Alitalia, Air Berlin). South America: Avianca (Taca), Azul, GOL, LATAM. Middle East: Emirates, Etihad Asia/Pacific:Cathay, China Air, Quantas, Singapore. Thai. As of early 2015, the four largest shares of European air traffic in percent were Lufthansa Group (13.0%), Ryanair (9.9%), International Airlines Group (8.1%), and Air France-KLM (8.1%). Shares in the U.S. were: Southwest Airlines (21.2%), Delta (21.2%), United (15.6%), and American (13.5%). Discount carriers including AirTran, ATA, Frontier, JetBlue, Southwest, and Spirit had grown to account for a 20% share of domestic air carrier capacity in 2004 as compared with 10% in 1995. But by 2008, ATA, Frontier, Aloha Airgroup, and Eos had filed for bankruptcy. In all, from 2000 to 2014, there were seven major airline bankruptcies and six major mergers. Such filings have included Eastern Airlines (1989), America West (1991), Pan American (1991), TWA (2001), United (2002), Delta (2005), Northwest (2005), Frontier (2008). The first two rules are intuitively obvious. As for the third, Petzinger (p. 189) goes on to explain that marginal pricing is a worthy strategy for the last seat sold but not for selling the first because by selling everything so cheap, total revenue is not maximized and the value of the product in the mind of the consumer is debased. Quote is from Lowenstein (2002), but it conflicts with Gil and Kim (2016) who found that competition from LCCs increases the service quality of major incumbents by raising the number of seats available on a route and improving on-time performance with fewer cancellations and delays. This observation, attributable to Donald Washburn, a former executive at Northwest Airlines, appeared in Lowenstein (2002). A similar sentiment is expressed in Michaels and Chipello (2006) in which it is observed that “Despite decades of steadily rising passenger traffic, the sector has racked up billions of dollars in losses and has rarely covered its financing costs. Yet the

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companies that serve commercial airlines—plane makers, fuel suppliers, airports and maintenance shops—regularly report fat profits.” 111. As explained by Stellin (2010a), in addition to financing issuers, the operational difficulties faced by start-ups include lack of access to takeoff and landing slots and gates at desirable airports and inability to sustain broadly based branding and marketing campaigns, which are much more easily accomplished through the economies of scale enjoyed by the larger carriers. The difficulties of combining legacy carriers are described in Bennett (2012) and the success of Alaska Airlines is discussed in Kaminski (2012) and Mouawad (2013d). See also Mouawad (2012c, 2013e), Wassener (2012), Clark (2013b), Mouawad and Drew (2013), Tully (2013), and Richtel (2013) who notes that since 1978 only a handful of 250 new airlines have survived. Leonard (2014), Mouawad (2014c, 2016), Carey and Wall (2016), and Levere (2017) write about the start-up of Norwegian Airlines. Willoughby (2014) discusses the American-US Airways merger progress. Nicas and Carey (2014a) write of how Southwest has become to resemble the legacy carriers. See also Carey (2014a) and Wall (2017b).

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Chapter 3

Water and Wheels

A tourist is a fellow who drives thousands of miles so that he can be photographed standing in front of his car.—Emile Ganest

Not everyone flies. Sometimes it may, in fact, still be more convenient, more fun, and less expensive to go by car, bus, or train—or to take a cruise. This chapter provides background about travel on vehicles that move on water or wheels.

3.1

Wetting the Whistle

Modern cruise ships are arguably the one mode of transportation that are also a destination in and of themselves. No one, for example, would think of a modern airplane in quite this way, not even while encamped in the plushest of first-class cabins. On a cruise, the ambiguity of purpose, however, is not unintentional. It is instead an important aspect and also the desired outcome of earnest marketing campaigns designed to stimulate in the middle-class traveler’s mind the most Sybaritic of fantasies. As such, the modern cruise ship operates as much as a floating hotel-resort as it does as a means of carriage.

3.1.1

Fantasy Islands

Although ships have been transporting passengers since the beginning of time, the first cruises were conducted by the Peninsula and Oriental Steam Navigation Co., which ran vessels from Britain to Spain and Portugal and to Malaysia and China beginning in 1844.1 But he “first American-originated cruise was probably the 1867 voyage of the paddle-wheel steamer Quaker City from New York.”2 This adventure—in which people would promenade the deck in the evening, sing hymns, and listen to organ music—was advertised as an excursion to exotic places of interest.3 © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 H. L. Vogel, Travel Industry Economics, https://doi.org/10.1007/978-3-030-63351-6_3

161

162 Fig. 3.1 Cruise-line industry passengers and berths, 1980–2019. Source: CLIA and company reports

3 Water and Wheels passengers (mil)

berths (000)

30

600

Global pass

24

450

berths

18 300 12 NA pass

6 0

150 0

80

90

00

10

The earliest year-round leisure cruises began around 1950, when a Miami operator, Frank Fraser, began to run ships to Caribbean ports. One of the first dedicated ships was the Nuevo Dominicano, which was only 300 feet long and carried only 177 passengers. The great innovation of the 1950s included the then luxurious addition of air-conditioning.4 The modern industry, however, only dates back to the early 1970s, when rising consumer disposable income and the development of new technology opened up the possibility of cruising on a giant ship purely for pleasure and not necessarily for the purpose of going anywhere in particular. Prior to that time, the giant ships—the Titanic and Queen Elizabeth, for instance—were, until the appearance of jet aircraft, the only way for most people to traverse the oceans. Prior to the 1960s, cruises were characterized by their long duration and distances covered as opposed to the relatively brief “movable resort” cruises of today. Miami-based entrepreneur Ted Arison, along with the financial help of Norwegian ship owner Knut Kloster (founder of the Norwegian Cruise Line, 1966), was among the first to capitalize on the opportunities for growth. Arison formed Carnival Cruise Lines in 1972 with the purchase of a rusting Canadian vessel that he renamed the Mardi Gras. Using this as a base, he quickly embellished and aggressively promoted the concept of fun and frolic aboard the ship to people of all ages and backgrounds and changed the nature of cruising into a market for mass tourism.5 Meanwhile, Royal Caribbean, a competitor founded in 1968, reinforced the concept by being the first to design ships specifically for warm water, year-round cruising.6 And in 1997 Norwegian Torstein Hagen founded Viking River Cruises with the purchase of four river ships. Ocean-going competitors to Carnival, including companies such as Royal Caribbean, Norwegian, and the smaller and later MSC (Mediterranean Shipping Company) soon developed cruise packages of their own, boosting worldwide industry growth to a compound annual rate of 7.4% from 1980 through 2010. Over this span, the global number of passengers carried by the industry rose to more than 17 million as compared to not even one-tenth as many in 1980 (Fig. 3.1). By 2019, the global number of ocean-going passengers had (pre-pandemic) grown to 26 million floating

3.1 Wetting the Whistle

163

Table 3.1 Top three brand names by major company as of 2020 Company Carnival

Royal Caribbean

Norwegian

Mediterranean Shipping

Brand Carnival Cruise Lines Princess Costa RCL Celebrity TUI NCL Oceana Regent Seven Seas MSC

Approximate Number of Ships 26 17 15 26 13 5 16 6 4 13

on an estimated 350 ships covering 70 brand names and directly and indirectly employing one million people. (The 2020 pandemic, however, ended most cruising for at least a year.) As in hotels (Chap. 4), branding is an essential marketing feature because the potential to attract passengers depends greatly on categories that are based on incomes and affordability, lifestyles, culture, language, and nationality. The marketing approach is then applied to and based on products and services designed to satisfy a wide variety of passenger needs and wants (Table 3.1). This price discrimination (see Chap. 1) approach results in segmentation that broadly includes economy, mid-range, and luxury brands—with the precise definition of each depending on the cruise line’s marketing targets and the amenities and service levels provided in each category. The cruise experience is thus highly customizable, with many different price levels and packages that might include or exclude certain meals, complementary services, and shore excursion tours of various types. Cruising accounts for only an estimated 5% of the North American vacation market, defined as persons who travel for leisure purposes on trips of three nights or longer involving at least one night’s stay in a hotel. The Cruise Lines International Association (CLIA) data further indicate that only around 25% of the North American and 15% of the U.K. population (and much less of the populations of Australia and continental Europe) has ever taken a cruise. Globally, the cruise industry accounts for only 3% of the world’s hotel rooms. The Caribbean still ranks as a primary destination, with the Mediterranean being the second most popular as measured by usual share of total bed-days (Caribbean ~35%, Mediterranean ~20%). The selection of destinations further depends for both the passengers and companies on a site’s seasonality, congestion, ease of port entry and associated fees, and geographical and cultural distinctivness and thus attractiveness. An origin-destination matrix for the largest markets appears in Table 3.2. Cruises are now also packaged to attract tourists interested in categories such as adventure, nature, specialty themes, coastal, river, or world expeditions. Travel agents, who book around 80% of cruise vacations and who collectively earn about $1 billion a year in commissions, meanwhile continue to be central to the

164 Table 3.2 Regional origindesination percentages, 2019. Percentage of passenger capacity for Carnival destinations and guest origins in percent for Royal Caribbean

3 Water and Wheels Destinations Caribbean Europe w/o Medterranean Mediterranean Australia/N.Z, Alaska China Other

30% 14 13 7 6 5 26

Origins N. America Europe Asia/Pacific Other

47% 25 24 3

Source: Carnival and Royal Caribbean SEC 10 K filings for fiscal 2019. See also World Tourism Organization, Cruise Tourism: Current Situation and Trends, 2019 According to the 2020 CLIA’s State of the Cruise Industry Outlook, the percent of ALBDs deployed by region was Caribbean, 32%; Mediterranean, 17%; Euorpe w/o Med, 11%; China, 6%; Australia/NZ/Pacific, 5%

arrangement of such packages. But the essence is that cruising is more about the itinerary than the destination.7 From a marketing perspective, vessel size (see below) is only one of several features that are purposely designed and branded for their appeal to different types of passengers—but with the challenge of appealing to younger groups given that up to a third of global passengers are over age 60. As in the hotel industry, there is generally some overlap and competition between segments but, for the most part, each segment is distinctive. For example, contemporary cruise lines (including Carnival and Royal Caribbean) target families and first-time participants in a broad range of ages and incomes typically for excursions of seven days or less on the largest ships. Premium lines (including Cunard and Princess) target passengers that are somewhat more experienced, affluent, and older. This segment features comfort and style for excursions of up to fourteen days and emphasizes destination activities and attractions. And in the luxury segment (including Seabourn and Windstar) a cruise would likely be on smaller modern ships able to provide top-scale services, dining, and other amenities, but at the highest per diem prices. Although North America is the source of about 60% global boardings, fleets are also being expanded to take advantage of demand potential in relatively low-saturation markets that include the Asian/Pacific (e.g., major operator, Star Cruises) and South American regions. In these regions, cruises are typically of shorter duration than are their counterparts elsewhere. China-originated cruising now also ranks high in global markets.8 Passenger unit growth has been largely sustained if not accelerated by the industry’s shift toward use of larger ships that have allowed efficiencies to be gained and prices to be lowered. The strategy is similar to that implemented by airlines in their transition to using wide-bodied jumbo jets for long-distance flights.

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Table 3.3 Large cruise ships, selected sample, circa 1996–2021 Name Carnival Corporation Mardi Gras Carnival Dream Queen Mary 2 Carnival Victory Carnival Triumph Carnival Destiny Royal Caribbean Wonder of the Seas Spectrum of the Seas Symphony of the Seas Ovation of the Seas Anthem of the Seas Ovation of the Seas Allure of the Seas Oasis of the Seas Navigator of the Seas Voyager of the Seas Norwegian Encore Escape Getaway Breakaway Epic

Year built

Passenger capacity

Approximate gross registered tons

2021 2009 2003 2000 1999 1996

5200 3646 2620 2758 2758 2642

183.900 130,000 150,000 101,000 102,000 101,353

2021 2019 2018 2016 2015 2016 2010 2009 2002 1999

5500 4246 5500 4180 4180 4180 5400 5400 3114 3114

130,000 168,670 228.100 167,800 167.800 167,800 225,000 225,000 138,000 142,000

2019 2015 2014 2013 2010

4200 4028 4000 4100

163,000 146,600 144,017 155.873

Source: Company reports

The largest of the ships are now several football fields long and able to feed and shelter the population of a sizable village. For example, the Carnival Destiny, built in 1996, sails with 101,353 tons (the first to ever exceed 100,000-tons), a length of 893 feet, and a passenger capacity of 2642 based on double occupancy. Oasis of the Seas, launched by Royal Caribbean in 2009 at a cost of $1.4 billion is one of the world’s largest at 225,000 tons. Royal Caribbean’s Symphony of the Seas, introduced in 2018 and able to serve 5518 guests, and Carnival’s new Mardi Gras at 180,000 tons, launched in late 2021 can carry 6614 passengers in 2641 cabins . These vessels, typically costing more than $1 billion to build, make aircraft carriers seem small in comparison.9 Such enormous capital commitments have consequently led to an oligopolistic industry structure in which some 80% of North American cruise capacity is handled by the Carnival, Royal Caribbean, and Norwegian company brands. A list of some of the largest cruise ships ever built appears in Table 3.3—with among the largest as of 2020 being Royal Carribean’s Allure of the Sea containing 2706 rooms, 16 decks, 22 restaurants, 20 bars, a shopping mall, a casino, and a water

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park and able to accommodate around 6300 passengers with a crew of 2400. Nearly all such behemoths are registered outside of the United States, where foreign governments often subsidize the cost of shipyard construction. In fact, foreign-flag ships, having greater flexibility in hiring, are likely to have significantly lower average unit labor costs than those flying the American flag. This is an important profitability enhancement factor because the ratio of crew to passengers may be as high as 50%.10 Many cruise companies further benefit from a loophole in the Federal tax code that exempts from taxation a foreign-registered firm’s income from ships and aircraft if the country in which the firm is organized (e.g., Panama, Liberia, and the Bahamas) offers equivalent exemptions to American companies.11 These rules were initially established to promote international shipping and trading by air.

3.1.2

Operational Aspects

As of 2019, the global cruise industry had approximately 500,000 berths (275,000 in North America) on around 260 ships and generated revenues of approximately $30 billion. To reflect demand versus supply, the industry prefers to measure occupancy rates, which, for the two major players (Carnival and Royal Caribbean), are normally more than 100%.12 As in any other capital-intensive businesses, occupancy rates (which implicitly reflect capacity utilization) are important in the setting of prices and in the determination of the returns on invested capital that are to be ultimately generated. The lower the expected long-run occupancy rate, the more short-run pricing volatility is likely to be seen.13 From the standpoint of perishibility of product, cruise ships are more like airlines than hotels.14 An unused hotel room at 6 P.M .might still be sold to a late-arriving traveler by 10 P.M., but once a cruise ship sails or the airplane lifts off, there can be no additional passengers boarded. For a ship this may mean that berths remain unsold for at least three and as much as seven days—a fundamental feature that sometimes creates more pressure to discount prices here than even in the hotel and airline industries. Given the relatively long turnaround times and the greater onboard, high-profit marginal revenues (and tips for crews) that can thus be generated it makes economic sense to try to fill a ship to the brim through price discounting. Many of these elements are reflected in statistical measures such as yield, which is defined as the average gross revenue per available berths (i.e., units of capacity) and occupancy rates—the equivalent of occupancy rates in hotels, only with the assumption that there are two passengers per room.15 Other related measures include the number of passenger-cruise days (PCD), which is essentially the number of passengers times the number of days cruised, and available passenger-cruise days (APCD), which is a gauge of industry supply (capacity).16 APCD may also be referred to as Available Lower Berth Days (ALBD).

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Of these metrics, however, perhaps the best overall summary is provided by the net revenue yield (NRY), which equals cruise revenues minus expenses (such as commissions and transportation) divided by available berths times days of operation:17 NRY ¼ ðavailable revenuesexpenses berthsÞ x ðdays of operationÞ A figure of 6% or above is considered to be an indicator of good performance. Changes in yield (akin to same-store sales in retailing) are an important variable because they drive changes in profitability, return on invested capital (ROIC), and hence also the price-earnings valuation multiple carried by a cruise company’s shares. The air/sea mix, which is the ratio of passengers purchasing airline and cruise tickets linked together to those only booking cruises may sometimes provide another useful analytical metric, but changes in the mix normally do not substantially affect operating income. Gross cruise costs are equal to total operating expenses plus expenditures on marketing, selling, and administration, whereas net cruise costs exclude costs of commissions, transportation, and miscellaneous. The space ratio of a ship, however, is measured in terms of gross registered tons (GRT), which has nothing to do with weight. GRT is instead a measure of the amount of usable space per passenger on a ship. By definition 1 GRT is 100 cubic feet of permanently enclosed volume, which means, for example, that a ship of 18,000 GRT carrying 750 passengers provides a space ratio of 24 tons per passenger. On modern ships, the passenger space ratio (PSR) may range from the low thirties to as high as sixty to seventy on luxury-class brands.18 PSR and cabin size are by far the most important determinants of the prices paid for cruises of similar itinerary and duration. PSR and passengers per crew (PPC) metrics thus obviously have a strong bearing not only on pricing but also profitability, growth strategy, and branding features. Gibson and Parkman (2019, p. 11), for instance, show that a large modern ship such as Royal Caribbean’s Harmony of the Seas (GRT 226,963, operating 2016) which can accommodate 6.780 provides a PSR of 33.48 cubic feet and a passenger to crew ratio of 2.94:1. Yet Seabourn’s Sojourn (GRT 32,000, operating 2010), which accommodates only 450 passengers can—despite its much smaller size—provide cruisers with 71.11 cubic feet of space and offer a passenger to crew ratio of 1.36:1.19 Although cruise revenues are generated from many different sources, the onboard sale of beverages usually ranks high in contribution to profits even though most of the revenue (e.g., for Carnival and Royal Caribbean, ~70%) is derived from ticket sales. Other large sources of onboard (ancillary) revenue would also often include sale of shore excursions (with margins >50%), retail sales from shops, specialty restaurants, jewelry and art auctions (with at least a 35% cut of sales to the ship), and promotions of photo, beauty salon, duty-free, and health spa services. With only 30% of passengers typically interested in gambling, casino revenues often do not

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contribute proportionately as much to total income (perhaps 10%) as is frequently assumed. As might be expected, the costs of providing numerous onboard services also vary by type of market segment. Excluding labor and overhead, food costs on a per diem or per passenger-day basis might be as high as $258 to $35 on the luxury end, as low as $10 to $14 for the mass-market segment, and somewhere in between for so-called premium segment cruises. However, because the operating (variable) costs of a cruise do not rise proportionally with the number of passengers, the industry has moved to increase the average ship-carrying capacity. As ship size rises from around 1500 berths to 2600 berths and with occupancy levels of around 100% (and ranging as high as 110% when more than two people are in a cabin), the cash flow (EBITDA) margin before corporate expenses can move up from 45% to 55%. The breakeven occupancy level for the larger ships meanwhile tends to decline to 50% as compared to 60% for the smaller ones.20 Yet once a ship reaches the size of about 2000 berths, the benefit from further scaling up begins to rapidly diminish. Yield management strategies that have been successfully implemented in the hotel and airline businesses have however not been especially helpful to the cruise industry for two reasons: Leisure, as compared to business travelers, are much more sensitive (elastic) in their demand as a function of price; and the all-inclusive nature of cruises (including several meals a day) leads to marginal costs per unit that are much higher than in hotels and airlines. To best implement yield management, it is important that detailed data analytics (i. e., big data and artificial intelligence systems) provide information on consumer behavior in each market segment and relate to historical demand, pricing, and booking patterns. An estimated percentage profit and loss statement that is typical for the largest companies (and which does not change much over time) appears in Table 3.4. The middle of Table 1.6 meanwhile provides a more aggregated view of the cruise industry’s (pre-pandemic) operating performance as compared to other travel sectors.21 It is notable that the industry—dominated by the publicly owned giants Carnival, Royal Caribbean, and Norwegian (with approximate respective market shares of 50%, 25%, and 12% in 2019)—has been able to shield so much pretax profit because of political effectiveness at minimizing taxes and in addressing and deflecting criticisms relating to safety, health, and environmental issues.22 As critical focus on these issues intensifies, industry profit margins will likely be narrowed.23

3.1.3

Economic Aspects

Economic Sensitivities Demand for cruise line services, like those for other travel services, are ultimately dependent on the overall health of the economy, particularly as measured in terms of such factors as unemployment rates, interest rates, and the growth potential and availability of disposable income. For example, significant sensitivity to economic conditions was seen in the recession of the early 2000s and

3.1 Wetting the Whistle Table 3.4 Estimated typical profit and loss statement (% of total Income), worldwide per passenger circa 2019

169

Ticket Onboard spnding Casino/bar Shore excursion share Spa other Total Operating costs Agent Commission fuel Coporate Payroll Deprec/Amort Food Other Interest Total Pretax profit Pretax margin (%)

Revenues $1325 500 275 100 50 75 2290 Expenses 260 240 190 265 200 175 110 140 70 $1590 $735 31.6%

% of total 57.0 21.5 11.8 4.3 2.2 3.2 100.0 16.4 15.1 11.9 12.9 12.6 11.0 6.9 8.8 4.4 100.0

See also Dickinson and Vladimir (1997, p. 135), https:// cruisemarketwatch.com/financial-breakdown-of-typical-cruiser/ and www.siimt.com/work/sites/siimt/resources/LocalContent/ 1172/6/Cruceros_2011_pw.pdf Note also that travel agencies are the most important source of cruise line bookings and most agencies derive a large and growing share of their revenues from the cruise business (Sect. 2.2)

even more so in the recession that officially began in December 2007, when demand dropped sharply and ships could only be filled by offering passengers steep price discounts.24 The coronavirus-caused deep recession of early 2020, however, revealed that the industry was totally unprepared to cope with the devastating global health and economic issues that nearly obliterated it. Ships of all the lines were—sometimes not-knowingly and/or involuntarily—boarding and harboring infected passengers, taking risks, and vastly unable to handle this major existential crisis.25 Neither did the industry have bargaining leverage when it came to receiving government bailout support given that most ships were registered outside the U.S. (see note 10). Still, no matter what the point in the economic cycle, on the supply side, additional new capacity as a percent of existing capacity is always an important determinant of industry pricing power and profitability.

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Marketing and Price Discrimination Strategies The basics of marketing cruise ship vacation packages are similar to what they would be for any other consumer service with mass-market appeal. The emphasis, though, would likely be on the entertainment and experiential aspects of a cruise. As in any other entertainmentrelated business, the percent of total operating budget spent on marketing and advertising as a percent of total costs per unit is rather high (above 12%), but not as high as the costs of fuel (+30%). In economic terms, the objective in spending so much per unit on promotion is, as described in Chap. 1 (Fig. 1.10), to shift the demand curve to the right of where it would otherwise be and to make the demand schedule more price-inelastic. In so doing, the ship operator can then also take better advantage of profit-enhancing price discrimination strategies that are similar to what airlines do by selling different seats at different prices (coach, premium economy, business, first-class) even though all travelers arrive at the same destination at the same time. For the largest companies, advertising as a percent of revenues can range above 4.5%, and combined marketing, selling, and administrative expenses can top 13.5%.26 Sunk Cost As in movie making, to use an example, the large capital costs of first building a ship are what economists would call—pardon the expression—sunk costs. This means that once a vessel is ready to float, all further strategic decisions by management must be based on prospective returns in the future (i.e., the original cost of the ship then becomes irrelevant). In this respect, Titanic the movie and Titanic the ship were the same even though the movie ultimately stayed afloat much longer than the ship.

3.2 3.2.1

Automobiles Jamming

Commercial production of automobiles began around the year 1900 and had a profound affect on not only on transportation but also on the development of new industries (e.g., motels, petroleum refineries, car service providers) and the structural economics of towns and cities. The resulting greater accessibility, mobility, and range of travel that now became possible, moreover, drastically altered urban and regional landscapes and upended the societal hierarchies and activities that had been typical of the prior century.27 The impact was far and wide. As with most consumer products that are born of new design and manufacturing technologies, autos were at first curiosities affordable only by the wealthy. Yet it didn’t take long for costs to decline and for passenger cars to be priced so that people of average means could buy them. In the first decade alone, half a million cars were sold, and by 1930, 27 million were registered, with more than half of all U.S. families owning at least one car. Although growth slowed during the middle, war, and Depression-filled years of the twentieth century, postwar prosperity had by

3.2 Automobiles

171

1980 pushed the incidence of car ownership to one in two persons, from one in five 50 years before. Technology, of course, played a role in making cars more user-friendly and easier to manufacture. And as more of them were registered, political pressures for highway improvements rose accordingly, with the percentage of paved roads increasing rapidly after 1920, when states devised various registration fee and gasoline tax schemes to finance road improvements. The extraordinary growth in automobile registrations combined with road improvements then had the effect of dramatically increasing the number of miles traveled—with much of the increase coming at the expense of the railroads (Fig. 3.2a). As Meyer and Oster (1987, p. 177) noted: total intercity travel by all modes (but excluding commuting) grew from 42 billion passenger miles in 1916 to 198 billion in 1929, with the automobile accounting for all the growth and its share increasing from less than 20 percent to over three quarters of the market in 1929. By 1940 intercity travel had increased to 330 billion passenger miles, and auto’s share had reached 89 percent.

Although construction of Connecticut’s Merritt Parkway and Pennsylvania’s Turnpike in the late 1930s first enabled traffic to flow faster, it was not until an Act of Congress initiated the Interstate Highway system in 1956 that the quality of the road system had caught up with the capabilities of the cars. As a result, intercity travel by automobile rose several-fold to over 1 trillion passenger-miles by 1970. Yet, the automobile’s share of market also peaked around that time: Jet aircraft were beginning to take an increasing percentage of intercity traffic volume (Fig. 3.2b). Meanwhile, as Fig. 3.3 shows, total government spending on highways has been consistently greater than for any other mode of transportation. Despite these expenditures, however, traffic jams are today probably no less common than they were many years ago (especially as U.S. bridge and highway infrastructure has not been adequately upgraded).

3.2.2

Car Rentals

The global $36 billion (60% in the U.S.) car rental business, with approximately 70% of its volume originating at airports, sits at the intersection of travel, where wings change into wheels. However, the business has long been structured as an oligopoly with brands including Hertz, Avis, and Enterprise, dominant. Enterprise is by far the strongest at off-airport locations, with over 50% of that business, but Hertz and Avis have more recently been expanding in that direction.28 Four distinct branding tiers have emerged in the North American market: Premium (Avis, Hertz, and National); mid-priced (Budget and Alamo); value (Dollar, Thrifty, and Enterprise); and deep discount (Advantage, Payless, and Fox). The traditional

172 Fig. 3.2 (a) Percentage share of intercity revenue passenger-miles (RPMs) for private carriers (automobile) versus public carriers (planes, trains, and buses), 1940–2019. (b) Percentage share of total public carrier intercity RPMs, 1940–2019. (c) Bus and rail revenue passenger-miles, 1940–2019

3 Water and Wheels

(a) 100

% of RPMs

75

Auto

50 planes + trains + buses

25 0 40

50

60

70

80

90

00

10

(b) % of RPMs

125

Air

100 Rail

75 50 Bus

25 0 40

(c) 125

50

60

70

80

90

00

10

RPMs (billions)

100 Rail

75 50

Bus

25 0 40

50

60

70

80

90

00

10

companies account for around 95% of the rental market, with brand ownership in 2020 being: Avis—Budget, Payless, Zipcar Enterprise—Alamo, National Hertz—Dollar, Thrifty

3.2 Automobiles

200

173

$ Billions

160 Highways 120

80 Aviation 40 Mass transit + rail 0 60

65

70

75

80

85

90

95

00

05

10

15

Fig. 3.3 Total public, federal, state, and local spending (capital, operations, maintenance) for transportation infrastructure, by type of infrastructure, 1956 to 2017. Source: Congressional Budget Office, available at www.cbo.gov/doc and Table W-1 at www.cbo.gov/publication/54539

In the United States, rentals are funneled through approximately 7000 airport locations and another 12,000 others routinely at car dealers or service stations. For many locations outside the United States, franchise arrangements are also used. A typical agreement might, depending on location, call for between 5% and 7.5% of gross rental revenues to go to the franchisor.29 At first glance, the business of renting cars to travelers seems simple enough. The price paid by the renter is somewhat proportionate both to the length of time for which the car is rented and the value of the car. The price paid would also be sensitive to local-market competitive conditions. And revenues per transaction ought to be higher from leisure than from business rentals because leisure rentals are generally for longer periods. Profit would result when the rental price received exceeds the all-in costs of buying and holding the vehicle and of administration and marketing to customers.30 A significant part of a rental company’s profit is, however, likely to be derived from the difference between prices paid for cars (whether leased or bought outright) and the prices for which they are sold after being used by customers. And if car rental volume declines and operating costs rise, substantial downward adjustments to the value of the fleet and to earnings and share prices will inevitably occur. In dominant airport-location companies such as Hertz, with around 30% share of the U.S. market, it is not unusual to find that most of the cars acquired (80%+) will be bought under manufacturer repurchase (i.e., “program”) agreements wherein the repurchase price is subject to mileage, repair, and depreciation-schedule charges. Because such arrangements tend to limit the rental company’s residual risk, cars acquired under these conditions are referred to in the industry as “nonrisk”31 The cost and the availability of suitable cars are thus important variables in the

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determination of profits. To further reduce risk, the major companies will tend to pool their inventories at independently operated rental facilities. The trade-off here, though, is between the lengths of time that a car is owned by the rental company and the car’s ultimate depreciated value on resale. The longer the vehicle is owned, the more rental turns it can potentially generate, with the average fixed cost per rental declining over time even as the variable costs of maintenance and repairs inevitably begin to rise. The larger companies will usually hold a car for at least six to seven months (and 18,000 miles), although some may be kept for more than a year. In 2019, there were around 2.2 million rental vehicles in the United States and the annual revenues generated per unit was estimated (see autorentalnews. com and annual Factbook) to have been $12, 600 ($1050 per month). Some key metrics for analysis would be the average number of rental days, vehicle utilization percentage, average revenue per vehicle, and average net monthly depreciation per vehicle. From a macroeconomic standpoint, the rental business is somewhat sensitive to general economic conditions and also more specifically to airline industry prospects and prices. Almost by definition, in prosperous times, both airlines and rental companies will benefit from strong pricing of their services and relatively benign behavior of fuel, borrowing, and labor costs—all of which are important to both of these similarly capital- and labor-intensive industries. Because of the close linkages between them, with one segment largely feeding the other, capacity utilization trends (fleet utilization in cars and load factors in airlines) must track, up and down, more or less in tandem. This implies that car rental company profitability is apt to be cyclically volatile, with operating and financial leverage relatively high. From a microeconomic standpoint, the goal of the car rental company is to maximize fleet utilization at the highest possible price. Marketing and price-discrimination (i.e., yield management) strategies and reservation systems retain their importance in the overall scheme of operations. And the analytical framework remains comparable to that applied to other oligopolistic, capital- and labor-intensive industry segments. The newer challenges to the traditional industry business model, however, are related to the proliferation of ride-sharing services such as Uber and Lyft and the eventual deployments of self-driving vehicles.32 Table 1.6 shows the composite financial operating performance of major car rental companies.33

3.3

Kings of the Road

The first scheduled intercity bus service in the United States began in 1913 in Minnesota using a seven-passenger Hupmobile that frequently broke down and whose arrival time was unpredictable.34 However, even without a network of good roads at the time, travel by bus flourished and by the mid-1920s more than 4000 companies were competing.

3.3 Kings of the Road

175

Nevertheless, regulations soon began to spread and almost every state had some, with the earliest regulations focused primarily on issues of passenger safety and highway maintenance. Later regulations evolved into protection from competition on intrastate routes and it took a Supreme Court ruling in 1925 to break the monopoly patterns that were being established. The turbulent conditions that came with the opening of interstate routes to competition then led to passage of the Motor Carrier Act in 1935. At that point, the Interstate Commerce Commission (ICC) became the regulator of interstate bus fares, safety, routes, mergers, and financial fitness.35 Such fitness was especially important given that the government had begun to see the industry as a capital-intensive public utility deserving overview similar to that which had already been long applied to the railroads.36 As a result, the government did not object to the many mergers and consolidations between carriers that occurred starting in the mid-1920s. Formation of national bus systems ensued and demand for long-distance services then increased rapidly. Already, by 1930, Greyhound had emerged as the dominant carrier, operating major routes and holding many intrastate as well as all major transcontinental rights. The only significant competition to Greyhound was fostered by the ICC, which certified new interstate bus operators and the creation of many railroad-owned bus subsidiaries. In 1936, several of these subsidiaries formed the National Trailways System, a company that eventually became Continental Trailways.37 As can be seen in Fig. 3.2c, the bus industry’s carriage volume still amounts to approximately 25 billion revenue passenger-miles a year. It had, however, been as high as 27 billion passenger-miles in 1945, at the end of World War II. Since then, however, bus ridership has steadily lost share of the intercity travel market, from nearly 10% in the mid-1940s to 2.5% by 1960, and to around 1% currently. Rising disposable income of the population at large combined with declining relative prices and technological improvements in other modes of travel had early on begun to shift ridership over to planes, cars, and even trains once the government-subsidized Amtrak began (in the 1970s) to compete on price in the Northeast. With industry operating costs as a percent of revenues rising to 95% in the late 1970s from an average of between 85% and 88% during the postwar period, profitpinched industry managements began to seek the regulatory relief that Congress provided in 1982 with passage of the Bus Regulatory Reform Act. The significantly loosened controls that followed have allowed operators such as Greyhound to extend their brand names and to lower costs through implementation of franchising arrangements with local carriers. Bus operators have also developed charter services that now account for about half of all intercity revenue passenger miles. Nevertheless, intercity buses are now used mostly for trips of under 200 miles and/or between cities not served well or at all by air and rail transportation. Because growth has remained sluggish and profits have been largely evanescent, the industry has evolved into a bifurcated structure, being almost monopolistic on some routes and monopolistic-competitive on others. As with other transportation modes, the costs of fuel, labor, and capital are important variables in the determination of profitability. Indeed, the industry’s profile of capital intensity is similar

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enough to that of the airline and rail industries that many of the equipment leasing and other tax-advantaged financing methods discussed in Chap. 2 apply here as well.38

3.4

Iron and Steel

One hundred years ago passenger trains, accounting for almost all intercity travel, were the only effective means of high-speed travel suitable for long distances. It all began with Britain’s new technology and speculative frenzy of the 1840’s—the dot. com bubble of the time—that followed the rapid, revolutionalry, and disruptive development of steam-powered locomotives and iron trancks. Throughout the twentieth century, however, technological advances, particularly in the form of internal combustion and jet engines, worked to the relative disadvantage of the railroads just as such change had worked to their benefit in the century before. As a result, the market share of long-distance intercity travel carried by rail has currently slipped to below 1% of revenue passenger-miles as compared to nearly 100% at the dawn of the automobile’s era circa 1900. Still, even today, there remain times and places in which travel by rail retains not only its peculiar charm but also an efficiency advantage. Although rail regulations served as a model for later regulations applied to the airline and bus industries, governments were initially little involved in the early development of railroads. In fact, the emerging railroads had competed successfully against many government-owned and sponsored canal and turnpike companies of the mid-1800s and had bankrupted most of them. By the 1870s, however, overcapacity had sparked rate wars among competing freight carriers and peace was not restored until monopolistic rate and revenuepooling agreements between carriers had been negotiated. Ultimately, complaints against these agreements led Congress to in 1887 pass what is known as the Interstate Commerce Act. The Act created the ICC and required that rates be set at reasonable levels while also outlawing discriminatory pricing and pooling practices among carriers. The Hepburn Act of 1906 (followed by the Mann-Elkins Act in 1910) then gave the ICC legal power to set rate ceilings and to issue more stringent regulations against alleged monopolistic practices. The first peak for rail ridership came in 1920 at 47 billion passenger-miles. After that came a series of events and technological developments—the recession of 1921, the Great Depression, and most significantly, buses, cars, and planes—that caused a persistent drop-off in ridership. The railroads tried to stem the decline by replacing older equipment with new, air-conditioned trains with sleeping cars, but any gains in ridership were short-lived. In fact, after 1945, the year of a second (wartime) peak (Fig. 3.2c), demand for passenger rail service began to fall progressively faster each year. Although there was some controversy as to how railroad companies allocated their costs between freight and passenger services, there was no doubt that, by the 1950s, passenger service deficits were large enough to offset the industry’s operating

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177

Table 3.5 Average passenger revenue per passenger-mile (current cents) by mode, 1960–2012 Year 2012 2010 2005 2000 1995 1990 1980 1970 1960

Air carrier, domestic, scheduled service 13.8 13.0 12.3 14.6 13.5 13.4 11.5 6.0 6.1

Class I bus, intercitya NAb NAb 11.2 9.4 9.4 9.3 7.3 3.6 2.7

Commuter rail 22.9 20.7 18.2 14.6 13.1 13.4 6.7 3.8 2.9

Intercity/ Amtrak 33.9 31.0 27.2 23.2 14.6 14.1 8.0 4.0 3.0

Source: Bureau of Transportation Statistics, National Transportation Statistics, Appendix D— Modal Profile, available at: http://www.bts.gov/publications/national_transportation_statistics/html a Regular route intercity service, 2005 estimated b NA indicates unavailable data

profits derived from carriage of freight. At the time, shippers had also begun to complain that the ICC was forcing them to subsidize passenger service by allowing high rates for freight. In those years, the financial strain on rail companies became so great that there was no recourse but for them to cut back on passenger routes. The trouble was that when such service cutbacks were attempted, local political pressures were often sufficient to deny the railroads’ abandonment petitions. Congress was finally forced to provide some regulatory relief measures in the Transportation Act of 1958. But service abandonments nevertheless remained as much a political as an economic issue through the 1960s. It was not until 1970, when Congress created the National Rail Passenger Corporation, known as Amtrak, that a potentially more viable solution to this problem was devised. Although Amtrak was founded as a quasi-governmental for-profit corporation that has survived into the twenty-first century (and in fiscal 2019 carried 32.5 million passengers on around 305 intercity trains per day on 21,400 miles of routes), it has yet to earn a profit and has remained dependent on annual operating subsidies (summing to more than $45 billion over 45 years beginning in 1971). Approximately half of its 2019 revenues of $3.5 billion were derived from the Northeast Corridor tracks, but Amtrak also collects fees from other entities for use of its assets.39 Most intercity passenger railways in the world are unprofitable and are generally subsidized by national (as in the U.S.) or local governments. Such subsidies receive political support because trains are seen as reducing highway congestion and pollution while conserving expensive fuel even though travel by air, car, or bus is usually much more cost effective on a per passenger or per mile operating basis.40 In all, rail is competitive on an operating and capital cost basis only over a few short-haul, high-density routes that are typical of those between European cities or in Japan, where high-speed intercity trains have the potential to remain profitable by charging high fares in markets with little airline competition.41 Comparisons of average passenger revenue per passenger-mile by mode are shown in Table 3.5.42

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3.5

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Finance and Accounting

Financial and accounting issues for companies providing services on land or sea are much the same as for airlines. The initial cost of each equipment unit—be it a locomotive, a cruise ship, or a fleet of cars—is enormous, and the securities markets for debt and equity are both usually tapped to at least some degree. Equipment trust certificate financing and sale-leaseback arrangements (as detailed in Chap. 2) are also frequently encountered, as there are purely financial or other companies that can take better advantage of tax and financing conditions than can the operators of such travel businesses. This is particularly evident when, as happens in a period of economic recession, cash flows are skimpy compared to needs, public equity and debt are relatively expensive, and tax-loss carryforwards are so large that the value of a depreciation tax shield to the operating company is minimal. Equipment depreciation schedules will otherwise follow Internal Revenue Service guidelines (Section 168) for the particular class of asset. For instance, cars may be depreciated on an accelerated basis over five years (so-called five-year property), whereas a jet plane is usually twenty years and a ship or vessel up to thirty years. In the case of car rental companies, purchases of cars are financed through funds from operations and borrowing programs. At-risk cars as well as those non-risk cars not returned to the manufacturer are sold through auctions and at used-car dealer locations. At Hertz, for example, upon sale of a car, the difference between the net proceeds from sale and the remaining book value is recorded as an adjustment to depreciation in the period when sold.

3.6

Concluding Remarks

One hundred or so years ago, rail was the only way to really travel in style over long distances. And the only way to cross the oceans was by large steamship. The trips were surely adventuresome and exciting for the passengers of those days but no one would think of a long train ride or ocean crossing as a vacation or as a form of entertainment. Travelers of the time didn’t have a choice: Airplanes, cars, buses, and cruise ships hadn’t yet been sufficiently developed for carriage of high-volume commercial traffic. Today we take all of these forms for granted, with travel by air dominant over medium to long distances. For the foreseeable future, it is likely that current modes of transportation will be improved upon in small increments that are more evolutionary than revolutionary. Technologically enhanced (e.g., magnetic levitation) high-speed intricate rails have, for example, been conceptualized for many years and may one day become cost effective.43 And a new generation of supersonic planes is nearly certain to be in service within a decade or two.44 For the distant future, though, we can only speculate at what any new modes might be.

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179

Notes 1. Dickinson and Vladimir (1997, p. 1). 2. Dickinson and Vladimir (2008, p. 4). 3. Ibid. 4. As reviewed in Garin (2005). 5. It also didn’t hurt that popular television series of the seventies included The Love Boat (1977–86) and Fantasy Island (1978–84). 6. The first Royal Caribbean ship, Song of Norway, went into service in 1970. A detailed industry history appears in Cartwright and Baird (1999) and also in Garin (2005). In 1965 Princess Cruises, operated by Stanley B. McDonald, was the first to focus on leisure travel markets. Gibson and Parkman (2019) covers history and operations in detail. By the end of the 1990s, Carnival accounted for approximately 40% of all industry revenues and Royal Caribbean, 30%. As of 2012, Carnival accounted for approximately 60% of all industry revenues, Royal Caribbean, 25%, and Norwegian Cruise Lines (partly owned by private equity firm Apollo Group) around 10%. See Ward (2008) and ABC’s 20/20 episode of January 20, 2012 about the cruise ship industry. 7. This notion may be credited to Rodrigue (2013, Chapter 7) 8. See Beam (2015). 9. Voyager had a contract price of approximately $500 million not including capitalized interest, change orders or owner’s extras. The Queen Mary 2, described in Perez (2003), cost $780 million and is the first liner to enter service since the sister QE2 in 1969. The QM2 length (technically an ocean liner) is 1132 feet; height from water level; 23 stories; and girth, 135 feet. Its maiden voyage to New York was in April 2004. As late as 1954, ocean liners carried one million passengers across the Atlantic as compared to only 600,000 on airlines. But by 1965, airlines carried four million and ocean liners only 650,000. See McCartney (2019). 10. The choice of a country depends on many factors including the place where the vessel is financed, the operating costs, and the routes the vessel sails. The United States and Britain, for example, have strict regulations concerning the use of unionized labor. So-called flag-of-convenience, “open registries” countries include Panama and Liberia, which are the most popular, and also Bermuda, the Bahamas, and the Netherlands Antilles. The higher operating costs with U.S. registration are in part caused by the U.S. requirement that all ships registered in the United States use only licensed American officers and that three quarters of the unlicensed crew be U.S. citizens. See Dickinson and Vladimir (1997, p. 66) and Garin (2005, Chap. 8) for more details. Note also that the Passenger Shipping Act of 1896 precluded foreign-flagged vessels from operating between U.S. ports when there is no U.S. flag competitor. The Jones Act of 1920 has had a significant influence on these issues and, as noted by Wayne (2003, 2004), Norwegian Cruise Lines was able to obtain an advantage by agreeing to pay American taxes and conform to American environmental and wage standards in serving the Hawaiian Islands beginning in 2004. The Act also makes U.S. river cruises more expensive than elsewhere.

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11. Sections 883 and 884 of the IRS code are relevant. Section 883 says that certain foreign corporations are not subject to U.S. income or branch profits tax on U.S. source income derived from or incidental to the international operation of a ship or ships or on income from the leasing of such ships. See, for example, Royal Caribbean’s 1998 10-K report to the Securities and Exchange Commission (SEC). The tax issue was covered in “Cruising for Fun and Profit” by the CBS show 60 Minutes on October 24, 1999. On February 8, 2000, the U.S. Treasury Department issued proposed regulations to Section 883. The proposals exclude from gross income for purposes of federal taxation the income derived by foreign corporations from the international operation of ships as long as a publicly traded corporation’s stock is not closely held. Tied into all of this is the notion, as noted in Garin (2005, p. 9), that “Everything that a cruise ship produces and consumes is, by definition, an export.” See Frantz (1999). 12. Actual occupancy levels for the industry, equivalent to load factors in airlines, are compiled by the CLIA based on information from the member lines. CLIA takes the number of potential passengers based on 100% occupancy times the number of bed-days as the denominator and actual number of passengers times the number of bed-days as the numerator. Additional operational aspects of a large ship are discussed in Nassauer (2010) and in Dowling (2006) who indicates that bed-days might be a better metric than average occupancy. If bed-days used are divided by total industry bed-days available (including idle vessels), the occupancy rate is likely to be in the range of 86% to 94%. 13. Also, as Dickinson and Vladimir (1997) suggest, prolonged overcapacity leading to price volatility and commoditization of services probably most adversely affects the VFR segment of the travel market. 14. Cruise lines also have high and low seasons for bookings. January through March, known as the “wave season,” accounts for as much as 35% to 50% a full year’s bookings. However, the summer season, when many families take trips, is typically more profitable. Petersen (2011) explains that many ships are now providing upgraded and much differentiated (ship-within-a-ship) services to passengers paying premium prices. Such guests also tend to spend more while onboard. 15. Unlike in hotels, if more than two people stay in the room (some cabins can accommodate three or four passengers), the occupancy is considered to be over 100%. 16. For stock valuation purposes, it is also sometimes useful to calculate enterprise value (EV) per berth. EV as described in Chap. 2, is number of shares outstanding multiplied by share price to which the amount net debt is added. Asset valuation comparisons on a time series basis as well as for one cruise-line company versus another can be made by taking EV and dividing by the number of berths. For example, Carnival’s long-term historical average was $370,000 per berth, but two months after the terrorist attacks of September 11, 2001, the value per berth had declined to $275,000 per berth or 25% below this average.

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17. This revenue yield aspect is similar to the RevPar (revenues per available room) metric that is used in the hotel industry, but in the cruise industry it’s called revenue per available lower berth day (ALBD). 18. Although the PSR is calculated by dividing the GRT by the number of available berths, Cartwright and Baird (1999, p. 108–9) note that the calculation can be made using an assumption of maximum occupancy, PSR(m), or assuming all cabins are being occupied by two persons, PSR(2). Differences in estimated average PSR(m) by type of service as of 1998 can be seen as follows: PSR(m) Size in s.f. Standard 29.8 125 Premium 47.5 155 Luxury 61.6 210 According to Cartwright and Baird (1999, p. xxii), the word tonnage comes from the medieval tun, meaning a barrel. Because GRT is a measure of enclosed space, the addition of an extra deck can dramatically increase GRT. In contrast, the size of warships is measured by the amount of water they displace. The International Convention on Tonnage Measurement in 1982 set the definition of GRT. 19. The cost of crews is always a significant factor affecting profits and, cconsidering the need for leaves and time off, the actual annual number of staff needed to service a large ship is usually about 1.5 times the number on any particular voyage—i.e., for any 1000 staff, the total employment “establishment cost” for the year would typically be 1500. 20. Larger ships can also spread the high fixed cost of onshore infrastructure facilities over a larger revenue base and also a multitude of brands but must, as described by Mouawad (2015), operate their complex systems with great efficiency. 21. These margins, but not the actual dollars of profit, are affected by the air/sea mix, which is the number of cruise passengers who purchase airline tickets with their cruise fare as a percent of the total number of paying passengers. There is no affect on operating profits because the airfare component of a cruise package is passed through the books of the cruise line as a corresponding revenue and expense item. A lower air/sea mix results in a higher margin because the same amount of profit is taken as a percent of a smaller sum of revenues. The air/sea mix has been trending down from around 30% as cruises in the United States have begun to originate from more seaports within a day’s driving distance. In European and Asian markets the trend has been just the opposite. According to cruisemarketwatch.com, the average line in 2011 derived around 75% of revenues from ticket sales 13.5% from casinos and bars, and 4.9% from shore excursions. On the cost side, 31% was related to core

182

22.

23.

24. 25. 26.

27. 28.

29. 30.

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operations, 11% to shipboard payrolls, 10.6% to agent commissions,10% to depreciation, and 7% to fuel costs. See also Bull (2013). Klein (2005) writes (p. 1) that “Governments believe they need cruise ships more than the cruise ships need them.” Brown et al. (2013) discusses the benefits and costs for communities that ships commonly visit. Mouawad (2013) suggests that large ship sizes might impair safety. Becker (2013, pp. 82 and 125–65), provides several examples of cruise industry issues that need to be addressed: “The air pollution from just one of the docked giant ships is the equivalent of 12,000 idling cars. . . .ships are not subject to the requirement for federal permits covering sewer and waste disposal systems. . .millions of passengers and crew members have left filthy discharges in their wake. . .cruise crowds streaming into foreign ports by the thousands have disfigured beaches and plazas. . .claiming in one instance to be a resort and in another a ship, the new floating hotels escaped paying billions of dollars in taxes and wages.” See also Seelye (2017), Moss (2018) on Chinese tourism effects in Thailand, Pannett (2018), Graham-McLay (2019) on similar effects in New Zealand, and Mervosh (2019), which notes that even effiecient ships generate three to four times more carbon dioxide emissions per passenger-mile than a jet airplane. See Esterl (2009). See McNish et al. (2020) and Smith et al. (2020). Although the comparisons here are largely to airlines and hotels, the industry prefers to view a cruise as a vacation alternative, with land-based resorts as the primary competition. Stopher and Stanley (2014, Chap. 2) provides a concise overview of the history of transportation. Hertz/Dollar Thrifty and Avis/Budget represent a mix of premium and low-priced brand owned by the same company. EuroCar, Sixt, and Fox operate discount brands in Europe. As noted by Loomis (2006), Enterprise’s revenues of $9 billion and profits of $700 million in 2005 were actually larger than those of Hertz, which in the same year generated revenues of $7.5 billion and profits of $378 million. By 2011, revenues had risen to $14 billion. Enterprise obtains much of its business from insurance companies, who provide temporary replacement cars to affected drivers under their policy obligations. With Hertz acquiring Dollar Thrifty for around 2.5 billion in 2012, the industry in the U.S. is dominated by Hertz, Enterprise Holdings, and Avis Budget Group. See Maynard (2002), Terlep and Dezember (2012), and Edleson (2013). Zipcar (bought by Avis in 2013) offers rentals by the hour or day. See Zipkin (2015) on emergence of new alternatives. Rental prices are tracked by the Abrams Rate Index, which measures the cost of a midsize car rented a week in advance. Beginning in early 2002, the major car-rental companies decided to bolster profits by eliminating travel agent commissions on certain corporate and government accounts such as those in the U.S. and Canada operating with negotiated discount plans. Prior to 2002, travel agencies, which book between

3.6 Concluding Remarks

31.

32. 33.

34. 35.

36. 37. 38. 39.

183

one-fourth and one-half of all rental agreements, would have been entitled to earn 5% of sales for corporate bookings and 10% for other types of bookings. A key factor here is the quantity discount received by car rental companies in their fleet purchases from manufacturers. Given that several of the automobile manufacturers have from time to time held partial equity interests in rental companies, the discounts on fleet purchases may amount to more than 30% of retail car prices. As noted in Loomis (2006), Enterprise differs from Hertz in that it actually itself sells the some 800,000 cars a year that it buys from manufacturers. See also Everson (2007) and Sorkin (2007). By 2006, rental companies began to hold onto cars longer because fewer cars were in short-term lease programs, which were then curtailed by manufacturers, and a larger percentage of the fleet were so-called risk cars because rental companies bore the resale price risk. See McCartney (2013). See Roberts (2018). Car rental company attributes for the largest public companies as of 2011 were approximately as follows: Avis/Budget had a fleet of 270,000 U.S and 120,000 foreign, Hertz had a fleet of 288,000 U.S. and 156,000 foreign, and Dollar/Thrifty, 103,000 U.S. Comparable data is not available for Enterprise Holdings, which bought the National and Alamo brands in 2007. But it is likely that the combined Enterprise fleet is in the area of 600,000. Avis/Budget and Hertz derive around 75% of revenues at airport locations and both generally see a business/leisure mix of around 45%/55%. It is estimated that Enterprise still derives less than 60% of its revenues at airport locations. See Meyer and Oster (1987, p. 165). Although the ICC was charged with a mandate to promote the bus industry while protecting the public interest, as almost always happens in regulated sectors, the ICC ended up better protecting the industry’s interests. Motivation for greater regulation was also kindled by the financial failure of a large Indiana bus company. See also Jackson (1984) and Schisgall (1985). Relevant bus transport studies include Lee and Steedman (1970), Wabe and Coles (1975), Williams (1981), and Williams and Hall (1981). According to the Amtrak 2011 Annual Report, total revenue in fiscal 2011 was $2.707 billion and total expenses, $3.956 billion, including ticket revenues of $1.9 billion. Congress had given Amtrak a mandate to break even by the end of 2002, but the railroad didn’t even come close to breakeven and required emergency cash infusions. In 2010, annual federal appropriations for operating, capital and debt service totaled $1.6 billion. See Machalaba (1999, 2001), where it is noted that Amtrak disputes the inclusion of capital depreciation in the Government Accounting Office numbers, A bibliography and general coverage of the subject is in Vranich (1997). See also Nixon (2012), Bradsher (2013) about the impact of fast trains in China, and Mann (2019) on movement toward profitability. Amtrak came close to breakeven in 2019, but that was pre-pandemic.

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40. The relatively short routes and high population densities as well as high gasoline prices in Europe make rail an obviously more viable and politically acceptable alternative there than in the United States. The different histories of rail ownership in the United States and Europe are covered in Dunn (1981). 41. Zoellner (2014a, b) analyzes the economics of train travel, indicating that highspeed trains are most likely to be profitable and effective for distances of between 200 and 600 miles (1000 km)—a journey lasting between one and three hours. Such “bullet” trains also require dense urban cores which contain numerous transportation options at each end. 42. Additional information is available from American Public Transportation Association information available at www.apta.com. 43. See Pfanner (2014) on Japan’s recent plans for floating trains and Nixon and Soble (2014). 44. See Varadarajan (2019).

References Beam, C. (2015). “The Pople’s Republic of Crusieland: The Cruise Industry Is Coming to China,” Bloomberg BusinessWeek, April 22. Becker, E. (2013). Overbooked: The Exploding Business of Travel. New York: Simon & Schuster. Bradsher, K. (2013). “Speedy Trains Transform China,” New York Times, September 24. Brown, R., Severson, K, and Meier, B. (2013. “Cruise Line’s Woes Are Far From Over as Ship Makes Port,” New York Times, February 15. Bull, A. O. (2013). “Cruise Tourism,” in C. A. Tisdell, ed. (2013), Handbook of Tourism Economics: Analysis, New Applications and Case Studies. Hackensack, NJ: World Scientific Publishing. Cartwright, R., and Baird, C. (1999). The Development and Growth of the Cruise Industry. Oxford, UK: Butterworth-Heinemann. Dickinson, B., and Vladimir, A. (1997, 2008). Selling the Sea: An Inside Look at the Cruise Industry. Hoboken, NJ: John Wiley & Sons. Dowling, R. K. ed. (2006). Cruise Ship Tourism. Oxfordshire, UK: CABI. Dunn, J. A., Jr. (1981). Miles to Go: European and American Transportation Policies. Cambridge, MA: The MIT Press. Edleson, H. (2013). “Car Rental Shuffle,” New York Times, January 8. Esterl, M. (2009). “Huge Cruise Ships Prepare for Launch but Face Uncertain Waters,” Wall Street Journal, December 4. Everson, D. (2007). “Heaps of Trouble: Renting a Car Becomes a Headache,” Wall Street Journal, October 3. Frantz, D. (1999). “Cruise Lines Reap Profit from Favors in Law,” New York Times, February 19. Garin, K. A. (2005). Devils on the Deep Blue Sea: The Dreams, Schemes and Showdowns that Built America’s Cruise-Ship Empires. New York: Viking. Gibson, P., and Parkman, R. (2019). Cruise Operations Management: Hospitality Perspectives, 3rd ed. New York: Routledge. Graham-McLay, C. (2019). “Bad Guests Push New Zealand to Rethink Its Welcome Mat,” New York Times, January 23. Jackson, C. (1984). Hounds of the Road: A History of the Greyhound Bus Company. Bowling Green OH: Bowling Green Popular Press.

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Klein, R. A. (2005). Cruise Ship Squeeze: The New Pirates of the Seven Seas. Gabriola Island, BC, Canada: New Society Publishers. Lee, N, and Steedman, I. W. (1970). “Economies of Scale in Bus Transport,” Journal of Transport Economics and Policy, 4. Loomis, C. J. (2006). “The Big Surprise is Enterprise,” Fortune, 154(2)(July 24). Machalaba, D. (2001). “Amtrak Boss Struggles to Get Train Service on Track in the U.S.,” Wall Street Journal, January 16. ———. (1999). “Can Fast Trains and Local Beer Save Amtrak?,” Wall Street Journal, January 27. Mann, T. (2019). “A Flight Plan for Amtrak,” Wall Street Journal, July 6. Maynard, M. (2002). “Car Rental Industry Is Forced to Shift Ways,” New York Times, November 28. McCartney, S. (2019). “Making 190,000 Tons Feel Cozy at Sea,” Wall Street Journal, December 19. ———. (2013). “My Rental Car Has How Many Miles?,” Wall Street Journal, August 29. McNish, J., Smith, R., Ailworth, E., and Pannett, R. (2020). “Ships Set Sail Knowing the Risk,” Wall Street Journal, May 2. Mervosh, S. (2019). “Carnival to Pay $20 Million for Dumping at Sea, Again,” New York Times, June 5. Meyer, J. R., and Oster, C. V., Jr. (1987). Deregulation and the Future of Intercity Passenger Travel. Cambridge, MA: MIT Press. Moss, T. (2018). “Thais Love Chinese Tourism – to a Point,” Wall Street Journal, February 16. Mouawad, J. (2015). “A Luxury Liner Docks, and the Countdown’s On,” New York Times, March 22. ———. (2013). “Too Big to Sail? Cruise Ships Face Scrutiny,” New York Times, October 28. Nassauer, S. (2010). “What It Takes to Keep a City Afloat,” Wall Street Journal, March 3. Nixon, R. (2012). “Trading Planes for Trains,” New York Times, August 16. Nixon, R., and Soble, J. (2014). “Backers of a Maglev Train Hope to Outpace Acela in the Northeast,” New York Times, October 23. Pannett, R. (2018). “Anger Over Tourist Hordes Sparks Global Backlash,” Wall Street Journal, May 23. Perez, E. (2003). “Cunard’s Grand Gamble,” Wall Street Journal, October 2. Petersen, A. (2011). “The Return of the Class System,” Wall Street Journal, March 30. Pfanner, E. (2014). “Japan Has High Hopes for Floating Trains,” Wall Street Journal, July 8. Roberts, A. (2018). “Car Rental Firms Try to Push Upstarts to the Curb,” Wall Street Journal, June 20. Rodrigue, J-P. (2013). The Geography of Transport Systems, 3rd ed. New York: Routledge. Schisgall, O. (1985). The Greyhound Story: From Hibbing to Everywhere. Chicago: Ferguson J. G. (Doubleday). Seelye, K. Q. (2017). “Cruise Ships Have made Bar Harbor Popular. But have They Ruined It?,” New York Times, December 31. Smith, M., Bennett, D., and Ha, K. O. (2020). “Life and Death on the Zaandam, Holland America’s Pariah Ship,” Bloomberg Businessweek, June 11. Sorkin, A. R. (2007). “Four Brands in Car Rental May Merge,” New York Times, February 14. Stopher, P., and Stanley, J. (2014). Introduction to Transport Policy: A Public Policy View. Cheltenham, UK: Edward Elgar. Terlep, S., and Dezember, R. (2012). “Hertz Deal Would Cap Car-Rental Deal Trend,” Wall Street Journal, August 27. Varadarajan, T. (2019). “A Private Jet May Break the Sound Barrier,” Wall Street Journal, April 13. Vranich, J. (1997). Derailed: What Went Wrong and What to Do About America’s Passenger Trains. New York: St. Martin’s Press. Wabe, J. S. and Coles, O. B. (1975). “The Peak and Off-Peak Demand for Bus Transport: a CrossSectional Analysis of British Municipal Operations,” Applied Economics, 7. Ward, S. (2008). “Full Steam Ahead for the King of Cruising,” Barron’s, April 7.

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Wayne, L. (2004). “Revival of U.S. Shipbuilding Is Set back by German Storm,” New York Times, January 29. ———. (2003). “Political Savvy Gets U.S. Flags on Foreign Ship,” New York Times, December 14. Williams, M. (1981). “The Economic Justification for Local Bus Transport Subsidies,” International Journal of Transport Economics, 8. Williams, M., and Hall, C. (1981). “Returns to Scale in the United States Intercity Bus Industry,” Regional Science and Urban Economics, 11. Zipkin, A. (2015). “Business Travelers Warming Up to Alternative Car Rentals,” New York Times, August 27. Zoellner, T. (2014a). “Making High-Speed Trains Work in the U. S.,” Wall Street Journal, February 1. ———. (2014b). Train: Riding the Rails That Created the Modern World – from the TransSiberian to the Southwest Chief. New York: Viking.

Further Reading Anderson, M. L. (2014). “Subways, Strikes, and Slowdowns: The Impacts of Public Transit on Traffic Congestion,” American Economic Review, 104(9)(September). Bary, E. (2016). “Uber’s Challenge. . .Replacing Rental Cars,” Barron’s, November 17. Brannigan, M. (1999). “Cruise Lines Look to the Land to Get Boomers on Board,” Wall Street Journal, December 6. Brannigan, M. and Perez, E. (2002). “In Takeover Battle, Rival Captains Clash to Woo a Princess,” Wall Street Journal, January 31. Carr, A., and Palmeri, C. (2020). “Carnival Executives Knew They Had a Virus Problem But Kept the Party Going,” Bloomberg Busuinessweek, April 16. Cowell, A. (2001). “P & O and Royal Caribbean to Merge Into Largest Cruise Line,” New York Times, November 21. De Lisser, E. (1995). “Forecast for Cruise Industry Is Stormy, and Some of the Smaller Fleets May Sink,” Wall Street Journal, November 24. DePalma, A. (2001). “Newly Popular in Disaster’s Wake, Amtrak Seeks U.S. Aid,” New York Times, September 25. Erlanger, S. (2012). “Oversight at Cruise Lines at Issue after Disaster,” New York Times, January 17. Finch, C. (1992). Highways to Heaven: The Auto Biography of America. New York: HarperCollins. Fogel, R. W. (1964). Railroads and American Economic Growth: Essays in Econometric History. Baltimore: Johns Hopkins Press. Frantz, D. (1999a). “For Cruise Ships’ Workers, Much Toil, Little Protection,” New York Times, December 24. ———. (1999b) “Alaskans Choose Sides in Battle Over Cruise Ships,” New York Times, November 29. Grady, D. (2002). “Virus Rattles Cruise Industry and Health Officials,” New York Times, December 6. Kay, J. H. (1997). Asphalt Nation: How the Automobile Took Over America and How We Can Take It Back. New York: Crown. Klein, R. A. (2002). Cruise Ship Blues: The Underside of the Cruise Ship Industry. British Columbia, Canada: New Society Publishers Lacher, I. (2005). “For Disney, All the Sea Is a Stage,” New York Times, June 25. Lieber, R. (2016). “With Uber and Lyft Nearby, Rental Cars May Be Ripe for a Comeuppance,” New York Times, December 10.

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———. (2012). “A Rate Sleuth Making rental Car Companies Squirm,” New York Times, February 18. Lubove, S. (1999). “Floating Pork Barrel,” Forbes, 163(9)(May 3). Machalaba, D. (2000). “High-Speed Trains, All Aboard?,” Wall Street Journal, December 5. ———. (1997) “Amtrak Quietly Hauls Cargo on Its Trains, to the Horror of Rivals,” Wall Street Journal, July 30. Mancini, M. (2000). Cruising: A Guide to the Cruise Line Industry. Clifton Park, NY: Delmar Thompson Learning. Mann, T. (2019). “Amtrak Studies Switch From Long Routes,” Wall Street Journal, February 21. Maynard, M. (2002). “Bankruptcy Maneuver Stirs Fight in Airport Car Rental Industry,” New York Times, February 22. Miller, L., and Stern, G. (1996). “Car-Rental Companies Neglect Core Business, Often Skid into Losses,” Wall Street Journal, February 15. Mzezewa, T. (2020). “In Coronavirus, $45-Billion Cruise Industry Faces a Big Challenge,” New York Times, February 13. Newman, B. (2005). “On the East Coast, Chinese Buses Give Greyhound a Run,” Wall Street Journal, January 28. Palmeri, C. (2017). “Cruises Could Be Big Winners in Cuba,” Bloomberg Businessweek, May 15, Paris, C. (2018). “Two Shipbuilders Corner Market for Cruise Vessels,” Wall Street Journal, February 12. Perez, E. (2004). “Cruise Lines Crack Down on Discounts,” Wall Street Journal, August 12. Porter, R. C. (1999). Economics at the Wheel: The Costs of Cars and Drivers. San Diego: Harcourt Brace (Academic Press). Raice, S., and Overberg, P. (2019). “The U.S. Struggles With High-Speed Rail - Illinois Shows Why,” Wall Street Journal, March 5. Raoul, J-C. (1997). “How High-Speed Trains Make Tracks,” Scientific American, 277(4) (October). Rogers, C. (2015). “Why Your Next Rental Will Be a Camry or Cruze,” Wall Street Journal, June 16. Severson, K. (2013). “This Charleston Harbor Battle Is Over Impact of Cruise Ships,” New York Times, February 20. Smith, M., Bennett, D., and Ha, K. O. (2020). “Life and Death on the Zaandam, Holland America’s Pariah Ship,” Bloomberg Businessweek, June 11. Stanley, B. (2008). “Cruise Operators Target Asian Travelers, Pitching Short Trips From Local Ports,” Wall Street Journal, April 28. Stringer, K. (2002). “An Even Better Car Deal: Not Owning One,” Wall Street Journal, December 26. Tagliabue, J. (2005). “Overseas, the Trains and the Market for Them Accelerate,” New York Times, December 30. Yoshino, K. (2008). “Cruise-ship Crime Gets Lawmakers’ Attention,” Los Angeles Times, June 18.

Part III

Being There

Abstract This part describes the lodging and hospitality–related businesses that serve travelers once they’ve arrived at their destination. The chapter covers the most mportant historical and operating aspects that are needed to understand how this sector functions and relates to other travel and tourism segments.

Chapter 4

Hotels

A head in every bed

That’s the goal of every lodging enterprise. But as shall soon become evident, achievement of this objective is easier said than done. Many factors come into play: the state of the economy in general, the specific supply/demand features for the industry as a whole, and of course—as the old real estate saying goes—location, location, and location.

4.1

Rooms at the inn

The airline business is a creation of the twentieth century: It wouldn’t exist were it not for the significant technological advances that have been implemented since 1900. By contrast, the lodging business has been around for thousands of years, pretty much since the beginning of mankind. Although the basics of the lodging industry are relatively simple, the operational and financial features have become increasingly complex and sophisticated. The earliest versions of what we have come to know as hotels or inns go back to the earliest days of recorded history. Inns dotted the main Roman roads that led to ancient Britain and later, in the Middle Ages, hospitality was dispensed by monasteries that provided travelers with separate dormitories. In thirteenth-century China, inns were relay houses established by the Mongols to accommodate travelers and to provide a postal service. A ryokan is simply a traditional Japanese inn. By 1604, inns must have been pretty important to the communities of that time because an act was passed in England that said, “the ancient, true and proper use of Inns, Alehouses and Victualling Houses was for the Receipt, Relief and Lodging of Wayfaring People traveling from Place to Place and not meant for the entertainment and harbouring of Lewd and Idle People to spend and consume their Money and Time in Lewd and Drunken Manner.”1 © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 H. L. Vogel, Travel Industry Economics, https://doi.org/10.1007/978-3-030-63351-6_4

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4 Hotels

Most early guests shared their accommodations with strangers and often set their own rate of payment. And because most guests arrived singly on foot or by horse or stagecoach, there was no need for a large number of rooms. Innkeepers, located primarily along well-traveled routes, were often just homeowners with some extra space and a willingness to provide food and lodging services. Indeed, for most of recorded history, hotels remained small, more like what nowadays would be called an inn or a bed and breakfast than a Hilton or Marriott. Although the word inn has been used since the 1400s, the word hotel which first appeared in London in the mid-1700s, is derived from the Old French ostel. The term came to characterize facilities in Europe and America that could shelter and feed travelers in what could at first be best described as a furnished mansion. The urban “luxury” hotel concept emerged in the 1800s from the roadside inns of medieval Europe, with one of Europe’s earliest being London’s Claridges, which opened under a different name in 1812. This was soon followed by early railroadcentric hotels in London that included the Victoria and Adelaide. And in the United States Boston’s Tremont House was completed in 1829 and was the first to provide indoor plumbing—a “luxury” for its time. The industry’s modern roots, however, go back only to the early 1900s. In 1919, for example, legend has it that on the way to buy a bank Conrad Hilton bought the Mobley Hotel of Cisco, Texas because that was the only way he could get a place to sleep. The erstwhile Mobley then went on to become the first of a worldwide chain, with the Hilton name becoming practically synonymous with the word hotel. Already by the 1910s and 1920s, so-called Tourist Camps or Tourist Courts, the predecessors to “motels” came into being. And by 1933, a group of west coast owners formed the non-profit United Motor Courts Association, whose purpose was to uphold quality standards. This group also published member directories and travel guides that were made available to guests at each location and enabled referrals to similar properties down the road. By the late 1930s, United had around 400 members, with properties extending to California, Texas, and Florida. Through many twists and turns, this group formed the core of today’s Best Western chain. At around the same time a similar group in the eastern U.S. broke away from United to form Quality Courts, which by 1963 converted to a for-profit franchising operation that was the predecessor of Choice Hotels. In the 1930s and 1940s, the lodging industry gradually evolved into larger nationwide chains mainly through buyouts of older, established major city properties. Not much new construction was completed in those decades, scarred as they were by the Great Depression and World War II. More rapid expansion had to await the end of the war, arrival of the middle class baby-boom generation, the sprawl of new suburban communities, technological improvements that opened up air travel to the general public, and construction of the federally funded Interstate Highway System that was born with passage of the Interstate Highway Act of 1956. The new roads were built just in time to feed traffic to roadside motor hotels, soon to be known as motels, that had begun to spring up all around the country and were amenity-enhanced successors to. the older tourist camp inns of the 1930s. The man most credited with popularizing a family-friendly version of these motels by

4.1 Rooms at the inn

193

including in the price of every room the now common but then revolutionary conveniences such as swimming pools, free parking, television sets, and air-conditioning was Kemmons Wilson, a Memphis entrepreneur. Wilson built the first Holiday Inn (named after the 1942 Bing Crosby movie) in 1952 and was soon able to expand the concept nationwide via franchising. Shortly thereafter, chains such as Howard Johnson, Hyatt, Marriott, Radisson, and Ramada were similarly formed. By the 1960s and 1970s, most of the large chains were well established in the United States and attention turned to overseas markets, where conditions seemed ripe for expansion. The broadening of the airline customer base that developed in response to airline price deregulation and introduction of jet-propelled, wide-bodied aircraft such as the Boeing 747 (see Sect. 2.1) made this possible. For the most part, the lodging industry withstood the great inflation and oil-shortage years of the 1970s reasonably well. During this time, however, there was also a steady improvement of hotel management systems, which enhanced productivity through introduction of automated reservation systems and computers into virtually every phase of operations. It was generally thought that all of this would lead readily to vertical integration of airlines and hotels. But the idea of the same company capturing all of the traveler’s spending—from home to hotel and back again—sounded better in theory than it actually worked in practice.2 In the early to mid part of the 1980s, a favorable tax environment featuring accelerated depreciation schedules and easy bank lending policies (boosted by deregulation of the savings and loan industry) stimulated a hotel construction boom that added more rooms than the market could easily absorb. Accelerated depreciation, in particular, increased the attractiveness of hotels as investments that could provide tax shelter against other sources of income and allowed hotels to be operated at a paper loss. Its introduction also underscored the distinctions between the functions of hotel management as opposed to hotel ownership; in other words, the differences between the lodging versus the real estate sides of the business.3 Although changes in the Tax Reform Act of 1986 (the most extensive since 1954) helped end the room boom, it was at least another seven years before new demand caught up with older supply.4 The late 1980s were also characterized by a rising number of hotel transactions, by aggressive bidding for so-called trophy properties that related to the Japanese economic bubble of that time, and by the overleveraging of assets to the point where the servicing of debts began to consume more than 10% of industry revenues.5 Economic recession and the Persian Gulf War in the early 1990s stunted the lodging industry’s growth for a while. But as Fig. 4.1 illustrates, by the middle of the 1990s, profits again soared as sharply rising demand finally absorbed the room glut created in the second half of the 1980s and allowed room rates for higher-end major properties to be significantly raised.6 The Great Recession that began in late 2007 and lasted until mid-2009 later reversed some of these gains. As shown in Fig. 4.2, the effect on leisure and

194

4 Hotels

48

Profit/room ($000)

$ billions

40

10 8

32

6

24 4 16 2

8

-

0 -8

(2) 80

90

00

10

20

Fig. 4.1 Lodging aggregate industry profit, bars (left), and per room, line (right), 1982–2019. Note: House profit is defined as profit before deductions for fixed charges and management fees, while net income includes those deductions. Source data: Smith Travel Research

Fig. 4.2 Comparative leisure and hospitality employment in recessions. Leisure and hospitality index of employment, seasonally adjusted. Source: U.S. Monthly Labor Review, Davila (2011)

hospitality employment in the United States was unusually severe but probably less so in other parts of the world, especially Asia. But the significant as it was, the 2007– 2008 setback was minor when compared to the global pandemic travel restrictions and economic lockdowns of early 2020, when occupancy plummeted by 80% or more and both large and small hospitality companies struggled for survival and depended on government subsidies, loans, and othe financial lifelines to remain viable. The industry’s milestone events are shown in Fig. 4.3. Still, good-time prosperity has not relieved the pressures for even greater efficiency, which has everywhere been increased via consolidation of hotel chains and

1910

The Plaza, New York, opens

St. Francis, San Francisco, opens

1930

Fig. 4.3 Lodging industry milestones, 1890–2015

1890

Savoy, London opens, 1889

Carlton opens in London

Ritz opens in Paris

Claridge's, London, opens

Brown Palace, Denver opens

Lodging Industry Milestones

1950

1970

1990

2010

Marriott bid for Starwood exceded Wyndham buys La Quinta Virus Pandemic

Macau and Singapore gaming soars

Hilton taken private for $26 billion

Bass buys Inter-Continental for $2.9 billion Hilton buys Promus for $3 billion Terrorists attack America Harrah's taken private for $27.8 billion Hilton buys back foreign unit for $5.7 billion Four Seasons taken private for $3.7 billion

Starwood buys ITT for $13.7 billion

Patriot American buys Interstate for $1.34 billion Marriott buys Renaissance for $947 million

Promus merges with Doubletree

Carlson buys Regent Intl. brand from Four Seasons

Starwood buys Westin for $1.6 billion

Aoki sells Westin to Starwood and partners

Saudi Prince Al-Waleed buys 25% of Four Seasons

ITT Sheraton buys Europe's CIGA chain

Four Seasons acquires Regent Intl. chain

Bass Plc. buys Holiday Inns for $2.2 billion

New World Development Ltd. buys Ramada for $530 million

Carnival Cruise begins

Disney World opens

UAL buys Westin

ITT Corp. buys Sheraton

Four Seasons founded

Howard Johnson motels begin

Interstate Highway Act First Marriott First Hyatt opens First automated reservation system (Sheraton)

Fontainebleu opens in Miami Beach Disneyland opens

First Holiday Inn

Inter-Continental chain founded by Pan Am

Grand Met sells Inter-Continental to Japanese Saison Group

UAL sells Westin to Aoki of Japan

Bass Plc. buys Holiday Inn

United Airlines buys Hilton Asian hotels ($1.1 billion)

Ritz-Carlton name rights sold

Pan Am sells Inter-Continental to Grand Met

Sheraton begins Hilton becomes first coast-to-coast chain, buys The Roosevelt and The Plaza

Waldorf-Astoria, New York built

Westin (originally Western) hotels begins

Ritz-Carlton, Boston opens

Conrad Hilton buys first Hotel Olympic, Seattle opens

4.1 Rooms at the inn 195

196

4 Hotels

Properties (000s)

Rooms (millions) 20

220

200

18

180

Properties

16

160 14

Rooms

140

12

120

10

100 92

96

00

04

08

12

16

20

Fig. 4.4 Properties grow larger. Number of worldwide chain-related hotel rooms and properties and average number of rooms per property, 1990–2020. Source data: Smith Travel Research, a CoStar company and author estimates for 2020

brands into just a few large companies. In all, as Fig. 4.4 illustrates, in 2015 there were more than 15.8 million chain-related hotel rooms, 169,000 properties, and 950 lodging brands in the world (and probably an equal number of small bed-andbreakfast, family-owned and operated rooms).7 The average number of rooms per property (not shown), however, has only risen gradually from 85 in 1995 to around 95 in 2019.

4.2 4.2.1

Basics Structural Features

The modern hotel industry is engaged in three distinct activities: owning, managing, and franchising, each of which presents different challenges and opportunities for profit and loss. Generally, the economic classifications range from those in which chains are oligopolistic in terms of their major properties and largely monopolisticcompetitive for all their smaller brands.8 In 2019, of the approximately 58,000 hotels with 5.0 million rooms in the U.S., around 69% were brand-affiliated. Hotels will usually be segmented by their target markets (city-center versus roadside motel), by the prices they are able to charge (luxury, mid-range, budget),

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Table 4.1 Average Daily Rates, U.S. chain hotels, indexed by segment, twelve months ended April 2011 Segment Luxury Upper upscale Upscale Upper midscale Midscale Economy

ADR $US $248.44 144.21 109.37 92.04 73.36 49.54

Multiple of budget/economy ADR 5.0 2.9 2.2 1.9 1.5 1.0

Source data: Smith Travel Research, Inc, a CoStar company

or by the types of specialized services and amenities they primarily provide (resort destination, airport, convention, all-suite, casinos). Hotel segments may also affect decisions as to whether to build new or buy an existing property. According to Smith Travel Research data, in 2015 and also probably currently, it was around 75% more expensive to develop than to acquire a luxury property and 40% more costly for upper upscale properties. But in the upscale and midscale segments the differential was reversed, being around 50% more expensive to buy than to develop.9 Distinctive segments will over time respond differently to changes in economic and local competitive positions and pricing strategies. To illustrate, the average daily rate (ADR) in 2011 at a luxury hotel chain in the United States was five times the rate of a budget/economy room (Table 4.1). Therefore, even a nationwide surge of construction or demand in one type of property does not necessarily affect noticeably the pricing of properties in other segments. The mix of ownership, management, and franchising activities will also determine a company’s risk/reward profile and sensitivity to economic changes. On the whole, though, the hotel industry may be characterized as being especially capital and labor intensive, seasonal, and able to generate large cash flows from depreciation. But unlike airline operations, which tend to have thin and volatile margins, hotel margins tend to fall into a wide range of possible outcomes that relate to a combination of local, national, and sometimes international conditions.

4.2.2

Operating Features

The lodging industry in the United States accounts for about 40% of the world total and extends across nearly 60,000 properties and 5.0 million rooms that generated revenues of around US $220 billion (pre-2020 pandemic). Generally, in the United States and elsewhere, the reasons for travel might typically fall into the following categories even though significant variation from these averages will occur depending on season, region, type of property, and price.

198

Purpose of trip Vacation Transient business Conference or group meeting Other, family, or personal

4 Hotels

Percent of total 25 30 25 20

No matter what the purpose, however, the first and most important characteristic of the lodging facility is its location. In the case of urban hotels proximity to the centers of business, shopping, government, and cultural activities is important, whereas for resorts the main feature is that of being located away from the normal home and business environments. A most important feature of the industry taken as a whole and/or for every local market is total inventory as measured in terms of room-nights—a property’s average available number of rooms times days in the year that theoretically could generate income if the property were to be entirely sold out every night. Room rates, the prices that the lodging facility can charge the traveler, are significantly determined often as much by location and nearby inventory as by any other qualities and quantities. Because posted room (rack) rates are often discounted and because not all rooms may be in service at all times (or provide the same sizes, views, and amenities), the industry tends to focus on the average dailly rate (ADR), which is derived by dividing total room-receipts by rooms occupied. It is thus a weighted average room rate of all the rooms sold on a particular day. Other commonly used metrics that are related to the ADR include revenues per available room (RevPAR)—which further includes food, beverage, entertainment and other items charged to a room—gross operating profit per available room (GoPAR), departmental operating profit per available room (DopPAR), and the sum of net revenues from all operated departments plus rentals (TRevPAR). Here, large fixed cost components will typically cause a 2% drop in net income for every 1% decline in revenues. Although RevPar is probably the most widely mentioned benchmarking metric— it’s simple to calculate and apply and is a combined measure of room rates with occupancy—it does not signify the ability of a property to generate revenue, it’s sometimes distorted (by including various other non-room related items), and isn’t an indicator of the financial soundness of a property. In this respect, a more meaningful key performance indicator (KPI) is gross operating profit per available room (GoPar). Hotel managements always strive to improve the ADR by changing the mix of guests; even a small upward change in ADR can significantly boost profitability given that fixed and semifixed costs of operations are often 40% to 50% of total costs. The impact of a change from Mix A, heavily weighted with tour groups, to a Mix B, weighted more toward individual travelers, might generate a small step-up in ADR of only a few dollars a night. But for a 400-unit hotel, the gain in revenue (12 months
12,000 room-nights a month
$4) generates a significant incremental addition to the bottom line of almost $600,000.10

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199

However, sometimes a more useful statistic is yield per room (YPR). YPR usually provides a more realistic picture of operating performance (when occupancy and ADR are inversely related) than ADR alone because it is calculated by dividing rooms sales by available room-nights instead of occupied room-nights. It is indeed possible to have a situation involving two adjacent hotels of the same size wherein the one with a lower ADR generates a higher YPR. YPR may also be simply expressed in terms of ADRs and the occupancy rate (OR)—a hotel’s capacity-utilization indicator showing the percentage of all rooms occupied—as: YPR ¼ occupancy rate ð%Þ
average daily rate ð$Þ All of these basic data, which include occupancy rates (ORs), ADRs, RevPars, GoPars, and YPR, may then be used to measure the effectiveness of management through compilations of index numbers (ratios) that relate performance to a specific hotel’s competitive set. For example, an occupancy index would be calculated as: Occupancy Index ¼

OR of hotel , Average OR of hotel0 s competitive set

and similarly, RevPar ðYieldÞ Index ¼

ADR Index ¼

RevPar of hotel Average RevPar of hotel0 s competitive set

ADR of hotel Average ADR of hotel0 s competitive set

ARR ðaverage room revenueÞ ¼

Total Hotel Revenue Number of rooms sold

Indexes that are near 100% suggest that the managers of the property have been effective in maximizing revenues and profits.11 For example, if the OR index is far below 100%, it might be that the ADR is too high as measured against the competition. And if the OR index is far above 100%, it is an indication that the ADR might be too low. Also, an ADR index that is below 100% would signal that prices could probably be raised without great adverse affect on the OR.12 The overriding economic principle applied to the setting of per diem room rates is that of price discrimination as discussed in Chap. 1. Hotels will attempt to charge what the market will bear, which is always a function of the customer’s ability and willingness to pay: The same room sold at a different time to a different customer

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4 Hotels

will command a different price. In other words, price elasticity is not a constant but is instead a variable in the pricing decision. Yet the goal is to always maximize profits, not to achieve 100% occupancy. This can be represented for each brand segment by tracing a concave (like an upside down dish) curve that estimates the highest point to which ADRs can be moved so as to maximize profits even though occupancy will be under 100%. Hotels, like airlines, have found a way to technologically address this essential price and room-allocation problem through the use of yield management methods that take into account the ongoing seasonal and other shifts in demand for room inventory on a real-time basis. Implicit in these programs are also considerations about the class of available rooms, the probable timing of incoming reservations, and the probable price discounts needed to encourage further sales. In practice, yield management systems are most effective if all or most of the following conditions are present:13 • • • •

Demand can be clearly segregated into distinct market segments. A large percentage of room reservations have a long lead time. The property provides a variety of different room types and room rates. Demand fluctuates significantly between periods of high and low occupancy.

Although the costs of construction, hotel purchase, and renovation fall into the category of sunk costs that (as discussed in previous chapters) should be irrelevant to future pricing strategies, these elements still also occasionally enter into pricing decisions. A reflection of this appears in the industry’s conventional rule-of-thumb suggesting an ADR equal to one-thousandth the average construction cost of the room. By this rule, for example, a 200-room hotel built at a cost of $20 million ought to have an ADR of $100 (20 million divided by 200 divided by 1000).14 Moreover, just as in the airline-seat, broadcast-time, or fresh-fruit businesses, perishability of product underlies the economic dynamic of room pricing. The revenue that a room might earn is gone forever once the day that it is empty passes. Thus, as the potential use date approaches, there is particular pressure to discount the room price even though this ought to a degree be offset by the need to keep a few rooms available for last-minute bookings, which can often be sold at higher than average prices that desperate latecomers might be willing to pay. The end result of the interplay among factors such as room rates and taxes, seasonality, local competition, location, national economic conditions, and price discrimination tactics is ultimately reflected in the hotel’s occupancy rate. In addition, successful hotels have: • a proximity to demand generators and retail and pedestrian-friendly neighborhoods; • a business mix that is not dependent on one segment and that is resilient to macroeconomic weakness; • well-controlled costs; • close attention to local supply dynamics; • ability to provide unique experiences.15

4.2 Basics Fig. 4.5 (a) Average U.S. hotel occupancy rates, (b) average daily hotel room rates, current and constant dollars, 1970–2015. Source data: SmithTravel Research, a CoStar company

201

140

$

%

90

Current $ ADR

105

75

70

60 OR (%)

45

35 Constant $ ADR

0

70

80

90

00

10

30

Since the late 1980s, the average occupancy rate for the whole industry has generally ranged from 62% to 65%, and averaged 64.8% between 1975 and 2000. This compares to an estimated industry-wide breakeven occupancy rate, according to consulting firm PriceWaterhouseCoopers (PwC) research, that declined (in part as a result of lower debt and equity financing costs) to approximately 53.6% in 1999 as compared to 62.6% in 1992.16 Occupancy and ADR trends for the industry are displayed in Fig. 4.5. On the microeconomic level, hotels thus operate in much the same way as do airlines or theme parks. The sunk and initial fixed costs are high, most marginal revenue after breakeven is highly incremental to profits, and up to half of the operating cost structure may be variable. Just as in the airline sector, hotel managers are thus incentivized to impose surcharges and fees whenever possible.17 Departmental Data Hotel operations are a composite of many different businesses all rolled into one. Although hotels are defined as places that provide overnight lodging for travelers, they most often do much more than just make a bed, bath, and bureau drawer available to guests. Hotels will usually provide food and beverage services. And operations can be further broken down into categories such as housekeeping, telephone/Internet, retail stores, and convention sales, as examples. The degree of emphasis on each area will vary with the nature of the property’s market niche. A full-service luxury hotel would provide a wide array of services and require many operating departments. It would derive perhaps two-thirds of total revenue from sales of room-nights. On the other end, a budget motel might not provide anything more than a room and a bed and not have even a basic food and beverage facility on the premises. Room-night sales would then be nearly all of total revenues. No matter what the extent of services, however, operating ratios for each department (as defined by the Uniform System of Accounts for Hotels—the generally accepted standard of global lodging industry practice) illuminate a property’s financial performance and productivity trends.18 Over time each type of property will develop standard expected ratios for each department and any significant deviations from the standards will then alert the property’s managers to problems and/or

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opportunities for improvements. Is the food costing too much? Is the liquor being stolen? Is the housekeeping department over- or understaffed? All of these questions can only begin to be addressed if the department operating ratios are analyzed and compared to typical expected values. Although it is possible to calculate hundreds of different operating ratios, the most important ratios would involve the rooms and the food and beverage departments. The first breakdown would be to see what percent of total sales are derived from rooms, food and beverage, telephone, retail shopping, and other distinct activity-segments. The next breakdown would involve the matching of expense to revenue categories so that each department’s operating profit margin and contribution to total operating income can be seen. For a mid-market urban hotel, for example, the rooms department might generate two to three times the operating margin of the food department. Further calculations such as average food and beverage spending per room and cost of maintenance per room would, of course, also provide useful information for management.19 Generally, however, it is the labor cost percentage—determined by dividing total department labor costs by total department revenue—that will be among the most important in providing a benchmark overview of operations (with food and beverage usually the highest ratio). Information from such labor ratios may then be supplemented with productivity trend comparisons that are made in terms of the number of employees per 100 occupied rooms, which, in the U.S. hotel industry, fell from an average of approximately 81 in 1990 to 73 by the early 2000s. Revenue and cost structures in terms of average ratios to sales along with department percentage apportionments for major regions of the world in 2019, are shown in Table 4.2. The gross operating profit (GOP) line at the bottom of this table is of particular significance because it is directly related to the industry’s standard measure of profitability: Earnings before interest, taxes, depreciation, and amortization (EBITDA) taken as a percentage of revenue. A large or luxury hotel running at an EBITDA margin of 35% or above is generally considered by financial analysts to be doing well. For budget hotels, unburdened by the need to have large staffs, fancy dining areas, and health clubs, the margin can be 40–45%. But for both hotel categories, payroll will usually account for more than half of rooms-department expenses and be a semi-fixed cost over the short run, with longer term payroll and benefit costs tied, especially in major cities, to negotiated labor union contracts (e.g., Hotel and Restaurant Employees International Union). Additional rooms-department costs tied to occupancy include cleaning and guest room supplies, laundry, linen, and uniforms. Management Contracts Often the owner of a property, perhaps a local builder or business entity, seeks the appreciation potential of a property’s real estate and access to its cash flow but has no particular expertise in management of the hotel’s operations. In other instances, a hotel chain prefers to spread its scarce capital over more units by taking a small (or no) share of equity in a property. In both instances, a management contract, which is an agreement between the principal hotel owner and

4.2 Basics

203

Table 4.2 Operating departmental apportionments in percent for major regions, 2019 Occ% Av. Number Rms ARR—USD$ Revenue % Rooms F&B Other Total Revenues Departmental Exp % Rooms F&B Other Dept. Total Dept. Exp. Total Dept Profit % Undistributed Op. Exp. GOP %

Africaa, b 0.71 247 102.35

Asiab 70.5% 302 129.66

Europeb 76.2% 206 171.37

Mid-Eastb 69.5% 286 165.72

USAa 74.9% 206 179.70

61.6% 29.2% 9.2% 100.0%

56.8% 38.3% 4.9% 100.0%

67.4% 27.6% 5.0% 100.0%

58.0% 36.0% 6.0% 100.0%

69.9% 23.4% 7.7% 100.0%

17.9% 65.0% 31.8% 32.9% 67.1% 26.0% 40.9%

23.1% 66.1% 40.6% 40.4% 59.6% 24.8% 34.6%

27.7% 74.4% 42.1% 41.3% 58.7% 22.3% 36.0%

20.9% 60.5% 42.3% 36.5% 63.5% 27.7% 35.7%

18.1% 44.6% 47.9% 36.7% 63.3% 25.5% 37.7%

Source: aPKF Hospitality Research, a CBRE Company, reproduced with permission and based on the 11th edition of the Uniform System of Accounts for the Lodging Industry (USALI), courtesy Robert Mandelbaum. See pip.cbrehotels.com b Courtesy Pablo Alonso, Hotstats.com

a management company, takes advantage of a hotel chain’s brand. It is the brand that creates the contract’s value and that attracts the customers and owners. The concept was innovated by Conrad Hilton and broadly implemented by Marriott starting in the late 1970s. Management companies, usually owned by the chains, have the expertise in hotel operations that an owner might not have. And through management contracts, a chain can enhance its brand name and capture a greater flow of activity over which to amortize costly investments in design and reservation systems infrastructure. Because of the minimal capital invested, hotel chains will usually find that management contracts are among their most profitable activities. Management contracts are complex legal and financial documents that may specify a broad range of operations (including the construction phase) over which the management company has control. For the management company, however, the key element is that it is paid whether or not the hotel is profitable. When business conditions are poor it is the owner who suffers the loss and when things are going well it is the owner who reaps the reward. But there are variations on this theme, with incentives built into most contracts so that the management company would benefit to a degree from any pickup in profitability. Competition among many hotel management companies limits the fees that can be charged in most markets. A typical management contract fee will be at least 3–4% of total property revenues or $800 per available room per year. The contracts can be structured in terms of pre-opening and post-opening responsibilities and may also

204

4 Hotels

include a mixture of both basic and incentive fees that vary according to the degree to which predetermined performance targets are met. In particular, incentive fees are often implemented on a sliding scale with better performance rewarded with an increasing share of profits. Such fees might be taken as a percentage (perhaps ~10%) of gross operating profit (GOP) which might also be defined as total income before fixed charges and management fees (IBFCMF). In practice, the larger the basic fee, the smaller the incentive fee (or vice versa).20 Another factor to consider in such contracts is the maintenance capital expenditure assumption that reflects the furniture, fixtures, and equipment (FF&E) reserve that is specified in hotel management or lending agreements.21 Such FF&E reserves for a full-service hotel might amount to 4–5% of annual hotel revenues and are cycled every five to seven years to fund nonstructural renovation projects that are needed to offset normal wear and tear and to remain technologically competitive (e.g., Wi-Fi in every room). Franchising Hotel companies have increasingly become global brand marketing organizations that look to franchising—the licensing of an exclusive territorial right to a name, a product, or a system—as a way to expand and to leverage up their brand equity through an enlarged distribution system. For the chain, a franchising arrangement can enhance profitability because fees earned from franchise operations are relatively large as compared to the amount of capital invested.22 The big chains thus shed large debt loads and risks and are then “asset light.” As a local business, the franchisee is also more likely than a large, distant operator to be responsive to local market needs and conditions (even though this does not necessarily preclude franchising by large companies). However, it is usually the franchisee that, operating as a small-business independent entity, arranges and is liable for construction, mortgages, and ownership of the property. Approximately 93% of hotels in the U.S. are franchised operations (and the early 2020 virus-related shutdowns and travel restrictions hit franchisees especially hard).23 In return for various fees—that might normally reach as high as 20% of revenues—the chain management provides the franchisee with considerable support that would often include site feasibility studies, help in financing, mass purchasing discounts on supplies, advertising, and perhaps most important of all, access to the chain’s reservation and yield management systems and frequent traveler programs. From the standpoint of the customer, there should in theory then be no discernible difference in service between the chain’s owned and operated properties and those that are franchised. In practice, though, it is not unusual for franchise operators (especially those of the mom-and-pop variety) to come into conflict with the chain’s management over fees, upkeep requirements, and territorial infringement issues. Franchisors also sometimes have problems with slow-paying, nonconforming franchisees, some of whom may also be skimming (i.e., excluding some sales from gross sales used as a base for calculation of various franchise fees). An even larger risk for franchisors is that franchisees may “milk” the brand (and thus weaken it) by maintaining minimal standards while enjoying RevPAR premiums obtained from the brand’s power to

4.2 Basics

205

attract customers. Because of such conflicts, properties sometimes change allegiances, every few years flying a different chain’s flag.24 Yet fee structures can vary, with the typical terms of a franchise agreement calling for a fairly large initial payment that is scaled to the number of rooms in the property, a royalty of 4% of room revenues, an advertising fee of 1.5% of room revenues, a reservation fee of 3.0% of room revenues (or alternatively a fixed dollar amount per reservation), and various other small charges for signs and sundry services provided to the franchisee.25 Time-Shares (VOIs), Condos, and Alternatives The subject of time-sharing of hotel units–typically condominium units built purposely with kitchen, living room, and other such amenities—could just as easily fit into either of the following sections on marketing or finance; it contains elements of both. The concept originated in the French Alps in the late 1960s and, in the inflation-racked 1970s, spread to the United States (which experienced a sharp decline in the condominium market). According to the American Resort Development Association (ARDA.org), a trade group, in 2019 there were approximately 1582 such resorts (206,380 units, with average occupancy rate 79.3%) in the United States that generated sales of $10.5 billion on an average timeshare-interval selling price of around $22,942. Large hospitality companies are the leading developers in this industry segment. Most major chains, particularly those with properties in destination-resort locations, have developed programs that permit vacationers to buy the guaranteed right to use a room for an interval of a few days each year and/or to swap such rights for someone else’s right at another property. The rights to use the hotel’s facilities through such vacation ownership interests (VOI) extend for a number of years into the future, often the life of the time-share purchaser. Such rights are generally structured in one of five ways: 1. 2. 3. 4. 5.

time-share ownership, interval ownership, leasehold time-sharing, vacation licenses, club memberships.

Of these structures, time-share ownership is by far the most common, entailing transfer of a fee simple estate (i.e., largely unrestricted property) to the purchaser.26 In all cases, however, relative prices will depend on a resort’s location and amenities offered, unit size, and season. In return for a relatively large upfront payment plus a commitment to pay annual maintenance and other fees, the purchaser of these time-share contracts has what amounts to the equivalent of an equity interest in a lodging at a favorite destination resort. The buyer is guaranteed the space at a nearly fixed cost even if regular room rates in the same property were to double or triple over time and even if it is impossible for non-VOI guests to get a reservation. The buyer also must put up only a fraction of what alternative lodging from, say, renting or buying a vacation house in the same resort area might cost. Up to fifty-one other buyers—one for each

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week of the year (but typically fifty, allowing a week for renovation)—may be contributing to the total buyers’ pool. Sales of the time-share interests will usually cover a large part (if not all) of the total investment in development of a property, thereby allowing the resort developer/ operator to pay down debts or to collect interest on the floating cash balances.27 For the hotel property owner, the largest risk—most likely related to an economic recession and/or a spell of tightening monetary policy by the Fed—is that potential buyers might encounter such difficulty in financing a unit that it significantly impairs the value of this kind of contract. For vacationers, often subjected to high-pressure sales tactics, the risk is that the purchased units cannot readily be resold. Still, initial property development profits will usually be quite high and developers will normally have the opportunity to earn additional profits by loaning funds to purchasers. The time-share manager will make a profit on the spread between the wholesale cost of mortgage funds and the price at which such financing is provided to buyers: Buyers will usually put down between 10% and 30% and take a sevenyear mortgage on the balance. Such loans and other receivables may then also be bundled and sold to large investors through securitization arrangements. The operator may also generate income from resort management fees and find further advantage in allowing VOI participants the option of swapping their time for points that can be used for stays at other hotels in the chain or for airline tickets or merchandise. Moreover, the property has a guaranteed occupancy rate far into the future, with relatively little risk that the time-sharer will renege on the commitment. Bit even if the buyer does renege, the same unit can usually be potentially be re-sold, or the lodging can be rented to non-VOI guests at prevailing regular room rates.28 In sum, a time-share operation typically profits by playing four distinct roles: first in developing and selling VOIs, then in financing customer purchases of the units, then in managing the resorts, and finally, in renting the pool of unsold or unused intervals. As timeshare projects move from construction to sell-out, the revenue mix shifts, with the consumer financing and management functions becoming proportionately more important as more units are occupied over more intervals.29 Property managements also hope to reap further promotional and brand-building benefits by having so many relatively prosperous guests experience the joys of the facility through what the buyer perceives as being a personal-equity interest. Alternatives to hotels, VOIs, and condos are, however, also becoming increasingly available in shared-space non-lodging accommodations serviced by online companies that include Airbnb, CouchSurfing, HomeAway (owned by Expedia), and TripAdvisor (including Flipkey, Holidaylettings, and Niumba). These companies are focused on vacation rentals—a global market that annually processes millions of paid listings with estimated collective revenues in 2019 of around $85 billion (50% or so in the U.S. and the other 50% spread over more than 175 countries). In this, about half are primarily rentals by owners (RBOs), with the other half led by professional property managers. It is notable that by 2014 Airbnb had already averaged 425, 000 guests per night, equal annually to 155 million guest stays and well above the 127 million annual guests for Hilton Worldwide. This quickly expanded by 2021 to 6 million listings in 100,000 cities.

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Table 4.3 Out-of-home food service segment revenues, 2015 and 2021 est Commercial Eating places Bars and taverns Managed services Lodging places Retail, vending, recreation, mobile Non-commercial restaurant services Military restaurant sales

US$ billions $648.0 471.1 20.6 49.5 36.7 70.2 58.5 2.7

% of totala 72.7 3.2 7.6 5.7 10.8 9.0 2.7

a

Total not exact due to rounding and overlapping segment data Source: National Restaurant Association Pocket Factbook 2015 at: http://www.restaurant.org/ News-Research/Research/Facts-at-a-Glance

Gross Booking Value (i.e., the dollar value of bookings inclusive of host earnings, fees, and taxes) a key performance metric, reached $38 billion covering 327 million nights booked in 2019. Other important valuation metrics include the number of listings, average number of guests per listing, average rent per guest, and the company’s fee structure.30 How much of the demand for such services is incremental or substitutional (i.e., taking demand away from hotels) is not yet known. But the interest thus far appears to be disproportionately concentrated in leisure travelers and in younger demographics—with a competitive effect primarily on lower-end properties. Restaurants Out-of-home food services were already known in ancient Egypt and Rome and Medieval venturers could often find simple meals being served at the earliest of inns, hostelries, taverns, and monasteries. And coffee houses (cafés) first appeared in Constantinople around 1550 and began to (quickly for that time) spread throughout continental Europe and the U.K. (e.g., Oxford and London). Not all hotels have restaurants, but the vast majority of them do, with food service in lodging establishments accounting in the United States for 5.7% of total awayfrom-home food service industry revenues of around $650 billion (Table 4.3). However, the devastating pandemic of 2020 led to the closing of at least 12% of locations (100,000+) and an estimated loss of $240 billion of revenues, so that aggregate data for 2021 was approximately the same as it had been six years earlier. Hotel-restaurants can range from simple buffet-style breakfast setups to luxury dining rooms and banquet halls for elaborate dinners. Although the primary purpose will always be to service the hotel’s visiting commercial and leisure travelers, such restaurants may also attract local patrons and provide catering services for local parties and events. Yet the whole operation may not be operated at all by the hotel but instead be leased out to an independently owned food-service firm or chain, with the hotel merely collecting a fee based, in part, on revenues generated. But no matter what the mix of patrons or the ownership/operating arrangement, restaurants would follow accounting classifications according to the Uniform System of Accounts for Restaurants. After a cost allocation for leasing of space, the two

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principal costs for any restaurant operation would include those for food and labor. Most restaurants will generally be profitable if such prime costs can together be held to below 60–65% of revenues. Cost ratios such as those for food, beverages, and labor are accordingly constantly scrutinized. It is normally necessary for costs as a percentage of total sales for food and beverage to be no more than around 30%, labor (payroll, taxes, and benefits) 30–35%, and occupancy (rent, utilities, and other) 10%. The restaurant’s bar would usually carry the highest profit margins given that costs of drink materials might be 20% of sales and staffing costs per revenue unit would normally be lower than in the rooms or other departments. Here, inventory control is an essential and decisive management ingredient. Profitability of food and bar services, however, will also both depend on the surrounding area’s restaurant and tavern density per 10,000 population (i.e., competition) which is an important determinant of rents, special events, and sales potential.31 More directly, revenues also depend greatly on menu prices and selections, service levels provided, the effectiveness of advertising and promotion and affiliation with the hotel’s or food chain’s brand, and the number of times seats or tables are used (i.e., turned over) per day. For fast-food and bistro-style restaurants, high turnover of seats is imperative because menu-item prices are relatively low, whereas high-priced luxury dining facilities will allow for a more leisurely experience.32 Prices are, of course, a function of many variables but are usually cost-based and would initially be estimated by multiplying the cost of food components by a factor of three so that the food cost percentage of total revenues is around 33%. From a hotel’s perspective, it is most important to align a restaurant’s capacity, menu-item prices and offerings, atmosphere, and marketing as closely as possible to the likely budgets and needs of business travelers and tourists without foregoing the profit potential that can be gained by also attracting diners from the surrounding local community.

4.2.3

Marketing Matters

Because most hotel markets are highly competitive at least for some parts of the year (or sometimes parts of the week)—the shoulder or low seasons, for instance— marketing is a critical tool in filling the rooms and maximizing returns on invested capital. Most major hotel chains spend at least 2–4% of total revenues on advertising and have also—in emulation of airline frequent-flyer marketing methods—begun to actively develop frequent-stayer (i.e., loyalty) bonus programs.33 In addition to the usual advertising and promotional campaigns that companies in most industries conduct, hotels will use to advantage reservation systems, frequent traveler programs, brand names, and the services of destination marketing organizations (i.e., DMOs, which are also known as convention and visitors bureaus). DMOs concentrate on the place, product, price, and promotional aspects of a specific

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location or region and prefer the term “visitor” to “tourist”. But it is he brand names that most suggest to the customer which of four broad categories—luxury (high-end full-service), basic full-service, limited-service, or extended-stay—a particular property presumes to represent. For marketing and sales purposes, customers may also be generally segmented into three categories: • Transients (60%): Rooms reserved at rack rates, with corporate negotiated, package and other rates booked via third-party websites. • Goups (35%): Rooms are sold simultaneously in blocks of 10 or more. • Contracted (5%): Rooms (for airline crews and permanent guests) are sold at contract-stipulated rates. Reservation Systems Although there was a time not so long ago when a reservation system was no more than a pencil’s marking on a smudged index card, reservation systems have come to function as the main traffic-control and business allocation nerve centers of a hotel’s operations. Without the reservation systems, most modern hotels would probably shut down and chaos would reign because neither the hotel desk clerks nor the arriving guests would know who is entitled to accommodation. Current technology embodied in reservation networks allows hotels to handle a volume of traffic that would have been inconceivable in earlier years. Here again, as in other networks, the Law of Connectivity (discussed in Chap. 2) is operative. A manifestation of this is that reservation systems are also potent marketing tools that can promote a property’s unique charms and benefits to faraway travelers who might not otherwise be so informed. The efficiency, courtesy, and general friendliness of the reservation system operators can make a good immediate impression on the prospective guest as perhaps no other promotional medium could. This is important because even small changes in occupancy rates can make a large difference in total profitability: yield management systems can then optimize room rates for specific customer classifications and dates.34 The profitability of such yield strategies will to some extent further depend on the needed degree of interaction between Global Distribution Systems (GDSs), which are intermediary networks (e.g., Amadeus, Travelport) that for a fee facilitate transactions between hotels and travel agents (especially when booking related services from airlines and cruise ships). Brand Names The power of a brand comes from the embedded information— concerning identity, image, and market positioning—that it efficiently conveys to the potential customer. Although brands don’t always provide the consistency of product and service that they should, in the hotel business a brand name at a minimum suggests the probable pricing range and level of service to be expected and perhaps functionality and prestige as well. Brands such as the Four Seasons and Ritz-Carlton convey a sense of luxury that the perfunctory, perfectly good budget rooms of Motel 6 do not have and are not designed to offer. Boutiques, which attempt to convey a youthful sense of style and account for more than 3% of hotels in the United States, are also strongly branded.

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Table 4.4 U.S. hotel brand categories, selected examples, 2019 Category Luxury (high-end, full-service) Basic full-service/Upper Scale Limited-service/economy/midscale Extended stay Boutique

Representative brands Four Seasons, Ritz-Carlton, Peninsula Hilton, Hyatt, Marriott, Sheraton Hampton, La Quinta, Motel 6, Moxy, Avid Homewood Suites, Residence Inn W, Andaz, Chatwal, Edition, Modo

In all, brands make marketing statements that attempt to funnel each class of traveler into the promoted chain’s units (but with the percentage of branded hotels in each major region of the world varying from around 40–70%).35 Brand names are thus important intangible assets that must be continuously supported, often in the form of frequent-stay reward point programs that are similar in concept to airline frequent-flyer programs.36 But especially for luxury and independent operators, online quality-of-experience reviews need to constantly be cultivated.37 Large chains also attempt to use branded locations (e.g., Times Square in New York, Hollywood in Los Angeles) as associative tags for Internet Search Engine Optimization (SEO) strategies. And chains also often initiate new brands that will not only appeal to different travel segments and fill gaps in coverage but that will also likely enlarge the pool of collectable fees. It is estimated that as of 2020 the worldwide number of hotel brands is around 1100, with Marriott operating 30, Wyndham, 20, and Hyatt, Hilton, and InterContinental between 17 and 19. Examples of brands in each of five major categories appear in Table 4.4. The effectiveness of marketing in terms of branding efforts, reservation systems, and pricing structures are then all reflected in the own and cross price elasticities of demand for lodging. The own price elasticity of demand is defined (see also Sect. 2.3) as the percentage change in room demand in market segment X caused by a change in room rates in segment X, all other things being equal. The cross elasticity of demand is defined as the percentage change in room demand in segment X that is caused by a percentage change in room rates in segment Y, all other things being equal. In other words, for two competing hotels in close proximity, room rate increases (decreases) in one hotel will lead to room demand increases (decreases) in the other hotel.38 A convenient way to gain marketing insights is to compare properties and features within categories or locations via scatters diagrams. By plotting occupancy rates versus ADRs (Fig. 4.6), it is easy to see how Las Vegas compares to London or New York or Atlanta. Las Vegas emphasizes relatively low room rates to attract visitors to gambling, food, and other attractions and, despite the large number of rooms (>150,000), is able to fill most of them most of the time with the help of its large trade show and convention center business. Atlanta, in contrast, hosts the world’s busiest airport (110.5 million passengers in 2019 according to IATA/ ICAO and Airports Council data) and is a major convention center site (#5 rank in the U.S.), but its hotels average a much lower occupancy rate than those in Las Vegas.

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Fig. 4.6 Average estimated occupancy rates in percent versus estimated average daily rates, 2012

90

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85 London

OR (%)

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Hong Kong

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Online Travel Agencies (OTAs) Such agencies have become major participants in all travel industry sectors but perhaps more so in hotel bookings than in any other sector. Most OTA websites function as metasearch engines for prices and offerings that appear on their network. But competition between reservation websites of the largest chains and the largest OTA’s has intensified greatly as chains and also airlines have developed their website portals to the stage that they can profitably and directly attract travelers and minimize intervening (“middleman”) fees. For Biooking/ Priceline and Expedia, the number of room-nights booked still measurably exceed the number of airline tickets and car rental days processed, which means that room bookings drive much of OTA segment revenues. The primary economic factors that affect the OTA industry are global GDP growth and exchange rates, although the price of oil has at times been another factor to consider. Digital travel sales worldwide as of 2020 are around $760 billion and are largely split by the three major OTAs. Although North American traffic has historically dominated with a share of around 30% of the total, activity in India and China has risen in conjunction with growing middle-class tourism and travel demand in these populous countries. OTA revenues are generated in three overall categories that include agency fees earned from an OTA’s intermediary function, merchant service-related fees for credit card processing and travel packaging; and advertising, which is the smallest source. Yet each of the three largest OTAs focuses on different—and sometimes overlapping hybrid—business models and strategies: Booking/Priceline on agency aspects, Expedia on merchants, and TripAdvisor on advertising.39 Booking/Priceline: Priceline.com, Agoda.com, Booking.com, RentalCars.com, Kayak.com, Ctrip, OpenTable.

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Expedia: Expedia.com, Travelocity.com, lastminute.com, Zuji.com, Egencia, Hotels.com, Hotwire.com, CarRentals.com, eLong (China), Trivago, HomeAway, and Orbitz (which includes Cheaptickets.com, ebookers.com, asiahotels.com, and HotelClub). TripAdvisor: Viator, Flipkey, Vacation Home Rentals, La Fourchette, TheFork, Tipbod.

4.3 4.3.1

Financial and Economic Aspects Financing Frameworks

The hospitality industry has always depended on ready access to capital for purposes of new construction, refurbishments, or acquisitions. And financial performance has been studied from many different angles that include input factors such as energy consumption and labor costs, customer relations aspects, and the various financial ratios that have already been noted.40 As a result, many specialized variations of debt and equity financing structures have evolved. The variations include many different types of mortgages, real estate investment trusts (REIT), and real estate mortgage investment conduits (REMIC). External sources of funding also tend to vary by region, with North American operators more reliant on REITs and CMBS (commercial mortgage-backed securities) financing than are properties in Asia which are largely funded by large parent companies and those in Europe which rely more on sale-leaseback arrangements. Mortgages Whereas it makes sense to use secured debt instruments such as equipment trust certificates for movable collateral such as airplanes and rail cars, it makes more sense to use mortgage-related securities for hotel companies with assets that are of long life and are fixed in location. Of course, hospitality industry companies will tap the conventional equity and debt or commercial lending markets whenever they can. Especially in this industry, however, companies would likely make use of other secured-debt instruments, primarily in the form of mortgage bonds.41 Although such bonds are nonrecourse and sometimes provide a claim against a specific building, they would more likely have ultimate claims on all the company’s property. Collateral trust bonds closely resemble mortgage bonds except that the claim for this type of bond is against securities held by the corporation. The creation, servicing, and distribution of mortgages and mortgage-backed securities has itself become a large industry whose interests have traditionally meshed with those of the hotel sector. The driving element, however, has been Wall Street’s ability to securitize practically any asset that can over time throw off a reasonably predictable stream of cash. Hotels happen to have many assets—everything from reservation systems to time-share mortgages to bundles of management contracts—that are prospective candidates for such securitization treatments.42

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REITs In essence, REITS are conduits that take rents and pass these on to investors. As investment vehicles they may be generally categorized as bonds masquerading as stocks because their market valuations are sensitive to those economic and financial variables that will normally more affect the prices of bonds than of stocks. REITs came of age through a 1960s Act of Congress that excused companies from paying any corporate taxes if they passed along 95% of their income to shareholders and had 75% of assets in defined real estate, cash, and government securities. The rules as originally devised and then modified in the Tax Reform Act of 1986 (specifying that REITs could manage their own properties) are spelled out in Internal Revenue Code Sections 856 (a) through 860. Further changes, reducing the dividend payout requirement from 95 to 90% of taxable income, were made in the REIT Modernization Act of 1999. Two fundamental types of REITS, the mortgage REIT and the equity REIT, are of importance to hoteliers because they may provide another source of financing that other travel-related companies might not as readily tap.43 It is also possible to have a hybrid mortgage and equity REIT, although most REITs specialize in the types of properties (apartments, hotels, office buildings, golf courses, etc.); regions; or cities in which they invest. The mortgage REIT invests in loans secured by real estate, with the mortgages both originated and underwritten by the REIT or purchased in the secondary market. Revenues are derived from interest earned on mortgage loans and income can be affected by fluctuations in interest rates and/or loan defaults. Equity REITs, in contrast, take an ownership interest in a property as opposed to acting as a lender. Shareholders in such REITs earn dividends or rental income from the buildings and can benefit from rising property values when the properties are sold for a profit. But although a corporation or a trust that qualifies as a REIT generally does not pay federal income tax, REITs are not allowed to pass tax losses to shareholders.44 From a financial performance and valuation perspective, REITs had long been judged on what, prior to new standards fully implemented in 2002, had been known as funds from operations (FFO).45 This metric is analogous to the EBITDA accounting convention that would be typically used in valuations of airlines, hotels, casinos, theme parks, or media properties. However, critics had faulted the methodology because the reported numbers were not audited and tended to overstate earnings while being subject to widely differing interpretations.46 Some companies, for example, had included gains on property sales, whereas others hadn’t. The new standard instead uses operating net income per share, which excludes special gains and losses from sales of properties. Non-REIT hotel operating companies are known as C corps and have the advantage over hotel REITs in that they can reinvest their capital back into the business rather than having to distribute most of their income to shareholders through dividends. However, hotel REITs (the largest one being Host Marriott) have two other alternative structures that they might adopt and that mitigate some of the capital-draining limitations of pure hotel REITs. They can either turn themselves into limited partnerships, which do not rely as much on public equity markets for

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capital, or they can create some nonqualified subsidiaries which, under REIT rules, allow REITs to collect more nonqualifying income (e.g., management fees). With such nonqualified units REITs can collect, through management of third-party properties, more than 5% (and up to 25%) of income. REMICs Real Estate Mortgage Investment Conduits are packages of commercial real estate loans that are assembled and then sold by investment bankers in the secondary financial markets. Such packages are particularly attractive to the major hotel franchise companies and hotel developers who use these funds for acquisitions or to refinance existing obligations. Only those developers or operators with the strongest balance sheets are candidates for REMIC financings. Collateralized mortgage-backed securities (CMBS) are also similar to REMICs in purpose and in the way they are assembled and marketed. Loans and Equity In addition, developers of hotel properties will often seek nonrecourse project financing—wherein only the property itself serves as loan security—from life insurance companies, savings and loan organizations, commercial bankers, and credit companies. Such loans would generally fall into three categories: • Short-to-intermediate debt instruments • Long-term debt instruments • Equity structures Short-to-intermediate loans are used by developers when a project involves high risk, i.e., when permanent financing does not cover the entire development cost or when the developer does not want to share equity. Loan categories of this type include construction loans that are tied to the prime interest rate. Going out further on the debt instrument time horizon are combinations of construction and term loans in which the developer provides at least 10% of the equity or some other combinations of permanent loans and mortgages.47 Equity structures might of course also include various limited partnership arrangements or joint ventures between lenders, operators, investors, and developers. For existing properties with few prospects of significant near-term profitability sellers—who would understandably be reluctant to realize write-downs and losses—will also sometimes turn to seller financing, which is comparable to a car dealership providing a loan to the car buyer. In this situation, the buyer would typically pay between 25% and 50% of the price upfront and the seller would finance the balance. The risk here is not eliminated but potentially postponed.

4.3.2

Accounting Issues

Although lodging industry operating systems have not required the development of unusual accounting concepts that are outside the realm of GAAP, companies in this

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industry often lease equipment and the complications of lease accounting, as discussed in Chap. 2, would also be relevant here. Another hotel accounting feature involves asset sales. Most chains will, in the course of business, be continuously buying and selling properties and will thus have no need to specifically denote in the accounting statements any of the profits and losses thereby earned or incurred unless such results are individually significant (i.e., material) in total impact. It is still possible, however, that a series of relatively small transactions could have collectively large and distortive affects on reported period income statements. Accounting treatments are of course also relevant in asset valuations as covered in Sect. 4.4.48

4.3.3

Economic Sensitivities

Total aggregate demand for hotel industry services is sensitive to changes in general economic conditions and follows growth patterns similar to and closely integrated with changes in other travel segments—for example, as shown in Fig. 4.7, to air travel. The rate of growth in demand for rooms, as found by Miller (1995, p. 56), is approximately 75% of the rate of change in GNP and similar correlations between average daily room rates and the consumer price index have been observed. Slowing of economic growth will normally result in a downturn in occupancy rates, if not also room rates, within six to nine months at the latest. Some evidence even suggests that whenever year-over-year RevPar gains disappear, the industry is heading into a 15

% change

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5 0 -5 -10 -15 -20 1985

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downward phase. Prevailing and prospective monetary and fiscal policies, consumer confidence levels, and many other factors—all of which are outside the control of hoteliers—influence if and when an economic slowdown will occur.49 All of these macroeconomic factors acting together affect RevPar averages and lodging stock prices. Figure 4.1 has shown that hotel industry profits have been quite volatile and sensitive to overall economic conditions and Fig. 4.8 illustrates that the annual percent changes in hotel occupancy rates and percent changes in U.S. GDP closely track each other. An even higher correlation, according to Smith Travel Research, is to gross private domestic investment (GPDI). Studies by PwC suggest that the correlation between demand and real GDP is normally around 0.9 and that demand elasticity relative to real GDP averaged 1.2 from 1967 to 1991 and 0.8 from 1991 to 2000 (0.5 in 2003).50 Directional changes in RevPar are also typically anticipated by and reflected in hotel share prices with lead times of at least six months, but this is not always a reliable indicator. Demand for rooms is also rather sensitive to changes in the price per gallon of gasoline, with a rise in fuel prices reflected relatively quickly in fewer room-nights sold. Although a similar inverse relationship is seen when airline ticket prices are raised, the effect is normally not as immediate or as large, probably because rising business-related air travel costs can usually be at least partially passed along through higher product prices. In all, about one-third of all lodging guests arrive by air. And it is still too early to assess the eventual long-run aggregate room-demand effects from advanced video technologies.

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Room supply and demand trends and changes in demand for lodging relative to changes in airline travel cost indices (with a one-year lag) and to changes in oil prices (with a two-year lag) appear in Fig. 4.9.51 The rate of new construction is another important business cycle-sensitive variable that can affect local occupancy and room pricing over the long term.52 Up to the mid-1980s, for example, tax laws had encouraged the building of many new rooms, with the result that it was nearly a decade before demand began to catch up with supply. Once that happened, however, the industry experienced sharply rising room and occupancy rates and profits that extended into the mid-2000s. This was reflected in industry pretax profits per room—an important variable in terms of stock market valuation perceptions—rising from zero in 1992 to approximately $6400 in 2015 (Fig. 4.1). The incremental net supply of new rooms (often tracked through construction data offered by F.W. Dodge) relative to the existing base—i.e., the new-to-existing, n/e ratio—is therefore important in assessment of local room-addition prospects. Such n/e (adjusted for income strata) ratios would, however, be much less useful in assessing the potential room demand in rapidly developing and densely-populated countries such as Brazil, China, and India, where rooms per capita are known to be extremely low as compared to in the U.S. or Europe. The ratio of rooms per thousand people in the U.S. is around 15.6 versus 1.0 or less in many emerging countries.53 The middle of Table 1.6 shows the industry composite operating performance for the recent years leading up to 2019 and Fig. 4.10 tracks lodging share price index changes, which tend to lead changes in RevPars. Another short-run economic factor that might adversely affect margins, especially during upturns, would be shortages in the local supply of labor. Although hotels use a mix of union and nonunion workers depending on location and position, overall labor costs would still be at least somewhat correlated to the national minimum wage and be affected by immigration trends. In boom times, minimum wage workers may also easily find higher paying jobs in other service industries. And although the role of unions in hotels and restaurants is not as central to operations as in airlines, union agreements (e.g., with the Hotel and Restaurant Employees or Culinary Workers Union) will normally influence growth trends in productivity and wages. The scope of industry sectors in terms of number of establishments, receipts, and payrolls is shown in the North American Industry Classification System (NAICS) data of Table 4.5. From this it can be seen that the casino segment has since 2002 improved labor-efficiency the most in terms of payroll as a percent of receipts (from 28.2% down to 23.4%). The non-casino hotel/motel segment has, however, apparently been able to expand receipts per employee somewhat faster (probably by being able to raise prices more and/or provide more service amenities) than in the other groups. And as an indicator of productivity improvements, in non-casino hotels, payroll as a percent of receipts fell to 24.1% in 2017 from 27.1% in 2002 to 24.1% in 2002. Technological advances have also helped the hotel industry to operate much more efficiently than in the past. The Internet has become especially important in allowing travelers to bypass travel agents and to see in the comfort of their offices and homes

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(a) millions

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4.4 Valuing Hotel Assets

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%change 15 10

RevPar

5 0 -5

S&P Lodging Stocks

-10 -15 -20 80

85

90

95

00

05

10

15

Fig. 4.10 Annual average percent changes of monthly S&P lodging share price index versus annual percent changes of lodging industry RevPar, 1980–2019

instantly available descriptive brochures, guest reviews, and room rate and reservation options. Yet technology can cut in the other direction too if, through advanced teleconferencing and e-mail and Internet presentations, people find that they can reduce their expenditures on travel.54 Hotels, like airlines, probably have fairly limited opportunities to find cost efficiencies of scale outside of the obvious administrative and corporate areas of advertising, reservation systems, frequent traveler programs, property clustering, and computerized billing. For instance, no matter how large a chain or a property grows, it will still take the housekeeping department a fairly constant amount of time to make up a room.55 Nevertheless, it is likely that there remains enough cost saving available on the administrative side to keep the global merger wheel yet spinning for a long time to come.

4.4

Valuing Hotel Assets

The valuation of hotel assets is usually a straightforward process in theory if not always in practice and the valuation concepts outlined in Sect. 1.6 provide an introductory overview. For analytical purposes, the terms hotel or real estate are practically synonymous as the standard financial methods centering on projected

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Table 4.5 Hotel, casino, food service, and amusement/theme park industry number of establishments, total receipts, payrolls, and employees, 2017, 2012, 2007, 2002 Payroll No. of Receipts (annual) Employees Estabs ($1000) ($1000) (paid) Hotels (except casino hotels) and motels (NAICS 721110) 2017 53,978 184,410,520 44,367,619 1,608,327 2012 38,763 136,887,332 35,808,135 1,453,812 2007 48,108 122,033,327 31,592,733 1,462,464 2002 46,295 89,357,109 24,204,364 1,366,850 Casino hotels (NAICS 721120) 2017 419 65,659,109 15,363,016 433,472 2012 392 51,004,734 13,113,296 409,568 2007 363 44,868,577 12,037928 379,382 2002 283 33,417,673 9,428,235 373,299 Food services and drinking places (NAICS 722) 2017 657,885 678,148,247 202,539,170 11,881,174 2012 598,512 516,551,775 152,774,615 10,048,664 2007 571,621 433,404,527 124,433,560 9,630,090 2002 504,641 321,400,508 92,599,349 8,307,625 Amusement and theme parks (NAICS 71311) 2017 352 17,815,792 4,140,837 160,978 2012 483 12,368,602 2,951,269 125,697 2007 634 12,206,545 2,391,331 101,247 2002 772 8,101,592 1,858,356 94,107

Receipts per Employee ($)

Payroll as % of receipts

114,660 94.158 83,444 65,374

24.1 26.2 25.9 27.1

151,473 124.533 118,268 91,673

23.4 25.7 26.8 28.2

57,078 51,405 45,005 38,687

29.9 29.6 28.7 28.8

110,672 98,400 120,562 86,089

23.2 21.0 19.6 22.9

Source: U.S. Economics Census, 2017 and earlier, Accommodation, Casino, and Food Services, U.S. Census Bureau, Available at: Data for years prior to 2012 may not be fully comparable because of classification changes and revisions

cash flows, risk premiums, and discount rates are used regardless of whether a property is referred to as a hotel or as real estate. In valuing hospitality real estate book value, or carrying value, which is the original purchase price less accumulated depreciation, does not usually convey useful information about current market conditions. Assessed value, which is the value assigned to the property for tax purposes and which is defined in terms of market value, may come a little closer to the price for which a property might be sold. Similarly, insurable value, the value based on replacement cost, and liquidation value, the price an owner is compelled to accept upon quick liquidation, are also misleading. Real estate appraisal would usually require valuation of a fee simple title, which is without limitations or restrictions (except for zoning laws) as compared to a partial interest title in which there are specific limitations or restrictions. After this, the methodology breaks down into at least four possible approaches based on cost, comparable sales, sum-of-the-parts, or income capitalizations. Further distinctions between market values and investment values are also often necessary as investors

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221

Table 4.6 Sum-of-the-parts approach Owned properties Leased properties Managed and franchised fees Other (incl. timeshare) Total Less projected long-term debt Plus cash Equity value Divided by fully-diluted shares outstanding Projected price per share

EBITDA $700 50 500 90 1340

Target multiple 9.0
7.0 12.0 9.0 10.0

Enterprise value $6300 350 6000 810 13,460 4460 540 5000 1250 $4.00

will have required return objectives, tax and cost of capital considerations, and time horizons that usually differ from those of a strategic buyer of a property.56 The cost approach might be useful in providing a rough estimate of what it might cost to construct a new building in a specific region. An approximation of reproduction cost could be obtained by multiplying the original cost of a property times a current construction price index that would be a multiple of the construction cost index at the time that the property was built. The cost approach, however, says nothing about valuing income-producing property cash flows. The asset transfer price comparison approach can provide useful price information when a number of similar nearby properties have been recently sold (i.e., transferred to another owner). The comparison works best, for example, with apartments in the same building or single-family homes on the same block and it may sometimes be a guide to valuing hotels situated near each other if the properties are of similar size and age. Comparable hotel data will often be measured on a transfer price per room or per square foot basis.57 In addition, the asset’s transfer price will be divided by the gross revenues generated by the asset to derive a price to revenues multiple. That is, a hotel transferred for $12 million and generating $6 million of revenues has been sold at a multiple of two times revenues. Also related to this is the average gross room revenue multiplier (GRRM)—a method commonly used for valuing economy hotels but that is less often applied in the valuation of upscale properties. Those are normally valued on the cap rate calculations as described in the next paragraphs. GRRMs across all location categories have tended to range from 2.5 times to 3.6 times. A sum-of-the-parts approach would typically take each of a company’s major operating lines—usually owned properties, leased properties, managed and franchised fees, and timeshares—and apply a target multiple (which depends on interest rates and recent overall stock market multiples) to the EBITDA of each operating line. A summation of those values less long-term debt plus cash would provide an equity value as in Table 4.6. Most often, however, hotel real estate would use the cap rate (income capitalization) approach. Here, a property’s income stream (cash flow excluding maintenance

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reserves) over a specified period is projected into the future and an appropriate capitalization rate (multiple) is then applied to this forecasted income stream. The cap rate represents the market’s sentiment of the moment, the cost of debt, the required return on equity, and the upside returns that buyers hope to achieve. This widely accepted real estate benchmark is calculated as a hotel’s net operating income (NOI) divided by its value or sale price. Although the annual NOI used in the calculation will be projected a year forward, the more verifiable trailing-twelvemonths data will, especially for risk-averse lenders, always be a decisive factor. The appropriate capitalization rate—in all cases tied indirectly to interest rate conditions in the economy as a whole—may be derived from a number of sources including capitalization rates for similar recent property transactions. Generally market value ¼

average annual income stream , overall capitalization rate

but this formula greatly oversimplifies the situation. A more sophisticated formula that takes into account the amount of debt to total financing would be: overall capitalization rate ¼ Pd
MC þ ð1  Pd Þ
Re , where Pd is the percentage of debt financing to total financing, MC is the mortgage constant, 1Pd is the equity financing percentage (because the sum of debt and equity is always 100%), and Re is the annual required return on the equity portion. The mortgage constant term stands for the capitalization rate for debt, which is the ratio of annual debt service to the original loan principal. It is a function of the interest rate, term of loan, and frequency of loan payments. For example, on $1 million of debt, an annual mortgage payment of $100,000 that includes the cost of interest and return of principal would result in a mortgage constant of 10%. A hotel loan for 70% of value, an annual interest rate of 10%, a mortgage constant of 0.10, and a required equity return of 15% would result in the following capitalization rate (CR): Capitalization rate ¼ 100
ð0:7
0:1Þ þ 100
ð0:3
0:15Þ ¼ 11:5% This capitalization rate may then be used to find the property’s capitalized value by dividing an estimate of average annual income by the capitalization rate (i.e., the market value equation). The property’s net operating income stream over its economic life—often defined as property-level EBITDA less recurring capital expenditures—may also be discounted using the capitalization rate (CR) as a discount factor. Discount Factor ¼ 1=ð1 þ CRÞn where n is the year number of the income stream being discounted. The sum of the discounted yearly income streams—then provides the property’s valuation estimate, an example of which (assuming no salvage value after five years) is shown in Table 4.7.

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223

Table 4.7 Property income streams discounted using overall capitalization rate, an example Year

1

Income stream (NOI) Discount factor @ 13% Discounted income stream Total Plus: Cash Construction-in-progress Receivables & deposits Minus: Long-term debt Implied net asset value (NAV)

$1 million 0.8850 $885,000 $3,517,300

2 $1 million 0.7831 $783,100

3 $1 million 0.6931 $693,100

4 $1 million 0.6133 $613,300

5 $1 million 0.5428 $542,800

1.500,000 2,000,000 1,500,000 3,000,000 5,517,300

As can be seen, if the net income stream is that of a hotel operating company, then the implied present value would further require that cash, construction-in-progress, and receivables and deposits be added and long-term debt be subtracted from the sum of the discounted annual streams to arrive at an implied net asset value (NAV). This would then naturally be divided by the number of rooms (and perhaps other features such as land size) to provide an estimate of NAV per room (or per acre or hectare). NAV is thus the theoretical measure of what would be left over after all tangible assets were to be sold and all liabilities were to be paid. As a surrogate for liquidation value, it provides a more accurate current-market measure than balance sheet book value which has typically been distorted—possibly over many years or decades of tax law changes and owners—by application of various historical cost estimates and depreciation methods. Even so, however, derivation of NAV may often be based on arguable assumptions and judgments related to untrustworthy pricing data for comparable properties and to inaccurate estimates of transaction costs and tax consequences. Asset valuation procedures will also generally be unable to directly capture in the discount factors applied to projected cash flows all of the intangible elements and encumbrances that might affect transfer prices.58 One such important feature would be the initial cap rate-spread to treasury securities (which tends to narrow in boom times and widen in recessions).59 For specific property types, room revenue multipliers would also be significant valuation factors given that Luxury properties might, for instance, trade for 5.6 times, Upscale about 4.1 times, and Economy 3.7 times. Other intangibles might further include the following: prospective local, regional, national, and international economic conditions prospective costs of fuel and of travel in general taken relative to incomes current visitor demographic and income profiles and forecasted changes

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Table 4.8 Stabilized income assumption method illustrated Stabilized income assumption: Mortgage terms Interest rate Mortgage constanta Amortization years Loan-to-value ratio Equity dividend pre tax WACC Debt (mortgage) Equity Overall capitalization rate Capitalized value Equity dividend Annual debt service

$11.00

mm

5.79 5.21 $11.00

Mm

8.00% 9.00% 20 50% 10% 50% 50%





Rate of return 9.00% 10.0%

¼ ¼

11 50% 50%





0.095 10.0% 9.00%

¼



0.045 0.05 0.095 115.789 115.79 115.79

a

Mortgage constant combines the return on capital (interest rate) and the return of capital through a sinking fund Based on deRoos and Rushmore (2002, p. 78)

prospective amount of new local competition to be built price elasticities (i.e., the prospective ability to raise room and food prices without driving customers away) potential for adding rooms or other facilities and attractions such as on-premise health clubs and food courts potential need for renovations and upgrades potential alternative uses of the land degree of recognition as a brand name or as a “trophy” property management agreement terms and potential encumbrances prospects for new local roads, transport hubs, or airport facilities or convention centers to be built availability of government subsidies or tax breaks local political and environmental conditions The weakness of all approaches, though, is that the farther out the income stream projections are made, the more unreliable and unrealistic they are apt to become. An alternative may thus be to instead forecast a property’s likely sale price at the end of an investment period (rather than over its economic life) and to then discount to present value the anticipated sale price at the end of the investment period. This amount would then be combined with the sum of the discounted present values of the interim cash flows and would provide an estimate of a property’s total present value. An illustration of a method that uses a single, stabilized estimate of net income rather than a projected net income stream over time is shown in Table 4.8. For hotel real estate companies that are publicly held the sum of the estimated asset valuations divided by the number of shares outstanding provides an estimate of

4.5 Concluding Remarks

225

value per share. For hotel management companies, valuation is also related to the strength of the brand, future unit additions, length of management and franchise agreements, and expansion opportunities. For franchises, valuation requires estimates of the average life of contracts in the system, the probability of contract renewal, and the discount rate. The estimated valuations as described might most frequently and practically be applied to privately negotiated transactions (including both portfolios of multiple properties and single assets). In any specific market, many factors will influence the buy-versus-build decision, but the most important would likely be the costs of acquiring existing properties as compared to the costs to acquire land and build new. Other things being equal, if it costs less to build (per room, say) than to buy existing properties, then there would likely be more new construction and vice versa. All of this is, of course, further affected by interest rates and by the cyclically varying ability and willingness of banks to underwrite commercial loans for either purpose. The easy financing environment that inflated the global housing-industry bubble into 2007 also created a similar peak (Fig. 4.11) in the total value of hotel transactions (~ $30 billion in the U.S.) at around the same time. Projections for 2020 began with cautious optimism but the global pandemic then significantly reduced transactional appetites for hotel prperties. A comprehensive valuation process should thus consider the three methods outlined: capitalization rates on operating income, transfer prices for comparable properties, and estimated replacement costs per room. Several additional factors including prospective new supply, property improvement plans, branding and loyalty programs, nearby market configurations, and prospective taxes must also be considered. Shares of public companies will generally become attractive for purchase (or a company for takeover) if and when market prices are significantly under (by at least 20%) the estimated asset value per share.60 No matter which valuation methods are used, however, as has often been said with regard to real estate and hotels, it all boils down to location, location, and location.

4.5

Concluding Remarks

It used to be that a hotel operator just had to change the sheets and the towels. Modern hotels have, however, evolved into complex organisms, practically alive with their own daily and seasonal patterns and tied into global information networks. Most hotels today are highly dependent on the technology of reservation systems and yield management methods that are similar to those used by airlines and described in Chap. 2. The major chains have the capital, know-how, broadly distributed properties, and asset bases to widely spread the costs of implementation. For this reason, the industry will continue to consolidate, even though across-theboard cost economies of scale are not likely to be seen. Large chains will also continue to emphasize asset-light operating models that generate more fees while

Total hotel transaction volume ( in billions USD)

2005

2006

2007

2008

2009

2011

Americas

2010

2013

Asia Pacific

2012

2014

EMEA

2015

2016

2017

2018

2019

H1 2019

H1 2020

Fig. 4.11 Global hotel investment volumes by region, 2005–2020E (excluding casino and land site sales). Source: Jones Lang LaSalle Hotel Investment Outlook, 1H 2020, reprinted with permission

$0

$10

$20

$30

$40

$50

$60

$70

$80

$90

$100

226 4 Hotels

4.5 Concluding Remarks

227

maintaining brand standards. And in the not-too-distant future (viz. late 2020s) the definition of a luxury hotel will likely be expanded to include extremely expensive rooms with spectacular out-of-the-world views available while orbiting the earth!61 Growth of this industry will always be tethered to events and conditions beyond direct control. Airlines might raise ticket prices, the cost of oil might rise sharply, local labor availability might be scarce, and a new competitor comes to town. However, some things such as service quality, property upkeep, advertising and promotion, and room rates fall largely into the controllable category. In the race to stay ahead, hotel managements have no choice but to take advantage of every available tactic and tool. Notes 1. From an Encyclopedia Britannica article on hotels. 2. United Airlines proved this through its purchase of the Westin chain in the early 1980s and its sale of Westin a few years later. Also, Pan American World Airways founded the Intercontinental Hotel chain in 1946 and the parents of TWA and United each owned Hilton International, the chain’s overseas arm. None of these airline-hotel arrangements lasted for long. 3. In hotels, for example, once fixed costs are covered, a large part of every incremental dollar of revenue contributes to profits and the variance of earnings and cash flow (EBITDA) tracks fairly closely. However, in the real estate business, depreciation and interest expenses are prominent characteristics with much greater variance between earnings and EBITDA usually evident. 4. The Tax Reform Act of 1986 ended the Investment Tax Credit, which since 1976 had allowed builders to deduct 6 5% of the capital cost of a project against taxes, and it also changed partnership rules. In addition, depreciation schedules were increased to 31.5 years from 18 years and earned income could no longer be sheltered by passive investment losses. Moreover, use of so-called nonrecourse bullet-loan financing—popular in the 1980s and featuring five to ten years of payments with a large payoff required at the end of the loan period— later led to a large number of hotel foreclosures when, in the midst of the weakdemand environment of the early 1990s, many payoffs came due. 5. By comparison, as of the end of the 1990s, debt service consumed only around 4% of industry revenues. 6. An alternative industry profit definition is that of house profit, i.e., profit before deductions for fixed charges and management fees. 7. The UNWTO previously compiled the following data, which is no longer available but is of historical interest. In 1997, the number of bed-places in Europe were 11.375 million, in the Americas, 9.334 million, and in East Asia/ Pacific, 6.708 million. These accounted for around 95% of all places. 8. In a local situation, a hotel or motel may be the only one in town or for miles around. In that case, the particular property would be a monopoly. 9. In the economy segment, the buy versus build differential was minimal.

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10. See Murthy and Dev (1993). Studies suggest that higher price positioning drives RevPar more than rising occupancy. See Enz (2013) and Enz et al. (2015). 11. In Hayes and Ninemeier (2007, pp. 196–98). 12. A night with a system-wide OR above at least 90% is known in industry jargon as a “compression night.” The number of such nights per year is generally a reliable indicator of demand strength given that many fewer such compressions will occur in an economic recession. 13. This follows Vallen and Vallen (1996, p. 104). 14. The Hubbart Room Rate Formula, described in Vallen and Vallen (1996, p. 231, and 2000, p. 299) and in Vanhove (2011, p. 133), provided a widely used standardized approach for setting average room rates until the industry began using newer computer software that enabled more precise tracking of demand estimates in the application of yield management techniques. The Hubbart costoriented formula, essentially working backward from a projected occupancy rate, estimates what the average room rate should be to be able to cover all expenses and to then provide a specified return on investment. The formula divides fixed costs, variable expenses, and a “reasonable” return on the property investment by the estimated number of rooms sold. It thus prices rooms from the perspective of the entrepreneur rather than the guests. It also provides no detail related to room size and class of quality variations while being imprecise as to occupancy rate and return on investment assumptions. Gregor (2006) reports that the cost of construction for high-end properties had risen (doubled from 2003 due to costs of labor, oil, marble, steel, concrete, sheet rock, and copper) to around $400 a square foot in 2006 and that it was no longer unusual for such established properties to fetch $1 million per room (or key) on transference. 15. From Major (2017). 16. Selected segment breakeven occupancy rates in 1998 were found to be as follows: Upscale Midscale (without food & beverage) Economy Upper-tier extended-stay

63.0% 49.0% 41.0% 60.0%

17. Analyses by the New York University Tisch Center for Hospitality and Tourism have indicated that surcharges and fees (e.g., for reservation cancelations, minibars, early departures, Internet, gym) reached a record of $2.7 billion in 2017. See also Kirkham (2017a) and Carrns (2019). McCartney (2015) explains that frequent-stayer (i.e., loyalty) bonuses such as Marriott’s rewards program, when later redeemed returned an average of 9.4% for every dollar spent. That is, for every $100 spent, $9.40 was returned in free rooms. Such loyalty programs in hotels differ from those in airlines, wherein the carriers directly support the travelers” benefits and have an incentive to restrain costs. As major hotel chains do not actually own most of the properties that bear their brand names, it is

4.5 Concluding Remarks

18.

19.

20.

21.

22.

229

instead the franchisees that finance the guest loyalty programs by paying into a pool of funds. Loyalty programs are important to the large chains because they bind dozens of different brands together and also provide the foundation for multiple credit-card rewards. The Uniform System of Accounts is a set of standards first published in 1926 by the Hotel Association of New York City, the founding chapter of the International Association of Hospitality Accountants. The system established standardized formats and account classifications to guide individuals in the preparation and presentation of financial statements and permits the statements of similar types of lodging properties to be readily compared. Uniform Systems of Accounts for the Lodging Industry (USALI) is available through the American Hotel & Motel Association Educational Institute. (www.ahma.com). The 11th revised edition was published in 2014 and implemented starting in 2015. Important changes involve reporting for labor costs, information and telecommunications, rooms department charges, resort fees and surcharges, and mixed ownership properties (e.g., condo-hotels). See McCartney (2020). According to the Uniform System of Accounts for the Lodging Industry (USALI), income received from transient reservation cancellations is recorded as room revenue, but it is not always clearly identified, whereas fees from cancellation of group meetings (attrition) are usually seen in a separate line item in miscellaneous income. Hotels have begun to tighten their transient cancellation policies in an attempt to better control inventory. See article by Robert Mandelbaum of CBRE in HNN, July 5, 2016. As Andrew and Schmidgall (1993, p. 350) note, “an incentive fee may be 15% of IBFCMF when the basic fee is 2% of gross revenue, or 10% of IBFCMF when the basic fee is 4% of gross revenue.” Segal (2009) reports that management fees for the Four Seasons chain are generally 3% of the gross and approximately 5% of profits, while owners must also chip in for chainwide funds for global sales, marketing, and reservations. Commercial lenders will normally insist on a dedicated FF&E reserve for mortgaged properties. Commercial mortgage-backed securities (CMBS) usually require an FF&E reserve of 5% of annual revenues. Sometimes, though, hotel owners unencumbered by mortgages elect not to fund a separate reserve for each property by instead managing cash flow to accommodate such ongoing expenses. Competitive pressures have made the need for upgrading has become more frequent and thus FF&E reserves of 6% may now be readily justified. Some of the decision as to the proper percentage depends on the levels at which a hotel will capitalize an expenditure or expense it. Bary (2003) writes of hotel developers eagerly seeking the expertise of the Four Seasons luxury hotel management. Consequently, Four Seasons can obtain favorable terms. Typically, a deal will run for over fifty years give the company a base fee equal to 3% of hotel revenues and an incentive fee pegged at 5–7% of profits. However, because there is no “hurdle rate” or level of profitability that must be attained before the fees are charged, such arrangements are better than those at competitor Ritz-Carlton. Four Seasons, thus, draws cash as soon as most

230

23. 24. 25. 26.

27.

28.

4 Hotels

of the hotels it runs are profitable. Also, operating costs, including those for Four Seasons workers, are covered by hotel owners, with only sales, marketing, advertising, and administration covered by Four Seasons. In Brown (2001) it is suggested that Marriott’s typical variable incentive fee may sometimes be as high as 50% of profits. See Creswell (2020). See Bernstein (2008) and Hudson (2010). A list of recent fees is available at the Lodging/Hospitality Franchise Fact File found at www.LHonline.com. In the time-share structure, the purchaser becomes a tenant in common with other purchasers of the same unit and owns 1/52 of the unit. Interval ownership is similar in concept except that common tenants agree to an interval in which there is an exclusive right to use for a specified period. The interval ownership typically reverts back to tenancy in common after between twenty and forty years. In leasehold structures, the purchaser leases the premises for a specified period of time but prepays the lease. Although vacation license structures also contain a similar “right to use” during designated times or in specific periods, the time-share buyer in these arrangements does not have an ownership interest in real property. Neither do purchasers of club membership arrangements, which are usually of shorter term (ten years) than the others. As noted in Binkley (2004), unfilled time-share units are also sometimes rented out for daily room rates. Destination clubs, which buy luxury homes in vacation destinations, however, sell memberships. The usual arrangement is to make a large upfront deposit and to then pay annual dues that are often more than $10,000. In return, each year members receive an allotment of days in which they can stay at the destination properties. However, members do not own any of the properties. Because households may own more than one interval, the number of intervals owned can grow faster than the number of timeshare owners. See Everson (2007) and Berzon and Hudson (2011). For example, if each unit is sold for $20,000 for each of fifty-two weekly periods a year and there are 100 units, the developer’s gross sales potential is $104 million. A variation of the VOI concept, condominium hotel units, has also more recently evolved. In a condominium arrangement, the hotel unit is sold to a single buyer who can then make the unit available to the hotel operator for rental to visitors when the owner isn’t using the unit. The hotel operator and the unit’s owner usually share (~ 40% for the owner) the rent revenues thereby generated, a feature that helps the buyer to more quickly pay down the mortgage on the unit. The condo owner also has the potential to benefit from price appreciation of the property even while deriving tax benefits from interest and depreciation deductions. As noted by Corkery et al. (2008), the outcome is not always favorable for owners. See Alsever (2006) and Carney (2008). Morgenson (2016) discusses pressure sales tactics and the difficulty in reselling units. See also www.pwc.com/us/en/technology/publications/assets/pwc-consumer-intelli gence-series-the-sharing-economy.pdf.

4.5 Concluding Remarks

231

For hotel owners and operators, such condo unit arrangements make it easier to finance hotel construction, reduce marketing costs relative to those in timeshare sales (because the unit is sold once, not fifty times), and provide additional hotel room inventory. According to Morrissey (2000), advertising and marketing costs absorb anywhere from 35 to 50% of a time-share unit versus only 10–13% of the price of a hotel-condo unit. See also Smith (2004), Pristin (2004), and Corkery (2006). Another variation to time-share ownership follows a country-club business model in which access to luxury resort homes is purchased with an upfront membership fee that begins at $150,000 plus payment of annual dues that might run to as high as $20,000 a year (for a maximum of sixty days of visits to any number of properties). This arrangement allows access to club properties for as many as perhaps six weeks a year and includes extensive services. The clubs are able to generally avoid overbooking in peak seasons by limiting memberships in each club. Companies involved include Private Retreats, Exclusive Resorts, Mirabella Estates, and Odyssey Club. See BusinessWeek, September 15, 2003; Smith (2003), and Johnson and Corkery (2006), and Sullivan (2012). According to the American Resort Development Association (www.arda.org/aif-foundation/research/timesharedatashare/overview.aspx), a timeshare trade group, in 2014 net timeshare sales were $7.9 billion generated from 1555 resorts in the U.S., the average sales price was around $20,500, and the occupancy rate was 80.7%. See also Kaufman et al. (2009) 29. Timeshare accounting follows the distinct protocols of the three business segments involved. For the resort development and sales aspect, FAS 66 and 67, “Accounting for Sales of Real Estate” and “Accounting for Costs and Initial Rental Operations for Real Estate Projects,” are respectively applied. These have been later supplemented in 2004 by FASB amendments via Statement of Position (SOP) 04-2, “Accounting for Real Estate Time-Sharing Transactions.” For projects that sell deeded interest in real estate and where the developer can immediately recognize 100% of the interval sales as revenues, there are additional criteria (e.g., developer has received at least 10% of the purchase price, the period for refund cancellation has expired, the receivable is collectible) that must be met. But for projects not yet completed, all revenues are deferred and recognized using the percentage of completion method. Costs are normally capitalized during the development and construction period, and are then amortized using a relative sales value method. In attempts to focus their business, finance, and growth strategies, large hospitality chains have often spun-off their timeshare units into separately traded public companies. Marriott International, Hilton Worldwide Holdings and Wyndham Worldwide are examples. 30. Airbnb profits from a 3% processing fee from hosts and a 6–12% guest fee on each transaction. See also Moyer (2017) and Benner (2017). Airbnb and other companies such as WhyHotel ad YouRent further extend the business model to convert vacant apartment building units to use as hotel units. Booking fees charged to both guests and hosts are the main source of revenues for the company. Bookings from local boutique hotels are also carried on the

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system. See also Brooker (2016), Kusisto (2017), and Farronato and Fradkin (2018). 31. According to Bureau of Labor data for 2015 cited in Stabiner (2016), restaurant density in the U.S. was highest in New York, New Jersey, and Connecticut, with 16.9 per 10,000 populations. But even in non-pandemic times about 25% of restaurants fail in their first year and 60% after three years according to a study by Parsa et al. (2005). 32. Guidelines for restaurant turnover might be as shown in the following table: Square-foot requirements and turnover rates.

Dining room Commercial cafeteria Coffee shop with counter and table service Deluxe restaurants Popular-priced restaurants

Turnover in patrons (sq. feet per seat) 13–18 15–18 13–18 11–15

(per seat per hour) 1.5–2.5 2–3 0.5–1.25 1–2.5

Source: Walker and Lundberg (1999, p. 77), The Restaurant: From Concept to Operation, 3rd ed. Reprinted with permission of John Wiley & Sons, Inc

As shown in Powers and Barrows (2003, p. 74), differences in service levels are reflected in productivity of staff, where direct labor hours per 100 guests is estimated at 10.5 hours for fast-food establishments, 18.3 hours for cafeterias, 20.7 hours for family restaurants, and 72.3 hours for luxury restaurants. See also Lundberg (1994), Schmidgall et al. (2002), McCracken and Adamy (2008) and Walker and Lundberg (2014). The restaurant industry overall employed 13 million people, which makes it the third-largest employer in the United States after the U.S. government and the health care industry. 33. Clark (2018) covers Marriott’s adjustments to Starwood’s loyalty program. 34. To circumvent travel agency fees, booking sites such as RoomKey.com have been launched by a consortium of large chains. See Salzman (2013) and Edleson (2013), in which the four models typically used by online travel agencies (OTAs) are discussed. OTAs can book rooms in ways similar to traditional travel agencies (sometimes referred to as global distribution systems, or GDSs) and the hotel then pays the OTA 5% commission. There is an auction system as used by Booking/Priceline; an opaque model as used by Hotwire.com in which consumers don’t know what brand they are buying; and a merchant model, in which an OTA buys room inventory from hotels and the hotel then typically pays a commission of between 18% to 38%. OTAs are estimated to account for nearly 20% of all bookings and the percent of room revenues paid to them by hotels may generally range from 10% to 25%. In 2016, Phocuswright research estimated that OTAs accounted for $99 billion of global hotel bookings, and in the U.S., $31.4 billion. See Kirkham (2017b). As of 2017, chains such as Hyatt began to challenge OTAs like Expedia to lower commissions. See note 38 below. 35. According to Smith Travel Research, in 2015 in shares of branded properties were: North America, 67%; Europe, 41%; Asia/Pac, 51%; Middle East/Africa, 44%; and South America, 41%.

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36. Hotel loyalty programs were launched in 1983 by Holiday Inn and Marriott and were originally conduits to airline programs wherein currency earned in hotels could be used for free flights on participating airlines. The programs, now often co-branded with credit cards, then evolved so that accrued rewards could be used for free room-nights and other benefits. Points in loyalty programs are accumulated when a guest checks into a hotel and the hotel’s owner pays a fee into a special fund that is structured to cover the expected costs of potential future point redemptions. When guests redeem their points for a free night or other benefits, the management company charges the fund to pay the hotel owner back for the room-night that is redeemed (but at a fraction of the published room rate). The challenge for the hotel is that it must have sufficient cash to cover all of the potential redemptions. As noted in Hudson (2010), the economic recession that began in late 2007 led to an increase of merchandise redemptions as compared to overnight stay redemptions. The hotel owner must then pay more to product suppliers for merchandise instead of being compensated for the cost of a room out of a reserve fund that hotels pay into. See also Audi (2007). 37. McGinty (2016) writes of a Microsoft Research study by Lewis and Zervas (2016) who found that “when ratings rose by one star, demand increased by 25% and prices grew by 9%. Independent and luxury hotels were more sensitive to the ratings.” Schoenberger (2017), however, writes that brand names are not as important as in the past. See also White (2019) on potential brand saturation. 38. For example, estimates by PriceWaterhouseCoopers suggest that at upscale hotels, a 1% rise in price (i.e., in real ADR) results in a 0.4% decline in room demand and a 0.6% decline in occupancy percentage points for each $1 increase in real ADR. The cross elasticity for the economy sector against midscale hotels without food and beverage indicates even greater sensitivity, with a 1% increase in economy prices raising midscale demand by 0.8% and with each $1 change in economy real ADRs raising midscale occupancy percentage points by 1.4%. See Hanson (2000). 39. In the “merchant model,” originated by Expedia, when a hotel is booked, the guest pays Expedia up front and Expedia buys the room on the guest’s behalf for a fee that might range up to 25% of what the traveler is paying. But instead of taking a large cut of the payment, Booking.com instead uses an “agency model,” in which the site lets hotels set their own smaller commissions of maybe 12%, and allows guests to pay when they arrive at the property rather than in advance. 40. See Jeffrey and Barden (2001), and O’Neill and Mattila (2006) on ARR, which is total hotel revenue divided by the number of rooms sold. 41. Mortgage bonds can be classified as being either open or closed. If they are closed, no more bonds may be issued against the mortgage. However, there may not be any limit as to the amount of bonds that may be secured, and if so, the issue is open. See also Eisen (2020). 42. Securitization converts identifiable and predictable cash flows into securities that may be easier to trade than are other forms of debt because different packages (tranches) of such securities can be designed to appeal to investors

234

43.

44.

45.

46.

4 Hotels

desiring different combinations of rights and risks. Also, the risk can be spread over a number of borrowers, and the costs of administration may be lower. A third type of REIT, known as a paired-share REIT, was limited to four companies that had been grandfathered into this particular structure when REITs were formed. For a long time, the paired-share structure allowed a REIT company and an operating company to function side by side, minimizing tax payments as compared to C corporations. Such tax advantages, for example, allowed Starwood Lodging to outbid Hilton in the 1998 takeover battle for ITT’s Sheraton chain. In response, Congress clamped down, and paired-share REITs are no longer factors in the market. Even Starwood changed over to a regular corporate structure in 1998. REITS are generally not subject to corporate federal income tax on that portion of REIT taxable income (i.e., at least 90%) that is distributed to shareholders. Under the U.S. Tax Code, the REIT cannot operate the hotels owned and acquired but must lease the properties and engage thirdparty independent contractors manage the hotels. And the REIT does not have the authority to require any hotel property to be operated in a particular way or to govern aspects of daily operations. REIT conversions such as those by Penn National and Pinnacle Entertainment have also been applied to the casino sector. See Hoffman and Rubin (2015). New equity REITs may also be formed with existing properties and/or real estate partnerships through an Umbrella Partnership Real Estate Investment Trust (UPREIT). This entity differs from a traditional REIT because a limited partnership structure is utilized, with the REIT functioning as general partner. The arrangement allows existing partnerships (or property holders) to contribute their property in exchange for a limited partnership interest in the new REIT operating partnership. After a period of time (usually one year), limited partners who contributed property can exchange some or all of their interest for cash or REIT shares. This will cause tax to be due on appreciation that occurred in the contributing partnership (although by selling their units over a period of time, the partnership unit holders may spread any tax over several years). Both holders of real estate partnership interest and REITs can benefit from the UPREIT. Real estate partnership unit holders transform their illiquid partnership interest into the more liquid REIT shareholder status. The REIT benefits by acquiring real property without having to generate capital to purchase the property. FFO, as adopted by the National Association of Real Estate Investment Trusts, provides a measure of cash from operations and is calculated by adding back real property depreciation expense to net income and adjusting for other extraordinary events. FFO should not, however, be relied upon as an ultimate measure of a REIT’s ability to pay dividends because it does not reflect recurring capital expenditures that are capitalized and not expensed. A reserve for these capital expenditures is therefore deducted from FFO. The result is cash available for distribution (CAD), a more accurate indicator of a REIT’s ability to pay dividends. FFO is defined as net income minus profit from real estate sales plus real estate depreciation. Adjusted FFO (AFFO) takes FFO and subtracts recurring capital

4.5 Concluding Remarks

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expenditures, amortization of tenant improvements, amortization of leasing commissions, and rent straight lining. But controversy abounds as to definitions used in practice, and great attention must be paid to the details. To boost FFO, REITs may be capitalizing some expenses rather than treating them as current expenses. REITs have been criticized for deeming certain costs nonrecurring, avoiding hits to their FFO. As Vanocur (1999) notes, “the figuring of FFO starts with net income as computed in accordance with GAAP. From that number gains or losses from debt restructuring and property sales are excluded. Real-estaterelated depreciation and amortization is added back, and the total is adjusted for unconsolidated partnerships and joint ventures.” Such differences in earnings measures are further discussed in Smith (2001a, b); the Wall Street Journal of March 20, 2002; and in Block (1998, p. 152), who indicates that FFO is also flawed because not all property retains its value every year and because not all REITS capitalize and expense similar items in similar ways. For this reason, the raw FFO data ought to be adjusted for recurring capital expenditures, amortization of tenant improvements, and other items to arrive at an adjusted FFO. The Wall Street Journal of August 11, 1999, writes that Archstone Communities Trust divided depreciable items into things such as carpets, roofs, and appliances that have a life of less than thirty years and those such as buildings and land improvements with a life of more than thirty years. Archstone treated depreciation of more perishable items as expenses instead of adding them back to cash flow, as most REITs have done. The REIT Modernization Act of 1999 allowed a REIT to own as much as 100% of the stock of a taxable REIT subsidiary that provides services (e.g., concierge, travel, and delivery) to REIT tenants and others. Previously, REITs could only own up to 10% of the voting stock of a taxable corporation, which made it difficult for hotel REITs to avoid potential conflicts of ownership and operating-control issues that arose when hotels had been required to lease properties to third parties. Under the new Act, financial results would be based on profits rather than hotel revenues. See Wall Street Journal, November 24, 1999; January 24, 2001; and February 21, 2001. 47. In assessing the risks of extending long-term loans, banks and other lenders will focus on loan-to-value (LTV) ratios and debt-service-coverage (DSCR) ratios that are comparable to the coverage and leverage ratios discussed for airlines in Chap. 2. According to PriceWaterhouseCoopers data, the LTV ratio for the industry averaged 61.3% between 1996 and 2001, while the average DSCR from 1995 to 2001 was 1.81:1 or 24% above the average of 1.46:1 for the years 1978–1989. The typical range for the LTV ratio is 60–75%. Lower breakeven occupancy levels, which declined from 65.2% in 1990 to 51.0% in 2001, also helped the industry avoid significant delinquencies during the economic downturn of 2001. 48. Pooling-of-interests accounting, a controversial concept in the mergers and consolidations of the 1990s, was no longer allowed after 2001. It had been approved only if certain strict criteria had been met. In a pooling, two companies

236

49.

50.

51.

52.

53.

54.

4 Hotels

combined their assets and liabilities as if they had always operated as a single entity. The advantage was that there is no charge to earnings for what in purchase merger accounting is known as goodwill amortization. Such goodwill represents the value of intangible assets such as brand names and reservation systems and operating know-how that a purchaser buys for a price that exceeds the target company’s stated book value. In a purchase-accounting type of merger this goodwill used to be charged, according to U.S. GAAP, as an expense and written off evenly over no more than forty years. After calendar 2000, goodwill is no longer amortized over any particular period and may remain on the books indefinitely, until it has been determined that the value of the acquired assets has been impaired. Prior to this change, amortization of goodwill had depressed stated earnings results, with such charges in large mergers often amounting to several hundred million dollars a year. See, also, Financial Accounting Standards Board (FASB) Statement No. 142 and the New York Times and Wall Street Journal, December 7, 2000. The industry has developed a forecasting tool known as the U.S. hotel industry leading indicator (HIL), which is a monthly composite of nine different components that, on the average, are able to estimate industry demand data by four to five months in advance of a change in direction in the business cycle. Among the HIL components are the Treasury bond yield curve, oil prices, job market conditions, hotel worker-hours, housing activity, foreign demand, new orders, and a vacation barometer. PwC economists have also estimated the elasticity of room demand with respect to real GDP between 1987 and 2000 by hotel segment: Upper upscale was 1.02; upscale 1.46; midscale with F&B, not significant; midscale w/o F&B, 1.24; economy, 1.03; Independent, 0.5 million admissions Source: International Association of Amusement Parks and Attractions, 2009 Season Survey. More recent data would be about the same

a

must develop its own set of standards. Some representative industry sample ratios (which are still about the same as in 2009) appear in Table 6.4.

6.3

Recreational Resorts

Amusement/theme parks are out-of-home facilities that specialize in location-based entertainment (LBE) activities, whereas recreation resorts are travel destinations that specialize in location-based recreation (LBR) activities that include golfing, skiing, camping, and tennis. Although the operational characteristics of such resorts greatly resemble those of amusement/theme parks, a fundamental difference is that amusement park guests have largely passive experiences—things are done for them or to them on a preformatted ride or attraction. In stark contrast, the essence of a visit to a golf or ski (or camping and tennis) resort is to engage in primarily active, unformatted, experiences produced and directed by the visitors themselves. However, LBE and LBR facilities both compete with as well as often complement each other while in pursuit of the same discretionary spending dollars and comparable demographically defined visitor sectors. Especially in skiing and golf, equipment sales and rental and instruction services provide significant revenues.13

6.4 Economic Sensitivities

299

Recreational resorts—essentially specialized theme parks—are subject to the same daily and seasonal risks and operating challenges that would be encountered in the operation of any other kind of theme park. The risks endemically include sensitivity to changes in airline routing and pricing, to changes in the overall economic environment, and to whims of the weather. In particular, such resorts are further characterized by their high operating leverage with respect to service prices and visitor volumes (and/or participation rates), their need for large upfront capital investments, and their relatively high rates of seasonal labor turnover. The key variables for ski resorts are the number of visitors and lift-ticket prices, whereas in golf, they are the number of rounds played and the price per round (i.e., playing or greens fees).14 The amount of risk capital required to develop attractive resort recreation facilities has indeed grown so large that consolidation of ownership has, of necessity, continued apace. The largest operators have geographically and seasonally diversified portfolios of resorts, relatively easy access to low-cost capital, broadly experienced management teams, and an ability to widely market services and build brands—all of which makes it difficult for a smaller operator to compete. As a result, the top 20% of ski resort operators already handle an estimated 80% of ski visits in the United States. The golf industry, though currently much less consolidated, has similar features. As the large operators further diversify, they also become increasingly involved in the lodging, restaurant, and time-share operations that are common to many travelrelated enterprises. For example, ski operators now derive a bit less than half of their revenues from sales of lift tickets, as they are now able to capture a larger percentage of visitors’ spending by providing more lodging, entertainment, and shopping experiences for their guests. And as golf course construction and real estate and lodging development projects are often intertwined, the potential alternative-use value of the underlying real estate is always an important long-run consideration: It is not difficult, for example, to imagine that the real estate of a golf course might be worth more if converted into condominium housing, a shopping mall, or an industrial office park.

6.4

Economic Sensitivities

A sense of how this industry’s operating performance compares with that of other economic segments is not readily derived. However, evidence from the North American Industry Classification System (NAICS) and U.S. Census of Selected Service Industries, which provides data on employment and payrolls (as shown in Table 4.4), suggests that parks in the aggregate have been able to gradually reduce the inherent labor intensity of operations (i.e., payroll as a percentage of receipts). There are also difficulties in correlating overall theme park admission trends with important economic time series such as those for GDP or real disposable income. Although an economic recession could be expected to affect admission growth

300 Fig. 6.3 Theme park attendance in the United States (in tens of millions), major parks including Disney’s, versus unemployment rate (%) and consumer credit as a percentage of personal income, 1980–2019

6 Amusement/Theme Parks and Resorts 24 20

Credit % of PI

16 Attendance

12 8 4 Unemployment rate (%)

0 90

Fig. 6.4 Worldwide attendance trends, top ten parks, attendance in N. America, Asia, Europe, and Latin America, 1991–2019. Source: Amusement Business and Themed Entertainment Association/Economics Research Associates data

150

95

00

05

10

15

millions

125

N.Amer

100 75 Euro

Asia

50

L.Amer

25 0 91

97

03

09

15

trends adversely at high-profile themed resort parks, other parks more dependent on day-trip and regional visitors ought to fare relatively better in such an environment. Rapidly rising fuel prices might also help the regionals at the expense of the destination resorts. Aggregate theme park admissions do, however, seem to be positively correlated with respect to population growth and consumer credit as a percentage of personal income and negatively correlated with respect to the unemployment rate. But the lags, as suggested by Fig. 6.3, are not well defined. Some further variables to consider would, of course, include changes in real admission-ticket and fuel prices, changes in airline fares and foreign-exchange rates, and demographic shifts over time. The demand for theme-park services is, in addition, likely to be more sensitive to the overall cost of travel relative to incomes than to anything else. The price of oil (see Sect. 1.7) has thus become a key variable given that it directly affects the ability of consumers to afford travel and that it also feeds immediately into the operating costs and pricing of theme park, hotel, car rental, and airline services. Worldwide park attendance trends are shown in Fig. 6.4.

6.6 Concluding Remarks

6.5

301

Valuing Theme-Park Properties

Real estate—the key asset of any park—normally has the potential to provide longterm returns on investment that, in the end, may surpass the average annual returns obtainable from day-to-day operations. However, for this to occur, the real estate usually needs to be developed for additional uses (housing, offices, studios, etc.) that are compatible with the park’s operations. It also helps, as a hedge against future inflation, if the park happens to lie in the path of ongoing population expansion (e.g., Disneyland, just south of Los Angeles) or if the park, through its own qualities, is able to congeal what would otherwise be haphazard population growth around itself (e.g., Disney World near Orlando).15 Given the long-term operating nature of all major parks, the usual established methods for valuing other entertainment properties may also be applied here. As in the airline and hotel (or broadcasting and cable) industries, for example, theme-park asset values are taken as a multiple of projected operating earnings before taxes interest, and depreciation and amortization (EBITDA) as sometimes adjusted for capital expenditures. Such multiples would normally be expected to vary inversely to interest rates. Other factors affecting the multiple applied to this definition of cash flow would include the following: Age and condition of the park’s rides and attractions Demographic and income trends in the surrounding region Potential for expanding ride and admissions capacity Potential for raising prices and/or per capita spending Prospects for development of nearby transportation facilities Proximity of other similar attractions Again, as in other segments, public market valuations are often considerably less than what private market valuations, based on a multiple of cash flow, might be. Well-situated theme parks with proven operating characteristics are thus often attractive candidates for leveraged buyouts in which large institutions will lend a major percentage of the required funding for the buyout based on the security of the park’s cash flow.16

6.6

Concluding Remarks

Admission growth trends for the major facilities have, over long periods, held consistently above the growth trends of real GDP. More recently, though, there have been signs of slowing (even prior to the pandemic in 2020). Parks are no longer a novelty and they compete for time and attention with many other entertainment alternatives. The amount of capital investment and technological sophistication required to maintain a leadership position has also grown enormously. New motion simulator

302

6 Amusement/Theme Parks and Resorts

rides and other computer-controlled “experiences” such as those developed in the framework of “virtual reality” and interactive video games are the new frontiers in the evolution of theme park concepts. The trend is toward provision of more immersive and personalized experiences. It is no wonder, then, that major media companies still view theme-park tie-ins as a natural fit. The major parks have, of course, themselves become important destinations for travelers. The industry is mature in North America, where it has developed into an entertainment form dominated by the few large firms having the marketing expertise and capital to continuously upgrade and expand their facilities. Now, faster growth is more likely to be seen in other parts of the world, with extensions of proven themed concepts into new markets such as China, Brazil, Singapore, and Korea.17 As a result, the major companies are becoming more like major hotel brand managers and franchisors, reaping licensing fees without incurring significant financial or developmental construction risks. Regardless of location, though, the degree of ultimate success will always have as much to do with intangible elements—quality of design, efficiency of service, and public fancy—as with anything else. Notes 1. The oldest amusement park is Bakken, just north of Copenhagen, which began attracting visitors in 1583, but, Silverman (2019) traces back to the twelfth century’s Bartholomew Fair. See Amusement Business, March 3, 1996. 2. The first true U.S. amusement park was Steeplechase Park at Coney Island, which was opened in 1897 by George Tilyou. Luna Park, in competition with Steeplechase and Dreamland, in 1904 attracted four million people—a remarkable number for that time (Nasaw 1993, p. 85). 3. See Thomas (1976, Chap. 20). Also, as Adams (1991, pp. 43–5) notes, the underlying concepts had also been proven in Tilyou’s Steeplechase Park. Leonard and Palmeri (2017) review recent developments at Disney and Universal. 4. The 160-acre site for Disneyland was selected by the Stanford Research Institute. 5. In attempts to emulate Disney’s concepts, the Marriott Corporation, Taft Broadcasting, Six Flags, and others began a construction boom that lasted throughout most of the 1970s. A total of at least $500 million was spent in the construction of parks such as Busch Gardens Old Country, Great Adventure, Kings Dominion, Great America, and Canada’s Wonderland. Among the largest U.S. corporate park operators after Disney in terms of total admissions are Comcast (Universal Studios); Sea World (also including Busch Gardens Tampa, Florida, and Williamsburg, Virginia, and Aquatica); Six Flags; Cedar Fair (Kings Island, Kings Dominion, Canada’s Wonderland); and Universal Studios (Orlando and Los Angeles). In 2011, Comcast bought Blackstone’s share of Universal Studios Florida for around $1.025 billion and in 2015, 51% of Universal Studios Japan for $1.5 billion. Blackstone bought the Anheuser parks in 2009 for $2.7 billion.

6.6 Concluding Remarks

6.

7.

8.

9.

10.

11. 12.

13.

303

Cedar Fair was acquired by Apollo Global Management in 2010. Blackstone sold part of its stake in SeaWorld in a 2013 IPO. That was followed by an initial investment of $1.1 billion to open the EPCOT Center in 1981, as well as $500 million for the Studio Tour, which opened in 1989. A subset of the themed amusement business involves regularly scheduled state fairs and regional expositions. These fairs are, in essence, movable, impermanent theme parks that have operating characteristics similar to those of permanent facilities. According to compilations by Amusement Business, the industry trade journal, in 1999 the top 50 fairs attracted a combined attendance of 45.5 million. However, because only about 60% of all admissions are paid, the industry generates less than $200 million at the gate. Several times this amount, however, is derived from activities conducted within the fairs. Water parks, another subset, have also become popular, with more than 30 million people visiting the top 20 global facilities. See also Lyon (1987). A study by the consulting firm Economics Research Associates indicates that, in the year 2000, 340 parks worldwide generated a combined attendance of 545 million and revenues of $13.5 billion, with North America accounting for 49% of all revenues. The data include North American parks with attendance greater than 500,000 and “significant” parks elsewhere. In the 1990s, the number of parks and revenues approximately doubled and attendance grew by 80%. See Amusement Business, January 10, 2000. Location-based entertainment is a term that has generally been used to describe ride-simulator theaters and advanced video-game arcades built in urban or suburban shopping centers. However, LBE would also describe theme parks, movie theaters, themed restaurants, sports stadiums, or casinos. A number of major European parks date to the early 1900s. As shown in Brown and Church (1987), Alton Towers in the United Kingdom was opened in 1924 and Kantoor (Duinrell) in the Netherlands in 1935. Both traditional carnival-type games and electronic video games also generate high marginal profits. The industry speaks of design days, which are used to estimate the times of occurrence and peak attendance capacity. Design days in the seasonal parks might normally average 1% to 2% of the annual expected attendance, and estimates would be based on the number of weekends, holidays, and special events that occur in a specific month. Hourly operating capacity is also of importance and is related to the number of “entertainment units” in which the average visitor participates per hour. In most parks, the average guest might participate in 1.5 to 2.5 entertainment units (i.e., rides, parades, and other attractions) per hour. See McClung (1991), Barnes (2010), Wanhill (2013), and Cornelis (2017). The number of visits to ski resorts has not recently grown much even while the industry has been powder-deep into consolidation. However, since the mid-1980s there has been a decided shift away from downhill skiing and toward cross-country skiing and snowboarding, which attracts younger and less wealthy

304

14.

15.

16.

17.

6 Amusement/Theme Parks and Resorts

participants. Although there is no reason to think that skiing and snowboarding will become less popular any time soon, it would seem that the major companies (including Doral International, Intrawest, and Vail) will likely find that much of their growth will come from acquisitions, provision of more lodging and entertainment activities, greater development of vacation home villages, and stronger brand marketing to families and to skiers based abroad. Excluding equipment, personal consumption expenditures on skiing totaled around $4 billion in 2015. Given that an estimated 15% of all golfers are residents of a golf course community, as much as one-third of all new course construction is tied into some type of lodging and/or residential project development. The number of golfing participants in the U.S. (about half of the world’s total) has not grown over the last decade, and the number of courses has actually diminished, as debtfueled expansion in the early 2000s could not be sustained and constraints on time and income availability for play increased. However, with approximately one-third of all U.S. golfers being over the age of forty, it seems likely that the number of participants in North America will again increase modestly. In all, personal consumption expenditures for playing fees and equipment likely amounted to $10 billion in 2014, but with an important slice of this spent on daily fees at private and municipally owned courses (which together amount to around 65% of all courses). The largest gains in participation rates will instead probably be seen in the more rapidly expanding Asian economies. Hotel operators Hilton and Marriott as well as REITs (e.g., National Golf Properties, Golf Trust of America, and Meditrust) own and/or operate golf courses. Because camping and tennis resorts are more geographically dispersed, require much less capital investment per facility than ski or golf resorts, are smaller, and are much less well-defined for purposes of this section, they are therefore not further discussed. Particularly in the case of smaller parks, it is conceivable, though not likely, that operation of the park will turn out to be merely an interim holding action in anticipation of the maturation of higher-value alternative uses. In such instances, the park would be worth more dead than alive. Maddaus (2019), however, writes that not all projects are successful, e.g., Fox’s Kuala Lumpur park. Important transactions include Taft Broadcasting, Marriott, and Bally Mfg. in the 1980s, Six Flags and Time Warner in the 1990s, and Blackstone Group Partners involving Universal Studios and Sea World acquisitions in the early 2000s. Cedar Fair was acquired by Apollo Global Management in 2010. See Kolesnikov-Jessop (2009).

References

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References Adams, J. A. (1991). The American Amusement Park Industry: A History of Technology and Thrills. Boston: Twayne Publishers (G. K. Hall & Co.). Barnes, B. (2010). “Disney Technology Tackles a Theme-Park Headache: Lines,” New York Times, December 28. Brown, J., and Church, A. (1987). “Theme Parks in Europe,” Travel & Tourism Analyst, London: The Economist, February. Cornelis, P. C. M. (2017). Yield Model For Theme Park Investments: How to Improve Your Return on Attractions. The Netherlands: CLC Media. Kolesnikov-Jessop, S. (2009). “Theme Parks See Potential in Asia,” New York Times, December 19. Kyriazi, G. (1976). The Great American Amusement Parks: A Pictorial History. Secaucus, NJ: Citadel Press. Leonard, D., and Palmeri, C. (2017). “Disney’s Galactic Gambit,” Bloomberg BusinessWeek, April 24. Lyon, R. (1987). “Theme Parks in the USA,” Travel & Tourism Analyst, London: The Economist Publications, January. Maddaus, G. (2019). “How a Kuala Lumpur Theme Park Became a Fox-Themed Fiasco.” Variety, January 23. Mangels, W. F. (1952). The Outdoor Amusement Industry: From Earliest Times to the Present. New York: Vantage Press. McClung, G. (1991). “Theme Park Selection: Factors Influencing Attendance,” Tourism Management,12(2)(June). Nasaw, D. (1993). Going Out: The Rise and Fall of Public Amusements. New York: HarperCollins (Basic Books). Silverman, S. M. (2019). The Amusement Park. New York: Black Dog & Leventhal. Thomas, B. (1976). Walt Disney: An American Original. New York: Simon & Schuster (Pocket Books, 1980). Wanhill, S. (2013). “The Business of Amusement Parks: Their Development and Operation,” in C. A. Tisdell, ed. (2013), Handbook of Tourism Economics: Analysis, New Applications and Case Studies.

Further Reading Bannon, L. (1996). “Universal Studios’ Plan to Expand in Florida Moves Disney to Battle,” Wall Street Journal, October 2. Barnes, B. (2016). “Disney introduces demand-based pricing at theme parks,” New York Times, February 28. ——— (2015a). “Disney Bulking Up Theme Parks as Universal Rises,” New York Times, August 17. ——— (2015b). “Comcast Invests by the Billion in Theme Parks, Hogwarts and All,” New York Times, August 2. ——— (2014). “A Billion-Dollar Bracelet Is the Key to a Disney Park,” New York Times, April 2. ——— (2013a). “Theme Parks Let in the V.I.P.’s,” New York Times, June 9. ——— (2013b). “The Digital Kingdom,” New York Times, January 7. ——— (2012). “Clash of the Theme Parks,” New York Times, May 21. ——— (2011). “From Britain, It’s Legoland,” New York Times, October 17. ——— (2008). “Will Disney Keep Us Amused?,” New York Times, February 10.

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Barnes, B., and Skipp, C. (2010). “Hoping Tourists Will Flock to Hogwarts (and Spend a Few Galleons),” New York Times, June 19. Bauerlein, V. (2015). “In Business of Ups and Downs, Coasters Are on a Roll,” Wall Street Journal, June 1. Belson, K. (2003). “A Japanese Theme Park Company Fails,” New York Times, February 27. Berck, J. (1994) “When Broadway Meets the Midway, It’s Big Business,” New York Times, August 28. Bianchi, S. (2008). “Dubai’s Next Big Plans: Theme-Park Destination,” Wall Street Journal, June 25. Binkley, C. (2001). “In Pursuit of Hassle-Free Slopes,” Wall Street Journal, March 16. Brooke, J. (2005). “Japan’s Ski Industry Stumbles on Age and Economy,” New York Times, March 24. Burkitt, L. (2014). “In China, Developer Has New Theme: Parks,” Wall Street Journal, December 8. Clavé, S. A. (2007). The Global Theme Park Industry. Wallingford, UK: CABI. Dean, J. (2017). “King of the Hill: No One Dominates the Ski Business Like Vail Resorts,” Men’s Journal, April. Eisner, M. D. (1998). Work in Progress. New York: Random House. Eliot, M. (1993). Walt Disney, Hollywood’s Dark Prince: A Biography. New York: Carol Publishing (Birch Lane). Faison, S. (1999). “Even If You Build Them. . .,” New York Times, August 3. Finch, C. (1975). The Art of Walt Disney: From Mickey Mouse to the Magic Kingdoms. New York: Harry N. Abrams. Flower, J. (1991). Prince of the Magic Kingdom: Michael Eisner and the Re-Making of Disney. New York: John Wiley & Sons. Fowler, G. A., and Marr, M. (2005). “Disney’s China Play,” Wall Street Journal, June 16. Fritz, B. (2016). “Potter Conjures Parks’ Comeback,” Wall Street Journal, April 13. ——— (2015). “Disney Parks Consider Off-Peak Prices,” Wall Street Journal, October 5. Gottdiener, M. (2001). The Theming of America: Dreams, Media Fantasies, and Themed Environments, 2nd ed. Boulder, Co: Westview. Grover, R. (1997). The Disney Touch, rev. ed. Chicago: Irwin. Gubernick, L. (1999). “How Safe Is That Theme Park?” Wall Street Journal, July 23. Gumbel, P., and Turner, R. (1994). “Fans Like Euro Disney but Its Parent’s Goofs Weigh the Park Down,” Wall Street Journal, March 10. Hannon, K. (1987). “All Aboard!” Forbes, 140(3)(August 10). Harwell, D. (2015). “How Theme Parks Like Disney World Left the Middle Class Behind,” Washington Post, June 12. Jackson, C., and Gamerman, E. (2006). “Rethinking the Thrill Factor,” Wall Street Journal, April 15. Laing, J. R. (2003). “Golf Glut,” Barron’s, July 28. Lainsbury, A. (2000). Once upon an American Dream: The Story of Euro Disneyland. Lawrence: University Press of Kansas. Leonard, D., and Palmeri, C. (2017). “Disney’s Galactic Gambit,” Bloomberg BusinessWeek, April 24. Ma, W., and Fritz, B. (2017). “China’s Theme Park Bid Has Few Attractions,” Wall Street Journal, July 21. Marr, M., and Cutler, K.-M. (2005) “Fine Line on Wild Rides,” Wall Street Journal, July 1. McCracken, J. (2008). “No Fun For Six Flags As Parks Face Slump,” Wall Street Journal, August 5, McDowell, E. (1998). “The New Monster of the Midway,” New York Times, June 21. Michaels, D. (2018). “European Know-How Revs Up Pricey Roller Coasters,” Wall Street Journal, March 6. ——— (2016). “Amusement Parks Hurtle Into Digital Realm,” Wall Street Journal, August 31.

References

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Mosley, L. (1987). Disney’s World: A Biography. Briarcliff Manor, NY: Stein and Day. Moss, T. (2020). “China Theme Park Sector Booms,” Wall Street Journal, August 31. Mrowca, M. (1983). “Amusement Park in Ohio Has Its Ups and Downs but Continues to Draw Crowds after 114 Years,” Wall Street Journal, July 8. Negroni, C. (2018). “Smaller Theme Parks” Pitch: Stay Longer Than a Day,” New York Times, November 7. Newport, J. P. (2007). “How Golf Went Off Course,” Wall Street Journal, April 2. Ono, Y. (1990). “Theme Parks Boom in Japan as Investors and Consumers Rush to Get on the Ride,” Wall Street Journal, August 8. Parasie, N. (2016). “Persian Gulf Tries to Tap Into Theme Parks,” Wall Street Journal, August 23. Schickel, R. (1968). The Disney Version: The Life, Times, Art and Commerce of Walt Disney. New York: Simon & Schuster. Schwartzel, E. (2019). “Disney Taps Power of Force At Theme Parks,” Wall Street Journal, May 31. Schweizer, P., and Schweizer, R. (1998). Disney: The Mouse Betrayed. Washington, DC: Regnery Publishing, Inc. Silverman, S. M. (2019). The Amusement Park: 900 Years of Thrills and Spills, and the Dreamers and Schemers Who Built Them. New York: Hachette/ Black Dog & Leventhal. Snow, R. (2019). Disney’s Land: Walt Disney and the Invention of the Amusement Park That Changed the World. New York: Simon & Schuster/Scribner. Spindle, B. (2001). “Cowboys and Samurai: The Japanizing of Universal,” Wall Street Journal, March 22. Stevenson, A., and Li, C. (2018). “Theme Parks and Ski Slopes: All Part of China’s Global Plan,” New York Times, August 1. Tagliabue, J. (2007). “Thrill Rides for Investors,” New York Times, July 4. ——— (2000). “Giving Theme Parks a Whirl: Europeans Warm to an American Experience,” New York Times, September 2. ——— (1995). “Step Right Up, Monsieur!: Growing Disneyfication of Europe’s Theme Parks,” New York Times, August 23. Tanikawa, M. (2001). “Japanese Theme Parks Facing Rough Times,” New York Times, March 2. Wrighton, J., and Orwall, B. (2005). “Despite Losses and Bailouts, France Stays Devoted to Disney,” Wall Street Journal, January 26. Yoshino, K. (2008). “Amusement Parks Playing to International Audiences,” Los Angeles Times, April 3.

Chapter 7

Tourism

A good holiday is one spent among people whose notions of time are vaguer than yours. —J. B. Priestly

Tourism involves people taking trips to a place or places outside their home communities for any purpose except daily commuting to and from work.1 Essentially, tourists are adventurers. And the travel industry would certainly be much smaller if people were not interested in touring—spending leisure time relaxing, sightseeing, and participating in their favorite resort and vacation activities. Although the economics of tourism is a topic closely related to the material presented earlier, it tackles somewhat different issues and analyzes supply and demand for travel from a perspective that differs from those of the previous chapters. For one, as is in live performing arts, consumption takes place at the point of supply and this requires travel to that point (destination). Here, the interest is also often expressed in terms of potential for regional economic development or environmental impact or need for government to implement transportation policies. But underlying all of these issues is the notion that tourism is the ultimate “experience” industry—a form of entertainment, if you will—that is embodied in the economic, cultural, environmental, and aesthetic features of destinations.2 That’s because, “it is in the destination that tourism demand reveals itself.”3 The destination is where the supply of transportation, accommodations, and various other related goods and services converges. This chapter provides an overview of the economics of tourism—a global business that, if all related activities are included, accounted for around 10% (in 2019) of international trade, total employment, and world GDP (as estimated by the World Travel and Tourism Council). A sense of the economic importance of travel and tourism is conveyed in Table 7.1. In small and relatively undiversified economies such as in Aruba, Bahamas, Maldives, and Seychelles, the direct contribution of travel and tourism can range from 30% to 60% or more of total GDP as compared to 15% or less in larger countries. The contribution of travel and tourism as a percent of GDP in such smaller countries is indeed so dominant that the numerous travel © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 H. L. Vogel, Travel Industry Economics, https://doi.org/10.1007/978-3-030-63351-6_7

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Table 7.1 Travel and tourism employment, relative contribution to employment and to GDP, top ten countries, 2019 Employment in millions 29.09

China India United States Philippines

27.40 5.91 5.81

Indonesia

4.75

Mexico Germany

4.67 3.13

Vietnam

2.57

Thailand United Kingdom

2.48 1.73

Antigua/ Barbuda Aruba St. Lucia US Virgin Islands British Virgin Islands Macau Maldives St. Kitts and Nevis Bahamas Anguilla

% of total employment 91.7 94.3 78.1

Macau

% of total GDP 91.3

Aruba Brit Virgin Isl. Maldives

73.6 57.0

55.5

59.1

US Virgin Isl. Bahamas Antigua/ Barbuda St. Lucia

52.2 51.3

Grenada Seychelles

40.5 40.5

68.8 66.4 65.5 59.5

56.5

43.3 42.7 40.7

Source: World Tourism & Travel Council, WTTC, https://wttc.org/Research/Economic-Impact, Global_Economic_Impact_&_Trends_2020.pdf, Statista

restrictions necessitated by the virus pandemic of 2020 led to relatively greater distress than in larger and more diversified economies.

7.1

Don’t Leave Home Without It

Money, that is. Promotion of tourism has always been based on the idea that a region or city could grow economically—provide jobs and business opportunities for its citizens—if tourists spend time and money. For this, a region or city needs something that attracts visitors from other areas. The attraction could be historic old ruins such as the Parthenon in Greece, mystical mountain top scenery such as Macchu Piccu in Peru, the beaches of the Mediterranean coast, the skyscraper canyons of Manhattan, or the gaming tables of Las Vegas and Monte Carlo. Any old steel mill will not do. Prior to the eighteenth century, travel for purposes of pleasure was rare. But the ancient Greeks apparently did travel to the Olympics. And the ancient world did have some of the earliest and most impressive sightseeing and tourist attractions, including the Great Pyramids in Egypt, the Hanging Gardens of Babylon, and sites of religious significance in Jerusalem. Still, in the times of the Roman Empire or of medieval Europe, most trips to nearby fairs and festivals would not last for more than a day and most of the demand for travel was derived from various trade, educational,

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and religious needs. At the time, travel was largely limited to nomads, warriors, pilgrims, and the elite.4 The collapse of the Roman Empire in the fourth and fifth centuries led to a steep decline in travel of all kinds and, for most people, travel for pleasure became inconceivable. In this dark period, only the most adventurous would set out on bad roads and risk being assaulted by bandits. It was not until the seventeenth and eighteenth centuries that the pace of travel revived, with diplomats, scholars, and the wealthy among the fortunate few able to make what was then coming to be known as the “Grand Tour” of European centers of learning, religion, and trade. Features of tourism (including spas fashioned on those of earlier Roman times) began to rapidly evolve as the Industrial Revolution spread across the continent. This was accompanied by the emergence of travel agents (the retailers) and tour operators (the wholesalers). These innovative entrepreneurial features marked the start of the modern era, which dates only from 1841, when an enterprising Thomas Cook began to book trips on the new English railroads of that day. For the upper classes, many of these excursions were tied to visits to health spas and seaside bathing resorts. Of course, such trips also ultimately came to be affordable by the public at large. Travel in early America, however, developed somewhat differently than in Europe if only because of the long distances involved. The interior of the continent was first penetrated on foot or horseback or in small boats. Later, covered wagons crossed the Great Plains and stagecoaches delivered mail in the Old West. Yet traffic could not expand significantly until the transcontinental railroads of the mid-1800s were built. Only then was it possible to extend large-scale, commercial tourist attractions and to make sites of interest available to many more visitors. Since then—with the proliferating modes of transportation available to the public and the costs of travel relative to incomes declining—tourism has become an important global industry directly generating in 2019 more than US$1 trillion of spending (including passenger transport) and operating through five main sectors (Vanhove 2011, p. 11): • Attractions such as natural landscapes, theme and wildlife parks, and heritage sites. • Accommodations including hotels, timeshare condominiums, guest houses, and campsites; • Transportation which includes airlines, railways, bus and shipping operations; • Travel organizers such as travel agents and tour and casino junket operators; • Destination organizers including national and local tourist offices and tourism associations. In all, global tourist receipts and arrivals, as estimated by the United Nation’s World Tourism Organization UNWTO and shown in Fig. 7.1a, have grown at compound annual rates of around 7.5% and 4.2% respectively, between 1980 and 2019. Figure 7.1b, meanwhile, illustrates tourism spending as a percent of gross world output.

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Fig. 7.1 (a) International tourist receipts and arrivals, 1960–2019. (b) World tourist receipts as a percentage of output, 1970–2019. Source: UNWTO and Brown et al. (1999)

(a) 1,600

millions & $ billions

1,200 800

Arriv als

400 Receipts ($)

0 60

(b) 2.0

70

80

90

00

10

20

Per Cap. GDP in $000s

%

World GDP p.c.

1.5

12 9

1.0

6

0.5

3

Tourist receipts % GDP, left

-

0 80

90

00

10

20

Table 7.2 World’s top 12 international tourist destinations (arrivals in millions excluding sameday visitors) and receipts, US$ in billions, 2019 By arrivals

Francea Spain USA China Italy Turkey Mexico Thailand Germany UKa Japan Austria

Intl tourist arrivals Millions 89.4 83.7 79.3 65.7 64.5 51.2 45.0 39.8 39.6 36.3 32.2 31.9

% total arrivals

By receipts Int tourism receipts

6.2 5.8 5.5 4.5 4.4 3.5 3.1 2.7 2.7 2.5 2.2 2.2

USA Spain France Thailand UK Italy Japan Australia Germany China (ex-Macao)b India Turkey

% global receipts $ billions 214.1 14.5 79.7 5.4 65.4 4.4 60.5 4.1 49.9 3.4 49.8 3.4 46.1 3.1 46.0 3.1 41.6 2.8 35.8 2.4 30.0 2.0 29.8 2.0

Source: World Tourism Barometer, Statistical Abstract,18(20) (May 2020), UNWTO, World Bank Preliminary estimate b Macao receipts, $39.5 billion a

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Table 7.3 Trends of international tourism receipts in US$ billions, receipts per arrival US$ and Euro, and arrivals in millions by region, selected regions, 2019 Region

Arrivals in millions

(Arrivals share of World total in %) Africa (5.0) Americas (15.1) North America (10.0) Caribbean(1.8) South America (2.4) Asia/Pacific (24.7) North-East Asia (11.7) South-East Asia (9.4) Oceana (17.9) Europe (50.9) Northern Europe (5.5) Western Europe (14.0) Central Europe (10.7) S. Mediterranean (20.8) Middle East (4.4) World (100.0)

US$ billions 39.1 342.6 265.5 35.9 28.5 443.8 187.5 147.7 61.9 574.2 91.1 179.6 68.9 234.5 80.0 1480

US$ per arrival 530 1560 1810 1330 800 1230 1100 1080 3550 770 1140 880 440 770 1250 1010

Euro per arrival 470 1390 1620 1190 720 1100 980 960 3170 690 1020 790 390 690 1110 900

73.2 220.2 146.4 27.1 35.6 360.6 170.6 137.3 17.5 744.3 79.9 204.3 156.2 304.0 64.2 1462

CAGR (%)a 2014– 2019 5.9 3.9 3.9 4.1 4.1 6.4 4.6 7.1 5.8 5.1 2.4 3.2 5.4 7.2 4.1 5.2

a

Compound Annual Growth Rate Source: Tourism Highlights, 2020, UNWTO, https://webunwto.s3.eu-west-1.amazonaws.com/s3fspublic/2020-05/UNWTO_Barom20_02_May_Statistical_Annex_en_.pdf

Table 7.4 Percentage share of international tourist arrivals by region, 1960–2019 1960 1970 1980 1990 2000 2010 2019

Africa 1.1 1.5 2.6 3.3 4.0 5.2 5.0

Americas 24.1 25.5 21.6 20.4 18.6 15.9 15.1

Asia Pacific 1.4 3.8 8.2 12.7 16.8 21.7 24.7

Europe 72.6 68.2 65.6 61.6 57.1 50.7 50.9

Middle East 0.9 1.1 2.1 2.2 3.5 6.4 4.4

Source: UNWTO Tourism Highlights, 2015, Sharpley and Telfer (2015, p. 11), and updated at: https://webunwto.s3.eu-west-1.amazonaws.com/s3fs-public/2020-05/UNWTO_Barom20_02_ May_Statistical_Annex_en_.pdf

UNWTO data on the world’s top twelve tourist destinations in 2019 are shown in Table 7.2 and tourism receipts and arrivals by region in Tables 7.3 and 7.4. It is estimated that more than 1.4 billion people—twice as many as in the early 1990s— traveled outside of their country’s borders in 2019. And with annual global travel

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spending in 2019 at around $1.55 trillion and arrivals at 1.46 billion, the average trip thus has a cost of around $1000. Tourist types The three most basic distinctions are domestic (within country of resident), outbound, and inbound tourism. But this is rather trivial given that tourists can much more valuably be classified by their budgets as well as by their purposes for travel and by their psychological propensities. Budget, purpose, and psychology provide three different ways in which developers and marketers can begin to understand a tourist attraction’s business potential from the tourist’s point of view. Of these, characterizations by budget are the most economically straightforward, leading naturally to marketing aimed at distinct segments defined by income and age. As has already been illustrated in Chap. 2, the estimated changes in demand for each target segment would be reflected in estimated price and income elasticity coefficients. Although budgets are most fundamental in determination of travel mode and trip distance, purpose cuts across all budget lines and might include everything from working out or relaxing at health spas, to visiting friends and relatives, to going to football games or attending business conventions. In fact, according to World Tourism Organization data, on a global basis, 40% to 45% of tourists are vacationers, 40% are traveling on business, 8% are visiting friends and relatives, and 5% are on government assignments.5 It should be normally expected that business and convention-related tourism segments (sometimes referred to as MICE—Meetings, Incentives, Conventions, and Exhibitions) are less sensitive to rising prices than would tourism related to vacations and visiting friends and relatives. And in contrast to vacationers, business tourists would more likely be constrained by the limits of time. A time elasticity of demand coefficient might thus also be estimated for each tourist segment, with ordinary price and income elasticities estimated for choice of accommodations and mode of travel.6 Sociologists, anthropologists, and economists have further classified tourists along the lines of their psychological propensities. Preferences of tourists, especially of the international variety, may be seen, according to McIntosh et al. (1999, p. 235) as ranging between four extremes: • • • •

Complete relaxation to constant activity Traveling close to one’s home environment to a totally strange environment Complete dependence on group travel to traveling alone Order to disorder (i.e., from formal and totally designated to informal and autonomous)

And tourist types might be similarly characterized as Adventurers, Worriers, Dreamers, Economizers, and Indulgers as listed in Burns (1999), or as Explorer, Elite, Off-Beat, Unusual, Incipient Mass, Mass, and Charter Mass as presented by Smith (1989). Closely related to these are the five clearly identifiable aspects of a tourist excursion that, as described by Candela and Figini (2012, pp. 21–2), are:

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• An anticipation phase in which trip decisions and plans are developed, • An outward journey phase which entails travel to selected destinations, • An experience phase in which activities of various kinds (e.g., sightseeing, hiking, attending shows and concerts and museum exhibits) are conducted, • A return journey phase in which travel is from the destination back to place of origin, • A memory phase in which the entire tourism experience is recalled and reviewed and often shared with friends and relatives. From a psychological standpoint, the experience of tourism further blends a degree of novelty with a degree of familiarity and the security of old habits with the excitement of change. In the taxonomy of Cohen (1972), tourists fall into four basic types: (a) organized mass tourists who have virtually every aspect of a trip planned in advance; (b) individual mass tourists, whose trips include a certain amount of individually determined activity away from the group; (c) explorers, who arrange most or all of a trip’s details themselves, yet still look for comfortable accommodations and transportation; and (d) drifters, who become almost fully immersed in the foreign culture and care little about physical comforts. Plog (1974) further provides a related classification of tourists as: • Those who are adventuresome and want to be among the first to try new products and services and are allocentrics (i.e., focused on varied activities), • Those who prefer the familiar in travel destinations and are psychocentrics, • The majority of people (i.e., midcentrics) who are in the middle of a normal distribution between extreme allocentric and psychocentric personalities.7 Yet as shown by Leiper (1990), tourism may also be defined as a system that includes the tourist, the space in which the tourist travels, and the travel and tourism industry components that provide a variety of services (e.g., accommodations, transport, and entertainment). This line of thinking can then be further extended to include political and administrative aspects and the affects of tourism on host communities (McIntosh et al. 1999). Aspects of tourism may also be analyzed with reference to the type of movement involved, the purpose of a visit (i.e., leisure, business, or personal), and the average length of stay (L ). These classifications distinguish tourism from other forms of travel and are the conventional dimensions used by the UNWTO. The tourism product may thus be defined as the bundle of goods and services (transportation, lodging, food, attractions, and shopping) that are typically demanded by tourists.8 The peculiar characteristic of this bundle is that it is consumed where it is produced and it is time-perishable: Yesterday’s airline seat or hotel room availability can never again be stored for future usage or sold. Ecotourism The field of ecotourism began to evolve in the late 1970s, when it became apparent that significant social and environment costs are often incurred in the development and growth of tourism. Although it is difficult to define with precision, the terminology suggests tourism that has a relatively small affect on local and regional resources and cultures and that is also sustainable over the long

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run. Ecotourism is often marketed to environmentally and socially conscious travelers who seek adventurous, back-to-nature elements in their “green travel” experiences and it is also increasingly of interest to mainstream travelers.9 More specifically, Honey (1999, pp. 22–23) notes that ecotourism necessarily: • • • • • • •

involves travel to natural destinations, minimizes impact, builds environmental awareness, provides direct financial benefits for conservation, provides financial benefits and empowerment for local people, respects local culture, supports human rights and democratic movements.

Tourism development provides many countries and regions with substantial income and economic growth opportunities, but the substantial costs incurred may often more than offset the potential benefits to be derived. Mass tourism, for all the spending that it attracts, tends to destroy native cultures and heritages, despoil the environments, displace and make things unaffordable and uncomfortable for the original residents, and ultimately desecrates and diminishes the very things that first attracted the visitors. “[T]he key to good tourism is to do your planning for the people who live there. . .and if that is done well, then the visitor will be happy.”10 To thus succeed over the long run, it is important for tourism planners to protect a site’s unique aspects—i.e., those inherent features that cannot be outsourced (to factories or similar-looking shopping malls and buildings located elsewhere) and that form the essence of a site’s brand and image. In all, the field of ecotourism provides a focused view of the costs and benefits of tourism development and growth and provides another way to classify and to understand the motivations of tourists.11 Attraction types Attractions may also be categorized by essential characteristics— mountains, seashore, theme parks, casinos, museums, shopping—and by ownership and sponsorship factors. Some attractions are nature-made and pretty much available for free, on the order of public goods. Others may be crassly commercialized places or events and be owned and controlled by private companies. And still other situations, perhaps the majority, would involve a mix of private and public support in the form of tax incentives or subsidies. Disney World in Florida and the Bellagio Hotel in Las Vegas would be examples of attractions supported primarily by private interests, whereas Buckingham Palace in London and the Louvre in Paris would be examples of attractions supported primarily by public interests. This review of the various attraction types follows from the more general notion that all tourism demand is tied to what a destination has to offer in terms of historical and cultural artifacts, natural and man-made resources, and many other intangible and emotionally-related elements. To illustrate, overcrowding and congestion and the resulting air pollution might dissuade some tourists even while others are attracted (via a “bandwagon effect”) precisely because a destination is so popular.

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317

Destinations might also have snob appeal that (via a “Veblen effect”) draws tourists savoring the exclusivity of visiting places that are relatively expensive. Attractions that evoke emotional responses that can energize visitor demand would further include film tourism, which showcases scenes and sites featured in popular movies and television programs. Examples include New Zealand, where visitations were boosted by the Lord of the Rings productions having been filmed there and Croatia (Dubrovnik) and Northern Ireland, which had been sites for HBO’s Game of Thrones series.12 Nevertheless, like other experience-related goods and services, destinations will normally fall into or out of favor in what has been described as a Tourism Area Life Cycle model (TALC) containing six distinct stages: exploration, involvement, development, consolidation, stagnation, and decline (occasionally followed by rejuvenation).13 Virtual tourism Development of powerful computer software and hardware and cloud-based Internet services has further led to a new segment known as virtual tourism—which includes virtual tourist agencies and allows people to take virtual vacations—all without the necessity of leaving home or traveling far from home. Such tourism has many advantages in that the cost to the virtual traveler of enjoying the immersive experience is much less than it would be on an actual trip. Although this type of tourism might not ever be able to fully replicate all of the smells, sights and sounds, and native people-meeting of an actual trip, it is nonetheless still greatly informative and has the additional advantage of reducing the wear and tear on many ancient historical locations, some of which already require extensive renovation and maintenance expenditures just to avoid being trampled to dust by hordes of visitors. The virtual experiences are greatly enhanced by carefully constructed high-resolution, three-dimensional images that could not have been presented with earlier technologies.14 Inclusive tours Air-tour (charter) operators emerged principally in Europe in the early 1950s, when scheduled airlines had spare capacity and older planes could be readily refurbished for civilian use. Many of the operators grew large enough to start their own charter (nonscheduled) airlines. Other smaller operators still function essentially as wholesalers that buy (sometimes from scheduled-airlines) blocs of vacant seats at discount and then incorporate destination accommodations and other services as part of inclusive tour (IT) or so-called group inclusive tour (GIT) packages. Such tour operators, who are usually affiliated with travel agencies, will generally also block-book hotel rooms at a discount, with the prices depending on season, hotel occupancy, and other such factors. A package might further include car rental, cruise ship, and sports or cultural event elements which would be otherwise booked separately by what are known as free (or foreign or fully) independent (FIT)-segment travelers.15 The IT packager bears the risk of paying for accommodations that may not be used or may be used at prices that are too low to fully cover costs. Because of price competition, the probable need to guarantee payment to airlines, and the uncertainty

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of demand, tour operators may thus in the long run actually end up earning more from interest received on deposits and prepaid holidays and from selling additional services than from direct packaging of tour components. The primary advantage to the tourist on an IT trip is low-cost fare relative to that usually found on scheduled flights. However, passengers sacrifice convenience, with departure and arrival times at off-peak hours, and they endure crowded conditions with few service amenities and meals.

7.2

Economic Aspects

For travelers, the key distinction in the economics of tourism as contrasted with that of travel is that the travel experience in itself becomes an integral part of the tourism experience—an experience that is singular and that cannot be consumed vicariously or at a different time and place. As in touring by cruise ship or sightseeing by motor coach or bicycle, the travel aspect is not only a means to an end but also an end in itself. From an economist’s standpoint, tourism has several overriding features that are valid in all situations. For one, tourism is an invisible export industry because, like the banking and insurance services industries, no tangible products are transported from one place to another. But it is also a highly unstable export because it is subject to strong seasonal variations as well as to pronounced and unpredictable influences from external forces—which may include everything from political unrest, unusual weather patterns, earthquakes, tsunamis, pandemics, and volcanic eruptions. The tourist product cannot be stored.16 The existence of giant globe-spanning airline and hotel companies notwithstanding, the tourism industry is also still highly fragmented and is closely integrated with other sectors of the economy for the simple reason that tourists require many destination support services. This involves everything from provision of fresh water supplies and sewage disposal systems to shops, restaurants, hotels, and banking and transportation infrastructures. Coordination of such regional tourism supply conditions is especially difficult because, as a service activity, tourism requires resources that may be separately or jointly purchased but that are consumed in sequence.17 In addition, tourism has distinct price and income elasticity features. As the World Tourist Organization (1994, p. 9) suggests, “if price changes and other factors are disregarded, a comparison solely between international tourist expenditures and world GDP (gross domestic product) can be used as a crude measure of the income elasticity of demand for international travel.” The trace in Fig. 7.2 “shows that both tourism expenditures and air travel expenditures have increased at twice the rate of world GDP, thus giving a crude income elasticity coefficient of 2.0.” Tourism price and income elasticity does, however, vary over time and by country and region.18

7.2 Economic Aspects Fig. 7.2 World GDP, international airline revenues, and international tourist receipt indexes (1980¼100), 1980–2020. Source: UNWTO and Brown et al. (1999)

319 1,400

Index

Tourist receipts

1,050

Airline rev

700 350 World GDP

80

90

00

10

20

Price discrimination is another familiar economic feature that is often applied in the pricing of tourism-related goods and services. As has already been discussed, price discrimination tactics can be seen in airlines (e.g., first-class versus coach); hotels (e.g., sea view or parking lot view); and in the types of quantity discounts that might be available for different goods and services purchased in different seasons of the year or even at different times of the day. Tourism, moreover, has a cultural dimension that relates to local and regional economic features. “[T]ourism can be seen not so much as a cultural industry in its own right but rather as a user of the products of other industries within the cultural sector—the performing arts, museums and galleries, heritage sites and so on.”19 The cultural capital of a tourist location, including both tangible and intangible aspects, is thus captured by the aesthetic, spiritual, social, historical, symbolic, and authenticity values that have been accumulated over time. This stock of capital may then give rise to a flow of services that may be consumed or be used to produce further goods and services. The public goods characteristics of tourism (Chap. 1) are evident when cultural attractions are preserved and sustained so that they can be enjoyed by current and future-generation visitors and local inhabitants without incurring a significant marginal cost per visitor.20 Economic externalities that affect the tourism product may be either positive or negative. If more tourism results in straining the local electrical grid or adding to environmental pollution, the externalities would obviously be negative. Conversely, if tourism leads to development of more and better local cultural or educational facilities, the externality would be positive. Tourism is always the portal through which countries present their cultural heritage (OECD 2009) and it is thus often overseen and promoted by a mixture of government and private interests.21 Tourists to heritage sites are, for instance, often motivated by a sense of nostalgia, historical curiosity, and wonder about how the past relates to the present. Sustainable tourism meets the needs of current generations without compromising a destination’s attractiveness and ability to serve future generations.

320 Fig. 7.3 Tourism development leads to demand for related goods and services, 1995–2019

7 Tourism US$ billions 200 Exports

150

Imports

100 50 Balance of trade

0 95

00

05

10

15

But for tourism to be viable a country must continuously address five major potential constraints on growth that relate to: • • • • •

Transportation infrastructure Accommodations Utilities and information infrastructure Marketing and promotional activities Education and training of tourism workers22

A country that fails to directly address these issues cannot be efficient and competitive in tourism over the long run. Trade balances for the United States are illustrated in Fig. 7.3. In all, the flow of economic activity to other industry segments that emanates from the growth of tourism is traced in Fig. 7.4. Additional details about the extent to which each segment affects the others can then be obtained by analysis of inputoutput tables as described later in this chapter and as illustrated in Table 7.8. In sum, tourism is usually presumed (e.g., in Sharpley and Harrison 2019) to be a catalyst that: • contributes to a region or country’s growth and to a reduction of poverty; • develops new entrepreneurial and other opportunities, resources, and infrastructure; • distributes wealth more evenly and produces additional social benefits. None of these features are necessarily evident or active in all places and at all times, but are instead often used to support and justify investments in tourism development projects.

7.2 Economic Aspects

321

Fig. 7.4 Tourism development leads to demand for related goods and services

7.2.1

Demand Models

Tourism always involves the demand for a bundle of goods and services as measured either using the values or the quantities that are consumed. And many different models have been developed to generate forecasts, with most of them implicitly or explicitly employing utility maximization concepts (see Chap. 1) and taking into account the demand dependencies of a large number of commodities. Among the most popular demand estimation models have at times been the linear expenditure system (LES), the Rotterdam model, and the almost ideal demand system (AIDS).23 In addition, the gravity model shown in Chap. 2 can be used to predict tourism flows between regions and countries. And universal scaling laws also suggest that the number of people traveling to any tourism site will inversely scale according to both the distance traveled and the frequency of visitation.24 All of such models will generate widely varying estimates that depend greatly on the types and quality of data, the underlying theoretical assumptions, and the econometric methods being used. Theoretical assumptions might involve equalsubstitutability and expected utility concepts. Predictive estimates will also be further skewed (and therefore be misleading) when risk factors including currency devaluations, potential political upheavals, labor strife, and the presence of rapid price inflation are omitted. For modelers, the challenges also extend to decisions as to whether demand is better measured using the number of arrivals or spending totals, whether the cost of travel to the destination is included or excluded, what modes of travel (air, rail, car, ship) and transport spending levels (luxury or economy-class) are involved, which

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relative prices provide the basis for estimation, and whether it is assumed that increased trade works to raise tourism or that tourism raises trade. The need for so many tourism demand estimation variables and interpretations adds significantly to the complexity (and unreliability) of modeling in this area. The only things for sure are that tourism demand will always be influenced by: • • • • • • • •

Income Prices and inflation rates Exchange rates Transport costs Travel time Marketing Security risks Local culture

7.2.2

Multipliers

At first glance, most people would assume that development of tourism could have only positive effects on a local economy. Justification for the development of tourist attractions is often indeed based on the notion that spending by tourists will increase job opportunities, stimulate new construction, and create a larger base of revenues for governments to tax. An increase in tourism may, however, also lead to more pollution of air and water, more traffic congestion and crime, and perhaps even a crowding-out of potentially more lucrative businesses. Thus, in the broadest sense, an increase (or decrease) of tourism will inevitably disturb the existing ecological balance of a region.25 The extent to which this happens depends on the degree to which an initial change is amplified through its secondary, repercussionary effects, much in the same way that an earthquake will produce aftershocks or that a sound made in a small chamber will produce an echo. Effects are also amplified by clustering, which is generally an aggregation of tourist activity that geographically concentrates interconnected companies and institutions.26 Economists attempt to measure what the total impact of an initial change of spending for tourism will be on a region’s economic output of goods and services by estimating a multiplier of the initial change. This initial change ripples through the economy via effects that are direct, indirect, and induced.27 Direct effects are seen in the first round of spending, wherein the change in the local economy’s output will be equal to the change in tourist spending. Indirect effects are then seen when, say, the lodging or airline establishment experiences a rise in demand and then needs to increase purchases of food and beverage and laundry services; companies providing those services then hire more staff and purchase more electricity and a wide variety of other items. All of this activity then raises regional income levels, a portion of which will then be re-spent on local goods and services.

7.2 Economic Aspects

323

Multipliers can be designed and refined to distinguish the probable impact of spending by different types of tourists. They may also be constructed to show the effects of increased tourism on income, employment (i.e., full time-equivalent jobs created), government revenues, and foreign exchange. However, such sterile multipliers would not ordinarily take into account the many “quality of life” aspects that are probably important to local residents and that are also central to the new and increasingly influential field of ecotourism studies. Nor would they indicate the amount of time required for all the various rounds of impact to take effect. Theoretical models in macroeconomics are also often adopted for estimation of tourist spending multipliers because a region’s economy may be treated as merely a scaled-down version of a nation’s economy. To make these models work, however, the key ingredient is an estimate of the local marginal propensity to spend, which is the percentage of every additional dollar of income received that will ultimately be spent on consumption of goods and services. Fortunately, this is a factor that can be approximated from surveys and/or from econometric analysis of local demographic, income, and retail sales data. The central notion is that: Tourism’ s Economic Contribution ¼ Number of Tourists  Average Spending per Visitor  Multiplier: This suggests that a part of every unit of income received will be spent (i.e., recirculated). The multiplier, k, can be then expressed as: k ¼ 1=ð1  MPC Þ, where MPC is the marginal propensity to consume. Yet, as Bull (1995, p. 150) notes, there are always leakages, and the simple model should be modified to take account of the marginal propensity to save, taxation of income, and expenditures on imports. A more sophisticated formulation would thus be as follows: multiplier ¼ 1=leakages ¼ 1=½ðMTR þ MPSÞ þ ðð1MTRMPSÞ  MPMÞ, where MTR is the community’s marginal tax rate, MPS is the marginal propensity to save as a proportion of gross income, and MPM is the community’s marginal propensity to import as a proportion of consumption expenditure. For example, assume that a community’s marginal tax rate and marginal propensity to save are both 20% and the marginal propensity to import is 10%. The community’s income multiplier would then be

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multiplier ¼ 1=½ð0:2 þ 0:2Þ þ ðð1  0:2  0:2Þ  0:1Þ ¼ 1=0:46 ¼ 2:17: Again, this assumption too may not always hold true because some of the tourism expenditure may leak into transport payments to foreign carriers, payments for food and beverage imports required to service tourists, and a variety of other financial obligations to foreigners. To therefore make the model even more realistic economists might use what is known as an orthodox (i.e., Keynesian) multiplier model that takes into account most of these import requirements. It modifies the ratio via multiplication by an import factor, MPMT, which is the marginal propensity to import goods and services related to tourist needs. In this form, the multiplier can now be expressed as k ¼ ð1  MPMT Þ  ð1=leakagesÞ: Generally, the higher is the propensity to consume, the larger the multiplier becomes and the higher the propensity to import, the smaller the multiplier. Multipliers will, moreover, vary greatly by region and sector. But regardless of form, region, or sector, multipliers always provide estimates of the marginal (additional) benefits that would be derived from an increase of tourism spending. Still, the usefulness of multiplier estimates may be limited because they do not relate total tourism expenditure to total income or job creation potential. Nor do they explicitly include the costs (e.g., environmental and cultural) that would be incurred and that should be included in a more robust and realistic cost-benefit (CBA) analysis. For purposes of financial analysis, such relatively simple multiplier models often do not directly take account of the incremental capital costs that would be incurred in production of an extra unit of output or income.28 Multipliers will, moreover, normally change or fluctuate over time and are not forever constant: Political and economic upheavals, terrorism activities, and climate-change effects will alter them.29 And tourism marketing will thus be always required to build and sustain a destination’s brand and resonance with travelers.30 Estimated tourist income multipliers in a few selected countries are shown in Table 7.5. The numbers would likely be significantly different today than when originally compiled (and different tomorrow from today).

Table 7.5 Estimated tourist income multipliers for selected countries

Destination Turkey U.K. Egypt Bermuda Bahamas Iceland Source: Fletcher (1989)

Personal income multiplier 1.96 1.73 1.23 1.09 0.79 0.64

7.2 Economic Aspects

7.2.3

325

Balance of Trade

David Ricardo’s classic economic theory of comparative advantage appears to be as applicable in tourism as it is elsewhere in the analysis of international trade. The theory suggests that if one country is more efficient than another in producing goods, gains from trade can be obtained from specialization in the production and export of goods and services in which the country holds a relative comparative advantage. All other things being equal, a comparative advantage in tourism is present in countries that have ample labor and land and plentiful natural resources that include mountains, beaches, wildlife, and important cultural touchstones. Many countries, seeking to favorably affect their balance of trade, are accordingly interested in tourism development. However, trade balances are influenced by many diverse factors and forecasts of such balances are always fraught with uncertainty. The underlying theory follows what is known as the Heckscher-Ohlin theorem, which suggests that a country’s factors of production—including labor, capital, and land/natural resources, rather than relative efficiencies of production—determine its comparative advantage. To begin, it is necessary to estimate the receipts from foreign visitors minus payments made abroad by the country’s own outbound tourists. In addition, the presence of foreign tourists may require that fairly sizable ancillary international payments for foreign goods and services (i.e., imports) be made.31 The degree of a country’s success in generating a positive balance of tourist trade may also depend greatly on foreign currency exchange rates and macroeconomic and political conditions. As for foreign exchange effects on tourism, it is to be expected that, all other things being equal, countries or regions with relatively strong currencies will experience a decline in tourism demand and that countries with weak currencies should normally expect an increase. Also, balances of tourism trade estimates probably do not fully capture externalities (uncompensated interdependencies)—the potential positive or negative intangible social effects. If tourism provides work-training opportunities for previously unskilled people, it clearly creates a positive externality. However, if tourism just adds to pollution, crime, and traffic, the externality would evidently be negative for the local residents. A comprehensive cost–benefit analysis (CBA) of the impact of tourism development would require that such externalities be included.32 The approximate tourism contribution to the balance of payments of several important tourist destination countries is indicated in Table 7.6. By comparing tourism receipts to the sum of what are known as visible receipts (goods) and invisible receipts (services), it can be seen that some countries (and regions) are much more dependent on tourism earnings than are others. Tourism receipts as a percent of GDP also vary greatly (Table 7.1). However, those countries with the highest tourism percentages of total exports and GDP typically find it difficult, even over the long term, to diversify into the provision of export products and services unrelated to tourism.

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Table 7.6 Tourism receipts, exports, employment, top ten countries (2018 and 2019), estimated tourism percent of total exports and GDP (current $US)

United States Spain China France Italy United Kingdom. Germany Thailand Australia Turkey World total

Tourism receipts $ billions 256.2 81.3 40.4 73.1 51.6 48.5 60.3 65.2 47.3 37.1 1649.3

Tourism % of total exports 10.2

GDP 2019 $ trillions 21.43

OECDa Tourism employ % of total employb 4.3

16.3 1.5 8.1 7.9 5.5

1.39 14.34 2.72 2.10 2.83

13.5 6.4 7.5 8.3 4.7

5.8 0.3 2.7 2.6 1.7

3.85 0.54 1.39 0.75

4.8 7.6c 5.2 7.2 6.9

1.6 15.9c 3.1 4.9 4.4

3.2 19.9 14.5 15.6 OECD average

OECDa Tourism receipts % of GDP 1.2

a

Organization for Economic Cooperation and Development 2016 data c World Bank data, 2018 and rough approximation d 2017 estimate Source: IMF International Financial Yearbook and UNWTO Yearbook of Tourism Statistics, CIA World Factbook, World Bank @ https://tcdata360.worldbank.org/indicators/ST.INT.RCPT.XP. ZS?country¼BRA&indicator¼1846&viz¼bar_chart&years¼2018#comparison-link, OECD @ https://stats.oecd.org/BrandedView.aspx?oecd_bv_id¼2b45a380-en&doi¼e5d0c450-en; https:// www.oecd-ilibrary.org/docserver/6b47b985-en.pdf?expires¼1599192579&id¼id& accname¼guest&checksum¼9B1C2B189FE79E0D1CBD60EC2695FC24 b

An index of travel and tourism competitiveness by country—derived from considerations of safety and security, governmental policies, infrastructure, and natural and cultural resources—is compiled by the World Economic forum and appears in Table 7.7. U.S. spending on foreign travel as a percent of personal consumption expenditures appears in Fig. 1.21.33 Although the economies of many small countries depend greatly on travel and tourism, even for the United States travel and tourism is estimated to be the secondlargest export industry (in 2019 behind only transportation equipment). For the U.S., travel trade receipts (exports) in 2019 were $256.2 billion and the travel trade balance (surplus) was around $66.0 billion as compiled by the U.S. Bureau of Economic Analysis.34

7.2 Economic Aspects Table 7.7 Travel and tourism competitiveness Index, top 12 countries, 2019

327 Rank 1 2 3 4 5 6 7 8 9 10 11 12

Country Spain France Germany Japan United States United Kingdom Australia Italy Canada Switzerland Austria Portugal

Score 5.4 5.4 5.4 5.4 5.3 5.2 5.1 5.1 5.1 5.0 5.0 4.9

Source: World Economic Forum, http://www3.weforum.org/docs/ WEF_TTCR_2019.pdf, and Blanke and Chiesa (2013)

7.2.4

Input-Output Analysis

Tourism’s contribution to a nation’s economy can also be estimated through analysis of input-output (I/O) tables (grids) that reflect sectoral interdependence and show what individual industries buy from and sell to each other.35 For analysis of tourism’s economic components, this demand-side approach allows for sharper distinctions between goods and services directed specifically at tourists rather than at local residents. The problem, in most instances, is that the Standard Industrial Classification (SIC) system does not facilitate the separate identification of tourism-related activities. For example, activities such as dining in restaurants would usually include visitors and nonvisitors (i.e., people who are close to their homes). “[A] measure of tourism activities would be understated if it included only the output of industries that are typically associated with tourism activities” and “would be grossly overstated if it included all the expenditures on eating and drinking.”36 To get around these problems, small sample surveys have been used to develop tourism satellite accounts that provide a consistent and systematic way to link tourism demand expenditures to the industries that produce tourism goods and services. The end result is a matrix that would be a much larger version of Table 7.8, which uses money values but could also be calculated in terms of other factors such as employment or land use, for examples. Subsets of I-O tables that rearrange information from the use and consumption tables and that separate demand into tourism and non-tourism and business and government categories are also often presented.37 Summing down the columns of a typical I/O table provides estimates of total industry inputs and values added, while summing across the rows provides estimates of final demand and total output. Here, however, the rows and columns have been transposed, with industries (the producing sector) shown across the rows and

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Table 7.8 Production account of tourism industries, an excerpt, 1992

Commodity Hotels and lodging places Eating and drinking places Passenger rail Taxicabs Domestic passenger air fares International air fares

Industry Hotels and lodging places ($ millions) 55,913

Eating and drinking places ($ millions)

16,613

220,685

Railroads and related services ($ millions)

Taxicabs ($ millions)

Air Transportation ($ millions)

1226 6614 48,449 22,605

Source: Okubo and Planting (1998, p. 14)

commodities (the consuming sector) down the columns. As indicated in Table 7.8, hotels and lodging places in 1992 produced $16.6 billion of eating and drinking services as compared to the much larger production of eating and drinking ($220.7 billion) by places that specialize in eating and drinking. Tables of this kind make it possible to estimate the impact that each dollar of increase in tourism expenditure has on other industries, and vice versa. Such estimates, however, implicitly assume that relationships among the various input factors are relatively stable and that the marginal input coefficients (using the inputs required per unit of output for each sector) in the matrix are mostly constant. In the real world, input factor relationships are dynamic and capacity limits are frequently reached. When that happens, substantial increases in construction (e.g., new hotels, roads, and airplanes) and in demand for additional services would cause marginal input coefficients to change rapidly.

7.3

Travel Laws and Regulation

Each industry sector and region and locality of course operates under specific laws and regulations that may differ from those in other places and times. It’s a jungle out there. However, for tourism and other sectors to efficiently work together there must be and there are several common legal features.38 In the U.S., these would among many others include airline, cruise ship and car rental laws and regulations relating to: • passengers’ “bill of rights”39 • discounting and membership programs and security deposit bonding

7.4 Concluding Remarks

329

• lost or damaged baggage, price and fee disclosure policies in advertising, refunds and cancellations • immigration, minimum wage, and work hour policies • Licensing policies • zoning, construction and environment, and amount of cash or other items subject to duties, tariffs, and perhaps confiscation. • Contamination and contagion as experienced in past food poisoning, flu, and virus outbreaks (e.g., the coronavirus of 2020) that might require passenger quarantine, cancellation of services and routes, and deep cleaning of facilities such as ship cabins, hotel rooms, and airline/airport lounges and check-in areas. Laws and regulations relating to lodging facilities, resorts, cruise ships, restaurants, casinos, and theme parks would to some extent overlap and/or be complementary to those involving modes of travel. Casinos, in particular, are subject to strict licensing of employees, oversight of games, and cash and credit collections. Hotel operators are expected to protect their guests and employees from harm. Restaurants have a responsibility to serve and maintain clean facilities and food and those serving alcoholic beverages are usually required to have liquor licenses. And real estate zoning and ride safety issues figure prominently in the planning and operations of theme parks.40 Laws of a statutory nature are promulgated by legislators and are often sponsored and agreed to by presidents, governors, mayors, or prime ministers. But there are also laws and ordinances that have evolved from habits, customs, and previous legal practices, decision, and precedents. And others are the result of lengthy and contentious international negotiations. The outcome of these are often codified in a jumble of rules such as those involving airline route “freedom” rights (Chap. 2, note 8), or in the 1982 United Nations Convention for the Law of the Seas (UNCLOS), which became effective in 1994 and governs the navigation and access rights that affect cruise line operations. Additional regulations concern the “flag” of the nationality in which the ship is registered (now usually Panama, Bahamas, Liberia). This pertains to staffing, construction codes and fees, and marine pollution regulations codified for examples by the U.S. Clan Water Act (1997) and the Oil Pollution Act (1990).41 All of these are important when deciding where to locate, develop, and encourage travel and tourism-related businesses.

7.4

Concluding Remarks

The definition of tourism is rather flexible and tourism statistics are dependent on how the data are collected and who is doing the collecting. A Webster’s dictionary definition limits tourism to the practice of traveling for recreation, whereas some government agencies practically define tourist and traveler as being one and the same. Most people would, for example, likely combine business travel to, say, a convention at a resort with a few rounds of golf and tennis, or hiking, swimming, or

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bicycling. This then blurs the definitional boundaries and makes them less analytically useful. Indeed, all tourism involves travel, but not all travel involves tourism. No matter what the definition, though, expenditures for tourism provide important support for travel-related businesses and tax-funded administrative budgets. Income and employment multipliers, profits and prestige, and balance-of-trade considerations are always at the core of decisions to initiate and encourage investments in tourism-facility projects, which may range from giant government-financed airports and convention centers to relatively small privately financed hotel-casinos and beach resorts. A key underlying rationale for all such projects is that “tourism cannot be outsourced.”42 Even so, the costs and benefits of such projects ought to be carefully considered as it is not always clear that development of sleek airports, roads, and hotels necessarily provide the local population with a net positive outcome. The result might instead be massive pollution of all types, local residents no longer being able to afford to reside in their native communities, hordes of visitors trampling heritage sites into ruinous dust, ancient cultures and traditions being displaced and forever lost, and spoilage of the tourism experience.43 In brief, sustainable tourism requires full recognition of effects on the economy, on societies and cultures, and on the environment. Implicit in all investment calculations is the assumption that macroeconomic conditions will remain favorable and that tourist attractions in one region can compete effectively with those in others for share of the global tourism market. Yet some regions will always be blessed with an inherent comparative advantage: When it comes to mountain scenery any Swiss village will have a comparative advantage to the flats of the American Midwest. Up to a point, spending on advertising and promotion and sharp pricing strategies can help in this regard. However, tourist preferences are always shifting and the competition for their spending is ever keen and intense. Notes 1. Smith (1995, p. 20) suggests that there is still no universally accepted operational definition of the words tourist or tourism even though both words have been a part of the language since the early 1800s. Also, the World Tourism Organization has grappled with guidelines and definitions. For statistical purposes, we can consider a tourist as a visitor whose visit is for at least one night and whose main purpose of the visit may be classified as (a) leisure and holidays, (b) business and professional, and (c) other tourism purposes. See also National Tourism Policy Study (1978). 2. See Carter and Gilovich (2010). 3. Quoted from Candela and Figini (2012, p. 12). 4. Lundberg (1985, p. 7). Pike (2016, p. 2) and Sigaux (1966) note that even in the Middle Ages, printed travel guides were available in France. 5. In Europe and North America more than 80% of tourism is domestic, whereas in the Pacific or Asia regions the domestic component tends to be much lower. 6. Taplin (1997) estimates ordinary elasticities of demand for vacation travel and accommodation in Australia. The estimated income elasticity for vacation air

7.4 Concluding Remarks

331

trips overseas is 2.1, for overseas hotel use is 2.2, and for domestic hotel use 1.0. Price elasticities of demand for vacation air trips overseas were –1.7, for overseas hotel use –1.28, and for domestic hotel use 0.54. Event planning and management related to business trips is a separate area of expertise as covered in van der Wagen and White (2010). 7. Other classification systems, for example, one developed by SRI International, include additional features such as values and lifestyles (VALS) and are designed to identify different types of consumers and their concerns. The Plog (1974) model, especially in relation to its product life cycle aspects, is analyzed also in Ho and McKercher (2014) found in N. Kozak and M. Kozak, eds. Third Interdisciplinary Tourism Research Conference, Proceedings Book. 8. Some frequently encountered ratios in tourism studies include: Average length of stay: L ¼ the total number of nights ðN Þ divided by the number of arrivals ðAÞ; Saturation index, SI ¼ A divided by P, the resident population of the destination region; Per capita spending, SPC ¼ Tourism expenditure, TE divided by A; Net propensity to travel, Xn ¼ the number of tourist in the region, T, divided by the total regional population, P. 9. Melinda Laverty, senior program officer at the American Museum of Natural History, in an October 2005 Columbia University Business School Social Enterprise Conference said “Ecotourism is responsible travel to natural areas that preserves the environment and improves the wellbeing of local people.” The Wall Street Journal of January 28, 2006, says “the term itself means different things to different people. About 75 certification programs now award seals of approval to ecoresorts, though many just put the resorts on the honor system.” Certification groups include Green Globe 21 (greenglobe21.com) and Blue Flag (blueflag.org). There is also the Ecotourism Society (ecotourism.org) and a Global Sustainable Tourism Council. 10. Quotation is from Becker (2013, p. 64–7). 11. Beyond this, Kusler (1991) and Lindberg (1991) have also attempted to categorize ecotourists by type. Kusler’s groupings, as described in (Fennell 1999, p. 56) include do-it-yourselfers, ecotourists, and school or scientific groups. The first category enjoys great flexibility, the second is highly organized, and the third sometimes involves relatively harsh site conditions. Lindberg, however, uses four basic tourist-type categories: hard-core nature, dedicated nature, mainstream nature, and casual nature. See also the Ecotourism Society’s Website at www.ecotourism.org and McLaren (1998), whose insights are valuable but whose conclusion against a capitalist and consumer-oriented economy is plainly misguided. 12. Sub-segments would further include educational-related (in Duhs 2013), medical, architectural, shopping, culinary, sports, space (eventually to the moon and

332

13. 14. 15.

16. 17.

18.

19. 20.

7 Tourism

beyond), religion, business incentive, creative, and sex tourism (e.g., in Thailand), which is reviewed in Singh (2014, pp. 134–44). See Beeton (2005) on films, Weed and Bull (2009) on sports, and Fourie et al. (2015) on religion. Creative tourism provides visitors the opportunity to participate in courses and learning experiences so as to enhance their creative potential. See Sharpley and Harrison (2019) and Duxbury and Richards (2019). See, for example, Butler (1980) and Haywood (1986). The virtues of virtual reality as related to tourism are covered in Blascovich and Bailenson (2011, pp 221–26). Tour operators, as explained in Candela and Figini (2012, pp. 247–8), use several contract types: In allotment (or allocation) contracts, tour operators bargain with service providers such as hotels and have a negotiated right in the release back period to return unsold rooms before a deadline. In free sale contracts, there is an immediate purchase of services and commitment to pay. And in commission contracts, none of the parties are bound to terms of dates or availabilities, thereby reducing the tour operator’s risk. See Mathieson and Wall (1982, p. 38). In contrast, demand for tourism services is derived from many different needs and segments, but the commercial implications of addressing each need and segment are, from experience, fairly well understood and can be more readily coordinated. For inbound (export) tourism, Smeral (1994) calculated that income elasticity between 1975 and 1992 averaged around 2.1 for the U.S. and Japan, but was below 1.0 for the U.K. and Germany. Price elasticities over the same period were around -0.4 for the U.S., 0.7 for the U.K., 0.9 for France, and a high 1.7 for Japan. Estimates of income elasticities of outbound (import) tourism for 1978 to 2008 (in Smeral 2010) were highest for the U.S. at 3.4, for Japan, 3.3, and for fifteen countries in the European Union, 2.2. In general, elasticities of tourism imports with respect to changes in relative prices tend to cluster around 1.0. This is also reviewed in Vanhove (2011, Chap. 1). Quotation from Throsby (2001, p. 129). Towse (2019, Chap. 10) provides an in-depth review of cultural tourism. See Throsby (2001, pp. 46 and 84–5). Of course, there are always going to be positive and negative economic externalities that need to be balanced. On the positive side, employment and business opportunities are enhanced by the presence of such attractions, which may have a bequest value for future generations and which confer prestige value to the society in which these are located. But there may also be a downside that comes from excessive pollution, traffic, and crime. Throsby (2001) also introduces contingent valuation methods (CVMs) which attempt to elicit information concerning the minimal level of compensation required by an individual to forgo consumption of a public good or the maximum amount an individual would be willing to pay to obtain a nonmarket amenity. In this regard, see also Van Kooten and Bulte (2000,

7.4 Concluding Remarks

21.

22. 23.

24. 25.

26.

27.

333

p. 113). Nicolau (2010) finds that tourists interested in cultural attractions tend to be less sensitive to price. The most common forms and structures provide government planning, policy, and investment initiatives, vocational training, research and statistical data, and support for promotional and marketing campaigns. In the United States Congress in 1981 passed a National Tourism Policy Act that for the first time established a national tourism policy. In Canada, the Canadian Tourism Commission (CTC) was formed in 1995 to create a business/government partnership for the purpose of enhancing the growth of Canadian tourism. In Japan, four agencies including the Department of Tourism and the Japan National Tourist Organization share responsibility for developing growth in this area. Gee et al. (1997) review the National Tourism Administrations (NTAs). See also Park (2014). See Adamou and Clerides (2009) and Singh (2014, p. 127). Jackson (2011) surveys such models. Demand models fall generally into three categories: Linear Expenditures Systems (LES); Translog Demand (TL), i.e., Rotterdam; and Almost Ideal Demand systems (AIDS). In LES models every good is a substitute for every other good, there are no inferior goods, and no two goods are compliments. Clements and Selvanathan (1988) further explain the Rotterdam model. On tourism determinants see Jackson (2011, pp. 224–34). Divisekera (2013a, b) provides additional explanations of the different models and approaches and distinguishes between (uncompensated) Marshallian and (compensated) Hicksian price elasticities of demand (PEDs). Uncompensated PEDs are based on marginal utility functions under a budget constraint, whereas compensated PEDs are based on minimizing expenditures at a fixed utility level. See Song and Li (2008), Song et al. (2010), Goh and Law (2011), and Divisekera (2013b, p. 78). West (2017, pp. 347–50). For instance, the Dominican Republic, a popular vacation destination, in 2019 experienced a steep decline in visits when an unusually large number unexplained tourist deaths had occurred. See also Stabler et al. (2010, pp. 240–1) and Romero and Bogel-Burroughts (2019). Clustering concepts are covered by Porter (1998), Huybers and Bennett (2003), Jackson and Murphy (2006), and Casasnovas (2014), in N. Kozak and M. Kozak, eds. (2014), Third Interdisiplinary Tourism Research Conference Proceedings Book. Multiplier models may be classified into several major types. Cooper et al. (1998, pp. 132–40) suggest, for example, that such models are typically based on either Keynesian, input-output, base, or ad hoc theories. The Keynesian depends largely on estimated marginal propensities to spend; input-output rests more on general equilibrium approaches; base theories assume that relationships in spending, income, and pricing are relatively stable over time; and ad hoc include mixtures of Keynesian and base theory assumptions designed to

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study specific impacts. See Stynes at: msu.edu/course/prr/840/econimpact/pdf/ ecimpvol1.pdf), in which multipli have been categorized as: Type I sales multiplier ¼ (direct sales + indirect sales)/direct sales, Types II and III sales multiplier ¼ (direct sales + indirect sales + induced)/direct sales. Type II includes households, whereas Type III treats households as exogenous. Most models suffer from data deficiencies, static assumptions about relative factor pricing, and supply constraints, as sectors are unable to increase output. Tourism development is also often done at the expense of another industry’s growth potential, an aspect that is often overlooked in multiplier studies. The capture rate is a ratio of local final demand to tourist spending. See Archer (1982, 1984). 28. For many countries this incremental capital to output ratio (ICOR) will range between 2.5 and 4.0, although the ratio varies over time and at different stages of tourism industry development. See also Sinclair and Stabler (1997, p. 126) and Stabler et al. (2010, pp. 240–1). 29. On effects of terrorism, see Alderman (2016). 30. Various other multipliers of interest may also be directly approximated by taking a nation’s or region’s total travel and tourism marketing budget and then dividing by the total number of sector-related jobs. A typical annual state budget might, for instance, be $30 million and if there are 250,000 related jobs, it suggests an investment of $120 per person. Another variation would be to take, say, a state’s tourism tax revenue and divide by the total tourism and travel marketing budget. If a state thus takes sector taxes of $1.0 billion and spends $20 million for sector marketing, tourism tax revenue returns per marketing dollar invested would be $50. 31. Such imports, related to foreign-guest preferences, might be for food, entertainment, electronics devices, types of cars, etc. Import and export data are in the U.S. Census Bureau FT 900 reports available at: www.census.gov/foreigntrade/Press-Release/current_press_release/ft900.pdf. 32. Cost-benefit analyses that focus on externalities are the province of a separate field of tourism study, ecotourism (or green tourism), which goes beyond the economist’s prime concerns about money flows and outputs. Ecotourism attempts to understand tourism’s full impact on a region’s ecology, including quality of life issues. It is based on the notion, supported by Krippendorf (1987) that tourism development should be consistent with its environment and arise naturally from the activities that are natural to the area. See also Ryan (1991, p. 104) and Vanhove (2013). 33. In 2014, global tourism receipts of US$1133 billion (985 billion euros) compared to total world merchandise exports of around US$19,064 billion and to total world commercial services exports of US$4974 billion. See www.wto.org/ english/res_e/booksp_e/world_trade_report14_e.pdf, World Bank at http:// search.worldbank.org, and also IMF World Economic Outlook, Table A9, at: http://www.imf.org/external/pubs/ft/weo/2011/02/pdf/tables.pdf

References

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34. At BEA.gov, Exhibits 3 and 4 show export and import services by major categories, including travel for all purposes. See also the outbound overview section of the Office of Travel and Tourism Industries (OTTI). OTTI data available at: www. tinet.ita.doc.gov. Another source is the Travel Industry World Yearbook, published by Travel Industry Publishing Company Inc., PO Box 280, Spencertown, NY 12165. 35. As Wassily Leontief said at a 1973 press conference after the announcement of his Nobel Prize for development of I/O concepts, “When you make bread, you need eggs, flour, and milk. And if you want more bread, you must use more eggs. There are cooking recipes for all the industries in the economy.” (Harvard University Gazette, February 11, 1999). 36. Quotation from Okubo and Planting (1998, p. 9). 37. As described by Fletcher (1989) and also in a Fletcher article in Witt and Moutinho (1994), the I/O tables can be broken down into many sectors and categories, possibly including types of visitors, purposes of visit, and so forth. Smith (1995) has indicated, the tourism forecasting models that might be used in conjunction with multiplier estimates include hypothesized behavioral and attitudinal relationships (expectancy-value models) that have been developed by psychologists. According to Smith (1995), most such models are based on work by Fishbein (1967). 38. Information sources include www.TravelLaw.com. See also Morris et al. (2008) and Barth (2011). 39. For instance, see McCartney (2017). 40. On hospitality and food services laws see https://www.hg.org/hospitality-law. html 41. See Gibson and Parkman (2019, pp. 68–78). 42. Quote appears in Becker (2013, p. 66). 43. Becker (2013) extensively covers such issues. See also Lombardi (2017).

References Adamou, A., and Clerides, S. (2009). “Prospects and Limits of Tourism-Led Growth: The International Evidence” WP41–09. Rimini, Italy: Rimini Centre for Economic Analysis. Alderman, L. (2016). “Terrorism Scares Away the Tourists Europe Was Counting On,” New York Times, July 30. Archer, B. H. (1984). “Economic Impact: Misleading Multiplier,” Annals of Tourism Research 11 (3). Archer, B. H. (1982). “The Value of Multipliers and Their Policy Implications,” Tourism Management, (December). Barth, S. C. (2011). Hospitality Law: Managing legal Issues in the Hospitality Industry, 4th ed. Hoboken, NJ: Wiley. Becker, E. (2013). Overbooked: The Exploding Business of Travel. New York: Simon & Schuster. Beeton, S. (2005). Film-Induced Tourism. Clevendon, UK: Channel View Publications. Blanke, J., and Chiesa, T. (2013). The Travel & Tourism Competiveness Report, World Economic Forum 2013.

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Blascovich, J., and Bailenson, J. (2011). Infinite Reality: Avatars, Eternal Life, New Worlds, and the Dawn of the Virtual Revolution. New York: HarperCollins (William Morrow). Brown, L. R., Renner, M., and Halweil, B. (1999). Vital Signs, 1999. New York: Worldwatch Institute and W. W. Norton. Bull, A. O. (1995). The Economics of Travel and Tourism, 2nd ed. Melbourne: Longman Australia. Burns, P. M. (1999). An Introduction to Tourism and Anthropology. London: Routledge. Butler, R. W. (1980). “The Concept of a Tourism Area Life Cycle of Evolution,” Canadian Geographer, 24. Candela, G., and Figini, P. (2012). The Economics of Tourism Destinations. Berlin:SpringerVerlag. Carter, T. J., and Gilovich, T. (2010). “The Relative Relativity of Material and Experiential Purchases,” Journal of Personality and Social Psychology, 98(1). Casasnovas, A. A. (2014). “The Role of Clusters in Tourism: The Case of Majorca,” Clements, K. W., and Selvanathan, E. A. (1988). “The Rotterdam Demand Model and Its Applications in Marketing,” Marketing Science, 7(1)(Winter). Cohen, E. (1972). “Toward a Sociology of International Tourism,” Social Research, 39(1)(Spring). Cooper, C., Fletcher, J., Gilbert, D., Wanhill, S., and Shepherd, R., ed.(1998). Tourism: Principles and Practice, 2nd ed. Harlow, UK.: Prentice Hall/Financial Times Management. Divisekera, S. (2013a). “Tourism Demand Models: Concepts and Theories” in C. Tisdell, ed. (2013), Handbook of Tourism Economics: Analysis, New Applications and Case Studies. Hackensack, NJ: World Scientific Publishing. Divisekera, S. (2013b). “Empirical Estimation of Tourism Demand Models: A Review” in C. Tisdell, ed. (2013), Handbook of Tourism Economics: Analysis, New Applications and Case Studies. Hackensack, NJ: World Scientific Publishing. Duhs, L. A. (2013). “Education Tourism,” in C. A. Tisdell, ed. (2013), Handbook of Tourism Economics: Analysis, New Applications and Case Studies. Hackensack, NJ: World Scientific Publishing. Duxbury, N., and Richards, G. (2019). A Research Agenda for Creative Tourism. Cheltenham, UK: Elgar. Fennell, D. A. (1999, 2003). Ecotourism: An Introduction. London and New York: Routledge. Fishbein, M. (1967). “Attitude and the Prediction of Behavior,” in Readings in Attitude Theory and Measurement, Fishbein, M., ed. New York: John Wiley. Fletcher, J. (1989). “Input-Output Analysis and Tourism Impact Studies,” Annals of Tourism Research, 16(4); also in Khan, Olsen, and Var (1993). Fourie, J., Rosselló, J., and Santana-Gallego. M. (2015). “Religion, Religious Diversity and Tourism,” Kyklos, 68(1)(February). Gee, C. Y., Makens, J. C., and Choy, D. J. L. (1997). The Travel Industry, 3rd ed. New York: John Wiley & Sons. Gibson, P., and Parkman, R. (2019). Cruise Operations Management: Hospitality Perspectives, 3rd ed. New York: Routledge. Goh, C., and Law, R. (2011). “The Methodological Progress of Tourism Demand Forecasting: A Review of the Related Literature,” Journal of Travel & Tourism Marketing, 28(3). Haywood, K. M. (1986). “Can the Tourist Area Life Cycle Be Made Operational?,” Tourism Management, 7. Ho, G. K. S., and McKercher, B. (2014). “A Review of Life Cycle Model by Plog from a Marketing Perspective,” in M. Honey, M. (1999). Ecotourism and Sustainable Development: Who Owns Paradise? Washington, DC: Island Press. Huybers, T., and Bennett, J. (2003). “Inter-firm Cooperation at Nature-Based Tourism Destinations,” Journal of Socio-Economics 32. Jackson, J., and Murphy, P. (2006). “Clusters in Regional Tourism: An Australian Case,” Annals of Tourism Research, 33(4).

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Jackson, K. (2011). “Reconsidering the Silk Road: Tourism in the Context of Regionalism and Trade,” in S. Cameron, Handbook on the Economics of Leisure. Cheltenham, UK: Elgar. Krippendorf, J. (1987). (Ferienmenschen) The Holiday Makers: Understanding the Impact of Leisure and Travel. London: Heinemann. Kusler, J. A. (1991). “Ecotourism and Resource Conservation: Introduction to Issues,” in Ecotourism and Resource Conservation: A Collection of Papers, Kusler, J. A., ed., Volume 1. Madison, WI: Omnipress. Leiper, N. (1990). Tourism Systems, Occasional Papers 2. Auckland: Massey University. Lindberg, K. (1991). Policies for Maximizing Nature Tourism’s Ecological and Economic Benefits. Washington, DC: World Resources Institute. Lombardi, P. (2017). “Arrivederci, Tourists,” Wall Street Journal, June 27. Lundberg, D. E. (1985). The Tourist Business, 5th ed. New York: Van Nostrand Reinhold. Mathieson, A., and Wall, G. (1982). Tourism: Economic, Physical and Social Impacts. London and New York: Longman. McCartney, S. (2017), “That Airline Seat You Paid for Isn’t Yours,” Wall Street Journal, July 27. McIntosh, R. W., Goeldner, C. R., and Ritchie, J. R. B. (1999). Tourism: Principles, Practices, Philosophies, 8th ed. New York: John Wiley & Sons. McLaren, D. (1998). Rethinking Tourism and Ecotravel. West Hartford, CT: Kumarian Press. Morris, K., Cournoyer, N, and Marshall, A. (2008). Hotel, Restaurant, and Travel Law, 7th ed. Boston: Cengage Learning. National Tourism Policy Study (1978). Washington, DC: U.S. Government Printing Office. Nicolau, J. L. (2010). “Culture-sensitive Tourists Are More Price Insensitive,” Journal of Cultural Economics, 34. OECD (2009). “The Impact of Culture on Tourism,” Paris: Organization for Economic Cooperation and Development. Okubo, S., and Planting, M. A. (1998). “U.S. Travel and Tourism Satellite Accounts for 1992” Survey of Current Business. Washington, DC: U.S. Department of Commerce, Bureau of Economic Analysis, (July). Park, M. Y. (2014). Heritage Tourism. New York: Routledge. Pike, S. (2016).Destination Marketing Essentials, 2nd ed. New York: Routledge. Plog, S. C. (1974). “Why Destination Areas Rise and Fall in Popularity,” The Cornell Hotel and Restaurant Administrative Quarterly, 14(4)(February). Porter, M. E. (1998). “Clusters and the New Economics of Competition,” Harvard Business Review, 6. Romero, S., and Bogel-Burroughts, N. (2019). “Crisis Hits Dominican Republic Over Deaths of U. S. Tourists,” New York Times, June 24. Ryan, C. (1991). Recreational Tourism: A Social Science Perspective. London and New York: Routledge. Sharpley, R., and Harrison, D. eds. (2019). A Research Agenda for Tourism and Development. Cheltenham,. UK: Elgar. Sharpley, R., and Telfer, D. J., eds. (2015). Tourism and Development: Concepts and Issues, 2nd ed. Bristol, UK: Channel View Publications. Sigaux, G. (1966). History of Tourism. London: Leisure Arts. Sinclair, M. T., and Stabler, M. (1997). The Economics of Tourism. London: Routledge. Singh, P. J. (2014). Globalized Arts: The Entertainment Economy and Cultural Identity. New York: Columbia University Press. Smeral, E. (2010). “Impacts of the World Recession and Economic Recession and Economic Crises on Tourism: Forecasts and Potential Risks,” Journal of Travel Research, 1. Smeral, E. (1994). Tourismus 2005. Vienna: Ueberreuter. Smith, S. L. J. (1995). Tourism Analysis: A Handbook, 2nd ed. Essex, UK:Longman. Smith, V. I., ed. (1989). Hosts and Guests: The Anthropology of Tourism, 2nd ed. Philadelphia: University of Pennsylvania Press.

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Song, H. and Li, G. (2008). “Tourism Demand Modelling and Forecasting – a Review of Recent Research,” Tourism Management, 29(2)(April). Song, H., Li, G., Witt, S. F., and Fei, B. (2010). “Tourism Demand Modelling and Forecasting: How Should Demand Be Measured?,” Tourism Economics, 16(1)(March). Stabler, M. J., Papatheodorou, A., and Sinclair, M. T. (2010). The Economics of Tourism, 2nd ed. London: Routledge. Taplin, J. H. E. (1997). “Generalised Decomposition of Travel-Related Demand Elasticities into Choice and Generation Components,” Journal of Transport Economics and Policy, 31(2)(May). Throsby, D. (2001). Economics and Culture. New York and Cambridge, UK: Cambridge University Press. Towse, R. (2019). A Textbook of Cultural Economics, 2nd ed. Cambridge, UK: Cambridge University Press. Van der Wagen, and White L. (2010). Events Management: For Tourism, Cultural, Business, and Sporting Events, 4th ed. New South Wales, Australia: Pearson. Vanhove, N. (2013). “Tourism Projects and Cost-Benefit Analysis,” in C. A. Tisdell, ed. (2013). Handbook of Tourism Economics: Analysis, New Applications and Case Studies. Hackensack, NJ: World Scientific Publishing. Vanhove, N. (2011).The Economics of Tourism Destinations. second ed., London: Elsevier. Van Kooten, G. C., and Bulte, E. H. (2000). The Economics of Nature: Managing Biological Assets. Oxford, UK: Blackwell. Weed, M., and Bull, C. (2009). Sports Tourism: Participant, Policy and Providers, 2nd ed. Oxford, UK: Butterworth-Heinemann (Elsevier). West, G. (2017). Scale: The Universal Laws of Growth. New York: Penguin Press. Witt, S. F., and Moutinho, L. (1994). Tourism Marketing and Management Handbook, 2nd ed. Hertfordshire, UK: Prentice-Hall International. World Tourist Organization (1994). Aviation and Tourism Policies: Balancing the Benefits. London and New York: Routledge.

Further Reading Adam, N. (2017). “Tourist Boom Bogs Down Iceland,” Wall Street Journal, August 21. Alsos, G. A., Eide, D., and Madsen, E. L., eds. (2014). Handbook of Research on Innovation in Tourist Industries. Cheltenham, UK: Edward Elgar. Bannon, L. (1996). “Universal Studios’ Plan to Expand in Florida Moves Disney to Battle,” Wall Street Journal, October 2. Barbaro, M. (2011). “A Wizard Rivals Mickey,” New York Times, January 9. Blaine, T. W. (1993). “Input-Output Analysis: Applications to the Assessment of the Economic Impact of Tourism,” in Kahn, Olsen, and Var (1993). Botterill, D., and Platenkamp, V. (2012). Key Concepts in Tourism Research. London and Thousand Oaks, CA: SAGE Publications. Brebbia, C. A., and Pineda, F. D. eds. (2010). Sustainable Tourism IV. Southampton, UK: WIX Press. Candela, G., and Figini, P. (2012). The Economics of Tourism Destinations. Heidelberg and New York: Springer Verlag. Carvajal, D. (2015). “In Tourist Destinations, a Picture of Excess,” New York Times, July 12. Cater, E., and Lowman, G., eds. (1994). Ecotourism: A Sustainable Option? Chichester, UK: John Wiley & Sons. Chambers, E., ed. (1997). Tourism and Culture: An Applied Perspective. Albany, NY: State University of New York Press.

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Cook, R. A., Hsu, C. H. C., and Taylor, L. L. (2017). Tourism: The Business of Hospitality and Travel, 6th ed. Boston: Pearson. Cornes, R., and Sandler, T. (1996). The Theory of Externalities, Public Goods and Club Goods, 2nd ed. New York and London: Cambridge University Press. Dileep, M. R. (2019). Tourism, Transport and Travel Management. New York: Rougtledge. Dwyer, L., and Forsyth, P. eds. (2006). International Handbook on the Economics of Tourism. Cheltenham, UK: E. Elgar. Evans, N., Campbell, D., and Stonehouse, G. (2003). Strategic Management for Travel and Tourism. Oxford, UK: Butterworth-Heinemann. Fletcher, J., Fyall, A., Gilbert, D., and Wanhill, S. (2013). Tourism: Principles and Practice, 5th edition. Harlow, UK: Pearson Education. Frechtling, D. C. (2001). Forecasting Tourism Demand: Methods and Strategies. Oxford, UK: Butterworth- Heinemann Frechtling, D. C. (1996). Practical Tourism Forecasting. Oxford, UK: Butterworth- Heinemann. Goodman, P. S., and Alderman, L. (2019). “Turbulence in Iceland’s ‘Tourist’ Trade,” New York Times, August 26. Graham, A., Papatheodorou, A., Forsyth, P., eds. (2008). Aviation and Tourism: Implications for Leisure Travel. Ashgate, UK and Brookfield, VT: Aldershot. Hakim, D., and Petropoulos, A. (2015). “A Last Resort,” New York Times, January 21. Herman, F. E., and Hawkins, D. E. (1989).Tourism in Contemporary Society. Englewood Cliffs, NJ: Prentice-Hall. Higham, J., ed. (2007). Critical Issues in Ecotourism. Oxford, UK: Elsevier (ButterworthHeinemann). Holloway, J. C. (2001). The Business of Tourism, 6th ed. London: Financial Times Management (5th ed. Essex, UK: Addison Wesley Longman). Kass, D. I., and Okubo, S. (2000). “U.S. Travel and Tourism Satellite Accounts for 1996 and 1997,” Survey of Current Business. Washington, DC: U.S. Department of Commerce, Bureau of Economic Analysis (July). LSE Consulting (2016). Travel Distribution: The End of the World As We Know It available at: http://www.amadeus.com/documents/reports/lse-report-travel-distribution-the-end-of-theworld-as-we-know-it.pdf. Lyle, C. (2011). “Climate Change Impacts and Inter-Agency Cooperation in Tourism and Travel,” ICAO Journal, 66(2). Mak, J. (2004). Tourism and the Economy: Understanding the Economics of Tourism. Honolulu: University of Hawaii Press. Martin, F. (1994). “Determining the Size of Museum Subsidies,” Journal of Cultural Economics, 18. McCartney, S. (2012). “The Best and Worst U.S. Cities for Travel Taxes,” Wall Street Journal, October 18. Medlik, S. (2003). Dictionary of Travel, Tourism & Hospitality, 3rd ed. Oxford, UK: ButterworthHeinemann. Mouffakir, O., and Burns, P. M., eds. (2012). Controversies in Tourism. Oxfordshire, UK: CABI Mourato, S., Ozdemiroglu, E., Hett, T., and Atkinson, G. (2004). “Pricing Cultural Heritage,” World Economics, 5(3). Neil, J., and Wearing, S. (1999). Ecotourism Impacts, Potentials and Possibilities. Oxford, UK and Boston: Butterworth-Heinemann. Oppermann, M., ed. (1997). Geography and Tourism Marketing. Binghampton, NY and London: Haworth Press. Page, S. J. (1999). Transport and Tourism. Essex, UK and New York: Addison-Wesley Longman. Page, S. J., and Dowling, R. K. (2002). Ecotourism. Harlow, UK: Prentice-Hall (Pearson). Pasztor, A. (2013). “Startup to Sell Balloon Trips to Edge of Space,” Wall Street Journal, October 22.

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Pasztor, A. (2008). “Economy Fare ($100,000) Lifts Space-Tourism Race,” Wall Street Journal, March 26. Pasztor, A. (2004). “Travel’s Last Frontier,” Wall Street Journal, January 29. Pechlaner, H., and Smeral, E., eds. (2015). Tourism and Leisure: Current Issues and Perspectives of Development. Weisbaden: Springer/Gabler. Pizam, A., and Mansfeld, Y., eds. (1999). Consumer Behavior in Travel and Tourism. Binghampton, NY: Haworth Press. Romero, S., and Bogel-Burroughts, N. (5019). “Crisis Hits Dominican Republic Over Deaths of U. S. Tourists,” New York Times, June 24. Schuman, M. (2016). “Chinese Tourists Pump Cash Into a Hot Destination: China,” New York Times, September 28. Simon, S., and Pasztor, A. (2011). “Slow Liftoff for Space Tours,” Wall Street Journal, September 1. “Starship Enterprise: the Next Generation,” The Economist, January 26, 2008. Sindreu, J. (2019). “What Thomas Cook’s Collapse Says About Modern Tourism,” Wall Street Journal, September 24. Singh, J. P. (2010). Globalized Arts: the Entertainment Economy and Cultural Identity. New York: Columbia University Press. Stabler, M. J., Papatheodoru, A., and Sinclair, M. T., eds. (2010). The Economics of Tourism, 2nd ed. London and New York: Routledge. Swarbrooke, J. (1999). Consumer Behavior in Tourism. Oxford, UK: Butterworth- Heinemann. Swarbrooke, J., and Horner, S. (2001). Business Travel and Tourism. Oxford, UK: ButterworthHeinemann. Tribe, J. (2011). The Economics of Recreation, Leisure and Tourism. 4th ed. Oxford, UK: Elsevier: Butterworth-Heinemann. Var, T., and Lee, C. K. (1993). “Tourism Forecasting: State-of-the-Art Techniques,” in Kahn, Olsen, and Var (1993). Verhovek, S. H., and Kaufman, L. (2001). “America’s Fear of Flying Has Devastating Effect on Tourist Businesses,” New York Times, September 20. Wearing, S., and Neil, J. (1999). Ecotourism: Impacts, Potentials and Possibilities. Weed, M., and Bull, C. (2004). Sports Tourism: Participants, Policy, and Providers. UK: Butterworth- Heinemann. (Elsevier). Weiner, T. (2001). “Mexico’s Green Dream: No More Cancúns,” New York Times, January 12. Witt, S. F., and Martin, C. (1992). Modelling and Forecasting Demand in Tourism. London: Academic Press.

Part V

Roundup

Abstract This part summarizes the key issues that affect all travel sectors as they relate to performance and government policy aspects. It is shown that all sectors require tradeoffs in terms of capital and operating costs and the benefits that might ultimately be provided.

Chapter 8

Performance and Policy

To travel hopefully is a better thing than to arrive. —Robert Louis Stevenson, An Apology for Idlers, 1877

8.1

Common Elements

As seen in Chap. 1, leisure time—broadly defined as time not spent at work—has been expanding slowly, if at all. Over the long run, the potential to expand leisure time depends on the rate of gain in economic productivity, which is in turn affected by the rate of technological development. Nevertheless, after deducting life-sustaining activities from nonwork time, we have what is known in the vernacular as free time. But time is never really free in an economic sense because there are always alternative-opportunity costs. It is this opportunity-cost aspect, applicable to both leisure and business travel, that enables travel companies to successfully engage price-discrimination strategies that have positive effects on profits. It is also why, for all but the shortest trips, travel by air can take share away from other travel modes even though air tickets may be priced significantly more in terms of cost per trip. Beyond these generalities are several frequently observed travel industry characteristics. • The industries are highly capital intensive Be it hotels, airlines, cruise ships, theme parks, or casinos, the initial amount of capital investment is large compared to potential future outlays and to ongoing operating and maintenance expenses. Thus, with the possible exception of travel agencies, travel industry company profitability is normally closely linked and sensitive to the costs of capital (i.e., interest rates). Also, sunk costs are usually relatively large. • The industries are highly labor intensive Travel industries are comprised of segments that largely service the public en masse in functions such as passenger loading, food dispensation, cleaning of rooms, dealing of card games, and so forth. These functions lend themselves to standardization, but not automation, which means that labor intensity will remain © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 H. L. Vogel, Travel Industry Economics, https://doi.org/10.1007/978-3-030-63351-6_8

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•

•

•

•

8 Performance and Policy

high and profits will always be sensitive to quality and quantity of labor availability and wage rate considerations. Constant returns to scale are dominant Although cost economies of scale can be achieved in administrative overhead reductions for hotel chains, or quantity discounts in the bulk purchase of, say, airline parts and equipment, the people-service nature of these businesses suggests that most returns on investment do not improve as the scale of the operation increases. Industry structure tends toward oligopoly but with monopolistic-competitive characteristics. Given the relatively large initial investments required, most travel industry segments quickly evolve into the monopolistic-competitive and oligopolistic market structures. As is typical of such structures, there is then need to allocate and fund proportionately large branding-support and advertising as a form of product and service differentiation. The marginal customer provides a proportionately high profit With fixed and semivariable costs often accounting for more than half of costs, every incremental customer provides a proportionately high contribution to profit. As a result, it usually makes sense to spend a relatively large portion of anticipated per customer revenues on marketing and promotion. This is seen in hotels, airlines, casinos, theme parks, or even in the use of sophisticated reservation systems. Relatively small changes in prices have large effects on profitability With travel being a mass-market business characterized by high operating and/or financial leverage and with semivariable and fixed costs of operations important, even small price changes, up or down, will usually have a substantial impact on profits, up or down. Price-discrimination strategies are broadly applicable Because of great differences in customer time-opportunity costs as well as spending budgets, elasticities of demand vary widely and can be readily exploited in the pursuit of profit maximization.

8.2

Public Policy Issues

Virtually all travel industry segments are affected, in one way or another, by an array of rules and regulations and subsidies that are an outgrowth of political and cultural environments, both past and present. Regulations concerning airline safety and training or pertaining to casino operations are obvious examples, but public policy decisions have an impact everywhere. Travel industry segments clearly do not operate in a vacuum in which only purely economic decisions prevail. What is the optimal balance between regulation and intervention and support and subsidy is as much a question answered by political, cultural, and sociological considerations as by those of economics and technology.

8.3 Guidelines for Evaluation

345

Whether in the United States or elsewhere, though, the basic concerns are always expressed in terms of: • • • • •

degree of regulatory oversight and stringency, free market (laissez-faire) versus intervention, concentration of ownership versus diversity, subsidies and tax breaks, operating efficiencies and industry structures.

All of these issues can and often will be mixed together in the political arenas and sometimes the public policy that emerges will weigh on corporate profits, the effectiveness of management, or the growth prospects for the industry. At other times, subsidies of various kinds promote politically inspired agendas that help one industry at the expense of another without noticeable net benefit to the public at large. However, trade-offs and opportunity costs of best alternatives foregone are always present and should never be ignored in the process of making policy decisions. The policy questions and initiatives range widely and deeply across all tourism and transportation segments. For instance, should the federal government guarantee loans to airlines? Should there be restrictions on foreign airline ownership percentages as there are in the United States and in many other countries that protect their flag carriers at almost any cost? How high should gasoline taxes be? How can urban transit systems remain viable without public funding support? Can intercity passenger rail service ever pay its own way? How, where, and when should government legalize gaming and wagering? Should fancy tourist facilities be subsidized by tax credits and other such incentives when, for the population at large, basic service needs (e.g., for health care, education, and housing) are not being adequately addressed? In each situation, public policy decisions have a great and often lasting affect on sector profits and growth prospects. And seldom are there any easy answers.

8.3

Guidelines for Evaluation

The preceding chapters provide a background for analysis of travel industry investments. However, many factors not explicitly treated here (Federal Reserve Bank policy, overall economic trends, and investor psychology) also influence investment performance (Fig. 8.1). Happily, it is not necessary to delve into those subjects to here extract a few basic investment-decision guidelines. Yet it is important to recognize that the investment analysis process always includes elements of both art and science and that, as in other industries and investments, there is no magic formula that guarantees success. Over the short run, anything can happen. For example, financial market bubbles and crashes will, by definition, broadly distort valuations of many asset classes.

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Over the longer run, above-average risk-adjusted returns are normally related directly to a company’s ability to move toward the generation of free cash flow and toward earning returns that exceed the cost of capital. Often, the most favorable conditions for investments in travel are when the economy is emerging from recession (with personal consumption expenditures starting to accelerate upward), when new technology is contributing significantly to cost reductions in production and distribution systems, and when government regulatory and taxation attitudes toward travel industries turn relatively benign. Cash flows and private market values Companies are usually analyzed in terms of what a private buyer or acquiring public corporation might be willing to pay for the right to obtain access to the cash flow (often represented by EBITDA) of the enterprise. Public market valuations are often in the range of one-half to threequarters of private values, which are estimated from going-rate multiples of projected cash flows that have been paid in recent private transactions. The primary focus and key metric of any investment analysis should always be on the prospects for and the availability of free cash flow—or what remains after capital expenditures and other required investments in operations—rather than on earnings per share growth alone. Such free cash flows can be used to repurchase stock, reduce corporate debt, pay cash dividends, acquire other companies, or invest in promising internal projects. The measurement of free cash flow to earnings will, however, be affected by overall economic growth and inflation rates and should not be applied without

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further analysis of the underlying details. Another related expression is to calculate capital expenditures divided by cash flow (i.e., capex/cf), with the ideal being a ratio of under 35%. Debt/equity ratios The ability to service debt varies widely among travel companies but it is always a function of the volatility of projected cash flows. The less volatile the cash flow the higher is the debt level relative to equity that can be comfortably accommodated on the balance sheet. Casino-industry companies would, for example, be generally expected to experience less cash flow volatility than companies in the airline industry. By and large, the major hotel, rail, bus, travel agency, and theme park companies would usually fall somewhere in the middle of the volatility range. Price/earnings (P/E) ratios For travel stocks, the price/earnings ratio seems to have lost a great deal of its usefulness as a tool in comparative investment analysis. In hotels, for example, earnings trends can be easily distorted by various frequent writedowns or gains on sales of properties. Companies is different countries also still operate under somewhat different accounting standards. If price/earnings ratios are nevertheless used to compare travel stocks with alternative investments, then adjustments for such differences in the accounting practices must obviously be made. Price/sales ratios Because price-to-sales ratios mostly do not suffer from the many potential accounting distortions that are frequently present in the calculation of earnings, such ratios have become increasingly popular in the evaluation of common stocks. For travel securities, however, the price/sales ratio (price per share divided by revenues per share) is perhaps most useful as a “reality check”—especially if adjustments that smooth or normalize sales over several periods are made to take into account any evidence that current period sales may be far above or below trend. Sales may be temporarily boosted far above trend, for example, with the opening of large new hotel properties or the addition of new airline routes, or they may be temporarily depressed far below trend because of an economic recession. Price-tosales ratios will be generally correlated to the size of profit margins. Enterprise values The total value of an enterprise is found by multiplying the number of shares outstanding by price and then adding net debt (i.e., total debt minus cash) and adjusting for off-balance sheet assets. Enterprise value (EV) is then often compared with earnings before interest and taxes (EBIT), EBITDA, or any other preferred measure of cash flow. When applied to similar companies in the same industry, such ratios enable firms with different capital structures to be compared on the same basis. EV ratios are thus somewhat more reliable than P/E ratios in deciding how expensive a stock is relative to its industry group. Book value This traditional yardstick for financial analysis normally has little relevance in the evaluation of travel company stock prices because the key earnings power may reside—as in the case of landing slots or gate allocations or brand names—in assets that have already been largely or completely written down or are intangible. Moreover, in the case of real estate assets, the historical cost basis is

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usually far below what a property might currently be worth. In other words, brand names and other intangible assets may have considerable value and yet not be reflected in the stated book numbers.

8.4

Final Remarks

The preceding pages have shown that travel is an enormous global business that employs either directly or indirectly at least one out of ten people in the world. Estimates of annual total world travel and tourism spending, depending on the definitions used, begin at the US$2 trillion dollar level and rise from there. The main operating and asset valuation features of travel-related industry segments can be analyzed using standard financial and economic methods. And despite differences in their surface appearances, most travel-industry segments must cope with the same or similar regulatory and environmental issues and respond in kind to uncontrollable macroeconomic forces that affect the costs of borrowing, labor, and fuel. The prospect of above-average growth for travel industries, however, depends to a large extent on the assumption that global wealth and incomes on a per capita basis will continue to rise and to be distributed more widely. The rate at which this happens will be influenced, as always, by politics as much as by gains in productivity. In much less than one hundred years from now, a new section in this book will probably be needed to cover the peculiar economics of tourism in space.1 Until that time arrives, though, we can look forward over the nearer term to evolutionary, not revolutionary, changes in the familiar modes of travel. As writer John Steinbeck observed, “People don’t take trips . . . trips take people.” Note The beginnings of such an “astro-tourism” industry were, for example, covered in “The New Space Race,” 60 Minutes, January 1, 2006. As described in Chang (2010), Boeing is already planning to book space tourists and brief orbital flights for wealthy adventure-seekers are becoming available. As Lee (2013) writes, space travel agents are in training and the founder of Budget Hotels has begun developing pods for spending time in Earth orbit and beyond. See also Seedhouse (2014), Chang (2017), Wall (2019), and Hough (2019).

References Chang, K. (2017). “Opportunity in Orbit,” New York Times, November 28. Chang, K. (2010). “Boeing Plans to Fly Tourists Beyond Earth,” New York Times, September 16. Hough, J. (2019). “The Space Economy Is Starting to Take Shape 50 Years After the Moon Landing,” Barron’s, July 13.

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Lee, D. P. (2013). “Welcome to the Real Space Age,” New York Magazine, May 27. Seedhouse, E. (2014). Tourists in Space: A Practical Guide, 2nd ed., Heidelberg: Springer//Praxis. Wall, R. (2019). “For $50 Million, Book Your Vacation in Space,” Wall Street Journal, April 12.

Appendix A: Sources of Information

The most convenient sources of macroeconomic data for use in travel industry studies include the following regular U.S. Department of Commerce publications: Survey of Current Business, containing personal-consumption expenditure figures for the preceding four years U.S. Labor Department, Monthly Review and Handbook of Labor Statistics, for articles and data on labor and employment issues U.S. Census Selected Services, which contains regional data on revenues, employment, and productivity U.S. Statistical Abstract for historical series U.S. Industrial Outlook, published every year with forecasts for the next five years. American Society of Travel Agents at www.ASTA.org. Information on specific travel business topics is also widely available in the following regularly published nongovernment-sponsored magazines, newspapers, journals, and Web sites.

Advertising Age Airfinance Euro Money Yearbook Airfinance Journal Airline Business Airports Council Intl. web site (www.aci-na.org) Airport World Annals of Tourism Research ATA Handbook and Web site (www.air-transport. org) Aviation Daily Aviation & Aerospace Almanac

Journal of Hospitality and Tourism Management Journal of Hospitality and Tourism Technology Journal of Sustainable Tourism Journal of Transportation and Statistics Journal of Transport Economics and Policy Journal of Travel Research Journal of Travel Research LegalGambling and the Law Lodging/Hospitality Lodging/Hospitality www.Lodgingresearch.com (continued)

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352 Cruise Industry News Hotels Magazine Hotel & Motel Management HotelsNewsNow.com ICAO web site (www.ICAO.org) International Journal of Hospitality Management International Journal of Contemporary Hospitality Mgmt International Journal of Tourism Research Journal of Ecotourism Journal of Gambling Studies

Appendix A: Sources of Information Office of Travel & Tourism Industries PlaneBusiness.com Research in Transportation Economics Tourism Economics Tourism Management Travel Agent Travel & Tourism Analyst (www.t-ti.com) Travel Weekly & TravelWeekly.com (US & UK) World Airline News World Tourism Organization Yearbook

See also Global Airline Industry Program, Airline Data Project, http://web.mit.edu/airlinedata/ www/default.html

Appendix B: Valuation Concepts

The valuation approaches discussed in Chap. 1.6 may be broadly applied to any asset class. However, travel industry analysts will also encounter financial notions of internal rates of return (IRR) and economic value added (EVA). The objective here is not to replicate the detail that would be provided in standard texts on financial theory and practice, but to provide a brief introduction to the basic concepts. Internal Rate of Return The time value of money is central to all valuation calculations, which must include the number of periods, n, over which cash flows in or out; present value, pv; future value, fv;, and an interest rate, r. Using these elements, project investments are decided on the basis of whether the required rate of return—the return in excess of the project’s cost of capital—will be earned and whether such a return is by comparison above those that might be earned by other projects also competing for the same capital at the same time. This required rate of return may also be further specified as the required return to debt capital, kd; to equity capital, ke, or to a weighted average of both. In ranking of alternative investment projects, whether involving a tangible asset such as a new airplane or less tangible assets such as landing rights, an internal rate of return (IRR) analysis is usually helpful, if not always totally decisive. The IRR is defined as the rate of discount, k, which makes the net present value (NPV) equal to zero. Because an increase of the discount rate (i.e., required rate of return) arithmetically decreases the NPV of a project, it is then possible through trial and error to determine the IRR at which a project’s NPV declines to zero. Assuming that the project is financed through equity only, then the discovered IRR provides an estimated return on equity (ROE). If the ROE is above the cost of equity capital, ke, the project should be accepted. If it is equal to the cost of equity capital, an investor might be indifferent to its prospects. And certainly, the project would be rejected if the IRR were below ke This approach will normally lead to decisions that are consistent with a strategy of maximizing NPV, but there are circumstances when this will not always be true. For example, it is possible that no IRR can be determined. Moreover, it is possible that © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 H. L. Vogel, Travel Industry Economics, https://doi.org/10.1007/978-3-030-63351-6

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mutually exclusive alternative projects are being considered. Rankings based on NPV alone would provide an immediate decision, whereas rankings based on IRRs suffer from problems of scale and from assumptions concerning the reinvestment rate. Although IRR may show the highest rate of return, it does not indicate the number of dollars of value that might be created. And it is possible that a project’s cash flow timing is such that the NPV never falls to zero or that the NPV crosses the horizontal axis and drops to zero more than once, thereby producing multiple IRRs. Obviously, a project with an IRR of 40% creating only $100 of NPV should not be chosen over a project with a 25% IRR but that creates $500 of NPV. The IRR method also makes the implicit assumption that a project’s cash flows are, over the life of the investment, able to be reinvested at the same rate as the IRR. Such an assumption is usually unrealistic.

Glossary

Aggregate The familiar type of summary series shown in most statistical reports. Generally, it is a total, such as the gross national product or retail sales, but sometimes it is an average, such as the index of industrial production or the index of wholesale prices. Air/Sea Mix Indicates the proportion of passengers who book air travel through the cruise line as part of a package instead of separately. A change in the mix affects margins, but not operating income as airfares collected by cruise lines are booked as an expense to the airlines. A higher air/sea mix leads to lower operating margins. Amortization of debt A gradual reduction of a debt through periodic payments covering the interest and part of the principal. Generally, amortization is used when the credit period is longer than a year. Common examples of amortization of debt are mortgage payments on homes, which extend over a period of 20 years or more. Asset A physical property or intangible right, owned by a business or an individual, that has a value. An asset is useful to its owner either because it is a source of future services or because it can be used to secure future benefits. Business assets are usually divided into two categories: current and fixed. Asset values The implied price buyers might be willing to pay to obtain control of an asset’s profit- and/or cash-generating potential. Asset values fluctuate according to changes in general economic conditions, interest rates, and expected returns. Block time In the airline industry, the time on a segment from when the aircraft’s engines are switched on at departure to the time they are switched off on arrival. This, of course, includes tarmac taxi time. Bond A written promise to pay a specified sum of money (principal) at a certain date in the future or periodically over the course of a loan, during which time interest is paid at a fixed rate on specified dates. Bonds are issued by corporations, states, localities (municipal bonds), foreign governments, and the

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U.S. government, usually for long terms (more than 10 years), although any security issued by the U.S. government for more than 5 years is defined as a bond. Book value The value of a corporation according to its accounting records. It is computed by subtracting all debts from assets; the remainder represents total book value. Total book value is also referred to as net assets. If a corporation has assets of $300,000 and debts of $100,000, its total book value is $200,000. In reports of corporations, the book value is usually represented on a per share basis. This is done by dividing the total book value by the number of shares. In the example given above, if the corporation had 10,000 shares outstanding, its book value would be $20 per share. The book value differs from the par value of the shares and also from the market value. Breakeven point The specific volume of sales at which a firm neither makes nor loses money. Above this point, a firm begins to show a profit; below it, it suffers a loss. Breakeven-point analysis is used to compute the approximate profit or loss that will be experienced at various levels of production. In carrying out this analysis, each expense item is classified as either fixed (constant at any reasonable level of output) or variable (increasing as output increases and decreasing as output declines). Business cycle Alternate expansion and contraction in overall business activity evidenced by fluctuations in measures of aggregate economic activity such as the gross national product, the index of industrial production, and employment and income. A business cycle may be divided into four phases: expansion, during which business activity is successively reaching new high points; leveling out, during which business activity reaches a high point and remains at that level for a short period of time; contraction, during which business volume recedes from the peak level for a sustained period until the bottom is reached; and recovery, during which business activity resumes after the low point has been reached and continues to rise to the previous high mark. Capitalized value The terms applied to a technique used to determine the present value of an asset that promises to produce income in the future. To calculate the present value, the total future income expected must be discounted, that is, offset against the cost (as measured by the current interest rate) of carrying the asset until the income has actually been realized. If the asset promises a stream of income, its capitalized value is calculated by adding together the present discounted value of the income in each year. The general formula for this calculation is I/(1 + r)t where I is the annual income, r is the current rate of interest, and t is the number of years involved. In this manner, an investor confronted with a choice of properties can determine which alternative is the most remunerative, though the formula tells nothing about the relative risks involved.

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357

Cash flow The sum of profits and depreciation allowances. (Instead of profits, many economists use retained earnings, which are profits after taxes and after deductions for dividend payments.) Gross cash flow is composed of total profits plus depreciation; net cash flow is composed of retained earnings plus depreciation. Thus, cash flow represents the total funds that corporations generate internally for investment in modernization and expansion of plants and equipment and for working capital. The growth of depreciation allowances over the years has made them a much more important part of cash flow than retained earnings. To facilitate comparisons of property values, however, travel businesses often take cash flow to be profits prior to deductions of interest, depreciation and amortization, and taxes. Code-sharing A common airline industry marketing practice in which, by mutual agreement between cooperating carriers, at least one of the airline designator codes used on a flight is different from that of the airline operating the flight. Common stock The capital stock of a corporation that gives the holder an unlimited interest in the corporation’s earnings and assets after prior claims have been met. Common stock represents the holder’s equity or ownership in the corporation. Holders of common stock have certain fundamental legal rights, including the following: preemptive rights; the right, in most cases, to vote for the board of directors, who actually manage the company; the right to transfer any or all shares of stock owned; and the right to receive dividends when they are declared by the board of directors. Competition The condition prevailing in a market in which rival sellers try to increase their profits at one another’s expense. In economic theory, the varieties of competition range from perfect competition, in which numerous firms produce or sell identical goods or services to oligopoly in which a few large sellers with substantial influence in the market vie with one another for the available business. Early economists envisioned perfect competition as the most effective assurance that consumers would be provided with goods and services at the lowest possible prices. Complementary goods Goods that must be accompanied by another good to be useful (e.g., perfect complements would be a left shoe and a right shoe). Contrariwise, close substitutes would be margarine and butter. Convertible debenture A certificate issued by a corporation as evidence of debt that can be converted at the option of the holder into other securities (usually common stock, but sometimes preferred stock) of the same corporation. Each debenture can be converted into a specified number of shares of stock at a stipulated price for a certain period. There are two advantages to convertible debentures for the issuing corporation: (a) The conversion privilege makes the debentures more attractive to investors and tends to reduce interest costs. (b) The debentures facilitate the extinction of debt because debt declines and equity (stock) increases as holders convert their debentures. The major disadvantage is discrimination against the company’s stockholders, whose equity is diluted as the holders of debentures convert them. At all times during the conversion period,

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there is a price relationship between the debenture and the stock. It is based on the conversion price, the number of shares into which each debenture can be converted, and the value that the market puts on the conversion privilege. For example, a $1000 debenture that can be converted into 50 shares of common stock at $20 per share will normally trade in the market at a price higher than $1000 because of the conversion privilege. Correlation The statistical technique that relates a dependent economic variable to one or more independent variables over a period of time to determine the closeness of the relationship between the variables. This technique can be used for business forecasting. When more than one independent variable is used, the relationship is called a multiple correlation. Cost recovery Accounting method of amortization in which all costs are charged against earned revenue and no profit is recognized until cumulative revenue equals cumulative costs. This method is not acceptable for financial-statement reporting under generally accepted accounting principles. Current assets Cash or other items that will normally be turned into cash within one year and assets that will be used up in the operation of a firm within one year. Current assets include cash on hand and in the bank, accounts receivable, materials, supplies, inventories, marketable securities, and prepaid expenses. Current liabilities Amounts owed that will ordinarily be paid by a firm within one year. The most common types of current liabilities are accounts payable, wages payable, taxes payable, and interest and dividends payable. Debenture A bond that is not protected by a specific lien or mortgage on property. Debentures (debts), which are issued by corporations, are promises to pay a specific amount of money (principal) at a specified date or periodically over the course of the loan, during which time interest is paid at a fixed rate on specified dates. Demand The desire, ability, and willingness of an individual to purchase a good or service. Desire by itself is not equivalent to demand: The consumer must also have the funds or the ability to obtain funds to convert the desire into demand. The demand of a buyer for a certain good is a schedule of the quantities of that good that the individual would buy at possible alternative prices at a given moment in time. The demand schedule, or the listing of quantities that would be bought at different prices, can be shown graphically by means of the demand curve. The term demand refers to the entire schedule of possibilities, not only to one point on the schedule. It is an instantaneous concept expressing the relationship of price and the quantity that is desired to be bought, all other factors being constant. Depreciation A reduction in the value of fixed assets. The most important causes of depreciation are wear and tear (loss of value caused by the use of an asset); the effects of the elements (i.e., decay or corrosion); and gradual obsolescence, which makes it unprofitable to continue using some assets until they have been fully exhausted. The annual amount of depreciation of an asset depends on its original purchase price, its estimated useful life, and its estimated salvage value. A

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number of different methods of figuring the amount of depreciation have been developed. Using the simple straight-line method, which considers depreciation a function of time, the annual depreciation cost is calculated by dividing the cost of the asset (original minus salvage cost) equally over its entire life. Discounted cash flow (DCF) method A method of measuring the return on capital invested. The value of a project is expressed as an interest rate at which the project’s total future earnings, discounted from the time that they accrue to the present, equal the original investment. It is more precise than most of the other methods used to measure return on capital invested because it recognizes the effect of the time value of money. It can be used to determine whether a given project is acceptable or unacceptable by comparing each project’s rate of return with the company’s standard. Discount rate Interest rate charged member banks by the Federal Reserve for the opportunity to borrow added reserves. Also used in DCF methods. Discretionary spending A measure, developed by the National Industrial Conference Board, that reflects the extent of consumer spending as the result of a decision relatively free of prior commitment, pressure of necessity, or force of habit. It includes all personal expenditures not accounted for specifically or in equivalent form in imputed income, fixed commitments, or essential outlays. The series measures the growth and ability of American consumers to exercise some degree of discretion over the direction and manner of their spending and saving. Drop A term used in the gaming industry to indicate the total monetary-equivalent value of cash, IOUs (“markers”), and other items that are physically deposited or dropped into a cash box of a gaming table or slot machine. EBITDA Earnings before deduction of interest, taxes, and depreciation and amortization. Often used as a convenient representation of the cash flow of media and travel-related businesses. However, EBITDA has lost some analytical favor because it doesn’t include the cash flow required to service debts (interest payments) and to purchase or construct new projects, services, or equipment. In times of rapid technological or business change, such purchases will normally require cash outlays that exceed depreciation and amortization. Econometrics The branch of economics that expresses economic theories in mathematical terms in order to verify them by statistical methods. It is concerned with empirical measurements of economic relations that are expressible in mathematical form. Econometrics seeks to measure the impact of one economic variable on another to enable the prediction of future events or to provide advice on economic-policy choices to produce desired results. Economic theory can supply qualitative information concerning an economic problem but it is the task of econometrics to provide the quantitative content for these qualitative statements. Economic growth An increase in a nation’s or an area’s capacity to produce goods and services coupled with an increase in production of these goods and services. Usually, economic growth is measured by the annual rate of increase in a nation’s gross national product (GNP) as adjusted for price changes.

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Economic model A mathematical statement of economic theory. Use of an economic model is a method of analysis that presents an oversimplified picture of the real world. Ecotourism Though there is no wide agreement on a strict definition, the term often suggests tourism that does not disturb the ecological balance of a region’s resources of land, labor, transportation, and other assets. Also known as “green tourism.” Elastic demand The percentage change induced in one factor of demand divided by a given percentage change in the factor that caused the change. For example, if the price of a commodity is raised, purchasers tend to reduce their buying rate. The relationship between price and purchasing rate, which is known as the elasticity of demand, expresses the percentage change in the buying rate divided by the percentage change in price. Elasticity The relative response of one variable to a small percentage change in another variable. Equilibrium The state of an economic system in which all forces for change are balanced so that the net tendency to change is zero. An economic system is considered to be in equilibrium when all the significant variables show no change over a period of time. Equity Amount of capital invested in an enterprise. It represents a participative share of ownership, and in an accounting sense it is calculated by subtracting the liabilities (obligations) of an enterprise from its assets. Excess reserves The surplus of cash and deposits owned by commercial member banks of the Federal Reserve System over what they are legally required to hold at Reserve Banks or in their own vaults. The excess-reserve position of a bank is an indication of its ability to invest in government bonds or to make loans to customers. Therefore, if the Federal Reserve System is trying to stimulate business in periods of economic sluggishness, it buys government bonds from private sellers, thus increasing bank reserves, and vice versa. Externality The result of choices by individuals and firms that affects other individuals and firms without operating through market prices. Externalities may be positive and beneficial to society or negative and harmful, as an air-polluting manufacturing process would be. FIT Denotes the free or foreign independent traveler market segment. See also IT. Foreign exchange All monetary instruments that give residents of one country a financial claim on another country. The use of foreign exchange is a country’s principal means of settling its transactions with other countries. Franchise A brand for goods and services that provides a distinct identity and that can be globally extended through franchise agreements that provide local owners with quantity purchase discounts, advertising and real estate support, etc. Airlines have distinct franchises in the routes that they fly (e.g., those of British Air, American, United, etc.). Hotel chains, car rental companies, travel agencies, and restaurant chains use franchise agreements to extend the brand (e.g., McDonald’s, Hilton, Marriott, Avis, Carlson, etc.).

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Free reserves The margin by which excess reserves exceed borrowings at Federal Reserve Banks. They are a better indicator of the banking system’s ability to expand loans and investments than excess reserves. Manipulation of the net freereserve position of member banks is an indication of the monetary policy that the Federal Reserve wishes to pursue. Gross domestic product (GDP) The measure of the value of all goods and services produced in a country no matter whether that output belongs to natives or foreigners. It is different from gross national product (GNP), which measures output belonging to U.S. citizens and corporations wherever that output is created. In the United States, the differences between the values of the two series have been slight. See Gross national product. Gross national product (GNP) The most comprehensive measure of a nation’s total output of goods and services. In the United States, the GNP represents the dollar value at current prices of all goods and services produced for sale plus the estimated value of certain imputed outputs, that is, goods and services that are neither bought nor sold. The rental value of owner-occupied dwellings and the value of farm products consumed on the farm are the most important imputed outputs included; the services of housewives are among the most important nonmarket values included. The GNP includes only final goods and services; for example, a pair of shoes that costs the manufacturer $2.50, the retailer $4.50, and the consumer $6.00 adds to the GNP only $6.00, the amount of the final sale, not $13.00, the sum of all the transactions. The GNP can be calculated by adding either all expenditures on currently produced goods and services or all incomes earned in producing these goods and services. Gross win The casino equivalent of revenues or sales in other businesses. It is from the gross win that operating expenses must be deducted. Handle A term used in the gaming industry to indicate the total dollar amount bet on the outcome of an event. Hold A term used in the gaming industry to indicate how much of the drop is retained (won) by the game operator through the course of play. Hold can be expressed as a percentage of the drop in which case it is known as the hold percentage, often in a shorthand way called “win.” Income effect A term used in demand analysis to indicate the increase or decrease in the amount of a good that is purchased because of a price-induced change in the purchasing power of a fixed income. When the price of a commodity declines, the income effect enables a person to buy more of this or other commodities with a given income. The opposite occurs when the price rises. By using indifference curves, it is possible to separate the income effect from the so-called substitution effect in which the demand for a price-reduced good rises as it is substituted for other goods whose prices have remained constant. Indifference curve A graphic curve that represents the various combinations of two goods that will yield the consumer the same total satisfaction. For example, a household may receive the same satisfaction from consuming a pound of steak or one pound of chicken. By assuming that the two commodities can be substituted

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for each other, it is possible to draw an indifference schedule that contains all of the possible combinations of the commodities that will yield the same satisfaction. When the schedule is plotted on a graph, with one commodity along the vertical axis and another along the horizontal axis, the curve that connects the points is called an indifference curve. Inelastic demand (inelasticity) A term used to describe a proportionally smaller change in the purchase rate of a good than the proportional change in price that caused the change in amount bought. When the demand for a product is inelastic, a relatively large price change is necessary to cause a relatively small increase in purchase. To calculate the elasticity of demand, the percentage change in buying rate (the quantity bought per period of time) is divided by the percentage change in price. Inflation A persistent upward movement in the general price level. It results in a decline in purchasing power. Interest The price paid for the use of money over a period of time. Individuals, businesses, and governments buy the use of money. Businesses pay interest for the use of money to purchase capital goods because they can increase production and productivity through the introduction of new plants and new machines. Inventory Supply of various goods kept on hand by a firm to meet needs promptly as they arise and thus assure uninterrupted operation of the business. In manufacturing, for example, inventory includes not only finished products awaiting shipment to selling outlets but also raw materials and countless other items required for the production and distribution of the product. IT Denotes the inclusive tour (i.e., packaged travel segment). Sometimes also known as GIT for group inclusive tour and contrasts to FIT (see above). Labor force According to the concept of the U.S. Department of Labor and the U.S. Bureau of the Census, the noninstitutionalized population, 16 years of age or older, who either are employed or are looking for work. Lead-lag relationship The timing of changes in one statistical series in relation to changes in another series. The term is frequently used in sales forecasting, which makes use of the timing pattern between a company’s sales and a particular economic indicator. Liabilities The debts or amounts of money owed by an individual, partnership, or corporation to others. Considered from another point of view, liabilities are the claims or rights, expressed in monetary terms, of an individual’s or a corporation’s creditors. In accounting, liabilities are classified as either short-term or long-term liabilities or as secured or unsecured liabilities. Short-term liabilities are those that will be satisfied, or paid, within one year. Load factor Term used by airlines, for a single sector flight, to indicate the passengers carried as a percentage of the seats available for sale. On a network of routes, the load factor is obtained by taking total passenger-miles as a percentage of total seat-miles available. Macroeconomics Modern economic analysis concerned with data in aggregate as opposed to individual form. It concerns itself with an overall view of economic

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life considering the total size, shape, and functioning of economic experience rather than the workings of individual parts. More specifically, macroeconomics involves the analysis of the general price level rather than the prices of individual commodities, national output or income rather than the income of the individual firm, and total employment rather than employment in an individual firm. Marginal cost The additional cost that a producer incurs by making one additional unit of output. If, for example, total costs were $13,000 when a firm was producing two machine tools per day and $18,000 when it was producing three machine tools per day, the marginal cost of producing one machine tool was $5000. The marginal cost may be the same or higher or lower in moving from three to four machine tools. The concept of marginal cost plays a key role in determining the quantity of goods that a firm chooses to produce. The purely competitive firm, which faces a given price set in the market, increases its output until marginal cost equals price. That point is the firm’s best-profit output point. The imperfectly competitive firm equates marginal cost to marginal revenue (additional revenue) to obtain the highest profits. For most firms, marginal costs decline for a while and then begin to rise. The pattern of the marginal-cost graph depends on the nature of the firm’s production function and the prices of the goods that it buys. Marginal propensities The marginal propensity indicates the proportion out of every dollar of additional income that consumers, on the average, are willing to save, invest, spend, and import. Marginal propensities are central to macroeconomic theories and models such as those of economist John Maynard Keynes in the 1930s. Marginal revenue The additional revenue that a seller receives from putting one more unit of output on the market. Margins See Profit margin. Market share The ratio of a company’s sales, in units or dollars, to total industry sales, in units or dollars, on either an actual basis or a potential basis for a specific time period. Microeconomics Modern economic analysis concerned with data in individual form as opposed to aggregate form. It analyzes the individual consuming unit rather than the total population and the individual commodity rather than total output. Microeconomics deals with the division of total output among industries, products, and firms and the allocation of resources among competing uses. Model The expression of a theory by means of mathematical symbols or diagrams. Modern portfolio theory A theory that enables investment managers to classify, estimate, and control the sources of investment risk and return. Monopoly A market structure with only one seller of a commodity. In pure monopoly, the single seller exercises absolute control over the market price because there is no competitive supply of goods on the market. The seller can choose the most profitable price and does so by raising the price and restricting the output below what would be achieved if there were competition. In a natural monopoly, the monopolist’s economies of scale are large.

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Monopsony A market structure with a single buyer of a commodity. Pure monopsony, or buyer’s monopoly, is characterized by the ability of the single buyer to set the buying price. In the case of a monopsonist who maximizes profits, both the buying price and the quantity bought are lower than they would be in a competitive situation. National income The total compensation of the elements used in production (land, labor, capital, and entrepreneurship) that comes from the current production of goods and services by the national economy. It is the income earned (but not necessarily received) by all persons in the country in a specified period. Nonborrowed reserves A reserve aggregate consisting of total bank reserves (deposits of the Federal Reserve and vault cash) minus borrowings by member banks from the Federal Reserve. Oligopoly A type of market structure in which a small number of firms supply the major portion of an industry’s output. The best-known example in the U.S. economy is the automobile industry in which three firms account for 65% of the output of passenger cars. Although oligopolies are most likely to develop in industries whose production methods require large capital investments, they also cover such diverse items as cigarettes, light bulbs, chewing gum, detergents, and razor blades. In economic theory, the term oligopoly means a mixture of competition and monopoly. The benefit or harm to the economy at large by oligopolies remains in dispute. Operating income Earnings before interest, other income, and taxes. Opportunity costs The value of the productive resources used in producing one good, such as an automobile, instead of another good, such as a machine tool. With relatively fixed supplies of labor and capital at any given time, the economy cannot produce all it wants of everything. Paretian optimum A situation that exists when no one (say person A) in a society can move into a position that A prefers without causing someone else (person B) to move into a position that B prefers less. In other words, a situation is not a paretian or social optimum if it is possible, by changing the way in which commodities are produced or exchanged, to make one person better off without making another person (or persons) worse off. See Second-best theory. Partnership A type of business organization in which two or more persons agree on the amounts of their contribution (capital and effort) and on the distribution of profits, if any. Partnerships are common in retail trade, accounting, and law. Passenger-miles (kilometers) The number of passengers on a flight multiplied by the stage distance as measured in miles or kilometers. Personal-consumption expenditures Expenditures that reflect the market value of goods and services purchased by individuals and nonprofit institutions or acquired by them as income in kind. The rental value of owner-occupied dwellings is included, but not the purchases of dwellings. Purchases are recorded at cost to consumers, including excise or sales taxes, and in full at the time of purchase whether made with cash or on credit.

Glossary

365

Personal income According to the concept of the U.S. Department of Commerce, the amount of current income received by persons from all sources, including transfer payments from government and business, but excluding transfer payments from other sources. Personal income also includes the net incomes of unincorporated businesses and nonprofit institutions and nonmonetary income such as the estimated value of food consumed on farms and the estimated rental value of homes occupied by their owners. PFC In airlines, refers to PFC is passenger facility charges (i.e., charges to passengers for use of airport facilities). PFC revenues are used to pay for runways, terminals, and other related assets. Price/earnings ratio The current market price per share of a company’s stock expressed as a multiple of the company’s per-share earnings. Production function The various combinations of land, labor, materials, and equipment that are needed to produce a given quantity of output. The production function expresses the maximum possible output that can be produced with any specified quantities of the various necessary inputs. Every production function assumes a given level of technology; once technological innovations have been introduced, the production function changes. Productivity The goods and services produced per unit of labor or capital or both; for example, the output of automobiles per person-hour. The ratio of output to all labor and capital is a total productivity measure; the ratio of output to either labor or capital is a partial measure. Anything that raises output in relation to labor and capital leads to an increase in productivity. Profit margin Net profit from operations divided by net sales and expressed as a percentage. This percentage measures the efficiency of a company or an industry. Nevertheless, profit margins vary widely among industries and among companies within a given industry. See Returns. Profits The amount left over after a business enterprise has paid all its bills. Prospectus Any communication, either written or broadcast by radio or television, that offers a security for sale. The prospectus contains the most important parts of the registration statement, which must give all information relevant to the issue. Public good A good for which the costs of production are independent of the number of people who consume it. National defense is an example, for one person’s consumption does not diminish the quantity available to others. TV programs are almost pure public goods because the program, no matter how it is recorded, remains unchanged regardless of how many people view it. In contrast, pure private goods, once consumed by an individual, are no longer available for someone else. For private goods, say a slice of bread, the costs of production are related to the number of people who consume it. Rack rate The maximum published rate applicable to a hotel’s room-type segment. Regression line A statistical term that indicates a relationship between two or more variables. The regression line was first used by Sir Francis Galton to indicate certain relationships in his theory of heredity, but it is now employed to describe many functional relationships. A regression, or least-squares, line is derived from

366

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a mathematical equation relating one economic variable to another. The use of regression lines is important in determining the effect of one variable on another. Required reserves The percentages of their deposits that U.S. commercial banks are required to set aside as reserves at their regional Federal Reserve Bank or as cash in their vaults. Reserve requirements vary according to the category of the bank. Resort Fee A hotel’s mandatory additional charge above the advertised price that is collected separately. It is basically misleading and deceptive because it does not represent the true per diem room rate. Returns The earnings or profit compensations received for owning assets or equity positions. Also, returns on sales are equivalent to profit margins. Risk The exposure of an investor to the possibility of loss of money. Profit is the investor’s reward for assuming the risk of economic uncertainty, such as changes in consumer tastes or changes in technology. The financial risk is based on natural, human, and economic uncertainties. Second-best theory A theory that analyzes alternative suboptimal positions to determine the second best when some constraint prevents an economy from reaching a paretian optimum. See Paretian optimum. Secular trend A statistical term denoting the regular, long-term movement of a series of economic data. The secular trend of most economic series is positive, or upward, indicating growth, the angle of the trend depending on how fast or how slow the growth rate is. Spoilage In airlines, the term refers to seats for which demand exists but which, for various reasons, nevertheless actually depart empty. There is no spoilage if at the date of departure the number of reservations equal capacity. Overbooking occurs if at the date of departure the number of reservations exceeds capacity. Supply The ability and willingness of a firm to sell a good or service. The firm’s supply of a good or service is a schedule of the quantities of that good or service that the firm would offer for sale at alternative prices at a given moment in time. The supply schedule, or the listing of quantities that would be sold at different prices, can be shown graphically by means of a supply curve. The term supply refers to the entire schedule of possibilities, not to one point on the schedule. It is an instantaneous concept expressing the relationship of price and the quantity that would be willingly sold, all other factors being constant. Tax credit A legal provision permitting U.S. taxpayers to deduct specified sums from their tax liabilities. Tax deduction A legal provision permitting U.S. taxpayers to deduct specified expenditures from their taxable income. Time series A set of ordered observations of a particular economic variable, such as prices, production, investment, and consumption, taken at different points in time. Most economic series consist of monthly, quarterly, or annual observations. Monthly and quarterly economic series are used in short-term business forecasting.

Glossary

367

Underwriter Any person, group, or firm that assumes a risk in return for a fee; usually called a premium or commission. Unemployment rate The number of jobless persons expressed as a percentage of the total labor force. The United States counts as unemployed anyone 16 years of age or over who is out of work and would like a job (even if that person is doing little about finding one). Upgauging In airlines, an increase in capacity by adding seats to existing aircraft and replacing smaller planes with larger ones. Utility he ability of a good or a service to satisfy human wants. It is the property possessed by a particular good or service that affords an individual pleasure or prevents pain during the time of its consumption or the period of anticipation of its consumption. The degree of utility of a good varies constantly. Thus, utility is not proportional to the quantity or type of the good or service consumed. Warrant An option that gives the holder the privilege of purchasing a certain amount of stock at a specified price for a stipulated period. Wet lease Refers to aircraft leasing that requires the lessor to provide the lessee with aircraft, crew, and sometimes also maintenance and insurance. Altogether, known as ACMI. Win See Gross win. Working capital, net The excess of current assets over current liabilities. These excess current assets are available to carry on business operations. As demand increases in prosperous times, a large volume of working capital is needed to expand production. Workweek The number of weekly hours per factory worker for which pay has been received, including paid holidays, vacations, and sick leaves. In the United States, workweek figures cover full-time and part-time production and related workers who receive payment for any part of the pay period ending nearest the fifteenth of the month. Because of increasing amounts of paid holidays, vacations, and sick leave, the paid workweek exceeds the number of hours actually worked per week. The average-workweek series compiled from payroll data by the U.S. Bureau of Labor Statistics differs from the series of weekly hours actually worked that is compiled from household surveys by the U.S. Bureau of the Census. It also differs from the standard or scheduled workweek because of such factors as absenteeism, part-time work, and stoppages. Yield (1) The percentage that is derived from dividing the annual return from any investment by the amount of the investment, for example, a stock’s annual per share dividend payment rate divided by its per share price. (2) In airlines, the average revenue per passenger-mile, obtained by dividing total passenger revenue by the total passenger-miles. (3) In hotels, the yield per room, calculated by dividing room sales by available room-nights instead of occupied room-nights. (4) In cruise ships, similarly, revenues per available berths.

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Index

A Abrams Rate Index, 182 Accelerated depreciation schedules, 193 Accounting issues airline industry, 104, 105, 176 automobile industry, 169 bus industry, 173 casino industry, 257 cruise line industry, 180 gambling industry, 252 hotel industry, 215 for hotel restaurants, 235 railroads, 100 Adjusted enterprise value (AEV), 107, 108 Adjusted FFO (AFFO), 234, 235 Admissions, amusement/theme park, 220, 291– 304 Advertising airline industry, 31, 72, 79, 208 casino industry, 31 hotel industry, 31, 208, 227 industrial structure, 31 intensity ratio, 115 Aeronautical revenues, 76, 120 Age and demand for leisure goods and services, 13 and leisure time, 7 transportation spending by, 15 Agencies, travel, see Travel agencies AIR 21, 127, 137 Air Commerce Act, 60 Aircraft Boeing 247, 61 Boeing 707, 62

Boeing 737, 62 Boeing 747, 63, 123, 193 Boeing Stratoliner, 61 Comet, 62 Concorde, 63 Douglas DC-3, 61 Douglas DC-4, 110 Douglas DC-10, 63 financings, 66, 100, 104, 131–133, 135, 137 fleet size, 85 Junkers F13 monoplane, 60 Lockheed L-1011, 63 Sopwith Camel, 60 speeds, 60–62, 84, 85, 124 wide-bodied, 63, 193 Airline Deregulation Act of 1978, 63 Airline industry accounting issues, 104, 105, 176 advertising, 31, 72, 79, 208 airport management, 76, 77, 105 capacity for carriage, 70 cargo carriage, 68 charters, 67, 74, 75, 92 deregulation, 57 economic characteristics airline-business failures, 81 antitrust, 30, 107, 127 cost control, 79, 81 cross-elasticities, 125 economies of density, 80 fleet selection, 79 geographic location and predominant condition, 81 hub-airport facilities, 80 income elasticity, 87

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 H. L. Vogel, Travel Industry Economics, https://doi.org/10.1007/978-3-030-63351-6

399

400 Airline industry (cont.) internet’s exponential growth, 81 macroeconomic sensitivities, 78–79 monopolistic competitive/oligopolistic, 88, 344 network industries, 81 operating cost per average ton-kilometer, 83 per capita income series, 87 predation, 93 price elasticities, 87, 88 productivity factors, 84 total operating expenses, percentage, 84 traffic flow rates, 89 traffic forecasting, 93–95 transportation modes, 91 transportation, pricing, 90 unit operating costs, 82 effect of prices on hotel industry, 90, 94 elasticities of demand, 78 fractional-ownership carriers, 67 history and milestones, 59 hub-and-spoke networks, 71, 80, 81, 85 labor relations, 67–68 leases, 103–105, 121, 125 major airlines, 66, 70, 84, 101, 106, 137, 138 marginal costs and revenues, 73 marketing advertising and reservation systems, 72–73 frequent-flyer program, 71, 73, 74, 93 primary marketing efforts, 71 travel agencies, 71, 74–75, 93 types, 71 national carriers, 66 oil, price of, 36, 211, 300 operating items, 101–104 operational characteristics, 66–78 overview, 110 passenger revenue per passenger-mile, 69 predation, 92–93 regional carriers, 67 regulations, 93 sale-leasebacks, 104–105 segments, 109 vs. S&P 500 index, 346 structural features, 66–68 taxis, 67, 113 technology in, 58–62, 78, 86, 91, 236 and tourism, viii, 62 traffic forecasting, 93–95 types, 68 valuation of assets, 106 yield, 68–74, 116, 130

Index Airline Pilot’s Association (ALPA), 67 Airline Reporting Corporation (ARC), 119 Airline Tariff Publishing Co. (ATPCO), 72 Airmail, 60–62 Air Mail Act of 1934, 61 Airports commercialization of, 77 GARBs, 76 globalization of, 77 Heathrow Airport, 61, 127 hubs, 76, 77, 80, 122 leases of, 97 managements, 76, 78, 120 privatizations of, 77, 78, 120 public shares in, 107 revenues, 76–78, 120, 121 structural features, 197 traffic, 76, 77, 80, 138 Airport throughput units (APU), 121 Air Safety Board, 62 Air/sea mix, 167, 181 Air Transport Association (ATA), 84, 96, 138, 351 Alberta, Canada, 47, 48, 273 Alliances, airline, 115 Allocentrics, 315 Alternative-opportunity costs, 343 American Airlines, 60, 61, 72, 113, 116, 132, 136 Amortization of debt, 28, 96 Amtrak, 175, 177, 183 Amusement parks attendance vs. unemployment and, 298 economic sensitivities, 297–298 financial operating characteristics, 291–296 history, 290, 291 milestones, 294 oligopoly structure, 26 overview, viii recreational resorts, 296–297 service industry census comparisons, 297 valuation of assets, 298–299 worldwide attendance trends, 298 Andrew, W.P., 229 Anticipation phase, 315 Antitrust, 29, 92, 108, 116, 128, 129 Antitrust policies and laws, 30, 127 APCD, see Available passenger-cruise days (APCD) Arison, T., 162 Asia casino industry in, 252, 271 gambling industry in Macau, 249, 271, 274 rail industry in Japan, 182 tourism agencies in Japan, 312, 327, 333

Index Assessed value, 220 Assets, 10, 78, 178, 193, 259, 301, 345 depreciation, 47, 96, 100, 223 NAV, 108, 223 sales in hotel industry, 215 theme parks, 298, 299 See also Valuation of assets Association of Flight Attendants (AFA), 67 Astro-tourism, 348 Atlantic City, New Jersey history of, 249 vs. Las Vegas, 256 receivables, 280 regulation, 250, 251, 258 revenues, 249, 250, 255, 273, 280 square footage, 251 visitor length of stay, 273 Atlantis hotel-casino, 275 Attendance trends for theme parks, 298 Attraction types, 316 Australia, tourism in, 312, 326, 327 Automobile industry, vii accounting issues, 169 average miles traveled in car, 168, 172 finance issues, 169, 172 history, 168 RPMs of vs. public carriers, 170 travel agent commissions, 180 See also Car rentals Auto rentals Abrams Rate Index, 180 depreciation schedules, 171, 176 fleet purchases, 181 structure of industry, 31 Available lower berth day (ALBD), 166, 181 Available passenger-cruise days (APCD), 166 Available seat-miles (ASM), 65, 70, 83, 127 Average cost (AC), 16, 48, 80, 81, 83, 84, 127, 279 Average daily rate (ADR), 197–201, 233 Avis, 171, 172, 182, 183

B Baccarat, 260, 263, 264, 280 Backward-bending labor-supply curve, 11, 44 Bad-debt allowances, 267 Baggage handling, 74, 85, 93 Bakken, 302 Balance of trade, in tourism, 325–327 Bank financing, 100 Bankruptcy in gambling industry, 275 Barrett, N.S., 44

401 Barriers to entry, 15, 78, 91, 129 Becker, G.S., 4 Bernoulli, D., 270 Berzon, A., 230, 274, 275, 277, 278, 280, 281 Betas, 100 Betbug, 275 Betfair, 275 Betting limits, 261 Betting service companies, 275 Bet-to-buy-in ratio, 279, 280 Beverage sales on cruises, 165 Bifurcated structure of bus industry, 173 Bingo, 251, 255, 257, 262, 269, 273, 274 Binion’s Horseshoe, 276 Blackjack, 260, 262, 263, 265, 276, 280 Blackstone Group, 304 Boeing 247, 61 Boeing 707, 62 Boeing 737, 62 Boeing 747, 63, 123, 193 Boeing Stratoliner, 61 Bonds, 33, 101, 106, 131–133, 212, 213, 233, 236, 238 Booking seasons for cruises, 178 Book value guidelines for evaluating travel-related, 345–346 hospitality real estate, 220 Brand name airline marketing, 106, 210 hotel industry, 209, 228 loyalty, 73, 117 Breakeven point, 295 Britain, airline industry development in, 61 British Airways, 61, 106, 111, 115, 117, 120, 128, 135 Broadcast of gaming ads, 276 Bryan v. Itasca County, Minnesota (1976), 274 Budgets, 3, 10, 17, 24, 36, 91 Build, operate, and transfer (BOT) deals, 78 Bull, A.O., 182 Bureau of Labor Statistics, 9, 11, 25, 41, 43 Bus industry accounting issues, 173 overview, 173 profitability, 173 regulations, 174 revenue passenger miles, 170, 173, 174 segments, 27, 29 structure of industry, 26, 27, 29 Business travel airlines, 125 demand for, 22, 125

402 Business travel (cont.) elasticities, 87, 88, 125 price elasticities, 125 Bus Regulatory Reform Act, 175 Button, K.J., 48, 130

C Caesars Palace, 267 Cage, in casinos, 268 California v. Cabazon Band of Mission Indians (1987), 41, 121, 171, 274 Camping resorts, 296, 302 Canada casino gaming, 274 charity games in, 273 CTC, 333 Canadian Tourism Commission (CTC), 333 Capacity airline, 67, 70–72, 85, 111 dumping, 93 Capital investment, 39, 58, 77, 109, 126, 299, 301, 304, 343 Capitalization rates, 222–225 Capital lease, 47, 103, 104, 134, 135 Carbon-taxes, 137 Card games, see Games of chance Cargo carriage in airline industry, 66, 68 Carnival Cruise Lines, 162, 163 Carnival Destiny (ship), 33, 161, 162, 165–167 Car rentals Abrams Rate Index, 180 advertising, 31 brand competitors, 169 depreciation schedules, 176 fleet purchases, 181 marketing, 171, 172 price-discrimination, 172 structure of industry, 26 travel agent commissions, 180 Carrying value, 220 Cash available for distribution (CAD), 234 Cash flows casino, 276 discounted, 32–33, 104, 106, 224 EBITDA, 33, 346 to equity, 353 free, 47, 103, 344 guidelines for evaluating travel-related, 343–345 theme parks, 33 volatility, 345 weak growth, 29

Index Casino gambling ads, 276 Casino industry, 259, 276, 347 accounting policies, 263–267 advertising, 31, 38, 263 in Asia, 250 baccarat, 258, 261, 262, 278 blackjack, 258, 260, 261, 263, 274, 278 in Canada, 250, 274 cash and credit, 264–265, 329 certifying customer’s financial credibility, 265 classification of, 275 craps, 244, 258, 260, 261, 277, 278 on cruise ships, ix, 34, 38, 341 duration of playing time, 259 expected utility and, 268 financial performance, 257–258 funding functions, 254–255 gambling and economics, 267–270 game performances, 262 gaming square footage, 249 history, 243–252 illegal activities in, 257 on Indian reservations, 245, 249 macroeconomic matters, 253–254 management policies, 263–267 marketing matters, 263–264 milestones, 251 in Nevada, 246–248, 255, 256, 261, 262, 265, 271, 273, 276, 278 in New Jersey, 247, 256, 277 performance standards, 260–262 procedural paradigms, 266–267 profit principles and terminology, 258–262 psychology, 267, 270 regulation, 15, 246, 248, 249, 256–257 revenues, 259 on riverboats, 244, 249, 263, 272, 273, 278 slots, 245, 261–263, 265, 269, 271, 274, 275 vs. S&P 500 index, 344 structural category, 26 in U.S., 250 valuation of assets, 257, 258 win rate, 260–262, 276 See also Atlantic City, New Jersey; Las Vegas, Nevada C corps, 213 Cedar Fair, 293, 302, 304 Central Credit Inc., 267 Certificates for major airlines, 66, 101 Chance, games of, see Games of chance Charity games, 275

Index Charter airlines, 67, 74, 75, 92 Circus Circus casino, 267 City pairing, 71 Civil Aeronautics Act of 1938, 61 Civil Aeronautics Authority (CAA), 61, 62 Civil Aeronautics Board (CAB), 62, 63, 74, 115 Civil Air Transport Subsidies Committee, 60 Clubs destination, 230 health, 224 poker, 250 Code-sharing, 71, 115, 122 Collateralized mortgage-backed securities (CMBS), 212, 214 Collateral trust bonds, 212 Comet, 62 Commercialization of airports, 77 Commissions, travel-agent, 119 Comparative advantage theory, 325 Comparative index, 194 Comparison methods, valuation variables, 33, 34 Competition management companies, 203 monopolistic, 26, 137 perfect, 26, 46, 128 Competitive-monopolistic model, 16 Comps, 264, 266, 267, 272, 278–280 Concession purchases, 78 Concorde, 63 Condominium hotel units, 230 Coney Island, New York, 292 Constant returns to scale, 86, 344 Construction, hotel, 193, 231 Consumer credit/debt, 14, 297, 298 Consumer price indexes (CPI), 25 Consumer price index for all urban consumers (CPI-U), 25, 30, 46 Consumer surplus, 18 Continental Trailways, 175 Contingent valuation methods (CVMs), 332 Contract Air Mail Act (1925), 60, 175 Contracts, management, 77, 78, 202, 203, 212 Copenhagen’s Bakken, 291 Corporate Gaming Act, 248 Costs, 3, 63, 165, 198, 256, 295, 311, 343 alternative-opportunity, 3, 341 approach, 91, 102, 128 average, 80, 81, 84, 85, 90, 91 categories, airline industry, 101 direct operating, 83, 102, 133 economies of scale, 26, 80, 109, 225, 342 of food on cruise ships, 176

403 hotel industry, 202 per passenger-mile, 80, 84, 90 prime, 208, 334 sunk, 17, 26, 109, 170, 200, 201, 343 in theme parks, 20, 298 of tourism, 315, 316 weighted average cost of capital (WACC), 33, 100, 104, 107, 224 See also Marginal cost Country-club business model, 231 Cramer, G., 270 Craps, 246, 260, 262, 263, 279, 280 Credit cards, use in slot machines, 262, 266, 279 Credit, in casino industry, 260, 264–265, 270, 272, 279 Credit slips, 262, 268, 278, 280, 281 Cross elasticity of demand, 125, 210 Cruise line industry accounting issues, 180 air/sea mix, 165, 179 booking seasons, 178 economic aspects, 166–168 economic sensitivities, 166–167 finance issues, 106, 176, 180 history, 177 marketing, 159, 161, 162, 165, 168 operational aspects, 164–166 origin-destination matrix, 161 passengers and berths, 160 price discrimination strategies, 168 profit and loss statement, 166, 167 sunk costs, 168, 341 yield, 165, 166, 179 Cruise ships foreign-flag, 164 size of, 166, 179 space ratio, 165 Cultural dimension of tourism, 319 Customers, profit provided by, 206

D Debt airline industry, 64 capital markets, 100 and demand for leisure goods and services, 13 equity ratios, 347 Debt-service-coverage (DSCR) ratios, 235 Debt-to-revenue ratio, 98 Deferred revenue approach, 105 De Grazia, S., 41

404 Demand, 4, 62, 162, 189, 250, 298 307, 342 airline industry, 109 barriers to entry, 15 cross elasticity of, 125, 210 demographics and debts, 13–15 expected utility, 12 hotel industry, 215 for leisure time, 9 productivity, 85 rail industry, 88, 95, 125, 174 for tourism, 7, 13, 332 See also Elasticities of demand Demographics, and leisure activities demand, 13, 14, 39, 44, 95, 207 Density, economies of, 80 Departmental data, for hotels, 201 Department of Tourism, 333 Department of Transportation (DOT) certificate, 66 Dependency ratio, 14, 44 Depreciation method cash flow, 28, 96 equipment, 95 hotel industry, 202, 223, 227, 230 Deregulation of airline industry, 30, 63–65, 74, 193 Destination clubs, 230 cruises, 161, 164 O-D market, 69, 113 Detroit, Michigan, 273 Direct effects of tourism, 322 Discounted cash flows, 32–34, 104, 106 Discount factors, 222, 223 Discount rates cruise line industry, 164 hotel industry, 220, 225 Discrimination, price, see Price discrimination Disneyland, 292, 294, 295, 301, 302 Disney, W., 292, 302 Disney World, 292, 294, 301, 316 Distance-decay function, 8, 12 Dollar Car Rental, 169 Douglas DC-3, 61 Douglas DC-4, 110 Douglas DC-10, 63 Drifters, 315 Drop, 36, 198, 262–264, 268, 278–280, 354 Drop boxes, 268 Dynamic fleet management, 70, 114

Index E Eadington, W.R., 270 Earnings before interest, taxes, depreciation, and amortization (EBITDA), 28, 33, 47, 97–99, 107 Economic growth, 14, 100, 120, 123, 215, 277, 316, 346 Economics advertising, 16, 26, 31, 38, 168 airline industry, 131, 172 amusement/theme parks and resorts, 289–302 gambling and, 272 hotel industry, 237 industry segments, 344 oil, 24, 35–37, 47, 48, 210 overview, 309 personal consumption expenditures, 7, 22–24, 27, 31, 344 primary principles, 15–21, 72 promotion, 17, 31, 39, 168, 320 structures, 26–31, 66, 212, 214 supply and demand factors, 9–15, 25 time concepts, 3–9 tourism, 35, 309, 318, 348 Economies of density, 80 Economies of scale, 15, 26, 66, 80, 110, 139, 225, 270, 344 Economy effect of demand for air transport on, 79 effect on airline industry, 131, 172 effect on theme park attendance, 20, 21, 298 recessions, and airline industry, 24, 27, 63, 97, 98, 168 Ecotourism, 315, 316, 323, 331, 334, 352 Elasticities of demand airline industry, 72 cross-elasticities, 17, 86, 125, 210, 269 income, 330 overview, viii, 48, 307 price, 88, 210, 331, 333 Enhanced equipment trust certificate (E-ETC), 101, 131 Enterprise, 33, 77, 107, 121, 171, 172 Enterprise value (EV) gambling industry, 269–272 per berth, 180 Entertainment, gambling as, 269 Entertainment services, 45, 265, 293 Entropy models, 95 Equipment depreciation schedules, 178 Equipment financing, 133

Index Equipment trust certificate (ETC), 101, 178 Equity airline industry, 68, 347 cash flows to, 29, 33, 96, 100, 176, 202, 345 hotels, 202, 204, 212, 213, 222, 347 REITs, 212, 213, 234 structures, 68, 131, 212–214, 234 Europe major theme parks in, 290, 292, 296 pleasure gardens, 289 Expected utility, 12, 39, 270, 321 Expedia, 74, 115–117, 206, 211, 212, 232, 233, 236, 237 Expenditures, personal-consumption, see Personal-consumption expenditures Experience phase, 315 Explorers, 314, 315 Export credit agency (ECA), 100, 133, 137 Export industry, tourism as, 318, 326 Externalities, 34, 44, 257, 319, 325, 332, 334

F Fair Labor Standards Act in 1938, 41 Fairs, 93, 104, 134, 135, 248, 291, 302, 303, 310 Federal Aviation Act, 63, 66 Federal Aviation Administration (FAA), 60, 63, 66, 112, 122 Federal Bureau of Investigation (FBI), 258 Federal Communications Commission (FCC), 257 Fees franchise agreements for hotels, 205 at tracks, 258, 260 Fee simple estate, 205 Fee simple title, 220 Fill slips, 268, 280, 281 Finance leases, 103, 104, 135 Financial Accounting Standards Board (FASB) statement 13, 103 Financial characteristics airline industry, 96 amusement/theme parks and resort, 291–296 casino industry, 259 Financing airline industry, 105 cruise line industry, 162 hotel industry, 215 nonrecourse bullet-loan, 227 railroads, 100 Fitness certificate, 66, 67

405 Flag-of-convenience, 179 Flamingo Hotel, 272 Fleet airline industry, 79 car rentals, 173, 174, 183 Flight scheduling, 72, 79 Forecasting, traffic, 93 Foreign-flag ships, 166 Four Seasons, 209, 210, 229, 230 Fractional-jet ownership programs, 67, 112 Franchises hotels, 214 rental cars, 171 Francis, N., 7 Free cash flow (FCF), 47, 103, 346 Free market, 247, 345 Free time, 6, 10, 14, 41, 42, 248, 343 Freight carriage, in airline industry, 62, 68, 69, 76, 177 Freight carriers, in rail industry, 101 Frequency share vs. market share, 92 Frequent-flyer programs, 71, 73, 74, 80, 93, 105, 110, 210 Fuel prices, 83, 96, 98, 123, 126, 216, 295, 300 Full pay-out lease, 135 Funds from operations (FFO), 178, 213, 234, 235 Furniture, fixtures, and equipment (FF&E) reserve, 204

G Gambling industry, 268 in Asia, 250, 252, 274 baccarat, 264 blackjack, 265 category, 210 craps, 244 expected utility and, 12, 268 funding functions, 255 gambling and economics, 267–270 gaming square footage in casinos, 249 history, 243, 244, 246–250, 252, 268, 270, 273 illegal activities in, 259 on Indian reservations, 249 internet gaming, 275 macroeconomic matters, 253 marketing matters, 210 in Nevada, 246, 248, 268, 269, 274, 275 in New Jersey, 269 profit principles and terminology, 258, 259, 262

406 Gambling industry (cont.) psychology, 267, 270, 279 regulation, 255, 269, 275 revenues, 275 on riverboats, 244 slots, 244, 262, 269, 275 valuation of assets, 32 See also Atlantic City, New Jersey; Las Vegas, Nevada Gambling Times, 261 Games of chance baccarat, 258, 261 blackjack, 258, 261 craps, 258, 261 slot machines, 252, 263, 274 win rate, 264 Game theory, 122, 270 Gaming, see Gaming industry Gaming commission, 258 Gaming control board, 258, 263, 266, 269 General airport revenue bonds (GARB), 76 Generally accepted accounting principles (GAAP), 103, 104, 135, 136, 214, 235, 236 Gerson, K., 7 Giffen goods, 45 Gini coefficient, 46 Globalization of airports, 77 Golf resorts, 304 Goodwill amortization, 236 Government regulation airline industry, 15, 61 as barriers to entry, 15 bus industry, 174 casino industry, 258 gambling industry, 268 Government, role in tourism, 254, 327, 329 Graham, A., 121 Gravity model, 95, 321 Greyhound, 175 Gross domestic product, U.S. (GDP) deflator series, 25, 46 vs. hotel occupancy rates, 201, 216 vs. revenue passenger-kilometers, 114 vs. tourism and airline industry, 22 travel and tourism expenditures as percentage, 318 Gross national product (GNP), 45, 215 Gross operating profit per available room (GoPAR), 198 Gross registered tons (GRT), 167, 181 Group inclusive tour (GIT) packages, 317

Index H Hambling committee, 60 Handle, 62, 63, 119, 127, 169, 209 Harrah’s, 265, 277, 279 Heathrow Airport, 61, 127 Heckscher-Ohlin theorem, 325 Hepburn Act of 1906, 176 Herfindahl-Hirschman Index (HHI), 26, 46 Hertz, 171–173, 178, 182, 183 High rollers, 265, 267, 280 Highway improvements, 171 Hilton, C., 192, 203 History airline industry, 57 amusement/theme parks and resorts., 290, 291 casino industry, 245 cruise line industry, 177 hotel industry, 278 Hold, 41, 66, 101, 103, 111, 174 Hold percentage (hold p.c.), 278, 280 Holiday Inn, 193, 233 Holiday time, 41 Hotel industry accounting issues, 214–215 advertising, 31, 38, 204, 205, 208, 210 asset sales, 215 brand name, 203, 208–210, 224, 228, 233, 236 condos, 205, 206, 229–231 departmental data, 201 economic sensitivities, 215–219 equity, 201, 202, 204–206, 212–214, 221, 222, 224, 234, 345 establishments, receipts, and payrolls, 220 expected utility and, 12 financing frameworks, 212–214 franchising, 196 history of, 189, 190 loans, 193, 194, 206, 213, 214, 222, 224, 225, 227, 235 management contracts, 202, 203, 212 marketing, 204, 205, 208–212, 229, 231 milestones, 194, 195 mortgages, 204, 206, 212–214, 222, 224, 229, 230, 233 n/e ratio, 217, 236 non-REIT, 213 operating features, 197–208 overview, 23, 202, 219 REITs, 212–214, 234, 235 REMICs, 212, 214

Index reservation systems, 193, 203, 208–210, 212, 219, 225 restaurants in, vii, 12, 27, 31, 34, 38 vs. S&P 500 index, 346 structure of, 201–203, 205, 210, 212, 230, 233, 234 time-shares, 67, 205, 206, 213, 230, 231 valuation of assets, 215 worldwide chain-related hotel rooms and properties, 196 Hotel industry leading indicator (HIL), 236 Hub-and-spoke networks, 85 Hubbart Room Rate Formula, 228 Hubbert, M.K., 47 Hupmobile, 174

I Illegal gambling, 255 Imperial Airways Limited, 60 Incentive fees, 204, 229, 230 Inclusive tours, 74, 317 Income and air travel, 87, 190, 216, 353 and demand for leisure time, 10, 11, 43 elasticity, 11, 17, 18, 44, 45, 78 and travel, 24, 297 Income before fixed charges and management fees (IBFCMF), 204, 229 Income capitalization approach, 220 Income effect, 11, 45 Income-time paradox, 7 Incremental capital to output ratio (ICOR), 334 Incremental cost method, 105, 118 Indian Gaming Regulatory Act (IGRA), 251, 274 Indian reservation gaming, 245 Indirect effects of tourism, 322 Indirect operating cost (IOC), 83 Individual mass tourists, 315 Industry structures, see Structures, industry Inns, 191–196, 207, 210, 291 Input-output analysis, 327–328 Insurable value, 220 Internally generated cash, 100 Internal revenue service (IRS) Section 168, 176 Sections 883 and 884 of Code, 178 International accounting standards for leases, 104 statement 17, 104 International Air Transport Association (IATA), 57, 64, 79, 83, 92, 102

407 International Association of Machinists (IAM), 67 International Civil Aviation Organization, 68 International landing agreements, 64 International tourism receipts for top ten countries, 308, 326 spending on, 326 trends of receipts, 313 Internet gaming, 250 hotel bookings, 211 Interstate Wire Act of 1956, 281 law of connectivit, 81, 122 virtual tourism, 317 Internet Gambling Enforcement Act of 2006, 281 Internet gaming, 250 Interstate Commerce Act, 176 Interstate Commerce Commission (ICC), 175–177, 183 Interstate Highway Act of 1956, 192 Interstate highway system, 171, 192 Interstate Wire Act of 1956, 250 Inverse elasticity pricing rule, 17 Investments in travel, 346 Investment tax credit, 227 IRS, see Internal Revenue Service (IRS)

J Jacobs, J.A., 7 Japan rail industry, 177 tourism agencies, 74 Japan Airlines (JAL), 62, 110, 115 Japan National Tourist Organization, 333 JetBlue, 66, 67, 70, 112, 115, 127, 128, 132, 138 Jets, development of, 62 Johnson’s model, 231 Jones Act, 179 Junkers F13 monoplane, 60 Junkets, 264, 265, 273, 278, 279, 311

K Kelly Act, 60 Keynesian multiplier model, 324 Kitty Hawk, 57, 58, 62 Klein, R.A., 182

L Labor cost percentage, 67, 202 Labor intensity, 299, 343

408 Labor issues airline industry, 68, 172 cruise line industry, 168 hotel industry, 197, 202, 237 Landing agreements, 64 Las Vegas, Nevada vs. Atlantic City, 256 gaming square footage in casinos, 251 history of, 248, 273 revenues, 249, 250, 269, 273, 276, 277 visitor length of stay, 273 Laverty, M., 331 Law of Connectivity, 81, 122, 209 Leasebacks, 104 Leases operating, 103 tax, 132 Legalization of gambling in New Jersey, 245, 247 politics of, 255 in Singapore, 251 Legalization of gaming, in Nevada, 248 Leisure goods and services apportionment among activities, 7 demographics and, 13 expected utility comparisons, 12 PCEs, 7 technological development, 9, 39, 341 Leisure paradox, 10 Leisure time, 3, 4, 7, 9, 11, 39 age and, 7 availability of, 4 debt and, 43 demand for, 9, 10 expansion of, 4 income and, 11 productivity, 9, 39, 43, 343 and tourist travel, 315 Veblen’s view, 7 Leontief, W., 335 Leverage ratio, 97–99, 235 Licensing in gambling industry, 258 Limited partnerships, 213, 214, 234 Limits, betting, 261 Lindbergh, C., 61 Liquidation value, 220, 223 Load factors (LF), 70, 74, 80, 97, 102, 114, 117, 124, 174, 180 Loans hotels, 214, 225 long-term, 132 short-to-intermediate, 214 Loan-to-value (LTV) ratios, 235

Index Location-based entertainment (LBE), 292, 298, 303 Lockheed L-1011, 63 Lodging industry accounting issues, 214 brand name, 210 condos, 205–207, 229 departmental data, 201 economic sensitivities, 216, 217, 219 equity, 33 establishments, receipts, and payrolls, 207 expected utility and, 39 franchising, 190 marketing, 193 milestones, 195 mortgages, 212 n/e ratio, 236 operating features, 197, 198, 201, 203, 206, 207 REITs, 213–214 REMICs, 214 reservation systems, 193, 210 restaurants in, 76, 297 vs. S&P 500 index, 344 time-shares, 205–207, 297 valuation of assets, 32 worldwide chain-related hotel rooms and properties, 196 Long-run average cost (LAC) curve, 89 Long-term loans, 235 Long, thin routes, 81, 123 Loss rebates, 279 Lotteries, 245, 246, 252, 255, 257, 258 Low-cost carriers (LCCs), 93, 131, 138 Lowenstein, R., 138 Loyalty programs, hotel, 228, 233 Lufthansa, 60, 81, 106, 115, 117, 138 Luna Park, 302

M Macau, gambling industry in, 276 Macroeconomics airline industry, 172 casino industry, 255 Major airlines, 66, 70, 84, 101, 106, 138 Managed competition model for casinos, 245 Management airport, 76–78, 81, 92, 106, 120 contracts, 77, 78, 106, 117, 202–204, 212, 225 hotels, 168, 193, 199, 200, 203, 204 Management company, 106, 203, 225, 233

Index Mann-Elkins Act in 1910, 176 Mardi Gras (ship), 162, 165 Marginal cost (MC) airline industry, 73 elasticity of demand and, 46 Marginal revenue (MR) airline industry, 89 Marginal utility (MU), 44, 270, 333 Margins profit margin, 34, 71, 164, 166, 202, 208, 345, 361, 363, 364 Markers, 262, 278 Market-efficiency theory, 269 Marketing airline industry advertising and reservation systems, 72, 73 frequent-flyer program, 71, 73, 74, 79, 106, 210 primary marketing efforts, 71 travel agencies, 31, 71, 74, 75, 116, 211, 232, 237, 358 types, 68 casino industry, 257 cruise line industry, 160, 161, 177, 178 hotel industry, 164 Market share, 26, 46, 92, 107, 109, 114 Marriott Corporation, 302 MC, see Marginal cost (MC) McClanahan v. Arizona Tax Commission (1973), 4, 41, 43, 274 McGrattan, E.R., 5, 6 McIntosh, R.W., 314, 315 Memory phase, 315 Meyer, J.R., 121, 171, 183 MGM Mirage, 45, 277 Microeconomics airline industry, 79–93, 95, 109, 201 competitive-monopolistic model, 26 marginal costs and revenues, 16 sunk costs, 109 Milestones airline industry, 59 amusement parks, 294 casino industry, 251 gambling industry, 253 lodging industry, 195 theme parks, 294 Modified Accelerated Cost Recovery System (MACRS), 131 Monopolistic competition, 26, 89 Monopoly model for casinos, 245 Moore, J., 121, 261 Morrell, P.S., 101, 118, 132, 135

409 Morrow Board, 60 Mortgage bonds, 212, 233 Mortgage REIT, 213 Mortgages, hotel, 204, 229 Motels, 22, 26, 27, 170, 192, 196 Motor Carrier Act in 1935, 175 Multipliers, 43, 79, 120, 221, 223, 257

N National carriers, 66 National Income Accounting, 45 National Income and Product Account (NIPA), 9, 22, 43 National Indian Gaming Commission (NIGC), 274 National Rail Passenger Corporation (Amtrak), 177 National Tourism Policy Act, 333 National Trailways System, 175 Natural monopoly, 26, 93 Needs vs. wants, income elasticity estimates for, 19 n/e ratio, 217, 236 Net asset value (NAV), 108, 223 Net present value (NPV), 33, 98, 104, 353, 354 Net revenue yield (NRY), 167 Neurosis, gambling as, 269 Nevada, casino industry in, 249, 258 See also Las Vegas, Nevada Nevada Gaming Commission Regulations, 280 Nevada Gaming Control Board regulations, 278 New Jersey, casino industry in, 247 See also Atlantic City, New Jersey Non-aeronautical revenues, 76, 120 Nonqualified subsidiaries, 214 Nonrecourse bullet-loan financing, 227 Non-REIT hotel, 213 Non-risk cars, 178 Nonscheduled airline operators, 67 North American Industry Classification System (NAICS), 75, 217, 220, 299 North Dakota, 275 Norwegian Cruise Lines, 162, 179 Nuevo Dominicano (ship), 162

O Oasis of the Seas (ship), 165 Occupancy index, 199 Occupancy rates cruise line industry, 201 hotel industry, 216 vs. percent change in GDP, 216

410 Oil prices and production effect on airline profits, 63 Oil production and consumption, 37 Okubo, S., 45, 328, 335 Oligopoly, 26, 66, 89, 130, 171, 247, 344 Oneidas, 273 Online gaming, 272 Online travel agencies (OTAs), 116, 117, 119, 211, 232, 237 Open registries countries, 177 Operating certificate, 66 Operating costs airline industry, 64, 68 direct, 81, 133 indirect, 83 resort, 298 theme parks, 300 Operating income before depreciation and amortization (OIBDA), 28, 47 Operating income, hotel industry, 46 Operating lease, 98, 100, 103, 104, 132, 134, 135 Operating leverage, theme park, 297 Operating performance airline industry, 101 cruise line industry, 166 Operating ratio, 97, 98, 201, 202 Options, valuation variables, 34 Organization of Petroleum Exporting (OPEC), 63, 110 Organized crime, 248, 258 Organized mass tourists, 315 Origin to destination (O-D) market, 69 Orthodox multiplier model, 324 Oster, C.V. Jr., 171, 183 Outward journey phase, 315 Own price elasticity of demand, 210 Own price of service, in regression forecasting, 94

P Paired-share REIT, 234 Partial interest title, 220 Partnerships, 47, 227, 234, 235, 254, 333 Passenger-cruise days (PCD), 166 Passenger-miles (kilometers), 24, 58, 65, 68, 80, 85, 171, 175, 176, 215 Passenger revenue per available seat-mile (PRASM), 69 Passenger Shipping Act of 1896, 179 Passenger space ratio (PSR), 167, 181 Passenger trains

Index accounting issues, 99, 174 finance issues, 99 overview, 174 Pay less than true odds principle, 258 Peninsula and Oriental Steam Navigation Co., 161 Perfect competition, 26, 46, 129 Performance standards, casino industry, 260–262 Performance, travel industry common elements, 343, 344 guidelines for evaluating travel-related, 27, 36, 348 overview, 39 public policy issues, 344, 345 Perishability of product, 200 Personal-consumption expenditures (PCEs) for air travel, 7, 27 for bus travel, 7, 27 for leisure activities, 7 overview, 22–24 real per capita spending, 23 transportation services, 7, 22, 23 trends in selected categories, 22, 23 by type of product/service, 22 Petzinger, T. Jr., 109, 138 Planting, M.A., 45, 328, 335 Pleasure gardens, 291 Point-to-point services, 124 Poker clubs, 252 Policy, travel industry common elements, 343, 344 guidelines for evaluating travel-related, 27, 348 overview, 335 public policy issues, 344, 345 Pooling-of-interests accounting, 235 Population social effects of tourism, 325 Power laws, 20, 21, 45 Predation, in airline industry, 92–93 Price discrimination application of, 319 cruise line industry, 168 hotel industry, 18 overview, 18–20 tourism industry, 318 Price/earnings (P/E) ratios, 345 Price effects, 25, 126 Price elasticities airline industry, 210 tourism industry, 87 Price inflation indexes, 26

Index Price/pricing airline industry, 18, 88, 319 car rentals, 173, 174, 300 changes in, effect on profitability, 88, 115, 167, 169, 344 discrimination, 18, 20, 69, 71, 88, 112 hotel industry, 30 inverse elasticity pricing rule, 17 of oil, 36, 110, 211, 300 Ramsey, 17, 126 rental cars, 180 subsidy-free, 91 Prices of substitutes, in regression forecasting, 94 Price-to-sales ratios, 32, 347 Prime costs, 208 Private market values, 107, 108, 238, 260, 346 Privatizations of airports, 77, 120 Procedural paradigms, casino industry, 268 Productivity airline industry, 35, 84 and leisure time availability, 9, 35 Profitability airline industry, 84, 88, 97, 114, 116, 130, 131 bus industry, 341 casino industry, 259, 272 effect of price changes on, 165, 167, 342 gambling industry, 259 hotel industry, 88 rental cars, 172 theme parks, 88 time-share operations, 204, 297 Profit and loss statement, cruise line industry, 168 Project finance privatizations, 78 Promotion airline industry, 31, 342 casino industry policies, 31, 342 cruise line industry hotel industry, 31, 342 industrial structure, 31 intensity ratio, 72, 115 Psychocentrics, 315 Psychological propensities, classification of tourists by, 314 Psychological roots of gambling, 267 Public goods characteristics, 20, 319 overview, 20 Public-opinion surveys, 4 Public shares, airports, 77

411 Q Quaker City (ship), 161 Quality of life considerations, 323 Queen Mary 2 (ship), 165, 179

R Radio, casino gambling ads, 276 Rail industry, 107, 174 accounting issues, 176 Europe, 182 finance issues, 176 revenue per passenger-mile, 170, 175 RPMs of vs. public carriers, 170 Railway Labor Act of 1926, 67 Ramey, V.A., 7 Ramsey pricing, 126 Rate of return on invested capital (ROIC), 47, 100, 167 Real estate assets, 106, 347 Real estate investment trusts (REIT) hotels, 213, 235 paired-share, 234 UPREIT, 234 Real estate mortgage investment conduits (REMICs), 212, 214 Recessionary economic cycles airline industry, 78 gambling industry, 78 hotel industry, 196 investments in travel, 78 theme park attendance, 293, 294 Recreational goods and services PCEs, 22, 23 real per capita spending, 23 Recreational resorts, 298–299 Regional carriers, 66 Regional expositions, 303 Regression forecasting, 94 Regulation airline industry, 93 as barriers to entry, 15 basic concerns, 64, 187, 329, 343 bus industry, 174 casino industry, 246, 256–257, 326 gambling industry, 275 REIT Modernization Act of 1999, 213, 235 Rentals, car, see Car rentals Reservation systems airline industry, 72, 193 hotels, 115, 193, 209, 212, 225 Resorts economic sensitivities, 297–298

412 Resorts (cont.) financial operating characteristics, 291–296 history, 291 in modern times, 290–291 overview, 231 recreational, 296–297 valuation of assets, 298–299 Restaurants advertising, 31 in hotels, 217 turnover, 232 Return journey phase, 315 Returns to scale, 85, 342 Revenue passenger-kilometers (RPK), 58, 114 Revenue passenger-miles (RPM), 68, 124, 172, 175, 176 Revenue ratio, 98, 99 Revenues advertising intensity ratio, 72 Amtrak, 183 cruise line industry, 165, 166 frequent-flyer program, 79, 93, 105 gambling industry, 165 hotel industry, 20, 207 hotel restaurants, 204 Nevada gaming, 264 theme parks, 88, 292, 344 Revenues per available room (RevPAR), 181, 198, 204, 215, 216, 219, 228 Ricardo, D., 325 Riverboats, gambling industry on, 246, 251 Road improvements, 171 Roberts, K., 7, 42 Robinson, J.P., 6, 42 Rogerson, R., 5, 6 Rones, P.L., 7, 42 Room-nights, 117, 198, 199, 201, 211, 216, 233, 237 Round-robin flights, 71 Royal Caribbean, 44, 162–168, 179, 180 Rupert, P., 7, 42

S SABRE reservation system, 72 Sale-leasebacks, 104 Satisfaction, see Utility Schafer, A., 24, 46 Scheduling, flight, 72, 79 Schmidgall, R.S., 229, 232 Schor, J.B., 41 Schwartz, D.G., 281 S-curve effect, 114

Index Seasonal variations recreational resorts, 296–297 theme parks, 303 tourism industry, 318 Section 883, IRS code, 180 Section 884, IRS code, 180 Securities CMBS, 229 travel industry investment guidelines, 345 Securities and Exchange Commission (SEC), 99, 136, 164, 180 Securitization, 101, 132, 206, 212, 233 September 11, 2001 terrorist attacks, 178, 274 Sharp, C.H., 3 Ships, see Cruise ships Short-to-intermediate loans, 214 Shy, O., 122 Siegel, Benjamin “Bugsy”, 248 Sinclair, M.T., 334 Singapore, legalization of gambling, 254 Single European Sky, 127 Six Flags, 293–295, 302, 304 Ski resorts, 299, 303 Skolnick, J.H., 248 Slot machines, 246, 249, 251, 252, 254, 258 Smith, S.J., 41 Social effects of tourism, 325 Sociedade de Turismo, 254 Sopwith Camel, 60 Southwest, 66, 67, 70, 113, 126, 132, 138, 139 S&P 500 index, 346 Space ratio, 167 Special-purpose entities (SPE), 105 Spectator sports, 8 Speed of aircraft, 84 Spoils conference, 61 Sports, betting on, 261, 275 Square footage of casinos, 249 SRI International, 331 Stabilized income assumption method, 224 Stabler, M., 333, 334 Stage length, 82, 83, 85, 117, 124, 131 Standard Industrial Classification (SIC) system, 327 State fairs, 303 Steeplechase Park at Coney Island, 302 Stiff sheets, 268 St. Petersburg paradox, 270 Strikes, airline industry, 67 Structures, industry airline industry, 57–59, 92, 93, 105 hotel industry, 21, 67, 164, 181, 196, 197 Subsidies

Index airline industry, 344 cruise line industry, 106 rail industry, 61, 93 Subsidy-free pricing, 91 Substitution effects, 11, 43, 45 Sunk costs cruise line industry, 162 hotel industry, 201 in travel and tourism, 17 Supply and demand barriers to entry, 15 demand for leisure, 10–11 demographics and debts, 13–15 expected utility, 12 productivity, 9–10 schedules, 10

T Table games, 247, 249, 254, 262, 263, 265 Taft Broadcasting Company, 302 Tariff guidelines for international routes, 92 Taxes cruise line industry, 106, 164 gambling industry, 248 hotel industry, 193 Taxis, airline, 67 Tax leases, 100 Tax Reform Act of 1986, 193, 213, 227 Technological development in airline industry, 61 automobile industry, 168 gambling industry, 265 hotel industry, 217 hotel restaurants, 198, 217 investment in travel, 39 and PCEs, 7 Television, casino gambling ads, 276 Tennis resorts, 304 Terrorist attacks, 62, 96, 98, 180, 276 Theme parks advertising, 31 attendance vs. unemployment and, 293 economic sensitivities, 297–298 estimated attendance, 291 financial operating characteristics, 291–296 histories, 293 in modern times, 290–291 milestones, 294 operating leverage, 299 overview, 289–302 profit as function of attendance, 298 recreational resorts, 296–297

413 revenues, 292 service industry census comparisons, 297 valuation of assets, 298–299 worldwide attendance trends, 298 worldwide facilities, 298 Thrifty, 171, 172, 182, 183 Ticketing, 73–75, 83, 85, 101, 102 Time, 3, 161, 191, 246, 292, 309, 343 and air travel, 318 availability of, 14 as commodity, 3, 4 economic value of, 3 (see also Leisure time) Time-shares, 67, 205, 212, 230, 231, 297 Titanic (movie), 170 Titanic (ship), 162, 170 Ton-kilometers, 68, 70, 71, 124 Ton-miles, 68 Tourism vs. airline industry and GDP, 350 astro-tourism, 346 attraction types, 316–317 balance of trade, 325, 330 costs, 7, 74, 120, 228, 311, 314 demand for, 7, 13, 36, 309, 318, 320, 328, 332 direct dependence of, 36 distance-decay function, 7 economic features, 319 ecotourism, 315, 316, 323, 331, 334, 350 estimated income multipliers for selected countries, 324 inclusive tours, 74, 317–318 input-output analysis, 327–328 international spending on, 20, 22, 325, 326 leisure time for, 307 multipliers, 119, 322–324, 330, 333 overview, 110, 335 production account, 328 promotion of, 310 receipts for top ten countries, 308, 326 top international destinations, ix, 13, 39, 307, 312–314, 318–319, 325, 326, 328 tourist types, 314, 331 trends of international tourism receipts, 313 virtual, 317, 332 Tourists age considerations, 87, 314 definition of, 329, 330 estimated income multipliers for selected countries, 330 types of, 323 Tracks, 37, 69, 72, 100, 119, 174

414 Trade balances, 325, 326 Trade-sales, 77 Traffic, airport, 21, 61 Traffic forecasting, 93 Trains, see Rail industry Trans-Canada Air, 61 Transfer price comparison approach, 221 Transportation Act of 1958, 177 Transportation services PCEs, 22, 23 public spending on, 14, 15, 22, 169, 171, 299, 311 real per capita spending, 23, 94 spending, by age, 15 Travel agencies advertising, 31, 71, 211, 358 airline industry, 345 car rental commissions, 26, 28, 31, 73, 180, 317 cruise line industry, 15, 28, 167 Travel industry barriers to entry into, 15, 91 challenge for, 36 common elements, 341–342 direct dependence of, 36 expected utility, 39 guidelines for evaluating travel-related securities, 343–346 income and, 24 overview, 39 PCEs, 27 power laws, 20–21, 45 primary principles, 15–21 as public goods, 20, 44, 316, 319, 332 public policy issues, 342–343 reasons for travel, 195 structural categories, 26 structures, 344 supply and demand factors, 9–15, 25 time concepts, 3–9 Travelocity, 74, 115–117, 212, 237 Travelweb.com, 237 Triangular flights, 71 Tribal casinos, 247 Trunk carriers, 66 Turnover, hotel restaurant, 208 TWA, 60, 61, 112, 113, 137, 138, 227

U Umbrella Partnership Real Estate Investment Trust (UPREIT), 234 Unemployment rates, 11, 168, 300

Index Uniform System of Accounts for hotels, 201 for restaurants, 207 Uniform Systems of Accounts for the Lodging Industry (USALI), 203, 229 Unions, airline industry, 68 United Airlines (UAL), 60, 61, 113, 227 United Nation’s World Tourism Organization (UNWTO), 227, 311–313, 315, 319, 326 United States business productivity in, 9 casino industry in, 257 hotel industry leading indicator, 236 major theme parks in, 290 oil production and consumption, 37 Universal Studios, 294, 295, 302, 304 Urban hotels, 198, 202 U.S. Bureau of Economic Analysis, 326 U.S. Census of Selected Service Industries, 299 U.S. Department of Commerce, 15, 43, 351 U.S. Penal Code, 275 Utility, 12, 26, 39, 43–45 expected, 270 marginal, 26, 44 Utility-function models, 270

V Vacation ownership interests (VOI), 205, 206, 230 Vacation time, 35 Valuation of assets airline industry, 299 amusement/theme parks and resorts, 220 casino industry, 220 hotel industry, 220, 299 Valuation of travel time savings, 43 Valuation ratios, 107, 238 Valuation variables comparison methods, 33–34, 108 discounted cash flows, 32–33, 100, 106 options, 34 Value AEV, 107, 108 assessed, 220 books, 118, 178, 220, 223, 236, 347 carrying, 118 enterprise, 107, 108 EV, 33, 107, 121, 180, 347 insurable, 220 liquidation, 223 LTV ratios, 235

Index NAV, 223 private market, 107, 108 of time, 3, 78, 133, 173, 174 Values and lifestyles (VALS), 331 Vanocur, B., 235 Vauxhall Gardens, 291 Victor, D., 24 Video lottery terminals (VLTs), 252, 276 Virtual tourism, 317 Volatility, cash flow, 346 Voyager (ship), 165, 179

W Wagering, see Gambling industry Walker, D.M., 232, 277, 281 Wall Street Journal, 111, 113, 115, 116, 127, 128, 135, 235, 331 Wants vs. needs, income elasticity estimates for, 19, 163 Water parks, 294 Watres Act, 61 Wealth, marginal utility of, 270 Web-based gaming, 252 Weighted average cost of capital (WACC), 33, 100, 104, 107, 224 Whales, 264, 278

415 Wide-bodied aircraft, 63, 193 Wilson, K., 111, 193 Win per square foot, 269 rates, 262–264, 278, 280 Witt, C.A., 94 Witt, S.F., 94 Women, labor force participation, 14 Work and workweek average hours, 41, 42 Worker fatigue, 11 Work load unit (WLU), 120, 121 WorldRes Europe, 237 World’s Columbian Exposition, 290, 294 World Tourist Organization, 318 World War I, 41, 58, 61 World War II, 5, 13, 62, 173, 190, 246

Y Yield airline industry, 72, 200, 223 cruise line industry, 162 hotel industry, 181 management, 18, 70–72, 74, 91, 117 Yield per room (YPR), 199