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Analyzing the Relationship Between Innovation, Value Creation, and Entrepreneurship
 9781799811695, 9781799811701, 9781799811718

Table of contents :
Cover
Title Page
Copyright Page
Book Series
Editorial Advisory Board
Table of Contents
Detailed Table of Contents
Preface
Introduction
Chapter 1: Value Creation, Innovation, and Entrepreneurship
Chapter 2: Creating Value Through Entrepreneurship Based on the Economic Cycle
Chapter 3: Innovation, Value Creation, and Entrepreneurship by Opportunity
Chapter 4: Social Entrepreneurship and Sustainable Development
Chapter 5: Untangling the Innovativeness-Performance Puzzle
Chapter 6: The Influence of Government Support Interventions on the Growth of African Foreign-Owned SMMEs in South Africa
Chapter 7: Innovation and Knowledge in Academia
Chapter 8: Blue Ocean Strategy as a Framework for Business Innovation in China and Spain
Chapter 9: The Online Platform Economy as an Entrepreneurship-Based Strategy for Value Creation
Chapter 10: Open Innovation as a Business Entrepreneurship Strategy
Chapter 11: Value Propositions for Companies in Their Payment Ads in Networks
Chapter 12: Talent Revolution
Chapter 13: Innovation in the Measurement of Tourism Competitiveness
Chapter 14: Some Considerations About Value Creation in Regard to Entrepreneurship and Innovation From Public Service Obligations on Scheduled Air Transport
Compilation of References
About the Contributors
Index

Citation preview

Analyzing the Relationship Between Innovation, Value Creation, and Entrepreneurship Miguel-Ángel Galindo-Martín University of Castilla-La Mancha, Spain Maria-Teresa Mendez-Picazo University Complutense of Madrid, Spain María-Soledad Castaño-Martínez University of Castilla-La Mancha, Spain

A volume in the Advances in Business Strategy and Competitive Advantage (ABSCA) Book Series

Published in the United States of America by IGI Global Business Science Reference (an imprint of IGI Global) 701 E. Chocolate Avenue Hershey PA, USA 17033 Tel: 717-533-8845 Fax: 717-533-8661 E-mail: [email protected] Web site: http://www.igi-global.com Copyright © 2020 by IGI Global. All rights reserved. No part of this publication may be reproduced, stored or distributed in any form or by any means, electronic or mechanical, including photocopying, without written permission from the publisher. Product or company names used in this set are for identification purposes only. Inclusion of the names of the products or companies does not indicate a claim of ownership by IGI Global of the trademark or registered trademark. Library of Congress Cataloging-in-Publication Data Names: Galindo Martín, Miguel Angel, editor. | Mendez Picazo, Maria-Teresa, 1963- editor. | Castaño Martínez, María Soledad, editor. Title: Analyzing the relationship between innovation, value creation, and entrepreneurship / Miguel-Ángel Galindo-Martín, Maria-Teresa Mendez Picazo, María-Soledad Castaño-Martínez, editors. Description: Hershey : Business Science Reference, 2019. | Includes bibliographical references and index. | Summary: “This book examines the relationship between innovation, value creation, and entrepreneurship”--Provided by publisher”-- Provided by publisher. Identifiers: LCCN 2019025558 (print) | LCCN 2019025559 (ebook) | ISBN 9781799811695 (hardcover) | ISBN 9781799811701 (paperback) | ISBN 9781799811718 (ebook) Subjects: LCSH: Entrepreneurship--Technological innovations. | Diversity in the workplace--Management. | Information technology--Management. | Knowledge management. | Value. Classification: LCC HB615 .A6824 2019 (print) | LCC HB615 (ebook) | DDC 338/.04--dc23 LC record available at https://lccn.loc.gov/2019025558 LC ebook record available at https://lccn.loc.gov/2019025559 This book is published in the IGI Global book series Advances in Business Strategy and Competitive Advantage (ABSCA) (ISSN: 2327-3429; eISSN: 2327-3437) British Cataloguing in Publication Data A Cataloguing in Publication record for this book is available from the British Library. All work contributed to this book is new, previously-unpublished material. The views expressed in this book are those of the authors, but not necessarily of the publisher. For electronic access to this publication, please contact: [email protected]

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The Advances in Business Strategy and Competitive Advantage (ABSCA) Book Series (ISSN 2327-3429) is published by IGI Global, 701 E. Chocolate Avenue, Hershey, PA 17033-1240, USA, www.igi-global.com. This series is composed of titles available for purchase individually; each title is edited to be contextually exclusive from any other title within the series. For pricing and ordering information please visit http://www.igi-global.com/book-series/advances-business-strategy-competitive-advantage/73672. Postmaster: Send all address changes to above address. ©© 2020 IGI Global. All rights, including translation in other languages reserved by the publisher. No part of this series may be reproduced or used in any form or by any means – graphics, electronic, or mechanical, including photocopying, recording, taping, or information and retrieval systems – without written permission from the publisher, except for non commercial, educational use, including classroom teaching purposes. The views expressed in this series are those of the authors, but not necessarily of IGI Global.

Titles in this Series

For a list of additional titles in this series, please visit: https://www.igi-global.com/book-series/advances-business-strategy-competitive-advantage/73672

Advanced MIS and Digital Transformation for Increased Creativity and Innovation in Business Gülay Ekren (Sinop University, Turkey) Alptekin Erkollar (ETCOP, Austria) and Birgit Oberer (ETCOP, Austria) Business Science Reference • © 2020 • 251pp • H/C (ISBN: 9781522595502) • US $225.00 Improving Business Performance Through Innovation in the Digital Economy Ionica Oncioiu (Titu Maiorescu University, Romania) Business Science Reference • © 2020 • 272pp • H/C (ISBN: 9781799810056) • US $225.00 Ethical Consumerism and Comparative Studies Across Different Cultures Emerging Research and Opportunities Ebtihaj Ahmed Al-A’ali (University of Bahrain, Bahrain) and Meryem Masmoudi (University of Bahrain, Bahrain) Business Science Reference • © 2020 • 248pp • H/C (ISBN: 9781799802723) • US $155.00 Handbook of Research on Managerial Practices and Disruptive Innovation in Asia Patricia Ordoñez de Pablos (University of Oviedo, Spain) Xi Zhang (Tianjin University, China) and Kwok Tai Chui (The Open University of Hong Kong, Hong Kong) Business Science Reference • © 2020 • 451pp • H/C (ISBN: 9781799803577) • US $235.00 Entrepreneurial Innovation and Economic Development in Dubai and Comparisons to Its Sister Cities Heather C. Webb (Dubai Men’s College, UAE) and Hussain A. Al Numairy (Dubai Men’s College, UAE) Business Science Reference • © 2020 • 364pp • H/C (ISBN: 9781522593775) • US $210.00 Theoretical and Applied Mathematics in International usiness Bryan Christiansen (Global Research Society, USA) and Fatima Shuwaikh (Université Paris Saclay, France) Business Science Reference • © 2020 • 358pp • H/C (ISBN: 9781522584582) • US $225.00 Strategic Marketing for Social Enterprises in Developing Nations Nigel Chiweshe (University of KwaZulu-Natal, South Africa) and Debbie Ellis (University of KwaZulu-Natal, South Africa) Business Science Reference • © 2019 • 373pp • H/C (ISBN: 9781522578598) • US $195.00 Handbook of Research on Entrepreneurship, Innovation, and Internationalization Nuno Miguel Teixeira (Polytechnic Institute of Setúbal, Portugal) Teresa Gomes da Costa (Polytechnic Institute of Setúbal, Portugal) and Inês Margarida Lisboa (Instituto Politécnico de Leiria, Portugal) Business Science Reference • © 2019 • 761pp • H/C (ISBN: 9781522584797) • US $395.00

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Editorial Advisory Board Francisco Jareño Cebrian, University of Castilla-La Mancha, Spain Francisco José Climent-Diranzo, University of Valencia, Spain Daniel Palacios-Marqués, University of Politècnica de València, Spain Jesús Manuel Palma-Ruiz, Universidad Autónoma de Chihuahua, Mexico Dionisio Ramirez-Carrera, University of Castilla-La Mancha, Spain Javier Ruiz Rincón, University Complutense of Madrid, Spain



Table of Contents

Preface................................................................................................................................................... xv Introduction........................................................................................................................................ xxv Chapter 1 Value Creation, Innovation, and Entrepreneurship: Feedback Effects..................................................... 1 Miguel-Angel Galindo-Martín, University of Castilla-La Mancha, Spain María-Teresa Méndez-Picazo, University Complutense of Madrid, Spain Chapter 2 Creating Value Through Entrepreneurship Based on the Economic Cycle........................................... 21 Fernando E. Callejas Albiñana, University of Castilla-La Mancha, Spain Isabel Martínez Rodríguez, University of Castilla-La Mancha, Spain Chapter 3 Innovation, Value Creation, and Entrepreneurship by Opportunity: An Analysis of European Countries................................................................................................................................................ 43 María-Soledad Castaño-Martínez, University of Castilla-La Mancha, Spain Chapter 4 Social Entrepreneurship and Sustainable Development: New Challenges and Opportunities.............. 64 Susana de los Ríos-Sastre, Universidad Pontificia Comillas, Spain Víctor M. González-Sánchez, Universidad Nacional de Educación a Distancia, Spain Chapter 5 Untangling the Innovativeness-Performance Puzzle............................................................................. 85 Tugba Gurcaylilar-Yenidogan, Akdeniz University, Turkey Safak Aksoy, Akdeniz University, Turkey Chapter 6 The Influence of Government Support Interventions on the Growth of African Foreign-Owned SMMEs in South Africa...................................................................................................................... 104 Lusambya Lukendo Moise, University of KwaZulu-Natal, South Africa Refiloe Khoase, University of KwaZulu-Natal, South Africa Patrick Ndayizigamiye, University of Johannesburg, South Africa  



Chapter 7 Innovation and Knowledge in Academia............................................................................................. 125 Andrea Rey-Martí, University of Valencia, Spain Carla Martínez-Climent, ESIC Business & Marketing School, Spain María Rodríguez-García, ESIC Business & Marketing School, Spain Chapter 8 Blue Ocean Strategy as a Framework for Business Innovation in China and Spain: A Summative Content Analysis of Innovation Initiatives and Value Propositions..................................................... 146 María Guijarro-García, ESIC Business and Marketing School, Spain Agustín Carrilero-Castillo, ESIC Business and Marketing School, Spain José Fernando Gallego-Nicholls, ESIC Business and Marketing School, Spain Chapter 9 The Online Platform Economy as an Entrepreneurship-Based Strategy for Value Creation: Some Considerations..................................................................................................................................... 182 José Manuel Saiz-Alvarez, Tecnologico de Monterrey, Mexico Chapter 10 Open Innovation as a Business Entrepreneurship Strategy: The Consumer as Value Creator in Digital Ecosystems............................................................................................................................... 201 Miguel Angel Gomez-Borja, University of Castilla-La Mancha, Spain Carlota Lorenzo-Romero, Universidad de Castilla-La Mancha, Spain Leticia del-Pozo Ruiz, Universidad de Castilla-La Mancha, Spain Chapter 11 Value Propositions for Companies in Their Payment Ads in Networks: How to Generate Value and Return............................................................................................................................................ 232 Rafa Marín Pastrana, Universidad Politécnica de Valencia, Spain Chapter 12 Talent Revolution: New Challenges in People Management............................................................... 247 Dolores Botella-Carrubi, Departamento de Organización de Empresas, Universitat Politècnica de València Camino de vera Valencia, Spain Marta Tudela-Torras, Universidad Católica de Valencia San Vicente Mártir, Spain Chapter 13 Innovation in the Measurement of Tourism Competitiveness............................................................. 268 Jose Manuel Guaita Martinez, Valencian International University, Spain José María Martín Martín, International University of La Rioja, Spain José Antonio Salinas Fernández, University of Granada, Spain



Chapter 14 Some Considerations About Value Creation in Regard to Entrepreneurship and Innovation From Public Service Obligations on Scheduled Air Transport..................................................................... 289 Antonio Martínez Raya, National University of Distance Education, Spain Víctor M. González-Sánchez, National University of Distance Education, Spain Compilation of References................................................................................................................ 307 About the Contributors..................................................................................................................... 368 Index.................................................................................................................................................... 372

Detailed Table of Contents

Preface................................................................................................................................................... xv Introduction........................................................................................................................................ xxv Chapter 1 Value Creation, Innovation, and Entrepreneurship: Feedback Effects..................................................... 1 Miguel-Angel Galindo-Martín, University of Castilla-La Mancha, Spain María-Teresa Méndez-Picazo, University Complutense of Madrid, Spain The literature has traditionally focused on the relationship between innovation and entrepreneurial activity, adopting mainly two perspectives when addressing entrepreneurship: empirical studies focusing on the behaviour of companies, and studies that consider entrepreneurship as a factor promoting the achievement of economic policy objectives. Following Schumpeter, innovation is a key source of value creation, generating growth in companies and the economy as a whole. But it is also important to remember the feedback effects generated in this process. This chapter analyses the relationship among three variables: entrepreneurship, innovation, and value creation, as well as the subsequent feedback effects. The theoretical aspects are considered and an empirical analysis is developed for the case of some European countries. Chapter 2 Creating Value Through Entrepreneurship Based on the Economic Cycle........................................... 21 Fernando E. Callejas Albiñana, University of Castilla-La Mancha, Spain Isabel Martínez Rodríguez, University of Castilla-La Mancha, Spain This chapter examines in-depth the behavior of necessity- and opportunity-driven entrepreneurship. First, it considers their relevance to total entrepreneurial activity. The chapter determines which social and economic factors affect the two types of entrepreneurship, as well as their relative importance for a sample of 32 previously selected countries during a period of expansion (2001-2008) and of crisis and recovery (2009-2016). The analyzed factors include monetary and fiscal policy instruments (economic factors) and representative variables of governance and human capital (social ones). The findings show that both necessity- and opportunity-driven entrepreneurship largely explain the behavior of total entrepreneurial activity. They moreover show that the explanatory factors of both kinds of entrepreneurship differ depending on the business cycle phase considered. These findings will be key to proposing efficient economic policy measures to promote entrepreneurial activity and, thus, economic growth in economies around the world.





Chapter 3 Innovation, Value Creation, and Entrepreneurship by Opportunity: An Analysis of European Countries................................................................................................................................................ 43 María-Soledad Castaño-Martínez, University of Castilla-La Mancha, Spain Technological progress is one of the main generators of increases in the production economy, involving the introduction of new products which, in turn, allows companies that carry out innovative actions to survive in the market. According to Schumpeter, innovation is an important source of value creation, improving growth in companies and economy. Thus, entrepreneurs introducing innovations in the market to take advantage of new business opportunities increase value creation, understood as the actions implemented to increase the value of goods and services created by enterprises. Likewise, the exploitation of these new opportunities that arises thanks to technological change are also largely conditioned by entrepreneurs’ human capital, availability of financial resources, investment in research and development activities, expectations, and efficient business regulations. Chapter 4 Social Entrepreneurship and Sustainable Development: New Challenges and Opportunities.............. 64 Susana de los Ríos-Sastre, Universidad Pontificia Comillas, Spain Víctor M. González-Sánchez, Universidad Nacional de Educación a Distancia, Spain There is no doubt about the relevant role of social entrepreneurs as social transformers and there seems to be broad consensus on the factors that characterize it, such as: a sustainable social orientation, the intensive use of innovation, and the aim of creating social value. This chapter offers an updated vision of social entrepreneurship around the world, showing the main advances made in recent years and analyzing the main challenges and opportunities for the near future. It includes a reflection on the concept of social entrepreneurship, since today there’s not a single definition of that term, and a review of the evidence on good practices in this field, which could serve as a model for future initiatives. Chapter 5 Untangling the Innovativeness-Performance Puzzle............................................................................. 85 Tugba Gurcaylilar-Yenidogan, Akdeniz University, Turkey Safak Aksoy, Akdeniz University, Turkey This chapter investigates the relationships between innovativeness and firm performance from a multidimensional viewpoint. As previous studies have shown controversial results on the performance implications for innovative capacity, the promising venue for the innovation research study is to address the question of under which conditions innovativeness leads to improved financial performance. To this end, the results of this study demonstrate some major findings. First, non-technical innovativeness exerts positive influence over technical innovativeness. Second, novelty of technical innovation activities causes a diminishing effect on financial performance due to the ambiguity of value-creation. Third, technical innovativeness enhances financial performance when the relationship between technical innovativeness and financial performance is mediated by market effectiveness and production efficiency. Overall, this chapter clarifies the conflicting results on the innovativeness-financial performance link and hence contributes to the innovation literature.



Chapter 6 The Influence of Government Support Interventions on the Growth of African Foreign-Owned SMMEs in South Africa...................................................................................................................... 104 Lusambya Lukendo Moise, University of KwaZulu-Natal, South Africa Refiloe Khoase, University of KwaZulu-Natal, South Africa Patrick Ndayizigamiye, University of Johannesburg, South Africa Foreign-owned SMMEs contribute positively to national economic growth. Foreign-owned SMMEs are sources of direct foreign investment and create employment opportunities for local citizens. Although the South African government has instituted several interventions to promote SMMEs growth, very little research has investigated the impact of such interventions on the growth of foreign-owned SMMEs. This study is an attempt to address this gap by investigating government-related support interventions that have an influence on the growth of African foreign-owned SMMEs. Using quantitative research methods and a sample of 60 African foreign SMMEs owners conveniently sampled from the Pietermaritzburg city, findings reveal that training support from the government is the only single intervention that significantly influences the growth of African foreign-owned SMMEs. Thus, this chapter proposes a regression model that depicts how receiving training support from the government influences the growth of African foreign-owned SMMEs in the South African context. Chapter 7 Innovation and Knowledge in Academia............................................................................................. 125 Andrea Rey-Martí, University of Valencia, Spain Carla Martínez-Climent, ESIC Business & Marketing School, Spain María Rodríguez-García, ESIC Business & Marketing School, Spain It has recently become very popular among academics to study the process of knowledge transfer within their own organization, with the aim of improving their innovation and performance on a general scope. Knowledge can be divided into two main groups: “explicit” and “tacit” knowledge. The main interest lies in tacit knowledge, since it is one that includes the specific “know-how” of an organization. The cooperation between the different units of an organization promotes the transfer of knowledge between the different organizational areas and positions the departments in an ideal situation to promote innovation. To understand the evolution of the scientific production in terms of innovation and knowledge up until now, the authors conducted a bibliometric analysis of research on this topic collected on the Web of Science. The results show a growing interest in the relationship of both topics due to the fact that the number of publications is an upward trend. Chapter 8 Blue Ocean Strategy as a Framework for Business Innovation in China and Spain: A Summative Content Analysis of Innovation Initiatives and Value Propositions..................................................... 146 María Guijarro-García, ESIC Business and Marketing School, Spain Agustín Carrilero-Castillo, ESIC Business and Marketing School, Spain José Fernando Gallego-Nicholls, ESIC Business and Marketing School, Spain The authors conducted summative content analysis on reported innovation initiatives indexed in the Web of Science for Spain and China from 2015 to 2019 to identify Blue Ocean Strategy dimensions and to analyze the national innovation systems of both countries using Hofstede’s cultural dimensions of long-term orientation and uncertainty avoidance, to explain the influence of culture on innovation



initiatives. The studies analyzed report structural and industry-level innovation proposals and programs that recommend elimination, reduction, raising, and creation. This chapter raises awareness among decision makers and legislators about the importance of cultural traits, and underscores four actions to undertake innovation initiatives, policies, legislation, and proposals. The chapter contributes to managerial practice by signaling a path to innovate incrementally, and contributes to researchers by establishing a baseline on the linkage between innovation, culture, and strategy. Authors also recommend areas for future research. Chapter 9 The Online Platform Economy as an Entrepreneurship-Based Strategy for Value Creation: Some Considerations..................................................................................................................................... 182 José Manuel Saiz-Alvarez, Tecnologico de Monterrey, Mexico The Online Platform Economy (OPE) is a part of the Gig Economy defined by the hiring of temporary and highly-flexible workers (freelancers and independent contractors) instead of full-time employees to perform tasks (“gigs”), as well as by using 4G and 5G ICTs-based technologies for crowdwork, crowdvoting, and crowdsolving. These online platform businesses provide businesses and consumers access to low-cost, on-demand labor. But gig workers’ experiences are more complex, as they have access to very flexible, potentially autonomous work. They also deal with challenges caused by the nature of the work, its precariousness, and their relationships with online platforms. This chapter studies OPEs and the Gig Economy. The author defines the concept of the Gig Economy and its importance, and analyzes it through a SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis. Then, the OPE, as a digital value creator, is studied. The chapter includes perspectives and conclusions. Chapter 10 Open Innovation as a Business Entrepreneurship Strategy: The Consumer as Value Creator in Digital Ecosystems............................................................................................................................... 201 Miguel Angel Gomez-Borja, University of Castilla-La Mancha, Spain Carlota Lorenzo-Romero, Universidad de Castilla-La Mancha, Spain Leticia del-Pozo Ruiz, Universidad de Castilla-La Mancha, Spain The relationship established through online channels between customers and organizations defines a new and challenging scenario. Within a digital environment and through innovation strategies based on joint participation, it is possible to interact with the customer in a more personalized way with more differentiating actions. To identify the relevance of current online business management actions, this chapter proposes an approximation to the term open innovation. Authors posit the growing relevance for organizations of the application of innovation strategies through external inputs, the interaction between various agents and crowdsourcing actions. They discuss the new role of the consumers as co-creating agents of value in the new ecosystems of entrepreneurship. Chapter 11 Value Propositions for Companies in Their Payment Ads in Networks: How to Generate Value and Return............................................................................................................................................ 232 Rafa Marín Pastrana, Universidad Politécnica de Valencia, Spain The maturity of social networks as part of the daily life of consumers has caused both large companies and all enterprises to try to take advantage of the potential they have to reach their audiences and clienteles with relatively low advertising budgets. However, many of them still do not assimilate the functioning



of these new media and use them as a simple promotional tool. The reduction of the organic scope, the stagnation of Facebook, the crisis of credibility, and the evolution of the networks themselves towards smaller communities, as happened at the beginning, complete a panorama that hinders the objective of maximizing profits and ensuring a ROI in line . How should this challenge be faced when the internet is displacing television as the main advertising investment support worldwide? Personalization and content marketing, customer service, and preference for quality and engagement are the main answers. Chapter 12 Talent Revolution: New Challenges in People Management............................................................... 247 Dolores Botella-Carrubi, Departamento de Organización de Empresas, Universitat Politècnica de València Camino de vera Valencia, Spain Marta Tudela-Torras, Universidad Católica de Valencia San Vicente Mártir, Spain In recent decades, talent management has undergone a great evolution (McDonnell, Collings, Mellahi & Schulerl, 2017). The increase in employment opportunities, the demographic winter, and the growing demands of the labour force have generated the need for a new model of people management (Collings, Scullion & Vaiman, 2015). This has resulted in companies struggling to acquire the most talented professionals. This chapter studies the revolution talent management has experienced and presents the main challenges in the new people management. Authors offer entrepreneurs and managers useful recommendations for adequate talent management. Chapter 13 Innovation in the Measurement of Tourism Competitiveness............................................................. 268 Jose Manuel Guaita Martinez, Valencian International University, Spain José María Martín Martín, International University of La Rioja, Spain José Antonio Salinas Fernández, University of Granada, Spain The Travel & Tourism Competitiveness Index (TTCI), developed by the World Economic Forum (WEF), is a composite indicator that integrates a total of 90 simple variables organized into 14 pillars or key dimensions of the tourism destination competitiveness. The main problem presented by this index comes from the aggregation of variables expressed in different measures, the duplicity of information, and their non-weighting in the synthetic index. This chapter proposes a new methodology for the construction of the TTCI that solves the previous problems and allows, in addition, identifying which are the pillars or dimensions that determine the differences in tourism competitiveness between the countries. The results have allowed authors to more precisely classify 136 countries according to their level of tourism competitiveness in 2017. To improve the tourism competitiveness of the countries, it is necessary to carry out policies that act on these pillars and others identified in this chapter. Chapter 14 Some Considerations About Value Creation in Regard to Entrepreneurship and Innovation From Public Service Obligations on Scheduled Air Transport..................................................................... 289 Antonio Martínez Raya, National University of Distance Education, Spain Víctor M. González-Sánchez, National University of Distance Education, Spain Airlines are open to and enjoy a high standard of regulations within the EU Internal aviation market. However, scheduled air services are at times restricted to the access of single markets due to the imposition of public service obligations. This situation is regarded as market failure so this chapter addresses some



key aspects in which these impositions can provide elements to create value in regional economies and the private sector through entrepreneurship and innovation. To this end, authors analyze the importance of such fundamental concepts in the transportation sector in regard to air routes not sufficiently covered by carriers in a free market regime despite business opportunity or lack of profitability. This chapter suggests how to improve participation of entrepreneurial companies in tender processes and award of contracts for these specific impositions. Compilation of References................................................................................................................ 307 About the Contributors..................................................................................................................... 368 Index.................................................................................................................................................... 372

xv

Preface

Traditional literature has focused the attention on the relationship between innovation and entrepreneurship activity. From this perspective, new innovations would be accompanied with positive effects that would enhance value creation. However, literature has not considered other indirect effects that would also have relevant consequences, such as the digital dividends effects and the knowledge talent behavior. For this reason, the main goal of the book proposed to analyze the theoretical and empirical aspects of innovation process as a factor that enhances value creation and the role of the entrepreneurship in this process. In this sense the feedback effects is also necessary to be considered because innovation stimulates and facilitates entrepreneurship because the highest levels of entrepreneurship are to be found in societies with the highest value creation and digital dividends: the higher levels of consumption, employment and cost reduction generated by the implementation of digital technologies motivates entrepreneurs to expand their activity and promotes the emergence of new entrepreneurs. But also positive outcomes generated by the implementation of innovations leader to higher competition and new markets, incentivizing entrepreneurs to introduce new innovations to react to these higher levels of competition, which are accompanied by their corresponding value creation. All these aspects are analyzed in the different chapters of the book. The book analyzes the relations between innovation, value creation and entrepreneurship. Innovation process enhances to entrepreneurs generate value creation. This possibility allows them not only to continue and increase their activity, but also has positive effects on the economy as a whole, that enhances economic growth and the creation of employment and wealth. The book proposed chapters study the different interrelationships between these variables, applying them at the micro and macro level, also considering the fiscal effects and making reference to different geographical areas. In this sense, this book is appropriate for researches interested in this field, as well as for university students and master students. The book includes 14 chapters divided into four sections. After an introductory chapter, the role of entrepreneurship and SMEs is analyzed in Section 1. The six chapters collected in this section focus on studying the entrepreneurship activity in order to create value also considering their positive effects on economic growth and employment. Chapter 1 titled “Value Creation, Innovation, and Entrepreneurship: Feedback Effects”, by MiguelÁngel Galindo-Martín and María-Teresa Méndez-Picazo, focuses on the relationship between entrepreneurship, innovation and value creation and the positive effects of these factors on economic growth, and, therefore, on employment and social well-being. These positive effects have led policymakers to show special interest in promoting entrepreneurial activity through economic policy measures, such as facilitating access to credit, reducing taxation and streamlining bureaucratic procedures.



Preface

The chapter carries out a theoretical and empirical analysis. From the theoretical perspective, the authors develop a Schumpeterian approach showing the entrepreneurship effects on economic growth. According to Schumpeter, entrepreneurs play a core role in value creation since, as they introduce innovations into the system, corporate profits increase, which has a positive impact on economic growth and employment. This section also addresses two of the key factors influencing the innovation process: human capital and the incorporation of new technologies. The chapter then examines how the institutions impact on the relationship between the three variables under study. The empirical analysis included in this chapter confirms the relationships mentioned above, taking into account not only the direct effects but also the feedback ones. To contrast the relationships the authors using partial least squares path modelling on 23 European countries for the period 2014-2016, estimating two models. First model analyzes the associations between entrepreneurship, innovation and value creation and their effects on economic growth. In addition, the exogenous latent model of social environment is included in the model as an influence on the latent variable of entrepreneurship. Second model shows the feedback effects economic growth generates on social environment entrepreneurship and value creation. The analysis of these feedback effects, not commonly conducted, is one of the most important novel aspects of this empirical analysis. The results of the model are consistent with the prior theoretical analysis; entrepreneurship, value creation and innovation have a positive impact on economic growth. In addition, the social environment positively affects entrepreneurship. Thus, improving the social environment stimulates entrepreneurship, which, in turn, encourages innovations. The feedback effects analyzed in the second model are also positive. Finally, the chapter presents a series of recommendations on economic policy that could potentially simulate entrepreneurial activity, such as reducing interest rates and improving access to credit, lowering taxes, subsidies for entrepreneurship, streamlining bureaucratic procedures and improving the social climate and entrepreneurial culture. Chapter 2 titled “Creating Value Through Entrepreneurship Based on the Economic Cycle”, by Fernando E. Callejas Albiñana and Isabel Martínez Rodríguez, uses a theoretical approach to analyze the key role of entrepreneurial activity in fostering economic growth and value creation. The chapter presents a study on entrepreneurial activity, differentiating between the two fundamental sources of motivation for an individual to engage in such activity: a perceived, unexploited business opportunity and the need to create one’s own employment due to a lack of available paid work. Accordingly, the authors begin by examining opportunity entrepreneurship and necessity entrepreneurship and their importance in overall entrepreneurial activity. They then analyze the joint effect of macroeconomic, monetary, financial and social factors on entrepreneurial activity, depending on an individual’s reason for starting an enterprise and the economic cycle. The chapter presents a theoretical study of the effects of monetary policy, fiscal policy, human capital and governments on necessity and opportunity entrepreneurship. The effects of monetary policy on entrepreneurial activity are examined, especially the way in which the volume of credit impacts on entrepreneurship, considering the phase of the economic cycle. With regard to fiscal policy, the authors study the effects of taxation on entrepreneurial activity. Drawing on Keynesian theory, the chapter argues that expanding aggregate demand by means of increasing public expenditure simulates entrepreneurial activity. The authors also consider how expansive fiscal policy in the form of increasing investment in human capital is also considered to affect entrepreneurship depending on the motivation.

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As well as purely economic factors, this study also considers social and cultural aspects, given that entrepreneurial activity is significantly influenced by the social environment in which entrepreneurs develop their activity. The authors then develop an empirical analysis by groups of countries depending on the level of entrepreneurial activity and the phase of the economic cycle, differentiating between two periods: growth (2001-2008) and the crisis and beginnings of recovery (2009-2016). To achieve these objectives, the authors propose two econometric panel data models. The first model is intended to capture the contribution of the rates of necessity and opportunity entrepreneurship to the overall level of entrepreneurship. The second model analyzes the factors that condition of necessity and opportunity entrepreneurship depending on the economic cycle. The main findings of this chapter are that human capital and governance are determinants of both necessity entrepreneurship and opportunity entrepreneurship over the two periods under study, with the positive association between government integrity and opportunity entrepreneurship being especially significant. Tax burden is a determinant for both types of entrepreneurship, although it has a greater impact on the behavior of necessity entrepreneurs than opportunity entrepreneurs. Thus, reducing taxation especially encourages necessity entrepreneurship in both periods under study, but more notably during the economic crisis. In contrast, expansive monetary policy in the form of lower interest rates is considered to be more effective in stimulating opportunity entrepreneurship. Chapter 3 titled “Innovation, Value Creation, and Entrepreneurship by Opportunity: An Analysis of European countries”, by María-Soledad Castaño-Martínez, studies the relationships between entrepreneurship, innovation and value creation, but with a special focus on specific factors affecting innovation and entrepreneurship, such as human capital, R&D investment, perception of opportunities, access to credit and regulations. The second section presents a brief review of the literature on the relationships and factors affecting entrepreneurship and innovation on value creation. The author then carries out a partial least squares analysis on 24 EU countries to 2015-2017. The exogenous latent variables proposed for this model are perception of opportunities, human capital, economic growth and business regulations, which would directly affect the latent variables of entrepreneurship and innovation, but this variable would also indirectly have an impact on value creation. The model also proposes a moderator effect between the human resources used in science, technology and R&D investment and value creation. In addition, the direct and indirect effects of opportunity entrepreneurship and innovation on the latent variable of value creation are analyzed. The results obtained are consistent with the theory previously presented: human capital, access to credit, R&D investment and the reduction of the administrative burden have a positive effect on innovation and opportunity entrepreneurship, and therefore, on value creation. Finally, the author makes a series of recommendations on economic policy based on her results which aim to incentivize entrepreneurial activity. The final exit from the crisis lies inevitably in consolidating the business sector and generating novel entrepreneurial initiatives as vehicles for economic progress and the reduction of unemployment, as is analyzed in various chapters in this book. Chapter 4 entitled “Social Entrepreneurship and Sustainable Development: New Challenges and Opportunities”, by Susana de los Ríos-Sastre and Víctor M. GonzálezSánchez, offers the reader an overview of the current situation of social entrepreneurship around the world, studying the foremost challenges and opportunities that social entrepreneurs are confronted with. Despite its lengthy trajectory and its social and economic impact, social entrepreneurship has traditionally been given scant attention, although its recent development has changed this situation. Despite xvii

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the lack of a definitive definition of social entrepreneurship, which has an impact on the selection of methodologies used to measure the phenomenon, a number of recent studies have demonstrated its growing importance. Consequently, social entrepreneurship is increasingly present in the agendas of government authorities. In the context of Europe although social entrepreneurship is not currently the subject of any specific policy, there do exist sectoral policies that encourage its development. This growing interest in promoting entrepreneurial initiative is based on its positive impact on economic growth evidenced in various studies. Despite such interest, the literature largely focuses on the factors influencing the generation of traditional entrepreneurship. The notion that entrepreneurial activity is integrated in the social environment has helped broaden out the spectrum of research toward social entrepreneurship, which essentially differs from private entrepreneurship in the nature of the project developed, innovation, the rationale and the risk. In fact, social entrepreneurship entails the production of economic and social value shared by individuals and communities, given that it is based on initiatives whose aim is the enrichment and development of a community, drawing on social interests based on innovation processes generated from unsatisfied needs. This chapter takes into account the aspects mentioned above in its analysis of the different definitions and measures of social entrepreneurship. The role of social entrepreneurship is analyzed under the 2030 Agenda for Sustainable Development, considering especially that social enterprises play a key role in achieving SDG 8 (Decent Work and Economic Growth) and SDG 10 (Reducing Inequality). There then follows a descriptive analysis of the situation of social entrepreneurship around the world, using data from the Global Entrepreneurship Monitor (GEM). Finally, the chapter’s last section is devoted to analyzing good practices undertaken by various companies in different countries. Chapter 5 entitled “Untangling the Innovativeness-Performance Puzzle”, by Tugba GurcaylilarYenidogan and Safak Aksoy, analyse the relationships between innovativeness and firm performance. The phenomenon of innovation has been studied from many perspectives, but it is especially significant because it generates positive effects on firm performance. In their analysis, the authors differentiate between technical and non-technical innovativeness. It is their opinion that non-technical innovation (organizational and marketing innovation) forms an important part of the innovation activities that support the development of technical innovation in high-technology companies. Hence, the impact of enhancing the performance of technical innovation is greater under the moderator effect of organizational and marketing innovation. Higher innovation leads to better economic performance as it influences the different sources of competitive advantage, as companies with a greater capacity for innovation can obtain competitive advantage by reducing costs and/or improving differentiation, which, in turn, leads to improved financial performance. However, it worth remembering that the value of product innovation depends on clients feeling their needs are satisfied and being willing to pay for such products. In order to reveal the relationships between technical and non-technical innovations and companies’ financial results, the authors survey 125 companies in Antalya (Turkey). Using their findings, they propose a model based on structural equation modelling (SEM), which estimates direct and indirect effects within complex causal systems that include multiple interactions between constructs They use AMOS statistical software to estimate the model. The authors thus propose moderator effects with the variables of market effectiveness and production efficiency in order to demonstrate the existence of positive indirect effects between innovativeness and financial performance.

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Finally, Chapter 6 entitled “The Influence of Government Support Interventions on the Growth of African Foreign-Owned SMMEs in South Africa”, by Lusambya Moise Lukendo, Refiloe Khoase and Patrick Ndayizigamiye, analyzes government policies designed to support foreign-owned SMEs in South Africa. The scant studies in this field despite the policies’ considerable contribution to economic growth and employment in the African country make this particular chapter interesting. The aim of the study is to determine which government measures influence the growth of foreign-owned African SMEs. Identifying such interventions will help design appropriate strategies to enhance the performance of foreign-owned SMEs, which, in turn, will contribute to the growth of the SME sector, increasing the employment rate in South Africa. Firstly, the authors review the literature, listing the different definitions of SME and analyzing the weight of foreign-owned SMEs in the economy of South Africa. They then analyze the concept of business growth, focusing specifically on six theories: resource-based view economic theory, managerial theory, evolutionary theory, social network theory, and networking theory. Secondly, they describe the goals of support interventions for SMEs in South Africa, especially those laid out in the White Paper on National Strategy on the Development and Promotion of Small Business in South Africa (1995) and the Small Business Development Department Report (2015-2016). The authors examine the measures to support training, financial support, technical support, business promotion policies and public infrastructures. Thirdly, the authors present their empirical analysis. They surveyed 60 non-South African citizens, running Small, Medium and Micro Enterprises in the Pietermaritzburg CBD (Central Business District) in South Africa. The data was analyzed using the Statistical Package for Social Sciences (SPSS). The authors used the following research techniques to analyze the data: frequency analysis, principal component analysis (PCA), Spearman’s correlation analysis and linear regression analysis. Their aim was to show that government support policies are positively related to the growth of foreign-owned South African SMEs. Their results reveal that very few foreign-owned African firms received government aid, be it financial support, technical assistance and support for training, despite previous studies reporting a positive association between the two variables. Section 2 focuses on the role of innovation including two chapters. Chapter 7 entitled “Innovation and Knowledge in the Academia: Innovation and Knowledge in the Academia”, by Andrea Rey-Martí, Carla Martínez-Climent and María Rodríguez-García, is a bibliometric analysis of the relationships between innovation and knowledge. Investment in innovation and knowledge provides organizations with advantages over their competitors. In recent years, there has been a growing interest in the association between knowledge generation and the promotion of innovation in organizations, since both elements are key in strategic terms and can generate competitive advantages for companies that engage in a strategy of investing in intangible assets. Before embarking on their bibliometric analysis, the authors define the concepts of knowledge and innovation, and analyze the ways in which knowledge can be acquired or transferred. Organizations can generate knowledge internally, but no innovation-intensive company can neglect external sources of knowledge acquisition, such as buying patent licenses, hiring external researchers or acquiring other firms. Thus, organizations that combine both forms of knowledge acquisition to develop innovative projects are those that present the best financial performance. The authors associate these forms of knowledge acquisition with more recent concepts of open innovation and ambidexterity. The aim of the chapter, then, is to conduct a bibliometric analysis drawing on quantitative biographic material extracted from the database on SSCI/JCR-ranked journals (WOS by Clarivate Analytics). The xix

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intention of the authors is to highlight the evolution of studies on this topic. In order carry out an exhaustive analysis, various aspects are considered: languages, research areas, year of publication, countries, journals and books, and authors. Broadly speaking, the authors show that the language in which the greatest number of works are published is English, followed by Spanish, the number of publications in which has grown exponentially since the start of the 21st century. The countries that publish most studies are the United States and the United Kingdom, and the journals with most articles published are Research Policy and Technological Forecasting and Social Change. The chapter also lists most cited authors and papers. Thus, this particular chapter is of great interest to people who work or are beginning to work in the field, as it provides a general overview of the issue of innovation and knowledge. Chapter 8 entitled “Blue Ocean Strategy as a Framework for Business Innovation in China and Spain: A Summative Content Analysis of Innovation Initiatives and Value Propositions”, by Maria GuijarroGarcia, Agustin Carrilero-Castillo and José Fernando Gallego-Nicholls, presents a comparative analysis of business innovation in China and Spain, based on 17 studies on innovation. The aim is to identify the Blue Ocean Strategy dimensions and two of Hofstede’s dimensions. To meet their objective, the authors define the Blue Ocean strategy and value innovation. Broadly speaking, the Blue Ocean strategy is based on creating new markets, differentiating your company from competitors, and keeping costs low, rather than the traditional strategy of competing in existing markets. This strategy was proposed by W. Chan Kim and Renée Mauborgne, professors from the INSEAD Business School, in their book, Blue Ocean Strategy. This strategy is based on the concept that organizations have to generate value for buyers, while reducing company costs at the same time. The strategy consists of capturing new demand and making the competition irrelevant. This strategy was designed by drawing on the study of cases of successful companies, but also of other companies that had not performed so well as the former cases. The authors briefly define and describe the innovation systems in China and Spain, the concepts of incremental and radical innovation and Hofstede’s cultural dimensions, of which they focus on two in particular with regard to both countries: uncertainty avoidance and long-term orientation. The authors draw on a series of research questions to compare the results of 17 publications, in order to see whether innovation in China and Spain complies with the four actions framework of the Blue Ocean Strategy. Although some of the previous chapters have touched on the changes in business management driven by digitalization, the following three chapters directly address the novel opportunities and challenges for companies of the platform economy and social networks. These chapters are grouped in Section 3. Chapter 9 entitled “The Online Platform Economy as an Entrepreneurship-Based Strategy for Value Creation: Some Considerations”, by José Manuel Saiz-Alvarez, addresses the novel topic of the online platform economy. A platform economy is one created and developed through digital platforms, that is, tools or software on the Internet facilitated by digital technology. Some platforms are traditional one-way business models, but most function as collaborative enterprises, where, thanks to the massive participation of users or networking, content is created and/or all types of information, knowledge, services and products are exchanged, bought, sold, rented, accessed or shared. The author focusses on one particular aspect of the platform economy, what is known as the “gig economy”. This term defines the employment model based on short, sporadic jobs, directly related to the development of communication technologies. Gig employees, among which there are a fast-growing number of millennials, offer their knowledge to firms and businesses by hours or days, without any xx

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contractual agreement. They are typically highly qualified individuals who work for one, or more than one employer, for specific, short periods. It is an economic model leveraged by many entrepreneurs, since platforms put freelancers into contact with employers, with the aim of engaging in a collaborative exchange, taking advantage of the developments of the Internet. Nonetheless, these novel types of activities may have significant advantages and disadvantages. Thus, the authors, following a section devoted to defining the gig economy and analyzing its importance, conduct a SWOT analysis of these new types of online activities and examine the relationship between the platform economy and value creation. In general terms, the platform economy is considered to have grown exponentially, although there are differences across countries. In developed nations, individuals are observed to offer their products and professional services in order to take advantage of a business opportunity. In developing countries, however, individuals enter into these types of economies, as they have no other employment opportunities. Thus, such online economic activities are helping reduce poverty, increase employment, and may potentially cut down economic migratory flows. This chapter also addresses the primary problems of the gig economy, such as the growing instability in certain jobs and the insecure nature of incomes. Chapter 10 entitled “Open Innovation as a Business Entrepreneurship Strategy: The Consumer as Value Creator in Digital Ecosystems”, by Miguel Angel Gomez-Borja, Carlota Lorenzo-Romero, and Leticia del-Pozo Ruiz, addresses the interesting topic of open innovation and the role of consumers in the new scenario of the platform economy. The concept of open innovation first appeared in the book “Open Innovation: The New Imperative for Creating and Profiting From Technology” published by Henry Chesbrough in 2003, where the author proposed a new innovation strategy in which firms go beyond their limits and enter into cooperation with external organizations or professionals. This involves combining their internal knowledge and external knowledge to implement strategy and R&D projects. In this context, universities and research centers are particularly significant within the ecosystem of agents with which the organization is related. In a sense, open innovation opens the door to collective intelligence. Such a concept marked a break with the closed way firms had traditionally managed innovation. With open innovation systems, enterprises can manage innovation externally, through patent licenses and technology transfer, or by jointly participating with suppliers, customers and external knowledge sources in their networks. To clarify the implications of open innovation for business strategy, the authors define the concept and compare it with the classic closed innovation model, explaining why firms are rapidly adapting to this novel model. Despite the advantages of open innovation, the increased information involved enhances the complexity and risks inherent in management. The following section focuses on crowdsourcing and how it differs from open innovation. Crowdsourcing entails reaching out to the multitude of sources on the Internet in search of creativity, experience and knowledge. Such tasks were previously undertaken by specialized professionals. Here, Internet users actively participate to exchange knowledge or make massive contributions to solve problems or respond to specific proposals that organizations post on the Internet. The chapter also describes other knowledge sharing modalities that might be useful for companies, such as crowd wisdom, crowd production, crowd collaboration, crowd voting and crowdfunding, as well as looking at the advantages for individuals of taking part in these collaborative processes. Finally, the authors analyze the role of consumers in this scenario, who become active agents, providing companies with information and knowledge to implement strategies across the Internet that better xxi

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meet consumers’ needs. They also address the concept of prosumer (producer-consumer), referring to joint production between customers and producer through the sharing of knowledge and experiences on the Internet, which affects firms’ innovations processes and value creation. Chapter 11 entitled “Value Propositions for Companies in Their Payment Ads in Networks: How to Generate Value and Return”, by Rafa Marín Pastrana, analyzes how widespread use of the Internet and social media is modifying firms’ marketing strategies and advertising campaigns. The author examines the recent changes in the consumption of digital content and how the audience of traditional television is falling due to users shifting to the consumption of digital content on Smart TVs with Internet connections, tablets, etc., while the real revolution in digital consumption is happening in the use of cellphones. Firms, then, need to orient and segment customers for their advertising on these devices to be effective. Companies study the digital footprint users leave when they search on the Internet, in order to create consumer/user profiles to whom they can direct specific advertising campaigns. Nonetheless, mass, indiscriminate advertising can be intrusive and provoke fatigue in users, generating the opposite of the intended effect. The author analyzes the role of Internet search engines, especially Google, in achieving advertising that is more effective. Finally, the chapter looks at the role of consumers on social media and its potential for companies, since these networks offer more direct communication with users. In addition, the author argues that although the potential of social networks for firms is significant, it must not be forgotten that the core of these media is the communication between families and friends, which makes it a substitute for the traditional “word of mouth”. Thus, it is key to design advertising campaigns that take this and its possible implications into account. Finally, the chapter examines the repercussions for the credibility of social networks of the recent Facebook scandal. Finally, Section 4 includes three chapters that studies some aspects related to entrepreneurship and value creation in some activities such as management, tourism and air transportation. Changes in talent management and the need for highly qualified workers have given rise to a new model of human resource management, addressed in Chapter 12 entitled “Talent Revolution: New Challenges in People Management”, elaborated by Dolores Botella-Carrubi and Marta Tudela-Torras. Organizations currently work in fast-changing environments, typically characterized by great uncertainty and volatility. This is largely the result of innovation processes that have recently become so rapid that the life cycle of products and services is growing ever shorter. Considering these fast-moving economic and social changes, the authors examine how the talent of individuals who work in organizations is managed. The chapter begins by reviewing the different definitions of talent and then compares talent management in the 20th and 21st centuries. The 20th century is typified by the development and retention of skilled professionals, that is, organizations attempt to stop highly qualified professionals moving to other companies. It was also when the management of internal and external talent emerged, whereby organizations try to identify individuals who can add value to the entity; these individuals might also be professionals from outside the organization. In other words, companies are interested in having the best professionals available. In contrast, the 21st century sees the emergence of human capital as a key element in the management of organizations. Moreover, populations have become more heterogeneous; workers are from different countries of origin and are of different gender, race and different generations. Society begins to consider that workers need to have a balance between their work life and personal life, while digitalization is transforming the way the different agents provide information, on both companies and workers. In some xxii

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cases, candidates now even choose their employers, especially those most highly qualified. This means that companies have to compete to capture the most talented professionals, which has led companies to prioritize positioning themselves on social media and creating an employer brand. Workers, then, are a key element in the value creation process, and hence, this chapter analyzes the new challenges of people management for the 21st century: employer branding, generational diversity and digitalization. Regarding employer branding, the authors analyze the creation of a brand to attract and retain the most talented workers who can contribute to value creation in the organization. They also examine the co-existence in a company of different generations, with different qualifications, values, preferences, and how this diversity is necessarily managed. In addition, they look at how digitalization, especially social networks, have changed the way talented workers are attracted and selected, and how this has generated considerable savings if costs in terms of money and time. Chapter 13 entitled “Innovation in the Measurement of Tourism Competitiveness”, by Jose Manuel Guaita Martinez, José María Martín Martín and José Antonio Salinas Fernández, proposes a new instrument to measure competitiveness in the tourism sector, which permits a comparison of the core elements and determinants of international competitiveness. Tourism is one of the key sectors that create value creation in many countries and thus, it is necessary to measure competitiveness in the industry in order to help policy makers design tourism policies that serve to encourage entrepreneurial activity in the sector. Competitiveness in tourist destinations has been widely studied, but there is no consensus on its definition. The authors conduct a review of the literature on the concept of tourism competitiveness, considering different factors or dimensions that influence the level of success of a given destination. A number of studies have considered variables related to the competitiveness of tourist destinations, including, on the one hand, objective indicators, such as number of visitors, tourist spending, employment created in the sector, and, on the other, subjective variables, such as the wealth and diversity of the cultural heritage or the quality of the tourist experience. Other authors, in contrast have examined variables including value creation, sustainability, and the wealth this sector generates in an economy. Due to this difficulty in reaching a consensus on how to measure international tourism competitiveness, the World Economic Forum (WEF) created the Travel & Tourism Competitiveness Index (TTCI) in 2007, which constitutes a useful tool to classify groups of countries according to their tourist performance. However, this index presents certain limitations, such as the aggregation of the indicators. Moreover, the index lacks a detailed analysis of the dimensions with the greatest impact on tourism competitiveness, and which determine the disparities between the countries under study. Taking these limitations into account, this chapter proposes an innovation in measurement of tourism competitiveness. This novel methodology resolves the problems arising from the aggregation of variables expressed in different units, the arbitrary weighting of such variables and the redundancy of the information generated by integrating them in a composite indicator. Given that the TTCI is an unweighted mean of 90 simple variables grouped into 14 pillars, the authors propose an innovation in the methodology based on the construction of synthetic indicators, incorporating factors such as social well-being, social and economic development and environmental sustainability. Finally, the chapter presents the results obtained for 136 countries and compares them with those of the TTCI, which allows the authors to better identify the pillars or dimensions that determine tourism competitiveness and explain the differences between the selected countries. The findings facilitate the design of tourism policies with a direct impact on the most significant dimensions of competitiveness, xxiii

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and which will have, therefore, the most effective outcomes. This innovation in the measurement of tourism competitiveness makes the process more objective, and, consequently, policies implemented based on these findings will be more in line with the real scenario Chapter 14 entitled “Some Considerations about Value Creation in regard to Entrepreneurship and Innovation from Public Service Obligations on Scheduled Air Transport”, by Antonio Martínez Raya and Víctor M. González-Sánchez, describes the situation of European airlines in the single market after the process of liberalization of air transport implemented in the European Union between 1993 and 1997. This opening up of air transport services gave rise to new business opportunities, but, some routes in peripheral areas were sidelined, provoking a market failure. Consequently, the liberalization and creation of a single market in the air transport sector triggered two situations. Firstly, airlines have made changes in their management systems and business strategies, leading to a reduction in costs, together with the introduction of innovations, all of which has enhanced their efficiency. Moreover, most of them have taken advantage of the benefits of a wider market. All the above has yielded various positive effects; airlines have been able to provide air transport services at lower prices and with an adequate quality, while experiencing, in turn, substantial growth. Nonetheless, some companies, such as Alitalia, have not been able to adapt to this process, generating a conflict between the Italian government and the European Commission. The second outcome of this process of market liberalization is that certain remote or less densely populated area have been neglected by the private airline companies, either due to their being unprofitable or through a lack of interest in covering these routes, even if they constitute a business opportunity. In these cases, the member states are able to intervene and impose the obligation of providing a public service. Thus, the member states are responsible for estimating air transport needs in their jurisdictions and for safeguarding the provision of services. Hence, they are tasked with awarding the contracts to airline companies, although they are obliged to inform the European Commission of the process. This chapter justifies the provision of these unserved routes as a public service because the improved connections and access to all areas of the European Union will contribute to the economic and social development of the affected regions. Thus, the inhabitants will have the benefits of enhanced connectivity and the company awarded the contract will normally receive a financial compensation for providing the services. Thus, the market failure arising from the liberalization of the air transport market in the European Union is resolved. Taking the above into account, the authors focus on the following points within this broad area of study: first, a singular framework to understand the problem of the imposition of public services on programmed air routes in the EU; second, how the imposed air routes may create value for regional economies by drawing on innovation and entrepreneurial spirit with the EU single market; and, finally, a case study, that of the obligatory public service air routes in Spain. The authors also analyze the problems that might arise in this process, the most notable being that member states might leverage these tendering systems to aid certain airlines, which would be a distortion of competition in the European single market. In addition, the chapter presents a brief analysis of the implications of Brexit for the air transport single market. In short, the chapters including in the book offer a study of three variables, entrepreneurship, value creation and innovation, which play are important role in the evolution of the economy in general and of the firms, taking into account the main interrelations among them.

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The consideration of economic growth as one of the important objectives of economic policy has led, among other issues, to the development of different models and to carry out a great number of estimations in order to determine the factors that could improve the achievement of this objective. This process was also benefited thanks to an improvement in statistical information, which allowed the inclusion of a greater number of variables in the estimations. In this way, not only the traditional quantitative variables (capital, labor ...) were considered, but others of a qualitative nature (rule of law, democracy ...) were also gradually included. In this process, one of the factors that have been considered as a relevant economic growth enhance factor is entrepreneurship, because this factor not only had direct effects on growth, through the employment they generated, but also indirectly, due to introduction of innovations to be more competitive. The main problem in order to analyse the entrepreneurial activity is to define it. From a historical point of view, the entrepreneur concept and the idea of entrepreneurial activity have been developed including different characteristics (Galindo and Mendez, 2010, pp. 7-9). Traditionally Cantillon (1755) is considered as the first thinker that used the concept “entrepreneur”. However, it is possible to find relevant references to entrepreneur activity and early forms of organization during the Scholastic School. Following to Raymond de Roover (1974, pp. 339-345) the Franciscan theologian and preacher San Bernardino of Siena (1380-1444) considered three kind of merchants whose services are valuable to the commonweal: Importers-exporters (mercantiarum apportatores), whose activity has also described by Duns Scotus; “store-keepers” (mercantiarum conservatores), that perform warehousing activities; and finally manufacturers (mercantiarum immutatores seu melioratores) whose activity is to transform raw materials into finished products. The word “entrepreneur” is of French origin and as Hebert and Link (1988, p. 17) states was used, in a common but imprecise form, before Cantillon´s book. The word can be found in Savary´s Dictionnaire Universel de Commerce published in Paris in 1723, considering that entrepreneur is a person who undertakes a project. This concept is not usually in the economic literature and Cantillon was probably the first in introduce this word in the economic analysis, considering entrepreneur as a self-employ person that adjust his activity to the market demand. From his point of view, the main entrepreneur’s function is to obtain profit and assume risk. Thanks to this entrepreneur activity society obtain benefits and it is so relevant that Cantillon divides society in two groups of individuals: entrepreneurs and non-entrepreneurs. From the Classical School of Thought point of view some authors also considered the role of the entrepreneurs. In this sense, Blaug (1986) as well as Schumpeter (1954) considered that these authors imagined an automatic production process in which there weren’t relevant decisions, except those related 

Introduction

to saving or consumption. For this reason a specific theory on entrepreneur was not developed. They were not so worry on to determine entrepreneur’s functions but on the capital accumulation process. In this sense, Kirzner (1973) considers that the Classical School was worrier on long-term, so it was more interest to analyse the capital than the achievement of pure benefit. Schumpeter (1954) stated that J. B. Say was the first thinker to attribute to entrepreneur –as a separate figure from capitalist- a certain position in the economic process scheme. Say (1803) considered that the entrepreneur had to apply the knowledge derived from the natural processes to achieve a practical goal and he foresees the Schumpeterian distinction between invention and innovation. The entrepreneur is the principal agent in the production process being a dealer between supply and demand and he assumes risk. From the Neoclassical perspective, Marshall (1980) considered an entrepreneur very similar to the Schumpeterian view. However, he viewed entrepreneurship as synonymous with business management and for this reason he suggested, in a similar way as Mangoldt (1855), that the payment of his function could be seen as rent on ability (Swedberg, 2000, p. 19). Marshall also considered that his relevance diminishes as soon as the business arte developed and their direction is more specialized. Walras (1954) developed a framework based on the general equilibrium in which the entrepreneur activity will be carried out. Therefore, from an historical point of view, authors have focused their attention in some characteristics or entrepreneur´s peculiarities that can be summed up in the following aspects (Herbert and Link, 1982, Nijkamp, 2000 and Galindo and Mendez, 2010): 1. Assume risks: Cantillon, Cole, Hawley, Knight, Mill, Mises, San Bernardino de Siena, Shackle and Thtinen. 2. Contributes financial resources: Böhm-Bawerk, Mises, Pigou and Smith. 3. Innovator: Bentham, Schmoller, Schumpeter, Shakle, Sombart, Thtinen and Weber. 4. Take decisions: Cantillon, Cole, Keynes, Marshall, Menger, Mises, Schultz, A. Walker, F. Walker and Wieser. 5. Sector´s leader: Marshall, Xenophon, Saint-Simon, Say, Schumpeter, Sombart, A. Walker, F. Walker, Weber and Wieser. 6. Manages or supervises: Marshall, Menger, Mill and Say 7. Organizes and coordinates the economic resources: Clark, Coase, Davenport, San Bernardino de Siena, Say, Schumpeter, Sombart, Weber and Wieser. 8. Firm owner: Hawley, Pigou, Quesnay and Wieser. 9. Uses the production factors: Keynes, A. Walker, F. Walker and Wieser. 10. Trade: Bentham. 11. Allocate resources: Cantillon and Schultz. From a modern perspective, the main problem is that there is not a generally accepted definition of this concept (Nissan, Galindo and Méndez, 2011). In general terms, Wennekers and Thurik (1999), following the ideas exposed by Herbert and Link (1989), Bull and Willard (1993) and Lumpkin and Dess (1996), define entrepreneurship as the manifested capacity and desire of the individuals to create new business opportunities—that is, new products, new organization forms, new production methods—and to introduce their ideas in the markets confronting uncertainty and other obstacles, adopting decisions on localization and on the use of resources. These decisions could be adopted individually or in networks included or not in institutions.

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Considering this definition, the following characteristics can be considered (Galindo et al. 2010, p. 133): First, the definition takes into account the economic agents’ behavior. In this sense, entrepreneurship cannot be only considered as an occupation but also an activity that considers the different circumstances and aspects of a person that carries out this activity. Second, entrepreneurships must consider uncertainty and the different obstacles inherent in the business creation process. Third, they must have information or main ideas about efficient production processes, as well as new organizational forms. However, this doesn’t mean entrepreneurs must attended special academic courses about management to learn or get such information. They can get the information or advice from experts to execute the idea. And finally, the entrepreneurs can be also encountered in big firms. In this case, they are named “entrepreneurs’” or “corporate preneurs.” (Arendt and Brettel 2010). Considering the modern perspective different types of entrepreneurships can be considered (Nissan, Galindo and Méndez, 2011, p. 315). First, taking advantage of profit opportunities (Kirzner 1973, 1999). Kirzner agrees with Schumpeter that an entrepreneur tries to take advantage of profit opportunities, but contrary to Schumpeter’s view, Kirzner says the entrepreneur learns from past mistakes and tries to correct them, driving the market toward equilibrium. Therefore, from this perspective is possible to consider a relationship between institutions and entrepreneurships that would have a positive effect on economic progress, because institutions facilitate the competitiveness level that entrepreneurships need and institutions also facilitate the incentives structure that encourages entrepreneurships to develop their activity. Second, it is important consider the role of uncertainty (Knight 1921). He distinguished between risk and uncertainty, being the former insurable because it refers to recurrent events, the relative frequency of which is known from experience. On the other hand, uncertainty is not insurable because it relates to events the probability of which is only subjectively estimated. Knight considered uncertainty as an important factor considered by entrepreneurs because they have to carry out their activity and to adopt decisions in an uncertain world. Their profits are a reward for bearing this uncertainty. Third, it is also interesting to consider the entrepreneurship differentiation defended by Baumol (1990), ranking them between “productive” and “non productive”. From his point of view, entrepreneurs are creative and ingenious, searching the more appropriate means to increase their wealth, power and prestige. The existing environment around them has an important influence on their decisions. For this reason, it is possible to find different kinds of entrepreneurships. Finally, it is also necessary the entrepreneur´s innovator role, following Schumpeter’s (1950, 1911) thesis. Schumpeter considers that entrepreneurship activity implies innovation in the introduction of a new product, organization or process, generating a destruction process. He creates new industries and for this reason he causes relevant structural changes in the economy. Entrepreneurs cannot be considered as inventors because they adopt the inventions created by others. When an entrepreneur gives up innovation, he loses his entrepreneur condition. For this reason the Schumpeterian vision implies that the entrepreneur is an innovator that destroys the existing structures. From a more modern and general point of view, entrepreneurship entails the creation of a new firm, but doesn’t imply that the entrepreneur must create new products. He/she can generate a new business without being an innovator in the Schumpeterian sense and assimilate the technological advances. Considering all these elements, an important literature has appeared in order to analyze the different aspects and effects of entrepreneurship activity identifying three essential elements: autonomy, innovation and opportunities (Lumpkin & Dess, 1996; Miller, 1983 and Stevenson & Jarillo, 2007, Galindo, Castaño and Méndez, 2018). Autonomy considers the entrepreneur’s independent behavior when achieving proposed objectives and using the opportunities presented (Lumpkin, Cogliser, & Schneider, 2009; xxvii

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Rindova, Barry, & Ketchen, 2009). Innovation involves the introduction of new technologies and the employment and outcomes from their application (Autio, Kenney, Mustar, Siegel, & Wright, 2014). An finally, opportunities could be considered as future possibilities that depend on individual preferences and that are susceptible to variation (Baron, 2006; Venkataraman, 1997). It is expected that entrepreneurships using these three elements can achieve value creation, considered as the actions that increase the value of the company’s goods and services. This value creation can be considered as an efficiency measure of entrepreneurship activity: the greater the value creation, the more effective the entrepreneurship. For this reason is important to analyze the relationship between value creation and entrepreneurship, not only for company evolution but also for the entire economy, makes it necessary to examine what factors could potentially enhance value creation. And innovation is a factor that has an important role in this process. The different chapters included in this book studies different aspects and topics related to these three elements.

REFERENCES Arendt, S., & Brettel, M. (2010). Understanding the influence of corporate social responsibility on corporate identity, image, and firm performance. Management Decision, 48(10), 1469–1492. doi:10.1108/00251741011090289 Autio, E., Kenney, M., Mustar, P., Siegel, D., & Wright, M. (2014). Entrepreneurial innovation: The importance of context. Research Policy, 43(7), 1097–1108. doi:10.1016/j.respol.2014.01.015 Baron, R. A. (2006). Opportunity recognition as pattern recognition: How entrepreneurs “connect the dots” to identify new business opportunities. The Academy of Management Perspectives, 20(1), 104–119. doi:10.5465/amp.2006.19873412 Baumol, W. J. (1990). Entrepreneurship: Productive, unproductive and destructive. Journal of Political Economy, 80(5, Part 1), 893–921. doi:10.1086/261712 Blaug, M. (1986). Economic history and the history of economics. New York: New York University Press. Bull, I., & Willard, G. E. (1993). Towards a theory of entrepreneurship. Journal of Business Venturing, 8(3), 183–195. doi:10.1016/0883-9026(93)90026-2 Cantillon, R. (1755). Ensayo sobre la Naturaleza del Comercio en General. Fondo de Cultura Económica, Méjico. de Roover, R. (1974). The scholastic attitude toward trade and entrepreneurship. In J. Kirshner (Ed.), Business, Banking, and Economic Thought in Late Medieval and Early Modern Europe. Selected Studies of Raymond de Roover (pp. 336–345). Chicago, IL: The University of Chicago Press. Galindo, M. A., Castaño, M. S., & Méndez, M. T. (2018). Digital transformation, digital dividends and entrepreneurship: A quantitative analysis. Journal of Business Research. doi:10.1016/j.jbusres.2018.12.014 Galindo, M. A., Mendez, M. T., & Alfaro, J. L. (2010). Entrepreneurship, income distribution and economic growth. The International Entrepreneurship and Management Journal, 6(2), 131–141. doi:10.100711365-010-0142-3 xxviii

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Galindo-Martin, M. A., & Méndez-Picazo, M. T. (2010). Institutions, entrepreneurship and economic growth. Paper presented at XIII Colloque Charles Guide PHARE, Paris, France. Herbert, R. F., & Link, A. N. (1989). In search of meaning of entrepreneurship. Small Business Economics, 1, 39–49. doi:10.1007/BF00389915 Kirzner, I. M. (1973). Competition & entrepreneurship. Chicago: University of Chicago Press. Kirzner, I. M. (1999). Creative and/or alertness: A reconsideration of the Schumpeterian entrepreneur. The Review of Austrian Economics, 11(1/2), 5–17. doi:10.1023/A:1007719905868 Knight, F. (1921). Risk, uncertainty, and profit. New York: Houghton Mifflin. Lumpkin, G. T., Cogliser, C. C., & Schneider, D. R. (2009). Understanding and measuring autonomy: An entrepreneurial orientation perspective. Entrepreneurship Theory and Practice, 33(1), 47–69. doi:10.1111/j.1540-6520.2008.00280.x Lumpkin, G. T., & Dess, G. G. (1996). Clarifying the entrepreneurial orientation construct and linking it to performance. Academy of Management Review, 21(1), 135–172. doi:10.5465/amr.1996.9602161568 Marshall, A. (1890). Principles of economics. Oxford, UK: Thommes Continuum. Miller, D. (1983). The correlates of entrepreneurship in three types of firms. Management Science, 29(7), 770–791. doi:10.1287/mnsc.29.7.770 Nijkamp, P. (2000). Entrepreneurship in a modern network economy. Research Memorandum 2000-42, Vrije Universitiet, The Netherlands. Nissan, E., Galindo-Martin, M. A., & Méndez-Picazo, M. T. (2011). Relationship between organizations, institutions, entrepreneurship and economic growth process. The International Entrepreneurship and Management Journal, 7(3), 311–324. doi:10.100711365-011-0191-2 Rindova, V., Barry, D., & Ketchen, D. J. Jr. (2009). Entrepreneuring as emancipation. Academy of Management Review, 34(3), 477–491. doi:10.5465/amr.2009.40632647 Say, J. B. (1803). Cours Complet d’Économie Politique Practique. Paris: Guillaumin. Schumpeter, J. A. (1911). The theory of economic development. New York: Oxford University Press. Schumpeter, J. A. (1950). Capitalism, socialism and democracy. New York: Harper & Brother. Schumpeter, J. A. (1954). History of economic analysis. New York: Oxford University Press. Stevenson, H. H., & Jarillo, J. C. (2007). A paradigm of entrepreneurship: Entrepreneurial management. In A. Cuervo, D. Ribeiro, & S. Roig (Eds.), Entrepreneurship (pp. 155–170). Berlin, Germany: Springer. Swedberg, R. (2000). The social science view of entrepreneurship. In R. Swedberg (Ed.), Entrepreneurship. The social science view (pp. 7–44). Oxford, UK: Oxford University Press.

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Venkataraman, S. (1997). The distinctive domain of entrepreneurship research: An editor’s perspective. In J. Katz, & R. Brockhaus (Eds.), Advances in entrepreneurship, firm emergence, and growth. vol. 3. Advances in entrepreneurship, firm emergence, and growth (pp. 119–138). Greenwich, CT: JAI Press. von Mangolt, H. (1855). The precise function of the entrepreneur and the true nature of entrepreneur’s profit. In F. M. Taylor (Ed.), Some readings in economics. Ann Arbor, MI: Academic Press. Wennekers, A. R. M., & Thurik, A. R. (1999). Linking entrepreneurship and economic growth. Small Business Economics, 13(1), 27–55. doi:10.1023/A:1008063200484

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Chapter 1

Value Creation, Innovation, and Entrepreneurship: Feedback Effects

Miguel-Angel Galindo-Martín University of Castilla-La Mancha, Spain María-Teresa Méndez-Picazo https://orcid.org/0000-0002-3045-0980 University Complutense of Madrid, Spain

ABSTRACT The literature has traditionally focused on the relationship between innovation and entrepreneurial activity, adopting mainly two perspectives when addressing entrepreneurship: empirical studies focusing on the behaviour of companies, and studies that consider entrepreneurship as a factor promoting the achievement of economic policy objectives. Following Schumpeter, innovation is a key source of value creation, generating growth in companies and the economy as a whole. But it is also important to remember the feedback effects generated in this process. This chapter analyses the relationship among three variables: entrepreneurship, innovation, and value creation, as well as the subsequent feedback effects. The theoretical aspects are considered and an empirical analysis is developed for the case of some European countries.

INTRODUCTION The last crisis suffered by the economies has meant that, among other issues, the analysis and determination of those factors and variables that exert a positive effect on economic growth and that stimulate business activity would be prioritized. In this sense, policies makers could design measures to enhance such factors and variables having also positive effects on other economic policy objectives, such as the creation of higher employment, and finally greater social welfare. Entrepreneurship has been highlighted as a factor that would have a positive effect in both areas. DOI: 10.4018/978-1-7998-1169-5.ch001

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 Value Creation, Innovation, and Entrepreneurship

For this reason, economic literature has focused on the role of entrepreneurs in the economy, considering entrepreneurs as generators of a country’s economic growth and, therefore, social welfare. The main reason is that entrepreneurs show an adequate capacity to generate products, and more specifically, to use productive resources in order to introduce innovations. Therefore, there are many empirical and theoretical analysis that views entrepreneurs also as generators of wealth and employment (Alpkan, Bulut, Gundy, Ulusoy, & Kilic, 2010; Andersen, 2011; Chilton & Bloodgood, 2010). Consequently, countries in which the effects of the recession are more severe, and show relevant unemployment rates introduce measures to boost entrepreneurial activity in their economic policies (Acs, Audretsch, Braunerhjelm, & Carlsson, 2004; Acs, Audretsch, Braunerhjelm, & Carlson, 2005; Acs, Audretsch, Braunerhjelm, & Carlsson, 2012; Acs & Szerb, 2007; Audretsch, Bonte, & Keilbach, 2008; Audretsch & Keilbach, 2004a, 2004b; Hamilton, 2007; Noseleit, 2013). With regard to specialized literature, the role of Entrepreneurship has been analyzed from two points, mainly in view of the empirical works focused on company behavior (Audretsch & Keilbach, 2004, Bierwerth, Schwens, Isidor, & Kabst, 2015; Ndubisi & Iftikhar, 2012 and Zahra, Jennings & Kuratko, 1999). Secondly, those who consider Entrepreneurship as one of the factors that inactively economic policy objectives, mainly economic growth in a direct way, and employment and social welfare indirectly (for example, Holcombe, 1998, Audretsch, 2005, Audretsch, Grilo, & Thurik, 2007, Alpkan, Bulut, Gundy, Ulusoy & Kilic, Acs, Audretsch, Braunerhjelm, & Carlsson, 2011, Braunerhjelm & Henrekson, 2013, Galindo & Méndez, 2014, Holcombe, 2007, Thornton, Ribeiro-Soriano, & Urbano, 2011, Castaño, Méndez & Galindo, 2015, 2016). In both groups of studies, it is considered that entrepreneurial activity would enhance growth innovation and value creation (Marchesnay & Julien, 1990, Vivarelli & Pianta, 2000, Sarkees & Hulland, 2009, Galindo Martin, Ribeiro & Méndez Picazo, 2012, Nambisan, 2017; Galindo, Castaño & Méndez, 2019), and the positive impact on innovation and value creation it would have a positive effect on shareholders, customers and workers. For these reasons it is possible to state that innovation, value creation and Entrepreneurship act together not only to stimulate business activity but also to achieve different economic objectives such as economic growth and the society welfare. A large body of the literature has focused on the relationship between entrepreneurship and each of these three factors individually, without considering the potential interrelations between them. The three essential elements of entrepreneurship considered by the specialised literature, that is, autonomy, innovativeness and opportunities allow that entrepreneurship will achieve the corresponding value creation, understood as the actions executed to increase the value of the goods and services created by the company. The higher the degree of value creation, the more effective is entrepreneurship assumed to have been in its activities. Thus, a considerable number of works have focused on the relationship between these two factors. On the other hand, the importance of this process, not only for the evolution of companies themselves but also for the economy as a whole, makes it important to examine the factors that potentially have an impact on enhancing value creation (Lepak, Smith & Taylor, 2007). It is also important to consider the effects of entrepreneurship and value creation on society in general. One way to contemplate these effects is through the improvement in economic growth, since higher growth could improve income distribution, increase employment and finally society welfare is improved. Regarding entrepreneurship there is a wide literature that shows the relationship between this variable and economic growth (Acs, Audretsch, Braunerhjelm, & Carlson, 2004, 2005, 2011; Acs & Szerb, 2007; Audretsch, Bonte, & Keilbach, 2008; Audretsch & Keilbach, 2004a, 2004b, 2008; Audretsch, Keilbach, & Lehmann, 2006; Belso Martinez, 2005; Braunerhjelm & Henrekson, 2013; Galindo & Méndez, 2014; 2

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Hamilton, 2007; Holcombe, 2007; Mueller, 2007; Noseleit, 2013; Roper, 2007; Spencer, Kirchhoff, & White, 2008; West, Bamford, & Marsden, 2008, among others). In general terms, greater entrepreneurial activity will mean greater growth. Regarding the value creation, it could be said the same. Due to this beneficial effect it is important to also consider those factors that have a positive impact on entrepreneurship and value creation, since the policies designed to favor them would have an indirect beneficial effect on growth. In this sense, two factors will be considered: social environment that would affect the entrepreneurship and innovations that influence value creation. Within this field, literature has traditionally considered innovation as an essential factor, since according to Schumpeter, it is one of the essential factors to value creation, generating significant growth for both companies and the economy as a whole (Schumpeter, 1934, 1939, 1942). It could also be added that the innovative processes that have taken place in the last decades have been accompanied by digital transformations that have also helped to stimulate value creation (Nambisan, Lyytinen, Majchrzak & Song, 2017; Galindo, Castaño & Méndez, 2019). Finally, it is also interesting to consider feedback effects, that is, how greater economic growth would positively stimulate entrepreneurial activity, which in turn would be stimulated to introduce innovations that would increase value creation. The aim of this chapter is to analyse the relationship between entrepreneurship, innovation and value creation, as well as the subsequent feedback effects. In section 2 the theoretical framework would be developed. In section 3 the empirical analysis is developed, using where we use the partial least squares (PLS) method to examine data from 23 countries, and Section 4 presents the main conclusions

Relationship Between Value Creation, Innovation and Entrepreneurship As it has been indicated in the previous section, entrepreneurship is considered to have a positive effect on economic growth. Probably, Schumpeter is one of the first authors to consider the relevant role of entrepreneurship in the economic growth process (Nissan, Galindo & Méndez, 2011). In his article entitled, “Theoretical problems of economic growth” published in 1947 (Schumpeter 1947, pp. 2-3), shows that different factors, such as social organization, institutions, technology… have been considered by the literature as economic growth enhancing. However, from his point of view, all these factors are not enough to explain economic growth process, being necessary to consider an additional factor that is entrepreneurship (Schumpeter, 1947, p. 8). From a Schumpeterian perspective, entrepreneur is a leader that “leads” the means of production into new channels (Schumpeter, 1934). He analyses the possibility of introducing new merchandise or improve the organization of his business, considering the possibility of increasing his profits. To achieve this objective, he will introduce the innovations most appropriate. So, technological progress and the introduction of innovations depend on entrepreneurial activity (Galindo & Méndez, 2013). In this sense, innovation is considered that innovation not only involves the introduction of new technologies but also the employment and outcomes from their application (Autio, Kenney, Mustar, Siegel, & Wright, 2014; Öberg, 2019). It is important to take into account the relationship between innovation and entrepreneurship. In this sense, Drucker (1998) states that innovation is at the heart of entrepreneurship activity and thanks to innovation process many entrepreneurships carry out their activity. Taking this perspective into account, a feedback effect between both factors can be considered: entrepreneurships innovate and the innovations stimulate other entrepreneurs to carry out their activity (Huang, Chou & Lee, 2010; De Cleyn & Braet, 2012; Zortea-Johnston, Darroch, Matear, 2012, Zhao, 2015; Bogers et al, 2017). 3

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Of the factors that enhance the process of innovation, two are more significant. First, human capital: entrepreneurs with more skills and a higher training facilitate not only innovation but also the introduction of new technologies in the production process (Jimeno, Folta, Cooper & Woo, 1997; Davidson & Honig, 2003; Cooper, 2006; Xiao & Smith, 2007; Hallin & Marnburg, 2007; Shaw & Williams, 2009; Unger, Rauch, Frese & Rosenbusch, 2011; Castaño, Méndez & Galindo, 2015; Höflinger, Nagel & Sandner, 2018; Lee & Trimi, 2018; Rajapathirana & Hui, 2018; Ryan & Daly, 2019). Considering all these aspects it is necessary to consider the role of entrepreneurship, who is a person that is an innovator or an entrepreneur in Schumpeterian terms. In this sense, the analysis must be carried out considering the economic agent`s behavior taking into account that entrepreneurship is not an occupation but an activity, being necessary to consider all the different circumstances and aspects of the person who is carrying out that activity and the role of uncertainty and obstacles inherent in the business creation process (Devece, Palacios-Marques & Fernandez, 2011; Giacomin, Janssen, Pruett, Shinnar, & Llopis, F, 2011; Nielsen & Lassen, 2012; Bettiol, Di Maria & Finotto, 2012, Galindo & Méndez, 2013). On the other hand, the entrepreneurship factor also includes persons that search information or ideas about efficient production processes, as well as new organizational forms. From this perspective, different types of entrepreneurships can be considered (Nissan, Galindo & Méndez., 2011, Galindo & Méndez, 2013). First is the innovator, following Schumpeter’s (1934, 1942) thesis. In this case, entrepreneurship activity implies innovation in the introduction of a new product, organization or process, generating a destruction process. The introduction of new technological production processes creates new industries that cause relevant structural changes in the economy. This is the type of entrepreneurship considered in this chapter. Second is the entrepreneur that takes advantage of profit opportunities (Kirzner, 1973, 1999). In this case, entrepreneurship is considered as an activity that tries to take advantage of profit opportunities, but, contrary to Schumpeter’s view, from this perspective it is considered that the entrepreneur learns from past mistakes and tries to correct them, driving the market toward a new equilibrium. Third, uncertainty element must be taken into account (Knight, 1921). In this case, it is important to distinguish between risk and uncertainty, being uncertainty an important factor in the entrepreneurial activity due to entrepreneurs must adopt decisions in an uncertain world. And the last type is the distinction between productive and non-productive entrepreneurships (Baumol, 1990). In this case, entrepreneurs are considered as creative and ingenious. Their main objective is to search the most effective and appropriate means to increase their profits, power and prestige. However, they must consider the existing environment around them because it would able to have an important influence on their entrepreneurial decisions (Galindo-Martín, Méndez-Picazo & Alfaro-Navarro, 2010, Farinos, Herrero & Latorre, 2011). As regards value creation, that is actions that increase the value of the company’s goods and services, it has been pointed out that there is a positive relationship between such value and entrepreneurship (Amit & Zott, 2001, Adner & Kapoor, 2010; Galindo, Castaño & Méndez, 2019; Hitt, Ireland, Sirmon, & Trahms, 2011; Huarng & Yu, 2011; Ireland, Hitt, Camp, & Sexton, 2001; Mishra, 2017; Van Praag & Versloot, 2007). It is necessary to consider that both factors, value creation and entrepreneurship, will enhance economic growth, having the positive effects on the country welfare. For this reason is important to determine those factors that have any effect on entrepreneurship and value creation since its improvement will indirectly enhance economic growth. With regard to entrepreneurship, in general terms, benefits are the essential variable that encourages their activity using innovation to achieve greater benefits. But, from a Schumpeterian perspective, it is also necessary to consider the

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social environment as relevant factor that greatly affects entrepreneurial activity. This variable includes the social groups’ reaction on entrepreneurial activity and especially to the innovation process that the entrepreneur introduces. Economic freedom and corruption, among others, are factors that could be included in social environment variable. They could generate a negative social environment that would negatively affect entrepreneurial activity. In order to enhance entrepreneurial activity, it is important to consider the social environment and especially the public governance. Together the fiscal and monetary policies designed by policy makers it is also necessary to consider the quality of government. Laws, corruption control, rule of law…, create incentives for economic agents to develop and to increase their activity, having a relevant effect on economic growth. In this sense, governance concept must be included and its analysis could be carried out from two perspectives. First, determining the factors under which government activity can be more efficient in terms of social environment and of welfare. And second, analyzing the outcomes obtained (Méndez-Picazo, Galindo-Martín & Ribeiro-Soriano, 2012) But it is also necessary to take into account that the institutions must include the following characteristics to achieve a positive effect on social environment and indirectly on economic growth (Acemoglu 2003, 27): 1. They must enforce the property rights for a broad section of the society. Thanks to such behaviour, individuals have incentives to invest because their property is secured. 2. They must constrain the actions of some pressure groups, elites as well as politicians, to avoid actions that could damage property rights (for instance to expropriate incomes). 3. They must introduce degrees of equal opportunities for broad segments of the society, so more individuals can participate in productive economic activities. This goal is achieved by facilitating access to a better human capital formation as well as facilitating access to financial resources to increase investment activity. For this reason, governance would have a direct and indirect effect on economic growth (Andersén 2011; Aspara, Lamberg, Laukia, & Tikkanen, 2011; Liu & Hsu 2011; Park, Lee, & Hong 2011; Petrakis, Valsamis & Kafka, 2018; Smolarski & Kut 2011) As far as value creation is concerned, Schumpeter (1934) indicates that innovation plays an important role in order to stimulate this variable. And as indicated above, the entrepreneur will introduce those innovations that allow him to improve his activity and obtain greater benefits. So, entrepreneurship is the main factor to promote economic growth and innovation is the instrument used to achieve the entrepreneurial objectives, being necessary to have an adequate social environment that allows it to develop its activity. Thanks to the innovation introduced a higher value creation is obtained having a positive effect on growth along with entrepreneurial activity. It is also necessary to consider the feedback effects generated by this process. Greater economic growth will not only improve the social environment, but will also provide more business opportunities for entrepreneurs so they will be willing to increase their activity and introduce innovations, which will increase the value creation, thus generating a beneficial circular effect on the economy.

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Empirical Analysis To test the relationships showed in previous section, this study uses a latent variables model with data from 23 European countries (Austria, Belgium, Bulgaria, Croatia, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Luxembourg, Norway, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, United Kingdom) for the period 2014-2016. In this analysis two types of estimations are considered. First, the relationship between entrepreneurship, value creation and economic growth is analyzed, including those factors that influence on entrepreneurship (social environment) and on value creation (innovation), taking into account that entrepreneurship influences on innovation. In this case, a positive relationship among all these variables is expected. The second behavior would include the feedback effects that occur in the economy. To this end, the growth effects on social environment and on entrepreneurship are considered, as well as the innovation effect on value creation. It is also expected a positive effect among all the variables considered. In order to carry out the empirical analysis a PLS (Partial least squares path modelling) estimation is developed using the PLS method with the SmartPLS 3.2.4 program. This estimation allows o establish a correlation between different latent variables due to the combination of the characteristics of principal component and multiple regressions. So, PLS regression is used when there are several explanatory variables or a proxy to an economic occurrence that is not observed directly, taking into account problems of collinearity; the latent variables synthesize and replace this information (Tenenhaus, 1998). This method consists of several composites that are hypothesized to be causally related to form a structural model. Each construct is measured with one or more variables and the model consists in carry out regressions paths among the composites (Rönkkö & Yitalo, 2010). Table 1 shows the different constructs and variables considered in the empirical analysis. Regarding to chosen indicators definitions for the latent variable named “entrepreneurship”, Total Entrepreneurial Activity Driven by Opportunity includes persons involved in TEA (Total Early-Stage Entrepreneurial Activity) who claim to be driven by opportunity as opposed to finding no other option for work; and who indicate the main driver for being involved in this opportunity is being independent or increasing their income, rather than just maintaining their income (Bosma, Litovsky, Coduras, & Seaman, 2017).

Table 1. Constructs and indicators Constructs

Indicators

Social Environment

• Corruption Perception Index (Transparency International) (CPI) • Index of Economic Freedom (The Heritage Foundation) (EcoFree)

Value Creation

• Apparent Labour Productivity (Eurostat) (ALP) • Gross Value per employ (Eurostat) (GVE) • Turnover per person employed (Eurostat) (TPP)

Innovation

• Motivational Index (GEM) (MOT)

Entrepreurship

• Total entrepreneurial activity driven by opportunity (GEM) (TEAoppo). • Entrepreneurial employee activity (GEM) (EEA). • (IMPOPP)

Economic Growth

• GDP per capita, PPP (World Bank-database) (GDPc) • General Government expenditure (% GDP) (World Bank-database) (GGFCE)

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On the other hand, Entrepreneurial Employee Activity (EEA) indicator is calculated by the Global Entrepreneurship Monitor (GEM) and it is the rate of involvement of employees in entrepreneurial activities, such as developing or launching new goods or services, or setting up a new business unit, a new establishment or subsidiary. GEM (Global Entrepreneurship Monitor, 2017) defines EEA as employees developing new activities for their main employer, such as developing or launching new goods or services, or setting up a new business unit, a new establishment or subsidiary. In particular, the report focuses on entrepreneurial employees who have a leading role in the creation and development of these new activities (Bosma, Wennekers, Guerrero, Amoros, Martiarena, & Singer, 2013). Finally, the Motivational Index included in the latent variable innovation is the ratio between improvement-driven opportunity TEA and necessity-driven TEA. It shows the level of optimism and long-term expectations of entrepreneurs. If they have positive expectations, they will be more motivated to introduce innovations to improve their activity.

Relationship Between Entrepreneurship, Value Creation, Innovation and Economic Growth Results The first group of analysis corresponds to the relationship between entrepreneurship, value creation, innovation and economic growth. The results of the estimation are shown in Figure 1. The value of the circles is R2 showing the goodness of fit for each t regression. The results show that the expected results are obtained since it is verified how social climate positively affects entrepreneurship, and how this latter positively affects economic growth. From the internal consistency of each variable point of view, measured by Cronbach’s alpha and composite reliability values, such consistence is reached, due to the variables get a Cronbach alpha higher than 0,70. The range of Cronbach’s alpha values are conventionally used to interpret the consistency of scales: 0.80 represents a good scale, 0.70 an acceptable one, and 0.60 a scale that is suitable for exploratory research (Barclay, Higgins, & Thompson, 1995; Nunnally & Berstein, 1994; Wong, 2013). In our case, the latent variables show levels higher than 0,7: Economic growth 0,71; Entrepreneurship 0,77, Social environment 0,84, Value creation 0,99 and innovation 0,84. Convergent validity is assessed by the Average Variance Extracted (AVE), with a minimum value of 0.50 being considered acceptable (Chin, 1998; Fornell & Larcker, 1981), which means that the factors must explain more than half the variance of their respective indicators. A value below 0.50 means that the error variance is greater than the explained variance. In our model, all the constructs have an AVE of more than 0.50.: Economic growth 0,57; Entrepreneurship 0,68, Social environment 0,86, Value creation 0,98 and innovation 1,00.

Feedback Effects The second type of analysis includes the feedback effects, for the total number of countries (Figure 2). As in the previous case, the signs obtained are the expected ones, in such a way the economic growth would have a positive effect on the socioeconomic variables, among them, distribution of the income and also on the Entrepreneurship. The Cronbach and AVE values are also adequate: Social environment 0,844 and 0,854; Economic Growth, 0,750 and 0,577; entrepreneurship 0,768 and 0,684 and Value creation 0,988 and 0,978.

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Figure 1. Model estimated

Considering the empirical results, entrepreneurial activity plays an important role to promote growth. In order to enhance such activity there are different policies that can encourage or hinder it. In this sense, different aspects or possibilities have been considered by the literature specialized, such as different types of policies (Gnyawali & Fogel, 1994; McMullen, Bagby, & Palich, 2008), or the impact of policy and regulation on entrepreneurship (Campbell & Mitchell, 2012). On the other hand, Kreft & Sobel (2005) propose to design policies reduce taxes and regulations in which private property rights are insured. From their point of view these policies are necessaries to encourage entrepreneurial activity to produce

Figure 2. Feedback effects

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economic growth. Stevenson & Lundström (2007) consider that policies designed to create conditions to promote entrepreneurship must stress on the culture of promoting entrepreneurship, the opportunity to acquire business skills, experience, and knowledge and of facilitate the availability of financial and nonfinancial resources, and decreasing obstacles to implementation. In general terms, the design of policies should create the adequate environment to encourage individuals to create or develop and entrepreneurial activity, either by promoting business opportunities generation, or by guaranteeing the property rights of such activity. The creation of an adequate social environment or social climate is important since it is not only an incentive for entrepreneurships but also to generate adequate expectations to develop their activity. Schumpeter (1934) attached great importance to the social environment in order to stimulate entrepreneurial activity. From his point of view there are some legal or political impediments, as well as culture, rule of law and institutional aspects that would have some influence on such activity, and would create the reaction of the social group to entrepreneurial activity including the innovation process The problem is that Schumpeter does not specify the variables that influence this social environment. It indicates that in the beginnings of capitalism, entrepreneurs often encounter some social opposition to the innovation process; they would be in difficulty in finding the social cooperation for the introduction of innovations. In general terms, the level of democracy and income distribution could be included in the social environment variable. Better income distribution (lower inequality) would reduce social stress and opposition to innovation. Accepting this possibility it would be convenient to design redistributive fiscal policies (Galindo, Méndez & Alfaro, 2010). It would be also necessary to improve the role of institutions in order to stimulate the behaviour of individuals and to support and to enhance the social entrepreneurship activity (North, 1990, Scott, 1995, Hall & Sobel, 2008, Estrin, Mickiewicz & Stephan, 2013; Stephan, Uhlaner &Stride, 2014, Bosma, Content, Sanders & Stam, 2018, Boudreaux, Nikolaev & Klein, 2019) On the order hand, in order to stimulate other variables that could have any influence on social environment, it would be desirable to design policies to facilitate access to finances and to promote higher education and the culture of entrepreneurship and innovation would have a positive effect in order to create new business opportunities (Herbig & Dunphy, 1998, De Clercq & Arenius, 2006; Gavron, Cowling, Holtham, & Westall, 1998; Reynolds, Hay, & Camp, 1999). On the other hand, a reduction of the taxes rate, would also promote economic activity due to the increased consumption resulting from greater available income. The bureaucracy is other aspect to be considered. In this sense, the European Commission (2012) sates that the administrative burden represents one of the fundamental obstacles to business creation: almost three quarters of entrepreneurs in Europe consider as too difficult the creation of their own company, principally because of administrative complexity. Therefore, excessive bureaucracy would have a negative effect in order to promote entrepreneurship activity (Begley, Tan, & Schoch, 2005; Grilo & Thurik, 2005; Hart, 2003; Stephen, Urbano, & van Hemmen, 2009). Finally, it is also important to consider the positive effects on such activity of an adequate rule of law and proper governance (Méndez-Picazo, Galindo-Martín, & Ribeiro-Soriano, 2012).

CONCLUSION The paper has analyzed the relationship between entrepreneurship, value creation and innovation and their effects on economic growth, considering theoretical and empirical aspects.

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The economic crisis produced at the end of the last decade has led to the search for factors that favor economic growth and thus are able to face to a higher unemployment and lower economic well-being that countries have experienced since then. Together with the traditional factors that have been considered to improve the economic growth, entrepreneurship has been given special importance. The main reason is that entrepreneurs show an adequate capacity to generate products, and more specifically, to use productive resources in order to introduce innovations. Thanks to this activity, greater employment is generated and indirectly greater social welfare. That is why policies have been designed to enhance entrepreneurial activity and look for the factors that would influence it, in order to positively affect economic growth in an indirect way. In this sense, and thanks to the improvement in the statistical information during the last decades about the measurement of entrepreneurial activity in some countries, some activities and variables related to entrepreneurship have been detected. In this sense, innovation is one of the variables that the empirical analyses have been given more importance. The main reason is that entrepreneurship introduces new technological processes to obtain greater benefits and improve his market position. And thanks to this process can be considered that it is possible to enhance economic growth introducing new innovation processes in the firms. Finally, value creation, that is, that increase the value of the company’s goods and services must also be considered. It is a variable that has been given less attention, and there are works that show a positive relationship between value creation and entrepreneurship. The chapter has analyzed the relationship between entrepreneurship, value creation and innovation and their effects on economic growth, considering theoretical and empirical aspects. The feedback effects are also considered. This kind of analysis is not usually carried out. From a theoretical point of view, the positive relationship between entrepreneurship, value creation and growth have been showed, which would lead to a greater welfare. On the other hand, from the empirical point of view, an estimate has been made for the case of 23 European countries considered the relationship between the three variables as well as the feedback effects. The results show the positive relationships showed in the theoretical point of view. The empirical analysis shows the expected results, the positive relationship among entrepreneurship, value creation, innovation and economic growth. And it is also important to note that the social environment positively influences entrepreneurship. This means that it is important to improve this environment to enhance entrepreneurship, which in turn will act positively on innovations. We must also highlight the positive relationship between value creation and innovations. That is why we have two types of economic policies aimed at promoting entrepreneurship. First, those policies that directly influence on entrepreneurship activity, such as fiscal or monetary policies. From the fiscal policy perspective, measures such as tax reductions (Kreft & Sobel, 2005), subsidies for entrepreneurial activities and bureaucracy reduction would have a positive effect. From a monetary policy perspective, low interest rates and more easily credit access would also have a positive effect. Second, those policies that have indirectly influence on entrepreneurship activity. In this case, we must consider the measures that would improve the social environment, since they would positively affect entrepreneurship. In this sense, actions aimed at improving the social climate and business culture would have a positive effect and, in particular, those that involved a better income distribution. Considering the empirical analysis carried out, the actions would have to be directed towards greater economic freedom, that is, to reduce the restrictions and some regulations that reduce the markets efficiency and difficult the entrepreneurial activity, bureaucracy, contracting legislation ... and also measures aimed at reducing corruption.

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Finally, we must also consider the feedback effects that have also been analyzed in the empirical study. It is found that economic growth is positively related to entrepreneurship, which indicates that growth provides more business opportunities in addition to generating positive future expectations regarding the evolution of the economy, encouraging entrepreneurship. Economic growth also positively affects the social environment, allowing a better distribution of income and reducing social stress. Finally, the empirical analysis also shows us the positive relationship between economic growth and value creation. The feedback effects indicate that the economic growth generated by the measures dedicated to stimulate Entrepreneurship, value creation and innovations, in turn presents a positive relationship with the three variables studied, thus giving rise to a virtuous circle, which will reduce the problems faced by the economies due to the crisis, specifically, higher unemployment and lower social welfare.

FUTURE RESEARCH DIRECTIONS The three factors analyzed in the chapter, value creation, innovation and Entrepreneurship, have been the object of attention by the speculated literature, but generally have not been analyzed together as has been done in this chapter. As it has been shown in the previous sections, there are important relationships among the three factors so that it is important to continue investigating the interactions among them, as well as incorporating other factors that could directly or indirectly influence them, for example, culture, changes in the credit conditions... On the other hand, it would also be important to consider the relationship between social entrepreneurs on value creation and innovation. Finally, this study could be improved including more countries in the sample and it would be interesting to divide it in two groups considering the growth level or the entrepreneurship activity level.

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Reynolds, P. D., Hay, M., & Camp, S. M. (1999). Global entrepreneurship monitor—1999 executive report. Kansas City, KS: Kauffman Center for Entrepreneurial Leadership. Rönkkö, M., & Ylitalo, J. (2010). Construct validity in partial least squares path modeling. ICIS 2010 Proceedings Paper 155. Retrieved from http://aisel.aisnet.org/icis2010_submissions/155 Roper, S. (2007). Entrepreneurship, innovation and economic growth. International Small Business Journal, 25(3), 337–338. doi:10.1177/02662426070250030604 Ryan, J. C., & Daly, T. M. (2019). Barriers to innovation and knowledge generation: The challenges of conducting business and social research in an emerging country context. Journal of Innovation & Knowledge, 4(1), 47–54. doi:10.1016/j.jik.2017.10.004 Sarkees, M., & Hulland, J. (2009). Innovation and efficiency: It is possible to have it all. Business Horizons, 52(1), 45–55. doi:10.1016/j.bushor.2008.08.002 Schumpeter, J. A. (1934). The theory of economic development. Cambridge, MA: Harvard University Press. Schumpeter, J. A. (1939). Business cycles: A theoretical and statistical analysis of the capitalist process. New York: McGraw-Hill. Schumpeter, J. A. (1942). Capitalism, socialism, and democracy. New York: Harper. Schumpeter, J. A. (1947). Theoretical problems of economic growth. The Journal of Economic History, 7(S1Supplement), 1–9. doi:10.1017/S0022050700065189 Scott, W. R. (1995). Institutions and Organizations. Atlanta, GA: Sage. Shaw, G., & Williams, A. M. (2009). Knowledge transfer and management in tourism organizations: An emerging research agenda. Tourism Management, 30(3), 325–335. doi:10.1016/j.tourman.2008.02.023 Smolarski, J., & Kut, C. (2011). The impact of venture capital financing method on SME performance and internationalization. The International Entrepreneurship and Management Journal, 7(1), 39–55. doi:10.100711365-009-0128-1 Spencer, A. S., Kirchhoff, B. A., & White, C. (2008). Entrepreneurship, innovation, and wealth distribution: The essence of creative destruction. International Small Business Journal, 26(1), 9–26. doi:10.1177/0266242607084657 Stephan, U., Uhlaner, L. M., & Stride, C. (2014). Institutions and social entrepreneurship: The role of institutional voids, institutional support, and institutional configurations. Journal of International Business Studies, 46(3), 308–331. doi:10.1057/jibs.2014.38 Stephen, F., Urbano, D., & van Hemmen, S. (2009). The responsiveness of entrepreneurs to working time regulations. Small Business Economics, 32(3), 259–276. doi:10.100711187-007-9096-4 Stevenson, L., & Lundström, A. (2007). Dressing the emperor: The fabric of entrepreneurship policy. In D. B. Audretsch, I. Grilo, & A. R. Thurik (Eds.), Handbook of research on entrepreneurship policy (pp. 94–130). Cheltenham, UK: Edward Elgar. doi:10.4337/9781847206794.00010 Tenenhaus, M. (1998). La régression PLS: Théorie et pratique. Paris, France: Editions.

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Thornton, P. H., Ribeiro-Soriano, D., & Urbano, D. (2011). Socio-cultural factors and entrepreneurial activity: An overview. International Small Business Journal, 29(2), 105–118. doi:10.1177/0266242610391930 Unger, J. M., Rauch, A., Frese, M., & Rosenbusch, N. (2011). Human capital and entrepreneurial success: A meta-analytical review. Journal of Business Venturing, 26(3), 341–358. doi:10.1016/j.jbusvent.2009.09.004 Van Praag, C. M., & Versloot, P. H. (2007). What is the value of entrepreneurship? A review of recent research. Small Business Economics, 29(4), 351–382. doi:10.100711187-007-9074-x Vivarelli, M., & Pianta, M. (Eds.). (2000). The employment impact of innovation: Evidence and policy. London, UK: Routledge. doi:10.4324/9780203458686 West, G. P. III, Bamford, C. E., & Marsden, J. W. (2008). Contrasting entrepreneurial economic development in emerging Latin American economies: Applications and extensions of resource-based theory. Entrepreneurship Theory and Practice, 32(1), 15–36. doi:10.1111/j.1540-6520.2007.00214.x Wong, K. K. (2013). Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin, 24(1), 1–32. Xiao, H., & Smith, S. L. J. (2007). The use of tourism knowledge. Research propositions. Annals of Tourism Research, 34(2), 310–331. doi:10.1016/j.annals.2006.09.001 Zahra, S. A., Jennings, D. F., & Kuratko, D. F. (1999). The antecedents and consequences of firmlevel entrepreneurship: The state of the field. Entrepreneurship Theory and Practice, 24(2), 45–65. doi:10.1177/104225879902400205 Zhao, F. (2005). Exploring the synergy between entrepreneurship and innovation. International Journal of Entrepreneurial Behaviour & Research, 11(1), 25–41. doi:10.1108/13552550510580825 Zortea-Johnston, E., Darroch, J., & Matear, S. (2012). Business orientations and innovation in small and medium sized enterprises. The International Entrepreneurship and Management Journal, 8(2), 145–165. doi:10.100711365-011-0170-7

KEY TERMS AND DEFINITIONS Distribution of Income: The way in which income is divided among the population of a country. Economic Growth: The increase in the production of goods and services in a country during a period of time. Entrepreneurial Activity: The life cycle of entrepreneurial ventures (nascent, new business, established business, discontinuation) and their impact (high growth, innovation, internationalization) (GEM, 2017). Entrepreneurial Employee Activity (EEA): indicator is calculated by the Global Entrepreneurship Monitor (GEM) and it is the rate of involvement of employees in entrepreneurial activities, such as developing or launching new goods or services, or setting up a new business unit, a new establishment or subsidiary. GEM (2017) defines EEA as employees developing new activities for their main employer, such as developing or launching new goods or services, or setting up a new business unit, a new establishment or subsidiary. 19

 Value Creation, Innovation, and Entrepreneurship

Entrepreneurship: A business venture launched by one or various individuals who identify market opportunities and are willing to assume economic risks so as to achieve profitability and consolidation over time. Human Capital: A productive resource which brings together the training, abilities and skills of individuals who take part in production processes and which are related to work productivity. It depends on factors such as education and experience. Institutions: The structures and mechanisms present in a society which regulate the conduct of individuals, promoting or discouraging certain behaviours. They may be formal (usually written, such as laws, norms, contracts) or informal (unwritten, such as customs, taboos, traditions). Rule of Law: Principle by which the citizens of a country are subject to the law, in such a way that the law has authority and influence in society. Social Entrepreneurship: A business venture which aims to provide goods or services which meet social needs using business tools to make the enterprise sustainable. Value Creation: That value is understood as actions dedicated to increasing the value of goods and services.

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Chapter 2

Creating Value Through Entrepreneurship Based on the Economic Cycle Fernando E. Callejas Albiñana University of Castilla-La Mancha, Spain Isabel Martínez Rodríguez University of Castilla-La Mancha, Spain

ABSTRACT This chapter examines in-depth the behavior of necessity- and opportunity-driven entrepreneurship. First, it considers their relevance to total entrepreneurial activity. The chapter determines which social and economic factors affect the two types of entrepreneurship, as well as their relative importance for a sample of 32 previously selected countries during a period of expansion (2001-2008) and of crisis and recovery (2009-2016). The analyzed factors include monetary and fiscal policy instruments (economic factors) and representative variables of governance and human capital (social ones). The findings show that both necessity- and opportunity-driven entrepreneurship largely explain the behavior of total entrepreneurial activity. They moreover show that the explanatory factors of both kinds of entrepreneurship differ depending on the business cycle phase considered. These findings will be key to proposing efficient economic policy measures to promote entrepreneurial activity and, thus, economic growth in economies around the world.

INTRODUCTION Entrepreneurship involves the set of activities related with identification, evaluation and exploitation of new business opportunities in the market (Peña et al., 2014, p.47). Entrepreneurs play a central role in the creation of economic and social value throughout the positive impact that their economic activity exerts on employment (Keynes, 1936; Halicioglu & Yolac, 2015), innovation (Schumpeter, 1911/1963;

DOI: 10.4018/978-1-7998-1169-5.ch002

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 Creating Value Through Entrepreneurship Based on the Economic Cycle

Acs & Audretsch, 2003; Galindo & Méndez, 2014), competitiveness (Thurik et al., 2008), economic growth (Urbano & Aparicio, 2016; Acs, et al.; 2017) and the social well-being (Ribeiro et al., 2007, Fritsch and Kublina, 2018). An entrepreneur can be innovative (Marshall, 1963/1890; Schumpeter, 1911/1963; Malerba y McKelvey, 2019), persevering, a leader (Say, 1803/1855; Weber, 1904/1955; Palazzeschi et al., 2018), risk and uncertainty tolerant (Knight, 1921/1947; Zahra, 2018) and have the quality of “alertness” to perceive new economic opportunities that no prior economic actor has yet recognized (Kirzner, 1973). Entrepreneurs not only venture for purely economic motivations, based on the pursuit of profit, but also for a psychological, personal, or social motivations as the desire for autonomy, independence, achievement, recognition, self-esteem, among others. All in all, every entrepreneurial initiative has some kind of motivation that drives it (De la Vega et al., 2008). All these components reflect the important role of entrepreneurs in the creation of both economic and social value. In recent years, there has been growing interest in the entrepreneurial phenomenon, not only by governments and other authorities since it was established as a key component of economic policy (Acs et al., 2017), but also by individuals who are increasingly attracted to the option of becoming entrepreneurs. The existing attraction for the figure of the entrepreneur and the consolidation as a meritorious employment option, has become evident in aspects such as the emergence of a large number of financial and fiscal assistance programmes aimed at this group; educational reforms to include entrepreneurial training programs; the standards, regulations and bureaucracy designed to simplify and facilitate the process of starting and developing a business, etc. The aim of the present study is two-fold. Firstly, it attempts to demonstrate that entrepreneurship is a crucial factor in the creation of value and that it should be used as a key component of economic policy in the achievement of that objective. Secondly, the behaviour of the entrepreneurial activity is analysed to identify what factors influence them and how these factors ‘effects differ across different countries and the stage of economic cycle, differentiating between growth (2001-2008) or crisis and the beginning of recovery (2009-2016). Besides the purely economic factors that have traditionally received considerable attention, the social and cultural factors are also considered in this study. It cannot be ignored that besides involving the economic activity itself, entrepreneurship constitutes an important social phenomenon. To achieve these objectives, econometric models are estimated with the panel data method. The world’s most entrepreneurial countries and the most representative economic and social factors of entrepreneurial activity, represented by monetary policy, fiscal policy, human capital and governance, have been selected. The Total Early-Stage Entrepreneurial Activity (TEA) index, an indicator defined by the Global Entrepreneurship Monitor project (GEM), has been used to measure total entrepreneurial activity. It measures the percentage of 18-64 population who are either a nascent entrepreneur or ownermanager of a new business. The research contributes both theoretically, advancing knowledge of the economic and socio-cultural factors that affect entrepreneurship, and practically, helping in the design of efficient policies to promote entrepreneurial activity across different countries and economic cycle stages. This is highly useful in a context in which entrepreneurial activity has become a key to promote long-term economic growth and value creation.

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 Creating Value Through Entrepreneurship Based on the Economic Cycle

BACKGROUND The study of entrepreneurs is not new. References to entrepreneurs can be found in Greek thought and in the scholastic economics of St. Bernardino of Siena (1431), who associated them with merchants. However, most authors agree that the first clear allusion to the figure of a businessman was made by Cantillon (Cantillon, 1755/1978), who used the term undertaker to refer to a person who ventures into business assuming a risk.

Theorical Framework and Hypothesis Development Today, entrepreneurship has become a priority objective of the governments of the world’s leading emerging and advanced economies, due to its positive impact on economic growth. The original factors, identified by Solow (1956) and Swan (1956), such as capital, labor, and productivity, together with more recent additions by Lucas (1988) and Romer (1986), have been joined by entrepreneurial activity (Carree & Thurik, 2003; Urbano & Aparicio, 2016), often with special emphasis on small entrepreneurs (Acs & Audretsch, 2003). Entrepreneurship owes its significant impact on economic growth to its promotion of job creation (Keynes, 1936; Thurik et al., 2008; Halicioglu & Yolac, 2015; Akinyemi et al., 2018), the technological change generated by the intensification of competition and increased productivity (Acs, 2006), and the innovative capacity of entrepreneurs (Audretsch et al., 2006; Galindo & Méndez, 2014).

Difference Between Necessity-Driven Entrepreneurship (NTEA) and Opportunity-Driven Entrepreneurship (OTEA) Since 2001, the Global Entrepreneurship Monitor (GEM) project has differentiated between two different types of entrepreneurial activity: entrepreneurship driven by “necessity” and entrepreneurship driven by “opportunity” (Reynolds et al., 2002; Fairlie & Fossen, 2017). Necessity-driven entrepreneurs are pushed to start businesses because they have no other job options and need a source of income (Peña et al., 2014, p.55). They largely arise as a result of purely economic motivations (Block & Sandner, 2009, p. 120; van der Zwan & Hessels, 2013) based on survival needs. Although their main motivation is to earn enough money for survival and sustenance (Carsrud & Brännback, 2011), they may also be motivated by occupational safety concerns (Tyszka et al., 2011, p.129) or their own professional or personal dissatisfaction, due to a lack of personal development and/or a need for recognition at work (Noorderhaven et al., 2004). Opportunity-driven entrepreneurs, on the other hand, choose to start or create a business based on the perception that there is a business opportunity that has not yet been taken advantage of (or has been taken advantage of only incompletely) by existing companies (Peña et al., 2014, p. 55). They are generally driven by both economic motivations, associated with the desire to increase their income (Carter et al., 2003; Cassar, 2007) and gain power, prestige, and/or status (Carsrud & Brännback, 2011), and non-economic ones (Block & Sandner, 2009; van der Zwan & Hessels, 2013), such as the need for independence and achievement (Amorós & Guerra, 2008, p. 8; Tyszka et al., 2011, p. 129) or the aspiration to create their own business, be their own boss, and develop new products (Carter et al., 2003; Cassar, 2007). This distinction is necessary because not all entrepreneurial initiatives contribute to economic growth in the same way, and the motivations to start the business can be very different. In this sense, and as Angulo-Guerrero et al (2017, p. 35), claim “the aim of governments should not only be to in-crease 23

 Creating Value Through Entrepreneurship Based on the Economic Cycle

entrepreneurship indiscriminately, but to also take into account the types of entrepreneurship”. Generally, opportunity-driven entrepreneurs have a greater positive impact on economic growth (Urbano & Aparicio, 2016), since they are comparable to larger companies with higher business volumes (Hechavarria & Reynolds, 2009; Block & Wagner, 2010) and higher growth expectations than necessity-driven entrepreneurs (Poschke, 2013). The latter are more likely to be located in lower-income regions with limited access to human capital, financial capital, technology, and other resources, which inhibits their potential to generate innovation and employment (Hessels et al., 2008, p. 327; Angulo-Guerrero et al., 2017; Roche & Conti, 2018). While many other secondary motivations can also influence the decision to become an entrepreneur (see De la Vega, 2008), as can mixed motivations (combinations of opportunity and need or having a job but looking for better opportunities) and other motivations, necessity-driven and opportunity-driven entrepreneurship are the two main kinds. Consequently, they explain total entrepreneurial activity to a greater extent. Hence, the following hypothesis is proposed: Hypothesis One (H1): Necessity- and opportunity-driven entrepreneurship explain total entrepreneurial activity.

Economic and Social Factors Affecting Entrepreneurship Economic and Financial Factors: Monetary Policy and Fiscal Policy Monetary policy has a significant influence on economic activity (e.g., Ciccarelli et al., 2015; Gertler & Karadi, 2015) and on the evolution of the real economy in the short term (Bernanke & Blinder, 1992; Stein, 2012). It plays a decisive role in entrepreneurship since the financial constraints that entrepreneurs face are one of the main obstacles to the creation of companies. That is why the application of expansive monetary policies focused on facilitating access to financing, is key to facilitating and encouraging the creation of companies (Gnyawali & Fogel, 1994; Ma et al., 2018). The recent financial crisis, which began in 2007, has led to very sharp declines in the generation of available loans (Ivashina & Scharfstein, 2009; Schnabl, 2012). This may negatively affect entrepreneurship, either through rationing of the loans granted (Stiglitz & Weiss, 1981), or because of the negative effects generated for aggregate demand or aggregate supply (Bernanke & Blinder, 1988). It must be recalled that a monetary restriction could be more worrisome for necessity-driven entrepreneurs, who tend to be linked to small companies, with low income levels (Block & Wagner, 2010) and lower growth expectations (Poschke, 2013) because they have less access to alternative sources of financing to bank credit (Ma et al., 2018). Aware of the difficulties they face to access credit, necessitydriven entrepreneurs are likely to choose to prioritize alternative sources of financing, such as informal money from family and friends or public subsidies since, coming from unemployment, they are often ideal candidates to receive grants to start a business (Fryges et al., 2011, p. 15). At the same time, fiscal policy is a key tool for entrepreneurial activity, since government aid and tax burdens are two decisive factors in the economic activity of entrepreneurs, determining a country’s entrepreneurial rate (Djankov et al., 2010; Harju & Kosonen, 2012). In keeping with a Keynesian approach (1936), it can be argued that government intervention in the form of the implementation of an expansive fiscal policy will stimulate aggregate demand and business activity (Arnold et al., 2011; Cumming & Li, 2013).

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 Creating Value Through Entrepreneurship Based on the Economic Cycle

The positive effects of an expansive fiscal policy will be greater if public spending is productive and manages to boost the productivity of production factors, such as public spending on education, which improves the quality of human capital (Aschauer, 2000). Likewise, tax incentives are a key factor in entrepreneurs’ business decisions, as tax increases reduce entrepreneurship and companies’ survival rate (Gentry & Glenn, 2000; Harju & Kosonen, 2012). Tax rates affect the willingness to take risks and, thus, entrepreneurial initiative (Arnold et al., 2011). Socioeconomics Factors: Human Capital and Governance Governance is defined as the way in which power is exercised in the management of a country’s economic and social resources for the purposes of development (World Bank, 1992). It is decisive in the entrepreneurial process. The creation of new companies requires certain political, social, and economic conditions (Van de Ven, 1993), and government and its actions play a fundamental role therein1. More specifically, it has been shown that the dimensions of governance may particularly affect opportunity and necessity entrepreneurship (Fuentelsaz et al., 2015; Angulo-Guerrero et al., 2017). For instance, market economy-oriented institutions and policies that provide an appropriate legal and regulatory framework may facilitate predictable and rationaldecision-making and favor the recognition and exploitation of entrepreneurial opportunities (Powell &Weber, 2013). The concept of human capital mostly dates back to the 1960s and the works of Schultz (1961) and Becker (1964), although the term itself is attributed to Pigou (1928). According to Becker (1964), human capital can be defined as the skills and knowledge that individuals acquire through investments in education, on-the-job training, and other types of experience. Many authors have found a positive effect of high levels of human capital on entrepreneurship (e.g., De Clercq & Arenius, 2006; Haber & Reichel, 2007). Higher levels of education increase the agility of the individual (Westhead et al., 2005) to create (Ucbasaran et al., 2008, p. 157) or identify and discover business opportunities (Shane, 2000; Sánchez, 2011), evaluate them (Detienne & Chandler, 2004), and exploit them (Shane & Venkatraman, 2000). They also provide people with greater self-confidence (Kim et al., 2006), enabling them to perceive the risk and costs assumed in relation to the exploitation of a business opportunity as being lower (Ucbasaran et al., 2008, p. 169). Entrepreneurs often perceive their own abilities as crucial to the success of their business (Cooper et al., 1988; Kahneman & Lovallo, 1994). It is thus also important for individuals to be able to recognize that they effectively possess the knowledge and skills necessary to be an entrepreneur2 (Peña et al., 2014). Although all these factors are determinant to entrepreneurship, it is not known whether they affect both necessity- and opportunity-driven entrepreneurship equally, as the motivations for each type are different. Furthermore, motivation can be conditioned by the business cycle phase (Fairlie & Fossen, 2017; Roche & Conti, 2018), so the explanatory variables that foster or hamper motivation and entrepreneurial action will also differ. In light of these considerations, the following hypotheses are proposed: Hypothesis Two (H2): The explanatory economic factors differ for necessity-driven and opportunitydriven entrepreneurship. Monetary policy is more efficient to promote opportunity-driven entrepreneurship and fiscal policy is more efficient to promote necessity-driven. Governance is more efficient to promote opportunity-driven entrepreneurship

25

 Creating Value Through Entrepreneurship Based on the Economic Cycle

Hypothesis Three (H3): During the expansion phase of the business cycle (2001-2008), monetary policy is not representative to promote necessity-driven or opportunity-driven entrepreneurship. During the crisis and recovery phase of the business cycle (2009-2016), the explanatory economic factors differ for necessity-driven (monetary policy) and opportunity-driven (fiscal policy) entrepreneurship.

CREATING VALUE THROUGH ENTREPRENEURSHIP BASED ON THE ECONOMIC CYCLE. APPROACH ANALYSIS With the aim of designing efficient policies that promote entrepreneurship and thus economic growth in different countries around the world depending on the business cycle, an empirical analysis has been done. Finally, all the hypotheses could be tested and, if possible, the countries more prone to entrepreneurship in each stage of the business cycle will be determined.

Sample and Data Collection The empirical work was carried out using the statistical method of panel data analysis. The information provided by the GEM database on total entrepreneurial activity (TEA) was taken as a reference, using 32 countries (sufficient statistical information) and time series from 2001 to 2016. The proposed models consider the three types of entrepreneurship (TEA, NTEA, OTEA) to be dependent variables; the rest are considered proxy variables of the socioeconomic factors: human capital and governance. For each type of entrepreneurship, two different periods were considered: 2001-2008 (expansion) and 2009-2016 (crisis and recovery). With a view to subsequently proposing econometric models, those countries for which there was sufficient data in the GEM were selected for each exploratory model of TEA and its NTEA and OTEA analysis components (Table 1). Likewise, the most representative countries were selected for each type of entrepreneurship in order to obtain valid conclusions for more national economies. This representativeness was determined by obtaining the average data for each country, for homogeneous periods of the business cycle (2001-2008 and 2009-2016). For each hypothesis, the group of countries of the sample will be different since the most representative of each type of entrepreneurship (NTEA, OTEA, TEA) and stage of the cycle (2001-2008 and 2009-2016) are selected. With this, we get that, for each case study (H1, H2 and H3), the selection of countries being the most representative. That is, the countries included in the interval average +/- standard deviation. In this way, the less representative countries, located outside this interval, are not considered. Second, the proxy variables for the economic factors (monetary policy and fiscal policy) and social factors (human capital and governance) (with sufficient data) were collected, as explained in the literature review above (Table 2).

Results Panel data regressions were run to test the hypotheses. The regression model results are shown in Tables 3, 4, and 5.

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 Creating Value Through Entrepreneurship Based on the Economic Cycle

Table 1. Countries considered for each of the exploratory models GEM

2001-2016

Australia, Austria, Belgium, Brazil, Canada, Chile, China, Czech Rep., Denmark, Finland, France, Germany, Greece, Hungary, Iceland, India, Ireland, Israel, Italy, Japan, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Slovak Rep., Slovenia, South Korea, Spain, Sweden, Switzerland, UK, USA

2001-2008

Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Israel, Italy, Japan, Netherlands, Norway, Portugal, Slovenia, Spain, Sweden, Switzerland, UK, USA

2009-2016

Australia, Austria, Belgium, Canada, Czech Rep., Finland, France, Germany, Greece, Hungary, India, Ireland, Israel, Italy, Japan, Mexico, Netherlands, Norway, Portugal, Slovenia, South Korea, Spain, Sweden, Switzerland, UK, USA

2001-2008

Denmark, Finland, Greece, Hungary, India, Israel, Italy, Japan, Mexico, Netherlands, Slovenia, Spain, Sweden, Switzerland, UK

2009-2016

Austria, Belgium, China, Czech Rep., Denmark, Finland, France, Germany, Greece, Hungary, India, Ireland, Israel, Japan, Mexico, Netherlands, Norway, Poland, Portugal, Slovenia, South Korea, Sweden, Switzerland, UK

2001-2008

Canada, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Israel, Italy, Mexico, Netherlands, Norway, Poland, Portugal, Slovenia, Spain, Switzerland, UK, USA

2009-2016

Australia, Austria, Belgium, Czech Rep., Denmark, Finland, France, Germany, Greece, Hungary, India, Ireland, Israel, Netherlands, Norway, Poland, Portugal, Slovenia, South Korea, Spain, Sweden, Switzerland, UK, USA

NTEA

OTEA

TEA

First, an exploratory econometric model of total entrepreneurial activity (TEA) was proposed. Models 1 and 2 were designed (Table 3) to consider the relative importance depending on the current business cycle phase (H1). The Hausman test was used to determine the most appropriate estimation method – fixed effects (FE) or random effects (RE) – in order to obtain the most robust parameters in each case. In the case of FE estimation, the individual effects offered interesting information about the countries that most resemble the behavior described by the model concerned. These models suggest that it is valid (P ≥ 0.99) to study and analyze TEA through the two main TEA components considered (NTEA and OTEA), both in expansion (β*NTEA/TEA=0.361, β*OTEA/TEA=0.656) and crisis and subsequent recovery (β*NTEA/TEA=0.393, β*OTEA/TEA=0.821) phases. Therefore, support was found for H1. Additionally, the study of individual effects shows that Model 1 (2001-2008), estimated with FE, is representative for 16 of the 24 countries included in the estimation (Table 4). Next, exploratory models of the behavior of NTEA (Table 5) and OTEA (Table 6) were proposed. As in the previous case, the effect of the business cycle phase – expansion (2001-2008) or crisis and beginning of recovery (2009-2016) – was analyzed. The NTEA exploratory model was estimated with FE in the expansion phase (Table 5. Model 3). Thus, the individual effects offer interesting additional information about the countries in which the estimate obtained was most representative for the period 2001-2008 (Table 7). The FE applied to estimate the OTEA exploratory models for the 2009-2016 period (Table 6. Model 6) made it possible to analyze the individual effects. It was thus also possible to determine the countries for which this was the most representative model during that period (Table 8). These models suggest that economic (β*TAX=-0.428, P≥0.95; β*TAX=0.440, P≥0.99; β*TAX=0.793, P≥0.99; β*TR=-0.488, P≥0.99) and social factors (β*CAP=0.583, P≤0.05; β*GOVINT=-0.338, P≤0.05; β*GOVINT=0.805, P≤0.05; β*REGQ=1.152, P≤0.05; β*TF=0.697, P≤0.05)exert a significant influence on the

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 Creating Value Through Entrepreneurship Based on the Economic Cycle

Table 2. Proxy variables (initial) for the socioeconomic factors affecting TEA Variable Entrepreneur GDP Monetary policy

Fiscal policy

Human capital

Governance

Emp

Concept

NTEA

Necessity-Driven Early-Stage Entrepreneur (% TEA)

OTEA

Opportunity-Driven Early-Stage Entrepreneur (% TEA)

TEA

Total Early-Stage Entrepreneurial Activity (%)

GDPPC

GDP per Capita (US$ current prices)

CRED

Internal credit to the private sector (% GDP)

Database GEM

World Bank

IR

Central bank interest rate (%)

FIN

Financing for entrepreneurs (including grants and subsidies)

PEM

Public expenditure (million euros)

PEG

Public expenditure (% GDP)

TAX

Tax burden (% of GDP)

Index of Economic Freedom (Heritage Foundation)3

PEET

Public Expenditure Education (% Total PE)

Datosmacro.com

PEEG

Public Expenditure Education (% GDP)

TERED

Tertiary Education

CAP

Perceived Capabilities

BASED

Basic Education

POSTED

Posterior Education

GOVINT

Government Integrity

BF

Business Freedom

LF

Labor Freedom

MF

Monetary Freedom

TF

Trade Freedom

IF

Investment Freedom

FF

Financial Freedom

RLAW

Rule of Law

REGQ

Regulation Quality

GOVEF

Government Effectiveness

PSAV

Political Stability and Absence of Violence

UNEMP

Unemployment, Total (%)

ACTP

Active Population

EMP

Employment

Datosmacro.com

UNESCO

GEM

The Index of Economic Freedom (Heritage Foundation)

World Bank (Worldwide Governance Indicator)

World Bank

behavior of entrepreneurs. They show that the explanatory factors NTEA and OTEA are different, and, also, that they vary depending on the business cycle phase. Thus, support was found for H2 and H3. The R2 of Model 3, Model 5 and Model 6 was small. This is because many other factors also influence the opportunity and necessity entrepreneur variables. The results obtained for the models are consistent with the literature. The results thus support a reliable and valid measurement instrument.

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 Creating Value Through Entrepreneurship Based on the Economic Cycle

Table 3. Exploratory explanatory models of TEA by NTEA and OTEA component Dependent variable: TEA

Model 1 (2001-2008)

Model 2 (2009-2016)

Independent variables (significant and uncorrelated)

NTEA (+) *** OTEA (+) ***

NTEA (+) *** OTEA (+) ***

Coefficients

NTEA: 1.193327 OTEA: 1.079397

NTEA: 1.056157 OTEA: 1.175731

Standardized coefficients (𝛃*)4

NTEA: 0.361273 OTEA: 0.655658

NTEA: 0.392887 OTEA: 0.82077

R2-adjusted

0.8979

0.8470

Estimation (Hausman Test)

FE

RE

N (groups)

66 (20 groups)

158 (24 groups)

(Note: *P>0.9; **P > 0.95; ***P > 0.99)

Table 4. Individual effects for the TEA exploratory model (2001-2008) Country

Individual Effect

Country

Representative Model

Individual Effect Representative Model

Spain

0.5717794

Italy

-0.5829853

United States of America

0.5205026

France

-0.6172714

Greece

0.4014072

Czech Republic

-1.396712

United Kingdom

0.3435784

Switzerland

0.0081241

Norway

0.0000528

Portugal

1.517445

Israel

-0.0503846

Mexico

1.203267

Netherlands

-0.2491726

Ireland

0.6952689

Finland

-0.2541364

Denmark

-0.2917907

Hungary

-0.293824

mean(M)

0.00294109

Canada

-0.3419353

Stand. Desv(SD)

0.664539112

Germany

-0.5617878

M+SD

0.667480202

Slovenia

-0.5626035

M-SD

-0.661598022

NO representative Model

Table 5. Explanatory exploratory models of TEA by NTEA component Dependent variable: NTEA

Model 3 (2001-2008)

Model 4 (2009-2016)

Independent variables (significant and uncorrelated)

TAX (-) ** CAP (+) ***

TAX (+) *** GOVINT (-) ***

Coefficients

TAX: -0.204512 CAP: 0.0317906

TAX: 0.306205 GOVINT: -0.014738

Standardized coefficients (𝛃*)

TAX: -0.42867 CAP: 0.58337

TAX: 0.4404 GOVINT: -0.3387

R2-adjusted

0.006

0.4397

Estimation (Hausman Test)

FE

RE

N (groups)

152 (23 groups)

150 (26 groups)

(Note: *P ≥0.9; **P ≥ 0.95; ***P ≥ 0.99)

29

 Creating Value Through Entrepreneurship Based on the Economic Cycle

Table 6. Explanatory exploratory models of TEA by OTEA component Dependent variable: OTEA

Model 5 (2001-2008)

Model 6 (2009-2016)

Independent variables (significant and uncorrelated)

TAX (+) *** GOVINT (+) **

IR (-) *** REGQ (-) *** TF (+) **

Coefficients

TAX: 0.107556 GOVINT: 0.060499

IR: -0.346143 REGQ:0.104731 TF: 0.152264

Standardized coefficients(𝛃*)

TAX: 0.793 GOVINT: 0.805

IR: -0.488 REGQ:1.152 TF: 0.679

R2-adjusted

0.049

0.041

Estimation (Hausman Test)

RE

FE

N (groups)

57 (19 groups)

143 (24 groups)

(Note: *P ≥0.9; **P ≥ 0.95; ***P ≥ 0.99)

Table 7. Individual effects for the NTEA exploratory model (2001-2008) Country

Individual Effect

Country

Representative Model

Individual Effect

Representative Model

Portugal

0.204221

Norway

-0.2199306

Ireland

0.199273

Czech Republic

-0.2464415

Belgium

0.1813598

Japan

-0.3665469

Hungary

0.1693212

Switzerland

-0.4329266

Canada

0.1578892

Slovenia

-0.4454242

Sweden

0.1456045

Italy

-0.7415408

India

0.13236

Netherlands

0.0762743

NO representative Model United States of America

0.6352744

United Kingdom

0.0386929

Korea (South)

0.5755618

Austria

0.0330844

Australia

0.3920521

Spain

-0.0011665

Switzerland

-0.4329266

Israel

-0.0314462

Slovenia

-0.4454242

Greece

-0.0400754

Italy

-0.7415408

Mexico

-0.0524376

mean(M)

3.84615E-09

Germany

-0.0936064

Stand. Desv(SD)

0.293961852

France

-0.1327632

M+SD

0.293961856

Finland

-0.1366626

M-SD

-0.293961848

30

 Creating Value Through Entrepreneurship Based on the Economic Cycle

Table 8. Individual effects for the OTEA exploratory model (2009-2016) Country

Individual Effect

Country

Representative Model

Individual Effect

Representative Model

Korea (South)

2.385812

Belgium

-2.410972

Hungary

0.5107059

Finland

-2.696171

Poland

0.1811969

Ireland

-2.899234

Greece

0.1174953

Germany

-3.129514

Portugal

-0.0374661

Denmark

-3.366085

Czech Republic

-0.4007677

Netherlands

-0.6947617

France

-0.7117671

India

9.147389

Slovenia

-0.781028

China

8.882409

Israel

-0.7858585

Mexico

6.212374

Norway

-0.9832955

Japan

-1.63423

Switzerland

-1.940321

mean(M)

3.84615E-09

Austria

-2.173176

Standard Desviation (SD)

0.293961852

Sweden

-2.351008

M+SD

0.293961856

United Kingdom

-2.355718

M-SD

-0.293961848

NO representative Model

POLICY IMPLICATIONS AND DISCUSSION The results of the analysis only offered support for H1; no support was found for the other hypotheses. According to the results of Model 1 and Model 2, the two main components of TEA are necessity and opportunity (De la Vega, 2008). Therefore, by studying the behavior of both, fully valid and significant conclusions can be reached regarding TEA without the need to study other forms of entrepreneurship. Additionally, the value of the standardized coefficients obtained in both periods makes it possible to conclude that OTEA explains TEA behavior to a greater extent than NTEA (β*OTEA/TEA=0.655 > β*NTEA/TEA=0.361; β*OTEA/TEA=0.820 > β*NTEA/TEA=0.392) and that it is even more relevant in the period 2009-2016 (β*OTEA/TEA=0.821 > β*OTEA/TEA=0.656). This finding is consistent with the GEM’s assertion that, although economies with a high GDP show lower levels of TEA, a greater proportion of this activity corresponds to opportunity-driven ventures (Xavier et al., 2013, p. 7). The interpretation of the standardized coefficients makes it possible to conclude which socioeconomic factors explain the behavior of NTEA and OTEA for each established period to the greatest extent. Fiscal policy, represented by the tax burden (TAX), explains the behavior of both types of entrepreneurship (NTEA and OTEA). However, with NTEA, it was decisive in both of the considered periods (2001-2008 and 2009-2016) (Table 5. Model 3 and Model 4), whereas, with OTEA, it was only decisive in the period 2001-2008 (Table 6. Model 5). With regard to the economic significance, the signs vary. TAX affected NTEA inversely in the expansion period (2001-2008) and directly in the crisis and recovery period (2009-2016) (Table 5. Model 3 and Model 4). In contrast, TAX and OTEA were positively related during the expansion period (2001-2008) (Table 6. Model 5). With regard to governance, as represented by

31

 Creating Value Through Entrepreneurship Based on the Economic Cycle

government integrity (GOVINT), it is a coincident variable for both types of entrepreneurship, although with a different sign and in different periods. In the case of NTEA, governance exerts a negative influence in times of crisis and at the start of recovery (2009-2016) (Table 5. Model 4); in contrast, it is directly related in the case of OTEA and occurs during the expansion period (2001-2008) (Table 6. Model 5). The proposed models are valid and representative for most of the countries analyzed. The effect of the explanatory factors on NTEA (Table 7) will be representative and significant for, at least, 16 countries in the total sample in an expansion period; in the case of OTEA, the estimate was more representative for 21 of the 24 countries included in the crisis period (Table 8). These findings have the following policy implications. First, in both of the periods considered, OTEA contributes more than NTEA to the generation of TEA (Table 3). Therefore, economic policies should encourage OTEA in order to promote the development of TEA, thereby generating economic growth. Second, the implementation of expansive fiscal policies with reductions of the tax burden (TAX) should be used to promote NTEA during periods of expansion (2001-2008). Necessity-driven entrepreneurs usually have less access to bank financing; they will thus prioritize alternative sources of financing, such as public subsidies (Fryges et al., 2011, p. 15). Therefore, fiscal policy is a key tool for this type of entrepreneurship. Additionally, one of the most important features of entrepreneurship is entrepreneurs’ recognition that they possess the knowledge and skills needed to start a business (CAP) (Peña et al., 2013). This is because it increases their self-confidence and likelihood of success (Cooper et al., 1988; Kahneman & Lovallo, 1994), which in turn reduces risk aversion, which is especially acute among necessity-driven entrepreneurs. Accordingly, the implementation of public policies focused on improving education could be a good measure to promote NTEA in periods of crisis (Table 5. Model 3). This finding is consistent with the opinion of political leaders who argue that entrepreneurship and higher-education policies should be considered in tandem (Millán et al., 2014). For the promotion of OTEA, the quality of governance should be improved, for example, by optimizing government integrity (GOVINT). Furthermore, the direct relationship between TAX and OTEA shows that a potential tax increase would not negatively affect that type of entrepreneurship, because such entrepreneurs have sufficient resources and access to new financing to assume greater tax obligations (Table 6. Model 5). Although these are different measures, governments should consider which type of entrepreneurship it would be most beneficial to incentivize and not only to increase entrepreneurship indiscriminately (Angulo-Guerrero et al., 2017). In expansion periods, in which business opportunities are more frequent and numerous, OTEA is more likely to be the most common. Third, the direct relationship between NTEA and TAX in the crisis phase and at the start of recovery periods (2009-2016) underscores the advisability of implementing expansive fiscal policies that do not create undue tax burdens for entrepreneurs who have no choice but to start a business due to the lack of alternative employment and low income. Additionally, governance has an indirect effect, meaning that the weaker GOVINT is, the higher the levels of necessity-driven entrepreneurship will be, undertaken by individuals whose employment and wealth levels are suffering, especially, those who were already at low-income levels to begin with (Table 5. Model 3). In contrast, if the aim is to encourage OTEA, then the implementation of expansive monetary policies, through reductions in interest rates (IR), would be the most efficient. This is corroborated by the fact that opportunity-driven entrepreneurs have easy access to financing dependent on interest rates, such as bank credit (Block & Wagner, 2010). It could also act by improving the quality of governance, in this case, 32

 Creating Value Through Entrepreneurship Based on the Economic Cycle

by optimizing regulation quality (REGQ) and/or trade freedom (TF). These results are consistent with the considerations of Clark et al. (2018) by finding that foreign market entry as a growth opportunity (Table 6. Model 6). As in the previous case, although these are different measures, the government should consider which type of entrepreneurship it should incentivize. In the case of a crisis and at the beginning of recovery periods, NTEA is more likely to be the most frequent type of entrepreneurship, since in this phase of the cycle, unemployment levels are higher and business opportunities are less frequent and numerous. Finally, the values of the standardized coefficients (Table 9) suggest that the most effective factors to influence to incentivize NTEA are CAP (expansion) and TAX (crisis and recovery). In contrast, the most effective factor to encourage OTEA is governance, both during growth (GOVINT) and crisis (REGQ, TF) phases. The present research contributes to the existing literature. It shows that necessity and opportunity are the most frequent forms of entrepreneurship and that economic and financial factors are not the only ones that influence entrepreneurial activity; social (Steyaert, 2007) and cultural factors of the environment also significantly influence entrepreneurs’ behavior (Gnyawali & Fogel, 1994, Thornton et al., 2011). Consequently, this research facilitates the development of a theory for implementation. Finally, by dividing the study into business cycle phases, the present research makes it possible to design more effective economic policy measures in each phase to encourage necessity- and opportunitydriven entrepreneurship and thus contribute to the growth of more developed economies. In view of current studies, there is a lack of empirical research on necessity- and opportunity-driven entrepreneurship that takes an integrative approach to deciding which type should be incentivized and how. The present research enriches the current literature and provides empirical evidence for decision making.

Table 9. Summary of results obtained: determinant factors and standardized coefficients

2009-2016

2001-2008

Fiscal policy NTEA

Monetary policy

TAX (-)

ˆ* β = 0.583 CAP/NTEA

* βˆTAX/NTEA = −0.428

OTEA

TAX (+)

NTEA

TAX (++)

Socioeconomic factors CAP (++)

GOVINT (++)

ˆ* β = 0.805 GOVINT/OTEA

GOVINT (-)

ˆ* β = −0.338 GOVINT/NTEA

REGQ (++) OTEA

IR (-)

ˆ* β = 1.152 REGQ/OTEA

TF (+)

ˆ* β = 0.679 TF/OTEA

33

 Creating Value Through Entrepreneurship Based on the Economic Cycle

CONCLUSION AND LIMITATIONS OF THE RESEARCH This paper has explored and examined the behavior of entrepreneurial activity in 32 national economies, considering two main types of entrepreneurship (necessity and opportunity). This distinction is necessary because not all entrepreneurial initiatives contribute to economic growth in the same way so the aim of governments should not only be to in-crease entrepreneurship indiscriminately, but to also consider the types of entrepreneurship to be more effective. To do this, it defined the factors that determine this behavior, as well as the relative importance of these factors in different phases of the business cycle. These empirical results find support for our theoretical arguments set out. First, the rate of total entrepreneurial activity (TEA) was shown to be sufficiently and very well represented by two of its components, i.e., necessity-driven and opportunity-driven entrepreneurship (NTEA and OTEA, respectively) (support for H1), with the latter being more relevant, especially in periods of recession and subsequent recovery (2009-2016). Second, the findings indicate that both types of entrepreneurship are affected not only by economic factors, but also social and cultural ones, specifically fiscal policy (TAX), monetary policy (IR), human capital (CAP), and governance (GOVINT, REGQ, TF). Furthermore, the impact exerted by these factors is different for each type of entrepreneurship and phase of the business cycle (support for H2 and H3). In light of the consistency between theory and practice, the analytical technique used here can be considered adequate. The empirical work had certain limitations. For instance, the data are not homogeneous due to the lack of statistical information for many of the years and countries considered in the selected databases, especially when the analysis is conducted for multiple countries as in the present case. When GEM presents the homogenized data without statistical gaps, the resulting conclusions will be more solvent and closer to reality. Notwithstanding its limitations, the present research opens avenues of future research. First, the empirical analysis aimed to provide an adequate and effective methodology for studying entrepreneurial activity, both in terms of the technique used, which is valid for all countries worldwide, and through the selection of the most representative countries for each type of entrepreneurship, so as to prevent distortions when working with countries with atypical behaviors (outside the range mean ± SD). Second, analyzing entrepreneurial behavior by levels divided into homogeneous periods makes it possible to use the results for decision-making by designing more effective economic policy measures to achieve the objective of promoting entrepreneurship and, with it, economic growth. TEA behavior could thus be further specified. At the same time, given the scant literature to date focused on the impact of socioeconomic factors on necessity- or opportunity-driven entrepreneurship (Hessels et al., 2008; Giacomin et al., 2011), future research could seek to overcome this limitation. As a final reflection, it would be interesting to perform causal econometric analyzes for each of the economies in isolation to determine, with a greater accuracy, which factors affect entrepreneurship, and even the relevance of each of them comparatively with other economies. When GEM presents all the homogenized information without statistical gaps, the resulting conclusions by countries will be more solvent and closer to reality, and even with the possibility of extending the study to more similar geographical areas. All of this constitutes the future research lines to continue contributing to the study of entrepreneurship as a relevant activity for economic growth and the value creation.

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 Creating Value Through Entrepreneurship Based on the Economic Cycle

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Reynolds, P. D., Bygrave, W. D., Autio, E., Cox, L., & Hay, M. (2002). Global entrepreneurship monitor: 2002 executive report. Kansas City, MO: Kauffman Center for Entrepreneurial Leadership. Ribeiro, D., Cuervo, A., & Roig, S. (2007). Introduction. In A. Cuervo, D. Ribeiro, & S. Roig (Eds.), Entrepreneurship: concepts, theory and perspective (pp. 1–20). Berlin, Germany: Springer. Roche, M. P., & Conti, A. (2018). Necessity never made a good bargain: external conditions, entrepreneurial motives, and startup outcomes. In DRUID18 Copenhagen Business School Conference, Copenhagen, Denmark (pp. 11-13). Romer, P. M. (1986). Increasing returns and long-run growth. Journal of Political Economy, 94(5), 1002–1037. doi:10.1086/261420 Sánchez, J. C. (2011). University training for entrepreneurial competencies: Its impact on intention of venture creation. The International Entrepreneurship and Management Journal, 7(2), 239–254. doi:10.100711365-010-0156-x Say, J. B. (1855). A treatise on political economy (C. R. Prinsep, Trad.) Philadelphia, PA: Lippincott, Grambo, & Co. (Original published in 1803). Schnabl, P. (2012). The international transmission of bank liquidity shocks: Evidence from an emerging market. The Journal of Finance, 67(3), 897–932. doi:10.1111/j.1540-6261.2012.01737.x Schultz, W. T. (1961). Investment in human capital. The American Economic Review, 51, 1–17. Schumpeter, J. A. (1963). La teoría del desenvolvimiento económico. México: Fondo de Cultura Económica (Original published in 1911). Shane, S. (2000). Prior knowledge and the discovery of entrepreneurial opportunities. Organization Science, 11(4), 448–469. doi:10.1287/orsc.11.4.448.14602 Shane, S., & Venkataraman, S. (2000). The promise of entrepreneurship as a field of research. Academy of Management Review, 25(1), 217–226. Solow, R. M. (1956). A contribution to the theory of economic growth. The Quarterly Journal of Economics, 70(1), 65–94. doi:10.2307/1884513 Stein, J. (2012). Monetary policy as financial-stability regulation. The Quarterly Journal of Economics, 127(1), 57–95. doi:10.1093/qje/qjr054 Steyaert, C. (2007). Entrepreneuring as a conceptual attractor? A review of process theories in 20 years of entrepreneurship studies. Entrepreneurship and Regional Development, 19(6), 453–477. doi:10.1080/08985620701671759 Stiglitz, J., & Weiss, A. (1981). Credit rationing in markets with imperfect information. The American Economic Review, 71(3), 393–410. Swan, T. W. (1956). Economic growth and capital accumulation. The Economic Record, 32(2), 334–361. doi:10.1111/j.1475-4932.1956.tb00434.x

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Thornton, P., Ribeiro-Soriano, D., & Urbano, D. (2011). Socio-cultural factors and entrepreneurial activity: An overview. International Small Business Journal, 29(2), 1–16. doi:10.1177/0266242610391930 Thurik, A. R., Carree, M. A., Van Stel, A. J., & Audretsch, D. B. (2008). Does self-employment reduce unemployment? Journal of Business Venturing, 23(6), 673–686. doi:10.1016/j.jbusvent.2008.01.007 Tyszkaa, T., Ciéslik, J., Domuratc, A., & Mackoa, A. (2011). Motivation, self-efficacy, and risk attitudes among entrepreneurs during transition to a market economy. Journal of Socio-Economics, 40(2), 124–131. doi:10.1016/j.socec.2011.01.011 Ucbasaran, D., Westhead, P., & Wright, M. (2008). Opportunity identification and pursuit: Does an entrepreneur’s human capital matter? Small Business Economics, 30(2), 153–173. doi:10.100711187006-9020-3 Urbano, D., & Aparicio, S. (2016). Entrepreneurship capital types and economic growth: international evidence. Technological Forecasting and Social Change, 102, 34–44. doi:10.1016/j.techfore.2015.02.018 Van De Ven, A. (1993). The development of an infrastructure for entrepreneurship. Journal of Business Venturing, 8(3), 211–230. doi:10.1016/0883-9026(93)90028-4 Van Der Zwan, P., & Hessels, J. (2013). Start-up motivation and (in) voluntary exit. EIM Business and Policy Research, Panteia/EIM Research Report (H201309). Weber, M. (1955). La ética protestante y el espíritu del capitalismo. Madrid, Spain: Editorial Revista de Derecho Privado. (Original published in 1904). Westhead, P., Ucbasaran, D., & Wright, M. (2005). Decisions, actions, and performance: Do novice, serial, and portfolio entrepreneurs differ? Journal of Small Business Management, 43(4), 393–417. doi:10.1111/j.1540-627X.2005.00144.x World Bank. (1992). Governance and development. Washington, D.C. Xavier, S. R., Kelley, D., Kew, J., Herrington, M., & Vorderwülbecke, A. (2013). GEM 2012 Global Report. Working Papers. Zahra, S. A. (2018). Entrepreneurial risk taking in family firms: the wellspring of the regenerative capability. Family Business Review, 31(2), 216–226. doi:10.1177/0894486518776871

ADDITIONAL READING Acs, J., & Szerb, L. (2007). Entrepreneurship, economic growth and public policy. Small Business Economics, 28(2–3), 109–122. doi:10.100711187-006-9012-3 Baliamoune-Lutz, M., & Garello, P. (2014). Tax Structure and Entrepreneurship. Small Business Economics, 42(1), 165–190. doi:10.100711187-013-9469-9 Baumol, W. J. (1968). Entrepreneurship and economic theory. The American Economic Review, 58, 64–71.

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Christiano, L. J., Eichenbaum, M., & Evans, C. (1996). The effects of monetary policy shocks: Evidence from the flow of funds. The Review of Economics and Statistics, 78(1), 16–34. doi:10.2307/2109845 Cullen, J. B., & Gordon, R. H. (2007). Taxes and entrepreneurial risk-taking: Theory and evidence for the U.S. Journal of Public Economics, 91(7–8), 1479–1505. doi:10.1016/j.jpubeco.2006.12.001 Darnihamedani, P., & Hessels, J. (2016). Human Capital as a Driver of Innovation Among NecessityBased Entrepreneurs. International Review of Entrepreneurship, 14(1), 1–23. Diochon, M., Menzies, T. V., & Gasse, Y. (2008). Exploring the nature and impact of gestation-specific human capital among nascent entrepreneurs. Journal of Developmental Entrepreneurship, 13(2), 151–165. doi:10.1142/S1084946708000909 Du, K., & O’Connor, A. (2018). Entrepreneurship and advancing national level economic efficiency. Small Business Economics, 50(1), 91–111. doi:10.100711187-017-9904-4 Martínez, I. (2015). Factores macroeconómicos y sociales que impulsan el emprendimiento. Análisis empírico por grandes áreas geográficas. Doctoral thesis. University of Castilla-La Mancha. Open access: RUIdeRA TESEO http://hdl.handle.net/10578/8967 Mcmullen, J. S. (2011). Delineating the domain of development entrepreneurship: A market-based approach to facilitating inclusive economic growth. Entrepreneurship Theory and Practice, 35(1), 185–193. doi:10.1111/j.1540-6520.2010.00428.x

ENDNOTES 1



2



3



A wide variety of indicators have been designed to define the characteristics of good governance. Given the difficulty of analyzing them all, this paper will focus on some of the most internationally recognized indicators that are also the most representative of entrepreneurship insofar as they provide valuable information about global entrepreneurship. The selected indicators are prepared and periodically collected by widely recognized projects and organizations in the field of economics and, in particular, the field of governance. Specifically, they are the Index of Economic Freedom (Heritage Foundation) and the Worldwide Governance Indicators (World Bank). We will use the indicator “perceived capacities” to measure this dimension. This indicator is defined by the GEM as the percentage of the population aged 18-64 who believe they have the skills and knowledge required to start a business. It is considered a determinant factor of entrepreneurial activity and to be directly related to an individual’s human capital. The Index of Economic Freedom (IEF) is an indicator developed by the Worldwide Governance Indicators (WGI) project (Kaufmann, et al., 2014) for the World Bank. It measures 12 quantitative and qualitative factors representative of economic freedom grouped into 4 categories: rule of law (property rights, government integrity, judicial effectiveness), government size (government spending, tax burden, fiscal health), regulatory efficiency (business freedom, labor freedom, monetary freedom), and open markets (trade freedom, investment freedom, financial freedom). For this study, the factors most representative of entrepreneurship were selected.

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4



42

The standardized coefficients obtained in the six models are not an output of Stata software. The standardized coefficients have been calculated directly from the unstandardized coefficients along * SD (x j ) with the standard deviations of the variables involved: ²j = ²j * SD (y)

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Chapter 3

Innovation, Value Creation, and Entrepreneurship by Opportunity: An Analysis of European Countries María-Soledad Castaño-Martínez University of Castilla-La Mancha, Spain

ABSTRACT Technological progress is one of the main generators of increases in the production economy, involving the introduction of new products which, in turn, allows companies that carry out innovative actions to survive in the market. According to Schumpeter, innovation is an important source of value creation, improving growth in companies and economy. Thus, entrepreneurs introducing innovations in the market to take advantage of new business opportunities increase value creation, understood as the actions implemented to increase the value of goods and services created by enterprises. Likewise, the exploitation of these new opportunities that arises thanks to technological change are also largely conditioned by entrepreneurs’ human capital, availability of financial resources, investment in research and development activities, expectations, and efficient business regulations.

INTRODUCTION Innovation has been considered beneficial for society because it improves growth potential, solves problems and meets needs in society, and enhances consumer satisfaction as it increases the supply of products and services (Comin, 2017). Innovation is the key driver of material well-being, a variable which has been included in diverse ways in economic growth models to explain differences in growth rates across countries. Solow (1956) showed that different levels of technology can generate significant differences in income per head between countries. Subsequently, Romer (1986, 1990) stated that technological progress is not simply the result of external (exogenous) advances in technology as advocated in the Solow DOI: 10.4018/978-1-7998-1169-5.ch003

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 Innovation, Value Creation, and Entrepreneurship by Opportunity

Growth Model, but is created by specific market activities, since the introduction and development of novel ideas gives rise to profitable technologies. Romer (1990) analysed the production of technology and the conditions for this to occur in markets, using not only capital and output as explanatory factors but also the role of financial institutions and economic policy. As well as factors of economic growth, models have also incorporated the role played by entrepreneurs in generating economic expansion. Baumol considers the role of the innovative entrepreneur working adamantly with his company to transform inventions into economically viable products through the constant discovery and application of new and more efficient ways of doing things and introducing new and better products, thus generating positive effects on economic growth (Baumol, 1993). Therefore, entrepreneurship is very closely related to innovation because it frequently involves the creation of something new or in a new way: new combinations, new productions methods, new ventures, new markets and new wealth (Brush et al. 2003). Thus, entrepreneurs exploit business opportunities, introducing in this process innovations that allow their economic activity to expand, facilitating in turn the entry into new markets and encouraging competitiveness. In short, they make full use of productive resources and generate wealth and employment (Aghion et al. 2009, Black and Strahan 2002, Chilton and Bloodgood 2010, Castaño, et al. 2016a). According to Klapper and Richmond (2011) and Djankov et al. (2002), start-up enterprises enhance general productivity and economic growth (Erken, et al. 2018). Aghion (2017) states that economic growth is generated by innovations arising from business investments. In the same line, a number of studies have shown that newly created companies contribute much more to job creation than more mature companies (Ayyagari et al. 2011; Haltiwanger et al. 2010; Acs, et al. 2016; Fotopoulos and Storey, 2019). In view of these positive effects of entrepreneurship on economic growth and employment, there is an increasing tendency among policy makers to incentivize entrepreneurial activity and consolidate that which already exists. The European Commission considers that small and medium-sized enterprises (SMEs) and entrepreneurship are essential to ensure economic growth, innovation, job creation and social integration in the European Union (EU). SMEs are the backbone of the European economy, accounting for 99% of companies in the EU. In the last five years, they have provided 85% of new jobs and two thirds of the total employment in the EU private sector (European Commission, 2013, 2019). Furthermore, in 2003, the EU expanded it operational concept of innovation, resulting in the third edition of the Oslo Manual in 2005. Since then, the EU has favoured a broader concept of innovation than the merely technological aspect, typically including four types of innovations: product, process, organisational and marketing. In addition, it is considered that creating value involves creating economic value and the agents for this creation are enterprises (OECD, 2005). According to the European Commission (2014), firms that prioritize innovation present the highest increases in turnover. Around 79% of European companies that have implemented at least one innovation since 2011 increased their turnover by more than 25% in 2014. The aim of this study is to analyse the relationships between entrepreneurship, innovation and value creation, focusing on specific factors that affect innovation and entrepreneurship, such as human capital, R&D investment, perception of opportunities, access to credit, and regulations and bureaucracy. The second section of this study presents a brief review of the literature on the relationships and factors affecting entrepreneurship and innovation, and their impact on value creation. In the third section, we conduct a partial least squares (PLS) estimation on the 24 countries belonging on the EU. In the final section, we present our conclusions.

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BACKGROUND Entrepreneurs play an essential role in the introduction of innovations in the market. Different studies have shown that entrepreneurs take advantage of business opportunities due to technological changes that create new processes, product, markets and new ways of organisation (Shane, 2001, Choi & Shepherd, 2004, Morris et al., 2010). The introduction of innovations in the market is one of the key factors in value creation, according to Schumpeter’s thesis (Schumpeter 1934, 1942).

Entrepreneurship, Innovation and Value Creation Entrepreneurs play a key role in introducing innovation and creating value. The literature in this regard has traditionally included the following (Amit and Zott, 2001): the theoretical views of the value chain framework (Porter, 1985), Schumpeter’s theory of creative destruction (Schumpeter, 1942), the resource-based view of the firm (Barney, 1991), strategic network theory (Dyer and Singh, 1998), and transaction costs economics (Williamson, 1975). It can be seen that there are multiple sources of value creation, which have been studied using different approaches. The aim of this chapter is not to analyse all these theories but to underline the Schumpterian idea which holds that, by introducing innovations in the market, entrepreneurs affect value creation, increasing the value of goods and services (Ferreira et al. 2017; Galindo-Martín et al. 2018). Schumpeter (1934), in his analysis of entrepreneurial behaviour, studied innovation, identifying several sources of innovation (hence, value creation) including the introduction of new goods or new production methods, the creation of new markets, the discovery of new supply sources, and the reorganisation of industries (Gartner, 1985, Amit and Zott, 2001, Choi and Shepherd, 2004; Galindo and Méndez 2014). The Schumpterian approach to innovation emphasises the importance of technology and takes account of new combinations of production factors that give rise to new products and production methods. These, in turn, lead to the transformation of markets and industries and economic growth. Innovation is a process that occurs within companies as a result of the benefits entrepreneurs can obtain by better attending to the demands of their customers or by differentiating themselves from their competitors (Williamson and Winter, 1993, Zortea-Johnston et al., 2012). Innovation and SMEs are closely linked for various reasons. First, developing a new idea is the key reason why entrepreneurs start a new business. Second, entrepreneurs or managers of small companies need a first-mover advantage to compete against their main rivals and ensure the enterprise survives. Third, SMEs are able to adjust to environmental changes more quickly than larger organisations due to their nimbleness in decision-making (Rosenbusch et al., 2011). Accordingly, we propose the following hypotheses: Hypothesis One: Entrepreneurial activity positively affects innovation and value creation. Hypothesis Two: Innovation positively impacts on value creation. Nonetheless, both entrepreneurial activity and innovation are influenced by multiple factors. This chapter focuses on the analysis of some of these factors. Specifically we address expectations of demand, perception of opportunities, human capital, R&D investment, access to credit, and regulations and bureaucracy. These factors have been chosen as they are they are currently the main focus of entrepreneurial policy in the EU (European Commission, 2013) 45

 Innovation, Value Creation, and Entrepreneurship by Opportunity

First, if we consider perception of opportunities, positive expectations help expand entrepreneurial activity, which can foster a virtuous circle characterised by innovation and business growth (Castaño et al. 2015). Moreover, if entrepreneurs perceive good business opportunities in their environment, this will incentivize other entrepreneurs to undertake business projects (De Cleyn & Braet, 2012; ZorteaJohnston, et al., 2012). Thus, it can be posited that: Hypothesis Three: Perception of opportunities incentivizes entrepreneurial activity. In addition, in countries with a higher level of income and favourable prospects of income growth, a virtuous circle is produced between entrepreneurial activity, innovation and increased demand, triggering a feedback effect between these variables (Drucker, 1998; Galindo-Martín et al. 2018). A number of other studies also report that increased demand and economic growth stimulate innovation (Jasinski, 2011; Castaño et al. 2016a). Hence, we suggest the following hypothesis. Hypothesis Four: Economic growth stimulates entrepreneurship and innovation. Second, it should be highlighted that one of the main problems for business incubation is the financial obstacles entrepreneurs face when developing their business ideas (van Auken, 1999). Undoubtedly, one of the first challenges confronting an entrepreneur when initiating a new business is obtaining the necessary financial resources. Taking into account that innovation involves risk and effort, obtaining such resources is one of the principal difficulties faced by entrepreneurs (Nixson and Cook, 2005; OECD, 2015). Even experienced entrepreneurs may have problems in accessing funding, which can hamper growth, expansion or the consolidation of businesses already created (Cooper et al., 1994). Several studies have shown that policies that aim to facilitate access to bank credit by means of reducing capital requirements, the creation of investment companies, provision of low-interest loans, credit guarantee schemes, among others, contribute to business creation (Gnyawali and Fogel 1994; van Gelderenet al. 2006; Gertler and Karadi, 2015). Furthermore, expansive monetary policies that increase the volume of credit available to companies has a positive impact on entrepreneurial activity and innovation (Black and Strahan, 2002; Lelarge, et al. 2010; Cole, & Sokolyk, 2018). Thus: Hypothesis Five: A greater volume of credit fosters entrepreneurial activity and innovation. In addition, various approaches differentiate between the inputs and outputs of innovation. According to Cohen and Levin (1989), there are studies focused on R&D inputs such as companies’ R&D expenses, staff working on R&D activities (Silva, 2007, Raymond y St-Pierre, 2010), public R&D expenditure (Klette et al., 2000; Castaño-Martínez, 2012, Castaño et al, 2016b; Booltink and Saka-Helmhout, 2018). and other studies that address outputs in innovation, especially, patents (Griliches,1998, Jaffe et al. 1993, Jaffe and Trajtenberg, 2002; Barney, 2010; Poschke, 2018). Human capital and knowledge also play a key role in innovation, since, as well as investment in R&D, highly qualified professionals with appropriate technological knowledge and attitudes towards cooperation and innovative capacity are required for innovation to occur (Zahra and Nielsen 2002, Dissou, et al. 2016; Castaño-Martínez et al. 2015; Zahra, 2015; Byrne, et al. 2016; Impullitti and Licandro, 2017; Malerba and McKelvey, 2019). Accordingly, the following hypotheses are proposed:

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Hypothesis Six: Higher R&D expenditure is positively correlated to positive outcomes of innovation. Hypothesis Seven: Highly qualified human capital and R&D investment have a positive impact on innovation. A high education level in entrepreneurs also provides the knowledge and tools required to start a business and helps them identify business opportunities (George, el. al. 2016; Hörisch, et al. 2017). Hypothesis Eight: Entrepreneurs’ human capital stimulates opportunity entrepreneurship and has a positive indirect impact on innovation. Finally, we study the influence of regulations and bureaucracy on entrepreneurship and innovation and their indirect impact on value creation. Governments use regulations and bureaucracy to implement different public policies in order to achieve certain aims for society that would not be reached without the imposition of obligations, such as the correct functioning of markets, equal conditions for companies and financial institutions competing in the single market and the safeguarding of the interests of workers and consumers. Regulations and legal formalities can become a problem in the current socio-economic environment as they can hinder innovation or create obstacles that limit trade and investment, and, in short, hamper economic efficiency, leading to lower levels of value creation. In addition, regulations have collateral effects as a result of the accumulative impact of regulations enacted by a large number of governmental institutions that reduce entrepreneurial interest and encourage the dispersion of resources, which can, in turn, limit expansion to new markets, reducing innovation and job creation (Autio and Fu, 2015; Bosma et al., 2018; Chowdhury, et al., 2019). For many SMEs, the costs involved in complying with regulations represent a significant part of their general expenses and net margin, diminishing the internal resources available to finance investments. This is of vital long-term importance given that these costs reduce financial reserves and scales companies down, increasing their vulnerability in the face of economic difficulties, limiting opportunities for growth and the generation of employment. Specifically, various empirical studies have shown that the creation of new companies is significantly lower in countries with greater regulations of entry, since stricter regulation of entry is associated with less efficient market outcomes, which, in turn, reduces entrepreneurship (Klapper et. al 2006, Djankov et al., 2010; Jacob, and Michaely, 2017; Chambers & Munemo, 2019). Hypothesis Nine: Efficient business regulation affects positively entrepreneurial activity and innovation. In summary, Figure 1 shows the relationships among the variables and the hypotheses that are to be studied in the empirical analysis.

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Figure 1. Proposed model: The relationships among the variables and the hypotheses Source: Own elaboration

EMPIRICAL ESTIMATION FOR EUROPEAN COUNTRIES Data and Methods In order to analyse the theoretical relationships previously presented, an exploratory empirical analysis was performed using a PLS estimation. The estimation was conducted using the PLS method with the SmartPLS 3.2.4 program. The empirical analysis is carried out on a total sample of 24 countries: Austria, Belgium, Bulgaria, Croatia, Denmark, Estonia, Finland, France, Germany, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Norway, Poland, Portugal, Romania, Slovakia Slovenia, Spain and Sweden, using data for 2015-2016. As can be seen in Table 1, opportunity entrepreneurship was chosen as the indicator of entrepreneurial activity as entrepreneurs who take advantage of new business opportunities are those who most innovate and who have the best business outcomes (Wennekers et al., 2005). Following Venkataraman (1997), an essential element of entrepreneurship is the study of new opportunities. Casson (1982) and Shane and Venkataraman (2000) define entrepreneurial opportunities as situations in which new goods, services, raw materials, markets and organizing methods can be introduced through the formation of new means, ends, or means-ends relationships. These situations do not need to change the terms of economic exchange to be entrepreneurial opportunities, but only need to have the potential to alter the terms of economic exchange (Eckhardt and Shane, 2003). The GEM observatory measures the motivation behind each entrepreneurial activity, distinguishing three types of motivation: net exploitation of a business opportunity, known as “opportunity entrepreneurship”; the need to create one’s own employment in response to the lack of other job alternatives, which is referred to as “necessity entrepreneurship”; and other motivations and situations which fall somewhere between the other two, known as “improvement entrepreneurship”. Together with the previous indicators, another has recently begun to be measured, which is the “motivational index”. This index measures the relation between opportunity entrepreneurship and necessity entrepreneurship, where the higher the score on the index, the greater is the opportunity motivation (Kelley, et al. 2012, p.13).

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Table 1. Latent variables and indicator. Latent Variable

Indicators

Value Creation (VC)

• Apparent labour productivity (Gross value added per person employed) (VC1) (Eurostat, 2019c) • Labour productivity- Compensation per employee (VC2) (World bank, 2019) • Turnover per person employed (VC3) (Eurostat, 2019c)

Opportunity Entrepreneurship (OE)

• Motivational Index (MI) (GEM, 2019a) • Total Entrepreneurship Activity by opportunity (TEAopp) (Gem, 2019a)

Innovation (IN)

• Patent applications (IN1) (Eurostat, 2019b) • Trademark applications (IN2) (World bank, 2019)

Volume of Credit (VC)

• Domestic credit provided by financial sector (% of GDP) (CR1) (World bank, 2019a) • Domestic credit to private sector by banks (VC2) (World bank, 2019a)

Human Capital of the Entrepreneur (HCE)

• University Degree (UDEGREE) (GEM, 2019b)

Economic Growth (EG)

• Gross domestic product per capita at market prices (GDPpc) (Eurostat, 2019) • Human Development Index (HDI) (UNDP, 2019)

Human resources in science and technology (HRST)

• Persons with tertiary education employed in science and technology (HC1) (Eurostat, 2019b) • Persons with tertiary education (HC2) (Eurostat, 2019b)

Research & Development expenditure (RD)

• R&D expenditure by business enterprise sector (%GDP) (RDE) (Eurostat, 2019b) • R&D expenditure by government sector (RDSP) (Eurostat, 2019b) • R&D expenditure by higher education sector (RDU) (Eurostat, 2019b)

Perception of opportunities (PO)

• In the next six months, will there be good opportunities for starting a business in the area where you live? (PO) (GEM, 2019b)

Business Regulations (BR)

• Ease of doing business global score (DB) (World bank, 2019b) • Getting credit (GCR) (World bank, 2019b) • Protecting minority investors (PINV) (World bank, 2019b) • Paying taxes (PTX) (World bank, 2019b)

Taking into account that in Section 2 we defined value creation as the increase in the value of goods and services (Galindo-Martín, et al. 2018), to construct the latent variable, we used labour productivity and turnover per person employed. Finally, innovation was measured using the outcomes of innovation. In addition, in the indices of entrepreneurial activity and entrepreneurial motivation, the GEM observatory measures some of the socio-economic characteristics of entrepreneurs and certain factors in the environment which might condition their behaviour. Table 1 shows the indicators chosen from each survey to form the latent variable of “human capital of the entrepreneur” and “potential competition”. To measure the regulations of entry, we used a variable from the World Bank Doing Business database, which reports on the legal procedures entrepreneurs are required to complete in order to start their business activity (e.g. authorisations, licences, permits, etc.), which is based on the methodology proposed by Djankov et al. (2002). This methodology includes the procedures in which entrepreneurs have to interact with external entities: local and national governmental offices, lawyers, auditors, banks, notaries, etc. An increase of just one step in the series of procedures involved in starting a business is no trivial burden for entrepreneurs. Accordingly, to construct the “business regulations” latent variable, we used various indicators from the Doing Business database (World Bank, 2019b), as can be seen in Table 1. The “ease of doing business” indicator captures the gap between an economy’s performance and a measure of best practice across the entire sample of 41 indicators for 10 doing business factors. The score ranges from 0 to 100, where 0 represents the worst regulatory performance and 100 the best regulatory performance. The specific factor scores used are: starting a business, dealing with construction permits,

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getting electricity, registering property, getting credit, protecting minority investors, paying taxes, trading across borders, enforcing contracts, insolvency. As was seen in the second section, one of the most significant problems faced by entrepreneurs is the access to financial resources to fund their innovation and business activities. On many occasions, the problem arises from incorrect functioning of financial institutions or an inappropriate institutional framework for the protection of investors’ property rights, all of which complicate entrepreneurs’ access to financing. To measure the adequate functioning of institutions in this area, we chose the sub-indices of “getting credit” and “protecting minority investors”, where, in the same way as the previous indicator, the higher the score on the index, the better the institutions function. (World Bank, 2019c). One of the aims of entrepreneurial policy in the EU is to reduce the administrative burden on entrepreneurs, especially with regard to payment of taxes and social security. Hence, “paying taxes” was chosen as an indicator of the “business regulations” latent variable, where a higher score on the index indicates that administrative procedures for the payment of taxes have been simplified. This empirical analysis was conducted using Partial Least Squares (PLS) estimation. PLS is an alternative prediction technique to the ordinary least squares (OLS) regression, being especially useful when the number of predictor variables is higher than the number of cases. PLS combines the characteristics of principal component analysis and multiple regression. (Tenenhaus, 1998). Therefore, a structural modelling approach was chosen to estimate the parameters of the research model. Structural Equation Modelling (SEM) allow us to (i) model relationships between multiple independent and dependent constructs simultaneously in a single, systematic and comprehensive analysis; (ii) combine reflective and formative variables; (iii) model the measurement errors; and (iv) confront a priori theory and hypotheses with data (Barclay, Higgins and Thompson, 1995). Two approaches to structural modelling exist: covariance based, and partial-least-squares based (Hair et al., 2016). It was decided to use the second type, Partial Least Squares (PLS), to test the hypothesized relationship between latent variables because: (i) these second-generation multivariate techniques permit the introduction of latent variables with multiple indicators; (ii) they are more appropriate when sample size is small; (iii) models are complex and causal; (iv) they do not require multivariate normality; and (v) they produce consistent parameters estimates (Barclay, Higgins and Thompson, 1995; Chin et al, 2003). Two sub-models are used in this type of study: the measure sub-model and the structural sub-model. The first defines the relationship between observable variables (indicators) and latent variables. The second measures the relationships between latent variables, indicating which latent variable influences directly or indirectly other latent variables. For the measurement sub-model, we used the study’s factorial structure, which allowed us to decide which items are used as indicators of each latent variable (factor), as shown in Figure 1. For the structural sub-model, following the theoretical framework set out in the previous section, the confidence factor was regarded as exogenous, as liable to affect the other factors.

Results and Discussion Figure 2 show the results of the estimation, where the cross-loading in the reflective measurement models are also included. Cross-loading items represent prime candidates for removal from subsequent analysis, with the goal of improving model fit. Nevertheless, these indicators are well assigned to the latent variables in the estimated model, since that they represent the economic point being analysed.

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Figure 2. Model estimated on European Countries

Source: Own elaboration

In order to analyse the mean degrees of fit to the structural model, Nagelkerke R2 coefficients associated with latent variable regressions only in the endogenous constructs were used. R2 indicates the construct variance explained by the model and all endogenous latent variables with values greater than 0.1 mean that there is an acceptable fit to the model (Falk & Miller, 1992). The model analysed presents an acceptable fit in the case of the latent variables (see Table 2). Besides, R2ajusted can be used as the criterion to avoid bias toward complex model. This criterion is modified according to the number od exogenous constructs relative to the sample size. The R2ajusted value reduces the R2 value by the number of explaining constructs and the sample size and thus systematically compensates for adding nonsignificant exogenous constructs merely to increase the explained variance R2 (Sarstedt et al. 2013). The measurement model was evaluated by an item’s individual liability; internal consistency; and Discriminant Validity. The simple relationship between each item and its respective construct was measured by the Cronbach’s alpha value. In all cases this value is greater than 0.7, the standard criterion (Nunnally and Berstein, 1994; Barclay et al., 1995) Moreover, the Composite Reliability Index and the AVE (convergent validity or the common medium variance from all the constructs) are calculated as reliability and validity of the measurement model. It is standard to accept composite reliability indices greater than 0.85, and convergent validity (AVE) greater than 0.5 (Fornell and Larcker, 1981; Raykov and Marcoulides, 2017). All latent variables show an AVE greater than 0.5, and also, rho is greater than 0.7 to all latent variable (Henseler, 2010; Henseler, et al. 2016). Significance cannot be calculated conventionally using PLS and hence the bootstrapping technique must be used. According to Hair et al. (2016, p. 153) a significance level of 10% is commonly used for exploratory studies. This analyses the significance of the relationships between variables. Figure 1 shows that the relationships are significant (p-value * = p ≤10%; **= p ≤5%; ***= p ≤1%).

51

 Innovation, Value Creation, and Entrepreneurship by Opportunity

Table. 2. Reliability and validity of the measurement model. Cronbach’s Alpha

Composite Reliability

AVE

Rho_A

BR

0.748

0.777

0.518

0.948

CR

0.942

0.972

0.945

0.948

EG

0.721

0.875

0.778

0.762

R Square

R Square Adjusted

0.622

0.516

0.748

0.679

EOPP

0.723

0.878

0.782

0.729

HCE

1.000

1.000

1.000

1.000

HRST

0.993

0.996

0.993

0.994

INN

0.712

0.854

0.614

0.726

PC

1.000

1.000

1.000

1.000

RD

0.983

0.989

0.967

0.983

0.789

0.779

VC

0.901

0.938

0.835

0.909

0.401

0.344

Source: Own elaboration

Table.3. Indirect effects between latent variables Specific Indirect Effects BR -> EOPP -> INN

0.069

CR -> EOPP -> INN

0.058

EG -> EOPP -> INN

0.040

HCE -> EOPP -> INN

0.005

PC -> EOPP -> INN

0.122

HRST -> RD -> INN

0.372

BR -> EOPP -> VC

0.038

CR -> EOPP -> VC

0.032

EG -> EOPP -> VC

0.022

HCE -> EOPP -> VC

0.003

PC -> EOPP -> VC

0.067

BR -> INN -> VC

0.057

CR -> INN -> VC

0.066

EG -> INN -> VC

0.238

BR -> EOPP -> INN -> VC

0.036

CR -> EOPP -> INN -> VC

0.030

EG -> EOPP -> INN -> VC

0.021

HCE -> EOPP -> INN -> VC

0.002

EOPP -> INN -> VC

0.151

PC -> EOPP -> INN -> VC

0.063

RD -> INN -> VC

0.216

HRST -> RD -> INN -> VC

0.192

Source: Own elaboration

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 Innovation, Value Creation, and Entrepreneurship by Opportunity

PLS allows the indirect effects between latent variables to be calculated (Table 3), which can add to the direct effects shown in Figure 2. The results of the PLS estimation support the previously presented theoretical ideas. First, there is a significant, positive relationship between entrepreneurship and innovation, with a coefficient of 0.292 (see Figure 1). Furthermore, entrepreneurs positively impact on value creation (0.162) and innovation also has significant, positive effects on the same element (0.517). Thus, Hypotheses 1 and 2 are supported and the theories of Schumpeter (1934) and Rosenbusch et al. (2011) are confirmed. If we look at the factors affecting entrepreneurship and innovation, it can be observed that the existence of good business start-up opportunities simulates opportunity entrepreneurship (0.146), thus confirming Hypothesis 3. In addition, economic growth has significant, positive effects on entrepreneurship (0.138) and innovation (0.46). Hence, the thesis posited by Drucker (1998) can be accepted, namely that there exists a virtuous circle between entrepreneurial activity, innovation and increased demand (GalindoMartín et al. 2018). It can also be observed that economic growth has a very considerable positive effect on innovation (see Figure 1). Therefore, Hypothesis 4 can be accepted. Looking at the effects of the volume of credit on entrepreneurship and innovation, we find a positive correlation with both elements, although this correlation is only significant in the case of entrepreneurship with p ≤10%, being non-significant in the case of innovation. Turning to the analysis of the relationships between human capital, entrepreneurship and innovation, in both the theoretical and empirical parts of this study, human capital was incorporated in two different ways; on one hand, entrepreneurs’ human capital was included and, on the other, resources in science and technology. This leads us to find a positive relationship between entrepreneurs’ human capital and entrepreneurship, although this relationship is non-significant (see Figure 2). There also exist positive indirect effects between entrepreneurship training, innovation and value creation, albeit with low coefficients (see Table 3). However, if we consider the effects of human capital together with R&D expenditure, we find the relationships are positive and highly significant (see Figure 1), with it being possible to state that highly qualified human resources together with investment in R&D positively affect the outputs of innovation (Castaño-Martínez, 2012, Castaño, et al. 2015; Malerba and McKelvey, 2019). In addition, there is a highly significant, positive correlation between the inputs and outputs of innovation and, hence, Hypothesis 6 is confirmed (Zahra and Nielsen, 2002; Zahra, 2015). We can also observe considerable indirect effects between the following latent variables: HRST -> RD -> INN -> VC with a coefficient of 0.192 and RD -> INN -> VC with a coefficient of 0.216. Finally, we incorporated the role of the institutions in entrepreneurship and innovation, by means of efficient regulation of the areas that most affect entrepreneurial activity and innovation. It was found that efficient regulations that reduce legal procedures, facilitate the provision of credit and protect small investors have a significant, positive effect on entrepreneurship and innovation, thus supporting Hypothesis 9.

FUTURE RESEARCH DIRECTIONS This chapter addresses the cases of entrepreneurs in certain countries and some of the determinants of innovation and entrepreneurship that are the current focus of entrepreneurial policy in the EU. This analysis could also be applied to other geographical areas outside the European Union, and comparative studies could be conducted. In this sense, the explanatory variables of the model may vary according 53

 Innovation, Value Creation, and Entrepreneurship by Opportunity

to the socio-economic conditions of each country. Thus, it might be interesting to include some of the indicators considered in the Doing Business database (getting electricity, for example) in the empirical analysis in the case of developing countries.

CONCLUSION This chapter analyses how entrepreneurs, through the innovations they introduce in the market, have a positive impact on value creation. This process, however, is affected by many factors and this work has focused on those currently prioritized in the business policies adopted by the EU. The empirical analysis leads us to draw several conclusions. Opportunity entrepreneurship in the EU positively affects innovations and value creation. Furthermore, favourable expectations for entrepreneurship and demand stimulate entrepreneurial activity. The human capital of entrepreneurs affects entrepreneurship, but when human resources and investment in R&D are included, the effects of human capital are greater and highly significant. Access to credit also facilitates entrepreneurship. Finally, efficient regulations also have a positive impact on entrepreneurship and innovation, since entrepreneurs consequently have more time and resources to explore new business opportunities and to introduce innovations in the market. In short, we should consider how public policies can encourage entrepreneurial activity. This chapter is not intended to be an analysis of all the measures of economic policy that can stimulate entrepreneurial activity. However, the empirical analysis allows us to affirm that economic policies aimed at incentivizing access to credit, investment in human capital and R&D, and enhancing regulatory frameworks affecting businesses have positive effects on entrepreneurship and innovation, and hence on value creation.

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ADDITIONAL READINGS Abdesselam, R., Bonnet, J., Renou-Maissant, P., & Aubry, M. (2018). Entrepreneurship, economic development, and institutional environment: Evidence from OECD countries. Journal of International Entrepreneurship, 16(4), 504–546. doi:10.100710843-017-0214-3 Acs, Z. J., Estrin, S., Mickiewicz, T., & Szerb, L. (2018). Entrepreneurship, institutional economics, and economic growth: An ecosystem perspective. Small Business Economics, 51(2), 501–514. doi:10.100711187-018-0013-9 Antonelli, C., & Gehringer, A. (2017). Technological change, rent and income inequalities: A Schumpeterian approach. Technological Forecasting and Social Change, 115, 85–98. doi:10.1016/j.techfore.2016.09.023 Bjørnskov, C. (2017). Growth, Inequality, and Economic Freedom: Evidence from the US States. Contemporary Economic Policy, 35(3), 518–531. doi:10.1111/coep.12199 Bjørnskov, C., & Foss, N. J. (2016). Institutions, entrepreneurship, and economic growth: What do we know and what do we still need to know? The Academy of Management Perspectives, 30(3), 292–315. doi:10.5465/amp.2015.0135 Boudreaux, C. J., & Nikolaev, B. (2018). Capital is not enough: Opportunity entrepreneurship and formal institutions. Small Business Economics, 1–30. Bradley, S. W., & Klein, P. (2016). Institutions, economic freedom, and entrepreneurship: The contribution of management scholarship. The Academy of Management Perspectives, 30(3), 211–221. doi:10.5465/ amp.2013.0137 Chen, F. W., Fu, L. W., Wang, K., Tsai, S. B., & Su, C. H. (2018). The Influence of Entrepreneurship and Social Networks on Economic Growth—From a Sustainable Innovation Perspective. Sustainability, 10(7), 2510. doi:10.3390u10072510 Coulibaly, S. K., Erbao, C., & Mekongcho, T. M. (2018). Economic globalization, entrepreneurship, and development. Technological Forecasting and Social Change, 127, 271–280. doi:10.1016/j.techfore.2017.09.028 Digan, S. P., Kerrick, S. A., Cumberland, D. M., & Garrett, R. P. (2017). The roles of knowledge and organizational form on opportunity evaluation. Journal of Small Business Strategy, 27(2), 65–89.

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Eijdenberg, E. L., Thompson, N. A., Verduijn, K., & Essers, C. (2019). Entrepreneurial activities in a developing country: An institutional theory perspective. International Journal of Entrepreneurial Behaviour & Research, 25(3), 414–432. doi:10.1108/IJEBR-12-2016-0418 Foss, N. J., Klein, P. G., & Bjørnskov, C. (2018). The context of entrepreneurial judgment: Organizations, markets, and institutions. Journal of Management Studies. Fryges, H., Kohn, K., & Ullrich, K. (2011). The interdependence of R&D activity and debt financing of business start-ups (summary). Frontiers of Entrepreneurship Research, 31(3). Fuentelsaz, L., González, C., & Maicas, J. P. (2019). Formal institutions and opportunity entrepreneurship. The contingent role of informal institutions. BRQ Business Research Quarterly, 22(1), 5–24. doi:10.1016/j.brq.2018.06.002 Hessels, S. J., Van Gelderen, M., & Thurik, A. R. (2008). Entrepreneurial aspirations, motivations, and their drivers. Small Business Economics, 31(3), 323–339. doi:10.100711187-008-9134-x Nasiri, N., & Hamelin, N. (2018). Entrepreneurship Driven by Opportunity and Necessity: Effects of Educations, Gender and Occupation in MENA. Asian Journal of Business Research, 8(2), 57. doi:10.14707/ ajbr.180049 Pinho, J. C. M., & Thompson, D. (2017). Institutional-driven dimensions and the capacity to start a business: A preliminary study based on two countries. International Marketing Review, 34(6), 787–788. doi:10.1108/IMR-12-2015-0279 Raza, A., Muffatto, M., & Saeed, S. (2018). Cross-country differences in innovative entrepreneurial activity: An entrepreneurial cognitive view. Management Decision, MD-11-2017-1167. doi:10.1108/ MD-11-2017-1167 Sahasranamam, S., & Nandakumar, M. K. (2018). Individual capital and social entrepreneurship: Role of formal institutions. Journal of Business Research. https://www.elsevier.com/locate/jbusres

KEY TERMS AND DEFINITIONS Business Regulation: The administrative procedures in which entrepreneurs have to interact with external entities: local and national governmental offices, lawyers, auditors, banks, notaries, etc. Doing Business: The Doing Business Project provides an objective measurement of the regulations for doing business: it is calculated by World Bank. This project consider the following kinds of regulations that may constitute an obstacle to entrepreneurial activity: starting business; dealing with construction permits; getting electricity; registering property; getting credit; protecting minority investors; paying taxes; trading across borders; enforcing contracts; resolving insolvency; employing workers; contracting with the government. Human Development Index: The Human Development Index (HDI) is a statistic composite index of life expectancy, education, and per capita income indicators, which are used to rank countries into four tiers of human development. A country scores a higher HDI when the lifespan is higher, the education

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level is higher, and the gross national income GNI (PPP) per capita is higher. It is calculated by United Nations Development Program (UNDP)’s Human Development Report Office. Innovation Inputs: Human resources employed is highly qualified and investments linked to the production of scientific and technical knowledge present a high risk due to the great uncertainty about the results that exist when starting an R&D project, which prevents establishing a priori the relationship between output and inputs used. Innovation Outputs: Production of scientific and technological knowledge with positive externalities, therefore, social profitability exceeds private one. Latent Variable: It is variable does not directly observable, represents an empirical fact that is difficult to measure with one variable, therefore, latent variable is constructed by several indicators. Opportunity Entrepreneurship: Entrepreneur that start-up to net exploitation of a business opportunity. Oslo Manual: As the internationally recognised methodology for collecting and using innovation statistics, the Oslo Manual is divided in: measurement of innovation; concepts and definitions, methods for collecting and analysis statistics on business innovation. Partial Least Squares Estimation: It is a statistical method that is related to the regression of principal components, instead of finding hyperplanes of maximum variance between the response variable and the independent variables, there is a linear regression by projecting prediction variables and observable variables to a new space. Because both the X and Y data are projected into new spaces, the family of PLS ​​models is known as a bilinear model factor.

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Chapter 4

Social Entrepreneurship and Sustainable Development: New Challenges and Opportunities Susana de los Ríos-Sastre Universidad Pontificia Comillas, Spain Víctor M. González-Sánchez Universidad Nacional de Educación a Distancia, Spain

ABSTRACT There is no doubt about the relevant role of social entrepreneurs as social transformers and there seems to be broad consensus on the factors that characterize it, such as: a sustainable social orientation, the intensive use of innovation, and the aim of creating social value. This chapter offers an updated vision of social entrepreneurship around the world, showing the main advances made in recent years and analyzing the main challenges and opportunities for the near future. It includes a reflection on the concept of social entrepreneurship, since today there’s not a single definition of that term, and a review of the evidence on good practices in this field, which could serve as a model for future initiatives.

INTRODUCTION The development of entrepreneurship occupies a prominent place on the agendas of numerous international organizations, and it is found among the priorities of all governments across the five continents, as there is no doubt regarding the benefits it can provide to both the economy and society. Over the last few decades, the situation experienced in many countries has shown how entrepreneurship has been and continues to be a fundamental pillar regarding job creation. Moreover, it acts as a promoter of growth and competitiveness, while at the same time contributing to the accomplishment of certain social objectives. Nowadays, the prominence of the social entrepreneurship within this field is becoming increasingly important. A simple glance at the international scenario provides an insight into the increasing number of entrepreneurial initiatives with a social aim and how social enterprises are beginning to be acknowledged as an essential agent within the global economic context. Among others, the Organisation for Economic DOI: 10.4018/978-1-7998-1169-5.ch004

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 Social Entrepreneurship and Sustainable Development

Co-operation and Development (OECD) and the European Commission highlight the resilience that social enterprises have demonstrated during the recent economic-financial crisis as well as their capacity to provide stability to the labour market (OECD/EU, 2017). In addition, the potential of the companies operating in the field of the social economy as promoters of sustainable economic growth is highlighted, with a view to achieving Sustainable Development Goals (SDGs) established in the 2030 United Nations Agenda (United Nations, 2018). Nevertheless, the organizations that have been working for many years in this field (for example, the Skoll Foundation, Ashoka, and the Schwab Foundation, among others) and which offer support and impetus to thousands of social entrepreneurs across the world, insist that the advances made in the field of social economy are still insufficient to meet the social and environmental needs existing in the world. On the other hand, the so-called Fourth Industrial Revolution1 occupies a prominent position in today’s major world forums and meetings. As a matter of fact, it was a crucial point at the last annual meeting of the World Economic Forum (WEF), which took place in Davos (Switzerland) last January. Leaders from more than one hundred governments met with representatives from a wide range of organizations from all backgrounds to discuss issues that are revolutionizing today’s global society. More specifically, they discussed on artificial intelligence (AI), energy storage systems, drones and robots, nanotechnology, biotechnology or neurotechnology, among other topics. In other words, it is about those technological advances that are changing the way we work in all the sectors of the economy, the ways we communicate and about understanding life. Professor Klaus Schwab, founder and executive chairman of the WEF and who seems to be the one who coined this term, points out that the reasons for the transcendence of this fourth revolution are: the speed with which innovations are produced, the breadth and depth of changes and the complete transformation of systems. He literally states that “it is the fusion of these technologies and their interaction across the physical, digital and biological domains that make the fourth industrial revolution fundamentally different from previous revolutions” (Schwab, 2016). It is obvious that social entrepreneurship cannot remain oblivious to this phenomenon. In this respect, there are those who consider the fourth industrial revolution as a great opportunity to boost the growth of social enterprises, while others admit that this transformation process will only benefit those who are capable of innovating and adapting themselves quickly to changes. Considering these aspects, this chapter presents an updated vision of social entrepreneurship around the world. First and foremost, a brief reflection on the concept of social entrepreneurship is carried out, since today there is not a precise definition of that term. Subsequently, the main advances achieved in recent years are shown and several challenges for the near future are presented and, finally, some evidences are provided on good practices in this field, which could serve as a model for future initiatives.

SOCIAL ENTREPRENEURSHIP: DIFFERENT MEANINGS FOR A SINGLE TERM Regardless of the efforts undertaken, by both academics and different public and private organizations, it is currently not possible to come up with a single definition of social entrepreneurship. This is somewhat understandable, bearing in mind that it is a term composed of two concepts (“entrepreneurship” and “social”) both of which have a multidimensional and complex character2. Nowadays, there are a vast number of articles, reports, researches and initiatives aimed at providing a concise definition of what is meant by entrepreneurship, in which the philosophical aspects of the

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term are mixed with the economic and legal ones, often concluding in an ambiguous definition, which is susceptible to different interpretations. There is no doubt that the situation becomes even more complicated when a measurement of the entrepreneurship is carried out. On the other hand, it is a term that is strongly linked to the figure of the entrepreneur as well as the activities he performs, which makes it inevitable that it is directly linked to entrepreneurial activities, that is, activities that are performed within a company. It is well known that the business world also has its complexity and the type of companies existing today is both wide and diverse. The purpose of this chapter is not to carry out a conceptual revision of the term entrepreneurship, but several lines are dedicated to emphasize some relevant contributions in this field, with the aim of recalling how its meaning has been developed up to the present day, since there are some characteristics in common with social entrepreneurship. Let us remind ourselves that in the 18th century the economist Richard Cantillon was a pioneer in developing a theory of entrepreneurship who offered a modern approach regarding the significant role of the entrepreneurs in the economy. including the contributions of eminent economists, such as Adam Smith or Joseph Schumpeter3 who coined the German term unternehmergeist (entrepreneur spirit) over a century ago and proposed a definition of entrepreneur as a key agent in the creation of innovative companies and a fundamental driver of economic growth (Schumpeter, 1934). From then onwards, new definitions have continuously emerged in academic literature proposed by scholars (for example, Ács and Audretsch, 2003) and public institutions (European Commission, 2012; Ahmad and Seymour, 2018; among others). Notwithstanding the many valuable contributions, there is currently no widely accepted definition of the term used; actually, there is even some confusion about it. Among other proposals, the OECD had already suggested some standard definitions in relation to entrepreneurship more than a decade ago with the intention of bringing clarity to the concept at a worldwide level (see Figure 1). By linking the term “entrepreneurship” to the “social” element complicates the situation, as each of the definitions emphasizes one of the aspects of the term, and it is not possible to find a single meaning. In order to have an idea of how the concept has evolved, without having to go back to its origins, the following paragraphs summarize some of the most commonly used definitions since the beginning of the 21st century. One author of undeniable prestige in this field is J. Gregory Dees, who has unfortunately passed away, and whose contributions have been fundamental in the development of social entrepreneurship Figure 1. Standard Conceptual definitions Source: Ahmad and Seymour, 2008

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in the academic sphere. His brief article entitled The Meaning of “Social Entrepreneurship4” is one of the most cited in this field. In this paper professor Dees explains how social entrepreneurs can become changing agents within the social sector: “adopting a mission to create and sustain social value (not just private value); recognizing and relentlessly pursuing new opportunities to serve that mission; engaging in a process of continuous innovation, adaptation, and learning; acting boldly without being limited by resources currently in hand, and exhibiting heightened accountability to the constituencies served and for the outcomes created” (Dees, 2001). A few years later, Austin et al (2006) defined social entrepreneurship “as innovative, social value creating activity that can occur within or across the non-profit, business, or government sectors”. A shorter definition, which pointed out two of the most significant aspects: the use of innovation and the creation of social value; and clarified that social entrepreneurship is not an exclusive phenomenon of non-profit organizations. In this same paper, these authors compare a simple way of understanding commercial entrepreneurship and social entrepreneurship, looking at similarities and highlighting which are the main differences. Those differences, from their point of view, can be summarized by four aspects: market failure, mission, resource mobilization, and performance measurement. During the same period, Mair and Martí (2006) defined social entrepreneurship as “a process involving the innovative use and combination of resources to pursue opportunities to catalyse social change and/or address social needs”. These authors also mentioned the use of innovation, highlighting the role of the social entrepreneur as a possible catalyst for social change and the purpose for attending social needs. Furthermore, Nicholls and Cho5 (2006), in addition to reviewing the outstanding definitions, identified the three fundamental dimensions of social entrepreneurship: sociality (referring to the social and environmental approach), innovation, and market orientation (pointing out that on many occasions there are enterprises that operate in commercial markets, trying to improve their performance). Nevertheless, the lack of consensus continues to be present both in the academic literature as well as within society in general and this will perhaps remain for longer as it is not so simple, in practice, to find pure types of organizations. What we do often find today is what we might call hybrids. In other words, social entrepreneurs have many characteristics in common with those who do not have the adjective “social” attached to them and a few other features that might differentiate them. In a collective effort to highlight the broad concept of social entrepreneurship, some authors even choose to explain what it is not. For example, Huybrechts and Nicholls (2012) clarify the reasons why social entrepreneurship is not a discrete sector, it is not a synonym of social business, it is not a new form of corporate social responsibility, and it is not the only model of social innovation. In addition to the difficulty of selecting one of the existing definitions, social entrepreneurship is confused in practice with other closely related terms, such as social enterprises6. It is evident that an enterprise is something more specific and less ambiguous than entrepreneurship7, and therefore it seems to be easier to define. However, by adding the social component, a wide range of possibilities opens up again, as empirical evidence shows that so-called social enterprises do not necessarily have to be non-profit organizations but can also take other forms as long as the profit motive of their owners does not become a priority. For example, the European Commission proposed the following definition as an approximation to the concept of social enterprise: “an operator in the social economy whose main objective is to have a social impact rather than make a profit for their owners or shareholders. It operates by providing goods and services for the market in an entrepreneurial and innovative fashion and uses its profits primarily to achieve social objectives. It is managed in an open and responsible manner and, in particular, involves

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employees, consumers and stakeholders affected by its commercial activities” (European Commission, 2016). Whatever the legal structure of a social enterprise (cooperative, foundation, association, or any other) and regardless of the country in which it is established, it is evident that the primary objective would be to have a positive environmental and social impact. The need to harmonized concepts related to the social economy remains a recurring issue, both in academic debates as well as in the market itself. Moreover, international organizations continue their works to remove the ambiguity over the terms mentioned (social entrepreneurship, social enterprise, among others). To provide a specific example, since there is no single European legal framework for social enterprises, a statute has recently been developed within the European Union for companies operating in the social sector within the various Member States, entitled “Statute for social and solidarity-based enterprises8”. It is a legislative initiative that seeks simplification as well as greater coordination in this field. Within this overall search for a more accurate definition of social entrepreneurship, some authors try to shed some light by analyzing the differences with other terms such as, social service provision and social activism. In particular, Martin and Osberg (2007) highlighted three phases that could help to understand social entrepreneurship: “1) identifying a stable but inherently unjust equilibrium that causes the exclusion, marginalization, or suffering of a segment of humanity that lacks the financial means or political clout to achieve any transformative benefit on its own; 2) identifying an opportunity in this unjust equilibrium, developing a social value proposition, and bringing to bear inspiration, creativity, direct action, courage, and fortitude, thereby challenging the stable state’s hegemony; and 3) forging a new, stable equilibrium that releases trapped potential or alleviates the suffering of the targeted group, and through imitation and the creation of a stable ecosystem around the new equilibrium ensuring a better future for the targeted group and even society at large”. Considering the above mentions it would be desirable to establish a broadly accepted definition of social entrepreneurship9. However, it does not seem easy to reach it because of the complexity around the concept.

SOCIAL ENTREPRENEURSHIP AS A TOOL TO ACCOMPLISH THE SDG (2030 AGENDA): THE MAIN PRESENT-DAY CHALLENGES The seventeen goals established in the 2030 Agenda for Sustainable Development of the United Nations and the specific targets set in each one of them, have given a new framework for most public and private initiatives over the last few years. With a timeline set for 2030, any individual or collective contribution is welcome, since they are ambitious goals which affect the global society of any country. The United Nations focuses on the potential of social entrepreneurship as an effective tool to achieve the SDGs, since it contributes to job creation and economic development, while it also helps to reduce social inequalities. In more concrete terms, social enterprises are considered to play a key role in achieving SDG 8 (Decent Work and Economic Growth) and SDG 10 (Reduced Inequality), as they are institutions with a distinctive combination: they are designed to attend to the social needs that are not covered, but strive to be economically sustainable; in other words, they help economic and social development, by giving support mainly to the most vulnerable groups in society. Based on this idea and considering the vulnerability of the younger segments of the population, the most recent studies carried out within the United Nations are focusing on the analysis of the opportunities and challenges surrounding Youth Social Entrepreneurship. The forthcoming United Nations World 68

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Youth Report, to be published in the course of 2019, will be entitled Youth Social Entrepreneurship: An Integrated Development Solution Toward the 2030 Agenda. This report will hopefully propose specific lines of action that will enable us to face up to the current challenges in the field of social entrepreneurship, especially regarding young people. From a global point of view, there is considerable consensus on the fact that the role of social enterprises would be more effective and efficient if an adequate entrepreneurial ecosystem were to be created. Although the characteristics of the participants in the social economy of each country together with their degree of development are different, there are certain common factors that must be considered if an entrepreneurial ecosystem is to function efficiently. There are numerous elements to be taken into account when talking about entrepreneurial ecosystems, among others: human, social and financial capital; infrastructures; the degree of training of the participants or the legal and fiscal framework. In this respect, the proposal of the European Commission may serve as a reference when analyzing the ecosystem of social enterprises in the EU area. In Figure 2 the factors that make up this ecosystem are summarized, including two of the most frequently discussed elements: the legal framework and access to finance. Nonetheless, as the figure shows, these are not the only aspects that can improve or slow down the development of social enterprises. The same report draws several conclusions about the necessary conditions towards the correct functioning of the entrepreneurial ecosystem, such as: the development of research and training strategies to improve the management skills of social enterprises; a broader recognition on behalf of national Figure 2. Social Enterprise Eco-System Source: Borzaga and Galera, 2016

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governments and the definition of coherent public policies (including public procurement strategies); strengthening the capacity of social enterprises to self-organize and the availability of financing strategies and plans adapted to the characteristics of social enterprises (Borzaga and Galera, 2016). In addition, some international organizations refer to the establishment of social entrepreneurship education programmes as improvement aspects, which do not necessarily have to be financed with public funds, since successful public-private collaboration initiatives already exist, for example, between schools and third-sector organizations (OECD/EU, 2017; among others). On the other hand, one of the most recent trends relating to the phenomenon of social entrepreneurship is the proposal of a systems change. The Schwab Foundation for Social Entrepreneurship, which manages the largest late-stage network of social entrepreneurs in the world, has placed at the center of the debate the notion of “systems change10” (see WEF, 2017). The arguments in favor of this change are mainly based on the limitations and slowness of conventional models (e.g. the duplication of branches, social franchises, among others) in order to respond to the vast and urgent needs of our society. Moreover, according to research undertaken by the Schwab Foundation, it seems that the social entrepreneurship sector is beginning to accept the limits of increasing growth, i.e. admitting that it is necessary to change the way successful social entrepreneur initiatives increase their scale of applicability. This does not necessarily mean that everyone must become a system entrepreneur, or abandon direct service models; on the contrary, it is about complementing each other. Additionally, the study suggests which are the qualities for a social entrepreneur to become a systems entrepreneur that it can be summarized in five aspects (see Figure 3). Therefore, social entrepreneurship continues to evolve and adapt to social changes. It is important to face new challenges, without missing opportunities for improvement.

THE SITUATION OF SOCIAL ENTREPRENEURSHIP AROUND THE WORLD As mentioned above, in order to assess the progress and true contribution of social entrepreneurship in meeting the Sustainable Development Goals, it is necessary to improve the measures used at an international level. Undoubtedly, the specific nature of entrepreneurship makes it difficult to measure and compare them between countries, which is why it would be convenient to achieve a rapid global consensus on the basic indicators that complement the existing ones. This section shows a photograph of the current situation of social entrepreneurship across the world, based on the results of specific research conducted by the Global Entrepreneurship Monitor (GEM), as it is considered as one of the most relevant initiatives in measuring entrepreneurship worldwide. To be precise, the data have been taken from specialized reports on social entrepreneurship conducted within the GEM Consortium. Figure 4 shows the average social entrepreneurial activity per region by comparing the available data for 2009 and 2015. The data are collected by differentiating between those social entrepreneurs who are in an operational phase (established businesses) from those who are still in a start-up phase (nascent social entrepreneurs). In all regions, the percentage of population between 18 and 64 years who is performing social entrepreneurship has increased in both categories. As it appears, a significant consolidation regarding the social entrepreneurial activity can be seen, reflected in the considerably greater increase in the number of people who are in the operational phase. In fact, while in 2009 the proportion of start-up phase was much higher in all areas to that of the number of social entrepreneurs who had 70

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Figure 3. Lessons for Systems Change Source: WEF, 2017

already progressed to the operational phase, the most recent data show the consolidation of operational entrepreneurship activity. Therefore, the differences between the social entrepreneurial activity in startup and operational phase changed trend in 2015. Apart from the Eastern Europe and Latin America and Caribbean11 regions, social entrepreneurship is superior in the operational phase. According to Bosma et al. (2016), even in Australia and in the US about one in ten people between 18-64 years of age is a social entrepreneur. Whereas by countries, some such as Israel, Luxembourg and Ireland have remarkably high rates of social entrepreneurship. In turn, the high rates of social entrepreneurship in Sub-Saharan Africa can be explained by the fact that these economies tend to be characterized by small-scale entrepreneurial activity in general, that is, they usually employ very few people and do not have very high turnover levels. As mentioned in previous paragraphs, some academics, policy makers and professionals point out that social entrepreneurship requires innovative solutions or innovative approaches, since the problem of society would not exist if it could have been solved by simply adopting general approaches. In this regard, as with commercial entrepreneurship, the demand for innovative products and services is also growing in the field of social entrepreneurship (Bosma et al., 2016). Figure 5 shows the share of the operational social entrepreneurship that could be considered as innovative. The average rate of innovation among the countries analysed by the GEM is 1.6% of the population between the ages of 18-64, with variations of an estimated minimum of 0.1% in Iran and Bulgaria to a maximum of 4.0% in the Philippines and Israel. In terms of geographical areas, Australia

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Figure 4. Social entrepreneurial activity by region Source: Terjesen et al., 2012, and Bosma et al., 2016

is the most innovative from the social entrepreneurship perspective accounting for 3.8%, followed by Latin America and the Caribbean with over 2% in 2015. It is precisely in Southern and Eastern Asia and Latin America and the Caribbean, which are the only two regions where social entrepreneurs who consider themselves to be innovators are in the majority with respect to the others. Meanwhile, in Eastern Europe, the average among the seven countries analyzed, barely exceeds 0.8%. Likewise, in Brazil and Vietnam there are at least twice as many social entrepreneurs considered innovative compared to those who do not see themselves as such. The GEM also assesses the extent to which social entrepreneurs prioritize social and environmental goals over financial goals. Achieving short-term financial returns is often necessary for surviving and creating long-term social impact. In other words, the social entrepreneur faces the dilemma of the potential financial impact on the organization (value capture) as opposed to the social impact that its activity may Figure 5. Operational social entrepreneurship activity by region: innovative and others by region Source: Bosma et al., 2016

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have on the society and on the environment (value creation). It is hoped that social entrepreneurs will seek to achieve value creation, since the objectives pursued are predominantly social (Bosma et al., 2016). Figure 6 shows the proportion of entrepreneurs linked to social entrepreneurial activity who feel largely identified when the GEM researchers ask them about their opinion on the following statement: “For my organisation, generating value to society and the environment is more important than generating financial value for the company”. In other words, those entrepreneurs that consider value creation to be more important than financial performance. There are significant disparities between the different regions, since in most areas, social entrepreneurs do not place value creation before value capture. Western Europe (25%), Latin America and the Caribbean (31%) and Australia and the US (58%) present a higher proportion of social entrepreneurial activity with clearly dominant social objectives, while in Chile and Colombia the percentage of the population between the ages of 18-64 who are social entrepreneurs and prioritize the social impact of their activity on society and the environment, is even double that of those who do not prioritize this value creation over value capture. Like most human activities, the entrepreneurship activity needs money to initiate and develop its objectives. New entrepreneurs generally rely on personal finance, as well as other funding from, for example, family and friends, or fundraising with banks, investors or public bodies. In accordance with the above, the main financial characteristic of social entrepreneurs lies precisely in the social objectives they pursue, which are sometimes not so close-related to those of the typical financial profitability. Therefore, the sources of financing of the social entrepreneurs do not always coincide with the interests of the traditional forms of financing. However, in recent years, various types of financing have emerged, such as impact investing and crowdfunding, which seem to respond more effectively to the needs of social entrepreneurs. Figure 7 below illustrates this idea. On the one hand, in all regions studied at least four out of five social entrepreneurs need for funding to start social entrepreneurial activity and, even it exceeds 90% in Sub-Saharan Africa, Eastern Europe, Australia and the US. On the other hand, the percentage of social entrepreneurs who invest their own money to start their business ranges from about two out of Figure 6. Operational social entrepreneurship activity and dominance of value creation over value capture by region Source: Bosma et al., 2016

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three in Western Europe to the regions of South-East Asia and Sub-Saharan Africa where at least four out of five use self-financing. Nevertheless, the average rate of self-investment (the percentage of selfinvestment over total investment) shows a greater disparity. Social entrepreneurs in South-East Asia, Middle East and North Africa finance a larger percentage (estimated to be over 60%) of the investment with their own funds, while the share of self-investment in Sub-Saharan Africa is around 30%. As previously discussed, social entrepreneurs also expect to obtain money in order to achieve their objectives through sources other than their own. According to Bosma et al. (2016), up to 38% of the world’s social entrepreneurial ventures depend on government funding, while family and banks are also important sources of financing for the social entrepreneurs (both of which account for around 24%). However, social entrepreneurs also depend on the financing of colleagues, friends, neighbours, private investors and online crowdfunding (see Table 1). The differences observed in the main sources of financing are quite significant from a regional perspective. The social entrepreneurs of South-East Asia and Sub-Saharan Africa rely heavily on their own resources, as well as on funding from family and friends. Meanwhile, personal funds and family savings play a less important role in Western Europe, Australia and in the US. It is precisely in Australia and in the US where the funds coming from government programs, donations or grants are most widely used, with approximately half of the social entrepreneurs who are awaiting access to these resources in order to start their activity. Furthermore, these two economies also show a greater propensity to use private investment and online crowdfunding as a source of financing for nascent social entrepreneurship. The case of Sub-Saharan Africa was singled out as a region where online crowdfunding linked to social enterprises is still a pending issue.

Figure 7. Funding required for start-up social entrepreneurs by region Source: Bosma et al., 2016

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Table 1. Other sources of funding used by nascent social entrepreneurs by region Family

Friends or neighbours

Employer or work colleagues

Banks or other financial institutions

Private investors or venture capital

Government programmes, donations or grants

Online crowdfunding

Southern and Eastern Asia

68%

47%

28%

37%

11%

25%

11%

Middle East and North Africa

51%

9%

12%

19%

9%

28%

11%

Sub-Saharan Africa

67%

39%

27%

42%

27%

38%

0%

Eastern Europe

49%

18%

23%

19%

19%

42%

14%

Western Europe

38%

14%

18%

25%

25%

43%

9%

Latin America and Caribbean

36%

23%

18%

24%

15%

41%

7%

Australia and US

37%

18%

30%

27%

27%

55%

18%

Note: Figures denote non-weighted country averages. Individual cases have not been weighted. Source: (Bosma et al., 2016)

GOOD PRACTICE EXAMPLES The trend over the past few years has led to a global recognition of the key role of the social enterprises, which is to achieve the ambitious goal of an all-inclusive economy and society. Several international organizations, including the OECD, state that in order to obtain the maximum potential from the social enterprises, it is essential to create an enabling ecosystem consisting of components in a coherent, interconnected and transversal manner. In other words, it is necessary to establish policies that facilitate the development of the so-called social enterprises in different areas (legal framework, access to finance, education and access to market, among others), with the participation of the active members of the different stakeholders and that these should be coordinated at the national and territorial levels. It would also be worth sharing the experiences of social entrepreneurs who work in different countries and backgrounds, so that they may serve as inspiration to others. As in other fields, one can learn through experiences from the past, especially when it takes place in diverse environments. In this sense, it is necessary to highlight the collaboration that the OECD and the European Commission are carrying out, not only to promote the entrepreneurial spirit of the European population, but also to facilitate access to interesting information on successful initiatives developed in Europe. More specifically, the recent report entitled Boosting Social Enterprises Development: Good Practice Compendium, prepared in conjunction with the two institutions, includes twenty highly diverse success cases (OECD/EU, 2017). The compendium shows how the initiatives have very different backgrounds, there is a great diversity of areas for application, as well as a mixture of funding sources (public, private, etc.). The Table 2 lists the above twenty cases, with a brief reference to the objectives of the programme or policy and the impact achieved (up to the date of closure of the information collected).

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Table 2. Initiatives on social enterprises SAW-B: A training and advisory services federation

BELGIUM (1981 – on-going)

Objectives To bring together social economy actors, from all sectors of activity, to exchange practices and highlight their concerns at the political level

Impact The establishment of a consultative body on social economy; the adoption of a legal definition of the social economy; the creation of the social-purpose company; and the formulation of public agreements or labels.

Social Innovation Factory: An early-stage business support structure

BELGIUM (2013 – on-going)

Objectives Raising awareness about social innovation and social entrepreneurship. Enabling actors to tackle challenges in a socially innovative and entrepreneurial manners

Impact It has helped more than 300 innovators develop their business model, find business partners, evaluate their impact, scale-up, and analyze their target group.

The National Strategy for the Development of Social Entrepreneurship

CROATIA (2015 – on-going)

Objectives Boost social enterprise creation and growth by establishing a more supportive institutional and financial environment. Decrease regional disparities, increase employment and ensure fair distribution of wealth.

Impact No data are available

Copenhagen Project House (KPH): An incubator for social startups

DENMARK (2009 – on-going)

Objectives 1. Create value for society by supporting cultural and social enterprises during the early and scaling stages. 2. Strengthen inter-sectorial partnerships by actively linking the public, private and voluntary sectors. 3. Focus on market failure areas where the municipality is not active and there is a need for new services.

Impact The KPH network of private partners has helped to meet entrepreneurs’ small practical needs and brokered substantial partnerships, creating opportunities for social entrepreneurs to test ideas in cooperation with experienced entrepreneurs, organisations and businesses, as well as develop new business and investment prospects. KPH now houses over 300 social entrepreneurs, more than 60 companies and organisations and hosts around 20 permanent cultural events.

Alter’Incub: A regional incubator

FRANCE (2007 – on-going)

Objectives To develop a multi-stakeholder response to unmet local needs. To drive the creation of social enterprises that enhance economic, social, and local development, and create jobs

Impact It created 250 jobs and 41 social enterprises in the region. It has contributed to defining social innovation and social enterprise in France and has helped define regional and national policies supporting social innovation. It now heads a network of five incubators in three regions of France

The Law on the Social and Solidarity Economy (SSE)

FRANCE (Entry into force in July 2014)

Objectives It aims to meet the need for recognition of SSE actors; to recognize SSE as a specific model of entrepreneurship; and to complete or reform a range of tools aiming to foster the development of SSE actors

Impact No data are available

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Table 2. Continued SAW-B: A training and advisory services federation

BELGIUM (1981 – on-going)

PHINEO: A financial intermediary

GERMANY (2010 – on-going)

Objectives To strengthen civil society while improving the impact of non-profit organisations (NPOs) and social-enterprises activity; building bridges among and between donors, social investors, NPOs and social enterprises

Impact Drawing broad attention to the need to heighten the impact of the social sector, thereby improving the visibility and credibility of NPOs and social enterprises. It has expanded its tri-sectoral network of private, public and civil-society stakeholders from 10 to more than 100 active partners. It has analyzed more than 800 NPOs and social enterprises, and awarded the impact label to 200 of them.

Financing Agency for Social Entrepreneurship (FASE): An intermediary for hybrid financing

GERMANY (2013 – on-going)

Objectives 1. Mobilise growth capital for early-stage social enterprises, to enable them to scale their impact. 2. Develop innovative financing strategies, securing more impactminded investors, and build a pipeline of investment-ready social enterprises

Impact FASE has successfully closed 20 transactions, channeling around EUR 8 million (as of December 2016) into the social finance sector and advising approximately 200 social enterprises on the nature, process and requirements of raising growth capital. It has added over 250 current and potential impact investors as part of their network and has published over 30 articles, interviews, and papers

Clann Credo: A social finance provider

IRELAND (1996 – on-going)

Objectives 1. Provide loans with affordable conditions to community, voluntary and social enterprises (CVSEs). 2. Strengthen the regional social investment market.

Impact It has lent over EUR 82 million to over 800 projects. It currently has a retail loan book of EUR 18.5 million. In 2011, an economic audit found that every euro injected into the economy by a Clann Credo client benefitted the economy by a further 32% (e.g. through wages or purchases of goods and services).

JEREMIE Sicily ESF Social Finance: A microfinance scheme

ITALY (2013 – 2016)

Objectives Support the creation and development of SMEs and social enterprises dedicated to promote the economic empowerment of vulnerable workers by facilitating access to the labour market through a microfinance scheme.

Impact By July 2016, 82 enterprises – 8.14% of applicants– had received individual loans averaging EUR 56,423. Applications that passed the non-financial partners’ preliminary appraisal had a higher (73.5%) success rate, proving the partners’ ability to generate value and define an innovative business model for the microfinance sector. Each enterprise that received a loan created two jobs on average.

Social Impact Factory: A business-support structure

NETHERLANDS (2014 – on-going)

Objectives 1. Inspire, connect and spur businesses to adopt socially responsible behaviours 2. Create an enabling environment for social enterprises

Impact In 2015, the Factory’s network comprised 90 social entrepreneurs, 7 large traditional businesses and 15 municipalities. In the six first months of its existence, the Social Impact Market has led to 21 matches, totalling EUR 75 000 in revenue. In 2015, 10 “complex problems” submitted by the local government were addressed: 75 organisations were involved and the total budget invested amounted to EUR 130 000.

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Table 2. Continued SAW-B: A training and advisory services federation

BELGIUM (1981 – on-going)

ES Fund TISE: A loan fund for social enterprises

POLAND (2013 – on-going)

Objectives The programme aims to provide existing social enterprises with repayable financing to foster the investment and job creation necessary to the expansion of their activity.

Impact As of May 2016: 431 loans to 371 social enterprises. The loans appeared to be an effective tool to combat unemployment with the capacity to create (436 new jobs) and preserve workplaces. The post-investment counselling that was provided to 241 enterprises improved the performance of the borrowers and overall effectiveness of the project

Portugal Inovação Social: An integrated approach for social innovation

PORTUGAL (2015 – 2020)

Objectives Establish and promote an investment market for social enterprises to catalyse and mobilise EU structural funds.

Impact Limited evidence of impact given the very recent launch of the programmes

Barcelona City Council Decree for Socially Responsible Public Procurement

SPAIN (2013 – on-going)

Objectives Use public procurement to create work opportunities for the most vulnerable members of society and thus improve social cohesion; foster collaboration among different sectors and develop the social sector (employment centres; WISEs; NPOs).

Impact In its first year, 75% of all published contracts incorporated the stipulated social clauses and 770 people in situations (at risk) of social exclusion benefited from the Decree. The Decree has not yet reached its full impact because many multi-annual contracts will only incorporate the social criteria when they come up for renewal. Many municipalities in the country replicated the methodology, text and structure applied in Barcelona

El Hueco: A local incubator

SPAIN (2012 – on-going)

Objectives Create a favourable environment for the creation and development of social enterprises in Sparsely Populated Areas (SPAs), such as the region of Soria in Spain

Impact In 2015, it helped to create 22 organisations and 120 jobs, and attracted 115 business advisors. Its co-working space hosted 30 organisations. Through its various events, networking, communication campaigns and media presence, it has raised awareness of social enterprises and the challenges they face.

Big Potential: An investment readiness support programme

UNITED KINGDOM (2014-2017)

Objectives Help voluntary, community and social enterprises (VCSEs) get ready for investment or win public contracts. Raise awareness of investment approaches for VCSEs.

Impact It has approved 128 Breakthrough grants (246 applications received) and 23 Advanced grants (58 applications received). It has gathered and accredited 39 Breakthrough support providers and 24 Advanced ones. 4 successful investments in VCSEs, raising a total EUR 1.2 million in finance.

A Partnership for Supporting the Social Enterprise Strategy

UNITED KINGDOM (2011 – on-going)

Objectives Inform, encourage and support social enterprises at the grassroots level to raise their profile through policy engagement and communication; recognise and acknowledge the value they bring to local communities and to meeting government objectives at both the local and national levels. Enhance the sector’s collective influence and contribution to policy development, both nationally and locally; and strengthen the capacity, membership base and sustainability of the partner organisations

Impact It has increased collaborative working, both through intermediaries and across individual social enterprises, at both local and national levels. The “synergy-led business culture” developed through the Strategy has attracted much attention from other business areas and regions. In Scotland, the design of a new strategy is in progress

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Table 2. Continued SAW-B: A training and advisory services federation

BELGIUM (1981 – on-going)

Specialisterne & SAP: A partnership for access to markets

MULTIPLE COUNTRIES DENMARK (2004 – on-going)

Objectives Pioneer new ways of harnessing skills of people with Autism Spectrum Disorder (ASD) and empower them by matching them with businesses in need of IT experts. Achieve sustainable procedures and operations, by implementing the SAP mission of thought leadership on global innovation and establishing a learning programme for all stakeholders involved. Re-design and re-orient the SAP human resource policies and processes to fully incorporate neuro-diversity (so that the programme’s parallel on-boarding process would no longer be necessary to access the talents of people with ASD).

Impact The SAP’s “Autism at Work Programme” operated in 8 countries (Germany, India, Canada, Brazil, the Czech Republic, Ireland, the United States and Australia) and provided work opportunities to more than 100 people.

Junior Achievement Europe: An education network

MULTIPLE (2001 – on-going)

Objectives Teaching young people as early as possible about the world of enterprise and entrepreneurship, including social entrepreneurship, by bringing together the public and private sectors into education; to foster innovative thinking and the improvement of work and life skills among young people

Impact In 2014/15, JA organisations reached 3.5 million students in Europe, supported by 117,000 teachers and 164,000 business volunteers. A study on the SIR programme revealed that 78% participating students were more confident in their ability to start a social enterprise; 86% were more aware of the social issues in their own community; 84% were more aware that social and business objectives could be complementary.

NESsT: A multipronged support structure

MULTIPLE (1997 – on-going)

Objectives Develop and invest in enterprises from multiple countries that use market-based solutions to create opportunities for viable employment and income generation

Impact By 2015: Supported 167 social enterprises; Invested EUR 10 million in financial support and capacity-building; Provided training in social entrepreneurship and business planning to 12,000 leaders from 5,300 organisations. NESsT enterprises achieve a 25% revenue growth on average.

Source: (OECD/EU, 2017)

On the same line, the World Economic Forum has recently published a White Paper12, which supports the idea that new practitioners of the social entrepreneurship sector learn better through the experiences of other social entrepreneurs. In this case, the aim has been to help the social entrepreneurs to understand the meaning of a systems change, not based on abstract concepts, but rather through the experience of real cases that could be qualified as good practices in the sector. The report titled Beyond Organizational Scale: How Social Entrepreneurs Create Systems Change includes an in-depth analysis of six cases of social entrepreneurship that have undergone a systems change (see table 3).

CONCLUSION The aim of this chapter has been to provide an overview of social entrepreneurship and to highlight its importance as an instrument to help in the achievement of the goals included the 2030 Agenda for Sustainable Development, adopted by all United Nations Member States in 2015. Considering it is an ambitious purpose with a near horizon, it is necessary to enhance the active participation of governments, private

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Table 3. Social entrepreneurs creating systems change Child & Youth Finance International (CYFI) It is a global network that focuses on increasing the economic citizenship of children and youth (aged 8-24). It hosts initiatives designed to mobilize a network of national governments, multilateral organizations, central banks and financial institutions to reshape financial and educational systems to economically and socially empower children and youth worldwide. Fundación Escuela Nueva (founded in 1987) It is a non-profit organization to preserve and promote an educational model (Escuela Nueva). It was originally developed to improve the quality of rural public primary schools in Colombia and it became a prominent government programme for the country’s rural schools. The model transforms conventional schools by putting children at the centre of the learning process and placing teachers in the new role of facilitator. Landesa (founded in 1992) The organization works closely with governments and civil society to design, promote and implement land rights reform initiatives that provide secure legal land rights to poor women, men and communities. Landesa identifies countries where land reform could act as a catalyst for moving people out of poverty. Nidan It incubates organizations that mobilize and strengthen the collective action of informal workers. Nidan identifies common needs across informal worker groups, develops sustainable business models and trains emerging leaders so that organizations can advocate for protective legislation and create sustainable markets for informal worker services and products. Then, Nidan provides supportive services to each of them, including financial reporting and audits, training and development for board governance, and ongoing access to its broader network. Sproxil It is a for-profit company dedicated to using mobile technology to enable consumers to verify product authenticity at the point of purchase. Sproxil’s initial offering was tailored to the pharmaceutical industry in Nigeria, which has one of the world’s largest counterfeit drug markets. It has expanded its services beyond pharmaceuticals, signing on clients in the agrochemical, consumer products, and oil and gas industries; as well as to other African countries, India and Pakistan. VillageReach It is a health systems-strengthening organization, works at the “last mile” of public healthcare, bringing innovative solutions to the challenge of reaching the most underserved communities in the world. It develops, tests, implements and scales new systems, technologies and programmes that improve health outcomes by extending the reach and enhancing the quality of healthcare. Its solutions address barriers in access, such as the accessibility of healthcare, constraints in human resources, the availability of information and inadequate infrastructure. Source: (WEF, 2017)

sector as well as civil society in order to achieve the 17 Sustainable Development Goals set out in United Nations Agenda, more specifically social enterprises can play a crucial role in achieving SDG 8 and SDG 10. In this context, Hummels (2018) has made a proposal for an additional Sustainable Development Goal expressed as: “Promote and strengthen the capabilities of individuals and the communities in which they live to actively participate in and effectively influence policies, practices and activities that are part of the global sustainability agenda”. In his work entitled The 18 Sustainable Development Goal: Social Entrepreneurship in a global society, the author emphasizes the role of social entrepreneurship to ensure that those who are the beneficiaries of its activity have the capacity to decide about their lives. Nowadays, there is no doubt about the positive impact of social entrepreneurship on society, mainly on the most vulnerable segments. It is also true that the phenomenon of social entrepreneurship is adapting to the changes experienced by society and, consequently it is influenced by the effects of the so-called 4th Industrial Revolution. In fact, the development of digital technology and artificial intelligence are offering new opportunities to the business world. After all, social enterprises are businesses, therefore they should benefit from technological advances. However, experience shows that they could also be the cause of inequalities and differences between different segments of the population. 80

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In spite of the great opportunities that the efficient use of technology can entail for social entrepreneurs, some challenges still remain around social entrepreneurship, such as: the creation of an appropriate legal framework for social enterprises, the need for an adequate financial ecosystem that combine public and private funding or improve the measurement of social value creation of social enterprises. Even the lack of a single universally accepted definition for social entrepreneurship suggests that is still a field under development.

REFERENCES Ács, Z. J., & Audretsch, D. B. (2003). Handbook of entrepreneurship research: An interdisciplinary survey and introduction. Boston, MA: Kluwer. Ahmad, N., & Seymour, R. G. (2008). Defining entrepreneurial activity: definitions supporting frameworks for data collection. OECD Statistics Working Papers, 2008/01. doi:10.1787/243164686763 Austin, J., Stevenson, H., & Wei‐Skillern, J. (2006). Social and commercial entrepreneurship: Same, different, or both? Entrepreneurship Theory and Practice, 30(1), 1–22. doi:10.1111/j.1540-6520.2006.00107.x Borzaga, C., & Galera, G. (2016). Social enterprises and their eco-systems: Developments in Europe. European Commission; doi:10.2767/823980 Bosma, N. S., Schøtt, T., Terjesen, S., & Kew, P. (2016). Global entrepreneurship monitor 2015 to 2016: Special report on social entrepreneurship. Global Entrepreneurship Research Association. Dees, J. G. (2001). The Meaning of “Social Entrepreneurship”. Duke University Working Paper. Retrieved from https://entrepreneurship.duke.edu/news-item/the-meaning-of-social-entrepreneurship European Commission. (2012). Entrepreneurship in the EU and beyond. Flash Eurobarometer, 354. Retrieved from http://ec.europa.eu/commfrontoffice/publicopinion/archives/flash_arch_360_345_ en.htm#354 European Commission. (2016). Social enterprises and the social economy going forward. A call for action from the Commission Expert Group on Social Entrepreneurship (GECES). Brussels, Belgium: European Union. Henrekson, M., & Sanandaji, T. (2018). Schumpeterian entrepreneurship in Europe compared to other industrialized regions. International Review of Entrepreneurship, 16(2), 157–182. Hummels, G. J. A. (2018). The 18 sustainable development goal: social entrepreneurship in a global society. Utrecht University - Discussion Paper Series 18-1, March. Huybrechts, B., & Nicholls, A. (2012). Social entrepreneurship: definitions, drivers and challenges. In C. K. Volkmann, K. O. Tokarski, & K. Ernst (Eds.), Social entrepreneurship and social business: an introduction and discussion with case studies (pp. 31–48). Heidelberg, Germany: Springer. doi:10.1007/9783-8349-7093-0_2 Mair, J., & Martí, I. (2006). Social entrepreneurship research: A source of explanation, prediction, and delight. Journal of World Business, 41(1), 36–44. doi:10.1016/j.jwb.2005.09.002

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Martin, R. L., & Osberg, S. (2007). Social entrepreneurship: the case for definition. Stanford Social Innovation Review, 5(2), 28–39. Nicholls, A., & Cho, A. H. (2006). Social entrepreneurship: the structuration of a field. In A. Nicholls (Ed.), Social entrepreneurship. new models of sustainable change (pp. 99–118). Oxford, UK: Oxford University Press. OECD/European Union. (2017). Boosting social enterprise development: good practice compendium. Paris, France: OECD Publishing. Orejas, R., Buckland, H. & Castizo, R. (2016). Study of social entrepreneurship and innovation ecosystems in the Latin American Pacific Alliance countries: Regional analysis: Chile, Colombia, Costa Rica, Mexico, & Peru. Inter-American Development Bank, Technical Note Nº 1148, 1-14. Peredo, A. M., & McLean, M. (2006). Social entrepreneurship: a critical review of the concept. Journal of World Business, 41(1), 56–65. doi:10.1016/j.jwb.2005.10.007 Saiz Álvarez, J. M. (Ed.). (2016). Handbook of research on social entrepreneurship and solidarity economics. Hershey, PA: IGI Global. doi:10.4018/978-1-5225-0097-1 Schumpeter, J. A. (1934). The theory of economic development. an inquiry into profits, capital, credit, interest, and the business cycle. Harvard Economic Studies 46. Cambridge, MA: Harvard University Press. Stevenson, H. H., & Jarillo, J. C. (2007). A paradigm of entrepreneurship: entrepreneurial management. In Á. Cuervo, D. Ribeiro, & S. Roig (Eds.), Entrepreneurship (pp. 155–170). Heidelberg, Germany: Springer. Terjesen, S., Lepoutre, J., Justo, R., & Bosma, N. (2012). Global entrepreneurship monitor: 2009 report on social entrepreneurship. Global Entrepreneurship Research Association. United Nations. (2018). World Youth Report: youth and the 2030 agenda for sustainable development. New York, NY: United Nations Department of Economic and Social Affairs. WEF. (2017). Beyond organizational scale: how social entrepreneurs create systems change. Geneva, Switzerland: World Economic Forum.

ADDITIONAL READING Information Resources Management Association. (2019). Social Entrepreneurship: Concepts, Methodologies, Tools, and Applications (3 vol). Hershey, PA: IGI Global. Lundström, A., Zhou, C., von Friedrichs, Y., & Sundin, E. (Eds.). (2014). Social Entrepreneurship: Leveraging Economic, Political, and Cultural Dimensions. International Studies in Entrepreneurship. Switzerland: Springer. doi:10.1007/978-3-319-01396-1 Seymour, R. G. (Ed.). (2012). Handbook of Research Methods on Social Entrepreneurship. Cheltenham: Edward Elgar Publishing Limited. doi:10.4337/9781781001059 Skoll Foundation. (2019). Programs for Social Entrepreneurship. Retrieved from http://skoll.org/about/ programs/ 82

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KEY TERMS AND DEFINITIONS Entrepreneurial Ecosystem: is the set of different elements (regulatory, economic, cultural, etc.) that can form an optimal environment for innovative organizations if they are appropriately combined and supported. Social Enterprise: is a (non-profit or for-profit) organization that uses traditional business methods to achieve (primarily) social or environmental outcomes and reinvests its profits back into the business. Social Impact: is the effect that individuals and organization’s actions have on the well-being of a community. Social Innovation: is the process of developing new products, services or models to find a more effective solution to social needs, seeking the social progress of the most vulnerable population. Systems Change: the process that shifts the links and interactions that form the architecture of a system, that is, to change the rules, the objectives and standards of a system at equilibrium.

ENDNOTES 1



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5

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Also known as Revolution 4.0. It is advisable to review the information available in https://www. weforum.org/focus/fourth-industrial-revolution. Some authors argue that in order to understand the meaning of social entrepreneurship it is necessary to carry out an in-depth analysis of the concepts “social” and “entrepreneurship” on an individual basis, as well as the relationship between them (Nicholls and Cho, 2006; Mair and Martí, 2006). To this day, the invaluable contributions of Schumpeter are, of course still being used. See, for example, the recent study by Henrekson and Sanandaji (2018). The original draft paper was published in October 1998. Only one of the chapters of the book edited by A. Nicholls himself is quoted in this text, although it is also recommended to read other chapters where there are very interesting contributions regarding the phenomenon of social entrepreneurship. For that reason, it is not surprising that when we refer to “social entrepreneurship” there are those who relate it directly to the so called “social enterprises”. An imprecise use of both terms has even been recognized by Borzaga and Galera (2016) in the last report on social enterprise eco-system which was prepared for the European Commission, and an example of the interchangeability of the terms could be how the “Expert Group on Social Entrepreneurship” also called GECES (Groupe d’experts de la Commission sur l’entrepreneuriat social) that was active from 2012 until 2018, have been replaced by “Commission Expert Group on Social Economy and Social Enterprises”. See Stevenson and Jarillo (2007) and works there cited. The European Parliament resolution of 5 July 2018 on a Statute for social and solidarity-based enterprises recognizes the terms “social enterprise” and “solidarity-based enterprise” are often used as synonyms, even though the companies to which they refer represent real situations that do not always coincide. For a compilation of interesting works on social entrepreneurship, see Saiz Álvarez (2016) and Peredo and McLean (2006).

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10



11



12

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According the Academy for Systems Change: it “involves deep shifts in mental models, relationships, and taken-for-granted ways of operating as much as it involves shifts in organizational roles and formal structures, metrics and performance management, and goals and policies”. Detailed information about that Academy is available at https://www.academyforchange.org/ Interesting information about Latin American countries is available at Orejas et al (2016). This research was undertaken in collaboration with the Schwab Foundation for Social Entrepreneurship and the Bertha Centre for Social Innovation & Entrepreneurship, University of Cape Town Graduate School of Business (WEF, 2017). Although these are just six specific cases, the practical learnings about systems change and the reflections raised for social entrepreneurs are of interest.

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Chapter 5

Untangling the InnovativenessPerformance Puzzle Tugba Gurcaylilar-Yenidogan Akdeniz University, Turkey Safak Aksoy Akdeniz University, Turkey

ABSTRACT This chapter investigates the relationships between innovativeness and firm performance from a multidimensional viewpoint. As previous studies have shown controversial results on the performance implications for innovative capacity, the promising venue for the innovation research study is to address the question of under which conditions innovativeness leads to improved financial performance. To this end, the results of this study demonstrate some major findings. First, non-technical innovativeness exerts positive influence over technical innovativeness. Second, novelty of technical innovation activities causes a diminishing effect on financial performance due to the ambiguity of value-creation. Third, technical innovativeness enhances financial performance when the relationship between technical innovativeness and financial performance is mediated by market effectiveness and production efficiency. Overall, this chapter clarifies the conflicting results on the innovativeness-financial performance link and hence contributes to the innovation literature.

INTRODUCTION Innovativeness is an evolving phenomenon of the new economy. Despite the central role of innovation for organizational growth in the knowledge economy, the performance implications of firm innovativeness still remain challenging. Innovative capacity of a firm would undoubtedly support the improvement of overall firm performance. However, empirical research on its performance implications shows controversial results. A large and considerable number of researchers investigating the technical innovativenessperformance relationship (e.g. Centobelli, Cerchione, & Singh, 2019; Cho & Pucik, 2005; Damanpour, Szabat, & Evan, 1989; DeCarolis & Deeds, 1999; Han, Kim, & Srivastava, 1998; Johne & Davies, 2000; DOI: 10.4018/978-1-7998-1169-5.ch005

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 Untangling the Innovativeness-Performance Puzzle

Li & Atuahene-Gima, 2001; Marques & Ferreira, 2009; Pett & Wolff, 2009; Roberts, 1999; Vermeulen, De Jong, & O’Shaughnessy, 2005; Xin, Yeung, & Cheng, 2010) support the positive performance implications. The others (e.g. Freel & Robson, 2004; Heunks, 1998; Moreira, Gherman, & Sousa, 2017) report either negative or statistically insignificant effect of technical innovativeness on performance. These conflicting research results deal exclusively with the unidimensional nature of performance measurement (Rosenbusch, Brinckmann, & Bausch, 2011; Subramanian & Nilakanta, 1996). The financial measures such as return on assets or profitability cannot fully account for all aspects of firm performance. Innovativeness requires extra investments and significant expenditures made in existing production systems, but at the same time potential future returns from the innovations cannot be known precisely since the success of innovation projects depends on the impact of novelties on the areas relevant for production and markets (Mackelprang, Bernardes, Burke, & Welter, 2018; Talay, Akdeniz, & Kirca, 2017). Starting from this gap, the study here aims at investigating the relationships between innovativeness and firm performance from a multidimensional viewpoint and hence answering the question of under which conditions innovativeness leads to improved financial performance. Unlike the previous studies examining direct positive or negative performance implications of innovation practice, this study considers indirect influences of innovativeness as well. For-profit organizations distinguish successful new products from unsuccessful ones due to the financial performance. This performance measure produces a misleading correlation between innovativeness and profitability in the short-run period. During the earlyphase of launching innovation, high capital expenditures for innovations may inevitably cause a negative influence on profitability ratio. The research findings provide evidence for consumer resistance to adopt the innovations in the introduction stage of product life cycle (Ram & Jung, 1991). Then, in correlation with consumer attitude and satisfaction, adoption and repetitive usage of a new product eliminates the negative influence of innovation resistance on profitability. In other words, positive financial outcomes from innovation activities, especially with a great amount of investments in R&D, most likely appear at a saturation point above which an increase in R&D intensity leads to negative returns (Molina-Morales & Expósito-Langa, 2012). Accordingly, this study advocates that firm-level innovativeness creates a positive aggregate impact on financial performance that results from the mediating effects of innovation process outcomes. Innovation process outcomes basically consist of measures for market effectiveness and production efficiency (OECD & Eurostat, 2018). Financial performance would be higher when the bottom line-profitability effect of firm innovativeness is mediated by market effectiveness with potential for value-creation from a revenue generation focus and production efficiency with potential for valuecreation from a cost reduction focus (Subramanian & Nilakanta, 1996). Based on the aforementioned arguments, we expect that firm innovativeness positively affects financial performance, yet that this effect depends on the value-increasing potential of innovation novelty. This study uses quantitative data for SMEs in manufacturing industry. SMEs have a limited availability of resources. The resource scarcity diminishes the organizational capacity to absorb innovation failure and risks. That is why research in such a specific context is more likely to produce more realistic conclusion on performance implications of firm innovativeness. Furthermore, the traditional output (e.g. number of new products and patents, share of sales derived from new products) and input indicators (e.g. R&D intensity, R&D employees, number of R&D alliances) are questionable for assessing the influence of innovativeness skills on the growth of SMEs. For this reason, we adopt the new paradigmatic approach to innovation measurement and evaluate firm innovativeness with a broader systemic nature of innovation including reciprocal relationship between technical and non-technical facets of innovations. The results of this study indicate that technical innovativeness leads to the changes in both “production and delivery” 86

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and “competition, demand and markets” and hence increases financial performance. On the other side, technical innovativeness has a negative direct effect on financial performance due to the ambiguity of value-creation for innovations. In addition to the direct and indirect effects of technological innovations, non-technological innovativeness encourages improvements in technical innovations whereas technical innovations are essential element of firm competitiveness in manufacturing industry. Overall, this study clarifies the conflicting results on the innovativeness-financial performance link and hence contributes to the innovation literature.

Literature Review and Theoretical Framework The technological determinist perspective considers science and technology as the transformation engine in society (Courvisanos, 2006; De Moor, Berte, De Marez, Joseph, Deryckere, & Martens, 2010). That is probably why innovation activities are commonly being perceived to comprise technological innovations. While the traditional rhetoric of industrial society has largely ascribed structural changes to the improvements in technology, innovation success depends on the diffusion of technological innovations (Rogers, 2010). Early adopters or prospectors of technological innovations become catalyst agents for change. In contrast to technological determinism, social constructivism treats technology as existing reality of society (Fritsch, 2011). Social interactions are capable of influencing work organization and management. Thus, new technologies are constructed by structural changes in society. From the constructivist approach, technology development is more user-driven and human-centered. Although both technology approaches emphasize the interaction between technological and social forces, they have been criticized for including a linear sequence of process that splits technology development away from the social innovation system. Then, the alternatives to integrative innovation models (Lundvall, 1988) began to describe technology as an entire system in which both social and technical aspects are interactively employed in enhancing firm performance. According to the contemporary nature of technology in knowledge society, innovation emanates not only from technical but also from social and organizational breakthroughs (Barañano, 2003; Sawhney, OECD & Eurostat, 2018; Wolcott, & Arroniz, 2006). Thus, the coverage of innovation activities is expanded to include a broader spectrum of economically useful knowledge among individuals, social networks, and organizations. On the one hand, technical innovation encompasses product and process innovations; on the other hand, non-technical innovation includes the implementation of new marketing strategies (e.g. significant changes in product design and packaging, product placement, product promotion or pricing) with new organizational methods in the business practices and procedures.

The Relationship Between Technical and Non-Technical Innovativeness The previous studies (Mothe & Uyen Nguyen Thi, 2010; Pereira & Romero, 2013) exemplify that the effect size of non-technical innovativeness on the capacity to innovate in technical activities varies depending on the industry type, but technical aspects of innovativeness steadily increase in higher values of organizational and marketing innovations. Non-technical innovation is an important element of innovation activities that supports the development of technical innovation in high-tech businesses. Therefore, performance-enhancing effect of technical innovativeness will likely to be higher in the conditioning effect of organizational and marketing innovativeness.

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The research stream of organizational change and adaptation has shown that organizational innovations and technical innovations are causally interrelated over consecutive time periods as changes in the social structure lead to changes in the technical system (Damanpour et al., 1989). Organizational innovations are associated with structural characteristics of organizational design. As the first category of organization innovations, the use of management information systems facilitates exploiting external sources of knowledge and hence increases the organizational capacity of a firm to create new knowledge towards technical innovation (Sawyer, Evans, & Bosua, 2014). In addition to the benefits for accessing and disseminating external knowledge, the use of management information systems serves to simplify operational information flows between various combinations of employees and businesses (Lee, 2015). Organizational innovation efforts focus on the effective application of information technology systems and quality management practices and hence improves business processes in production and delivery. As a result, advanced information systems may have a positive correlation with improvements in business processes. The second, designing a more flexible organization structure ensures employee participation in decision making processes (Allen & Henn, 2007). It promotes to better teamwork and faster problem resolution. Thus, highly motivated employees become more creative and productive while looking for the ways to innovate existing business routines and procedures. The third, building external relationships with other firms and institutions exerts a stronger effect to increase the firm’s production capacity rather than the new knowledge and value creation from complementarity resource endowment (Yasuda, 2005). Thus, it mostly relates to exploitative innovation strategy. In this case, external collaboration would necessitate process integration and mutual adjustments in production and delivery schedules. In addition to the correlation between organizational and process innovativeness, the capacity to innovate in marketing activities significantly augments changes and improvements in existing products as the other branch of technical innovativeness (Souder & Song, 1997; Verhees & Meulenberg, 2004). In case engineering design delivers a specific production characteristic that creates more consumer value, the capacity for product innovations can meet the manufacturing development goals (Luchs & Swan, 2011; Michalek, Feinberg, & Papalambros, 2005). The marketing-related managerial decisions such as aesthetical design features, pricing, positioning, and sales channels formalize the basic product configuration in terms of characteristics and functionalities (Tatikonda & Montoya-Weiss, 2001). Thus, discovering new ideas and marketing methods for businesses fosters product innovativeness. As well as major influences of competitors having a proper understanding of customer expectations and preferences guides initiating to product innovation. Thus, we hypothesize a positive relationship between technical and non-technical innovativeness: H1: The higher a firm’s non-technical innovativeness, its capacity to innovate in technical activities will be the higher. H1a: The capacity of a firm to innovate in marketing activities positively correlates with product innovativeness. H1b: The capacity of a firm to innovate in organizational activities positively correlates with process innovativeness.

The Relationship between Technical Innovativeness and Firm Performance Higher innovativeness leads to better financial performance by influencing the different sources of competitive advantage. According to the Oslo Manual (OECD & Eurostat, 2018), innovative firms aim 88

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at gaining superior performance by either shifting the consumer’s demand curve (through increasing product quality and offering new products to existing/new markets) or the firm’s supply curve for a product (through reducing unit costs of production, purchasing, distribution or transaction). This situation points out the indirect positive effects of innovativeness on financial performance. In other words, firms with a higher innovative capacity can gain competitive advantage by lowering costs and/or improving differentiation, which in turn leads to improved financial performance. For instance, innovative new products offer new technical features and functionality that increase the quality and variety of existing product or create totally new areas of application. Market novelties from product innovations are closely linked to superior customer value. This customer-oriented approach positively influences the willingness of customer to adopt a new product and pay for it. Not only market value gains (e.g. higher sales, customer satisfaction, and growth in market share) but also productivity gains (e.g. cost efficiency, quality, flexibility, and speed) may improve overall profitability (Gunday, Ulusoy, Kilic, & Alpkan, 2011; OECD & Eurostat, 2018). Developing new production and delivery methods throughout process innovation activities enhances the efficiency or quality of production and hence leads to improved financial performance. As non-technical innovation stimulates technical innovation (Miller, 2001; Mothe & Uyen Nguyen Thi, 2010; Schmidt & Rammer, 2007), innovators perform better with the revenue generation effect of market novelties and cost reduction effect of production efficiency. Thus, we drive the following hypotheses: H2: Technical aspects of innovativeness have the potential for value-creation in terms of market effectiveness and production efficiency. H2a: Product innovativeness causes a revenue generation effect of market effectiveness. H2b: Process innovativeness causes a cost reduction effect of production efficiency. Previous studies have extensively shown that technical innovativeness impacts firm performance (Bigliardi, 2013). However, empirical studies present mixed findings with respect to the relationship between innovativeness and performance. Some authors (Centobelli et al., 2019; Cho & Pucik, 2005; DeCarolis & Deeds, 1999; Marques & Ferreira, 2009; Li & Atuahene-Gima, 2001; Pett & Wolff, 2009; Roberts, 1999; Xin et al. 2010) demonstrated that technical aspect of innovativeness exerts a positive influence on firm performance. Damanpour et al. (1989) broaden the performance implications of technical innovativeness while emphasizing the role of organizational innovation in facilitating technical innovation. According to their findings, a balanced rate of adoption of organizational and technical innovation positively affects firm performance. Han et al. (1998) exemplified the incentivizing role of market-oriented corporate culture to improve organizational and technical innovativeness. Reciprocal interaction between organizational and technical innovativeness then contributes positively to corporate performance. Johne & Davies (2000) provided further support for performance enhancing effect of marketing innovativeness. The findings of the work by Vermeulen et al. (2005) showed that better innovation performance (i.e. number of new product introductions) is a result of an increase in non-technical innovativeness and there is a positive relationship between new product introductions and performance. However, contradictory evidence was also provided by some others. The findings from the studies of Freel & Robson (2004) revealed a negative relationship between technical innovativeness and growth in sales or productivity for SMEs in manufacturing industry. On the other side, Heunks (1998) found no performance differences between SMEs diverging at novelty degree of product innovations. The finding of this study also showed that process innovativeness tends to stimulate growth and productivity; but the direction of its impact on profitability is still negative. Whereas the development and introduction 89

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of innovations needs to make a significant resource investment, dedicated resources to the innovation process do not always create positive impacts on economic activity due to the consumer resistance to technology adoption. Therefore, the innovation process outcomes characterized by production efficiency and market effectiveness are essential for realizing the success of short-run financial performance. Otherwise, innovativeness would be highly risky since performing innovative technical activities consumes resources and hence causes a diminishing effect on financial performance. Accordingly, we consider technical innovativeness to have indirect effects through product efficiency and market effectiveness as well as its direct effect on financial performance. Although a number of direct and indirect effects may be identified, the other promising venue of the research regards to which type of performance objectives from innovations exerts a stronger impact in enhancing financial performance. Consistent with the diffusion theory of innovation, it may be expected that organizational objectives for competition, demand and markets bring about much superior performance. Thus, we develop following hypotheses: H3: Technical innovativeness undermines financial performance due to the ambiguity of value-creation. H3a: Product innovativeness has a direct and negative impact on financial performance. H3b: Process innovativeness has a direct and negative impact on financial performance. H4: Technical innovativeness causes better financial performance through either the revenue generation effect of market effectiveness or the cost reduction effect of production efficiency. H4a: Product innovativeness causes better financial performance through the revenue generation effect of market effectiveness. H4b: Process innovativeness causes better financial performance through the cost reduction effect of production efficiency. H4c: Rather than the cost reduction effect of production efficiency, the revenue generation effect of market effectiveness leads to much superior financial performance.

RESEARCH METHOD The research study here investigates the performance implications of firm innovativeness. In consistent with the Oslo Manual (OECD & Eurostat, 2018), the methodological approach of this study addresses the indirect effects of firm innovativeness on financial performance through non-financial performance outcomes of innovations. Innovativeness is related with a firm’s capacity to innovate in a broader spectrum of technical and non-technical innovations. Novelty degree of innovations determines firm innovativeness. As well, innovation success depends on the non-financial performance outcomes of innovation process relevant for productivity and market novelties. As described above in detail, this study advocates that production efficiency and market effectiveness have possible mediating effects on the relationship between technical innovativeness and financial performance. To this end, with this study it was aimed at conducting a quantitative research for SMEs in manufacturing industry. The performance implications of innovation in SMEs have currently attracted an increasing interest since the output measures for innovativeness (such as patents and number of new products) cannot be determinative in evaluating corporate performance. In correlation with this, the present study focuses on process measures for innovativeness.

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Sample and Data Collection This study uses a questionnaire-based survey to test the links between innovativeness, financial and nonfinancial measures of performance in SMEs. SMEs, helping to create more employment opportunities for economic and social development, play an important role in the Turkish economy. They constitute over 99 percent of total enterprises and 75 percent of national employment (The Union of Chambers and Commodity Exchanges of Turkey [TOBB], 2019). As well, the SMEs in Turkey account for approximately 56 percent of total production and 50 percent of the total investment. Antalya, known as the Turkish Riviera, is the largest Mediterranean coastal city in Turkey. Although this settlement is one of the most important tourism headquarters of the country and the world, industrial investments are also encouraged to support tourism and agriculture. Industrial investments are made in compliance with the principles of environmental and social sustainability. Hence, manufacturing is especially sensitive to sustainability-oriented innovations. Depending on the innovative potential and innovation-based growth policy, Antalya Organized Industrial District (AOSB) constitutes a suitable research milieu. AOSB operates with 21 sectors and classified them into the eight industrial categories. These categories are metal products, machinery, and energy industry, construction industry, food industry, plastic, polyester and acrylic products, agriculture, fertilizer and chemicals, wood furniture, textiles, and paper and packaging industry. The administrative management of the industrial district supports new innovative initiatives for the production of valueadded products. For this purpose, several efforts were initiated to create an angel network for their startup ecosystem. Apart from this observation, the research population of this study comprised a total of 269 firms operating in the organized industrial district of Antalya/Turkey (Antalya Organized Industrial District [AOSB], 2015). Consistent with the duration constraint for completing this project supported by the regional development fund, the data collection lasted two months with a team of six people in the fall of the year 2015. In the process, the first step was to contact with the managers/executives of the cluster firms via phone. Hence, they were informed about the research intention and requested approval for participation. 183 companies were contacted. 125 of those firms accepted to participate in the research. 10 firms were unwilling to participate and unavailability notification was received by 48 firms due to their heavy workload. Then a survey was conducted through personal interviews, which in turn resulted in an effective response rate of 47%. The data obtained from a particular industrial cluster in Turkey were analyzed with the AMOS (version 16) statistical software supported by SPSS. AMOS software is one of the widely used programs to execute the analysis of structural equation models (Byrne, 2016). Unlike many others before it, this program is also applicable for small samples. Structural equation modelling (SEM) estimates direct and indirect effects within complex causal systems that include multiple interactions between constructs. Methodology of the SEM approach allows to be performed both confirmatory factor analysis (CFA) and multiple regression analysis together. CFA is applied to verify the factor structure as a pattern of correlations within a set of observed variables. This analysis enables to test the hypothesis for model validation. In CFA results, goodness-of-fit indices demonstrate the probability of statistical significance in the relationship between observed variables and their underlying latent constructs. Similarly, model fitting and testing for multiple interaction effects show whether a good fit exists between the overall model and the hypothesized model. As well, the results consist of parameter estimates, standard errors, and test statistics for each parameter in the model.

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Analyses Following the Oslo Manual (OECD & Eurostat, 2018) framework, firm innovativeness was measured using with the four factors of items to capture the extent of which positive changes (/innovations) a firm has been making on new product development activities over the last three years. Whereas the first factor of technical innovativeness with the three items (i.e. the degree of changes in technical product specifications and functional characteristics, ergonomic product design features, components and materials) is product innovativeness, the second factor with the two items encompasses process innovativeness that means significant improvements in production techniques and procedures, and inward & outward logistics methods and procedures. Besides integrating each innovation factor separately, the unification of product and process innovation activities as well as marketing and organizational activities respectively generates a measure instrument for technical and non-technical innovativeness. Marketing innovativeness is measured with a four-item scale including significant changes in product aesthetic design, product packaging, sales channels and product placement methods, product promotion and advertising techniques. The measure for organizational innovativeness includes the amount of change in innovation activities such as business routines and practices, information processing systems, workplace organization with greater employee autonomy in decision making, and managing external relationships. According to the measurement of these constructs, executives were asked to rate firm innovativeness on the value chain activities consisting of production, marketing, and the infrastructure of the firm such as organizational structure and control systems using a 5-point scale ranging from (1) no change, (2) minor improvements, (3) minor but continuous improvements, (4) major/remarkable improvements, (5) radical/transformational improvements. Cronbach’s alpha value for both technical innovativeness (α= 0.72) and non-technical innovativeness (α= 0.81) is well above the recommended threshold level of 0.70. Excluding the process innovativeness, each component of innovativeness has acceptable value of alpha (α ≥ 0.7). The alpha value for process innovativeness is 0.53 that falls in the acceptable range of estimate for reliability (Kline, 2000). Performance outcomes have been listed in the Oslo Manual into the three main categories of incentives that promote innovations. They are relevant for competition, demand and markets, production and delivery, and workplace organization. In this study, we investigated the first two categories of performance to test the effects of non-financial innovation outcomes on financial performance. The first performance category of innovation outcomes comprises competition, demand and markets. In this category of innovation outcomes, new product-development speed, market share growth, opening up new markets, building product visibility and awareness, and so forth are of the criteria for non-financial performance that determines market effectiveness. The latter category of performance outcomes for production and delivery captures improvements in quality, flexibility, and efficiency. The construct for production efficiency consists of organization performance goals such as production costs, volume flexibility of production, production and delivery speed, production quality. In addition to measurement of nonfinancial performance in terms of market effectiveness and production efficiency, financial performance was measured with relative comparisons of financial ratios including return on sales, return on assets, EBITDA margin and cash flow from operating activities. The survey participants identified the average relative performance of the firm compared to its main competitors over the past three years by assessing the measures for product efficiency and market effectiveness on a 7-point Likert scale ranging from much lower than competitors (=1) and equal to competitors (=4) to much higher than competitors (=7). Cronbach’s alpha value is 0.80 for market performance, 0.71 for production performance, and 0.91 for 92

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financial performance. In addition to the reliability test for the two main categories of innovativeness (i.e. technical and non-technical innovativeness) with the performance outcomes for innovations, confirmatory factor analysis (CFA) was conducted. The measures show a good fit of the model (Goodness-of-fit indices are; χ2 = 301.411, df = 257, RMSEA= 0.04, CFI= 0.96, IFI= 0.96, TLI=0.95).

Findings This paper presents a framework model for guiding the systematic investigation of innovation for value creation (see Figure 1). Based on the multifaceted performance outcomes of innovativeness, the overall framework was partitioned into two different layers (see Figure 1a and 1b) including the appropriate coupling of product and marketing innovations at the first stage and of process and organizational innovations at the second stage. So that the recommended mediating effect of performance was tested between financial performance and specific type of technical innovativeness (i.e. market effectiveness for product innovativeness and production efficiency for process innovativeness). The theoretical models were estimated using structural equation modelling with AMOS 16.0. The findings for the overall model show that the hypothesized model provides a good fit to the observed data. The chi-square/degrees of freedom ratio is within the recommended level of 2.00 to 1.00 (χ2 / df = 1.35), indicating an acceptable fit between the hypothetical model and the sample data (Carmines & McIver, 1981). Inconsistent with the goodness-of-fit measure for chi-square statistic, the probability value is significant. However, the chi-square statistic is very sensitive to sample size and hence no longer relied upon as a basis for acceptance or rejection (Vandenberg, 2006). As the multiple model fit indices provide a more holistic view of goodness-of-fit measures, the findings from the research model in this study indicate that the measures of goodness of fit are highly acceptable (RMSEA= 0.04, CFI= 0.96, IFI= 0.96, TLI=0.95). The values for CFI, IFI and TLI indices are of over the 0.9 threshold while RMSEA is within the acceptable level of 0.8, suggesting reasonable fit (Hair, Anderson, Tatham, & Black, 1998). Figure 1.

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Figure 1 summarizes the results of the SEM analysis for the overall research model. Consistent with the prediction of H1, the results indicate that the relationship between non-technical innovativeness and technical innovativeness (β= 0.587, p