Eurasian Economic Perspectives: Proceedings of the 28th Eurasia Business and Economics Society Conference [1st ed.] 9783030485306, 9783030485313

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Eurasian Studies in Business and Economics 15/1 Series Editors: Mehmet Huseyin Bilgin · Hakan Danis

Mehmet Huseyin Bilgin Hakan Danis Ender Demir Uchenna Tony-Okeke  Editors

Eurasian Economic Perspectives Proceedings of the 28th Eurasia Business and Economics Society Conference

Eurasian Studies in Business and Economics 15/1 Series Editors Mehmet Huseyin Bilgin, Istanbul, Turkey Hakan Danis, San Francisco, CA, USA Representing Eurasia Business and Economics Society

More information about this series at http://www.springer.com/series/13544

Mehmet Huseyin Bilgin • Hakan Danis • Ender Demir • Uchenna Tony-Okeke Editors

Eurasian Economic Perspectives Proceedings of the 28th Eurasia Business and Economics Society Conference

Editors Mehmet Huseyin Bilgin Faculty of Political Sciences Istanbul Medeniyet University Istanbul, Turkey Ender Demir Faculty of Tourism Istanbul Medeniyet University Istanbul, Turkey

Hakan Danis MUFG Union Bank San Francisco, CA, USA Uchenna Tony-Okeke School of Economics, Finance and Accounting Coventry University Coventry, UK

The authors of individual papers are responsible for technical, content, and linguistic correctness. ISSN 2364-5067 ISSN 2364-5075 (electronic) Eurasian Studies in Business and Economics ISBN 978-3-030-48530-6 ISBN 978-3-030-48531-3 (eBook) https://doi.org/10.1007/978-3-030-48531-3 © The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG 2020 This work is subject to copyright. All rights are solely and exclusively licenced by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Preface

This is Volume 1—Eurasian Economic Perspectives of the 15th issue of the Springer series Eurasian Studies in Business and Economics, which is the official book series of the Eurasia Business and Economics Society (EBES, www.ebesweb.org). This issue includes selected papers presented at the 28th EBES Conference, which was held on May 29, 30, and 31, 2019, in Coventry, UK. The conference is hosted by the Centre for Financial and Corporate Integrity (CFCI), Coventry University, in collaboration with Coventry Business School Trading Floor. EBES Executive Board selected David B. Audretsch from Indiana University, USA, as the EBES Fellow Award 2019 recipient for his outstanding contribution to the areas of innovation and entrepreneurship. During the conference, David B. Audretsch received the EBES Fellow Award and gave a speech entitled “Entrepreneurship: The Role of Culture.” Moreover, Klaus F. Zimmermann (Editor-inChief, Journal of Population Economics (SSCI)), David B. Audretsch (Editor-inChief, Small Business Economics (SSCI)), Marco Vivarelli (Editor-in-Chief, Eurasian Business Review (SSCI)), and Dorothea Schäfer (Editor-in-Chief, Eurasian Economic Review (Scopus and ESCI)) organized “JOURNAL EDITORS SPECIAL SESSION—How to Publish in WOS Journals?” During the conference, participants had many productive discussions and exchanges that contributed to the success of the conference where 167 papers by 303 colleagues from 46 countries were presented. In addition to publication opportunities in EBES journals (Eurasian Business Review and Eurasian Economic Review, which are also published by Springer), conference participants were given the opportunity to submit their full papers for this issue. Theoretical and empirical papers in the series cover diverse areas of business, economics, and finance from many different countries, providing a valuable opportunity for researchers, professionals, and students to catch up with the most recent studies in a diverse set of fields across many countries and regions. The aim of the EBES conferences is to bring together scientists from business, finance, and economics fields, attract original research papers, and provide them with publication opportunities. Each issue of the Eurasian Studies in Business and v

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Economics covers a wide variety of topics from business and economics and provides empirical results from many different countries and regions that are less investigated in the existing literature. All accepted papers for the issue went through a peer review process and benefited from the comments made during the conference as well. The current issue covers fields such as economics of innovation, finance, macroeconomics, and regional studies. Although the papers in this issue may provide empirical results for a specific county or regions, we believe that the readers would have an opportunity to catch up with the most recent studies in a diverse set of fields across many countries and regions and empirical support for the existing literature. In addition, the findings from these papers could be valid for similar economies or regions. On behalf of the series editors, volume editors, and EBES officers, I would like to thank all presenters, participants, board members, and the keynote speakers, and we are looking forward to seeing you at the upcoming EBES conferences. Istanbul, Turkey

Ender Demir

Eurasia Business and Economics Society (EBES)

EBES is a scholarly association for scholars involved in the practice and study of economics, finance, and business worldwide. EBES was founded in 2008 with the purpose of not only promoting academic research in the field of business and economics but also encouraging the intellectual development of scholars. In spite of the term “Eurasia,” the scope should be understood in its broadest terms as having a global emphasis. EBES aims to bring worldwide researchers and professionals together through organizing conferences and publishing academic journals and increase economics, finance, and business knowledge through academic discussions. Any scholar or professional interested in economics, finance, and business is welcome to attend EBES conferences. Since our first conference in 2009, around 12,011 colleagues from 99 countries have joined our conferences and 6858 academic papers have been presented. EBES has reached 2257 members from 87 countries. Since 2011, EBES has been publishing two journals. One of those journals, Eurasian Business Review (EABR), is in the fields of industrial organization, innovation, and management science, and the other one, Eurasian Economic Review (EAER), is in the fields of applied macroeconomics and finance. Both journals are published quarterly by Springer and indexed in Scopus. In addition, EAER is indexed in the Emerging Sources Citation Index (Clarivate Analytics), and EABR is indexed in the Social Science Citation Index (SSCI) with an impact factor of 2.143 as of 2018. Furthermore, since 2014 Springer has started to publish a new conference proceedings series (Eurasian Studies in Business and Economics) which includes selected papers from the EBES conferences. The 10th, 11th, 12th, 13th, 14th, 15th, 16th, 17th, 18th, 19th, 20th (Vol. 2), and 24th EBES Conference Proceedings have already been accepted for inclusion in the Conference Proceedings Citation Index— Social Science & Humanities (CPCI-SSH). Subsequent conference proceedings are in progress.

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We look forward to seeing you at our forthcoming conferences. We very much welcome your comments and suggestions in order to improve our future events. Our success is only possible with your valuable feedback and support! With my very best wishes, Klaus F. Zimmermann President EBES Executive Board Klaus F. Zimmermann, Central European University, Hungary Jonathan Batten, Universiti Utara Malaysia, Malaysia Iftekhar Hasan, Fordham University, USA Euston Quah, Nanyang Technological University, Singapore John Rust, Georgetown University, USA Dorothea Schafer, German Institute for Economic Research DIW Berlin, Germany Marco Vivarelli, Università Cattolica del Sacro Cuore, Italy EBES Advisory Board Ahmet Faruk Aysan, Istanbul Sehir University, Turkey Michael R. Baye, Kelley School of Business, Indiana University, USA Mohamed Hegazy, The American University in Cairo, Egypt Cheng Hsiao, Department of Economics, University of Southern California, USA Noor Azina Ismail, University of Malaya, Malaysia Irina Ivashkovskaya, State University – Higher School of Economics, Russia Christos Kollias, University of Thessaly, Greece Wolfgang Kürsten, Friedrich Schiller University Jena, Germany William D. Lastrapes, Terry College of Business, University of Georgia, USA Sungho Lee, University of Seoul, South Korea Justin Y. Lin, Peking University, China Brian Lucey, The University of Dublin, Ireland Rita Martenson, School of Business, Economics and Law, Goteborg University, Sweden Steven Ongena, University of Zurich, Switzerland Peter Rangazas, Indiana University-Purdue University Indianapolis, USA Peter Szilagyi, Central European University, Hungary Amine Tarazi, University of Limoges, France Russ Vince, University of Bath, UK Adrian Wilkinson, Griffith University, Australia Naoyuki Yoshino, Keio University, Japan

Eurasia Business and Economics Society (EBES)

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Organizing Committee Klaus F. Zimmermann, PhD, Central European University, Hungary Mehmet Huseyin Bilgin, PhD, Istanbul Medeniyet University, Turkey Hakan Danis, PhD, Union Bank, USA Alina Klonowska, PhD, Cracow University of Economics, Poland Orhun Guldiken, PhD, University of Arkansas, USA Ender Demir, PhD, Istanbul Medeniyet University, Turkey Sofia Vale, PhD, ISCTE Business School, Portugal Jonathan Tan, PhD, Nanyang Technological University, Singapore Ugur Can, EBES, Turkey Reviewers Sagi Akron, PhD, University of Haifa, Israel Ahmet Faruk Aysan, PhD, Istanbul Sehir University, Turkey Mehmet Huseyin Bilgin, PhD, Istanbul Medeniyet University, Turkey Andrzej Cieślik, PhD, University of Warsaw, Poland Hakan Danis, PhD, Union Bank, USA Ender Demir, PhD, Istanbul Medeniyet University, Turkey Oguz Ersan, PhD, Kadir Has University, Turkey Conrado Diego García-Gómez, PhD, Universidad de Valladolid, Spain Giray Gozgor, PhD, Istanbul Medeniyet University, Turkey Orhun Guldiken, University of Arkansas, USA Peter Harris, PhD, New York Institute of Technology, USA Mohamed Hegazy, The American University in Cairo, Egypt Gokhan Karabulut, PhD, Istanbul University, Turkey Christos Kollias, University of Thessaly, Greece Davor Labaš, PhD, University of Zagreb, Croatia Chi Keung Marco Lau, PhD, University of Huddersfield, UK Gregory Lee, PhD, University of the Witwatersrand, South Africa Nidžara Osmanagić-Bedenik, PhD, University of Zagreb, Croatia Euston Quah, PhD, Nanyang Technological University, Singapore Peter Rangazas, PhD, Indiana University-Purdue University Indianapolis, USA Doojin Ryu, PhD, Chung-Ang University, South Korea Uchenna Tony-Okeke, PhD, Coventry University, UK Sofia Vale, PhD, ISCTE Business School, Portugal Manuela Tvaronavičienė, PhD, Vilnius Gediminas Technical University, Lithuania Marco Vivarelli, PhD, Università Cattolica del Sacro Cuore, Italy

Contents

Part I

Economics of Innovation

The Importance of Emerging Industries: The Case of Biopharma . . . . . Cristina Porumboiu The Hiramatsu Concept of “One Village, One Product” as an Element of Regional Industrial Specialization and a Cluster Policy Tool . . . . . . . Anna H. Jankowiak Entrepreneurship, Innovation, and Economic Growth: Evidence from Saudi Arabia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Yusuf Opeyemi Akinwale, Adel Abdullah Alaraifi, and Aljohara Khalid Ababtain Part II

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Finance

The Impact of Capital Structure on Firm Performance and Risk in Finland . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Shab Hundal, Anne Eskola, and Sofiya Lyulyu

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Financial Behavior of Investors: Long-Run Overreaction Phenomenon in Euronext Stock Exchange . . . . . . . . . . . . . . . . . . . . . . . Vilija Aleknevičienė and Inga Aleksandravičiūtė

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New Evidence of the Influence of Post-materialism Orientations on the Financial Markets Mechanisms . . . . . . . . . . . . . . . . . . . . . . . . . . Raluca Simina Bilți

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An Analysis of Working Capital Management Strategy in Small Enterprises Operating Within Group Purchasing Organizations . . . . . . 103 Grzegorz Zimon

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Corporate Governance as a Corporate Social Responsibility Reporting Determinant . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 Triinu Tapver Part III

Macro Economy

Evaluation of the State Strategy of Spatial Development Effectiveness of the Russian Federation: A Cluster Approach . . . . . . . . . . . . . . . . . . . 131 Julia Dubrovskaya, Elena Kozonogova, and Tatiana Pestereva Protection Standards in Bilateral Investment Treaties and Their Contribution in Attracting Foreign Direct Investment . . . . . . . . . . . . . . 141 Argyrios Benteniotis, Vasiliki Delitheou, and Eleftherios Podimatas Part IV

Regional Studies

The European Union as a Platform for the European NGOs’ Operations: Market Versus Democracy . . . . . . . . . . . . . . . . . . . . . . . . . 155 Boguslawa Drelich-Skulska and Malgorzata Domiter The Demand and Supply Analysis and Comparison of Dwellings in Szczecin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 Anna Gdakowicz and Ewa Putek-Szeląg Artificial Intelligence and State Economic Security . . . . . . . . . . . . . . . . . 185 Murat Uzun Assessment of the Features of the Spatial Organization of the Russian Economy Based on the Global and Local Moran Indices . . . . . . 195 Elena Kozonogova and Julia Dubrovskaya

List of Contributors

Aljohara Khalid Ababtain College of Business Administration, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia Yusuf Opeyemi Akinwale College of Business Administration, Abdulrahman Bin Faisal University, Dammam, Saudi Arabia

Imam

Adel Abdullah Alaraifi College of Business Administration, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia Vilija Aleknevičienė Department of Economics and Management, Vytautas Magnus University, Kaunas, Lithuania Inga Aleksandravičiūtė Department of Economics and Management, Vytautas Magnus University, Kaunas, Lithuania Argyrios Benteniotis Department of Economic and Regional Development, Panteion University of Athens, Athens, Greece Raluca Simina Bilți Doctoral School of Economics and Business Administration, West University of Timișoara, Aurel Vlaicu University of Arad, Timișoara, Romania Vasiliki Delitheou Department of Economic and Regional Development, Panteion University of Athens, Athens, Greece Malgorzata Domiter Department of International Economic Relations, Wroclaw University of Economics and Business, Wroclaw, Poland Boguslawa Drelich-Skulska Department of International Economic Relations, Wroclaw University of Economics and Business, Wroclaw, Poland Julia Dubrovskaya Economics and Finances Department, Perm National Research Polytechnic University, Perm, Russia Anne Eskola School of Business, JAMK University of Applied Sciences, Jyväskylä, Finland xiii

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List of Contributors

Anna Gdakowicz Institute of Economics and Finance, University of Szczecin, Szczecin, Poland Shab Hundal School of Business, JAMK University of Applied Sciences, Jyväskylä, Finland Anna H. Jankowiak Department of International Economic Relations, Wroclaw University of Economics and Business, Wrocław, Poland Elena Kozonogova Economics and Finances Department, Perm National Research Polytechnic University, Perm, Russia Sofiya Lyulyu School of Business, JAMK University of Applied Sciences, Jyväskylä, Finland Tatiana Pestereva Economics and Finances Department, Perm National Research Polytechnic University, Perm, Russia Eleftherios Podimatas Department of Economic and Regional Development, Panteion University of Athens, Athens, Greece Cristina Porumboiu Doctoral School of Economics and International Business, Bucharest University of Economic Studies, Bucharest, Romania Ewa Putek-Szeląg Institute of Economics and Finance, University of Szczecin, Szczecin, Poland Triinu Tapver TalTech School of Business and Governance, Tallinn University of Technology, Tallinn, Estonia Murat Uzun Institute of Security Sciences, Turkish National Police Academy, Ankara, Turkey Grzegorz Zimon Faculty of Management, Department of Finance, Banking and Accounting, Rzeszów University of Technology, Rzeszów, Poland

Part I

Economics of Innovation

The Importance of Emerging Industries: The Case of Biopharma Cristina Porumboiu

Abstract The aim of this chapter is to highlight the importance of emerging industries in a continuously changing and globalized world, dominated by constant shifts of consumers’ behavior, when the arising new needs fuel the innovative approach of companies to upgrade their products and services. The interest in these new industries, in fact, traditional industries driven by disruptive ideas, is increasing within the business world in accordance with their high-growth potential, social performances, and innovation. Among the most important emerging business sectors, the biopharmaceutical industry attempts to create a very attractive commitment for increasing people’s lives, through biological substances and biotechnological means, leaving behind the traditional drugs manufactured through chemical substances. Structured in two parts, this study firstly summarizes the stages of industries’ life cycles and the characteristics, challenges, and importance of emerging industries. Secondly, it presents the case of biopharma industry emergence, with a focus on the determinant factors of industry emergence and the sources of competitive advantage of biopharma industry. Keywords Emerging industries · Clusters · Biopharmaceuticals · Life sciences · Competitive advantage

1 Introduction The continuous change of business environment, led by globalization and advancing technological development, represented in the last decades the proper premise for traditional companies to redesign their business models. The results of these shifts bring today millions of jobs, not only to the European labor market (54 million jobs C. Porumboiu (*) Doctoral School of Economics and International Business, Bucharest University of Economic Studies, Bucharest, Romania e-mail: [email protected] © The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG 2020 M. H. Bilgin et al. (eds.), Eurasian Economic Perspectives, Eurasian Studies in Business and Economics 15/1, https://doi.org/10.1007/978-3-030-48531-3_1

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of top 10 emerging industries in Europe) according to European Cluster Observatory (2016), but to the global level as well. Despite the market data scarcity, the attractiveness of the new industries is persistently increasing as a result of high returns compared with the mature industries (Bjørgum 2016) and the social and environment-oriented solutions developed for “the growth and employment of the future” (European Commission 2014). One of the most attractive new industries is derived from the pharmaceuticals, and based on the newest biotechnologies developed, drug manufacturing upgraded to a new level of innovation. Biopharma employed in 2014 more than 2.3 million people in Europe (European Cluster Observatory 2016) and continues to increase in sales with more than 170% worldwide, compared with 2007 (Clarivate Analytics 2018). According to a report of Allied Market Research (2018), the global biopharma market accounted for more than US$186 billion and it is expected to double by 2025. What may be a very significant key element in new industries’ emergence is the abundance of resources in specific locations, as defined by the current literature as clusters (Porter 1980). Starting from the main characteristic of these economic agglomerations as drivers of competitiveness and growth, biopharma industry raised up based on the accumulated knowledge of traditional industry, combined with the advancing biotechnologies. Moreover, the linkages created within the agglomeration’s actors increased the competitiveness of business environment, being supported as well by the governmental agencies, academics, and other institutions. Thus, this chapter enriches the current literature by summarizing not only the main characteristics of the emerging industries as analyzed in different studies in the last decades but focuses on the importance of their connection with other actors within the same geography. Moreover, the theoretical aspects of literature are exemplified with the description of a young industry, of which emergence was less analyzed in accordance with its competitive advantage. In the following, I will bring together the main features of emerging industries as previously analyzed in different papers, in order to highlight the importance of the emerging industries for the world economy, with a focus on biopharmaceutical industry. Structured in two parts, this study firstly summarizes the stages of industries’ life cycles and the characteristics, challenges, and importance of emerging industries. Secondly, it presents the case of biopharma industry emergence, with a focus on the determinant factors of industry emergence and the sources of competitive advantage of biopharma industry.

2 About Emerging Industries Starting from Porter’s (1980, p. 5) definition of industries, as “the group of firms producing products that are close substitutes for each other” and Low and Abrahamson’s (1997) definition of industries evolution, the emerging industries are new industries in the early stages of development, the initial phase of industries’ evolution, as described in the current literature. A more complex definition describes

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the emerging industries as “newly formed or re-formed industries that have been created by technological innovations, shifts in relative cost relationships, emergence of new consumer needs, or other economic and sociological changes that elevate a new product or service to the level of a potentially viable business opportunity.” (Porter 1980, p. 215). Considering that the industries evolve following a “predictable pattern” (Low and Abrahamson 1997), most of the studies conducted in the industries’ emergence unanimously define three evolutionary phases of industries’ lifecycles, despite the difficulty in defining the boundaries of each stage (Phall et al. 2011): emerging, growth, and maturity. However, Gustafsson et al. (2016), based on more than 50 articles used for conducting a systematic review of industries’ emergence, drew a different classification of cycles: the initial stage, the coevolutionary stage, and the growth stage, but underlying similar characteristics of each stage. “The game without rules,” as Porter (1980, p. 215) described this stage of industries, is characterized by lack of information or regulations regarding the products and market. However, this uncertainty may represent a great opportunity for new firms (Gustafsson et al. 2016), which bear a higher risk. Focused mostly on innovation, the firms experience slow growth, due to limited sales. At this phase, the competition within the industry is low, the firms experience slow growth, due to limited sales, being more focused on innovation than on efficiency (Low and Abrahamson 1997). According to Phall et al. (2011), there are two other early stages of industrial evolution before the emerging phase: the “precursor” stage—where the industry emergence is determined by the scientific developments, and the “embryonic” stage—where the scientific developments are transposed into technological prototypes New industries rising importance for the world economy is due to the significant technological upgrade and environmental solutions proposed (European Cluster Observatory 2012), as they involve “exploiting a new source of supply of technology, developing a new product, or tapping a new market” (Low and Abrahamson 1997, p. 443). As human needs continuously change, the emerging industries follow their power (Horii 2011). The European Commission, through its Horizon 2020 strategy, highlights the importance of emerging industries as drivers for “the growth and employment of the future” (European Commission 2013, p. 11), due to the fact that they “will boost industrial competitiveness and underpin future economic growth, jobs, and progress towards a resource-efficient economy”. (European Commission 2013, p. 13). At the European level, the emerging industries accounted in 2016 for about 46% of all traded industry employment and are concentrated in approximative 20% of European locations (European Cluster Observatory 2016). At the European level, the most important ten emerging industries, according to the European Cluster Observatory (2014), based on highest economic growth and overall size are: advanced packaging, biopharmaceuticals, blue growth industries, creative industries, digital industries, environmental industries, experience industries, logistical services, medical devices, and mobility technologies.

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Characteristics of Emerging Industries

Several papers (Low and Abrahamson 1997; Phall et al. 2011; Gustafson et al. 2015; Forbes and Kirsch 2011; Audretsch 2020) highlighted uncertainty as a key characteristic of emerging industries. Porter (1980) went further describing this feature, mentioning in his book the technological uncertainty faced by companies, unable to identify what technology to use or which one is more efficient, and the strategic uncertainty, due to poor or very poor information about competitors, market/industry conditions or customers. The most significant challenges in studying the emerging industries, as identified by Forbes and Kirsch (2011) in their study, are the lack of data for studies and the incapacity to identify these early industries until they become mature. According to the European Cluster Observatory Report (2012), the period of time required for the development of such industry varies between 2 and 50 years in accordance with the business sector. Compared with the mature industries, the potential returns of early stages industries are higher (Bjørgum 2016), despite the slow productivity rates experienced until knowledge accumulation (Horii 2011). As production costs rely on knowledge level of industries (Horii 2011), the emergence of new industries implies high costs for companies due to lack of sectorial experience. Through establishment of entirely new sectors or reshape of traditional ones, costs are strongly influenced by the level of R&D needed by the emerging industries (European Cluster Observatory 2012). Compared with the mature industries that take advantage of past knowledge, emerging sectors can bring innovative solutions for satisfying new needs, substituents of existing companies’ offerings. For covering the high initial costs, the companies belonging to emergent sectors have the same funding opportunities as the mature industries’ companies: governmental financial support through grants and subsidies (especially the industries oriented to social and environmental issues (Porter 1980), traditional financial instruments such as bank loans, overdrafts, credit lines, leasing, or factoring) or alternative and riskier instruments such as crowdfunding, venture capital, mezzanine, and distressed debt) (Seretakis 2012; European Investment Fund 2017). As the new industries become attractive because of innovative and creative solutions offered (European Cluster Observatory 2012), “embryonic companies” (Porter 1980, p. 218) are established. Alongside with them, spin-offs from existing firms join the new industries, combining past knowledge with new technologies. More specific to emerging industries are the academic spin-offs, which ensure the knowledge and technologies transfer from universities/research organizations to the public sector (Czarnitzki et al. 2014). University employees become entrepreneurs and facilitate the translation of academic knowledge to productive knowledge (Fontes 2005), despite the decreasing time and efforts allocated to research activity, following the spin-off (Czarnitzki et al. 2014). New industries arise when existing players change their business model, implementing disruptive ideas, according to European Cluster Observatory Report (2012), mostly in clusters, defined by Porter (1998, p. 216) as “geographically

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proximate group of interconnected companies and associated institutions in a particular field, linked by commonalities and complementarities”. From Ketels and Memedovic’s perspective (2008), three pillars are important to consider for clusters’ definition, such as (a) geography—proximity of firms, concentrated in a region, (b) value creation—interconnected different industries, and (c) business environment—influences of networks. Alongside with the collaboration benefits of networks, companies gain support for dealing with industry’s specific uncertainties (Rong et al. 2013).

2.2

Challenges of Emerging Industries

More than taking advantage of past experiences and resource agglomerations, emerging industries are facing a series of challenges for their development, starting from raw materials, initial costs, infrastructure, and customers’ confidence. Based on Porter (1980), the development of the early stages industries enhances the following problems: • Obtaining the needed raw materials may be a severe problem for emerging industries’ products in order to satisfy the new needs, or if new specialized suppliers are not established. • Alongside with the high initial investments necessary for companies’ establishment in the new industries (Horii 2011), the scarcity of raw material provides is another financial challenge faced by players. • Even if some emerging industries are reformed traditional sectors, shifted through innovative solutions, they still encounter problems while establishing the production infrastructure, depending on industry’s specificity (Russo 2003). • Despite the substituent innovative products release on the market by companies belonging to newly emergent sectors, the increasing large of similar products results in confused customers, uncertain about products’ quality. Due to technological uncertainty, customers can decide to postpone buying products, especially if they know about the features of the next product generation (Porter 1980). • Low confidence of financial institutions for obtaining loans is another problem of emergent sectors mostly due to its specific uncertainty, unless they are recognized as exceptions as it was the case of minicomputers and data transmission (Porter 1980). However, this challenge is also faced by start-ups that do not have enough assets to use as collaterals for bank loans (European Savings and Retail Banking Group 2016). • Depending on the connections of emergent sectors with their “parent-industries,” companies are facing prolonged regulatory approvals, with negative effects over their growth possibilities.

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3 Emergence of Biopharma Industry Biopharmaceuticals refer to pharmaceuticals (medicinal products, therapeutics, prophylactics, and in vivo diagnostics) with active agents inherently biological in nature and manufactured using biotechnologies (Rader 2008). Figure 1 presented the most important levels in biopharma’s emergence.

4 Sources of Competitive Advantage of Biopharma Industry In order to assess the quality of the business environment and the sources of competitive advantage of the biopharmaceutical industry it is required an analysis of Porter’s Diamond Model (1990). Originally designed for identifying nation’s competitive advantage, the model can be also used for industries’ analysis. According to the Porter’s model, the determinant forces of life sciences’ competitive advantage are as follows: (a) Factor conditions—It refers to the business inputs such as human resources, capital, and infrastructure, necessary for assuring industries’ efficiency, quality, and specialization. As identified by several studies (Birch 2017; Decarolis and Deeds 1999; Kleyn et al. 2007), the main source of competitive advantage of the whole life sciences including pharmaceutical and its subsector of biopharmaceuticals, healthcare, medical devices, and biotechnology, is the accumulated knowledge (Birch 2017; Decarolis and Deeds 1999; Kleyn et al.

19th century: emergence of pharmaceuticals 1976: emergence of biotechnology (establishment of the first biotech company Genentech) 1982: First biopharmaceutical product – Humulin (recombinant human insulin), developed by Genentech Early 1980s: emergence of biopharmaceuticals based on development of biotechnology Late 1980s: emergence of biopharmaceuticals based on shifts in production lines of big industry players.

Fig. 1 The history of biopharma industry. Source: Author’s own study, based on Jong (2006) and Jagschies et al. (2007)

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2007), therefore the high specializations of human resources and technologies developed are the most important industry’s inputs. Biopharma industry is also characterized by high skilled researchers and employees, 7 out of 15 largest universities specialized in pharmaceuticals and other life sciences are as well ranked in the top 10 universities worldwide in 2019, according to QS World University Ranking (2019). The increased innovation power of the pharmaceutical industries, also transferable to biopharma, associated with technological developments used in research and development activities and great results, is another factor that supported the emergence of this business sector. According to the Clarivate’s State of Innovation Report (2018), both biotechnologies and pharmaceuticals subsectors registered an increase of innovation of 22%, and 20%, respectively, for the period 2015–2016—only food, beverage and tobacco, and cosmetics and well-being sectors were more innovative. Not only technology and high-skilled employees are essential for industry’s development, but also the capital dedicated to research and development. (b) Demand conditions of the whole life sciences industry refer to the necessity of anticipating and satisfying current and future healthcare challenges, such as life expectancy, fertility, mortal disease such as cancer and prevention solutions for other diseases. Moreover, these requests are backed by United Nations’ (2017) forecasts of an increasing world population to 9.8 billion by 2050 and 11.2 billion by 2100. Therefore, the quality of living proportionally depends on the solutions developed by life sciences companies; so biopharmaceuticals remain in charge to improve existing antibiotics and cancer treatment in parallel with research of resisting bacteria (Clarivate Analytics 2018). (c) Related and Supporting Industries. Presence of local suppliers is another determinant factor for competitive advantage because they can deliver efficient, rapid, and customized inputs. Being close located, both companies and suppliers evolve through exchange of information and upgrading infrastructure due to the changing needs of the customers. Biopharma is mainly supported by the following industries: • Chemicals—The raw material supplier for the pharmaceuticals, the chemical developments enhance the development of new or existing drugs, therefore the innovation pace of this sector is reflected in the growth of the other one. • IT—Biopharma’ development would not be possible without the technological developments of the past decades and definitely the future drugs, devices, and healthcare services will improve people’s welfare based on the Internet of medical things (Deloitte 2019). • Logistics—As drugs need to be transported in specific conditions such as temperature, light, humidity, and the storage and transportation services are very important for the biopharma’ activities. • Packaging—With the same importance as for the logistics, the packaging used for drugs are required to maintain the products’ quality from the production factory to patients.

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(d) Context for Firm Strategy, Structure, and Rivalry for the pharmaceuticals mainly consider the high regulations over the industry and tax incentives. The commercialization of drugs is conditioned by the approval of the regional bodies such as the European Medicines Agency (for the European Union), the Food and Drug Administration (for the United States), or of the national divisions of Health Ministry such as the Japanese Pharmaceuticals and Medical Devices Agency (for Japan). More than regulating the market, the institutions aforementioned spur the industry’s rivalry through support for innovation (Food and Drug Administration 2019). Following the large period of time dedicated to research and development, the pharmaceuticals, are required to wait up to 2 more years for being launched on the market, according to a report of KPMG (2018). At the European Union level, there are four types of procedures, centralized and decentralized which allow companies to distribute drugs at the national or regional market. Regarding the tax regimes, the US authorities are trying to incentivize the whole pharmaceuticals industry through research and development tax credits. An example of such financial support is the Orphan drug credit—a loan facility in amount of 50% of companies’ expenses for qualified clinical tests. Other countries are following the American model and offer refundable or nonrefundable tax credits (Australia, Canada, China, India, and the United Kingdom) or extra deduction tax levels up to 130% in the United Kingdom or 150% in China according to an analysis of EY Tax Insights (2019).

5 Conclusion Considering the accumulated knowledge of traditional industries, alongside the technological upgrades in accordance with the newest solutions and, in the last, but not the least, the agglomerations of resources, the emerging industries reshape the global economic world in its fourth industrial revolution. The importance of redesigned industries is increasing for the world economy, not only for the new solutions developed or high financial returns, but mostly for satisfying the changing needs of customers. In particular, the newly emerged sub-industry of biopharmaceuticals targets healthcare improvements in cancer treatment and other resistant bacteria. As emphasized by this study, despite the tough challenges initially faced, the early developed business sectors have great premises for their development. The case of biopharmaceuticals is even more interesting due to the monitoring and approving constraints. Nonetheless, based on the sources of competitive advantage of biopharma companies and forecasted results, we can conclude that this industry’s development will significantly improve the quality of life through new products.

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Acknowledgments This paper was co-financed by The Bucharest University of Economic Studies during the PhD program.

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The Hiramatsu Concept of “One Village, One Product” as an Element of Regional Industrial Specialization and a Cluster Policy Tool Anna H. Jankowiak

Abstract OVOP (“one village, one product”) can be interpreted as an early phase of creating clusters, bearing in mind the differences and similarities between these two phenomena. The chapter aims to present the development of the Hiramatsu concept by including the developing countries alongside developed countries in the existing model and to evaluate the concept implementation possibilities for the development of regional industrial specializations and cluster policies. The chapter presents three research questions: (RQ1) may the Hiramatsu concept be used in the developing countries?, (RQ2) can the one village, one product model foster the development of regional industrial specializations? and (RQ3) can the Hiramatsu concept be a tool of model cluster policy? As a result of the research conducted in the chapter, it can be concluded that the Hiramatsu concept can be implemented in the developed and developing economies as an element of regional policy, wherever there is a large concentration of industry. This concept can also be a useful executive tool in cluster policy. Keywords One village · One product · Clusters · Regional development · Cluster policy

1 Introduction The concept of “one village, one product” (OVOP) was created in Japan in 1979 by M. Hiramatsu, the governor of Oita prefecture. It is an innovative concept that fits in with the regional development policy, which assumes that competitive products are identified in selected regions, and thus, local brands are created. These products are then produced and sold on a massive scale, which, in simplified terms, translates into A. H. Jankowiak (*) Department of International Economic Relations, Wroclaw University of Economics and Business, Wrocław, Poland e-mail: [email protected] © The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG 2020 M. H. Bilgin et al. (eds.), Eurasian Economic Perspectives, Eurasian Studies in Business and Economics 15/1, https://doi.org/10.1007/978-3-030-48531-3_2

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regional development. For the research carried out in the chapter, it is essential that this concept was created and has been implemented in a highly developed country, but was partly used in other Asian, African, and South American developing countries. OVOP can be interpreted as an early phase of creating clusters, bearing in mind the differences and similarities between these two phenomena. Therefore, it seems interesting to incorporate OVOP into the concept of cluster policy as a tool necessary for the development of regional industrial specialization. OVOP is aiming at the local community to create at least one marketable product originating from their local resources as part of endogenous development. The chapter aims to present the development of the Hiramatsu concept by including the developing countries alongside developed countries in the existing model and to evaluate the concept implementation possibilities for the development of regional industrial specializations and cluster policies. The chapter presents three research hypotheses: (H1) the Hiramatsu concept may be used in the developing countries, (H2) the one village, one product model, can foster the development of regional industrial specializations, and (H3) the Hiramatsu concept can be a tool of model cluster policy. The author relies on the elements of the comparative method and systemic analysis. The OVOP concept has not been widely discussed in the literature, and no large-scale studies have been carried out so far. Such research has been mainly conducted by Yoshimura (2004), Hayashi (2007), and Kurokawa (2008). Therefore, it can be assumed that there is an extensive research gap and the potential to explore this topic. At the same time, the issue is up to date when the Hiramatsu concept is incorporated into the subject of regional development and cluster policy. The chapter is divided into four parts. The first part presents the theoretical background of the Hiramatsu concept. In the second part, the author presented OVOP in Japan and other countries that decided to implement the idea in their own economies. The third part explains OVOP as an element of the development of the regional specialization and the last part is the essential part of the chapter where the comparison of OVOP and clusters is presented.

2 The Hiramatsu Concept: Theoretical Approach OVOP concept was presented for the first time in 1979, but its origins should be traced back in the early 1960s. In the low-industrial region of Oita prefecture, in a Japanese town Oyama, the president of the Oyama agricultural cooperative—H. Yahata—proposed a policy of changing the cultivation of agricultural products in the region. This approach represented the strategy of transition from the traditional agricultural product, which was rice in this region in order to diversify the agricultural production. Initially, the production of plums and chestnuts was planned, but later also high-grade mushrooms and herbs as well as a variety of processed agricultural products (Natsuda et al. 2011). Rice production in the region was not profitable and productive, which was associated with unfavorable geographic shape

The Hiramatsu Concept of “One Village, One Product” as an Element of Regional. . .

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and the associated process of the outflow of labor. The choice of plums and chestnuts was not accidental, because they occurred naturally in the region, and the specialization in their production allowed to use available production advantages. It also contributed to the economic and demographic stability of the region. Farmers from Oyama also started to produce food from plums and chestnuts (e.g., wines and pickles), thanks to which they obtained higher profits from their production. Also nowadays, the Oyama region is one of the more dynamically developing regions in Japan. Yahata’s concept became the inspiration and foundation for the creation of One Village One Product in 1979. The creator of the expanded concept was M. Hiramatsu, the then governor of the Oita prefecture, who introduced his vision in all the cities of the prefecture. Each of the cities based its production on a specific product characteristic for this city, which allowed for more effective use of local resources and the inclusion of a significant number of workforce and local entrepreneurship into the specialization. It can, therefore, be pointed out that the Hiramatsu concept is a unique approach to local development by local specialization, and the basis of success for local entities is to become independent from the actions of national authorities. Before the introduction of OVOP in the Oita prefecture, the economic development of the region, like most regions in Japan during this period, was heavily dependent on the funds received from the central government and investments of large Japanese corporations. After strengthening the local potential and joining forces, economic development was closely related to the situation in a given region. Yoshimura (2004) stresses that the most important task for sustainable regional development efforts (including OVOP concept) is to promote community-oriented economic and industrial policies by utilizing local resources (including nature, culture, and history). Hayashi (2007) highlights the importance of the communityoriented nature of any regional development policy, and he connected it with the importance of agglomeration, clustering, and an innovative environment. Igusa (2008) presents the view that the Japanese model applies to Asian countries and according to Kurokawa (2008), the OVOP movement as a development policy for developing countries. Stenning and Koichi (2008) emphasizes the networking activities as a critical feature of the OVOP idea, Yamagami (2006) claims that the reason of the success OVOP lives in the diversity and Okura (2007) notices the importance of continuous support from local governments (Kurokawa et al. 2010). The classic understanding of OVOP concept is built on three principles, as follows (Kurokawa et al. 2008): thinking globally, act locally—with distinct local flavors and cultures, and people in the regions create a product, which can be sold locally and internationally; self-reliance and creativity—it is up to the local people to decide which products they can and want to produce; human resources development—to foster visionary local leaders and challenging local spirit. According to Ueda (2009), the OVOP concept can be characterized by the following assumptions: flexible support structure—to support any producer groups such as cooperatives, self-help groups, and enterprises in the region; a platform for collaboration—collaboration with existing support programs/projects of the government and NGOs; development of social economy—social and economic benefits

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leading to solidarity in the community; promotion of social participation—encourages contacts with people outside of their local groups such as consumers and traders, leading to self-confidence, and empowerment; utilization of local strengths—add value to local resources, skills, ideas, tradition, scenery, and historical monuments. According to Oita International Exchange Promotion Committee (2019), the OVOP movement was proposed to: prevent depopulation and loss of energy in the Oita prefecture; find and nurture products/industries that could best represent and benefit the region; eradicate heavy dependency upon government, and to promote autonomy and entrepreneurship among regional people. The following OVOP features that have contributed to the success of this concept can be indicated: changes in the division of labor by including residents in the production process; increasing specialization in a given region; stimulating local entrepreneurship by including a growing group of residents in the labor market; raising the quality of the workforce in the region by including it in the production process of goods and providing specialized services; effective use of local factors of production and resources through constant monitoring of the results of local production and continuous improvement of processes; expansion of local infrastructure through the construction of necessary roads, bridges, sewers, power lines, etc.; new jobs both in the production of local goods as well as in their distribution or marketing; development of the local market by increasing the scale of sales and exports from the region; strengthening regional authority units by putting into their hands tools to support and manage local resources. In conclusion, it can be stated that OVOP is not just a concept of regional development in the sense of the economic development of a given region, but it contributes to increasing the human resources in the district.

3 OVOP in Japan and Other Imitating Countries The Hiramatsu concept has become extremely popular in Japan. First of all, this popularity resulted from its effectiveness in improving economic development in the region, and secondly, Hiramatsu was firmly committed to promoting the concept. He gave interviews, travelled around the country to promote ideas, and offered training for local managers and leaders. The presented Hiramatsu concept has become so important in Japan that since its implementation, each province in Japan has been developing unique products under the local brands. The following examples of products that are the subject of OVOP in Japan can be enumerated: (1) Products: Chicken rice ball, Oita city, Oita prefecture; (2) Products: Homemade winner without any artificial additives, Takeda city, Oita prefecture; (3) Products: Common mackerel, and horse mackerel (Seki-aji and Sekisaba) Oita prefecture; (4) Products: Karintou (snack fried sugar-coated dough) Hita city, Oita prefecture; (5) Products: “Dangojiru” (healthy traditional local noodle with a variety of vegetables) Oita prefecture.

The Hiramatsu Concept of “One Village, One Product” as an Element of Regional. . .

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The interest in OVOP and its recognition outside of Japan starts in the early 1980s. OVOP movement is currently implemented in many countries and regions of the world, becoming an effective element of development policy. Countries that have introduced the Hiramatsu concept include Thailand, Vietnam, Korea, China, Cambodia, the Philippines, Indonesia, and the United States. This movement is currently accessible in Africa, where OVOP can be observed in 12 countries (Kenya, Ethiopia, Mozambique, Uganda, Tanzania, Nigeria, Zambia, Madagascar, South Africa, Senegal, Ghana, and Malawi). However, the Hiramatsu concept has many modifications, which also manifests itself in the different nomenclature used in particular regions: One Factory One Product (Shanghai, China), One City One Product (Shanghai, China), One District One Product (Shanghai, China), One Village One Treasure (Wuhan, China), One Town One Product (Jiangsu, China), One Capital One Product (Jiangsu, China), One Barangay One Product (The Philippines), One Region One Vision (The Philippines), Satu Kampung Satu Produk Movement (Malaysia), Back to Village (East Java, Indonesia), One Tambon One Product Movement (Thailand), One Village One Product Movement (Cambodia), Neuang Muang Neuang Phalittaphan Movement (Laos), Neg Bag Neg Shildeg Buteegdekhuun (Mongolia), One Village One Product Day (Los Angeles, USA), and One Parish One Product Movement (Louisiana, USA) (Kalia 2015). It should be noted that the initiatives mentioned earlier are variations of OVOP. Although they usually meet a similar objective of regional development, they are conducted differently. Differences are mainly manifested in the way of initiating an institutional service of the program in different countries. The administration of the OVOP process in Japan is not exercised by a national authority, but by the regional or even private sector. Initially, in Oita prefecture, the coordination of the process was taken over by the local authority called OVOP Promotion Council, but in time it was replaced by Oita International Exchange Promotion Committee. At the foundation of such OVOP institutionalization is the assumption that people should be the initiators of changes in the region and be able to influence the regional situation instead of expecting benefits coming down from the government. The way of traffic management differs OVOP implemented in Japan from other versions of it used in other countries, such as in Thailand and Malaysia, where both the initiator of the program and its contractor are the authority from the national level. The time horizon is also different because, in Japan, it is treated as an indefinite movement, but in other countries, programs are usually closed and run in the form of forwarding plans, e.g., 3–5 years. It is related to the effects of the program, which in the Japanese model are of a long-term nature, and in other countries, faster-expected effects are awaited, which is related to the control of individual OVOP plans. In Japan, products that are the subject of the OVOP idea are most often targeted at meeting local and national needs, while, for example, in Thailand, they are also intended for the international market. According to the hypotheses set out in the introduction to the article, it should be stated that the Hiramatsu concept may form the basis for creating similar projects in developing countries, but the concept model will be diversified. It results mainly from diversified development policy objectives implemented in individual countries as well as equipment and availability of resources.

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4 OVOP as an Element of Development of the Regional Specialization The concept is a part of local development policy, and it can become a well-known rural development model of regional revitalization policy (Savitri 2008). The Hiramatsu concept is part of the regional development strategy, but according to its assumptions, it was to be complementary to other activities carried out by local authorities. OVOP has a strictly local character and can be seen as a bottom-up initiative. It is controlled only in the initial stages of its development, later to give it the lead of the local labor force and business leaders. In the aspect of administering OVOP activities, in principle, it should not be supervised by any national authority, and the role of the leader in the enterprise can be played by private capital. The local authority can support actions, but it does not have to be a leader or initiator. OVOP, therefore, can be called a process-oriented policy involving many actors. According to Igusa (2008), OVOP movement has specific relations with local government, which can be described as follows and divided into three phases: 1. In the initial phase: Local government directly called for the grass-roots leaders to take the initiative of movement; who then asked the local people to find at least one product in each town that can be commercialized; after that, the movement was propagated by media. 2. In the product development phase: Prefectural government propagate OVOP products in the global market; and create a group of local researcher to technical support for product development. 3. In the production phase: Special trainings were offered to regional and industrial leaders; and effective channels of distribution and marketing of OVOP products were created and used. The role of regional authority in shaping OVOP movement is limited to supporting functions, sometimes initiating but never dominant. The leaders are always local entrepreneurs, supported by the authority in the field of consulting, marketing, training, infrastructure, etc. (Fig. 1). It can, therefore, be concluded that OVOP is created using the bottom-up method with the support of local authorities. It is an element identical with the emergence of clusters in given regions, which mostly operate effectively if they are a consequence of using a bottom-up method in their creation. OVOP, as a bottom-up movement, directly contributes to increasing local specialization in a specific production. Products under OVOP are selected based on local resources and skills possessed by the local community. Therefore, they are not solutions imposed by the central authority, which often does not know the specific conditions of the local market. In principle, residents are the party initiating the selection of products for production, guided by the best of their interests. In the Japanese OVOP concept, products made as part of this movement meet the needs of local and national recipients so that they have a sense of serving the whole community. The introduction of the OVOP initiative allows the deepening of regional

The Hiramatsu Concept of “One Village, One Product” as an Element of Regional. . .

Local resources

Products

Local brands

More income

Selfconfidence

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Economic development

(Local) Goverment • • • • • •

Awareness raising & promotion (e.g. award schemes) Train local leaders Marketing support R & D and technical support Supporting equipments & facilities Simplifying regulations, etc.

Fig. 1 The role of local government in OVOP by Ueda. Source: Ueda (2009)

specialization, both in the form of product specialization and specialist skills used by the local workforce. However, within the OVOP, specialization encounters certain development barriers, as it is based only on regional resources that exist in a limited size. Hence, there is an excessive exploitation of regional resources, which may adversely affect the region’s economy in a long time.

5 OVOP and Clusters and Cluster Policy The OVOP concept aims at helping enterprises in a region to focus on a product or industry which is unique to that area. The OVOP institution is working with the companies or individual producers to make their products more competitive in local and national markets. The essential tools are financial support, technology support, specialized skills or services providing, building the network focused on a common goal, etc. The OVOP movement encourages the activities of local human, material, and cultural resources to create value-added to customers and the region. The assumptions mentioned above of the OVOP concept coincide with the definition of clusters, and therefore, they can be treated as a very early phase of the existence of regional clusters. According to the assumptions, clusters are entities associating at least three groups of entities, and these are enterprises (micro, small and medium and

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Table 1 Similarities and differences between OVOP and clusters Initiator Method of creation

Product

Knowledge The role of government Cooperate work Use of resources The scale of action Institutional support

OVOP Local manufacturers and entrepreneurs Bottom-up

Clusters Companies or government Bottom-up or top-down (the majority of clusters are created by bottom-up initiative, but there are some examples for clusters created by government entities) Traditional and modern with a high degree of technological advancement

Traditional, unique, with a lower level of technological advancement Mutual learning from associated entities Supporting

Initiating and supporting

Marketing, sales, and supply

Marketing, sales, and supply

Only local resources

Local and imported to the region

Local and national time

Local, regional, national, and international

Appointed initiative coordinator

An appointed cluster manager

Mutual learning from associated entities

Source: Author’s own work

large units being transnational corporations), units supplying knowledge to the cluster (universities, technology parks, specialized laboratories) and representatives of local authorities supporting the activity of clusters. There are many similarities and differences between the two concepts that are presented in Table 1. The identical factor is the flow of knowledge both between enterprises associated with the cluster and between OVOP participants (Fig. 2). Mutual learning from the business partners, suppliers, and customers positively influences the shaping of new technologies and products or their more efficient use. Entities within OVOP are usually one production chain, while cluster entities do not have to be interconnected with production but, for example, technologically. Please note that the flow of knowledge and mutual improvement is an essential factor in OVOP, but it is crucial for the existence and development of clusters. Marshall noticed positive aspects of the existence of interconnections in one industrial district in the following three areas—the benefits of knowledge and information transfer between companies; the benefits of specialization allowing to achieve a high level of competence in given production; and the benefits of a geographic consolidation of the labor market resulting in the attraction of skilled workers to the region. Production in OVOP is based on unique products and services characteristic for a given community, usually on a small scale due to insufficient resources of local production factors. However, the scale of clusters is larger. It is based on production factors present in the cluster’s existence, but it can be strengthened by capital and

The Hiramatsu Concept of “One Village, One Product” as an Element of Regional. . .

Trade fairs, exhibitons

Learning from others

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Buyers/ Consumers

OVOP Sellers

Finance

Processing Book-keeping Costing Marketing

Technology and Skills

Buyers

Management know/how

Learning from others R&D

Consumers

UNITS

Sellers

Finance

CLUSTER

Technology and Skills

Buyers

Management know/how

Fig. 2 Knowledge flow in OVOP and in cluster. Source: Author’s own work based on Murayama (2012).

employees coming to the region with the emergence of the cluster. Both OVOP and clusters can be a contributing factor raising the attractiveness of a given location for specialized employees and new companies, although this is more common in the case of clusters than OVOP. The existence of production under the OVOP initiative may contribute to the region’s development also in the form of new jobs and new technologies. Tasks implemented by local and central authorities within the framework of the OVOP movement, which was presented in the previous paragraph of the chapter, are

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also the same as the tasks facing the cluster policy implemented by particular countries in the global economy. Cluster policy can be defined as obligations and actions of state or local authorities aiming to provide support to existing clusters, or create favorable conditions for the creation of new clusters. However, there is a problem in clearly defining the cluster policy, which may be the result of difficulties in separating the cluster policy from other policies carried out in a given national economy (Boekholt and Thuriaux 1999; Raines 2003). One can, therefore, formulate the thesis that OVOP should become an element of cluster policy, or broadly understood development policy, which cluster policy is a part of. Similar tools used in the two discussed cases are primarily those related to financial support. These tools are undoubtedly the easiest to use by the authorities, but on the other hand, they are also most desirable by supported entities. It can be assumed that the most critical role of the government in OVOP as well as in clusters is the role of the initiator who, through its activity, will connect entities from the region around one initiative, especially in the first stage of the initiative’s development. The authorities should look for resources in the region in the form of entrepreneurs and companies that can naturally interact with each other and contribute to economic development. In the next stage, when the production or provision of services is already an ongoing process, the role of government should be focused on supporting the organization in this process, providing specialized analytical and advisory services, market research, and marketing. At this stage, the role of the authority is to support entities, inform and make new businesses aware of the existence of these initiatives and effectively advertise the manufactured products. Therefore, this leads to a conclusion that there are many similarities both in the OVOP clusters and the OVOP movement itself and in the role of governmental institutions in both initiatives. OVOP are, by definition, strictly local initiatives with a small scale of activity and therefore they can become the first (or actually zero) stage in the process of creating clusters in the region. OVOP task may be to help to diagnose and search for local products and necessary resources, which may become, with appropriate support, the driving force of the economic and social development. When the foundations emerge in the form of starting (or at least choosing) regional production, it can naturally evolve into a cluster, i.e., expand both in quantity and in quality. The scale of production, the scale of impact, the number of affiliated entities, their type may increase (may include new entities such as universities), and local and national authorities will be more involved. Undoubtedly, the nature of OVOP will change, and they will become definitively more similar to clusters, but they will constitute an element increasing the attractiveness and competitiveness of entities in the region and the entire region.

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6 Conclusion The Hiramatsu OVOP concept, initially created for the needs of the local economy in the Japanese prefecture, has become the basis for regional development, both in economic and in social terms in many countries around the world. It is reasonable to assume that the movement discussed may develop irrespective of the level of economic development of the country in which the region is located. This is possible because OVOP is a bottom-up, regional initiative closely related to the situation in the region and not in the national economy. Therefore, the Hiramatsu concept applies to both developed and developing countries. OVOP movement, thanks to the use of local resources in an extremely effective manner, contributes to the deepening of regional specialization most often in the form of a local product or service. OVOP production involves entire local community, both the resources of the workforce as well as its skills and the leadership skills. On the one hand, it is a positive phenomenon, because it affects the development of the region and improves the quality of life of local communities, but on the other hand, is a barrier to further development. Local resources are limited to some extent, and if there is no inflow of resources from outside of the region, the production will not develop. If, on the other hand, external resources are introduced, a situation may arise that the identity and product associated with the OVOP movement will be lost. Based on the assumptions related to clusters and OVOP presented in the article, it is justified to conclude that they are identical phenomena, similarly pursuing goals, although these goals are diverse. OVOP arises as a natural consequence of the existence of a specific production or products in a given region, and in the majority of cases, the scale of operations remains local, the aim is the development of the local community, its human resources and economic progress. Clusters, on the other hand, are not always the result of historical regional production (although sometimes they are the consequence of equipping the region with specific production factors1), the scale of activity is national or global, and the goal is the economic development of affiliated enterprises, and consequently, the region in which they operate. The linking feature, however, is a collaboration, exchange of best practices, knowledge, and technology, cooperation, which would not be possible in isolation from other entrepreneurs in the region and synergies that provide constant cooperation. Finally, there are reasonable grounds to conclude that the OVOP movement may become the basis for the emergence of regional clusters, and at the same time, the initiative may be included in the broadly understood cluster policy. Acknowledgments The paper is a part of a research project financed by the National Science Centre, Poland, no. 2018/02/X/HS4/02806.

1 The most commonly known cluster in the global economy is the Silicon Valley, which was established in a given territory, because of the fact that region is equipped with silicon.

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References Boekholt, P., & Thuriaux, B. (1999). Public policies to facilitate clusters: Background, rationale and policy practices in international perspective. In T. Roelandt & P. den Hertog (Eds.), Boosting innovation: The cluster approach (pp. 381–412). Paris: OECD. Hayashi, K. (2007). Nihon no chiikikaihatsu no keiken to kaihatsutojoukoku: Hirakareta chiikikaihatsu o mezasite messeeji tosite nani o tsutaeruka [Regional development in Japan and Developing courtiers: Toward the open minded regional development policy, what kinds of message can we transmit?] Bunkyo daigaku kokusaigakubu kiyou, 18(1). Igusa, K. (2008). The problem of the regional revitalization in Asia and One Village One Productadaptability of Oita model to Asian countries. Journal of OVOP Policy, 1, 5–19. Kalia, S. (Ed.). (2015). Promoting socio-economic development through business integration. Hershey, PA: IGI. Kurokawa, K., Tembo, F., & Velde, D. W. (2008). Donor support to private sector development in sub-Saharan Africa. Understanding the Japanese OVOP programme. JICA - ODI Working Paper, 290, 1–48. Kurokawa, K., Tembo, F., & Velde, D. W. (2010, June). Challenge for the OVOP movement in Sub-Saharan Africa―Insights from Malawi, Japan and Thailand (JICA Research Institute Working Papers, No. 18) (pp. 1–42). Murayama, H. (Ed.) 2012. Significance of the Regional One-Product Policy-How to use the OVOP/ OTOP movements. The Policy Science Association of Ritsumeikan University. Natsuda, K., Igusa, K., Wiboonpongse, A., Cheamuangphan, A., Shingkharat, S., & Thoburn, J. (2011). One Village One Product—Rural development strategy in Asia: The case of OTOP in Thailand (Ritsumeikan Center for Asia Pacific Studies Working Paper, No. 11-3) (pp. 1–38). Oita International Exchange Promotion Committee. (2019). http://www.ovop.jp/en/. Accessed 25 Mar 2019. Okura, Y. (2007). OVOP to burando senryaku [Regional development and OVOP: Implications from the brand image survey in Oita, Japan]. Business Review of Kansai University, 51(6). Raines, P. (2003). Cluster behaviour and economic development: New challenges in policy evaluation. International Journal of Technology Management, 26(2–4), 191–204. Savitri, D. (2008). An approach of sustainable development: rural revitalization as the pioneer of OVOP movement. Journal of OVOP Policy, 7, 21–30. Stenning, N., & Koichi, M. (2008). Knowledge and networking strategies for community capacity development in Oyama-machi: An archetype of the OVOP movement. Journal of OVOP Policy, 1, 5–20. Ueda, T. (2009). Social enterprises and JICA-supporting “One Village One Product” (OVOP) movement in Africa (OVOP). Tokyo: Japan International Cooperation Agency. Available at http://www.ilo.org/public/english/region/asro/tokyo/conf/2009se/tu.pdf. Accessed 25 Mar 2019. Yamagami, S. (2006). Isson ippin undo no genten: Ooyama chou no beisaku kara kajusaibai, kinokosaibai eno tenkan no kiseki [The origin of OVOP: The experience of Oyama town’s diversification strategy]. Seisaku kagaku, 14(3). Ritsumeikan University. Yoshimura, T. (2004). Sustainable local development and revitalization: Case of One Village One Product movement, its principles and implications. The United Nations Centre for Regional Development. Available at http://www.uncrd.or.jp/hs/doc/04a_14jun_teru_ovop.pdf. Accessed 15 Mar 2019.

Entrepreneurship, Innovation, and Economic Growth: Evidence from Saudi Arabia Yusuf Opeyemi Akinwale, Adel Abdullah Alaraifi, and Aljohara Khalid Ababtain

Abstract There have been growing interests on studies focusing on the shifting from resource economy to knowledge economy, and entrepreneurship and innovation seem to take leading roles in such discourse. Despite the fact that entrepreneurship has been recognized for the last few decades as an essential component of economic growth, which is facilitated by technological innovation, yet several studies could not establish such, especially in developing economies. Since Saudi Arabia government is dedicated to the achievement of Vision 2030 among which are diversifications of the economy from oil, increase the participation of small and medium enterprises and reduction of unemployment, there is a need for this study. This study examines the impact of entrepreneurship and innovation on economic growth in Saudi Arabia using the data obtained from World Bank Development Indicators (WDI) for the period 2005–2016. The result of the regression analysis revealed that innovation positively and significantly impacted on entrepreneurship. The results of the endogenous growth model further reveal that while entrepreneurship and innovation positively influence economic growth, the impact of entrepreneurship is significant but that of innovation is not significant on economic growth. This implies that entrepreneurship directly impacted on economic growth but innovation only impact on economic growth through entrepreneurship. Saudi government should be committed to further create a more suitable entrepreneurship ecosystem whereby improved entrepreneurial framework conditions, such as increasing the level of R&D transfers and innovation, finance for entrepreneurs, enhancing post-school entrepreneurship training and encouraging the participation of the private sector are achieved. Keywords Entrepreneurship · Economic growth · Innovation · Vision 2030 · Saudi Arabia · R&D

Y. O. Akinwale (*) · A. A. Alaraifi · A. K. Ababtain College of Business Administration, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia e-mail: [email protected]; aaalaraifi@iau.edu.sa © The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG 2020 M. H. Bilgin et al. (eds.), Eurasian Economic Perspectives, Eurasian Studies in Business and Economics 15/1, https://doi.org/10.1007/978-3-030-48531-3_3

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1 Introduction Entrepreneurship has been acknowledged to be a crucial factor in achieving economic development throughout the world (Erken et al. 2018; Urbano and Aparício 2016; Acs et al. 2012; Stam and Stel 2009; Acs et al. 2008). It uplifts the economic growth by introducing innovation, promoting competition, as well as increases the rivalry (Vivarelli 2013; Wong et al. 2005). 30–50% of differences in national growth rates could be traced back to the differences in entrepreneurship rates (Zacharakis et al. 2000; Reynolds et al. 1999). According to Schumpeter (1934), an innovative entrepreneur is an individual whose function is to start an enterprise. It is also argued that innovativeness is about deviating from the current technologies toward a more novelty approach, which means that innovation revolves around the ability of the institution to incubate novelty and new ideas and procedures that lead to new services, products as well as processes (Akinwale 2018a; Lumpkin and Dess 1996). The study of Wennekers and Thurik (1999) found that entrepreneurs play at least 13 different roles in the economic literature among which are assuming risk, innovating, identifying, and recognizing the beginning of a new venture. Many new small and medium enterprises (SMEs) have been occupying a significant position in the contemporary knowledge and entrepreneurial economy with the aid of Information and Communications Technology (ICT) revolution, globalization, and both incremental and radical innovation (Mahmud et al. 2019; Akinwale et al. 2018a; Prieger et al. 2016; Audretsch and Thurik 2000). Researchers have disputed the attribution of the fundamental economic growth in few decades ago to factor inputs namely land, labor, and capital alone (Solow 1957); as consideration has lately been given to entrepreneurship and innovation in the growth of the economy (Holcombe 1998). Entrepreneurs who put emphasis on product, process, organization, and marketing innovation play a nucleus role in sustainable development in an economy (Akinwale 2017; Baumol and Strom 2007; Olomu et al. 2016; Adeyeye et al. 2013). While entrepreneurship could be seen as the cause of economic growth through innovation, innovation itself could be seen as a factor that creates entrepreneurship from the product of various inventions leading to economic growth (Akinwale 2018b; Galindo and Méndez 2014). Schumpeter (1947), among other studies, accentuates the significant role of entrepreneurship and innovation in the economic growth process. This came by acknowledging that there are various factors which explain economic growth of a nation and that no single factor theory can ever be satisfactory (Galindo and Méndez 2014; Wennekers et al. 2002; Schumpeter 1947). Technological innovation has been identified as a fundamental determinant of economic growth (Akinwale and Grobler 2019; Hasan and Tucci 2010; Akinwale et al. 2012; Guloglu and Tekin 2012; Romer 1986; Hawash and Lang 2019). While there are some studies that examined the interrelationship between entrepreneurship, innovation, and economic growth, majority of such studies focus on the developed economies (Erken et al. 2018; Acs et al. 2012; Harbi et al. 2011). There is a dearth of study that assesses the relationship among these three variables in the developing and emerging economies which made fewer facts to be known on this

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relationship from these developing economies despite the vital policy implications that would emanate from the nexus of these variables in such economies. Small and medium firms could be the main drivers of sustainable growth in these developing economies unlike the developed economies which have lots of large firms (Stam and Stel 2009; Baumol 2002). One of the emerging regions striving to leapfrog on the experience of the developed economies is the Gulf region, and Saudi Arabia is one of the main proponents of sustainable growth in this region taking into consideration the peculiarities of the economic structure in her economy. Saudi Arabia realizes the role of SMEs in the economic growth as they provide jobs, increase the exports, as well as developing innovations. However, there is a limited number of studies examining the nexus between entrepreneurship, innovation, and economic growth in Saudi Arabia. Meanwhile, Saudi Arabia is rapidly transforming her economy toward achieving Saudi Vision 2030 set by the government. Few of the goals of Vision 2030 is increasing the share of non-oil exports in non-oil GDP from 16 to 50%, reducing the dependency on oil to have a more diversified economy, decreasing the unemployment rate of Saudis from approximately 12 to 7%, increase the private sector’s contribution from the current level of 40 to 65% of GDP, improve from the present position of 25 to be among the top 10 in the global competitive index, and elevating the contribution of SMEs to the GDP to reach 35% from 20% (Saudi Vision 2016). Majority of the goals aforementioned in the Vision 2030 of Saudi Arabia could not be realistic without the commitment of the political will to drive technology innovation and entrepreneurship in both private and public sectors of the economy (Ababtain and Akinwale 2019). It has been observed in recent time that the government has started backing up a few of the goals in “Vision 2030 document” with budgetary allocation to research and innovative activities as well as the establishment of entrepreneurship centers in some public universities. It becomes crucial to understand and investigate the relationship between entrepreneurship, technology innovation, and economic growth in Saudi Arabia. This study would reveal the impact of the contribution of entrepreneurial and innovative efforts of the Saudi government on her GDP growth. Section 2 presents the literature for the study, Sect. 3 presents the entrepreneurial framework condition in Saudi Arabia, Sect. 4 explains the data and methods used in the study, while Sects. 5 and 6 analyze the data and concludes the chapter.

2 Literature Review and Hypotheses Development Entrepreneurship is a landmark towards wealth creation and economic growth as it provides a colossal contribution toward the quality of life of people, sectors, and the entire economy (Ababtain and Akinwale 2019; Daubaraitė and Startiene 2017; Adusei 2016; Stam and Stel 2009). Entrepreneurs participate greatly in the creation of new economic activities through innovation which aids the generation of wealth, jobs, and growth in the society (Mahmud et al. 2019; Soriano and Peris-Ortiz 2011).

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Innovation could be seen as a tool for entrepreneurs in which he/she utilizes as an instrument to facilitate his/her business growth (Akinwale et al. 2018b; Holcombe 1998; Drucker 1985). Consequently, innovations stimulate creative destruction in which any entrepreneurs or firms that fail to introduce the new technologies would disappear as a result of competition (Schumpeter 1934). So entrepreneurship and innovation could also be seen as different sides of a coin (Soriano and Huarng 2013). The Neoclassical theories in the past have attributed economic growth to main land, labor, and physical capital (Smith 1776), and the recent endogenous growth theories have apportioned a large portion of economic growth that ordinarily could not be explained to technology innovation which is exploited by the entrepreneurs (Romer 1986, 1990; Lucas 1988). Innovation has played a great role in encouraging entrepreneurs to create new businesses, and innovation and entrepreneurship have displayed their significant role toward economic growth (Schumpeter 1947). Consequently, innovation and entrepreneurship have been included in the economic growth model of some recent studies (Urbano and Aparício 2016; Galindo and Méndez 2014). Some of the empirical studies that have been conducted on entrepreneurship and economic growth, on one hand, innovation and economic growth on the other hand, and the three variables together are shown in this section that enables this study to come up with research hypotheses considered in this chapter. Li et al. (2012) explored the influence of entrepreneurship on economic development in China using a panel data set covering 29 provinces for the duration of 20 years. The study revealed that economic growth is positively explained by entrepreneurship. While some studies (Carree and Thurik 2008; Beck et al. 2005) have shown a positive and significant association between entrepreneurship and economic growth, using small business ownership, self-employment, and new business creation as proxies for entrepreneurship and GDP for economic growth, few other studies showed a negative relationship between them (Reynolds et al. 2003; Iyigun and Owen 1998; Yamada 1996). Adusei (2016) explored the importance of entrepreneurship to GDP in 12 developing countries for the period 2004–2011. Entrepreneurship was measured by the number of newly registered businesses in a country in a financial year and the control variables include financial development, inflation, economic openness, human capital, gross domestic investment, and government spending. The results using random-effects regression revealed that entrepreneurship has a strong positive influence on the economic development; and that economic growth is positively and significantly influenced by the openness of the economy. The results also showed that the differences in the sampled countries in economic growth are positively explained by entrepreneurship, which results in entrepreneurship being essential for economic development in the developing economies. Daubaraitė and Startiene (2017) analyzed the relationship between creative industries and economic growth. The finding shows that the creative industry which employs personal creativity, skills, and talents creates wealth and jobs and leads to economic growth. Acs (2006) argued that business ventures that start of opportunity will grow and lead to economic growth more than necessity entrepreneurship. In another study, Acs and Armington (2006) showed that high levels of entrepreneurship correlate with slow economic growth. Harbi et al. (2011)

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conducted a study among 34 OECD countries for 11 years and found that selfemployment increases development in the economy in the short run, nonetheless, it reduces economic development in the long run. Hamdan (2019) investigated the effect of entrepreneurship on GDP in the United Arab Emirates for the period 1996–2015, the dependent variables are measured by the GDP and non-oil GDP, whereas the independent variable is entrepreneurship and it is measured by two factors which are number of new firms and the rate of creating new firms, whereby oil prices and economic diversification are used as control variables. The results using cross-sectional regression analysis revealed that entrepreneurship has a positive influence on UAE’s economic growth, and also showed that entrepreneurship and economic growth have a dynamic relation as entrepreneurship enhances non-oil GDP sectors that contribute straight to the economic diversification. Galindo and Méndez (2014) investigated the relationships between innovation, entrepreneurship, and economic growth in 13 developed countries for the period 2002–2007. The study used a Schumpeterian approach to link GDP, innovation and entrepreneurship, and adopted panel data with fixed effects. Innovation proxy by a number of patent issues, and entrepreneurship is proxy by private investment in millions of USD and human capital in millions of USD. Their outcomes revealed that entrepreneurship and innovation positively influence economic growth. Guloglu and Tekin (2012) analyzed the causal relations among R&D expenditures, innovation, and economic growth in 13 high-income OECD economies and their study revealed strong positive association between R&D, innovation, and economic growth. The result of the pair-wise Granger causality test implied that R&D intensity engenders innovation which latter enables economic growth, as prescribed by endogenous growth theory. This study suggests that R&D activity and innovation together Granger cause economic growth, and also shows that economic growth and R&D expenditure jointly Granger cause innovation. The global entrepreneurship monitor (GEM) introduced total entrepreneurial activity (TEA) as a variable that represents the adult entrepreneur who started a business or in the process of starting a business that he or she entirely or partly own and manage, and the business is less than 3.5 years old (GEM 2018). GEM identifies four different types of entrepreneurial activity (TEA) rates: high growth potential TEA, necessity TEA, opportunity TEA, and overall TEA. Necessity- and opportunity-driven TEA are the main ones relating to the starting off one’s businesses. While necessity-driven TEA is the percentage of TEA of the adult who has started a business out of necessity to be self-employed because there is no better alternative, opportunity-driven TEA is the percentage of TEA of the adult population who have started a business out of an opportunity they found at the market. Some of the recent studies also argued on the types of entrepreneurship out of the two which is better for economic growth (Reynolds et al. 2002; Wong et al. 2005; Nyström 2008; Valliere and Peterson 2009; Urbano and Aparício 2016).

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Rodrigues (2018) investigated the effect of entrepreneurship on the economic growth by using large data that consists of 79 countries—34 OECD and 45 non-OECD countries for the period 1990–2016. The result of the study using fixed-effects panel data estimations found that opportunity entrepreneurship brings up economic growth while necessity entrepreneurship constrains it. Nonetheless, economic growth and entrepreneurship are positively related. Urbano and Aparicio (2016) examined the influence of entrepreneurship capital types on economic growth among 43 countries of which 25 were from OECD countries and 18 were from non-OECD countries, for a period between 2002 and 2012. Their results using panel data and regressions analysis indicated that economic growth is positively and significantly influenced by opportunity TEA, signaling that entrepreneurship activity was a crucial element impacting economic growth in all countries included in the study. This result is similar to the study of Aparicio et al. (2016) whereby necessity entrepreneurship contributed to the GDP by solving small problems and reducing the unemployment rate at non-OECD countries but did not have an effect on long-run economic growth; whereas, opportunity entrepreneurship is more associated with economic growth and prosperity. Hafer (2013) investigated the role of entrepreneurship on economic growth using the Kauffman Index of entrepreneurial activity (KIEA) as the measure of entrepreneurial activity among 50 U.S. states for 5 years between 2000 and 2005. The result using regression analysis revealed that a higher level of entrepreneurial activity also shows high levels of economic growth, the researcher recommended enhancements in the entrepreneurial climate in order to raise economic growth. Wong et al. (2005) assessed the influence of innovation and the four different types of entrepreneurship based on the GEM 2002 data on the economic growth among 37 countries. Entrepreneurship and innovation were predictors for economic growth; and their results using linear regression revealed both innovation and entrepreneurship explained the variations in the economic growth for the sampled countries. Zhou and Luo (2018) identified the impact of technology innovation on economic growth in China though with some lag for the period 1997–2015. Akinwale and Grobler (2019) further revealed the positive impact of technology innovation on economic growth in South Africa. Meanwhile, some studies could not establish the positive impact of innovation on economic growth (Zhao et al. 2012; Akinwale et al. 2012). Some studies have asserted that innovation activities do not only directly impact economic growth, but also stimulate it through encouraging new business formation, which generates employment opportunities and more outputs (Wennekers and Thurik 1999; Kirchhoff 1994). According to Audretsch (1995), innovation inspires and assists entrepreneurs to create new businesses so as to penetrate certain sectors of the economy that is characterized by an entrepreneurial technological regime Based on the aforementioned regarding the empirical reviews of the related studies as well as the scarcity of similar studies in the Kingdom of Saudi Arabia, this study, therefore, formulates the two hypotheses as follows:

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H1: Innovation positively and significantly influence entrepreneurship. H2: Entrepreneurship and innovation positively and significantly influence economic growth. H2i: Innovation has a positive and significant impact on economic growth. H2ii: Entrepreneurship has a positive and significant impact on economic growth.

3 Entrepreneurial Framework Conditions in Saudi Arabia Based on the data obtained from the National Expert Survey as shown in GEM (2018), this subsection provides a bird’s eye view of an ecosystem of entrepreneurship in Saudi Arabia. The following are the selected factors that facilitate the startup of a business in an economy: (i) Financing for Entrepreneurs (FFE): The availability of financial resources for SMEs. (ii) Government Supports and Policies (GSP): The extent to which public policies support entrepreneurship. (iii) Governmental Programs (GP): The presence and quality of programs directly assisting SMEs at all levels of government. (iv) Post-School Entrepreneurial Education and Training (PSE): The extent to which training in creating or managing SMEs is incorporated within the education and training system in higher education such as vocational, college, and business schools among others. (v) R&D Transfer (RDT): The extent to which national R&D will lead to new commercial opportunities and is available to SMEs. (vi) Physical and Services Infrastructure (PSI): This is concerned with the ease of access to physical resources, such as communication, utilities, transportation, land or space, at a price that does not discriminate against SMEs. (vii) Cultural and Social Norms (CSN): The extent to which social and cultural norms encourage new business methods or activities that can potentially increase personal wealth and income. Each of these factors is measured on a scale of 1–5 with 1 being the least rank and 5 being the highest rank. Table 1 shows the ratings of the factors influencing the entrepreneurial framework conditions in the Kingdom of Saudi Arabia in the years 2009, 2016, and 2017, as well as comparative analysis with the United Arab Emirates and Qatar as they are in the same Gulf region. When an annual trend is examined for Saudi Arabia, it could be seen that five (Financing for entrepreneurs, Government supports and policies, Post-school entrepreneurial education/training, R&D transfers, and Physical and Services infrastructure) out of the seven factors declined between 2009 and 2017, though physical and services infrastructure initially increased between 2009 and 2016 before declining in 2017. Meanwhile, the

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Table 1 Entrepreneurial framework condition for selected gulf countries Country Qatar Saudi Arabia United Arab Emirates Qatar Saudi Arabia United Arab Emirates Qatar Saudi Arabia United Arab Emirates

Year 2017 2017 2017 2016 2016 2016 2009 2009 2009

FFE 2.64 2.34 2.96 2.67 2.39 2.66 NA 3.01 3.02

GSP 3.43 2.35 3.74 3.25 2.41 3.51 NA 2.71 3.39

GP 3.24 2.29 3.23 3.23 2.12 3.34 NA 1.97 2.71

PSE 3.04 2.17 3.32 3.46 2.26 2.84 NA 2.35 3.3

RDT 2.63 1.78 2.92 2.62 1.85 2.55 NA 1.99 2.38

PSI 3.81 3.38 4.4 3.87 3.99 4.25 NA 3.77 4.14

CSN 2.93 3 4.06 3.23 2.72 3.69 NA 2.52 3.04

Source: Global Entrepreneurship Monitor (2018)

continuous rising of Government program and Cultural and social norms is not surprising as the government has shown political commitment toward entrepreneurship by continuous creating various programs at different levels as well as supporting the use of culture and social norms to foster entrepreneurship in various sectors such as entertainment and sports among others. The ratings for all the factors are below 3.0 in the year 2017 except for physical and services infrastructure and cultural/social norms. R&D transfer has the lowest rating for Saudi Arabia in 2017. Table 1 also revealed that Saudi Arabia lagged behind the United Arab Emirates and Qatar in the 3 years observed except in the year 2017 when cultural and social norms of Saudi Arabia surpassed that of Qatar. This clearly shows that there is a need for the government to create more enabling environment for the Startup firms to flourish as well as encouraging the private sector to support entrepreneurship. However, there is no doubt that the Saudi government is making tremendous efforts toward the support of entrepreneurship in order to achieve Vision 2030. This is also evidenced in the report of GEM (2018) whereby Saudi Arabia was reported to witness an increase in the innovation level as 43.6% of TEA businesses showed some innovation component in 2017 which was 8.8% higher than that of 2016. Thus, the Saudi Arabia government is expected to improve the entrepreneurial framework condition so as to support the startup and the existing firms in the economy.

4 Data and Methodology 4.1

Data

The variables of interest in this study are basically entrepreneurship, economic growth, and technology innovation. In addition to the variables that are of primary concern in this study, two controlled variables are added as a result of their importance in the endogenous growth model adopted that includes gross fixed capital formation and labor force.

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Although there are studies (Urbano and Aparício 2016; Li et al. 2012) that have used various variables such as self-employment and TEA to proxy entrepreneurship but due to weaknesses and scarce of adequate data on some of these variables for Saudi Arabia, this study in line with few other studies (Adusei 2016; Klapper et al. 2007)) adopt a number of newly registered businesses in a given year to measure entrepreneurship (ENTRP). Economic growth is proxy by real GDP per capita (GDPpc) and is measured in terms of per capita GDP deflated to the base year of 2010 (constant 2010 US$), whereas innovation (INN) is proxy by total number of patents application in a given year. Meanwhile, labor force (LB) comprises people aged 15 years and above who supply labor for the production of goods and services in the country, and capital (GFCF) is represented by gross fixed capital formation in an economy. All these data are obtained from World Bank Development Indicators (WDI) for the period 2005–2016. The period of data is constrained by the data available for a number of newly registered businesses in a country.

4.2

Model

Two models are developed based on the hypotheses formulated. In the first model, entrepreneurship (ENTRP) is a dependent variable whereas innovation (INN) is an independent variable. The variables are transformed to natural logs so as to remove spurious regression. This is to determine the nature and significance of the relationship between entrepreneurship and innovation; specifically to evaluate the impact of innovation on entrepreneurship. This is shown in the natural logarithm form as follows: ln ðENTRPÞt ¼ β0 þ β1 ln ðINNÞt þ εt

ð1Þ

where lnENTRP is entrepreneurship, lnINN is innovation, t is the period considered for the study, β0 is the constant term, β1 is the coefficient of innovation and ε is the error term. In the second model, this follows the endogenous growth model whereby economic growth is expanded to include innovation and entrepreneurship. This model examines the impact of entrepreneurship and innovation on economic growth. This is shown in Eq. (2) as follows: ln ðGDPpcÞt ¼ α0 þ α1 ln ðENTRPÞt þ α2 ln ðINNÞt þ α3 ln ðLBÞt þ α4 ln ðGFCFÞt þ εt

ð2Þ

where lnGDPpc represents economic growth rate, lnINN is innovation, lnLB is labor force and lnGFCF represents capital. The study used the OLS regression method to analyze the data.

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5 Analysis and Discussion of Results The summary of the descriptive statistics of the data is presented in Table 2. The mean value of lnGDPpc (27.05) is the highest with the lowest standard deviation value of 0.14, whereas lnENTRP has the lowest mean value (8.70) with the highest standard deviation value of 0.44. Diagnostic test using ARCH, Breusch–Godfrey Serial Correlation LM Test and Jarque–Bera (JB) was also conducted. The null hypothesis for the normality of the data, no heteroskedasticity, and no serial correlation could not be rejected as each has p-values of 0.48, 0.70, and 0.60, respectively. This indicates that the model passed the required diagnostic tests conducted. The result of the first hypothesis showing the relationship between innovation and entrepreneurship is shown in Table 3. The table shows that lnINN is positively related to lnENTRP, which means that the proportion of lnENTRP would increase by 2.3 if there is 1 unit increase in lnINN. In other words, an increase in the number of patents created in Saudi Arabia generates more than double the number of newly registered firms. Also, the probability value (P-value) is 0.0015, which is below 5% level of significance, thus leading to the rejection of null hypothesis stating no significant impact of lnINN on lnENTRP. The proportion of variation in lnENTRP explained by lnINN is 68% which is above 50%. This result indicates that innovation has a positive and significant impact on entrepreneurship in Saudi Arabia. This is in line with some studies (Galindo and Méndez 2014; Kirchhoff et al. 2007; Audretsch 1995). Table 4 reports the results of hypotheses 2i and 2ii using the growth model in which lnGDPpc is the dependent variable. The model is divided into panels A and B Table 2 Descriptive statistics Mean Median Maximum Minimum Std. Dev.

lnGDPpc 27.05430 27.04040 27.26075 26.85797 0.146421

lnENTRE 8.705077 8.710352 9.276783 8.009695 0.448595

lnGFCF 25.60469 25.65603 25.94024 25.04597 0.276454

lnINN 10.34674 10.39229 10.48718 9.972360 0.154979

lnLB 16.14695 16.13355 16.41310 15.89222 0.180717

Source: Authors’ compilation Table 3 Regression results for entrepreneurship (lnENTRP)

Explanatory variables Constant Innovation (lnINN) R-squared Prob(F-Statistics) Standard errors in parentheses Source: Author’s compilation  Probability value significant at 5% level  Probability value significant at 1% level

Model 1 –15.47 (5.58) 2.33 (0.54) 0.68 0.001

Entrepreneurship, Innovation, and Economic Growth: Evidence from Saudi Arabia Table 4 Regression eesults for economic growth (lnGDPpc)

Model 2 Constant Innovation (lnINN) Entrepreneurship (lnENTRP)

Panel A 25.05 (0.83) 0.10 (0.11) 0.35 (0.04)

Capital (lnGFCF) Labor (lnLB) R-squared F-Statistics

0.91 118.57

35 Panel B 15.96 (5.15) 0.05 (0.11) 0.06 (0.01) –0.06 (0.18) 0.72 (0.22) 0.96 154.03

Standard errors in parentheses Source: Author’s compilation  Probability value significant at 5% level  Probability value significant at 1% level

whereby panel A takes into consideration only two independent variables lnENTRP and lnINN, whereas panel B takes into consideration the control variables lnGFCF and lnLB in addition to lnENTRP and lnINN. The primary objective of this model is to assess the positive and significant impact of entrepreneurship and innovation on economic growth in Saudi Arabia. Panel A shows that lnINN and lnENTRP have positive effects on lnGDPpc with coefficient values of 0.10 and 0.35, respectively. That is an increase in innovation and entrepreneurship by 1% would increase economic growth by 0.10% and 0.35%, respectively. Moreso, while lnENTRP is statistically significant on lnGDPpc at 1% level of significance, lnINN is not statistically significant. The proportion of variation in lnGDPpc explained by lnENTRP and lnINN is 91%. Furthermore, both lnINN and lnENTRP are jointly significant in explaining lnGDPpc since the p-value of F-statistic is less than 1% which indicates joint significance at 1% level. On the other hand, panel B which includes the control variables shows similar results with panel A. All the variables except lnGCFC have a positive impact on lnGDPpc, though only lnENTRP and lnLB are significant at 5% level with P-values 0.015 and 0.014, respectively. The proportion of variations in lnGDPpc explained by the independent variables has increased to 96% compared with panel A, and P-value of F-statistics (0.000) also indicates that all the variables are jointly significantly in predicting economic growth. The results of the model show that while entrepreneurship has a positive and significant impact on economic growth, innovation has a positive and insignificant impact on economic growth. Also, while hypothesis 2i is rejected because of the insignificant impact of innovation on economic growth, hypothesis 2ii is accepted since entrepreneurship has a significant impact on the two panels. The results are in line with some related studies (Hamdan 2019; Akinwale and Grobler 2019; Urbano and Aparício 2016; Adusei 2016; Carree and Thurik 2008; Kirchhoff 1994).

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The results of the two models clearly reveal that innovation is an important contributory factor to entrepreneurship as more innovation positively and significantly increases the number of newly created businesses in Saudi Arabia. Meanwhile, as innovation increases the number of business created, innovation could not on its own has significant impact on economic growth without entrepreneurship. This is implied in the second model as entrepreneurship has positive and significant impact on economic growth but innovation though has positive effect but does not have any significant impact. It becomes apparent that there is a great need for the Saudi Arabian government to continue to increase her spending on R&D and innovation and at the same time create an enabling environment for Startups, SMEs, and large firms as their entrepreneurial ingenuity would convert such innovation into economic growth.

6 Conclusions This study assesses the effects of entrepreneurship and innovation on economic growth in Saudi Arabia. While entrepreneurship was measured by a number of newly registered businesses, innovation, and economic growth were measured by the total number of patent applications and real GDP per capita, respectively. The results of model 1 using regression analysis reveal that innovation has positive and significant impact on entrepreneurship, indicating the number of newly created businesses increases significantly as new patents are being generated through inventions and innovations. Furthermore, considering labor force and capital with the addition of innovation and entrepreneurship in the endogenous growth model, the second model establishes positive and significant impact of entrepreneurship on economic growth in Saudi Arabia; whereas, positive but insignificant impact of innovation on economic growth was also established. These results imply that while innovation is a major contributory factor to entrepreneurship in Saudi Arabia, it does not have significant impact on economic growth directly but only have significant impact on economic growth indirectly through entrepreneurship. Meanwhile, entrepreneurship positively and significantly influences economic growth which could be through employment generation, increases in the outputs produced, improve the existing ways of doing things, and wealth creation among others. There is no better time than now for Saudi Arabia’s government to further support entrepreneurship through its policy. Since the nation is supported with a political will toward achieving Vision 2030, further efforts should be made to create a suitable entrepreneurship ecosystem whereby improved entrepreneurial framework conditions—in terms of R&D transfers and innovation, financing the entrepreneurs, post-school entrepreneurship training, encourage the participation of the private sector and more infrastructure—are achieved. Further study could be conducted by examining the effect of necessity- and opportunity-driven TEA on economic growth using GEM data, though this data is still relatively scanty for Saudi Arabia

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Acknowledgments The research is executed within the research project financed by the National Center for Entrepreneurship and Freelancing Studies & Research in the Kingdom of Saudi Arabia.

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Part II

Finance

The Impact of Capital Structure on Firm Performance and Risk in Finland Shab Hundal, Anne Eskola, and Sofiya Lyulyu

Abstract The decision pertaining to the capital structure is one of the most strategic, perpetual, and at the same time challenging corporate decisions. Having an optimum capital structure is an important aspect of the financing of firms. Firms often struggle to create an optimum balance between their debt and equity. The current chapter aims to explore whether the capital structure impacts the performance (financial and nonfinancial) and the financial risks of the firms in Finland. In the current chapter, the secondary data of 50 large-cap Finnish public firms listed at the Helsinki stock exchange has been obtained for the period 2011–2017. The findings of the research disclose that leverage affects most of the accounting, market, and hybrid performance measures negatively. On the other hand, the effect of leverage on the nonfinancial measures has been found to be insignificant. Similarly, a high level of leverage leads to increase in the total risk; however, it does not affect the systematic risk. The current chapter is one of the fewest studies that employed comprehensive analysis through multiple measures of firm performance, risk, and capital structure in the context of the Finnish corporate sector. Keywords Capital structure · Firm performance · Risks · Return · Debt · Equity

1 Background Although the decision related to the composition of firm financing, also known as capital structure, is one of the most important decisions of firms, however, this decision is not standalone by its nature as any change in the capital structure may affect other vital aspects related to firms such as their performance and risk exposure. Even more puzzling is that both theoretical and empirical literature has failed to establish any singularity between changes in the capital structure and resultant S. Hundal (*) · A. Eskola · S. Lyulyu School of Business, JAMK University of Applied Sciences, Jyväskylä, Finland e-mail: shabnamjit.hundal@jamk.fi; anne.eskola@jamk.fi; [email protected].fi © The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG 2020 M. H. Bilgin et al. (eds.), Eurasian Economic Perspectives, Eurasian Studies in Business and Economics 15/1, https://doi.org/10.1007/978-3-030-48531-3_4

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effects on performance and risk exposure of firms. In other words, both ex ante theoretical arguments and ex post empirical evidence show that any change in the capital structure can affect the firm value/performance and firm risk exposure differently. One of the key strategic goals of firms is to enhance their financial performance to meet the expectations of their investors. However, the firms also must ensure that while fulfilling the utility function of investors the solvency of firms cannot be compromised since an insolvent firm not only affects the investors unfavorably but also damage the interests of other stakeholders. Therefore, a rational firm must maintain a judicious balance between its indicators of financial performance (for example, profitability ratio) and solvency. The firm’s capital structure, which is comprising of the debt and equity and represents the financing of firms, is an important determinant of the solvency of firms, among other things. Therefore, every firm strives to achieve the optimum level of capital structure. However, firm managers often struggle to create the optimum capital structure, which is expected to be compatible to the long-term financing needs, institutional characteristics and operational complexities of firms, since the firm’s needs, priorities and business/ economic environment are ever-changing, among other things (Chadha and Sharma 2015; Baker and Martin 2011; Donaldson and Preston 1995). The relevance of capital structure can also be studied through the capital structure irrelevance theory propounded by Modigliani and Miller (1958). The hallmark of this theory is that only investments (assets) add to the firm and financing (capital structure) is nothing more than a façade since it only signifies different combinations of debt and equity, therefore, the financing decisions are irrelevant. Nevertheless, several subsequent studies have found that due to market imperfections (for example, taxation) it is possible to change the firm value by changing the proportion of debt in the capital structure. The trade-off theory explains that the burden of corporate tax does not fall on the debt servicing since interest is paid before a firm pays its corporate tax and resultantly it can obtain a higher level of interest tax shield after paying a higher level of finance costs to the debtholders by enhancing relative share of debt in the firm financing (Kraus and Litzenberger 1976). However, the changing level of debt not only affect the firm value but also profitability and risk exposure of the firm, consequently it is possible that the benefits of debt (leverage) are outweighed by the falling profits, risk firm risk exposure, adverse investors reaction and personal income tax rate, among other things (Hundal et al. 2018; Salim and Yadav 2012). Since the abovementioned effects of leverage are not uniform, therefore, it is of utmost importance to ascertain the impact of capital structure on the various measures of firm performance and firm risk exposure to make the financial planning of the firm seamless. The current study endeavors to explore the following two research questions-whether, the firm-level capital structure influences, first, the corporate performance, and second, the financial risk of the firms. To address the abovementioned research questions the unbalanced pooled secondary data of 50 Finnish publicly listed firms have been analyzed for the period 2011–2017. The results reveal that the rising proportion of debt in the capital

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structure, implying an increase in the leverage ratio, affects most of the accounting, market, and hybrid performance measures negatively. On the other hand, the effect of increasing leverage ratio on the nonfinancial measures has been found to be insignificant. Similarly, more leverage inclined capital structure of the firms leads to an increase in the total financial risk, however, the systematic risk is not affected by it. An important theoretical contribution of the current chapter is that it not only investigates the dynamics of capital structure on the firm performance but also on the corporate financial risk exposure. Similarly, the empirical contribution of the current article is that it is one of the fewest studies exploring the effects of capital structure on the multiple measures of, first, firm performance including financial (accounting, stock market, hybrid) and nonfinancial measures and, second, financial risks exposed by firms, particularly in the context of the Finnish corporate sector. Section 2 of the current chapter highlights the in-depth literature review and theoretical underpinnings. Section 3 addresses various aspects of the research methodology. Section 4 presents the results, whereas Sect. 5 underlines the main conclusions of the study.

2 Literature Review and Theoretical Underpinnings According to Swanson et al. (2003), capital structure represents a mix of debt and equity of a firm that finances its assets including various investment projects. The capital structure signifies “the liabilities and equity” side of the balance sheet of firms and thus highlights where money comes from. The first main component of the capital structure is equity, which is the residual interest of the shareholders in the firm value. The firm can raise equity financing by selling its shares. Often the main objective of raising equity financing is to raise financial resources to invest in the assets having a long-term impact on the firm value. The assets side of the balance sheet signifies where money goes to (Agarwal 2013). The reward to shareholders largely depends on the growth (actual and potential) of the firm and its operational success, among other things (Arnold 2008). Corporate debt is characterized by the regular repayments and it includes interest obligations and part of the principal amount of debt over a specified maturity time. The debt can be in several forms such as bonds, bank borrowings, leases, and commercial papers (Swanson et al. 2003; Arnold 2008; Berk and DeMarzo 2017). Otzekin (2015) argues that in order to understand capital structure determination, it is important to study the costs and benefits associated with the leverage. The debt has several advantages, first, the borrowing firm is obliged to pay at the predetermined interest rates only. Resultantly, the corporate profits commensurate with its revenue, given that the debt repayments and other costs do not change. Second, the tax deduction is another benefit associated with the debt. In the income statements of firms, the tax is subtracted from the gross profit only after the interest payments have already been made, implying that a firm can reduce its tax obligations

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by increasing the relative share of debt in its composition of financing. This phenomenon is known as the tax shield. Nevertheless, debt may have many unfavorable effects on the firm too. First, banks or other lenders stay higher than the shareholders in the pecking order when the firm is making repayment of its financial liabilities in a situation of bankruptcy or liquidation. As a result of such a situation, shareholders may find themselves getting exposed to additional risk, which accumulates even further since the shareholders receive dividends (if any) after the debtholders are paid interest. Shareholders can start demanding a higher risk premium in such a situation and as a result cost of capital can increase. Second, a higher proportion of debt in the total capital can adversely affect the credit ratings of the firm, consequently, the firm may face an adverse situation in the debt market characterized by higher interest rates (including premium) and unfavorable terms and conditions related to loan (debt covenants) imposed by financial institutions. Third, a higher level of debt of the firm can increase its bankruptcy risk as the lenders can claim its assets in case the firm fails to comply with terms of loan, especially those related to repayment of debt, which can lead to even its liquidation (Hillier et al. 2012). Fourth, high leveraged firms may find it difficult to issue equity as potential as well as existing shareholders perceive such a situation as an erosion of their financial stakes in such firms since the increased debt and subsequently enhanced debt servicing can leave fewer resources for shareholders. Finally, the rising debt of a firm can lead to agency conflicts between shareholders and management. The corporate managers of a firm can launch an investment spree financed by substantial amount of borrowing and such move by the managers can help them to entrench themselves deeper in the corporate echelon to such an extent that they virtually become indispensable for the firm at the expense of shareholders (Hundal 2016, 2017). Similarly, equity is associated with several advantages. First, the shareholders, particularly those having the long-term perspective, take an informed decision to remain with the firm by investing in firm equity, resultantly firm management gets extra freedom to reinvest the financial resources into new projects, which can enhance the firm value (Zickefoose 2014). Second, from the resource dependence theory viewpoint, the shareholders of a firm not only bring financial resources, but also their experience, managerial, and technical skills and relational capital, which can increase the credibility of the firm in the market (Hundal 2016, 2017). Nevertheless, equity has several disadvantages too. First, equity financing requires sharing the decision-making rights with the shareholders, and this puts extra strain on the professional managers of the firm to function independently, and thus leading to a different type of agency problems. Second, the rate of return on equity demanded by its shareholders is often higher than the rate of interest on the debt owing to the additional risk exposure of equity owners. Even though the firm may choose not to pay to the equity holders for certain period, nonetheless, it still must share its earning with the shareholders in the future. If the firm does not pay to the shareholders, then the latter may start selling their equity stakes and thus negative stock market reaction can ensue (Zickefoose 2014; Fong Chun Cheong 2015).

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Based on the above discussion, it can be understood that the capital structure decision is one of the long-term strategic decisions that firms take. This decision requires contemplation, revision, and modification in such a way that it is compatible with the changing needs and requirements of the firm (Agarwal 2013). Theoretically, the concept of optimum capital structure underpins a situation when the financing mix cannot add value to the firm any further (Baker and Martin 2011). One of the first theories of the capital structure is known as the capital structure irrelevance proposition, which defies the relevance of any optimum capital structure since such a scenario is no more than a utopia in the financial world. This theory was developed by Modigliani and Miller (1958) and it states that the firm adds to its value only through “the asset side,” that is, the investing side of the balance sheet. The “equity and liabilities” side of the balance sheet only represents financing side, which is no more than the packaging of its financial resources, therefore, the firm cannot create the value through the financing side of the balance sheet and as a result the capital structure decisions of the firm are rendered irrelevant (Frank and Goyal 2007; Salim and Yadav 2012; Focardi and Fabozzi 2004). Similarly, Myers (2001) highlights in the trade-off theory conflicts between the debt tax shield and the threat of bankruptcy that can be caused by the debt. A firm can achieve the optimal leverage at a point where the marginal present values of the debt tax shield on a unit of additional borrowing become equal to the cost of financial distress of the same. Contrary to the popular perception that highly profitable firms borrow less, the trade-off theory underlines the opposite relationship that is more profitable firms borrow more. If the firm has a high level of profits, then it will end up paying more taxes unless it borrows substantially and pays more finance costs. Nonetheless, if such measures are followed continuously and the firm becomes over-leveraged then financial distress costs can increase and push the firm toward bankruptcy (Frank and Goyal 2007; Brigham and Ehrhardt 2007; Sekar et al. 2014; Myers 2001). The nature of financing sources (internal and external) is not perceived to be the same and it can be stated that firms must give preference to internal sources to finance its investment in comparisons to external ones because there are no information asymmetries attached to the internal financing. However, the growing size and business complexities can necessitate firms to obtain external financing, however, some studies, for example, Fama and French (2005) and Leary and Roberts (2010) recommend firms to turn to the debt instead of raising equity if at all firms need external financing. The key argument in favor of debt is that firms issuing external equity may expose themselves to the high level of agency costs, especially if they are functioning in a business environment proliferated with information asymmetries. Asquith and Mullins (1986) find in their empirical analysis that when a firm makes an announcement of issuing new equity the price of its current equity in the stock market drops by 3%. The debt, on the other hand, is considered to be causing no or lesser downward impact on the stock price. According to peckingorder hypothesis, the retained earnings are better than the debt, and debt is better than equity, therefore, managers should borrow instead of external equity financing in order to protect the equity price from dropping and thus maximizing firm value (Frank and Goyal 2007; Sekar et al. 2014; Myers 2001). Binsbergen et al. (2011)

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have developed an approach that predicts the optimum amount of debt that increases the market value of the firm without adding any additional risk exposure of the firm. They argue that the growing debt helps the firm performance to increase, nevertheless, this association is not infinite. When the firm debt reaches its debt capacity, the disadvantages of debt start exceeding advantages. The firm-level equilibrium is established where the marginal cost and marginal benefit related to borrowings are equal. Otzekin (2015) provides four predictions with respect to the proportion of debt in the capital structure of firms based on determinants such as bankruptcy costs, tax benefits, and agency costs that managers use when striving to achieve the optimal capital structure. The first prediction is that firms decrease their leverage due to the fear of higher bankruptcy costs. Furthermore, a lower leverage ratio may imply that the firm is experiencing a meager profitability ratio, small sized, owning fewer tangible assets, and operating in the inflationary economic situation. Secondly, a higher expected value of tax shield can trigger a higher proportion of debt in the capital structure of firms. Thirdly, firms having high profitability and at the same time low growth opportunities can be inflicted with agency costs related to equity capital, therefore, such firms are expected to have relatively more debt. Lastly, firms owning more tangible assets and having low growth opportunities are exposed to lower agency costs, therefore, firms should have relatively more debt. Venkatraman and Ramanujam (1986) have given the three-circle model in which financial performance represents the business performance, and the latter determines the overall organizational effectiveness. The financial performance can be enhanced through the optimum utilization of resources, whereas the operational performance can be improved through the stakeholders’ utility maximization pursuit (Selvam et al. 2016). The need for the performance measurement is unnegotiable as it allows to identify the level of effective usage of the organizational resources (Al-Matari et al. 2014). As one of the main objectives of the firm is the shareholders’ wealth maximization and meeting the expectations of its investors, therefore, financial performance measures become the essential indicators of a firm’s ability to generate revenue from its business activities. Furthermore, when considering the perspective of other stakeholders of the firm, strategic or nonfinancial performance measures begin to occupy a pivotal place to evaluate the effectiveness of the firm’s actions (Selvam et al. 2016). The market-based performance measures underline the expectations related to the future value of the firm. Arguably the market-based measures incorporate historic profitability and past growth performance along with the expected stock market, and firm-related developments (Selvam et al. 2016). From the point of view of the shareholders, the stock market performance of listed firms is measured to evaluate the standing of their market value in the equity market—if the equity of the firms is overpriced, fairly priced, or underpriced, among other things (Peavler 2017). The total market value of the firm, also known as market capitalization, is the product of its number of equity shares traded in the stock market and prevailing stock market price per equity share.

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Brealey et al. (2014) contend that the accounting measurement of firm performance represents the effectiveness of its managerial resources. Furthermore, accounting performance represents the profitability of firms (Vernimmen et al. 2014). According to Bajkowski (1999), financial statement analysis quantifies the operating and financial settings of firms. Similarly, firms can also apply various hybrid measures of performance, for example, Tobin’s Q, is calculated by dividing the market value of debt and equity by the replacement cost of the assets of firms (Khanna and Palepu 2001). Therefore, if the Tobin’s Q coefficient is more than 1, it implies that the market value of the firm is more than the replacement cost of its assets. In other words, the market value of the firm is more than its book value. However, the calculation of Tobin’s Q is difficult primarily because a large proportion of the corporate debt is institutional debt that is not actively traded in the debt market; therefore, Tobin’s Q Proxy is measured in the current chapter for the empirical analysis (Hundal 2017). The Tobin’s Q Proxy is the sum of market value and shareholders’ equity plus book value of debt, divided by the book value of assets. Since Tobin’s Q Proxy consists of both the market as well as the historic accounting numbers, therefore, in the current chapter Tobin’s Q Proxy is considered as the hybrid measure of firm performance. Firms can also utilize several nonfinancial performance measures too, especially when adhering to the utility function of the firm stakeholders other than shareholders. It may be argued that traditional financial tools applied to measure firm performance are not compatible with the ever-changing dynamics of the business environment, for instance, the developments related to the technological, and competitive environment. According to another argument, the nonfinancial tools of measuring firm performance underscore favorable and unfavorable characteristics of firm operations, growth orientation, and organizational development. The nonfinancial performance measures may enable the firm management to track firm performance in the light of the business environment, market size, organizational structure, and firm strategy, among other things. The critics put forward an argument that financial performance primarily focuses on the short-term performance, however, nonfinancial measures throw light on long-term strategic goals of firms. The performance measures such as investments in research and development (R&D) can help to maximize the long-term utility function of stakeholders’ (Bassani et al. 2010; Vittorio and Federico 2009; Wingate 2015; Zizlavsky 2016). Several studies show that firms having long-term value maximization orientation give due importance to investing in R&D investments even if they are likely to compromise short-term profitability (Sougiannis 1994; Nissim and Thomas 2000). Similarly, many researchers argue that the use of intangible assets, like intellectual capital, goodwill, or customer loyalty, depicts long-term growth orientation, and stakeholders’ wellbeing (Wyatt 2008; Aggelopoulos et al. 2016; Haji and Ghazali 2018). Intangible assets can be acquired externally or even self-created; the former includes mergers and acquisitions, and the latter includes the assets of high value. However, there are several shortcomings related to the accounting rules and practices that restrict the inclusion of certain intangible assets in financial statements, and such intangible assets include brand names, trademarks, patents, technology, in-process R&D, and

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customer relationships, among others. The association between the leverage and intangible assets of the firm is a topic of immense interest among researchers and business, and financial analysts in the modern business world. However, it may be argued that firms owning more tangible assets can have more borrowings because tangible assets can be redeployed and/or confiscated by the lenders at a smaller transaction cost in the event of default committed by the borrowing firms. Moreover, the valuation of tangible assets is not only less complicated but there is also less uncertainty involved when calculating future cash flow arising of such assets, resultantly, lenders may charge lesser borrowing cost if tangible assets are used as collaterals by borrowing firms. Intangible assets often fail to match the abovementioned advantages associated with tangible assets. The risks faced by a firm underpin the uncertainty related to the potential events that can impact the fulfillment of its various objectives, especially those related to strategy, operations, and finance. From the perspectives of both firms and investors, risk-return trade-off assumes a pivotal place (Watson and Head 2016). The shareholders often face the risk by holding shares of a firm in their portfolio whose realized dividend payouts and final share price is likely to be less than the expectations (Berk and DeMarzo 2017). The rational shareholders strive to minimize the risk level for a given expected return on investment. The quantification of risk exposure to the investment projects is extremely important in the financial decision-making process. The total financial risk faced by investors is often measured by the standard deviation statistic of its stock return, cash flows, and revenue of the firm/portfolio they invest in (Watson and Head 2016). The total financial risk can be split into unsystematic, and systematic risks (Lofthouse 1994). The unsystematic risk is the firm-specific risk and it depends on various factors related to a specific industry or a firm. Investors striving to minimize the unsystematic risk diversify their portfolio by investing in the stocks of different firms belonging to different industries, sectors, and even locations (Dimson 1998). The market risk, on the other hand, is measured by the systematic risk as it spreads for all the industries, and sectors and is not restricted to a specific industry or firm. There are several determinants of systematic risk, for example, trade cycles, regulatory policies and changes in the interest, and exchange rates (Watson and Head 2016). The systematic risk cannot be reduced by diversification, and it can be only minimized by adopting an effective risk management policy, especially with the help of financial hedging. Based on extensive literature review the following hypotheses have been developed: H1: The capital structure affects the firm’s performance. H1a: The capital structure affects the firm’s performance (market-based measures). H1b: The capital structure affects the firm’s performance (accounting-based measures). H1c: The capital structure affects the firm’s performance (hybrid measures). H1d: The capital structure affects the firm’s performance (nonfinancial measures).

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H2: The capital structure affects the financial risk exposure of firms. H2a: The capital structure affects the systematic risk exposure of firms. H2b: The capital structure affects the total risk exposure of firms.

3 Research Methodology The data analyzed in the current research is secondary. The major sources of data are NASDAQ OMX Nordic stock market database and annual reports of the sample firms. The total sample is consisting of 50 publicly traded large-cap Finnish firms. The sample firms represent various industries including oil and gas, materials production, industrials, consumer goods and services, health care, telecom, and technology. The financial institutions and utilities were excluded from the sample due to the differences in their leverage regulations. The unbalanced pooled data were collected from January 01, 2011 to December 31, 2017, therefore, covering a period of seven years. The total number of firm-years is 323. In the current study, leverage ratios are applied as the capital structure, which is the principal determining variable. To measure the firm-level leverage, two measures of debt-to-equity (D/E) ratio have been used. This measure shows the extent of liabilities that a firm owes for each monetary unit of equity. A lower (higher) than 1 leverage ratio implies that firms have more equity (debt) than debt (equity). One may draw an inference from a high leverage ratio that the firm is in financial distress. On the other hand, a lower leverage ratio may imply that the firm is following a conservative financing policy and/or its debt capacity is lower. The firms having a higher proportion of physical assets, lower operating costs, and consistent cash flows, ceteris paribus, have a higher debt capacity. Debt Total Liabilities Ratio ðD=EÞ ¼ Equity Shareholders EquityBook or market value

ð1Þ

The principal determined variables are the ratios measuring the market, accounting, nonfinancial performance, and risks. The investors often use the market-to-book value ratio (MBVR) to compare growth in their equity investment. The MBVR represents the value that is placed by the market on the equity issued by the firm. The MBVR also shows the efficacy of the utilization of firms’ assets by their managers and the subsequent reaction of the stock market (Peavler 2017). Market  to  Book Value Ratio ðMVBVÞ ¼

Market Value of Equity Book Value of Equity

ð2Þ

The other measure of the market performance is the Price-to-Earnings ratio (PE), which can be calculated by the following formula:

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Price  to  Earnings Ratio ðPEÞ ¼

Share Price Earning Per Share

ð3Þ

The interpretation of a rising PE ratio is that the stock market is reflecting confidence in the firm’s current and expected level of the firm earnings. The most commonly used ratios measuring accounting performance are the return on equity (ROE) and return on assets (ROA). The ROE shows how efficiently a firm utilizes the financial resources provided by its shareholders to generate returns (net income). This ratio represents the firms’ profitability, as it indicates how efficiently financial resources provided by the shareholders are utilized by the firms’ managers (Oliver and Horngren 2010). The ROA also measures how efficiently firms’ financial resources provided by both debtholders and shareholders are utilized. The total assets (the denominator used in the calculation of ROA) is the sum of total liabilities and shareholders’ equity. Therefore, the ROA indicates the profit generated by the firms by utilizing everything they own including cash, equipment, inventory, and machinery (Bajkowski 1999). The third accounting ratio is the earnings per share (EPS), which shows the net profit earned by the firm for each outstanding equity share issued by it (Elliot and Elliot 2009). The EPS is also known as the investor’s ratio as the trends in the EPS are closely monitored by the equity holders and the analysts. In order to calculate Jensen’s Alpha, the daily firm stock return and market (index) return are calculated and subsequently annualized by applying the following formula: Return ¼

Closing priceCurrent day  Closing pricePrevious day Closing priceprevious day

ð4Þ

The risk-free rate of return needed to calculate the benchmark rate of return, as theorized by the Capital Asset Pricing Model (CAPM), has been taken from the Suomi Pannki (The Bank of Finland) database. The ten-year government bond rate has been used as the proxy of the risk-free rate. The CAPM formulation is as below: RA ¼ Rf þ βðRm  Rf Þ

ð5Þ

where: RA—required return on investing in Firm A Rf—risk-free rate of return β—firm-level beta (measure of the systematic risk) Rm—market return Table 1 shows the description of the variables used in the empirical analysis. The ordinary least square (OLS) multivariate regression model in the current chapter is as below:

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Table 1 Description of variables Variable Label Independent variables Debt-to-Book DE1 value of Equity Ratio Debt-to-Market DE2 value of equity ratio

Definition/formulation

Source

This firm-level “capital structure” variable is the ratio of book value of liabilities to the book value of shareholders’ equity. This firm-level “capital structure” variable is the ratio of book value of liabilities to the market value of shareholders’ equity (market capitalization).

Annual reports

Dependent variables Market performance measures Price-to-earnPE The stock price of the firm divided by its ings ratio EPS. The ratio of the firm’s market capitalization to the book value of its shareholders’ equity. Jenson The measure of over(under)performance Alpha of the firm’s stock return in relation to its expected return, calculated by subtracting the cost of equity (determined by CAPM) from the actual return. Accounting performance measures Earnings per EPS (Net income—Dividends on preferred share stock)/average number of outstanding shares Return on ROA A measure of profitability, calculated as Assets the ratio of operating profit to total assets of the firm. Return on ROE A measure of profitability, calculated as equity the ratio of operating profit to shareholders’ equity of the firm. Nonfinancial performance measures Investments in RDSales Innovativeness measure calculated as the Innovations ratio of investments in R&D to total sales of the firm. intangibility IntgTA Intangibility measure calculated as the ratio ratio of total intangible assets to total assets of the firm. Hybrid performance measure Tobin’s Q TobinQ The total of the market value of shareproxy holders’ equity and book value of debt, then divided by the book value of assets of the firm. Risks Systematic risk BETA The volatility measure of the firm’s stock return to the market return changes.

Market valueto-book value ratio Jenson’s Alpha

MVBV

Annual Reports and NASDAQ OMX Nordic

Annual reports and NASDAQ OMX Nordic Annual reports and NASDAQ OMX Nordic NASDAQ OMX Nordic

Annual reports

Annual reports

Annual reports

Annual Reports

Annual reports

Annual reports and NASDAQ OMX Nordic

NASDAQ OMX Nordic (continued)

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Table 1 (continued) Variable Total risk

Label SD

Control variables Share of indeIndDirProp pendent directors Current ratio CACL

Total assets

Assets

Market capitalization

MarkCap

Definition/formulation Measured by the standard deviation of the firm’s stock return.

Source NASDAQ OMX Nordic

The ratio of the number of independent directors to the total directors in a firm’s board of directors. A measure of liquidity, calculated as the ratio of current assets to current liabilities of the firm. Natural logarithm of total assets (LnAssets), measuring firm size (book value). Natural logarithm of market capitalization (LnMarkCap), measuring firm size (market value)

Annual reports

Annual reports

Annual reports

NASDAQ OMX Nordic

Source: Compiled by authors

yi,t ¼ αi,t þ

t X

βk xi,t þ εi,t

ð6Þ

k¼1

where: yi—Dependent variable or firm i in the period t αi, t—Intercept of the model xi, t—Corresponds to the ith explanatory variable in the tth year ε—The random error with the expected mean 0 and variance σ 2 In the empirical analysis, the following multivariate OLS regression models have been used: PEi,t ¼ αi,t þ β1 ðDE1Þi,t þ β2 ðDE2Þi,t þ β3 ðMVBVÞi,t þ β4 ðJensonAlphaÞi,t þ β5 ðEPSÞi,t þ β6 ðROAÞi,t þ β7 ðROEÞi,t þ β8 ðRDSalesÞi,t þ β9 ðIntgTAÞi,t þ β10 ðTobinQÞi,t þ β11 ðBETAÞi,t þ β12 ðSDÞi,t þ β13 ðIndDirPropÞi,t þ β14 ðCACLÞi,t þ β15 ðLnAssetsÞi,t þ β16 ðLnMarkCapÞi,t þ εi,t

ð7Þ

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MVBVi,t ¼ αi,t þ β1 ðDE1Þi,t þ β2 ðDE2Þi,t þ β3 ðPEÞi,t þ β4 ðJensonAlphaÞi,t þ β5 ðEPSÞi,t þ β6 ðROAÞi,t þ β7 ðROEÞi,t þ β8 ðRDSalesÞi,t þ β9 ðIntgTAÞi,t þ β10 ðTobinQÞi,t þ β11 ðBETAÞi,t þ β12 ðSDÞi,t þ β13 ðIndDirPropÞi,t þ β14 ðCACLÞi,t þ β15 ðLnAssetsÞi,t þ β16 ðLnMarkCapÞi,t þ εi,t

ð8Þ

JensonAlphai,t ¼ αi,t þ β1 ðDE1Þi,t þ β2 ðDE2Þi,t þ β3 ðMVBVÞi,t þ β4 ðPEÞi,t þ β5 ðEPSÞi,t þ β6 ðROAÞi,t þ β7 ðROEÞi,t þ β8 ðRDSalesÞi,t þ β9 ðIntgTAÞi,t þ β10 ðTobinQÞi,t þ β11 ðBETAÞi,t þ β12 ðSDÞi,t þ β13 ðIndDirPropÞi,t þ β14 ðCACLÞi,t þ β15 ðLnAssetsÞi,t þ β16 ðLnMarkCapÞi,t þ εi,t

ð9Þ

EPSi,t ¼ αi,t þ β1 ðDE1Þi,t þ β2 ðDE2Þi,t þ β3 ðMVBVÞi,t þ β4 ðJensonAlphaÞi,t þ β5 ðPEÞi,t þ β6 ðROAÞi,t þ β7 ðROEÞi,t þ β8 ðRDSalesÞi,t þ β9 ðIntgTAÞi,t þ β10 ðTobinQÞi,t þ β11 ðBETAÞi,t þ β12 ðSDÞit þ β13 ðIndDirPropÞi,t þ β14 ðCACLÞi,t þ β15 ðLnAssetsÞi,t þ β16 ðLnMarkCapÞi,t þ εi,t

ð10Þ

ROAi,t ¼ αi,t þ β1 ðDE1Þi,t þ β2 ðDE2Þi,t þ β3 ðMVBVÞi,t þ β4 ðJensonAlphaÞi,t þ β5 ðEPSÞi,t þ β6 ðPEÞi,t þ β7 ðROEÞi,t þ β8 ðRDSalesÞi,t þ β9 ðIntgTAÞi,t þ β10 ðTobinQÞi,t þ β11 ðBETAÞi,t þ β12 ðSDÞi,t þ β13 ðIndDirPropÞi,t þ β14 ðCACLÞi,t þ β15 ðLnAssetsÞi,t þ β16 ðLnMarkCapÞi,t þ εi

ð11Þ

ROEi,t ¼ αi,t þ β1 ðDE1Þi,t þ β2 ðDE2Þi,t þ β3 ðMVBVÞi,t þ β4 ðJensonAlphaÞi,t þ β5 ðEPSÞi,t þ β6 ðROAÞi,t þ β7 ðPEÞi,t þ β8 ðRDSalesÞi,t þ β9 ðIntgTAÞi,t þ β10 ðTobinQÞi,t þ β11 ðBETAÞi,t þ β12 ðSDÞi,t þ β13 ðIndDirPropÞi,t þ β14 ðCACLÞi,t þ β15 ðLnAssetsÞi,t þ β16 ðLnMarkCapÞi,t þ εi,t

ð12Þ

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RDSalesi,t ¼ αi,t þ β1 ðDE1Þi,t þ β2 ðDE2Þi,t þ β3 ðMVBVÞi,t þ β4 ðJensonAlphaÞi,t þ β5 ðEPSÞi,t þ β6 ðROAÞi,t þ β7 ðROEÞi,t þ β8 ðPEÞi,t þ β9 ðIntgTAÞi,t þ β10 ðTobinQÞi,t þ β11 ðBETAÞi,t þ β12 ðSDÞi,t þ β13 ðIndDirPropÞi,t þ β14 ðCACLÞi,t þ β15 ðLnAssetsÞi,t þ β16 ðLnMarkCapÞi,t þ εi,t

ð13Þ

IntgTAi,t ¼ αi,t þ β1 ðDE1Þi,t þ β2 ðDE2Þi,t þ β3 ðMVBVÞi,t þ β4 ðJensonAlphaÞi,t þ β5 ðEPSÞi,t þ β6 ðROAÞi,t þ β7 ðROEÞi,t þ β8 ðRDSalesÞi,t þ β9 ðPEÞi,t þ β10 ðTobinQÞi,t þ β11 ðBETAÞi,t þ β12 ðSDÞi,t þ β13 ðIndDirPropÞi,t þ β14 ðCACLÞi,t þ β15 ðLnAssetsÞi,t þ β16 ðLnMarkCapÞi,t þ εi,t

ð14Þ

TobinQi,t ¼ αi,t þ β1 ðDE1Þi,t þ β2 ðDE2Þi,t þ β3 ðMVBVÞi,t þ β4 ðJensonAlphaÞi,t þ β5 ðEPSÞi,t þ β6 ðROAÞi,t þ β7 ðROEÞi,t þ β8 ðRDSalesÞi,t þ β9 ðIntgTAÞi,t þ β10 ðPEÞi,t þ β11 ðBETAÞi,t þ β12 ðSDÞi,t þ β13 ðIndDirPropÞi,t þ β14 ðCACLÞi,t þ β15 ðLnAssetsÞi,t þ β16 ðLnMarkCapÞi,t þ εi,t

ð15Þ

BETAi,t ¼ αi,t þ β1 ðDE1Þi,t þ β2 ðDE2Þi,t þ β3 ðMVBVÞi,t þ β4 ðJensonAlphaÞi,t þ β5 ðEPSÞi,t þ β6 ðROAÞi,t þ β7 ðROEÞi,t þ β8 ðRDSalesÞi,t þ β9 ðIntgTAÞi,t þ β10 ðTobinQÞi,t þ β11 ðPEÞi,t þ β12 ðSDÞi,t þ β13 ðIndDirPropÞi,t þ β14 ðCACLÞi,t þ β15 ðLnAssetsÞi,t þ β16 ðLnMarkCapÞi,t þ εi,t

ð16Þ

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SDi,t ¼ αi,t þ β1 ðDE1Þi,t þ β2 ðDE2Þi,t þ β3 ðMVBVÞi,t þ β4 ðJensonAlphaÞi,t þ β5 ðEPSÞi,t þ β6 ðROAÞi,t þ β7 ðROEÞi,t þ β8 ðRDSalesÞi,t þ β9 ðIntgTAÞi,t þ β10 ðTobinQÞi,t þ β11 ðBETAÞi,t þ β12 ðPEÞi,t þ β13 ðIndDirPropÞi,t þ β14 ðCACLÞi,t þ β15 ðLnAssetsÞi,t þ β16 ðLnMarkCapÞi,t þ εi,t

ð17Þ

The empirical analysis in this study includes descriptive statistics and multivariate OLS regression analysis by using the SPSS software.

4 Results Table 2 represents the descriptive statistics of the variables used in the analysis. The sample mean values of DE1 is 0.84, implying that for each 1 Euro of the book value of the shareholder’s equity, the sample firms borrow 0.84 € of debt. On the other hand, the mean values of DE2 is 0.36, implying that for each 1 Euro of the market value of the shareholder’s equity, the sample firms borrow 0.36 € of debt. For the accounting performance measures, the mean ROA, ROE, and EPS are 3.87%, 6.35%, and 0.62 €, respectively. Similarly, the mean values of the market Table 2 Descriptive statisticsa (firm years ¼ 323) Variables DE1 DE2 PE MVBV JensonAlpha EPS (€) ROA (%) ROE (%) RDSales (%) IntgTA (%) TobinQ BETA SD IndDirProp (%) CACL Assets (million €)b MarkCap (million €)b

Range 20.68 8.74 542.67 527.77 1.06 11.88 24.93 41.02 36.17 56.80 5.96 2.12 11.35 60 22.87 44,889 36,375

Minimum 0.02 0.01 –161.67 0.02 –0.34 –2.44 –0.45 –2.11 1.25 0.04 0.07 0.14 0.97 40 0.12 12 2.7

Maximum 20.70 8.75 381.00 527.79 0.72 9.44 24.48 38.91 37.42 56.84 6.03 2.26 12.32 100 22.99 44,901 36,378

Mean 0.84 0.36 14.74 3.94 0.04 0.62 3.87 6.35 9.87 13.36 1.92 0.43 2.12 73 1.62 7714 15,356

Standard deviation 2.23 1.69 42.67 40.11 0.14 1.26 14.78 22.61 9.06 11.51 12.85 1.14 1.22 8.22 1.76 362 1697

Source: Compiled by authors The values are coefficients/percentages/Euro b Natural logarithmic values are used in the multivariate OLS regression analysis a

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performance measures including PE, MVBV, and JensenAlpha are 14.74, 3.94, and 0.04, respectively. The value of MVBV ratio higher than 1, implying that on an average the sample firms are over-valued. Similarly, a positive JensenAlpha highlights that the sample firms over-perform when compared to the minimum benchmark return on equity as determined by the CAPM. The mean value of the TobinQ, a hybrid firm performance measure, is 1.92. Similarly, the mean value of the RDSales and IntgTA, the non-financial performance indicators are 9.87% and 13.36%, respectively. For the risk measures, the mean value of BETA and SD is 0.43 and 2.12, respectively. Table 3 highlights the OLS regression analysis results of the dependence of the market performance measures and hybrid performance measure (TobinQ) upon the two leverage variables—DE1 and DE2 and other control variables [Eqs. (7)–(9) and (15)]. The impact of DE1 and DE2 is significantly negative on all the market-based (except for the PE), and hybrid performance measures. The increase in the book, and market value of the equity for a given value of the debt, leads to the decline in the value of both DE1 and DE2, consequently, there is a favorable impact on the MVBV, JensonAlpha, and TobinQ. RDSales affect PE negatively. These findings are in line with those of Hundal (2017). The total risk unfavorably affects market performance measures. The BETA and IndDirProp have been observed to be insignificant. Both firm-size variables—LnMarkCap and LnAssets affect the JensonAlpha positively. Table 4 shows the effect of leverage on accounting performance measures [Eqs. (10)–(12)]. Similar to the findings of Hundal (2017), both DE1 and DE2 affect most of the accounting measures of firm performance unfavorably implying that a higher level of debt leads to a higher level of debt servicing and as a result profit after paying finance costs diminishes and resultantly the accounting performance of firms diminishes. The effect of RDSales and IntgTA on ROA and ROE, respectively, is unfavorable. An interpretation of this finding is that a firm investing in its nonfinancial measures such as R&D and intangible assets can end up sacrificing its short-term profitability. Similarly, a higher level of total risk affects ROA adversely. The effect of market risk, measured by BETA, on the accounting performance measures, is negative. This finding implies that firms facing higher market risk may find a decline in their accounting profits too. The firm size variables–LnAssets and LnMarkCap affect the accounting performance of firms positively. This finding implies that firms with a larger size can utilize their resources efficiently and reap economies of scale and resultantly generate a higher level of profit. On the other hand, IndDirProp affects EPS negatively. Table 5 shows that capital structure does not affect OLS nonfinancial performance [Eqs. (13) and (14)]. Neither DE1 nor DE2 affects intangibility of assets ratio and R&D to sales ratio. The empirical analysis further shows that the market and hybrid performance firm measures affect both nonfinancial performance measures— IntTA and RDSales favorably. An interpretation of this finding is that firms giving a remarkable performance in the stock market consider the nonfinancial performance important too. A possible reason for such a phenomenon is that investors

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Table 3 Effects of leverage on market performance measuresa (firm years ¼ 323) Dependent variables (Constant) DE1 DE2 MVBV JensonAlpha

PE 9.781 (0.581) –0.968 (–0.373) –1.278 (–0.377) 0.109 (0.097) 47.304 (2.098)

PE TobinQ ROA ROE EPS RDSales IntgTA SD BETA CACL LnMarkCap LnAssets IndDirProp R2 DW test statistic

0.978 (0.088) –0.565 (–0.764) 0.777 (0.042) 0.099 (0.039) –103.25 (–1.944) –0.679 (–0.337) –0.777 (–3.643) 6.022 (0.331) –0.289 (–0.162) –0.074 (–0.028) 0.878 (0.307) –1.872 (–0.132) 0.33 1.92

MVBV –0.137 (–0.259) –0.018 (–2.191) –0.092 (–5.737)

0.567 (4.559) 0.000 (0.011) 0.973 (85.724) –1.382 (–9.488) 0.334 (8.187) 0.016 (1.002) 0.007 (0.596) 0.003 (0.276) –0.061 (–6.876) 0.003 (0.251) 0.034 (9.627) 0.004 (0.375) –0.008 (–0.753) 0.002 (0.247) 0.56 2.02

JensonAlpha –0.140 (–1.079) –0.051 (–2.149) –0.038 (–4.866) 0.075 (1.168)

0.001 (2.134) –0.023 (–0.351) 0.357 (4.369) 0.065 (0.884) 0.002 (0.029) 0.086 (0.769) –0.035 (–0.595) 0.046 (5.793) –0.011 (–0.186) 0.068 (1.029) 0.011 (2.206) 0.168 (1.712) 0.039 (0.599) 0.27 1.97

Significant at