Managerial decision making: A holistic approach 9783030280635

Table of contents :
Synopsis......Page 7
Preface......Page 9
Acknowledgments......Page 13
Contents......Page 15
About the Authors......Page 19
1.1 The Issue This Book Attempts to Address......Page 23
1.2 The Systems Approach......Page 28
1.3.1 Long-Term Expectations and Short-Term Predictions......Page 32
1.3.2 The Essence and Origin of Quantities......Page 34
1.3.3 Irregular Information and Systems Science......Page 35
1.4 Major Contributions of This Work......Page 37
1.5 Organization of Contents in This Book......Page 41
Bibliography......Page 42
Part I: The Theoretical Foundation......Page 45
2.1 The Concept of Systems......Page 47
2.2 The Systemic Yoyo Model......Page 50
2.3 Some Elementary Properties of the Systemic Yoyo Model......Page 57
Bibliography......Page 61
Chapter 3: The Dynamics of Market Competition......Page 63
3.1 The Problem of Concern and Literature......Page 64
3.2 Conditions of the Market......Page 66
3.3 Monopoly and Profit Stagnation......Page 68
3.4 Market Invitation for Innovation......Page 69
3.5 Expected Profits of New Entrants......Page 71
3.6 Conclusions......Page 73
The Proof of Theorem 3.1......Page 75
The Proof of Theorem 3.2......Page 76
The Proof of Theorem 3.3......Page 79
The Proof of Theorem 3.4......Page 80
The Proof of Theorem 3.5......Page 82
Bibliography......Page 83
4.1 The Problem to Be Addressed and Its Importance......Page 87
4.2 Potential Appearance of Micro Entrants......Page 88
4.3 General Properties of the Market......Page 91
4.4 Interactions Between Micro Entrants and Incumbent Firms......Page 94
4.5 Discussion......Page 98
4.6 Conclusion......Page 100
Appendix: Proofs of Theorems......Page 101
Bibliography......Page 102
Part II: The Present Era of Transient Competitive Advantages......Page 105
5.1 The Literature......Page 107
5.2 Markets Evolve Faster and Consumers Become Less Patient......Page 110
5.3 Sustainability Is Replaced by Transiency......Page 112
5.4 An Organizational Essence......Page 115
5.5 Conclusion......Page 118
The Proof of Theorem 5.1......Page 119
Relevant Technical Details of Bjerknes´ Circulation Theorem......Page 120
The Proof of Theorem 5.2......Page 121
Bibliography......Page 123
6.1 The Literature......Page 125
6.2 Competitions: Either Internal or External......Page 127
6.3 Adapting to the New Era: Necessary Steps......Page 130
6.3.1 The Model Firm......Page 131
6.3.2 The Needed Transitional Steps......Page 133
6.3.2.1 An Ambition That Is Long Term and Unwavering......Page 134
6.3.2.2 Relationships That Are Stable......Page 136
6.3.2.3 Agility with Strategies......Page 139
6.3.2.4 Innovation: The Norm of Business......Page 141
6.4 Looking at an Actual Case......Page 143
6.4.1 The Birth......Page 144
6.4.2 The Second Generation......Page 145
6.4.3 Peter Grace: The Third Generation......Page 146
6.4.4 Beyond Grace Family......Page 147
Appendix: Technical Details......Page 149
Bibliography......Page 151
Part III: The Innovativeness of Firms, Seen from Within......Page 153
7.1 The Literature......Page 155
7.2 Innovation: The Concept......Page 158
7.3 Clearly Stated Mission: The Starting Point of Everything Else......Page 159
7.4 Strategic Orientation......Page 162
7.5 Strategies Aiming at Growth......Page 165
7.6 Operational Procedures......Page 166
7.7 Managerial Recommendations......Page 169
7.8 Conclusion......Page 170
Bibliography......Page 171
Chapter 8: Impacts of Culture, Structure, and Leadership......Page 177
8.1 The Literature......Page 178
8.2 Firms´ Culture......Page 181
8.2.1 Formation of Individual´s Philosophical and Value Systems......Page 182
8.2.2 Formation of Organizational Culture......Page 184
8.2.3 Mission and Ambition: Unifying Forces of Organizational Culture......Page 185
8.3.1 The Firm´s Size......Page 187
8.3.2 The Firm´s Structure......Page 188
8.4.1 The Concept of Leadership......Page 190
8.4.2 Leadership Commitment......Page 192
8.4.3 Relation Between Leadership and Innovativeness......Page 193
8.5 Managerial Recommendations......Page 194
8.6 Conclusions......Page 195
Appendix: How Firm Size Is Determined by the Market......Page 196
Bibliography......Page 197
Part IV: Development of Nationally Self-Sustained Momentum of Growth......Page 202
9.1 The Literature......Page 203
9.2 The Representative Agrarian Nation......Page 207
9.3 Specific Steps for Developing Self-Sustained Momentum......Page 209
9.3.1 Establish the Long-Term National Goal......Page 210
9.3.2 Develop the Basic Standards of Moderate Living......Page 213
9.3.3 Engineer the Market Fermentation......Page 214
9.3.4 Promote Primary Target Industries......Page 217
9.3.5 Round Off the Initial Success......Page 220
9.4 What May Go Wrong?......Page 221
9.5 Conclusion......Page 224
Bibliography......Page 225
Part V: Going International or Staying Domestic?......Page 229
10.1 Introduction......Page 231
10.2 Domestically Speaking......Page 232
10.3.1 Exporting into a Less Developed Market......Page 234
10.3.2 Exporting into an Advanced Market......Page 236
10.4.1 International Trade and Productivity......Page 237
10.4.2 International Trade and Employee Wages......Page 240
10.4.3 International Trade and Firms´ Survival......Page 242
10.5 Conclusion......Page 245
The Proof of Theorem 10.3......Page 246
The Proof of Theorem 10.4......Page 247
The Proof of Theorem 10.5......Page 248
Analysis of a Non-Exporter......Page 249
Bibliography......Page 250
Chapter 11: Trade Dumping and Antidumping......Page 253
11.1 The Literature......Page 254
11.2 Competition Between Two Players......Page 256
11.2.1 Nash Equilibrium of Trade......Page 257
11.2.2 Mixed Strategies for the Game of Dumping and Antidumping......Page 259
11.2.3 Dumping in the World Market......Page 260
11.3 Consumers: The Ultimate Determinant......Page 262
11.4 An Analysis of Costs and Benefits......Page 266
11.5 Application in a Real-Life Case......Page 267
11.6 Conclusion......Page 269
Bibliography......Page 270
Appendix: Relevant Mathematical Foundations......Page 273
The Concept of Wedge Product in n......Page 274
Geometric Interpretation of x1 x2 xk......Page 279
Properties of Wedge Product......Page 284
A Few Final Words......Page 291
Bibliography......Page 293
Index......Page 311

Citation preview

Jeffrey Yi-Lin Forrest  Jeananne Nicholls · Kurt Schimmel  Sifeng Liu

Managerial Decision Making A Holistic Approach

Managerial Decision Making

Jeffrey Yi-Lin Forrest • Jeananne Nicholls Kurt Schimmel • Sifeng Liu

Managerial Decision Making A Holistic Approach

Jeffrey Yi-Lin Forrest Slippery Rock University Slippery Rock, PA, USA

Jeananne Nicholls Slippery Rock University Slippery Rock, PA, USA

Kurt Schimmel Slippery Rock University Slippery Rock, PA, USA

Sifeng Liu Institute for Grey Systems Studies Nanjing University of Aeronautics & Astronautics Nanjing, Jiangsu, China

ISBN 978-3-030-28063-5 ISBN 978-3-030-28064-2 https://doi.org/10.1007/978-3-030-28064-2

(eBook)

© Springer Nature Switzerland AG 2020 This work is subject to copyright. All rights are reserved 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, express 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

Synopsis

The purpose of this volume is to provide managers and entrepreneurs with a readily available tool to support their daily decision-making so that they know their decisions are mostly reliable and made on the basis of a sound scientific foundation, and scholars with a brand new approach to the research of managerial decision-making. To accomplish this practically significant and theoretically important outcome, instead of data mining and anecdotal analysis, this book establishes results by employing systems science and logic reasoning in general and the systemic yoyo model in particular. This abstract while intuitive in approach avoids all the serious limitations of econometric methods and anecdotal analyses. This book is composed of five parts, entitled, respectively, “The Theoretical Foundation”; “The Present Era of Transient Competitive Advantages”; “The Innovativeness of Firms: Seen from Within”; “Development of Nationally Self-Sustained Momentum of Growth”; and “Going International or Staying Domestic?” The first part introduces the relevant details of systems science needed for the rest of this book and establishes a general theory on the dynamics of market competition and when and how micro entrants would enter a well-occupied market. The second part focuses on the fact that the business world is presently in the era of transient competitive advantages, where the once sustainable advantages become transient and short-lived. It explains why markets evolve faster and consumers become less patient than ever before, why companies are under both internal and external pressures to compete, and how companies can successfully ride the waves of transient competitive advantages. The third part addresses the issue of how a firm can survive and succeed by looking internally at the concept of firms’ innovativeness, which is the origin of growth. It investigates which of the numerous internal factors, identified empirically by many different scholars in the past, are actually the primary determinants of firms’ innovativeness and which ones are secondary. Such knowledge is practically significant because managers and entrepreneurs can now focus their time and effort on developing the primary determinants instead of wasting resources on the secondary ones. The fourth part looks at the national economy by addressing the problem of v

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Synopsis

how an impoverished agrarian nation could develop a self-sustained momentum of growth. Considering the fact that it has been practically impossible, except China in recent decades, for any impoverished agrarian nation to develop an original Industrial Revolution, this part of the book represents a very important contribution to the literature on the Industrial Revolution. The fifth part of this volume considers the question of whether a firm should consider going international or not. To this end, this part first establishes the relationship between international trades and firm performance and then looks at the issue of trade dumping and antidumping. Currently, important large-scale decisions in business are mostly made based on data mining or anecdotes. However, scientifically speaking, such ways of decisionmaking have been time and again shown to be flawed. That also explains why one magnificent business success of one location generally cannot be duplicated in another location although various scholarly conjectures or theories are developed on why the initial success was achieved. Because of this reason, this book is expected to open up a brand new territory of research valuable for working managers, entrepreneurs, and business/economics scholars. As shown within this book, many of the conclusions logically drawn on the basis of systems science can be practically applied to produce tangible economic benefits. This book is written for those readers who are either graduate students, researchers, or practitioners in the areas of strategy, management science and engineering, economics, and decision science, either theoretical or applied. By studying this book, by referencing back to it regularly, and by employing systems methods, as presented in this volume, to resolve various demanding issues in business, the reader will master a brand new tool of analysis and an intuition. By employing the new tool and intuition, he/she will be able to make useful decisions relatively quickly without wasting unnecessarily the valuable time and a lot of the limited financial resources.

Preface

Because of our combined background and training in areas of mathematics and natural science, we find that there is a lot that needs to be done in the area of managerial decision-making in particular, and social science in general. The major difference we observed between mathematics/natural science and managerial decision-making (or social science) is that in the former case, as long as a new gadget (or a theorem) is produced with its functionality (respectively, consequences) well known, other people will most likely be able to design and produce (respectively, prove) a similar gadget (respectively, theorem) although the specific design (respectively, argument) of the original gadget (respectively, theorem) is not known. However, for the case of managerial decision-making (or social science), the situation is not the same. By observing business successes and by theorizing the reasons why these successes are achieved, people generally cannot duplicate the desired economic outcomes in another business setting in other parts of the world. To this end, the Industrial Revolution of England and the magnificent success of the Silicon Valley (California) are two of many such instances. To answer the question of what leads to the challenge that faces decision-making managers and entrepreneurs, one only needs to compare how mathematics and theories of natural science are developed against how managerial hypotheses are conjectured. For the former case, each particular theorem or theory is developed based on some very intuitive and straightforward postulates or laws, accompanied by the consecutive introduction of specific terms. And the connection between the starting postulates/laws and each consequent result is established through rigorous logic reasoning developed on seemingly reasonable playgrounds, such as the ndimensional coordinate system, n ¼ 1, 2, 3, . . ., consisting of n real-number lines that cross each other at a common point, known as the origin. On the other hand, managerial hypotheses are mostly conjectured based on some particular anecdotes or specific sets of data. To establish the hypotheses as propositions so that they can be more widely applied than where the anecdotes and data originally come from in business decision-making, econometric tools are mostly used. In this process of developing each and every managerial proposition, uncertainties inevitably appear vii

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Preface

first, at the stage of conjecturing the hypotheses and second, at the stage of econometrically analyzing the data. It is because from the same set of evidences, different conclusions can be drawn depending on the decision-maker’s background and because econometric tools are all, without any exception, constrained by their respectively strict requirements. Based on this recognition, this book attempts to develop a general theory of managerial decision-making on the basis of a few elementary postulates, by employing logic as the method of reasoning and the systems science in general, and the systemic yoyo model in particular, as the intuitive playground. By doing so, we are able to take individually background-based guesswork out of the development of the theory. Due to this reason, all established conclusions are expected to be generally employable in real-life applications. Different from all branches of mathematics that are based on numerical variables, such as calculus, and various methods of econometrics, systems science focuses on the investigation of organizations and structures. That is why we adopt systems science as our way of intuitively seeing how business entities behave in their interactions with each other, because business entities generally possess their respectively different, yet rich, internal structures. For example, each firm has its specific organizational culture, tradition, operational routines, etc., constituting the unique background on which the firm forms its particular understanding out of what the market is presenting. Differences in these internal structures lead to varied firmspecific understandings of the same market signal. And, it is these internal organizational structures that make systems science more readily and more adequately employable for us to study business decision-making than any of the other available tools developed on numbers or numerical variables, such as calculus and statistics. Here, calculus helps decision-makers to make predictions by extrapolating the present situation (also known as the initial value) into the future, while statistics expand the past trend (also known as data or anecdotes) into the future. However, managerial decision-making is more or less about predicting such a future that is drastically different from both the present and the past. That explains why there is an urgent need for the theory of managerial decision-making to go beyond the capability boundaries of the classical calculus-based methods and statistics-based tools. Although the concepts of numbers (and numerical variables) and systems are abstracted out of the same physical world, they represent the world from two different and harmonizing angles. In particular, when a business organization is treated as a collection of unrelated people, properties, etc., the concept of numbers comes into play. For example, firm X employs n employees, occupies m office buildings, etc. On the other hand, when the organization of the firm is viewed holistically, then the concept of systems naturally emerges. For example, this firm X is really a binding platform that connects such elements as employees, capital assets, properties, etc. to form an organic whole. It is these relationships that the firm exists both physically and intellectually. In other words, most problems of managerial decision-making are essentially about organizations or systems, be they individuals, seen as economic agents whose behaviors are dictated by their personal value systems, firms, markets, industries, economies, etc.

Preface

ix

Even though the concepts of numbers and systems share the same origin—the natural world—they represent two very different aspects of the world. The former is small scale and local, while the latter is large scale and organizational. More importantly, numbers exist only postexistence. That is why using number-based theories to make predictions has not been very successful, just as we discussed earlier about calculus and statistics. In other words, when one uses post-event evidence to predict the appearance of a not-yet-occurring event is doomed to be not very successful. On the other hand, systems emerge at the same time when physical or intellectual existence comes into being. That is the very reason why the methodology of systems is more appropriate than all theories developed on numbers and variables for the investigation of economic entities when their internal structures cannot be ignored. As promised, this book presents a general theory of managerial decision-making with results generally applicable in practice. At the same time, we attempt to make this theory satisfy the following conditions: 1. 2. 3. 4.

It is reader-friendly to as many people as possible. It coincides with people’s intuition. It possesses certain beauty that can be felt easily. It is capable of producing meaningful results and insights for practical purposes.

As is argued by Y. Lin (2009) in the monograph Systemic Yoyos: Some Impacts of the Second Dimension (CRC Press, New York), only with these characteristics, the theory developed herein has a chance to enjoy a glorious and long-lasting life. In particular, to satisfy condition 1, each and every theoretical result presented in this book will be accompanied by nontechnical explanations. In other words, the arguments, be they logical or systemic or both, can be skipped over without affecting the reading of the rest of the book. To satisfy condition 2, established results will be illustrated as much as possible with systemic intuitions so that the reader can see why the results are generally true. To satisfy condition 3, various figurative presentations of the systemic yoyo model are provided. And to satisfy condition 4, this book considers an array of exciting topics where managerial decision-making is always located at the center square. In particular, among others, we will carefully and in details look at the following topics: 1. 2. 3. 4. 5. 6. 7. 8. 9.

How market competition plays out dynamically How monopoly can possibly lead profit stagnation How markets always signal their invitation for competition and innovation What makes markets evolve faster and consumers less patient What a firm needs to do to successfully ride the waves of transient competition advantages What factors internal to a firm primarily determine the innovativeness of the firm What a national government could do to foster the development of a selfsustained momentum of economic growth Whether or not a firm should consider going international or just staying domestic How such trade behaviors as dumping and antidumping interact with each other.

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Preface

We hope that you, the reader, will enjoy reading and referencing this book in your real-life decision-making practice and scholarly exploration. If you have any comments or suggestions, please let us hear from you by dropping us a message. Jeffrey Yi-Lin Forrest can be reached at [email protected] or jeffrey. [email protected], Professor Jeananne Nicholls at [email protected], Professor Kurt Schimmel at [email protected], and Professor Sifeng Liu at sfl[email protected]. Slippery Rock, PA, USA

Jeffrey Yi-Lin Forrest

Acknowledgments

This book contains many research results previously published in various sources. We are grateful to the copyright owners for permitting us to use the material. They include Emerald Publishing Gordon & Breach Science Publishers (Yverdon-les-Bains, Switzerland, and New York) Hemisphere (New York) International Association for Cybernetics (Namur, Belgium) International Federation for Systems Research (Vienna, Austria) International Institute for General Systems Studies, Inc. (Slippery Rock, Pennsylvania) Kluwer Academic and Plenum Publishers (Dordrecht, Netherlands, and New York) MCB University Press (Bingley, UK) Northeastern Association of Business, Economics and Technology Pergamon Journals, Ltd. (Oxford) Scientific Research – An Academic Publisher Springer Nature Taylor & Francis, Ltd. World Scientific Press Wroclaw Technical University Press (Wroclaw, Poland)

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Contents

1

Facing the Challenge Holistically . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 The Issue This Book Attempts to Address . . . . . . . . . . . . . . . . 1.2 The Systems Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Scientific Irregularities: The Norm of Business Life . . . . . . . . . 1.3.1 Long-Term Expectations and Short-Term Predictions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3.2 The Essence and Origin of Quantities . . . . . . . . . . . . 1.3.3 Irregular Information and Systems Science . . . . . . . . . 1.4 Major Contributions of This Work . . . . . . . . . . . . . . . . . . . . . 1.5 Organization of Contents in This Book . . . . . . . . . . . . . . . . . . Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Part I 2

3

1 1 6 10 10 12 13 15 19 20

The Theoretical Foundation

Basics of Systems Science . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 The Concept of Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 The Systemic Yoyo Model . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Some Elementary Properties of the Systemic Yoyo Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

25 25 28

The Dynamics of Market Competition . . . . . . . . . . . . . . . . . . . . . . . 3.1 The Problem of Concern and Literature . . . . . . . . . . . . . . . . . 3.2 Conditions of the Market . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Monopoly and Profit Stagnation . . . . . . . . . . . . . . . . . . . . . . . 3.4 Market Invitation for Innovation . . . . . . . . . . . . . . . . . . . . . . . 3.5 Expected Profits of New Entrants . . . . . . . . . . . . . . . . . . . . . . 3.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix: Proofs of Theoretical Results . . . . . . . . . . . . . . . . . . . . . . . The Proof of Theorem 3.1 . . . . . . . . . . . . . . . . . . . . . . . . . . . The Proof of Theorem 3.2 . . . . . . . . . . . . . . . . . . . . . . . . . . .

41 42 44 46 47 49 51 53 53 54

35 39

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4

Contents

The Proof of Theorem 3.3 . . . . . . . . . . . . . . . . . . . . . . . . . . . The Proof of Theorem 3.4 . . . . . . . . . . . . . . . . . . . . . . . . . . . The Proof of Theorem 3.5 . . . . . . . . . . . . . . . . . . . . . . . . . . . Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

57 58 60 61

Market Entry and Market Partition . . . . . . . . . . . . . . . . . . . . . . . . 4.1 The Problem to Be Addressed and Its Importance . . . . . . . . . . 4.2 Potential Appearance of Micro Entrants . . . . . . . . . . . . . . . . . 4.3 General Properties of the Market . . . . . . . . . . . . . . . . . . . . . . 4.4 Interactions Between Micro Entrants and Incumbent Firms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix: Proofs of Theorems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

65 65 66 69

Part II

72 76 78 79 80

The Present Era of Transient Competitive Advantages

5

What Is Happening? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 5.1 The Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 5.2 Markets Evolve Faster and Consumers Become Less Patient . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 5.3 Sustainability Is Replaced by Transiency . . . . . . . . . . . . . . . . 90 5.4 An Organizational Essence . . . . . . . . . . . . . . . . . . . . . . . . . . 93 5.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96 Appendix: Technical Details Relevant to This Chapter . . . . . . . . . . . . 97 The Proof of Theorem 5.1 . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 Relevant Technical Details of Bjerknes’ Circulation Theorem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 The Proof of Theorem 5.2 . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 The Formation of Personal Values . . . . . . . . . . . . . . . . . . . . . 101 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101

6

Successfully Ride Waves of Transient Competitive Advantages . . . . 6.1 The Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Competitions: Either Internal or External . . . . . . . . . . . . . . . . 6.3 Adapting to the New Era: Necessary Steps . . . . . . . . . . . . . . . 6.3.1 The Model Firm . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.3.2 The Needed Transitional Steps . . . . . . . . . . . . . . . . . 6.4 Looking at an Actual Case . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4.1 The Birth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.4.2 The Second Generation . . . . . . . . . . . . . . . . . . . . . . . 6.4.3 Peter Grace: The Third Generation . . . . . . . . . . . . . . 6.4.4 Beyond Grace Family . . . . . . . . . . . . . . . . . . . . . . . . 6.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix: Technical Details . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

103 103 105 108 109 111 121 122 123 124 125 127 127 129

Contents

Part III 7

8

The Innovativeness of Firms, Seen from Within

Effects of Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.1 The Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 Innovation: The Concept . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3 Clearly Stated Mission: The Starting Point of Everything Else . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.4 Strategic Orientation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.5 Strategies Aiming at Growth . . . . . . . . . . . . . . . . . . . . . . . . . 7.6 Operational Procedures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.7 Managerial Recommendations . . . . . . . . . . . . . . . . . . . . . . . . 7.8 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Impacts of Culture, Structure, and Leadership . . . . . . . . . . . . . . . . 8.1 The Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2 Firms’ Culture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2.1 Formation of Individual’s Philosophical and Value Systems . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2.2 Formation of Organizational Culture . . . . . . . . . . . . . 8.2.3 Mission and Ambition: Unifying Forces of Organizational Culture . . . . . . . . . . . . . . . . . . . . . 8.3 Firms’ General Characteristics and Structure . . . . . . . . . . . . . . 8.3.1 The Firm’s Size . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3.2 The Firm’s Structure . . . . . . . . . . . . . . . . . . . . . . . . . 8.4 Firms’ Leadership . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.4.1 The Concept of Leadership . . . . . . . . . . . . . . . . . . . . 8.4.2 Leadership Commitment . . . . . . . . . . . . . . . . . . . . . . 8.4.3 Relation Between Leadership and Innovativeness . . . . 8.5 Managerial Recommendations . . . . . . . . . . . . . . . . . . . . . . . . 8.6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix: How Firm Size Is Determined by the Market . . . . . . . . . . . Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Part IV 9

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133 133 136 137 140 143 144 147 148 149 155 156 159 160 162 163 165 165 166 168 168 170 171 172 173 174 175

Development of Nationally Self-Sustained Momentum of Growth

The Procedure that Is Supported by Solid Theories . . . . . . . . . . . . 9.1 The Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.2 The Representative Agrarian Nation . . . . . . . . . . . . . . . . . . . . 9.3 Specific Steps for Developing Self-Sustained Momentum . . . . 9.3.1 Establish the Long-Term National Goal . . . . . . . . . . . 9.3.2 Develop the Basic Standards of Moderate Living . . . . 9.3.3 Engineer the Market Fermentation . . . . . . . . . . . . . . . 9.3.4 Promote Primary Target Industries . . . . . . . . . . . . . . . 9.3.5 Round Off the Initial Success . . . . . . . . . . . . . . . . . . 9.4 What May Go Wrong? . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

183 183 187 189 190 193 194 197 200 201

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Contents

9.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 204 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205 Part V 10

11

Going International or Staying Domestic?

International Trade and Firm Performance . . . . . . . . . . . . . . . . . . 10.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.2 Domestically Speaking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.3 Entry into a Foreign Market, Either Less Developed or Advanced . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.3.1 Exporting into a Less Developed Market . . . . . . . . . . 10.3.2 Exporting into an Advanced Market . . . . . . . . . . . . . 10.4 A General Theory on International Trades . . . . . . . . . . . . . . . . 10.4.1 International Trade and Productivity . . . . . . . . . . . . . 10.4.2 International Trade and Employee Wages . . . . . . . . . . 10.4.3 International Trade and Firms’ Survival . . . . . . . . . . . 10.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix Proofs of Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Proof of Theorem 10.3 . . . . . . . . . . . . . . . . . . . . . . . . . . The Proof of Corollary 10.1 . . . . . . . . . . . . . . . . . . . . . . . . . . The Proof of Theorem 10.4 . . . . . . . . . . . . . . . . . . . . . . . . . . The Proof of Theorem 10.5 . . . . . . . . . . . . . . . . . . . . . . . . . . Analysis of a Non-Exporter . . . . . . . . . . . . . . . . . . . . . . . . . . Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

211 211 212

Trade Dumping and Antidumping . . . . . . . . . . . . . . . . . . . . . . . . . 11.1 The Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2 Competition Between Two Players . . . . . . . . . . . . . . . . . . . . . 11.2.1 Nash Equilibrium of Trade . . . . . . . . . . . . . . . . . . . . 11.2.2 Mixed Strategies for the Game of Dumping and Antidumping . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.2.3 Dumping in the World Market . . . . . . . . . . . . . . . . . 11.3 Consumers: The Ultimate Determinant . . . . . . . . . . . . . . . . . . 11.4 An Analysis of Costs and Benefits . . . . . . . . . . . . . . . . . . . . . 11.5 Application in a Real-Life Case . . . . . . . . . . . . . . . . . . . . . . . 11.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

233 234 236 237

214 214 216 217 217 220 222 225 226 226 227 227 228 229 230

239 240 242 246 247 249 250

Appendix: Relevant Mathematical Foundations . . . . . . . . . . . . . . . . . . . 253 Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273 Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 291

About the Authors

Jeffrey Yi-Lin Forrest also known as Yi Lin, holds all his educational degrees in pure mathematics and had 1 year postdoctoral experience in statistics at Carnegie Mellon University. He had been a guest professor of economics, finance, mathematics, and systems science at several major universities in China, including Nanjing University of Aeronautics and Astronautics. And currently, he is a professor of mathematics and research coach for the School of Business at Slippery Rock University, Pennsylvania, and the president of the International Institute for General Systems Studies, Inc., Pennsylvania. He serves either currently or in the past on the editorial boards of 13 professional journals, including Kybernetes: the International Journal of Systems, Cybernetics and Management Science, Journal of Systems Science and Complexity, International Journal of General Systems, The Journal of Grey System, etc. Currently, he serves as the editor in chief of three book series, “Systems Evaluation, Prediction, and DecisionMaking” (CRC Press, New York), “Communications in Cybernetics, Systems Science and Engineering” (CRC Press, Balkema), and “Communications in Cybernetics, Systems Science and Engineering – Proceedings” (CRC Press, Balkema). Some of his research was funded by the United Nations, the State of Pennsylvania, the National Natural Science Foundation of China, and the German National Research Center for Information Architecture and Software Technology. As of the end of 2018, he has published well over 400 research papers and nearly xvii

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About the Authors

50 monographs and special topic volumes. Some of these monographs and volumes were published by such prestigious publishers as Springer, Taylor & Francis, World Scientific, Kluwer Academic Publishers, Academic Press, etc. Over the years, his scientific achievements have been recognized by various professional organizations and academic publishers. In 2001, he was inducted into the Honorary Fellowship of the World Organization of Systems and Cybernetics. His research interests are wide ranging, covering areas like economics, finance, management, marketing, data analysis, predictions, mathematics, systems research and applications, philosophy of science, etc. Jeananne “Nan” Nicholls is a full professor of marketing at Slippery Rock University (SRU) where she has been since 2011 after spending 20+ years in senior positions in technology-based economic development in Ohio, West Virginia, and Pennsylvania – managing $40+ million worth of research grants and projects. She has degrees from Kennesaw State University (DBA), Duquesne University (MBA), and Carlow University (BS). She is a Fellow in the Direct Selling Education Foundation, is the VP of Collegiate Relationships for the Pittsburgh American Marketing Association, and is a board member of The Education Partnership. She received SRU’s 2015 President’s Award for Academic Advising and was named the 2016 Pittsburgh American Marketing Association (AMA) Distinguished Educator of the Year and has been SRU’s AMA chapter adviser since 2011. Additionally, she has been a coauthor on three best faculty conference papers. Her research interests include behavioral reasoning theory (BRT), marketing/education, firm performance, and online social presence among other things. She teaches marketing and management courses at the graduate and undergraduate levels.

About the Authors

xix

Kurt Schimmel is a professor of marketing at Slippery Rock University of Pennsylvania. He has authored over 100 peer-reviewed articles, book chapters, research monographs, and presentations. He has also served on over 25 graduate theses. His research interests include individual and group decision-making, decision heuristics, and behavioral reasoning theory. Some of his research was funded by the American Bar Association. He has served as an editor for the Journal of Business, Economics and Technology and was a founding member of the editorial board of the Journal of Internet Commerce. He was a doctoral fellow of the American Marketing Association. Additionally, he is a graduate of the Pennsylvania State University Academic Leadership Academy. He has served on several boards of directors for nonprofit and regional economic development organizations. He has held multiple positions including graduate director at West Virginia University, associate dean at Robert Morris University’s School of Business, and dean at Slippery Rock University College of Business. He is currently chair of the School of Business at Slippery Rock University. Sifeng Liu is senior member of the IEEE, honorary fellow of WOSC, and senior fellow of Marie Curie International Incoming Fellowship under the 7th Framework Programme of the European Union. He received his PhD in systems engineering from Huazhong University of Science and Technology, China, in 1998. He is currently a distinguished professor of Nanjing University of Aeronautics and Astronautics and a research professor of De Montfort University. He is serving as the founding director of the Institute for Grey Systems Studies, the founding president of the International Association of Grey Systems and Uncertainty Analysis, the founding chair of TC of the IEEE SMC on Grey Systems, and the founding president of Grey System Society of China. He is also serving as the founding editor of Grey Systems: Theory and Application (Emerald) and the editor in chief of The Journal of Grey Systems (Research Information). He had worked at Slippery Rock University in Slippery Rock and New York Institute of Technology in New York, USA; Sydney University in Sydney, Australia; and De Montfort

xx

About the Authors

University in Leicester, UK, as a visiting professor. And he led the College of Economics and Management, NUAA, from 2001 until 2012. His main research activities are in grey system theory and applications. He has directed more than 50 research projects from China, the UK, UN, and EU. He has published over 600 research papers and 26 books by Science Press, Springer-Verlag, Taylor & Francis Group, and John Wiley & Sons, Inc. He is currently serving as the editor of the book series Grey Systems published by Science Press. His works cited 32 thousand times by others and had translated to Korean, German, and Romanian. Over the years, he has been awarded 18 provincial and national prizes for his outstanding achievements in scientific research and applications. In 2002, he was recognized by the World Organization of Systems and Cybernetics. His H-index is 55. He has won several accolades such as the “National Excellent Worker of Science and Technology,” “National Excellent Teacher,” “National Advanced Individual for Returnee,” “Expert Enjoying Government’s Special Allowance,” and “National Expert with Prominent Contribution.”

Chapter 1

Facing the Challenge Holistically

This chapter describes the challenge this book will address that faces decisionmaking managers and entrepreneurs and explains why there is an urgent need to resolve related issues in order to meet the challenge. After this challenge is clearly presented, this chapter turns its attention to illustrate why systems science and systems methodologies are the appropriate approach for managers and entrepreneurs to use in their daily decision-making while pointing out weaknesses existing in the widely employed methodologies – anecdotal analysis, calculus-based tools, and statistics-based methods. The rest of the chapter is organized as follows: Section 1.1 describes the very issue this book attempts to address. Section 1.2 introduces the basics of systems approach and explains why it is an appropriate tool for studying issues of managerial decision-making. Section 1.3 focuses on the topic of scientific irregularity – what it is, why it appears, and how it influences the lives of decision-making managers and entrepreneurs. Section 1.4 details the contributions of this work. And Sect. 1.5 concludes this introductory chapter by outlining the contents of this book.

1.1

The Issue This Book Attempts to Address

There are major differences between natural and social sciences. For example, in natural science, scholars traditionally investigate lifeless objects and the operational laws underneath the evolutions of physical things. Experience and rapid development of technology of the past several hundred years have witnessed the magnificent success of this approach. And, in social science, academics widely examine events and social processes involving people based on past data and known anecdotes, producing various data-specific and/or anecdote-specific theories hoping that they can be generally applicable to scenarios beyond the limitations of the original data and anecdotes. As consequences, in natural science, predictions are produced based on the basic laws; their accuracies can be checked quite readily later on by © Springer Nature Switzerland AG 2020 J. Y.-L. Forrest et al., Managerial Decision Making, https://doi.org/10.1007/978-3-030-28064-2_1

1

2

1 Facing the Challenge Holistically

comparing what are predicted and what actually happens over time. And, in social science, predictions are generally made by using data or anecdotes of the past through extrapolating the existing pattern observed in the data or anecdotes into the future. However, the accuracies of the predictions are very difficult to check, because after learning about what is expected (or predicted), human participants generally modify their behavioral patterns according to their respective needs for the future to be. For example, when meteorologists forecast what weather conditions are forthcoming, the prediction does not have any bearing on the occurrence of the weather event. However, when influential financial analyzers predict how the stock market is going to move, be it upward or downward or sideway, in the coming weeks or months, individual investors generally position themselves accordingly, making the prediction mostly incorrect. Because the methodologies and approaches used in natural and social sciences are different, scientists tend to use affirmative terms to state their conclusions, while scholars in social science generally use such words as “believe,” “should,” and “would.” For example, Kotler et al. (2010), Krauss (2011), and Stengel (2011) believe that today’s customers want to be treated as whole human beings and be acknowledged that their needs go beyond pure consumerism. In this instance, the word “believe” means, scientifically speaking, that these scholars are not quite sure about the correctness of what they are saying. Because Philip Kotler is considered as one of the most influential marketing thinkers (Kaul 2012), the example given above simply indicates that most decisions in the area of marketing are made based on anecdotes or data mining or both so that the decision-maker also knows that his/her decision could be wrong in general and when applied to scenarios beyond the limitations of the data or anecdotes employed in their studies. In fact, in natural science and mathematics, neither anecdotes nor data mining are recognized as reliable ways to produce dependable theorems and theories beyond potential facts finding; and by employing data mining, one can also easily discover “realities” that only exist with the particular sets of data used in the analyses (Lin and OuYang 2010). When we narrow our general discussion in the previous paragraphs to the case of managerial decision-making, the following situation emerges, representing a great and exciting opportunity of scholarly research. When a technological breakthrough appears, by using the laws of science, engineers from different parts of the world are generally able to design and produce a similar technology without knowing the protected details of the original breakthrough. However, contrary to this situation in natural science, the case with managerial decision-making is not the same. For example, by closely observing business successes and by theorizing the reasons why these successes are achieved, people generally cannot duplicate the desired economic outcomes in another business setting in other parts of the world. To this end, the Industrial Revolution of England and the magnificent success of the Silicon Valley (California) are two of many such instances. Many developing countries have tried very hard in the past 100 plus years to launch their own versions of Industrial Revolution without luck (Rostow 1960; Wen 2016).

1.1 The Issue This Book Attempts to Address

3

When the product market indicates that an increasing proportion of consumers make their purchase decisions based on whose price is more competitive, it can be recognized as an invitation the market sends out for innovation and additional competition; see Chap. 3 for more details. However, due to differences in their backgrounds, such as knowledge, skill, and philosophical value systems, and in availabilities of their respective resources, managers and entrepreneurs react to such market invitations differently. Due to the differences in understanding the market and in the consequent reactions responding to the market call, these risk-taking managers and entrepreneurs experience varied degrees of success. That is, decisionmaking managers and entrepreneurs generally face the challenge of how to appropriately understand a market signal and how to choose a suitable reaction in order to produce their desired business success. In order to see what has led to this both theoretically and practically difficult challenge that faces decision-making managers and entrepreneurs alike, let us do a quick comparison without any detailed deliberation between how theorems in mathematics and theories of natural science are developed and how managerial hypotheses are first conjectured and then confirmed before practically used. In mathematics and natural science, scholars first carefully develop a set of basic and intuitive postulates and laws, respectively. The validity of these postulates and laws is supported by some relevant and unquestionable knowledge or by repeated confirmation of lab results. Then each time when a new concept or term or phenomenon is introduced or considered, a group of theorems or a theory is established by using logic reasoning so that each conclusion is derivable directly or indirectly from the initial set of postulates or laws (Kline 1972; Bauer 2015). Here, the development of knowledge exploration in mathematics and natural science is similar to how a dictionary is composed – all words are explained by some very basic words, whose meanings are assumed to be clear without any further explanation or are explained by each other. For example, a set is defined as a collection of elements, while an element is defined as a member of a set (Kuratowski and Mostowski 1976), where “set” and “element” are two very basic words that are used to define each other and other words. Speaking differently, the initial sets of postulates and laws capture the essence of all mathematical scenarios and physical phenomena. As the mankind expands its exploration of nature, these sets also grow accordingly. Additionally, other than logic reasoning is universally employed, seemingly reasonable playgrounds, such as the n-dimensional coordinate system, n ¼ 1, 2, 3, . . ., consisting of n real number lines that cross each other at a common point, known as the origin, are mostly utilized to support the background intuition that underlies rigorous logic reasoning. In fact, beyond playing the role of intuition, the one-dimensional coordinate system (i.e., simply the real number line) has been used to develop the theory of real numbers – the Dedekind cuts – that confirms the existence of irrational numbers; the two-dimensional coordinate system has been used to establish some of the most basic results of calculus, including limx ! 0sinx/ x ¼ 1; the reason why we say that such a playground as the n-dimensional coordinate system is seemingly reasonable is because it does not exist in real life. Even so, it has been very useful and helpful in human understanding of nature.

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1 Facing the Challenge Holistically

Fig. 1.1 The blind men tempt to conceptualize what an elephant is like

In terms of managerial decision-making, various hypotheses regarding individually specific populations are mostly conjectured based on some particular anecdotes or repeated experience or associations of both. When an economic potential and/or theoretical value of some hypotheses is seen, researchers are aroused to test the hypotheses by using data and econometric methods in order to establish propositions so that they can be more widely applied in business decision-making than the range within which the anecdotes and data originally come from. The entire process of initially developing hypotheses, followed by testing, and then establishing general propositions is similar to the situation described in the proverb of “the blind men and an elephant” (Goldstein 2010, p. 492). In this proverb, a group of several blind men attempt to learn and conceptualize what an elephant is like by touching it, because none of them has ever come across an elephant before. If each blind man can only feel a different part of the elephant’s body, such as the side, the tusk, a leg, an ear, the nose, the back, and the tail, they then hypothesize how the elephant looks like very differently from one another based on their limited experience and knowledge, although their sensing abilities are perfect, Fig. 1.1. In this analogy, we imagine to treat the elephant as the population of concern, the blind men’s initial touches of the elephant as the anecdotes from which hypotheses are developed. As for data collection and econometric testing, they can be seen as that after their hypotheses are developed, the men go back to where they are allowed to touch the elephant to collect additional evidences and then confirm whether or not their hypotheses are sufficiently supported. So, they individually make their completely different inferences about how the elephant looks like. In this fictitious scenario, none of these men has obtained the correct answer. To this end, one naturally questions the imposed constraint that each of these men is only allowed to touch the elephant at a particular location, because in reality these men naturally

1.1 The Issue This Book Attempts to Address

5

want to explore the elephant in its entirety as much as possible before making their inferences. To address this question corresponding to our discussion here, let us return to issues facing decision-making managers. When anecdotes and data are employed to formulate hypotheses, one always runs into such problems as sampling error, missing representation, etc. For example, in the study of market entry and entry timing, conclusions have been drawn on the available data of some successes, while those data of failed attempts are simply not available (Zachary et al. 2015). In the analysis of the innovativeness of manufacturing firms, the very concept of innovativeness is defined in dissimilar ways partially due to the reason of data availability, while specific-data-backed conclusions are universally stated (Becheikh et al. 2006). In the investigation of the relationship between a firm’s market reach – domestic, or importing, or exporting, or any combination of these three options – and its performance, conclusions are mostly drawn on the data collected from a few developed countries because data from other countries are simply not available (Wagner 2012a, b). In the examination of the Industrial Revolution, most needed data are not possible to collect, because the event occurred long time ago and the process leading to the eventual recognition of the Revolution traversed a few hundred years (Rostow 1960). In all these listed and other unlisted studies, the “blind men” are the researchers, who are only allowed to “feel” particular parts of the underlying population, although they want to explore more than what is allowed. Hence, in terms of managerial decision-making, managers have to ask themselves the following question: How much can they place their faith on the “general” conclusions derived empirically in their decision-making?

Other than what is discussed above, two additional issues that are worthy of our attention are that (1) from the same set of evidences, different conclusions can be drawn depending on the decision-maker’s background and knowledge structure, and (2) econometric tools, which are widely used in testing hypotheses, are all, without any exception, constrained by their, respectively, strict requirements. Summing up the discussions in the previous paragraphs, the issue this book attempts to address is how to Develop a general theory of managerial decision-making in a similar fashion as that is commonly the approach used in mathematics and natural science.

That is, on the basis of a few elementary postulates, general conclusions are derived through logic reasoning on the intuition of a playground that is appropriate for us to imagine how organizations evolve and interact with each other. Considering the fact that the concept of systems is the right tool for visualizing structures and organizations, this book will employ systems science in general and the systemic yoyo model in particular as the intuitive playground. By doing so, we are able to take individually background-based guesswork out of the development of the theory. And because of this very reason, all established conclusions in this book are expected to be generally employable in real-life applications.

6

1.2

1 Facing the Challenge Holistically

The Systems Approach

Different from all branches of mathematics that are based on numerical variables, such as calculus, differential equations, etc., and various methods of econometrics, systems science focuses on the investigation of organizations and structures or various kinds of systems (Lin 1999; Klir 1985). Because business entities generally possess their, respectively, different, yet rich, internal structures, we adopt systems science in this book as our way of intuitively seeing how business entities evolve, respectively, and behave in their interactions with one another. System (or organization or structure) really exists everywhere, especially in investigations of issues related to managerial decision-making. For example, each human being is a very complex biological system, which is made up of smaller systems. Simultaneously, the person is also a member of many social and economic systems, such as a family, neighborhoods, communities, etc. Each day the person interacts with a range of various man-made systems, such as a car, an ATM machine, retail stores, the company she works for, etc. These systems, be they natural, social, or artificial, interact with each other constantly. So, beyond employing the concepts of numbers and variables to investigate problems and issues of managerial decisionmaking, which has been what is mostly done in the literature, we see an urgent need to employ the concept of systems and relevant methods to study events and social and economic processes in order to obtain brand new while practically useful understandings and conclusions. Here, what do we mean by “urgent”? When employing readily developed methodologies to help with managerial decisionmaking, we generally use either a calculus-based method or a statistics-based tool or a combination of both. However, any calculus-based method in essence helps decision-makers make predictions by extrapolating the present situation (or known as the initial value) into the future, while each statistics-based tool expands the past trend (or known as data or anecdotes) into the future. So, if we understand managerial decision-making as being more or less about predicting such a future that is drastically different from both the present and the past, then there is an urgent need for the theory of managerial decision-making to go beyond the capability boundaries of the classical calculus-based methods and statistics-based tools. In other words, after having tried various methods developed for data mining and anecdote analysis without producing many reliable scientific conclusions, now is the time for us to go straight to the underlying fundamental principles underneath the surface of numbers, numerical variables, and anecdotes that can lead to scientifically sound conclusions and practically reliable consequences. Historically, the concept of systems has been directly or indirectly introduced by scholars in different disciplines over the recorded history in various languages. In order not to deviate away from our main focus here, let us look at two recent cases as examples. In the area of economics, Rostow (1960) wrote that: “The classical theory of production is formulated under essentially static assumptions . . . to merge classical production theory with Keynesian income analysis . . . introduced the dynamic variables: population, technology, entrepreneurship, etc. But . . . do so in forms so

1.2 The Systems Approach

7

rigid and general that their models cannot grip the essential phenomena of growth . . . We require a dynamic theory . . . which isolates not only the distribution of income between consumption, savings, and investment (and the balance of production between consumers and capital goods) but which focuses directly and in some detail on the composition of investment and on developments within particular sectors of the economy.” In other words, Rostow had realized the need to investigate economics in a systemic fashion. And, in the area of biology, von Bertalanffy (1924) pointed out the fact that because the fundamental character of living things is their organization, the customary investigation of individual parts and processes cannot provide a complete explanation of the phenomenon of life. Since these and other earlier works on the urgent need for systems thinking and methodology of our modern time, many others, such as Porter (1985), Klir (1985), Lin (2009), etc., also demonstrate how powerful holistic way of thinking and relevant methodology can be in terms of producing conclusions that are realistically reliable and practically usable regarding organizations, such as business entities, and how these organizations, such as economies or markets, etc., interact with each other. As a matter of fact, since the 1920s, such a holistic view of nature, organizations, and social events has permeated the spectrum of knowledge (Lin 2009) with the exception that in some areas, it is more widely applied than other areas. For example, applications of holistic thinking and advanced systems methodologies in the area of managerial decision-making have been seriously lacking. Hopefully, this work will help make up this deficit. As for the concept of systems, similar to how numbers and algebraic variables are theoretically abstracted from the physical world, systems can also be proposed out of any and every object, event, and process that exist in nature. And although both the concepts of numbers (and numerical variables) and systems are abstracted out of the same world, they represent the world from two different and harmonizing angles. For instance, when a firm is seen as a collection of parts with their relationships ignored, then the firm can be described by using numbers, such as n employees, m offices, $x of venture capital investments, etc., and some superficial relationships between these numbers. However, to investigate any business firm appropriately in terms of managerial decision-making, the firm needs to be seen as an organization with deeply embedded culture, strictly followed philosophical values, and day-today routines of operations, among others. It is these organizational relationships that the firm exists both physically and intellectually. That is, most problems of managerial decision-making are essentially about organizations or systems, be they individuals, seen as economic agents whose behaviors are dictated by their personal value systems, firms, markets, industries, economies, etc. In other words, behind each organization, such as a business firm, a market, a regional economy, etc., there is an abstract, theoretical system within which the relevant whole, component parts, and their interconnectedness are emphasized. As a matter of fact, it is because of these interconnected whole and parts that the totality is known as a firm, market, industry, economy, etc. Speaking differently, when internal structures can be ignored, numbers and algebraic variables can be very useful in terms of describing numerical relationships without touching the essential concept of organization; otherwise the world consists of dominant systems (or structures or organizations).

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1 Facing the Challenge Holistically

Even though the concepts of numbers and systems share the same origin – the natural world – they represent two very different aspects of the world. The former is small scale and local, while the latter large-scale organizational. More importantly, numbers exist only post existence. That is why using number-based theories to make predictions has not been very successful. In other words, when one uses post-event evidence to predict the appearance of a not-yet-occurring event, he/she is doomed to be not very successful. On the other hand, systems emerge at the same time when physical or intellectual existence comes into being. That is the very reason why the methodology of systems is more appropriate than all theories developed on numbers and variables for the investigation of economic entities when their internal structures cannot be ignored. When studies of various kinds of systems and organizations are put together as an area of knowledge, we have the so-called systems science. This science investigates the systemhood of all things, be they lifeless objects, social organizations, or evolutionary processes. That is what makes it different from the traditional science that is classified by the thinghood it studies. With systems science and the traditional science coexisting, it gives rise of a two-dimensional spectrum of knowledge, where the traditional science constitutes the first dimension and the systems science forms the genuine second dimension (Klir 2001). Speaking differently, systems research focuses on those properties of systems and associated problems that emanate from the general notion of structures and organizations, while the division of the traditional science has been done largely on properties of particular objects. Therefore, results of systems science naturally transcend all the disciplines of the traditional science, making the existing disciplinary boundaries irrelevant and superficial. The importance of this second dimension of knowledge cannot be in any way over-emphasized. By making use of this extra dimension, the exploration of knowledge has gained additional strength in terms of the capability of solving more problems that have been challenging the very survival of the mankind since the beginning of time. Such strong promise that systems research holds relies materialistically on the particular speaking language and intuition behind systemic logic thinking – the systemic yoyo model (Lin 2007), Fig. 1.2, similar to how the Cartesian coordinate system plays its role in the development of the traditional science (Kline 1972). Specifically, what this systemic yoyo model says is that any system of concern, be it a physical entity or an intellectual thought, be it tangible or intangible, a living being, an organization, a culture, a civilization, etc., can be seen as a kind of realization of a certain multidimensional spinning yoyo with an eddy field around. It stays in a constant spinning motion as depicted in Fig. 1.2a. If it does stop its spinning, it will no longer exist as an identifiable system. What Fig. 1.2c shows is that due to the interaction between the eddy field, which spins perpendicularly to the axis of spin, of the model, and of the meridian field, which rotates parallel to axis of spin, all the materials that actually return to the input side travel along a spiral trajectory. In terms of why each system possesses such an abstract structure, it can be seen from different angles (for details see discussions in Chap. 2). Speaking briefly, on the

1.2 The Systems Approach

9

Fig. 1.2 The systemic yoyo model shown in three-dimensional space. (a) Eddy motion model of the general system. (b) The meridian field of the yoyo model. (c) The typical trajectory of how matters return

basis of the blown-up theory (Wu and Lin 2002), a general theory of development and evolution, and the discussion on whether or not the world can be seen from the viewpoint of systems (Lin 1988; Lin et al. 1990), the concepts of inputs, outputs, and converging and diverging eddy motions are coined together in the model shown in Fig. 1.2 for each thing and every system imaginable. That is, each system is a multidimensional entity that spins about its axis. If we fathom such a spinning entity within the three-dimensional space in which we live, we will have a structure as artistically shown in Fig. 1.2a. The input side pulls in all things, such as materials, information, energy, profit, investment, etc. After funneling through the “neck,” all things are spit out in the form of outputs. Some of the things, spit out from the output end, never return to the other side and some will (Fig. 1.2b). For the sake of convenience of communication, such a structure as shown in Fig. 1.2a is referred to as a yoyo due to its general shape. As expected, this yoyo model has successfully played the role of intuition and playground for scholars who investigate the world and explore new knowledge holistically, just as what the Cartesian coordinate system did for the traditional science (Lin Y 2009; Lin and Forrest 2011; Forrest 2013, 2014; Forrest and Tao 2014; Ying and Forrest 2015). In particular, this yoyo model of general systems has been successfully applied in the investigation of Newtonian physics of motion, the concept of energy, economics, finance, history, foundations of mathematics, small-

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probability disastrous weather forecasting, civilization, business organizations, and the mind, among others. Along this same line of logic, in this book we will use this model as our intuition to establish our conclusions.

1.3

Scientific Irregularities: The Norm of Business Life

With the business world being increasingly globalized, many well-established companies have either disappeared or become irrelevant (McGrath 2013). Underneath such drastic changes in the business landscape is how forces of competition have been reshaping the strategies companies design and employ (Porter 1979). In other words, when a firm is incapable of forecasting and accordingly making appropriate adjustments to the fast-changing trends or paradigm shifts, the firm will definitely exit the market soon. In this regard, there are plenty of sad stories, such as those of Kodak, Xerox, and Motorola’s one-time dominance in the analog cellular telephone business (Barker 1993). In the present business world, clinging to established competitive advantages and accustomed routines of operation is no longer viable. That is, managers and entrepreneurs have to be futuristic and visionary, which generally requires them to be confident and narcissistic in their actions that correspond to their predictions of the future (Navis and Volkan 2016). They are the key for their firms and organizations to stay abreast of the speed of business. In other words, companies that cannot successfully foresee the future and adjust quickly become victims of rapidly shifting business landscapes (McGrath 2013). That is because there are very few blue oceans, as explained by Kim and Mauborgne (2005), whereby there is little to no competition. This realization, for example, was deployed by Cirque du Soleil when they transformed the picture of a circus from animals to acrobatic, nimble human performers. That is the very reason why in the previous section, we stated that managerial decision-making is more or less about predicting such a future that is drastically different from both the past and the present. In this section, from a different and more fundamental angle, we demonstrate why there is an urgent need for the theory of managerial decision-making to go beyond the capability boundaries of the traditional science in general and classical calculusbased methods and statistics-based tools in particular.

1.3.1

Long-Term Expectations and Short-Term Predictions

For illustration purposes, let us use human life as our metaphor. In this regard, no one suspects the accuracy of the following long-term expectation: each person dies sooner or later. However, in life the really significant issue is the short-term or imminent prediction of how and when a person dies, where prediction is defined as the foretelling of the imminent future that is different of the present or the past or both. When attempting to address such problems scientifically, Bergson (1963),

1.3 Scientific Irregularities: The Norm of Business Life

11

Koyré (1968), Prigogine (1980), and OuYang et al. (2001) realize that the traditional science is such a science that is about invariances without involving evolutions of small scales and imminent changes. That explains why the traditional science does not have the ability to foretell immediately forthcoming breakoffs in trends and paradigms in general and disruptive innovations in particular. However, over time things do evolve and business landscapes do shift disruptively. Therefore, there are corresponding laws of evolutions and theories and methods for investigating evolutions that can be used to support managers to make their decisions regarding the future. To meet this challenge, results and methods of the traditional science have been conventionally employed to develop various theories and methods for forecasting purposes although no part of the traditional science essentially involves evolution, leading to not quite satisfactory outcomes. Such attempts lead to the appearance of the concept of small-probability information or the so-called irregular information (Lin and OuYang 2010), which has not been addressed by the traditional science developed on the ideals of quantitative regularization and stabilization of time series. In fact, as a philosophical problem, the concept of irregular information touches on the central problem of Lao Tzu (time unknown), “Any Tao that can be explained is not the Tao.” It exists exactly at the very central problem that the traditional science has walked away from – the essence of the multiple varieties of the natural world – when it pursues after the generality and uniformity by using quantities. For further details, see Chap. 1 (Lin and OuYang 2010). So, efforts need to be devoted to investigate ways of thinking, tools for intuition, and methods of reasoning beyond the well-developed quantitative system of the traditional science in order to help decision-making managers and entrepreneurs to effectively predict the future. In the Eastern world, especially in China, knowing has been facilitated by using the epistemology of structural transformations of mutual interactions since thousands of years ago. People there place more emphasis on the materialistic morphologies caused by blocked movements and relevant changes in the attributes of moving things. To this end, the “Book of Changes” (Wilhalm and Baynes 1967) is the classic of evolution theory and has been employed as the standard of knowing and understanding. When facing a challenge, Chinese people’s first reaction is to analyze how things and/or events constrain each other mutually, leading to theories and action plans of mutual existences and constraints. Speaking differently, the essence of the traditional science is a collection of formal analyses based on quantities. So, each analysis has to comply with the rules of quantitative calculus. On the other hand, when analyzing evolutions through studying movements, one needs to be clear about the things and events involved instead of merely the extracted quantities. That explains why the quantitative calculus most likely does not hold true when employed to study evolutions and interactions of organizations and why using such methods of invariances for decision-making managers to investigate changing events and social processes has to face difficulties and challenges. As for the currently available principles and techniques of prediction, which are established on the basis of the traditional science, they are essentially versions of live

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monitoring what has already happened or is happening instead of predicting what is about to occur. This fact is well illustrated in Laplace’s statement (Kline 1972): “If I know the initial value, I can tell you everything about the future,” and represents a serious challenge facing decision-making managers and entrepreneurs who need to know when and how the next major disruptive technology appears. Fortunately, because of the development of high-speed computers, we are able to directly digitize observational data and handle irregular information that cannot be effectively dealt with before by using quantitative means. This end helps us uncover a passage to connect modern technology with the ancient science and methodology. As a consequence, scholars will be able to propose the epistemological foundation of evolution science on which decision-making managers and entrepreneurs will be able to analyze evolving things, events, and processes (Lin and OuYang 2010).

1.3.2

The Essence and Origin of Quantities

Pythagoras of the ancient Greece believed that numbers are the origin of everything; numbers and their properties represent the key for comprehending all things in the universe. Such belief eventually influenced the development of the traditional science as the religious foundation (Kenny 2012). Correspondingly, Zhan Yin of ancient China, who lived in the time of warring states, pointed out that there are things numbers cannot describe (Qu 1985). That explains how later generations of Chinese people treated numbers and the reason why they did not admire numbers nearly as highly as Westerners. It is clear that quantities cannot appear before events or existence, representing merely post-event formal measurements or records. This fact reduces the hope of using quantities to predict the occurrence of future events and existences. Specifically, numbers dwell in Cartesian coordinate systems (also known as Euclidean spaces) as measurements of the imaginary linear axes. That leads to the issue of unboundedness of the quantitative 1. However, the natural world is curved and never reaches this quantitative 1. This fact reveals the limitation of quantitative analysis and where the quantitative reasoning and systems thinking are different epistemologically. To know the world and to predict what is going to happen in the near future through analyzing movements systemically, one has to consider the attributes and systemic structures of moving things, such as functions, locations, internal organizations, etc., and individual things’ specifics, and how they interact with one another. Speaking in the contemporary language of science, interactions of things and organizations of parts belong to non-inertial systems. That is the difference between how the traditional science uses quantities and inertial systems of the first push and how systems science employs structures and organizations as the target of focus and non-inertial systems of the second stir (Lin and OuYang 2010). Because the movements of things with and without internal structures are of different characteristics, the epistemologies and methodologies needed to deal with these movements have to

1.3 Scientific Irregularities: The Norm of Business Life

13

be different. The formality and generality of quantities offer methods – such as calculus, statistics, and consequent theories – of analysis for investigating movements and oscillations of things without internal structure. However, when systems are concerned with, which is where decision-making managers come into play, quantities have experienced great difficulties. Even so, these two collections of problems, one is about the movements and oscillations of invariant things and the other interactions of evolutionary things, can be naturally associated with each other by using the concept of rotational stirring energies or the systemic yoyo model, leading to the overall system of the two-dimensional science (Lin 2009). The fundamental form of movement of things, be they physical, intellectual, or economic, is rotation (Lin 2009). Vilhelm Bjerknes (1898) was the first person in the traditional science who pointed out that the fundamental form of fluids’ (either atmospheric or oceanic) motion is rotation (in essence, solids also mainly move in the form of rotation). This result was seen by Saltzman (1962) as a major betrayal to the traditional science. From this fundamental, rotational form of movement of things, the concepts of stirring energy and second stir (Lin and OuYang 2010) and the yoyo model (Lin 2009) are introduced. That indicates that since systems science deals with organizations and interactions of organizations and the systemic yoyo model involves the significance and effects of organizational “rotations” (Chen et al. 2005), they are expected to provide support for decision-making managers and entrepreneurs to resolve the problem of how to adequately comprehend the meaning of irregular information in their efforts of making important decisions (OuYang et al. 2001; OuYang and Chen 2006).

1.3.3

Irregular Information and Systems Science

In particular, to resolve this problem of adequately comprehending the meaning of irregular information, let us first look at the concept of information. Although this concept is closely related to people’s daily lives, it was Shannon (1949) who first defined information by using probability and relevant manipulations. Since then, this concept has been associated with uncertainty, intensifying the scientific debate between determinacy and indeterminacy within the world of learning. The school of determinacy employs stability (or continuity and differentiability) to eliminate specifics of each specific application, and that of indeterminacy uses stable time series to get rid of small-probability events. So, from different directions these schools reach the same destination: specifics and complexities of particular events and processes are eliminated in order to obtain the desirable generality. However, the practical chance for obtaining the desired generality, just as averages, is smaller than that of obtaining any small-probability event. In other words, irregular information cannot be ignored by decision-making managers and entrepreneurs just and simply for the reason that quantities cannot handle it, although neither of the schools, in terms of use value, can deal with irregular information successfully. That motivates the world of learning to comprehend events and processes (or systems) and address

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the issues of how to understand irregular information and how to practically apply it to make more reliable predictions. Through analyzing a huge amount of real-life cases, Lin and OuYang (2010) find that irregular information is closely related to collisions of rotational fields of things, and by purposely introducing irregular information, they are able to predict transitions in forever changing trends of (weather) development. Hence, they conclude that irregular information appears for reasons, representing the dynamic mechanism of evolving structures and that its importance goes beyond the formality of quantities and directly involves the attributes and properties of the underlying systems. The current effort of digitization employs the name of quantities to go beyond quantification, signaling the fact that human knowledge of nature, both physical and intellectual, has entered the era of events and processes (or systems thinking). In principle, irregular information is about a change that has occurred within the underlying systemic evolution, while digitization provides a new methodology for dealing with the change and for what is expected to come next. Digitization constitutes another methodology different of those of dynamic equations and statistics. It makes such ancient method of knowing by using figures more refined than ever before, marking a new development in the scientific system of knowing the world through analyzing the underlying systems. Because of the duality of rotations and their different spinning directions, at the same time when irregular information is created or observed, damages in the original systems are also caused. So, in managerial decision-making, there is an urgent need to reconsider the business significance of time and irregular information. Hence, the concept of rotation makes use of the structural digitization of information and helps managers and entrepreneurs to walk out of the realm of quantities and enters into that of organizations and non-inertial systems (or systems science). The history has shown that the development of knowledge comes from calls of unsettled problems and challenges. So, in investigations of business scenarios, the first issue of primary importance is to clearly understand the essence of the question being considered, while the issue of which theories potentially apply is secondary. Managers and entrepreneurs have to avoid the habit of fitting indiscriminately certain methods and theories without considering the attributes of the question in hands. As problems lead to the development of knowledge, the appearance of the problems challenges those known theories that can no longer resolve new problems and the accepted system of thoughts. The traditional science has not produced managers and entrepreneurs who can foretell the future effectively with reliability. Specifically, present scholars who teach and investigate predictions and decisionmaking cannot provide meaningful ways to foretell when and how drastically different events will occur and when and how disruptive technologies will appear. Therefore, no matter how this situation is seen, it has to be a serious problem that needs to be resolved urgently for decision-making managers and entrepreneurs. There is no doubt that from the first push of the traditional science to the second stir of the systems thinking, not only will science itself face the problem of transformation but more importantly also will our very way of knowing have to go through fundamental changes. In this book, we make it clear that the concept of

1.4 Major Contributions of This Work

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systems is more adequate than quantities when managers and entrepreneurs need to make their decisions, because quantified events and processes do not really comply with the rules of quantitative calculus, events and processes are not random, and that issues decision-making managers and entrepreneurs face in their effort to prediction the future challenges the traditional science and the relevant epistemological propositions. When the traditional science is enjoying extracting eternal (invariant) information out of events, the systems research collects the information of change from events and processes in order to see how the business world actually evolve over time. Knowledge exploration is about challenging the accepted wisdom; forever newer technologies are developed to provide convenience and improvement and save lives. The corresponding areas of predicting what is forthcoming is about how to combine challenge and save together so that both of these demands can be met simultaneously. When facing imminent crises or challenges, decisions have to be made instantly and whether or not they are correct decisions will be studied later. That illustrates the practical importance and use value of the systemic yoyo model, although the model also represents a significant breakthrough in theory. In short, what is discussed in this section explains why small-probability information is often seen as irregular, if managers and entrepreneurs still look at the business world from the angle of the traditional science. In such a case, scientific irregularities will become the norm of their business lives.

1.4

Major Contributions of This Work

The contributions of this book to the existing knowledge can be, respectively, seen at (1) the level of particular topics and (2) the level of methodology. In this section, we will describe the contributions from these two different angles. First, at the level of particular topics, this volume addresses the following practically significant and theoretically important open questions, among others: • What characteristics of a market indicate the market invitation for new competition and innovation? • How can a general theory on the dynamics of firm competitions within a market be developed so that it can be readily used to explain how interactions among incumbent firms and between the incumbents and entrants shape industry logic and to help corporate leaders understand entrant-incumbent relations so that decisions on either market entry timing or how to deal with entrants for the incumbents can be made with better precision and preparation? • How can one explain plausibly and deductively what is happening with the increasingly accelerating changes behind magnificent successes and devastating failures taking place in the present business world? • Has the growth of using technology created a business environment where once sustainable competitive advantages have become transient and short-lived?

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• Are there necessary steps that a firm needs to go through in order for the firm to potentially ready itself for successfully riding waves of transient competitive advantages? • What are the main strategic tactics that underlie the innovative activities of a manufacturing firm? • How do manufacturing firms’ culture, structure, and leadership affect the innovativeness of the firms? • Although in the past 100 plus years many countries from around the world spent great amounts of energy and enormous efforts to modernize and to industrialize themselves, they failed to develop their self-sustaining momentum of economic growth. So, what are the key steps necessary for a nation, no matter how backward it is in any chosen standard, to succeed with such desirable objective? • Due to the ongoing globalization of economies from around the world, international business activities and performance of firms have been a hot topic of research in recent years. However, both empirical and theoretical works suffer from serious limitations and are not sufficiently reliable for practical purposes. Correspondingly, the natural question this book attempts to address is: Can a general systemic theory be developed so that it makes reliably inferences, develops guidelines for practical purposes, and avoids the problematic weaknesses in the previous works? • Within the hot topics of international trade, the issue of dumping and antidumping is still poorly understood, where mechanisms of antidumping have been most often used for protectionist purposes and for harassing trade partners. This volume takes a neutral stand between exporting and importing nations in order to reveal how exporters and importers actually interact with each other. Corresponding to these individual questions, this book establishes: 1. A sufficient and necessary condition under which an existing market invites for new competitions and innovations. 2. A theory on the dynamics of firm competitions within a market, practically useful for corporate leaders to understand entrant-incumbent relations so that decisions on either market entry timing or how to deal with entrants can be made with better precision and preparation. 3. A theory on the fast-evolving business landscape, where markets change faster and consumers become less patient than ever before. This theory can plausibly and deductively be used to explain what is happening in the increasingly globalizing economy. 4. A list of four necessary conditions for a firm to meet and to go through in order to prepare itself for successfully riding waves of transient competitive advantages. 5. A general explanation for why a firm needs to have clearly stated missions and a long-term, unwavering ambition, on which all the 16 strategy variables, identified by various scholars in the literature, are classified into primary and secondary forces underneath the innovativeness of a manufacturing firm, where the secondary forces naturally appear when the primary ones are established first.

1.4 Major Contributions of This Work

17

6. A theory on how philosophical and value systems are formed for individuals and organizations. This theory is then employed to study how organizational culture is formed, why mission and ambition are two powerful unifying forces of organizational culture, and then why, theoretically, organizational culture represents a significant determinant of the innovativeness of a firm, etc. 7. A list of necessary steps for an impoverished agrarian nation to develop its selfsustained momentum of economic growth, while this work also addresses the question of what can go wrong in its noble effort. 8. A general theory of international trades that provides brand new insights, integrates the findings already reported in the literature, and provides reliable guidelines for applications and future research. At the same time, this theory avoids all the pitfalls and weaknesses of the previous works. 9. An intuitive understanding of the phenomenon of dumping and antidumping by analyzing the competition between one importing nation and one exporting nation within the context of the world economy. And very specific conditions are developed for when antidumping measures work, when they only work partially, and when they do not work at all. Correspondingly, specified are conditions for when dumping schemes will work effectively, partially or not at all. Second, at the level of methodology, the following is the major contribution this work makes to the existing literature: it shows that instead of inductive reasoning, deductive reasoning needs to be employed to produce scientifically sound theories and conclusions. By inductive reasoning, it means the exclusively used logic of thinking in the literature in areas related to this work, where either anecdotes or data mining or both are employed to draw conclusions. Although such conclusions are mostly written in general terms, they are known in science to be not reliable or not scientifically sound. To this end, this book develops and establishes theoretically sound results by introducing logic reasoning, systems thinking, and systemic yoyo model to the area of managerial decision-making. By doing so, this work shows how empirical conclusions, drawn previously and inductively on either anecdotes or data mining by various scholars, can be deductively established, disapproved, or improved. Scientifically speaking, such conclusions are more reliable than those conjectured on the basis of either anecdotes or data mining or both. Another commonly employed method of reasoning in the existing literature of managerial decision-making is written statements. In comparison, although such statements are articulations of logic, they are very different from mathematical equations and systemic expressions, which also forms of expressions of reasoning. In particular, on their own, even the most logical and precise written arguments are often inconclusive because they are linear and sequential, while most real-life situations of decision-making involve nonlinearity, complexity, and uncertainty. Therefore, written arguments cannot control for simultaneous effects of multiple arguments in combination; and they are generally unable to pinpoint out the optimal outcome – “equilibrium” – out of many. On the other hand, even though mathematics and systems science are also languages, they are precise and capable of handling

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nonlinearity, complexity, and uncertainty better than written arguments. They feature complex claims or arguments in their totalities while controlling for simultaneous effects of multiple, interacting variables. They provide technical procedures to pinpoint out the optimal equilibrium. Like others before us, in this book we use both mathematics and systems science to rigorously derive the main results. So, in terms of methodology and the reliability of conclusions, this end represents the main contribution of this work to the existing literature at the level of methodology. Speaking differently, because of the specific methodology employed, this work is able to convert many indecisive conclusions and dilemmas uncovered by empirical studies into definite theoretical results either positively or negatively. In particular, the reason why anecdotal analysis does not lead to general conclusions can be vividly illustrated by the following example. The anecdotes 02 ¼ 0 and 12 ¼ 1 are well-known. From these two instances, can one conclude that n2 ¼ n, for any natural number n? Of course not. In fact, in mathematics, people have constructed scenarios where an incorrect conclusion seems to be correct based on many specific anecdotal cases. As for why data mining can lead to non-existing facts, the following example makes a perfect explanation. Let X be a random variable defined below: X ¼ 1 when a fair coin flipped once shows the head; and X ¼ 0, when the flipping of the coin shows the tail. Then the expected value of this random variable is E ðX Þ ¼ 50% ∙ 1 þ 50% ∙ 0 ¼ :5, where the variable X does not take this value 0.5 according to the implicit assumptions. At this junction, it needs to be noted that expectations are widely used in managerial decision-making. As for why theoretical modelling, developed on calculus-based methods, also leads to unreliable conclusions is because in the literature, what is commonly done is fitting the situation of concern into an available model by modifying the situation. For example, mutually substitutable goods that are available in the marketplace are modelled as a continuum; and existing firms that produce the goods are modelled as another continuum in order to fit the situation of concern into a model of differential calculus. When this scholarly practice is pointed out, one naturally asks: Should the study be the other way around: modify the tool to fit the situation of concern? In fact, all the listed and related unlisted issues of methodologies are exactly the reason why this book focuses on the thinking logic and methods of systems science, because Lin and OuYang (2010) have detailed the reasons why these issues of methodology can easily and definitely lead to misleading conclusions or mixed non-conclusions. In short, comparing what is developed in this book and what has been established in the literature, this work definitely enriches the relevant knowledge at the height of theoretical abstraction with a much wider range of practical applicability.

1.5 Organization of Contents in This Book

1.5

19

Organization of Contents in This Book

This book develops a cohesive general theory of managerial decision-making. Other than Chap. 1 that introduces the reader to this work with all the related background information, the entire volume consists of five parts and ten additional chapters. The first part presents the necessary basics of systems science and theoretical foundations for the rest of the book. In particular, this part consists of three chapters. Chapter 2 looks at the concept of systems, the systemic yoyo model, and some elementary properties of systems. Chapter 3 investigates how incumbent firms conduct their business while attempting to protect their existing turfs and prevent newcomers from entering their market territory. Chapter 4 continues what is developed in the previous chapter and looks at the issue of market entry of micro entrants and market partition and how these micro entrants and incumbent firms actually interact with each other. Part II studies the present era of transient competitive advantages, which is drastically different from the past where competitive advantages tend to last. This part consists of two chapters. In particular, Chap. 5 looks at what is really happening and why by addressing a few related questions, such as why markets have been evolving faster and consumers become less patient than ever before, why sustainability is replaced by transiency, and what will be the one organizational essence that can help a firm to successfully make its paradigm shift. Chapter 6 considers the issue of how to successfully ride waves of transient competitive advantages by looking at both internal and external competitions, necessary steps a firm need to go through to adapt to the new era. Part III classifies internal factors, empirically identified by many scholars in the past, that affect the innovativeness of a manufacturing firm into primary factors and secondary ones, where the leadership only need to focus their effort and investment on the former, while the latter will naturally follow. This part consists of two chapters. In particular, Chap. 7 addresses the effects of strategies by formally defining the concept of innovation for manufacturing firms and by addressing the importance of a clearly stated mission. Chapter 8 analyzes the impacts of a firm’s culture, structure, and leadership. Part IV looks at a very important question facing developing countries: How can a developing nation develop its nationally self-sustaining momentum of economic growth? This part is made up of one chapter. This chapter theoretically develops a practically useful procedure for any developing nation that desires to develop its selfsustaining momentum of growth to follow. And then the chapter points out places things can potentially go wrong in a developing country’s effort to develop its selfsustaining momentum. Part V presents issues regarding the choices of going international or staying domestic for business firms. This part consists of two chapters. In particular, Chap. 10 studies these choices and related firm performances by looking at the general performance status of domestic-only firms and what kinds of firms may go international before developing a general theory of international trades. Chapter 11 considers a presently hot issue of trade dumping and antidumping. After a series of

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general propositions are established, the chapter employs the results to analyze the trade relationship between China and the USA. At the conclusion of this book, an appendix is given, where rigorous mathematical foundations are presented for the systemic yoyo model. Because of the way the results in this book are established, we expect that scholars, decision-making managers, and entrepreneurs will find this book timely and beneficial in their works. And to make this book reader friendly, each chapter is constructed as self-contained as possible so that the reader does not have to flip through the pages to look up the relevant concepts or results. Acknowledgment The following colleagues have contributed to the success of this volume. In particular, Jeananne Nicholls and Kurt Schimmel, School of Business, Slippery Rock University (USA), wrote Chap. 1. Sifeng Liu, Department of Management Science and Engineering, Nanjing University of Aeronautics and Astronautics (China), wrote Chap. 2. Jeffrey Yi-Lin Forrest, John Buttermore, and Theresa Wajda, School of Business, Slippery Rock University (USA), wrote Chap. 3. Jeffrey Yi-Lin Forrest, School of Business, Slippery Rock University (USA), and Gideon D. Markman, Management Department, Colorado State University (USA), wrote Chap. 4. Jeffrey Yi-Lin Forrest and Pavani Tallapally, School of Business, Slippery Rock University (USA), and Yang Yingjie, Centre for Computational Intelligence, De Montfort University (UK), wrote Chap. 5. Jeffrey Yi-Lin Forrest and Jennifer Nightingale, School of Business, Slippery Rock University (USA), wrote Chap. 6. Jeffrey Yi-Lin Forrest and Sunita Mondal, School of Business, Slippery Rock University (USA); Reginald Tucker, Stephenson Department of Entrepreneurship and Information Systems, Louisiana State University (USA); and Canchu Lin, School of Business, Carroll University (USA), wrote Chap. 7. Jeffrey Yi-Lin Forrest, School of Business, Slippery Rock University (USA); Reginald Tucker, Stephenson Department of Entrepreneurship and Information Systems, Louisiana State University (USA); Canchu Lin, School of Business, Carroll University (USA); and Sunita Mondal, School of Business, Slippery Rock University (USA), wrote Chap. 8. Jeffrey Yi-Lin Forrest, School of Business, Slippery Rock University (USA); Huachun Zhao, School of Economics and Finance, Jiangxi Normal University (China); and Lawrence Shao, College of Business, Slippery Rock University (USA), wrote Chap. 9. Jeffrey Yi-Lin Forrest, School of Business, Slippery Rock University (USA); Mikael E. Trebing, Research Department, Federal Reserve Bank of Philadelphia (USA); Anindya Chatterjee, School of Business, Slippery Rock University (USA); and Joachim Wagner, Institute of Economics, Leuphana University of Lueneburg (Germany), wrote Chap. 10. Huachun Zhao, School of Economics and Finance, Jiangxi Normal University (China), and Jeffrey Yi-Lin Forrest and Benjamas Jirasakuldech, School of Business, Slippery Rock University (USA), wrote Chap. 11. Jeffrey Yi-Lin Forrest, School of Business, Slippery Rock University, wrote Appendix. And collectively, Jeffrey Yi-Lin Forrest, Jeananne Nicholls, Kurt Schimmel, and Sifeng Liu organically connected all the individual chapters together into a holistic body of theory.

Bibliography Barker, J. A. (1993). Paradigms: The business of discovering the future. New York: Harper Business. Bauer, S. W. (2015). The story of western science: From the writings of Aristotle to the big bang. New York: W. W. Norton & Company.

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OuYang, S. C., & Chen, G. Y. (2006). End of stochastics and quantitative comparability. Scientific Research Monthly, 14, 141–143. OuYang, S. C., Lin, Y., Wu, Y., & Xiao, T. G. (2001). Physics properties of Schrödinger equation and excessive expansion of the concept of wave motions. Advances in Systems Science and Applications, 1, 112–116. Porter, M. E. (1979). How competitive forces shape strategy. Harvard Business Review, 57, 137–145. Retrieved September 27, 2017 from https://hbr.org/1979/03/how-competitiveforces-shape-strategy. Porter, M. E. (1985). Competitive advantage: Creating and sustaining superior performance. New York: Free Press. Prigogine, I. (1980). From being to becoming: Time and complexity in the physical science. San Francisco: W. H. Freeman and Company. Qu, Y. (1985). The songs of the south: An anthology of ancient Chinese poems by Qu Yuan and other poets (David Haykes, Trans.). London: Penguin Classics. Rostow, W. W. (1960). The stages of economic growth: A non-communist manifesto. Cambridge: Cambridge University Press. Saltzman, B. (1962). Finite amplitude free convection as an initial value problem. International Journal of Atmospheric Sciences, 19, 329–341. Shannon, C. E. (1949). The mathematical theory of communication. Champaign, IL.: Illinois University Press. Stengel, J. (2011). Grow: How ideals power growth and profit at the world’s greatest companies. New York: Crown. von Bertalanffy, L. (1924, May). Einführung in Spenglers Werk. Literaturblatt Kolnische Zeitung. Wagner, J. (2012a). Exports, imports and profitability: First evidence for manufacturing enterprises. Open Economies Review, 23, 747–765. Wagner, J. (2012b). International trade and firm performance: A survey of empirical studies since 2006. Review of World Economics, 148, 235–267. Wen, Y. (2016). The making of an economic superpower: Unlocking China’s secret of rapid industrialization. Singapore: World Scientific. Wilhalm, R., & Baynes, C. (1967). The I ching or Book of changes (3rd ed.). Princeton, NJ: Princeton University Press. Wu, Y., & Lin, Y. (2002). Beyond nonstructural quantitative analysis: Blown-ups, spinning currents and modern science. River Edge, NJ: World Scientific. Ying, Y. R., & Forrest, J. Y. L. (2015). Capital account liberation: Methods and applications. New York: CRC Press, an imprint of Taylor and Francis. Zachary, M. A., Gianiodis, P. T., Payne, G. T., & Markman, G. D. (2015). Entry timing: Enduring lessons and future directions. Journal of Management, 41(5), 1388–1415.

Part I

The Theoretical Foundation

Chapter 2

Basics of Systems Science

To make this book self-contained, this chapter introduces the basics of systems science necessary for the reader to understand all the conclusions developed in the rest of the book. This chapter is organized as follows: Section 2.1 introduces the reader to the concept of systems and its related history. Section 2.2 studies the basics of the systemic yoyo model and where it is from. Section 2.3 looks at some elementary properties of the yoyo model.

2.1

The Concept of Systems

Each system is fundamentally of the following characteristics: it consists of a set of objects, a set of relations between the objects, and a structure of layers, and it interacts with its environment. The idea of systems has been widely employed in the ancient medicine about 5000 years ago at the time of Yellow Emperor (Zhu 2001). And in terms of modern science, this idea can be traced to at least as early as the one-element Ionians (624–500 B.C.). In their search for order in the constantly changing world, Ionians employed an approach of naturalistic and materialistic bent. They pursued causation and clarifications through using the eternal working of things instead of any divine, mythological, or supernatural intervention. These Ionians believed for one reason or another that all things have their origin in a single knowable element: water, air, fire, or some indeterminate, nebulous substance (Perlman 1970). Throughout history the idea of systems has been used by many great thinkers to study different problems in their then-appropriate languages. For example, Aristotle’s statement that “the whole is greater than the sum of its parts” represents a basic problem of modern systems science, reflecting the fact that the concept of systems had been felt through ages. As a profound thinker of the fifteenth century who linked medieval mysticism with the first beginnings of modern science, Nicholas of Cusa introduced the notion of the coincidentia oppositorum. As a co-founder © Springer Nature Switzerland AG 2020 J. Y.-L. Forrest et al., Managerial Decision Making, https://doi.org/10.1007/978-3-030-28064-2_2

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2 Basics of Systems Science

of calculus, Leibniz studied the hierarchy of monads that looks quite like the concept of layered systems of modern systems science. As the well-known author of the psychophysical law, Gustav Fechev particularized supra-individual organizations of higher order than the usual objects of observation in the way of the naive philosophers of the nineteenth century and romantically anticipated the ecosystems of modern parlance. For more related history, see (von Bertalanffy 1972). Although the idea of systems had been used theoretically and practically throughout history, the concept of systems was not formally introduced until the second decade of the twentieth century when von Bertalanffy (1934) wrote: Since the fundamental character of the living thing is its organization, the customary investigation of the single parts and processes cannot provide a complete explanation of the vital phenomena. This investigation gives us no information about the coordination of parts and processes. Thus the chief task of biology must be to discover the laws of biological systems (at all levels of organization). We believe that the attempts to find a foundation for theoretical biology point at a fundamental change in the world picture. This view, considered as a method of investigation, we shall call “organismic biology” and, as an attempt at an explanation, “the system theory of the organism.”

Here, the concept of systems was officially introduced. After nearly 100 years of theoretical investigations and practical tests, this concept has been widely accepted by scientists in all disciplines (Blauberg et al. 1977). To establish a unified theoretical foundation for all seemingly different approaches of systems analysis, developed in various disciplines, Mesarovic, in the early 1960s, introduced the formal definition of (general) systems, based on Cantor’s set theory, as follows (Mesarovic and Takahara 1975): A (general) system S is a relation on nonempty sets Vi: S


Y fV i : i 2 I g

ð2:1Þ

where I is an index set and elements in the sets Vi are the elements of the system S. To make this definition of systems more symbolically operational for the purpose of developing a practically useful systems theory, Lin (1987) defines the concept of general systems as follows: S is a (general) system provided that S is equal to an ordered pair (M, R) of sets. That is, symbolically, we have S ¼ ðM, RÞ

ð2:2Þ

where R is a set of some relations on the set M. Each element in M is called an object of the system S, and M and R are called the object set and the relation set of S, respectively. Such a structure of general systems unifies objects, which are seen as isolated in the traditional science, the objects’ relations, which are the so-called organizations in the area of managerial decision-making, and the structure of layers, which corresponds to the hierarchies of organizations. Here, elements in either the nonempty sets Vi, i 2 I, in Eq. (2.1) or the object set M in Eq. (2.2) are the objects of the system, the subset S in Eq. (2.1) or each element in the relation set R of Eq. (2.2) represents a relation between the system’s objects, and the elements of the system can be systems

2.1 The Concept of Systems

27

too. By using such idea of layers inductively, we can see that an element S1 of the system S can be a system, an element S2 of the object system S1 can again be a system, etc. At this junction, a natural philosophical question arises: Can this process of layers continue on forever? If the answer to this question is “yes,” then the conclusion that “the world is infinitely divisible” will follow! If the answer is “No,” it will mean that the world is made up of fundamental elements, if everything in the universe can be seen as a system. For the relevant history to this end, see (Moore 1990) and listed references there. By considering the interrelationship between a systems and some of its environments of, Bunge (1979) furnished a model of systems as follows: For a nonempty set T, the ordered triple W ¼ ðC, E, SÞ

ð2:3Þ

is a system over T if and only if C and E are mutually disjoint subsets of T and S is a nonempty set of relations on C [ E, where C and E are called the composition and an environment of the system W, respectively. Philosophically, Klir (1985) defined the concept of general systems as follows, which contains the most general meaning of the concept as originally posted by von Bertalanffy: A system is what is distinguished as a system.

Since 1976, Xuemou Wu and his followers have established a good number of different theories under the name “pansystems.” The so-called pansystems analysis represents a new research of multilevels across all known disciplines. This analysis deals with general systems, relations, symmetry, transformation, generalized calculus, and shengke (means survival and vanquishing), which collectively are known as the emphases of pansystems. Based on studies of these emphases, the analysis and the consequent theory of methodology blend philosophical reasoning, mathematical logic, and mechanical structures into one solid body of knowledge (Wu 1990). The discussion in the previous paragraphs and the great promise systems science seems to hold naturally lead to the following question: Considering the fact that the idea and the working of the concept of systems can be traced all the way back the beginning of the recorded human history, why were the concept of systems and relevant matters not investigated more systematically before but now? The following are two definite reasons. • The development of technology, e.g., computer technology, designs of satellites, climate control of giant buildings, etc., reveals the fact that history is in such a special moment that each discovery of a relation between different areas of knowledge can and has materially produce useful product(s) and consequent economic benefits. • Human knowledge has reached such a level that methodologies adequate for the study of organizations and structures have become available.

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In terms of the magnificent successes of the traditional science, it is Descartes and Galileo who contributed the needed methods of reasoning and administration, where Descartes suggested to divide the problem under consideration into as many small parts as possible and study each isolated part (Kline 1972) and Galileo recommended to simplify the complicated phenomenon of concern into basic parts and processes (Kuhn 1962). In the history of science and technology, these methods of reasoning and administration have been very successfully applied, leading to great victories one by one (von Bertalanffy 1972). Beyond so, these methods are still currently widely employed in research activities of natural and social sciences. Presently, due to the synthesizing tendency of knowledge exploration and the transverse development of technology, scholars and administrators are forced to study problems and issues with many cause-effect chains (i.e., systems), where internal organizations and structures cannot be ignored. So, relevantly adequate logics of thinking and methodologies need to be introduced in order to successfully deal with such problems whose focus is on systems, organizations, and structures. In other words, in the study of such problems, Descartes’ and Galileo’s methods have to be modified and improved, because these methods emphasize on separating the problem and phenomenon of concern into parts and processes instead of being a whole. But according to von Bertalanffy and others in the area of managerial decision-making (e.g., Porter 1979, 1985), we need to recognize that other than a pile of innumerable isolated “parts,” each business decision is more about how these parts work together organically as a whole. The basic characteristic of business decisions is about organization(s) and interactions between the interior and the exterior of the organization(s). Thus, the chief task of managerial decision-making is about knowing the world systemically.

2.2

The Systemic Yoyo Model

When making a managerial decision, the scenario of concern generally involves at least one system, which is open, complex, and giant. The reason why the system is open is because it interacts with other systems in its environment; it is complex because it involves factors that mutually influence each other so that it is most likely difficult or impossible to really tell which factor(s) really causes other factors to appear; it is giant because many factors seem to exert influence simultaneously making related analyses based on methods of the traditional science, be they calculus-based or statistics-based or language-based, difficult to carry out. When the involved complexity turns out to be large scale, it generally makes the already tedious processes of analysis and consequent decision-making even more drastically challenging. In the traditional science, numbers and points on the real number line are one-toone matched so that each number is visually seen as a point on the line while each point on the line is treated as a real number. Because of this one-to-one identification of numbers and points, algebra and geometry are merged into an organic theory,

2.2 The Systemic Yoyo Model

29

where algebra plays the role of method along with logical reasoning and geometry the role of intuition. In this unified theory, one of the most difficult issues for scholars to address is the inherent linearity – each real number is imagined as a point on a straight line. That leads to challenges of nonlinearity. Expanding the idea of identifying numbers with points on the real number line, each quantitative variable is treated as a moving point in the Cartesian coordinate system or in a Euclidean space. Hence, when a great number of such moving points are considered jointly and collectively within a managerial decision-making problem, the level of difficulty of the problem generally goes beyond the bounded aptitude of human mind. Among other challenges, such as the aforementioned linearity, this difficulty stands for one of the core reasons for the theoretical and practical challenge faced in dealing with systems that are open, complex, and giant tangled in most managerial decision-makings. Thus, in terms of managerial decision-making, the following question naturally arises: Can a systemic intuitive background that is different from that of Euclidean spaces be introduced so that such a great number of moving particles and masses of various combinations of these particles can be more conveniently managed while some of the other issues of the Cartesian coordinate system can be avoided?

The reason why the sought-after systemic intuition needs to be different from Euclidean spaces in general and the Cartesian coordinate system in particular is because many recent and age-old challenges, such as complexity, uncertainty, chaos, etc., facing the traditional science are categorically consequences of how Euclidean spaces and the Cartesian coordinate system are composed of linear axes (or straight number lines). In particular, when managers and entrepreneurs employ the methods of the traditional science to investigate business scenarios, they are really using tools developed linearly in fictitious spaces to analyze situations involving various kinds of curvatures; for more in-depth discussion along this line, see Lin and OuYang (2010). And the logic underneath the previous question is that because systems science, as the second dimension of knowledge, studies systemhood of objects, events, and processes, while the traditional science, the first dimension of knowledge, studies thinghood of objects, events, and processes [for details, see Klir (1985)], the difficulty managers and entrepreneurs face when they have to deal with open, complex, giant systems is really one they experience in the first dimension of knowledge. Hence, it is natural for anyone to imagine that there will be a relatively more manageable means in the second dimension for managers and entrepreneurs to carry out their large-scale tasks of decision-making. To geometrically fashion why this logic of reasoning will work out in real life in dealing with systems that are simultaneously open, complex, and giant, let us first imagine a one-dimensional flow, moving along the real number line. If there is a blockage at a point x ¼ a, then the flow has to stop at this location, unless the congestion of the flow at the point can go around the blockage from another dimension. Similarly, let us next imagine a city that is surrounded by a solid, steady city wall in the ancient times (or an enclosed bounded area in the two-dimensional plane). If the wall has no gap, which represents an enclosed curve in the plane, then it

30

2 Basics of Systems Science

is literally impossible for any army to break into the city from within the two-dimensional space. Now, if one launches an air strike by making use of another dimension beyond the known two dimensions, then the forces of his or her side can be easily parachuted into the city by employing this third dimension. Speaking differently, challenges managers and entrepreneurs face when they make decisions in business are mainly created by the fact that they restrict themselves in a lower dimension of knowledge without beneficially making use of systems science, the newly found second dimension of science. When each business decision-making is treated as a system problem-solving (Klir 1985), managers and entrepreneurs can practically confirm that many of their decisions are actually related one way or another, representing different areas of the business landscape, be they large-scale or small-scale, global phenomena, or regional events, that evolve collectively in concert. When one decision that may seem independent and local is changed, many other seemingly unrelated decisions are also revised correspondingly. This fact logically implies that developments of the business world need to be investigated as wholes, and the whole evolution of each and every business organization and structure of concern need to be emphasized in order to understand how business entities evolve both collectively and individually and how they interact with each other. In such evolutions that are seen as wholes, what is critically important for managers and entrepreneurs to know is the discontinuities that commonly exist between the related but relatively independent whole evolutions, Figs. 2.1 and 2.2. In these figures, each of the circular pools stands for an organization or a business firm that is modelled as a systemic yoyo field. So, it is within the zones between the fields that either local patterns or jet streams appear. And it is within these discontinuous and seemingly chaotic regions that transitional changes (or blowups, or

Fig. 2.1 Two wholes interact enharmonically. (a) Some local patterns appear. (b) A jet stream appears. (c) A jet stream is created. (d) Some local pools are created

2.2 The Systemic Yoyo Model

31

Fig. 2.2 Two wholes interact harmonically. (a) Some local patterns appear. (b) A jet stream appears. (c) A jet stream is created. (d) Some local pools are created

disruptive developments), such as the appearance of disruptive technologies or conventional theories, occur. These disruptive developments symbolize how the originally gradual and continuous changes of old structures, such as operational routines, organizational models, management philosophies, competitive advantages, etc., are being obtrusively replaced by new ones. In such a situation, if the relevant scenario is modelled as an abstract mathematical system symbolically, then the established model is generally nonlinear (Wu and Lin 2002); and when the model becomes invalid for certain particular parametric values, the invalidity reflects the destruction of old structures and establishment of new ones. For more in-depth discussion, see (Lin 2009). In terms of the general dynamic system, Newton’s second law of motion states that each acting force is equal to the product of the mass of the object being acted on and its acceleration of motion, where the object that is being acted upon is assumed to have no size and no volume, while the acting object is totally missing. That is, for a manager and an entrepreneur to employ this law to situations of his/her decisionmaking, he/she has to make certain adjustments. For example, the concept of time needs to be different from one company to another; the availability of resources, talents, information, etc. is different from one firm to another. In other words, time is uneven across the landscape of the business world, and the distribution of all other economic variables is also uneven. With all these necessary adjustments made appropriately, it can be shown that Newton’s second law of motion implies that each nonlinear mutual reaction between the uneven internal structures of acting and reacting entities, be they physical objects or business organizations, and between the unevenness of the external forcing entity and that of the entity that is being acted upon, definitely produces eddy motions; for the relevant technical details, see (Lin 2009).

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2 Basics of Systems Science

Other than what is discussed above, the common existence of eddy motions is seen in daily observations of natural phenomena, various occurrences of business events, and laboratory studies from as such small scales as atomic structures to as such huge scales as nebular structures of the heavenly operations. As a matter of fact, theoretical studies (Lin 2009) reveal that eddy motions appear as the consequence of interactions of uneven structures and uneven distributions of resources. Hence, if managers and entrepreneurs treat their decision-making at the height of structural, organizational, and systemic evolutions, then the business situation of concern involves only two forms of motions: clockwise and counterclockwise rotations. To summarize what have been discussed in the previous paragraphs, we can conclude that all structures and organizations in the business world (and in the universe) are in a state of constant, rotational movement. This fact can be actually seen by using the basic knowledge of calculus: because the distribution of resources, such as investments, talents, information, etc., in the business world is uneven, it follows that each business organization possesses an uneven internal structure. Out of such an uneven structure, there naturally exist gradients, a concept of calculus. With gradients, there appear forces. And combined with uneven arms of forces (Lin 2009, p. 31), the carrying materials or organization will have to rotate in the form of moments of forces, Fig. 2.3. In this figure, the function ρ ¼ ρ(x, y, z) stands for the internal structure of the organization of concern; ρ0x , ρ0y , and ρ0z the partial derivatives ! ! of ρ with respect to x, y, and z; and P1 and P2 the gradient forces at location ! P1 ¼ (x1, y1, z1) and P2 ¼ (x2, y2, z3), respectively. The joint effort of these forces P1 ! and P2 is naturally a rotation. The previous discussion implies that the landscape of the world economy is theoretically composed of eddy currents. The eddy pools within the currents are of

Fig. 2.3 Gradient forces within an organization lead to rotational movements

2.2 The Systemic Yoyo Model

33

Fig. 2.4 Appearance of sub-eddies. (a) How two harmonic yoyo fields create sub-eddies. (b) How two inharmonic yoyo fields create sub-eddies

different levels and scales. For example, the first level that consists of the largest eddy pools will be the systemic yoyo models of regional economies. Within each such eddy pool, there are pools of the next level, consisting of the yoyo fields of companies, etc. At the bottom level, the yoyo pools represent individual consumers, each of whom is made up of his/her consumption preferences, philosophical and value system, etc. In other words, within the landscape of the world business, eddy fields of different sizes and scales interact with each other, while the entire landscape can be seen as a huge ocean of eddies, which change and evolve constantly. One of the important characteristics of spinning fields is the difference between the structural properties of inward (or converging) and outward (or diverging) spinning and the discontinuities between these pools. Due to the stirs in the form of moments of forces, in the discontinuous zones, there might exist sub-eddies and sub-sub-eddies, Fig. 2.4, where sub-eddies are created naturally by the large eddies M and N through their individual spin directions. The sub-eddies contain highly condensed amounts of resources and energies, representing where new business opportunities appear. In other words, business trends are not simply expansions of some already existing phenomena. Instead, they represent sub-eddy zones or new opportunities concentrated with irregularly or unconventional structured entities and energies and investments. That is where the so-called nearly zero probability events appear and disruptive technologies occur and where small-probability information and small-probability chance of success are observed and acted upon by spirited managers and entrepreneurs. Based on what is discussed above, the following systemic yoyo model, Fig. 2.5, is introduced (Lin 2007) by coining together the concepts of inputs and outputs and converging and diverging eddy motions for each object and every system, organization, or structure imaginable. Specifically, each system or process considered in a

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2 Basics of Systems Science

Fig. 2.5 Eddy motion model of the general business organization. (a) The yoyo model in our threedimensional space. (b) The side view. (c) The spiral trajectory of meridian field

managerial decision-making can be abstractly imagined as a multidimensional entity that spins about its axis. If such a spinning entity is fathomed in the threedimensional space in which we live, we have a structure as shown in Fig. 2.5a. The side of the inputs sucks in all things, such as materials, information, talents, investments, etc. After funneling through the neck, all things, such as products, services, etc., are spit out in the form of outputs. Some of the things, spit out from the end of outputs, never return to the other side, and some will (Fig. 2.5b). Such a structure is called a systemic yoyo due to its general shape. What this systemic yoyo model says is that each entity that is considered in a managerial decision-making, be it physically tangible or not, a business firm or a process, an organization or an alliance of firms, a culture or several interacting cultures, a civilization or a collection of intermingling civilizations, etc., can all be seen as a realization of a certain multidimensional spinning yoyo with a spin field around it, either visible or invisible. It stays in a constant spinning motion, Fig. 2.5a. If it does stop its spinning motion, it will no longer exist as an identifiable organization, system, and/or structure. Figure 2.5c shows the interactions between the eddy field, which spins perpendicularly to the axis of yoyo body, of the model, and the meridian field, which rotates parallel to the axis of spin (Fig. 2.5b). Due to this interaction, when things return to the inputs side, they travel along a spiral trajectory.

2.3 Some Elementary Properties of the Systemic Yoyo Model

2.3

35

Some Elementary Properties of the Systemic Yoyo Model

Because each yoyo spins as in Fig. 2.5a, the spin field consists of an eddy field and a meridian field. The former field lines are perpendicular to the axis of rotation of the yoyo structure, Fig. 2.5b, and the latter field lines move parallel to the axis, Fig. 2.5b and c. The meridian lines travel into the input side, through the neck, and then out of the output side. Some of the things spit out of the output side travel through the space and return to the input side. Somehow these meridians help to hold different layers of the eddy field of the yoyo structure together. For the sake of convenience of communication, for any given yoyo structure, the input side will be referred to as the South Pole of the structure and the output side the North Pole. In this abstract and intuitive systemic yoyo model, there are two key words “spin” and “neck” that need some explanation. In particular, the word “spin” is used to capture the meaning of “angular momentum” or the presence of “angular momentum” intrinsic to a body (or organization) as opposed to that of orbital angular momentum of angular momentum that is the movement of the object about an external point. For example, the spin of the Earth stands for the Earth’s daily rotation about its polar axis. The orbital angular momentum of the Earth is about the Earth’s annual movement around the sun. Generally, a two-dimensional object spins around a center (or a point), while a three-dimensional object rotates around a line called an axis, where the center and the axis must be within the body of the object. The concept of spin has been widely studied in many different areas of knowledge, such as mathematics, astronomy, quantum mechanics, and social science areas, respectively. For example, in social science areas, the theory and practice of public relations heavily involve the concept of spin. In such a case, a person, such as a politician, or an organization, such as a publicly traded company, signifies his/her or its often biased favor of an event or situation. Traditional studies of public relations rely generally on creative presentation of facts. However, by “spin” it tends to imply untruthful, deceitful, and/or highly manipulative tactics used to influence the attitudes and opinions of the public (Stoykov and Pacheva 2005; Bernays 1945). The word “neck” here used in this yoyo model is an abstraction of the fact that the organization or system processes its inputs in a specific way in order to produce its outputs. In other words, the word “neck” aggregates the meaning of all the steps of business operations, such as the initial design and the eventual production of marketable products and all business operations in between. In terms of business ecosystems, the totality of all interrelated business entities and economic agents can be imagined as a systemic yoyo, if this totality is situated in isolation from other yoyo structures. Because business firms, organizations, and entities are of different kinds and scales, the business world of any chosen magnitude can be seen as an ocean of interacting eddy pools (each of which represents an economic entity) of different sizes. Each of these yoyo fields spins about its center or axis, which is either visible or invisible and can be vividly imagined as the spin field

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of air in a tornado in our three-dimensional physical space. In its solenoidal structure, at the same time when the air within the tornado spins about the eye in the center, the systemic yoyo structure continuously sucks in and spits out air. The tornado takes in things, such as water and others on the bottom, and lifts up everything it takes in; and then it gives out the things from the top or along the side of the spinning field. Simultaneously, the tornado also breathes in and out with air in all horizontal directions and elevations. When the spin field of the tornado takes in more than it gives out, the tornado grows larger and becomes more powerful with increasing effect on everything along its path. If the opposite holds true, then the tornado weakens in its process of dying out. If an equilibrium is reached between the intake and output of the tornado, then the tornado can last for a while. Generally speaking, each systemic yoyo experiences a period of stable existence after its initial formation and before its disappearance. For the convenience of our discussion in this book, we assume that the spinning of yoyo structures satisfies the following left-hand rule, although generally yoyo fields do not have to satisfy this rule: Left-Hand Rule (Lin 2009) When holding our left hand, the four fingers represent the spinning direction of an eddy plane, and the thumb points to the North Pole direction along which the yoyo structure sucks in and spits out things along its central axis (the neck). (Once again, please note that in the business world, the systemic yoyos of organizations do not have to comply with this left-hand rule.) Affected by eddy spins, the meridian directional movement of things in a yoyo structure is actually slanted instead of being perfectly vertical. In Fig. 2.5c, the horizontal vector stands for the direction of spin on the yoyo surface toward the reader and the vertical vector the direction of the meridian field, which is opposite of that in which the yoyo structure sucks in and spits out materials. Other than breathing in and out things from the input (the South Pole) and output (the North Pole) sides, the yoyo structure also takes in and gives out things in all horizontal directions and elevations, just as in the case of tornadoes discussed earlier. As shown in Fig. 2.5, each yoyo body has an outside surface, through the inside of which the mechanism of input and output takes place. However, due to the interactions of the yoyo field with other outside systems located within the environment, although this surface holds most of the contents of the spinning yoyo, the existence of this surface is most an imagination of our human mind. For example, if we fathom the input-output organizational structure of the company Apple as a spinning systemic yoyo, then the imaginary surface of the yoyo body does not materialistically exist. As the spinning yoyo field, which is the combination of the eddy and meridian fields, constantly takes in and gives out things, no clear boundary exists between the yoyo structure and its environment. That is once again parallel to the circumstance of a tornado that does not have a clear-cut separation between itself and its surroundings. To help us comprehend the general structure of systemic yoyos, let us employ the so-called quark structure from Chen (2007). When doing so, each spinning yoyo, as shown in Fig. 2.6a, is seen as a 2-quark structure, where if the yoyo body is cut

2.3 Some Elementary Properties of the Systemic Yoyo Model

37

Fig. 2.6 Cases of 3-quark yoyos. (a) Two u-quarks and one d-quarks. (b) One u-quarks and two d-quarks

Fig. 2.7 Cases of 4-quark yoyos. (a) Three u-quarks and one d-quarks. (b) Three d-quarks and one u-quarks. (c) Two d-quarks and two u-quarks

through its waist horizontally in the middle, then the top half is known as an absorbing quark and the bottom a spurting quark. Just as the real-life case of business organizations, a firm may have several units established to absorb inputs, such as venture capital, raw materials, human talents, etc., while it produces only one product or vice versa. In particular, if a firm has two absorbing quarks and one spurting quark, we have a 3-quark yoyo field, shown in either Fig. 2.6a or b. In the first case in Fig. 2.6a, the two absorbing u-quarks represent local spinning pools, while together they also travel along in the larger eddy field P. Similarly, in the second case of Fig. 2.6b, the two spurting d-quarks are regional spinning pools. At the same time when they spin individually, they also travel along in the large yoyo structure of N. In these cases, the u- and d-quarks all spin in the same direction except that each u-quark spins inwardly while each d-quark outwardly. Correspondingly, the case of 4-quark yoyo field is shown as one of the cases in Fig. 2.7a–c. Evidently, different yoyo structures have different numbers of absorbing u-quarks and spurting d-quarks. And, the u- and d-quarks in different yoyos are dissimilar in terms of their masses, sizes, spinning speeds and directions, and the absorbing and spurting speeds of materials. This fact is sufficiently supported by organizational structures of business entities, where the number of divisions related attracting investments, securing resources, talents, etc. and the number of divisions

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Fig. 2.8 Hide’s version of dishpan experiment. (a) A symmetric flow pattern. (b) An asymmetric flow. (c) Another asymmetric flow

related to production and selling are generally not equal to each other; and these units perform their functions differently from one company to another. All related details are omitted here. To prepare for the rest of this book, we next look at the well-known dishpan experiment. First let us look at Hide’s version of the experiment. Raymond Hide (1953), University of Cambridge, England, filled the ring-shaped region between two concentric cylinders with a liquid. He then sat the container on a rotating turntable with the periphery heated and the center cooled. To simulate the Earth when viewed from above the North Pole, Hide rotated the table counterclockwise. Although everything in the experiment was arranged with perfect symmetry about the axis of rotation, for example, no impurities were added in the liquid, the bottom of the container was flat; Hide observed the flow patterns as shown in Fig. 2.8a–c. In particular, when the heating temperature is fixed, a transition from the circular symmetry in Fig. 2.8a to the asymmetry in Fig. 2.8b and then to that in Fig. 2.8c takes place as the speed of rotation is increased past critical values one after another. On the other hand, when a sufficiently rapid but fixed speed of rotation is fixed, a similar transition will occur when the heating temperature reaches critical strengths one after another, while a backward transition to the symmetry in Fig. 2.8a occurs when the heating temperature reaches another still higher critical strength. And, in the stage shown in Fig. 2.8c, a chain of identical circular eddy motions appears. As these circular local eddies travel along, they alter their shapes in unison in a regular periodic fashion, and after many rotations of the turntable, they will regain their original shape and then repeat the cycle. After Hide’s work, in the late 1950s, Fultz et al. (1959) of the University of Chicago constructed the following version of the dishpan experiment. They partially filled a cylindrical vessel with water and then placed the vessel on a table rotating counterclockwise, as does the Earth when viewed from above the North Pole, with heating near the periphery and cooling near the center. The vessel’s bottom simulated one hemisphere of the Earth’s surface, the water and the air of this hemisphere, the rotation of the table the Earth’s rotation, and the heating and cooling, respectively, the excess heating of the atmosphere in low latitudes and the excess cooling in high latitudes.

Bibliography

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Fig. 2.9 Patterns observed in Fultz’s dishpan experiment. (a) Pattern of uniform flow. (b) Pattern of a chaotic flow

As with the case of Hide’s experiment, although everything in the experiment was arranged with perfect symmetry about the axis of rotation, Fultz and his colleagues observed the expected flow patterns appeared, as shown in Fig. 2.9a, b, and the choice depended on the speed of the table’s rotation and the intensity of the heating. As in the case of Hide’s experiment, the number of eddy leaves in Figs. 2.8b, c and 2.9b is determined by the intensify difference of heating and cooling between the periphery and the center and the speed of rotation of the dish. Now, by fitting this dishpan experiment to the previous discussion of quark structures, we can naturally see that in theory, there is the potential of observing such a yoyo structure that it has n u-quarks and m d-quarks, where n  1 and m  1 are arbitrary natural numbers, where these quarks spins individually and along with each other in the overall spinning pool of the yoyo field.

Bibliography Bernays, E. (1945). Public relations. Boston: Bellman Publishing Co.. Blauberg, I. V., Sadovsky, V. N., & Yudin, E. G. (1977). Systems theory, philosophy and methodological problems. Moscow: Progress Publishers. Bunge, B. (1979). Treatise on basic philosophy. Vol. 4: A world of systems. Dordrecht, Holland: Reidel. Chen, G. R. (2007). The original state of the world: The theory of Ether Whirltrons. Hong Kong: Tianma Books Limited. Fultz, D., Long, R. R., Owens, G. V., Bohan, W., Kaylor, R., & Weil, J. (1959). Studies of thermal convection in a rotating cylinder with some implications for large-scale atmospheric motion. Meteorological Monographs (Vol. 21, No. 4, pp. 1–104). Boston: American Meteorological Society. Hide, R. (1953). Some experiments on thermal convection in a rotating liquid. Quarterly Journal of the Royal Meteorological Society, 79, 161.

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Kline, M. (1972). Mathematical thought from ancient to modern times. Oxford: Oxford University Press. Klir, G. (1985). Architecture of systems problem solving. New York: Plenum Press. Kuhn, T. (1962). The structure of scientific revolutions. Chicago: University of Chicago Press. Lin, Y. (1987). A model of general systems. Mathematical Modelling: An International Journal, 9 (2), 95–104. Lin, Y. (2007). Systemic yoyo model and applications in Newton’s, Kepler’s laws, etc. Kybernetes: The International Journal of Cybernetics, Systems and Management Science, 36, 484–516. Lin, Y. (2009). Systemic yoyos: Some impacts of the second dimension. New York: Auerbach Publication, an imprint of Taylor and Francis. Lin, Y., & OuYang, S. C. (2010). Irregularities and prediction of major disasters. New York: CRC Press, an imprint of Taylor and Francis. Mesarovic, M. D., & Takahara, Y. (1975). General systems theory: Mathematical foundations. New York: Academic Press. Moore, A. W. (1990). The infinite. London: Routledge. Perlman, J. S. (1970). The atom and the universe. Belmont, CA: Wadsworth. Porter, M. E. (1979). How competitive forces shape strategy. Harvard Business Review, 57, 137–145. Retrieved September 27, 2017 from https://hbr.org/1979/03/how-competitiveforces-shape-strategy. Porter, M. E. (1985). Competitive advantage: Creating and sustaining superior performance. New York: Free Press. Stoykov, L., & Pacheva, V. (2005). Public relations and business communications. Sofia: Ot Igla Do Konetz. von Bertalanffy, L. (1934). Modern theories of development (J. H. Woodge, Trans.). Oxford: Oxford University Press; New York: Harper Torch Books (1962); German Original: Kritische Theories der Formbildung. Berlin: Borntäger (1928). von Bertalanffy, L. (1972). The history and status of general systems theory. In G. Klir (Ed.), Trends in general systems theory (pp. 21–41). New York: Wiley-Interscience. Wu, X. M. (1990). The pansystems view of the world. Beijing: People’s University of China Press. Wu, Y., & Lin, Y. (2002). Beyond nonstructural quantitative analysis: Blown-ups, spinning currents and modern science. River Edge, NJ: World Scientific. Zhu, M. (Trans.). (2001). The medical classic of the yellow emperor. Beijing: Foreign Language Press.

Chapter 3

The Dynamics of Market Competition

This chapter, which is mainly based on (Forrest et al. 2017b), studies the dynamics of a coordinate monopoly with m incumbent risk-neutral firms regarding how these firms compete by adjusting prices and when new competition(s) will enter the market with expectations of making more profits than any of the incumbents. Major findings include (1) how risk neutrality in a developed marketplace can lead to stagnation in expected profits and irrational decision on pricing, (2) a sufficient and necessary condition under which new competitor(s) will enter the market, although the market is coordinately monopolized, etc. In terms of practical applications, this chapter presents an aspect of managerial decision-making on how to compete and why, although the consequent level of profits is not expected to change much or any at all, and how some key issues on the timing of market entry are theoretically resolved. For both managers and entrepreneurs, this chapter shows that even for the minimum objective of business survival, incumbent firms, no matter how established and how successful they are, have to without any choice participate in market competition and look for new market opportunities. The rest of this chapter is organized as follows: Section 3.1 describes the very problem this chapter attempts to address, followed by a literature review. Section 3.2 introduces the market conditions on which the rest of the chapter is based. Section 3.3 looks at the specified market of coordinated monopoly and the consequent stagnation in expected profits. Section 3.4 shows how market actually signals its invitation for competition and innovation. Section 3.5 looks at when new competitor(s) can potentially make more profits than any of the incumbent firms. And this chapter is concluded in Sect. 3.6 along with some open questions posted for future research.

© Springer Nature Switzerland AG 2020 J. Y.-L. Forrest et al., Managerial Decision Making, https://doi.org/10.1007/978-3-030-28064-2_3

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3.1

The Problem of Concern and Literature

For managers, a real-life challenge is how to recognize an opportunity of expansion that presents itself in many different ways. For entrepreneurs, a practically difficult task is to determine how to appropriately analyze a prospect of a new business venture in order to snatch an emerging new development because the prospect can be investigated from various angles that are diversely dissimilar. As the vast literature indicates, market competition can appear and has been appearing most unexpectedly out of nearly any scenario, such as the introduction of new products, a synergetic collocation of some known concepts, a revolutionary improvement of the labor productivity, or others. Hence, the following natural question for decision-making managers and entrepreneurs arises: Because potentially successful products and related markets coexist, even though one or both of them may be initially conceptual, existing only in human imagination, can an existing market actually signal the arrival of new development and the potential emergence of new competition?

Aiming at this question, this chapter establishes a series of theoretically important and practically meaningful results regarding the dynamics and completion of the marketplace. In particular, Theorem 3.4 answers this question positively by establishing a sufficient and necessary condition under which an existing market will experience new competitions. In other words, this chapter presents some exciting results regarding the dynamics of a coordinately monopolized market. After presenting two important characteristics of the coordinately monopolized market – same size (α) bases of loyal consumers and constant amount of expected profits for all incumbent firms – this chapter shows that the magnitude β of consumer surplus of the market is an increasing function in the selling price P. Other than providing a sufficient and necessary condition for when new competitions appear in the market, this chapter also presents the fact that the new competition may generate at least as much profits for the new entering firm(s) as any of the incumbent firms. In terms of the relevant literature, Belu and Caragin (2008) look at the possibilities for a company to enter a new (or foreign) market and the associated market assessment and analysis. For a firm to enter a new market, Kopalle and Lehmann (2006) develop a two-period model to reflect how advertised quality influences consumer expectations, how the expectations determine consumers’ satisfaction shaped by the existing deviation between the actual quality and the expectations, and how the satisfaction consequently affects the performance of the product(s) in the second period. That is, a focal company chooses between fewer consumer repeats with advertised high quality and a good number of consumer repeats with advertised low quality. In terms of market entry, Siebert (2015) investigates the optimal strategies for entering into either a new or empty market by addressing the number of products of different qualities that need to be introduced. A profitable strategy for entering an

3.1 The Problem of Concern and Literature

43

empty market is found to be the introduction of multiple products in order to proliferate the product space that also helps to deter any entry by competitors. And for entering a new market, the optimal strategy is found to be the introduction of a single product only for the reason that firms need to differentiate their products first to soften price competition with their rivals’ products and second to avoid cannibalizing their own (high quality) product demand. In terms of the role of downstream market competition under symbiotic production, Guo et al. (2012) show that incorporating different types of competition in the product market could partially eliminate the inefficiency caused by repeated marginalization. These authors recommend the introduction of callback services or Internet telephones in order to create an environment similar to downward market competition so that international tariffs are significantly reduced. Chang et al. (2015) consider how market competition affects the dynamic relationship between corporate governance and capital structure, finding that market competition increases incentives for firms with weak governance structures to maximize the wealth of shareholders, which in turn raises the adjustment speed toward target leverage. And, the difference in the adjustment speeds of firms with weak and strong governance structures is shown to be less than expected. Debruyne and Reibstein (2005) investigate the timing for incumbent firms to enter new market niches produced by new technological innovation, finding that market conditions and company-specific characteristics are not sufficient to explain entry timing; instead entry is a contagious process. This work shows that incumbent firms are more responsive to innovations in their industry when their competitors do so. Specifically, this work shows that incumbent firms are directly affected by entering firms of similar size and resources and that when a highly similar company appears, the company enters for reasons beyond the sole attractiveness of the market. Because when a new product (attacker) appears in a competitive market, it generally provokes reactions from the existing products (defenders); Kumar and Sudharshan (1988) consider optimal defensive strategies, assuming all the defenders respond to an optimal attack. Analogous to Lane (1980), these authors also assume that N products enter sequentially with perfect foresight on the subsequent entry, and then through employing a new technology, an unanticipated attacker appears; that the N defenders respond in price; and that once an equilibrium is obtained, advertising and distribution scale sales. Then this work shows that under the decoupled response function models of advertising and distribution, uniformly distributed tastes, and nonincreasing market size, the optimal defense strategy for existing brands is to, respectively, decrease their prices, advertisement, and distribution. Similar conclusions are also established by Hauser and Shugan (1983) based on different consumer response models and a different equilibrium assumption. This literature review demonstrates that results given in this chapter enrich the literature and carry what is known many streets forward and make many indecisive conclusions or dilemmas on market entry timing based on empirical studies (Zachary et al. 2015) definite.

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3 The Dynamics of Market Competition

Conditions of the Market

The oligopoly market of our concern is assumed to satisfy the following conditions: • It is occupied by m firms, namely, 1, 2, . . ., m. • These incumbent firms provide their mutually substitutable products with varied qualities and follow-up services. • These firms firmly control their respective market shares with the following of their solid bases of loyal consumers. • There are consumers in the marketplace who make their purchase decisions based on whose price is the most competitive. These consumers are known as switchers. • The incumbent firms are risk neutral and plan to continuously reap in their respective profits by securely defending their established turfs while competing over the switchers with adjustable prices they charge their consumers. • These incumbent firms produce their horizontally differentiated products at constant marginal costs, which are set to zero without loss of generality. • The managements of the m incumbent firms are well aware of the pricing strategies of the other firms and have established their best responses by playing the Nash equilibrium through pure self-analyses. Because of all these assumptions, the market of our concern is referred to as coordinately monopolized (by these existing firms). Speaking differently, the aforedescribed market is in a state of mutual forbearance, where incumbent firms mitigate rivalry by dividing markets in proportion to firm strength (Bernheim and Whinston 1990). They cede dominance to their stronger competitors in those market segments where they are less efficient, while in exchange the latter do the same in segments where the former are more efficient (Li and Greenwood 2004). The firms’ codependence gradually motivates them to de-escalate rivalry (Yu and Cannella Jr. 2012). Eventually, the rates of entry and exit in the market decrease (Fuentelsaz and Gómez 2006), and interfirm hostility declines (Haveman and Nonnemaker 2000). First, let us look at the situation where there are only two incumbent firms, that is, m ¼ 2. Assume that the market share of loyal consumers of Firm k is αk, k ¼ 1, 2, satisfying that these consumers only purchase the product of Firm k provided that the price is no more than their reservation value, which is set to 1. Then β ¼ population size  α1  α2 represents the size of the market segment of switchers who base their purchase decisions on which price is the lowest. By dividing this market share partition by the population size, the parameters α1, α2, and β are normalized. Without loss of generality, these same symbols will still be used for the relevant population proportions. That is, we have the following equation α1 þ α2 þ β ¼ 1: The first question that we like to address is how the market shares α1 and α2 are related to each other within the assumed perfectly identical and symmetrical conditions.

3.2 Conditions of the Market

45

Fig. 3.1 A systemic bird’seye view of our oligopoly market

Fig. 3.2 Asymmetric flow pattern observed in Fultz’s dishpan experiment

To this end, firstly, let us think of the specified marketplace as a closed system so that the marketplace has to have the fundamental characteristics of the general system (Lin 1987, 1999). In particular, the dynamics of the marketplace can be seen as an abstract yoyo field (Lin 2007, 2009) as shown in Fig. 2.5. Secondly, when the marketplace is seen as an abstract yoyo field, one can look at the multidimensional yoyo body at a distance from above either the convergent input side or the divergent output side, while imagine that everything here takes place in our three-dimensional space. That is, one is looking at a pool of spinning fluid, where the word “fluid” is an abstraction of all kinds of things, such as goods, information, money, credit, etc., that appear and exist in business activities. In other words, graphically one is looking at the market of concern as the pool of spinning fluid shown in Fig. 3.1. Now, the well-known dishpan experiment shows that when the movement of the fluid within the rotational dish is under enough pressure created by either the sufficient speed of rotation or sufficient difference in the temperature between the center and the periphery of the dish, the pattern of uniform movement, as shown in Fig. 3.1, will develop into the chaos shown in Fig. 3.2. The number of local eddy leaves is determined either by the rotational speed or by the temperature difference or both and increases with the speed and the temperature difference.

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The perfect symmetry in the setup of this experiment is equivalent to the assumed conditions of our marketplace. They surely do not stop the occurrence of the local eddy leaves in the spinning fluid. This fact implies that if there are only two local pools that appear within the dishpan or our closed marketplace, it is impossible for the two local eddy pools to have different sizes. In other words, this systemic yoyo intuition suggests that the market shares α1 and α2 of our firms should be the same. That is, we should have α1 ¼ α2. As a matter of fact, symbolically, the following result can be proven; see the appendix of this chapter for the detailed proof. Theorem 3.1 In the mixed strategy Nash equilibrium, the two firms’ market shares in this coordinately monopolized market are the same. That is, α1 ¼ α2. If we look at Theorem 3.1 intuitively from the marketing perspective, this result makes perfect sense because everything in this oligopoly market is set up perfectly symmetrically. Otherwise, the firm with smaller market share may try to adjust its price in an attempt to expand its market weight so that this firm is no longer risk neutral and the market is no more coordinately monopolized. On the other hand, in practice this result is apparently incorrect due to the fact that incumbent firms are constrained by their own particular conditions. In other words, in the real business world, even in a nearly ideal market of coordinated monopoly, the market shares of loyal consumers of the existing firms will generally be different from one firm to another. However, even so, the existing firms can still behave as what is assumed earlier due to their respective realization of their individual restrictions and limitations. In other words, within their respective constraints, the incumbent firms occupy proportionally an “identical” market share, where the word “identical” means in reference to each firm’s respective limitations.

3.3

Monopoly and Profit Stagnation

Based on what is established in the previous section, this section looks at the general case when the oligopoly and coordinately monopolized marketplace has m firms. Based on Theorem 3.1 and the systemic intuition by using the dishpan experiment, assume that the size of the loyal consumer base of each incumbent firm is a constant α such that these consumers only purchase the product of their respective firms provided that the price is not more than their reservation value, which is again set to 1. Let the magnitude of the segment of all switchers, who switch from one firm’s product to another totally depending on prices, in the marketplace be β. Then we have the following equation: mα þ β ¼ 1,

ð3:1Þ

where both α and β are normalized as described earlier. Then, the following result holds true, the proof of which is given in the appendix of this chapter.

3.4 Market Invitation for Innovation

47

Theorem 3.2 For this coordinately monopolized market, each of these m incumbent firms’ expected profits in the symmetric Nash equilibrium is equal to α, a fixed constant, even though each of these firms attempts to entice the switchers as much as possible, while exploits its base of loyal consumers by charging them an as high price as possible. Systemically speaking, this result holds true because when the entire market of our concern is modelled as the entire spinning dish in Fig. 3.2 and each of the m incumbent firms as one of the local eddy leaves, there then are a total of m local eddies in the spinning dish. Therefore, no matter how much effort each of the local eddy leaves put into its spin to pull additional fluid particles into its field, some of fluid particles always wonder around the spin field without actually becoming part of any of the local eddies. Speaking differently, when the flow pattern of fluid in Fig. 3.2 is stably formed, it will be impossible for the eddy leaves to grow any larger.

3.4

Market Invitation for Innovation

The previous theorem states the fact that even though the m incumbent firms attempt to snatch as many switchers as possible through altering their selling prices, the firms’ respective expected profits are equal to a constant. So, for decision-making managers and entrepreneurs, they may naturally ask the following question: Do the unchanging expected profits of the incumbent firms mean that the consumer surplus of the market might not change at all? Speaking systemically, the question can be casted as follows: In the flow pattern in Fig. 3.2, if the stirring energy (Lin 2009) of any of the local eddy leaves stays constant, will the scale of the eddy pool have to be kept the same? Here, the constants are modelled by the concept of stirring energy, which as initially proposed by Shoucheng OuYang in 2008 when he labored to understand rotational movements of things. To address this question, we have the following result; see the appendix of this chapter for the technical proof. Theorem 3.3 For the afore-described coordinately monopolized market, the consumer surplus in the symmetric mixed strategy Nash equilibrium is an increasing function of the price P, when P satisfies the condition 1  β  P  1, such that when P ¼ 1, the magnitude of consumer surplus is equal to β ¼ 1  mα, and when P ¼ 1  β, the magnitude of consumer surplus is equal to 0. The results established above jointly post the following practically interesting question for decision-making managers and entrepreneurs: No matter how hard the incumbent firms compete with each other by adjusting their prices, their expected profits stay the same and is equal to α (Theorem 3.2), which is the same as how much each firm can make from its loyal consumers by charging them the reservation value 1. However, in real life to compete and win generally costs money, which, intuitively speaking, will eat into the expected profits. So, why will any of the m incumbent firms bother to compete for switchers?

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To address this question, we have the following result; see the appendix of this chapter for the proof. Theorem 3.4 In the coordinately monopolized market occupied by m incumbent firms, as previously described, at least one new enterprise enters the market profitably, as a competitor of the incumbent firms, if and only if the magnitude β of the consumer surplus satisfies β ¼ 1  mα  α. If a market is coordinately monopolized by m incumbent firms, as described in this chapter, it generally and indirectly means that (1) the technology involved in production has been well developed and (2) the relevant business operations and management have been standardized. So, to enter such a mature market competitively and profitably, the entering business enterprise must have innovatively introduced a brand new technology that can provide additional savings on costs and/or an efficient routine of operation that reduces the overall expenditure of running business. This understanding explains why the entrant can uniformly randomize its selling price P over the interval [0,1], where 0 stands for the marginal cost and 1 the reservation price a loyal consumer is willing to pay, because by doing so, the entrant can establish itself within the market while expecting to make profits. In other words, to enter the market successfully, the entrant can offer its product at any price as long as a sale can be made, while no loss is incurred. As before about the incumbent firms, the constant marginal cost of this entering firm is set to zero without loss of generality. Systemically speaking, the conclusion of Theorem 3.4 can be seen readily by using the systemic yoyo model. In particular, let us treat the afore-described market as the spinning dish in Fig. 3.2 and each of the m incumbent firms as a local eddy leaf. Then, the symmetry assumed in the marketplace, just like that that exists in the dishpan experiment, suggests that it is impossible that: 1. An as large blank space as the area occupied by one of the eddy leaves can appear within the circular chain of the local eddies. In other words, due to symmetric distribution of forces, the local eddy leaves have to be evenly spaced within the spinning dish along the periphery and around the center of the dish. 2. The bordering areas between adjacent local eddy leaves and those between the periphery of the dish and the chain of local eddies are too big, because the appearance of the local eddy leaves is caused by uneven distributions of acting forces on the fluid particles located at different distances from the center of the dish. Now, Theorem 3.4 provides an answer to the question just posted. Although the m incumbent firms are assumed to be risk neutral and want to continuously reap in their respective profits by securely defending their established turfs, they still have to attract and win over the switchers in order to reduce the size of the market segment of switchers. Otherwise, a growing magnitude of the switchers’ segment will inevitably invite new competition into the market. Not only so, collectively all new entrants can also potentially make more profits than any of the incumbent firms, as evidenced by the result in the following section.

3.5 Expected Profits of New Entrants

3.5

49

Expected Profits of New Entrants

What is very theoretically interesting and practically shocking is that when the magnitude of the consumer surplus grows to a sufficiently large value, the new entrant of the market, if only one new firm enters, has a chance to make more profits than any of the incumbent firms. In particular, we have the following result, whose proof is detailed in the appendix of this chapter. Theorem 3.5 If the magnitude β of the consumer surplus satisfies β ¼ 1  mα  α, then there is such a threshold value α 2 (0, 1/(m + 1)) such that when α  α, that is, when the magnitude α of the loyal consumer base of an incumbent is at least as large as this particular threshold value α, the following hold true: • The expected price of the incumbent firms is higher than that of the new entering firm. • The expected profits of any incumbent firm are lower than those of the new entering firm. The existing α value in Theorem 3.5 simply means that for the incumbent firms to become risk neutral, the number of these incumbents needs to be small, and their market shares have to be sufficiently large for these firms to generate their comfortable level of profits as they want. To emerging markets, the result stated in Theorem 3.5 applies especially well. For example, this conclusion can be employed to perfectly analyze the market of personal computers in the 1970s and 1980s (Sobel 1999), where the totality of consumers is not well defined and not easily identifiable, while it is expanding quickly. That is, the magnitude of the consumer surplus β, as specified in Theorem 3.5, is most likely greater than, and constantly increasing, that of any single existing firm’s base of loyal consumers. In such business scenarios, technically advanced, managerially mature and established companies can simply wait on the sideline until those poorly funded and/or inexperienced start-up firms have well developed the market with a more readily identifiable population of consumers before they enter the market. At the same time, these companies can theoretically expect to make more profits than any of the firms that already exist in the marketplace and helped to form the market. At this junction, for theoretical and practical purposes, the literature on market entry timing can be utilized to demonstrate the significance of Theorems 3.4 and 3.5. See Zachary et al. (2015) for a good review of this literature. In particular, by entry timing, it means the timing of entry as the order of entry into a new or existing space, such as market, industry, or geographic region, relative to competitors, technology development, product life cycle, or other contextual referents. Specifically, Lieberman and Montgomery (1988) proposed the concept of first-mover advantage (FMA), which implies how extra time over later entrants allows first and/or early movers to build their bases of loyal customers and develop capabilities, leading to their advantageous market positions and early gain perpetuations. However, studies

50

3 The Dynamics of Market Competition

(see Lieberman and Montgomery (2013) and listed references there) also suggest that time benefit later entrants because first and early movers have already uncovered relevant risks, uncertainties, and potential capability gaps and suffered from various costly mistakes. In other words, in the empirical study of market entry timing, there is a seemingly reasonable logic that can be used to explain both: • Why first and early movers achieve better outcomes. • Why later entrants displace first movers (Lévesque et al. 2013). Such useless logic produced out of empirical studies vividly demonstrates the limitations of such investigations in general and data mining and anecdotal analysis in particular. As for this specific literature, one of the reasons why such a dilemma is produced for decision-making managers and entrepreneurs is that when empirical analyses were employed in these studies, the sets of collected data did not include those of failed first and early movers, which are not well recorded and, therefore, not available. At the same time, this said literature is produced by using samples dominantly collected in North America, creating a situation similar to that described in the scenario of the blind men and elephant in Chap. 1. That is why similar conclusions are drawn naturally for the same reason as why people living on the lands of similar landscape hold similar philosophical beliefs and value systems (Lin and Forrest 2011). Although the previously stated dilemma appears, researches, conducted since Lieberman and Montgomery (1988) initially proposed FMA, have confirmed the fact that entry timing really matters for the performance of companies, even though particular contingencies and antecedents can well dictate the timing of a specific market entry (Fosfuri et al. 2013; Szymanski et al. 1995; VanderWerf and Mahon 1997). Based on a totally different approach, developed on sound scientific background, Theorem 3.4 implies that when there is a sufficient consumer surplus in the marketplace, there will naturally be new competitions either from new startups or firms that have available recourses and capabilities to mobilize. That is, market characteristics beget the entry of new comers with the promise of potentially making more profits than any of the incumbent firms no matter what particular contingency and antecedent a firm can be under. On the other hand, the symmetry, assumed generally in this chapter, indicates that new entrants have at least similar levels of capabilities and resources as the incumbent firms (the earlier movers) do. Otherwise, the incumbent firms can easily scale up their strengths of competition by mobilizing their advanced capabilities and available resources to effectively fail the entrants out of the market. That fact suggests that in real life, established and successful business entities should not be early movers of any new market, if all possible, until some first and early movers have demonstrated the existence and depth of the market. This end in fact theoretically ratifies the discovery of Golder and Tellis (1993). Their work analyzes 500 products in 50 different product categories. They find that the average market share of pioneers is about 10% with nearly half of the pioneers failing outright.

3.6 Conclusions

51

In contrast, early followers enjoyed higher market shares of about 28% and lower failure rates of around 8%. So, these scholars conclude that early followers are more successful than pioneers, because long-term survival and performance depend on the ability to acquire and leverage resources and capabilities for large-scale production of products. This conclusion is also supported by Dobrev and Gotsopoulos (2010), while what is established in this chapter provides a scientifically sound, reliable support. Additionally, Theorem 3.4 also backs up the work by Markides and Geroski (2005), where they maintain that large, multi-business enterprises exploit slack resources and complementary capabilities to scale up their operation and bypass early entrants. That is, having a size advantage, either a large or small size advantage, is more fitting for a later entry, as noticed by (Zachary et al. 2015); and having a technological and/or managerial advantage also makes a firm more fitting for a later entry, as shown by Theorems 3.4 and 3.5. By combining Theorems 3.4 and 3.5, the following result holds true clearly, where by a major competitor, it means an entrant who can potentially make as much profits as any of the incumbent firms. Corollary 3.1 In the afore-described coordinately monopolized market, if the magnitude β of the consumer surplus satisfies β ¼ 1  mα  α, then there is a strong possibility for a major competitor to enter the market. Because all the results established in this chapter are based on the analysis of rigorous theoretical reasoning and systemic thinking, these results carry all the empirical studies on the entry timing effects (Lieberman and Montgomery 2013) to a much higher level and can be treated as a part of the general theory underneath these related empirical studies.

3.6

Conclusions

This chapter theoretically investigates the dynamics of a coordinately monopolized market for the purpose of providing practically useful and reliable recommendations. Other than practical importance, the theoretical significance of the established results in this chapter includes: • When a coordinated monopoly is formed, the expected profits of each incumbent firm will become stagnant. • As long as there are switchers, who make purchase decisions only based on prices, in the marketplace, the incumbent firms, even with their coordinated monopoly of the market, have to realistically procure as many of the switchers as possible. • When the magnitude of the switchers segment is sufficiently large, new competitions will enter into the market.

52

3 The Dynamics of Market Competition

• Along with the appearance of new competitions, the new arrivals can potentially make more profits than each of the incumbent firms. As contributions to the literature of market entry timing, this chapter clears up a few indecisive conclusions established by empirical studies. For example, this chapter theoretically shows that: • As long as a market contains a sufficient magnitude of consumer surplus, new competition will naturally appear no matter what particular contingencies and antecedents a particular firm is under. • Established, successful firms should not be early movers of any new market until some first and early movers have well demonstrated the existence and depth of the market. • Having an advantage in size or technology or management makes a business firm fit for a later entry into a newly formed market. The systemic yoyo model is successfully employed to establish the results in this chapter, where the market of concern is intuitively treated as a spinning yoyo field and treated as the dynamics of the “fluid” movement in Fig. 3.2. By continuously thinking along this line on the bases of the dishpan experiment, the following open questions and related issues arise, which can be potentially more thought provoking than what have been obtained in this chapter. Question 3.1: Generalize Theorem 3.1 to the case of m firms. Question 3.2: If the market of concern expands quickly, then new competitions will constantly appear (Theorems 3.4 and 3.5). In such a scenario, how can the riskneutral incumbent firms adjust themselves to meet new challenges? In particular, if a new comer realistically makes more profits than each of the incumbent firms (Theorem 3.5), how can the incumbent firms react to the challenge? Question 3.3: Opposite to the situation given in the previous question, how can the incumbent firms make adjustments, if their established market starts to shrink and eventually disappear, as the flow pattern in Fig. 3.2 starts to transform back into the one in Fig. 3.1 with time? In summary, this chapter merely captures some fascinating “photographic” shots of the dynamics of an evolutionary process at a freezing moment. Considering the fact that each market goes through stages of birth, growth, maturity, and death over time, the most significant results will be those that portrait not only momentary shots, as what are presented in this chapter, but also reveal the laws underlying the evolution of the development process: birth, growth, maturity, and death. Such results on managerial decision-making will satisfy the characteristics of postmodern science described in (Lin 2009).

Appendix: Proofs of Theoretical Results

53

Appendix: Proofs of Theoretical Results The Proof of Theorem 3.1 Let Fk(P) be the price distribution of Firm k, k ¼ 1, 2. Then the profits for Firm 1 from its loyal consumers are α1P, and those from its share of the switchers are [1  F2(P)]βP. So, Firm 1’s objective function is Zþ1 max F1 ðPÞ E ðΠ1 Þ ¼

fα1 P þ ½1  F 2 ðPÞβPgdF 1 ðPÞ

ð3:2Þ

1

where Π1 is Firm 1’s profits, E(Π1) is the expected profits, and Firm 1 likes to maximize its expected profits by selecting its appropriate price distribution. Because Firm 1 likes to attract as many switchers as possible to potentially increase its profits from the guaranteed level α1 from its loyal consumers by charging them the reservation value 1, the following holds true α1 P þ βP  α1 : So, P  α1/(α1 + β). Because P ¼ 1 is the reservation value of the loyal consumers, the objective function of Firm i in Eq. (3.2) becomes Z1 max F1 ðPÞ E ðΠ1 Þ ¼

fα1  P þ ½1  F 2 ðPÞβ  PgdF 1 ðPÞ:

ð3:3Þ

α1 α1 þβ

The equilibrium indifference condition for Firm 1 is α1  P þ ½1  F 2 ðPÞβ  P ¼ α1  1, which leads to α1 ð1  PÞ , βP

ð3:4Þ

¼ 0 and F 2 ð1Þ ¼ 1:

ð3:5Þ

F 2 ðPÞ ¼ 1  satisfying  F2 Similarly, one has

α1 α1 þ β



54

3 The Dynamics of Market Competition

α2 ð1  PÞ , βP

ð3:4aÞ

¼ 0 and F 1 ð1Þ ¼ 1:

ð3:5aÞ

F 1 ðPÞ ¼ 1  satisfying  F1

α2 α2 þ β



So, Firm 1’s expected profits are Z1 E ðΠ 1 Þ ¼

fα1 P þ ½1  F 2 ðPÞβPgdF 1 ðPÞ α1 α1 þ β Z1

¼

α1 dF 1 ðPÞ

ð3:6Þ

α1 α1 þ β ¼ α1 F 1 ðPÞj1α1

α1 þβ

¼ α2 : Similarly, the expected profits of Firm 2 are α1. If α1 6¼ α2, without loss of generality we can assume α2 > α1. Then from the assumptions about the loyal consumers, one has α1 ¼ E(Π2)  α2 > α1, a contradiction. So, this end means α1 ¼ α2. QED

The Proof of Theorem 3.2 When these incumbent firms compete by using prices, there is no pure strategy Nash equilibrium. (Note: for the case that no symmetric pure strategy equilibrium exists, please consult with Narasimhan (1988) and Varian (1980)). In fact, for any pure strategy portfolio (x1, x2, . . ., xm), if there is a unique index i 2 {1, 2, . . ., m} such that xi < xj

ð3:7Þ

where j 2 {1, 2, . . ., m} and j 6¼ i, then Firm i has successfully attracted all the price switchers and can therefore slightly raise its price xi to bring in additional profits as long as the new price still satisfies the condition in Eq. (3.7). So, the pure strategy portfolio (x1, x2, . . ., xm) is not a Nash equilibrium. If the cardinality |I| of the set

Appendix: Proofs of Theoretical Results

55

n  o I ¼ i 2 f1, 2, . . . , mg : xi ¼ minm j¼1 xj is greater than 1, then Firms k, k 2 I, have absorbed all the switchers. Because everything in this scenario is set up symmetrically, each of these firms would have taken in β/|I| portion of the switcher segment. So, Firm k’s profits, k 2 I, are αxk þ

βxk : jI j

So, one of these firms, say Firm k, can lower its price slightly to x0k , satisfying x0k α þ β= j I j > , xk αþβ to bring in additional profits by attracting all the switchers. That is, the portfolio of pure strategies (x1, x2, . . ., xm) is not a Nash equilibrium. A similar argument can show that even when not all firms k 2 I share the same portion of the price switchers, the firm with the fewest price switchers can slightly lower its price to increase its profits by attracting all price switchers. That is, we once again show that the portfolio of pure strategies (x1, x2, . . ., xm) is not a Nash equilibrium. Lastly, if for any i 2 {1, 2, . . ., m}, xi ¼ 1, then Firm j, for any chosen j 2{1, 2, . . ., m}, can slightly lower its price from the reservation value 1 to anywhere in the interval (α/(α + β), 1) to increase its profits by taking in the entire segment of switchers. So, (1, 1, . . ., 1) is not a Nash equilibrium, either. That is, this particular game does not have any pure strategy Nash equilibrium. However, this game does have a symmetric mixed strategy Nash equilibrium (Zhou et al. 2015). To this end, let Fi(P) be the price distribution of Firm i, i 2 {1, 2, . . ., m}. First, assume that there are only two competing firms i and j, that is, m ¼ 2. At price P, Firm i’s profits from its loyal consumers are αP, and its profits from switchers are [1  Fj(P)]βP. So, the objective function of Firm i is Zþ1 max Fi ðPÞ EðΠi Þ ¼



   αP þ 1  F j ðPÞ βP dF i ðPÞ

1

Z1 ¼

ð3:8Þ 



  αP þ 1  F j ðPÞ βP dF i ðPÞ

0

where Πi ¼ Πi(P) represents Firm i’s profits at price P, E(Πi) Firm i’s expected profits for all possible prices, and for this Firm i’, its objective is to maximize these expected profits by appropriately choosing its particular price distribution Fi(P). The

56

3 The Dynamics of Market Competition

reason why the upper and lower limits of the integral are changed, respectively, from +1 and 1 to 1 and 0 is because when P < 0 or when P > 1, the profits are zero. Assume that there are three incumbent firms, namely i, j, and k, that are involved in the price competition. Then, at price P, Firm i’s profits from its loyal consumers are αP. The portion of switchers Firm j does not get is γ ¼ [1  Fj(P)]β, which is still available for Firms i and k to take. Now, [1  Fk(P)]γ¼ [1  Fk(P)][1  Fj(P)]β is the portion of switchers taken up by neither Firm j nor Firm k. So, they are left for Firm i to take in. So, the objective function of Firm i is Z1 max Fi ðPÞ EðΠi Þ ¼



   αP þ 1  F j ðPÞ ½1  F k ðPÞβP dF i ðPÞ:

ð3:9Þ

0

So, mathematical induction implies that when there are m incumbent firms that compete through pricing, the portion of switchers Firm i is able to take in is Ym   1  F j ðPÞ β: j6¼i Therefore, the profits Πi Firm i generates when the firm sells its product at price P are given by αP þ

Ym   1  F ð P Þ βP, j j6¼i

and Firm i’s objective function is

max F i ðPÞ EðΠi Þ ¼

Z1 n

αP þ

o ½ 1  F ð P Þ βP dF i ðPÞ: k j6¼i

Ym

ð3:10Þ

0

Firm i can earn α by charging the reservation value 1, because the firm’s loyal consumers will purchase its product at that maximum price. However, to potentially maximize profits, each of these incumbent firms adjusts its price P in order to take in as many of the switchers as possible. At the same time, no firm has incentive to price its product below α/(α + β), because any selling price below α/(α + β) will yield profits less than α despite of attracting all switchers, where αP þ βP  α ! P 

α : αþβ

The Nash equilibrium indifference condition for Firm i is αPþ

Ym j6¼i

½1  F k ðPÞβ  P ¼ α  1, when

α  P  1, αþβ

ð3:11Þ

Appendix: Proofs of Theoretical Results

57

for i, j ¼ 1, 2, . . ., m, and i 6¼ j. So, the symmetric equilibrium price distribution is the following continuous function  F ðPÞ ¼ F i ðPÞ ¼ F j ðPÞ ¼ 1 

ð1  PÞα Pð1  mαÞ

1 m1

, when

α  P  1, αþβ

ð3:12Þ

satisfying the boundary conditions: 

α F αþβ

 ¼ 0 and F ð1Þ ¼ 1:

ð3:13Þ

In this unique mixed strategy Nash equilibrium, there is no mass point of prices that the firms charge with positive probability. Hence, each firm’s expected profits are E ðΠ Þ ¼

Zþ1 n

αP þ

o ½ 1  F ð P Þ βP dF ðPÞ k j6¼i

Ym

1

Z1 αdF ðPÞ

¼ α αþβ

ð3:14Þ

¼ αF ðPÞj1α

αþβ

¼ α: In short, in the Nash equilibrium of symmetric mixed strategies, each incumbent firm’s expected profits do not change, although the firms try to attract as many switchers as possible, while exploits its loyal consumers by charging them an as high price as possible. QED

The Proof of Theorem 3.3 From Theorem 3.2, we know that in the symmetric mixed strategy Nash equilibrium, the expected profits for each incumbent firm are α. That is the same as whether or not an incumbent firm simply charges its loyal consumers the reservation value 1 without putting in any effort to entice switchers. To this end, there are two possibilities: (i) Each incumbent firm charges expectedly the reservation value P ¼ 1. (ii) Each firm charges expectedly a price P less than 1. If case (i) is true, then the magnitude of consumer surplus is expectedly equal to β ¼ 1  mα because all the switchers are waiting for discounts. If case (ii) is true,

58

3 The Dynamics of Market Competition

from its loyal consumers, each incumbent firm’s profits are αP (< α). So, the additional expected profits α  αP need to come from switchers so that αP þ

ðβ  γ ÞP ¼ α, m

ð3:15Þ

where γ stands for the proportion of those consumers who are still waiting for deeper discounts from the prevalent price P, and each of the m incumbent firms acquires the same percentage of the switchers’ segment of the market, because all the incumbent firms are assumed to be identical as how they are set up earlier. Now, Eq. (3.15) implies that γ ¼1

1β : P

ð3:16Þ

So, the proportion of consumer surplus is an increasing function of price P satisfying that when P ¼ 1, γ ¼ β; and when P ¼ 1  β, γ ¼ 0. QED

The Proof of Theorem 3.4 (⟹, the necessity) Suppose that a new enterprise enters into the coordinately monopolized market occupied by m incumbent firms. So, each of these m firms establishes its selling price after taking into account the price of the new firm and those of all other existing firms. So, the equilibrium indifference condition of Firm k is αPþβP

Ym j6¼k

  ð1  PÞ 1  F j ðPÞ ¼ α  1:

ð3:17Þ

So, for these m incumbent firms, (3.17) provides the following symmetric equilibrium pricing strategy: 

α F ðPÞ ¼ 1  βP

1 m1

:

ð3:18Þ

However, for the expression F(P) in Eq. (3.18) to be a well-defined probability distribution, we must have 

α 1 βP

1 m1

 0,

which implies that α/β  P  1. That is, the consumer surplus β  α.

ð3:19Þ

Appendix: Proofs of Theoretical Results

59

(⟸, the sufficiency) Assume that the magnitude β ¼ 1  mα of the consumer surplus is greater than or equal to α. It suffices to show that there is one business enterprise that will profit expectedly by competing in this coordinately monopolized market with the incumbent firms through employing a uniformly randomized price strategy over the interval [0,1], where the marginal cost of the entrant is also assumed to be 0. From the assumption that β ¼ 1  mα  α, we have α/β  1. So, for any price P in the closed interval α/β  P  1, the expression F(P) in Eq. (3.18) will be a welldefined mixed strategy for each of the m incumbent firms. And this strategy satisfies the equilibrium indifference condition in Eq. (3.17). This fact implies that for each of the m incumbent firms, its lowest allowed price is α/β. To complete this proof, it suffices to show that the entering firm actually expects to make profits in this new market. In fact, because 1

lim F ðPÞ ¼ 1  ðα=βÞm1 6¼ F ð1Þ ¼ 1,

P!1

the cumulative price distribution function F(P) has a jump discontinuity at the 1 reservation value P ¼ 1. The amount of jump is ðα=βÞm1 . That is, F(P) has a mass 1 point of size ðα=βÞm1 at the reservation value P ¼ 1. So, the expected profits of the entering firm are equal to the following: α=

Zβ

Zþ1

E e ðΠ Þ ¼ α=

Zβ

Z1

m  m1 α βP½1  F ðPÞ dP þ β β

m

βPdP þ 0

ð3:20aÞ

α= β

0

¼

βP½1  F ðPÞm dP

βPdP þ

α= β

ð3:20bÞ

where the first term on the right-hand side of Eq. (3.20a) stands for the expected profits of the entering firm when its selling price is the lowest in the marketplace and when it captures the entire segment of switchers. The second term of Eq. (3.20a) is equal to the entering firm’s expected profits when it is in direct competition with the m incumbent firms. Evidently, the first term in the right-hand side of Eq. (3.20b) satisfies α=

Zβ βPdP ¼

α2 > 0, 2β

0

the second term is 0, because the integrant is positive, and the third term is positive. So, the expected profits of the entering firm Ee(Π) is greater than 0. In other words,

60

3 The Dynamics of Market Competition

this argument implies that if the magnitude of the consumer surplus satisfies β ¼ 1  mα  α, there will be then at least one new firm that will enter the market to compete with the incumbent firms. QED

The Proof of Theorem 3.5 (Continued from the proof of Theorem 3.4.) Let us compute the expected price of the m incumbent firms as follows: Zþ1 E m ðPÞ ¼

P  F 0 ðPÞdP

1

Z1 ¼ α= β

1  m1 α P  F ðPÞdP þ 1  β

0

8 1

m1 > α α > >  1

 > β > m1 β < α , þ β m  2 ¼   > > >α α > > : β 1  ln β ,

ð3:21Þ

if m  3 if m ¼ 2

and the expected profits of any of the m incumbent firms are 1  m1 Z1 n o Ym α E m ðΠ Þ ¼ α  P þ β  Pð1  PÞ j6¼i ½1  F ðPÞ dF ðPÞ þ α  β

α= β

Z1 ¼ α= β

1  m1 α αdF ðPÞ þ α ¼ α: β

ð3:22Þ On the other hand, the expected price of the new entering firm is Ee(P) ¼ 1/2, and the expected profits of the firm, based on Eqs. (3.20a) and (3.20b), is 8 > > >
2 2 > > : α  α ln α þ β α , β β 2β β

if m  3 ð3:23Þ if m ¼ 2

Bibliography

61

From Eq. (3.21), it follows that 8 > > > >