Shaping Social Enterprise: Understanding Institutional Context and Influence 1787142515, 9781787142510

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Shaping Social Enterprise Understanding Institutional Context and Influence

For Annalise, Sarah, and Daniel

Shaping Social Enterprise Understanding Institutional Context and Influence

Edited by Janelle A. Kerlin

United Kingdom

North America

Japan

India

Malaysia

China

Contents List of Figures

vii

List of Tables

ix

About the Authors

xiii

Acknowledgments

xvii

Preface xix

Alex Nicholls

CHAPTER 1

The Macro-Institutional Social Enterprise Framework: Introduction and Theoretical Underpinnings Janelle A. Kerlin

CHAPTER 2

An Updated Quantitative Assessment of Kerlin’s Macro-Institutional Social Enterprise Framework Thema Monroe-White and Muhammet Emre Coskun

CHAPTER 3

49

China: The Diffusion of Social Enterprise Innovation: Exported and Imported International Influence Tracy Shicun Cui and Janelle A. Kerlin

CHAPTER 5

27

South Korea: Government Directed Social Enterprise Development: Toward a New Asian Social Enterprise Country Model Bokgyo Jeong

CHAPTER 4

1

79

Romania: Fostering Social Enterprise in a Post-Transitional Context: Caught between Social Enterprise Country Models Mihaela Lambru and Claudia Petrescu

109

v

vi

CONTENTS

CHAPTER 6

Spain: Understanding Social Enterprise Country Models across Time and Sub-Country Regions Ramon Fisac-Garcia and Ana Moreno-Romero

CHAPTER 7

Chile: The Influence of Institutional Holdovers from the Past on the Social Enterprise Country Model Sebastian Gatica

CHAPTER 8

169

Sweden: Tracing Social Enterprise across Different (Social) Spheres: The Interplay among Institutions, Values, and Individual Engagement Malin Gawell

CHAPTER 9

139

199

Zambia: Innate Resource Legacies and Social Enterprise Development: The Impact of Human Agency and Socio-Spatial Context in a Rural Setting Rosemary Chilufya and Janelle A. Kerlin

217

CHAPTER 10 Australia: Understanding Future Social

Enterprise Model Development through Individual-Level Policy Discourse Analysis Chris Mason and Jo Barraket

253

CHAPTER 11 Conclusion: Revising the Macro-Institutional

Social Enterprise Framework Janelle A. Kerlin

Index

277

307

List of Figures Chapter 1 Figure 1

Macro-Institutional Processes and Causal Paths for Models of Social Enterprise (Original). . . . . . . . . . . . . . . . . . .

9

Alter’s Typology of Social Enterprises. . . . .

30

Accumulated Number of Active Certified Social Enterprises. . . . . . . . . . . . . . .

56

Number of Newly Registered and Surviving Social Enterprises from Respective Year. . . .

56

Macro-Institutional Processes and Causal Paths for Models of Social Enterprise. . . . .

64

South Korean Government’s Intent and Its Intended Causal Path. . . . . . . . . . . . .

71

Growth and Trends of Social Enterprise Related Organizations. . . . . . . . . . . . .

83

Figure 2

Diffusion of Innovation by NPI. . . . . . . .

94

Figure 3

Diffusion of Innovation by the British Council. . . . . . . . . . . . . . . . . . . .

97

Social Entrepreneur Program by the British Council. . . . . . . . . . . . . . . . . . . .

99

Dynamics of Convergence and Emergence on Social Enterprises in Chile. . . . . . . . . . .

187

Chapter 2 Figure 1 Chapter 3 Figure 1 Figure 2 Figure 3 Figure 4 Chapter 4 Figure 1

Figure 4 Chapter 7 Figure 1

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LIST OF FIGURES

Chapter 8 Figure 1

Figure 2

The Third Sector and the Welfare Mix: Illustration of Current Shifts in Swedish Policies. . . . . . . . . . . . . . . . . . . .

203

Different Versions of Social Entrepreneurship and Social Enterprises. . . . . . . . . . . . .

206

Type of Resources Accessed. . . . . . . . . .

236

A Revised Macro-Institutional Social Enterprise Framework. . . . . . . . . . . . .

299

Chapter 9 Figure 1 Chapter 11 Figure 1

List of Tables Chapter 1 Table 1

Global Competitiveness Report’s Criteria for Stages of Economic Development. . . . . . .

10

Salamon and Sokolowski’s Models of Civil Society Sector Structure. . . . . . . . . . . .

13

Table 3

Original Country Models of Social Enterprise.

14

Table 4

Macro-Institutions in Five Countries and Associated Social Enterprise Country Models.

15

Social Enterprise Characteristics for Five Countries and Associated Social Enterprise Country Models. . . . . . . . . . . . . . . .

16

Table 1

Informal Institutional Fixed-Effect Models. .

39

Table 2

Reduced Model with Institutional Variables Predicting Social Enterprise. . . . . . . . . .

41

Socioeconomic Data for Countries Including South Korea. . . . . . . . . . . . . . . . . .

68

Social Enterprise Characteristics for Countries Including South Korea.. . . . . . . . . . . .

69

Models of Social Enterprises and Mapping of the South Korean Case. . . . . . . . . . . .

72

Table 1

Socioeconomic Data for Seven Countries. . .

88

Table 2

Main NPI Programs 2006 2012. . . . . . .

92

Table 3

Social Enterprise Country Models and Mapping of the China Model. . . . . . . . .

101

Characteristics of Social Enterprise in China.

102

Table 2

Table 5

Chapter 2

Chapter 3 Table 1 Table 2 Table 3 Chapter 4

Table 4

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x

LIST OF TABLES

Chapter 5 Table 1

Socioeconomic Indicators for Central and Eastern European Countries (2010). . . . . .

115

Social Economy Actors in Romania Number, Surplus/Profit, Employees in 2010. .

120

Table 3

Economic Indicators for NGOs. . . . . . . .

123

Table 4

Economic Indicators for Mutual Aid Associations. . . . . . . . . . . . . . . . . .

126

Economic Indicators for Cooperatives. . . . .

128

Table 1

RCI 2013 Scores for Spanish Regions. . . . .

153

Table 2

Dimensions of the Civil Society Sector in Spain. . . . . . . . . . . . . . . . . . . . .

156

Social Economy Entities in Catalonia and the Basque Country. . . . . . . . . . . . . . . .

159

Social Enterprise Characteristics for Spain.. .

161

Table 1

Civil Societies with Liberal Patterns. . . . . .

179

Table 2

Institutional Context of Chile for the Emergence of Social Enterprises in 2010.. . .

181

The ABC Approach for Social Enterprises in Chile. . . . . . . . . . . . . . . . . . . . .

192

Criteria for Regional Sampling of Case Study Regions. . . . . . . . . . . . . . . . . . . .

227

Social and Economic Information on Zambia. . . . . . . . . . . . . . . . . . . .

229

Table 3

Sector of the Organization.. . . . . . . . . .

232

Table 4

Year of Establishment. . . . . . . . . . . . .

233

Table 5

Mission of Organization.. . . . . . . . . . .

234

Table 2

Table 5 Chapter 6

Table 3 Table 4 Chapter 7

Table 3 Chapter 9 Table 1 Table 2

List of Tables

xi

Table 1

Social Enterprise Characteristics for Australia.

263

Table 2

Socioeconomic Data for Australia. . . . . . .

265

Table 3

Sources for Textual Analysis. . . . . . . . .

267

Overview of Country Models of Social Enterprise Revised. . . . . . . . . . . . . . .

301

Chapter 10

Chapter 11 Table 1

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About the Authors Jo Barraket is the Director of the Centre for Social Impact and Professor at Swinburne University of Technology in Australia. Her research interests include social enterprise, social innovation, and the role of the social economy in new public governance. Rosemary Chilufya, originally from Zambia, is currently a doctoral student at the University of Huddersfield, United Kingdom, and a Special Research Fellow at the Copperbelt University in Zambia. Her research interests center around human security, regional development, and social entrepreneurship. Muhammet Emre Coskun is a doctoral candidate in the Department of Public Management and Policy at Georgia State University, USA. He conducts quantitative research on international NGOs and their poverty impact as well as on institutions and social enterprise. Tracy Shicun Cui, originally from China, is currently a doctoral student in the Department of Public Management and Policy at Georgia State University, USA. Her research focuses on nonprofit finance and social enterprise in China. Ramon Fisac-Garcia is Assistant Professor in the Business Administration Department at the Universidad Politecnica de Madrid in Spain. He conducts research on organizational analysis, performance improvement, and impact assessments of social enterprises. Sebastian Gatica is Adjunct Assistant Professor and Director of The Social Innovation Lab in the School of Management at the Pontificia Universidad Católica de Chile. He was an Ashoka Fellow and advisor to the Chilean Fourth Sector Enterprise Commission.

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ABOUT THE AUTHORS

Malin Gawell is Associated Professor at Södertörn University in Stockholm, Sweden. Her primary research interests are in social and societal entrepreneurship, social enterprise and civil society. Her research relates to individuals, organization as well as policy levels. Bokgyo Jeong, originally from South Korea, received his PhD from the University of Pittsburgh and is currently an Assistant Professor at Kean University in New Jersey, USA. His research interests include nonprofit management, social enterprise/economy, international development, and collaboration between international organizations and NGOs. Janelle A. Kerlin is Associate Professor in the Department of Public Management and Policy at Georgia State University, USA. Her research interests include comparative social enterprise, nonprofit commercial revenue, and international NGOs. She is an associate editor for the Social Enterprise Journal. Mihaela Lambru, PhD, is Professor in the Faculty of Sociology and Social Work, University of Bucharest, Romania. Her research focuses on the development of the third sector, social enterprise, and worker cooperatives in Romania and Eastern and Central Europe. Chris Mason, PhD, is Senior Research Fellow with the Centre for Social Impact at Swinburne University of Technology in Australia. His research interests include social enterprise, policy development, discourse, identity, and corporate social responsibility. He is an associate editor of the Social Enterprise Journal. Thema Monroe-White is the Director of Research and Evaluation at VentureWell, Atlanta, USA, where she initiates and oversees research and evaluation in support of programs, grant proposals, and thought leadership initiatives. She holds a PhD in Science, Technology, and Innovation Policy from the Georgia Institute of Technology, USA. Ana Moreno-Romero is Associate Professor in the Industrial Organization Department at the Universidad Politecnica de Madrid in Spain. Her research examines the organization of work, human resources, corporate social responsibility, and networked organizations. Alex Nicholls is Professor of Social Entrepreneurship at the Said Business School, University of Oxford, United Kingdom. His research interests include a range of topics within social

About the Authors

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entrepreneurship and social innovation. He is editor of the Journal of Social Entrepreneurship. Claudia Petrescu, PhD, is a principal researcher in The Research Institute for Quality of Life at the Romanian Academy of Science, Romania. Her research examines community development, the social economy, the third sector, and social enterprise in Romania.

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Acknowledgments Numerous people have participated in the development of this volume both directly and indirectly over the course of several years. What started as a conversation with Sebastian Gatica from Chile at the EMES social enterprise conference in Europe evolved over time into a book idea that took on a life of its own. At that same conference, I met Claudia Petrescu and Mihaela Lambru who expressed an immediate interest in providing the Romanian experience with institutions and the development of social enterprise. Bokgyo Jeong was also eager to discuss how the South Korean case leant itself to a different model for social enterprise, a discussion which he evolved into the in-depth paper on the topic found in this volume. Along the way Bob Doherty, editor of the Social Enterprise Journal, was gracious enough to support a special issue of the journal devoted to critiquing the Macro-Institutional Social Enterprise (MISE) framework I had developed. The issue brought the first five papers into the project, versions of which are in this volume. The special issue was published in August 2015 and included four papers that were chosen as a result of a call for papers. Through this process, papers on Chile by Gatica and South Korea by Jeong were published as well as a paper on Spain by Ramon Fisac-Garcia and Ana Moreno-Romero and another on Australia by Chris Mason and Jo Barraket. The fifth paper in the special issue was provided by Thema Monroe-White with the help of myself and Sandy Zook my graduate research assistant. Monroe-White had tested the MISE framework in multi-level regression analysis as a part of her dissertation and was willing to publish the results for the first time in the special issue. The call brought in more papers than could be published in the special issue and thus the book includes both the five papers from the issue as well as papers on Romania by Lambru and Petrescu and Sweden by Malin Gawell who had also expressed interest. The book also contains two chapters led by PhD students with my assistance. I met Rosemary Chilufya from Zambia xvii

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ACKNOWLEDGMENTS

at the International Social Innovation Research conference in the United Kingdom, where the papers from the special issue were presented. At about the same time, Tracy Shicun Cui from China came along as my research assistant and graduate student to delve into the subject in her home country. Also newly published here is a paper in large part undertaken by Muhammet Emre Coskun that updates the work of MonroeWhite. He is also my research assistant and a graduate student in my department. He has my gratitude for the many hours he devoted to setting up and running the multi-level regression analysis needed to capture elements not included in the first version. I am also grateful to Alex Nicholls who showed interest in the book project from the start and was gracious enough to provide the preface. It goes without saying that those who reviewed papers for the special issue of the Social Enterprise Journal as well as those who provided editing of final drafts for the book are much appreciated. In particular, my Department of Public Management and Policy at Georgia State University provided financial support for the many hours of graduate research assistance. My special thanks goes to Emerald Press for their support through both the publication of the special issue of the Social Enterprise Journal as well as this volume. My heartfelt gratitude goes to my husband who was supportive throughout the process especially with his help of our three children.

Preface Although the phenomenon is anything but new, scholarly enquiry into social entrepreneurship and social enterprise began in earnest in the early 2000s (Nicholls, 2006). From the beginning, the field was framed as an international, indeed global, set of activities addressing a wide range of social issues across many different contexts (Bornstein, 2004). Several important international support networks evolved during this period too aiming at building networks of social entrepreneurs, linking them to supportive institutions and resources, and celebrating their work. Ashoka, the Schwab Foundation for Social Entrepreneurship, and the Skoll Foundation all aimed to have a global reach focused, first, on developing countries and, subsequently, also embracing social entrepreneurship/enterprise in the rich, developed nations (see Nicholls, 2010). This important work was often organized regionally or via country-specific organizational structures. However, despite this, there has been relatively little work done on examining the contextual nuances and comparative institutions of social entrepreneurship/social enterprise within and across countries. Partly, this has been a legacy of a fundamental assumption that was made early on in the evolution of the study of social entrepreneurship/social enterprise namely, that the key, determining, variable of its impact, success and distinctiveness lay in it representing a new form of entrepreneurship. As a consequence, academic centers and initiatives designed to study, teach, and popularize social entrepreneurship/social enterprise emerged in business schools around the world a setting thought to be best suited to research entrepreneurship. However, over time the assumption that entrepreneurship was the key differentiator of social entrepreneurship/social enterprise has been increasingly challenged and it is now as common to find scholars, practitioners, and policy-makers exploring the meanings and implications of the social in this emergent field. One aspect of this new line of research has been a greater focus on contexts, eco-systems, and institutions (Bloom & Chatterji, 2009). xix

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But, what is meant by the social here? Of course, this is a slippery and potentially all-encompassing term that can disappear up its own ontology. However, research suggests that for social entrepreneurship/social enterprise, at least, the social refers to distinctive (intended) outcomes and processes developed to address intransigent or systemic failures in the provision of welfare goods and services and, in some cases, of basic economic development. This means that social entrepreneurship/social enterprise can best be understood as outcome and process innovation addressing social market failures (Mair, Martí & Ventresca, 2012). The types of innovation developed by social entrepreneurs vary considerably from macro-level, disruptive examples (microfinance, Fair Trade) that are, in fact, quite rare to more modest, meso- and micro-level, action that focuses on sector-specific issues (low cost solar energy, mobile ante-natal clinics, subsidized cataract surgeries). In the latter case, innovation is often a consequence of developing organizational hybridity the blending together of logics, discourses, and practices from the third sector, government, and the commercial market as strategic action. Such hybridity-as-strategy can allow new insights into key social problems that, in turn, can drive new solutions that are not open to the status quo of siloed, sectoral action (Battilana & Dorado, 2010). When hybridity focuses on addressing the effects of unjust or inequitable social relations, then such activity has become known as social innovation a more systemic and structural set of actions that serves to frame, but only rarely represent, the more grass-roots work of most social entrepreneurs (Nicholls & Murdock, 2011; Nicholls & Ziegler, 2015). So how can the social within social entrepreneurship/social enterprise be best understood and analyzed? As was noted above, it has been increasingly recognized that the social in this field is contingent and contextual differing in its boundaries and defining features in different cultural, economic, and geographic settings. One important example of this can been seen in the development of a coordinated policy response across governments to develop the social impact investing market (see Nicholls, Emerson & Paton, 2015). Pioneered by the UK government in the 2000s, the value of a policy agenda for social impact investing across nations was established in July 2013 at a meeting hosted by the government in London during the G8 Summit chaired by the United Kingdom. One key outcome was the establishment of a Social Impact Investment Taskforce comprising the G8 countries minus Russia and with Australia included.

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This Taskforce worked for a year on building a common set of policy objectives across its member states whilst always recognizing significant local differences in policy implementation. The Taskforce reported back on a raft of issues in 2014 and was considered sufficiently successful to be followed up with a larger Global Social Impact Investment Taskforce encompassing more of the G20 countries and others in 2015/2016. In late 2016, the World Economic Forum published the results of survey data exploring the Top 10 best countries in which to develop and practice social entrepreneurship (WEF, 2016). This research provided an interesting example of comparative country analysis in this field. The data were extracted from a survey conducted by the Thomson Reuters Foundation in 45 of the world’s biggest economies as ranked by the World Bank. Each of the country surveys contacted 20 experts focused on social entrepreneurship, including academics, social entrepreneurs, investors, policy-makers, and support network staff. In total, 880 experts were surveyed with 619 responses of the respondents, 48 percent were women. The questions asked explored the funding, policy support, market development, and access to talent for social entrepreneurship/social enterprise in each country. The survey analysis concluded that the United States was the “best” country for social entrepreneurship followed by Canada and the United Kingdom. However, the research did not attempt to explain why country contexts differed nor how they could be changed better to suit the development of social entrepreneurship/social enterprise. In the light of these praxis-focused examples, scholarly work on the comparative country contexts of social entrepreneurship/ enterprise has been surprisingly limited to date. However, it is in the context of this considerable research gap that the work of Professor Kerlin fits. Kerlin pioneered comparative regional analysis of social enterprise when she edited her groundbreaking book Social Enterprise: A Global Comparison in 2009. This widely cited collection built upon an important body of research papers already published by Kerlin (2006) and quickly established itself as the first and most authoritative book on this subject. Central to the research was the development of a MacroInstitutional Social Enterprise (MISE) Framework that considered the roles of cultural, government, economic, and civil society factors and their inter-relationships as contextual drivers of diversity in the development of social enterprise in different countries and regions. The research applied the MISE Framework to

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establish a series of country/regional models of social enterprise built upon distinctive articulations of the same, key, institutional factors. The collection considered eight contexts: Western Europe, East Central Europe, South East Asia, the United States, Zimbabwe and Zambia, Argentina and Japan. The new book presented here builds upon the legacy of Kerlin’s (2009) work to review and revise the MISE Framework and extend the country analysis to seven new territories: South Korea, China, Romania, Spain, Chile, Sweden, and Australia. In addition, the work on Zambia that was begun in the 2009 volume is revisited and revised here. This new research tests Kerlin’s theoretically and empirically grounded framework systematically to look at how informal and formal macro-institutions and micro-level stakeholders together shape social enterprise country models. There is a greater emphasis here on culture as an informal institution than in the 2009 work. Moreover, the country models have been enhanced with two new types based on Asian country analysis. Overall, this new book acknowledges the role of micro-level actors more fully than before. As a consequence, this work represents a significant step forward in helping frame how to analyze and understand the evidenced empirical reality of the many divergent manifestations of social enterprise globally. This work has important implications for the future institutionalization of social entrepreneurship/social enterprise globally as its provides vital guidance to policy-makers, potential funders, and aspiring social entrepreneurs in terms of how best to address “wicked problems” in complex contexts. Professor Kerlin’s work also provides rich material for further academic research and study. The phenomenon of social entrepreneurship/social enterprise is increasingly recognized as offering an important contribution to wider attempts at addressing the United Nations Sustainable Development Goals (British Council, 2016; UNDP, 2016). In order for social entrepreneurship/social enterprise to fulfill its promise in improving the lives of millions, its adaptability and contextual flexibility needs to be understood, codified, and institutionalized. This book represents an important contribution to this endeavor. Alex Nicholls Professor of Social Entrepreneurship Said Business School University of Oxford

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References Battilana, J., & Dorado, S. (2010). Building sustainable hybrid organizations: The case of commercial microfinance organizations. Academy of Management Journal, 53(6), 1419 1440. Bloom, P., & Chatterji, A. (2009). Scaling social entrepreneurial impact. California Management Review, 51(3), 114 133. Bornstein, D. (2004). How to change the world: Social entrepreneurs and the power of new ideas. Oxford: Oxford University Press. British Council. (2016). Social enterprises step up to tackle the SDGs. Retrieved from https://www.britishcouncil.org/society/social enterprise/news events/news social enterprises tackle SDGs. Accessed on September 30, 2016. Kerlin, J. A. (2006). Social enterprise in the United States and Europe: Understanding and learning from the differences. Voluntas: International Journal of Voluntary and Nonprofit Organizations, 17(3), 246 262. Kerlin, J. A. (2009). Social enterprise: A global comparison. Lebanon, NH: Tufts University Press. Mair, J., Martí, I., & Ventresca, M. (2012). Building inclusive markets in rural Bangladesh: How intermediaries work institutional voids. Academy of Management Journal, 55(4), 819 850. Nicholls, A. (Ed.). (2006). Social entrepreneurship: New models of sustainable social change. Oxford: Oxford University Press. Nicholls, A. (2010). The legitimacy of social entrepreneurship: Reflexive isomor phism in a pre paradigmatic field. Entrepreneurship Theory and Practice, 34(4), 611 633. Nicholls, A., Emerson, J., & Paton, R. (2015). Social Finance. Oxford: Oxford University Press. Nicholls, A., & Murdock, A. (Eds.). (2011). Social innovation: Blurring bound aries to reconfigure markets. Basingstoke: Springer. Nicholls, A., & Ziegler, R. (2015). An extended social grid model for the study of marginalization processes and social innovation. CRESSI Working Paper 2/2015. UNDP (United Nations Development Programme). (2016). Sustainable develop ment goals. Retrieved from http://www.undp.org/content/undp/en/home/sustain able development goals.html. Accessed on September 30, 2016. WEF (World Economic Forum). (2016). These are the best economies to be a social entrepreneur. Retrieved from https://www.weforum.org/agenda/2016/09/ these are the best countries to be a social entrepreneur/. Accessed on September 30, 2016.

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CHAPTER

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The MacroInstitutional Social Enterprise Framework: Introduction and Theoretical Underpinnings Janelle A. Kerlin

T

he concept of social enterprise continues to raise the interest of people around the world. From practitioners to policymakers, activists, and funders of the social good, social enterprise has captured the imagination and hopes of a growing cross-section of society that seeks to find a more sustainable answer to the problems of society (Lundstrom, Zhou, von Friedrichs, & Sundin, 2014). Though definitional issues remain, in practice, many have simply seized upon its core components: market-based revenue generation with social benefit as a primary aim. Indeed, a vast and growing number of diverse activities, programs, and organizations actualize this concept on a daily basis across the globe. With its seemingly limitless opportunities and enduring fascination, the question of what makes social enterprises what they are in today’s societies has become a central question. In an attempt to address this question, this volume

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JANELLE A. KERLIN

considers the influence on social enterprise of some of societies’ most powerful forces: institutions. Institutions and their role in the making of particularly situations of poverty and poverty alleviation have gained increasing attention as scholars seek to understand root causes (Acemoglu & Robinson, 2012; Banerjee & Duflo, 2011; Hazenberg, BajwaPatel, Mazzei, Roy, & Baglioni, 2016; Mair, Martí, & Ventresca, 2012; Roy, McHugh, Huckfield, Kay, & Donaldson, 2015). Institutions can range from the largest macro-level organizations found on national and international levels to the smallest entities on the local level. These can include the more obvious national, regional, and local governments as well as the less obvious institutions of civil society, the market economy, and entities working on an international level such as the European Union. In addition to these formal institutions, the informal institution of culture, expressed in the values, norms, and beliefs of societies, is also of interest. Indeed, there is evidence that all of these institutions help shape many aspects of social enterprises from their organizational form to their governance structure, program activities, funding strategies, outcomes, and many others even their incidence in a country (Kerlin, 2009, 2013, 2015; Stephan, Uhlaner, & Stride, 2015). Given that these institutions look different in different countries, it follows that the social enterprises they influence will look different across countries as well. Understanding how institutions shape social enterprises can not only help explain why and how they look different in different places, but also assist in knowing where to intervene to support their work in diverse contexts. Indeed, understanding social enterprise has become a preoccupation for an increasing number of researchers from a growing number of fields (Doherty, Haugh, & Lyon, 2014; Lundstrom et al., 2014). Until recently however, the only research that discussed the influence of institutions on the development of social enterprise was qualitative case studies that often compared social enterprise across countries or regions (Borzaga & Defourny, 2001; Chell, Nicolopoulou, & Karata¸s-Özkan, 2010; Dacanay, 2004; Defourny & Kim, 2011; Defourny & Nyssens, 2010; Galera & Borzaga, 2009; Kerlin, 2006, 2009; Mair et al., 2012; Nyssens, 2006). Based on this work, there is now a general consensus both within and without this group that differences in social enterprise across countries can be explained in part by variations in institutional context (see also Austin, Stevenson, & Wei-Skillern, 2006; Dacin, Dacin, & Matear, 2010; Defourny & Nyssens, 2016; Young, Searing, & Brewer, 2016).

The Macro-Institutional Social Enterprise Framework

3

However, much remains to be done in this area specifically in terms of systematic research to identify patterns of institutional influence across countries and their discrete influence on social enterprise. Though there was early reference to the influence of government, market, and civil society institutions, these were not examined systematically to understand patterns across countries until recently. Kerlin (2009) made a first attempt with her preliminary typology of social enterprise country models based on qualitative country and regional studies in her edited book, Social Enterprise: A Global Comparison. However, this foundational study was lacking in theoretical and quantitative rigor and the work of other authors was in its infancy as well. Indeed, based on an extensive review of research on hybrid organizations, Doherty et al. (2014, p. 429) suggested that the field address among other questions: “To what extent have different institutional frameworks and contexts supported or discouraged the establishment of hybrid organizations?” Unfortunately, research on this and related questions has moved slowly in part due to a lack of data but also a reliance on one or two approaches to studying the phenomenon. This included either qualitative country case studies of social enterprise as discussed above, theoretical musings on the topic (Kerlin, 2013), or, with the newly available global entrepreneurship monitor (GEM) data (Lepoutre, Justo, Terjesen, & Bosma, 2013), advanced quantitative analyses that attempt to link country-level variation in institutions with variation in social enterprise that sometimes involved testing of basic theory (Estrin, Mickiewicz, & Stephan, 2013; Hechavarría, 2016; Hoogendoorn & Hartog, 2011; Puumalainen, Sjogren, Pasi, & Barraket, 2015; Stephan et al., 2015). What was lacking was a framework approach that rigorously incorporates all three: theoretical development of a framework tested by qualitative and quantitative empirical research that mutually informs one another (Haugh, 2012). To address this weakness in the research, this volume proposes to test a theoretically-based framework through quantitative and qualitative research with the goal of creating a tool that identifies different configurations of informal and formal macro-institutions that shape specific social enterprise country models. Indeed, the focus of this book is Kerlin’s Macro-Institutional Social Enterprise (MISE) framework originally introduced in an academic journal article in 2013 (Kerlin, 2013). The article first established the theoretical underpinnings for the framework by drawing on the theory of historical institutionalism, a discussion

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briefly reviewed in this chapter. Based on this, it described and illustrated apparent causal paths between major socioeconomic institutions that appear to influence the development of social enterprise in countries. This is also described below. To preliminarily test the framework, the article included limited case studies of five countries which showed that socioeconomic country-level data representing the institutions matched in a predictable fashion with varying characteristics of the social enterprise phenomenon in those countries. Social enterprise models for each type of country social enterprise situation were then created. To further test the MISE framework, Kerlin solicited social enterprise researchers from around the world through a call for papers to apply the framework to their countries and provide a qualitative critique of it in the process. Four country critiques were selected from this process. Another researcher, Thema Monroe-White, used multilevel regression analysis to run an initial quantitative test of the framework drawing on the GEM data. Though missing data on civil society, the quantitative analysis showed that specific configurations of macro-level institutions could explain a significant part of the variance in social enterprise across countries. The four country critiques and the quantitative critique were published in a special issue of the Social Enterprise Journal edited by Kerlin in 2015 (Kerlin, 2015). This volume picks up this research stream by not only including the four qualitative country critiques (South Korea, Spain, Australia, Chile) from the Social Enterprise Journal special issue but by also adding four new country critiques of the framework (Sweden, China, Zambia, Romania). With the help of Muhammet Emre Coskun, it also updates the quantitative analysis by rerunning it with newly available civil society data as reviewed in Chapter 2. The concluding chapter of this book then draws on the critiques to revise the MISE framework and associated social enterprise country models. The newly revised framework is therefore published here for the first time.

Understanding Terms Before proceeding further, we clarify here some of the commonly used terms in the book. The first term, as expected, is social enterprise. We use a broad definition to capture the large variation in what is considered social enterprise in the countries in this

The Macro-Institutional Social Enterprise Framework

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volume and elsewhere. Following Kerlin (2009), we use the definition of any market-based approach to address social issues where social benefit is a primary aim and a business source of revenue provides support for an activity or organization. We assume that environmental concerns are subsumed in this definition. Generally speaking, we ascribe to a view that allows for more narrow definitions of social enterprise to be crafted at the country level to accommodate different contextual forces that are shaping it in the first order. Other terms involve the broader concept of institutions. We use a definition of institutions by Scott (2008, p. 49) that encompasses both formal and informal structures that have achieved a high level of resilience: “Institutions are comprised of regulative, normative, and cultural-cognitive elements that, together with associated activities and resources, provide stability and meaning to social life.” Formal institutions are, “structures of codified and explicit rules and standards that shape interaction among societal members” (North, 1990 in Hechavarría, 2016, p. 1026). Informal institutions are “enduring systems of shared meanings and collective understandings that, while not codified into documented rules and standards, reflect a socially constructed reality that shapes cohesion and coordination among individuals in a society” (Scott, 2005 in Hechavarría, 2016, p. 1026). Importantly, North (1990) proposes that a country’s culture is a reflection of its informal institutions. Also relevant from sociology is the idea that the logic and rationale underlying formal institutions (seen as solutions to societal problems) are based in informal institutions (North, 1990; Scott, 2005). Thus, we share the view that cultural values undergird and shape formal institutions. In this work, we consider both formal institutions and informal cultural institutions on three levels of society: macro, meso, and micro. Drawing from political science, macro-level institutions include government, economy, and civil society presence on a national-level and macro-level cultural values are those that can be isolated at a country level. Meso-level institutions are regional governments including provinces and counties as well as large municipalities that often have these designations (Keating, 2013). Meso-level institutions can also be regional economies and regional-level civil society actors such as federations, networks, and capacity-building intermediaries that support and connect micro-level organizations among themselves and with higher order entities (Mair et al., 2012; Shea, 2011). Micro-level institutions are local-level governments, civil society, and economies.

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We use the term “micro-level stakeholders” to include both individuals and local organizations (Hazenberg et al., 2016). Finally, though varying cultural values are found on the meso- and micro-levels we find that ‘meso- and micro-level intangible resources,’ as we term them, to be important and prominent manifestations of the values on these levels and thus our focus. These intangible resources include social capital, community resiliency, and mutual dependency among others (Putnam, 1993). Much of our orientation here was informed by details found in the qualitative country chapters and summarized in the concluding chapter.

The Theory of Historical Institutionalism1 The MISE approach proposes that macro-institutions and processes can account for a large part of the variation in social enterprise across different countries. This is in line with the theory of historical institutionalism which suggests that institutions, both formal and informal, can create causal paths whereby the development of newer institutions is shaped by both the constraints and supports offered by prior and present institutions. This approach to institutions also emphasizes the importance of underlying power relationships, both in terms of how power is involved in the creation of institutions and how institutions then create and structure power in different ways. Specifically, historical institutionalism asserts that “Effective institutions influence at the individual as well as the collective level beliefs, normative commitments, and preferences. Their major effect at the macro-level is to create and maintain power disparities and to broadly structure shared and antagonistic interests” (Rueschemeyer, 2009, p. 207). Power here is therefore understood to support the continuing existence of institutions, but also to condition disparities that may ultimately work to shift power to previously subordinate groups, the latter providing the explanation for changes that occur in institutions over time (Mahoney, 2003).

1

Parts of this and the following section are excerpted from Kerlin (2013).

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In applying it to social enterprise, the theory suggests that current institutions largely responsible for shaping different country models of social enterprise, initially arose from a rich mix of culture, local (including social classes), regional and global hierarchies, and political-economic histories. These elements structured the development of the present day state, which then helped shape the current economic situation and civil society. In the following discussion, we draw on theory that shows how antecedent events and processes shaped the type of state in power. We then discuss research on how the state in turn influences economic development and civil society. The question of how states come to be democratic or authoritarian in nature is addressed by many social scientists in the comparative historical analysis tradition (Mahoney, 2003). Skocpol’s (1979) States and Social Revolutions, for example, finds three necessary and sufficient conditions for social revolutions: “international pressure from a more advanced state or states; economic or political elites who had the power to resist state-led reforms and create a political crisis; and organizations (either village or party) that were capable of mobilizing peasants for popular uprisings against local authorities” (Goldstone, 2003, p. 64). Another important work relating democracy and economy is Rueschemeyer, Stephens, and Stephens’ (1992) Capitalist Development and Democracy, which finds that capitalist development is associated with democracy due to its alteration of the balance of power between the working class and the landed elite. Theorists have also long supported the idea that institutions at meso- and micro-levels, which in this case include social enterprise, business, and civil society organizations, are highly structured by state institutions and policies. As Rueschemeyer (2009) states: Taken together, the effects of purposeful state policies (even if they may often have unintended or not fully intended outcomes) and the indirect, Tocquevillean consequences of the very presence of state structures and policies leave no doubt that states and state-society relations constitute a powerful and influential environment for social and economic dynamics at the meso-and microlevels of social life. (p. 258) Indeed, authors writing within the specific fields of business and civil society often point to the importance of state institutions and policies in shaping their respective sectors over time.

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In terms of business, Baumol (1990) questions the prevailing understanding about numbers of entrepreneurs and their effect on economic growth by showing that productive entrepreneurship (as opposed to unproductive black market or rent seeking) is likely determined by the rules of society. His hypothesis is that “it is the set of rules (and not the supply of entrepreneurs or the nature of their objectives) that undergoes significant changes from one period to another and helps to dictate the ultimate effect on the economy via the allocation of entrepreneurial resources” (Baumol, 1990, p. 894) (parentheses added). Using a historical approach, he provides evidence from four periods in history that institutions, rules, and norms in societies are a determining factor in the kind of entrepreneurship and economic development a society experiences. Most of these institutions and rules are generated by those governing society. On the civil society side, in a key statement on the influence of democratic versus authoritarian governance on civil society, Salamon and Sokolowski (2009) summarize their comparative historical analysis of the sector: In sum, the key dimension that shapes the state-civil society relationship is democratic governance. The presence of such governance protects the civil sector from arbitrary state control and repressions, thus allowing it to function … the absence of democratic governance, however, entails authoritarian measures that governments take to restrain political opposition which impede the functioning and development of the civil society sector. (p. 26)

The Original MISE Framework Based on the preceding discussion, the MISE framework proposes that the state ultimately plays a key role in understanding a country’s social enterprise model. Indeed, the preceding literature lends significant support to the idea that, due to government’s connection to civil society and the economy which influence social enterprise, country models for social enterprise may be indirectly shaped to a great degree by what government chooses to do and not to do over time. Figure 1 shows the original MISE framework which illustrates the links between the state and economic stages and models of civil society, which are then linked to

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Table 1: Global Competitiveness Report’s Criteria for Stages of Economic Development. GDP per capita (in US$) Stage 1: Factor driven

17,000

OR If 100% of a country’s total exports are in mineral goodsa the country is assumed to be in the Factor Driven Stage (if over 70%, the GDP based stage rating is adjusted downwards.)

Source: Adapted from Sala i Martin et al. (2010, p. 10, Table 2). a Measured using a five year average 2003 2007. Total exports include goods and services. Mineral goods include crude oil, gas, other petroleum products, metal ores and other minerals, liquefied gas, coal, and precious stones. For addi tional explanation, see Sala i Martin et al. (2009, p. 42, footnote 24).

The factor-driven stage is characterized by reliance on the export of mineral goods and poor supportive policies and infrastructure. The efficiency-driven stage is characterized by industrialization where productive efficiency is expanded and product quality improved, both facilitated by improving state policies. The innovation-driven stage is found in countries where a high standard of living and growth is supported by the continued introduction of unique and innovative products in a sophisticated business environment. Though largely categorized on the basis of GDP per capita, each individual country assessment shows how strengths and weaknesses in the country’s 12 pillars are often indicative of that country’s GDP and further helps explain the country’s current stage of economic development (Sala-i-Martin, Blanke, Hanouz, Geiger, & Mia, 2010). Though the GCR categorization is currently viewed as one of the most comprehensive cross-country economic comparisons hence its inclusion in this study we acknowledge its limitations including its linear determinism and failure to also recognize the influence a country’s economic development can have on its institutional framework. The connection between the economy and entrepreneurship is key for understanding how an economy can influence social enterprise activity. The GEM Report for 2009 (Bosma & Levie, 2010) describes entrepreneurship at the different stages of

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economic development. Of particular interest to the framework, they find that for factor-driven economies the decline in agricultural work and movement of workers to extractive industries results in an oversupply of labor that leads to subsistence entrepreneurship. Indeed, the report finds that this kind of selfemployment driven by necessity tends to be more prominent in less developed economies. For efficiency-driven economies, the move toward large-scale industrialization for increased productivity goes along with national economic policies that increasingly favor large businesses. Favorable conditions for emerging economic and financial institutions and openings in industrial supply chains support the development of entrepreneurship in small- and medium-sized manufacturing sectors. In innovationdriven economies, increasing wealth and desires of high-income societies support the expansion of the service sector at the same time, as knowledge and research and development institutions support the aspirations of innovative entrepreneurs who are then willing to challenge larger, established economic players.

A Side Note on Culture and Entrepreneurship Given the broad nature of culture, this research preliminarily explores the two aspects discussed in the culture literature deemed most likely to influence social enterprise: level of in-group collectivism (vs. individualism) and level of uncertainty avoidance in terms of what a society values. In particular, this research takes the view supported by Tiessen (1997) that collectivism and individualism each support different key functions of entrepreneurialism. While the literature has long supported the idea that individualism supports entrepreneurial behavior broadly construed, Tiessen (1997) argues that individualism specifically supports the generation of variety through innovation (Shane, 1992, 1993), while collectivism supports the leveraging of resources internally and through external ties. Both the generation of new ideas and the ability to leverage resources are key to economic success on a societal level, which helps explain why some largely collectivist countries (the Asian tigers for example) have experienced economic success (Franke, Hofstede, & Bond, 1991). Low levels of uncertainty avoidance have also been associated with innovation (Shane, 1993). Thus, the cultural aspects

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discussed here influence two different functions of entrepreneurship innovation and networked resources each of which has a positive effect on economic activity.

From Government (and Economy) to Civil Society, Empirically Government actions also appear to be a leading factor shaping civil societies around the world. Based on two decades of empirical research, Salamon and Sokolowski’s (2010) models of civil society sectors differentiate five different types (Table 2). The first three types, liberal, welfare partnership, and social democratic, are all found in developed countries and to a significant degree are shaped by the structure of the welfare state. The last two types, deferred democratization and traditional, are influenced to a lesser extent by the welfare state and more so by identifying characteristics of other aspects of government, including its absence in certain spheres. The economy is inherently important in the discussion to the degree that it makes possible the different types of welfare states or does not provide resources for one. In the latter situation, international aid may fill the gap, which has its own influence on civil society and ultimately social enterprise.

From Economy and Civil Society to the Original Country Models of Social Enterprise In Table 3, the typologies for economic development and civil society are combined to create models for social enterprise that incorporate how both contexts shape the organizational patterns for social enterprise in a given country. Models were identified only for those cross-sections between the two typologies where countries actually fell. The cross-sections where only one or two countries fell were labeled “transitional” (these countries were often identified as being in transition in terms of either their economy or civil society). The specific characteristics of social enterprise were drawn from the descriptions of social enterprise found in Kerlin (2009) for countries in the particular models (additional sources used are cited in the model descriptions). These models

Model

I. Liberal

Dimension Workforce size

Volunteer share

Government support

Philanthropic support

Large

Medium high

Medium small

Medium high

Expressive share Smaller than service

II. Welfare partnership

Large

Low medium

High

Low

Smaller than service

III. Social democratic

Large

High

Medium

Medium

Larger than service

IV. Deferred democratization

Small

Low

Low

Limited Advocacy

V. Traditional

Small

Medium high

Low

Medium

Source: Salamon and Sokolowski (2010). Note: Defining characteristics are shaded.

The Macro-Institutional Social Enterprise Framework

Table 2: Salamon and Sokolowski’s Models of Civil Society Sector Structure.

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14

Table 3: Original Country Models of Social Enterprise. Economy Factor driven

Efficiency driven

Innovation driven

Civil society Liberal

Autonomous Diverse E.g., United States

Welfare partnership

Dependent Focused E.g., Italy, Germany

Social democratic

Enmeshed Focused E.g., Sweden, Austria

Deferred democratization

Traditional

Autonomous Mutualism E.g., Argentina, Ukraine Sustainable Subsistence E.g., Zimbabwe, Uganda

(transitional) E.g., Slovak Republic

(transitional) E.g., South Africa (B)

B = Borderline country for model of civil society.

are meant to function as ideal types for social enterprise. Thus, in some cases countries may diverge somewhat from outlined characteristics though still be considered largely aligned with the indicated model. The framework can be applied to a country by combining socioeconomic data on macro-level institutions for the country (Table 4) with the characteristics of social enterprise for the same country (Table 5). Written descriptions of the original social enterprise country models follow. For the Sustainable Subsistence model, social enterprise is characterized by individualized small group efforts of entrepreneurs to provide poverty relief through subsistence employment for themselves and their families. These activities are supported by international aid and often appear in the form of microfinance-supported projects due to the need to provide a sustainable form of assistance and improve small-scale economic

Table 4: Macro-Institutions in Five Countries and Associated Social Enterprise Country Models. Governance Government effectivenessb (0 100)

Economy GCI rankingc (1 = most competitive)

Civil Society Sector modeld (B = Borderline)

Zimbabwe

5.57

3.8

136

Argentina

5.51

48.3

87

Deferred Democratization (B)

Italy

4.94

67.0

48

Welfare Partnership (B)

Dependent Focused

United States

4.25

91.4

4

Liberal

Autonomous Diverse

Sweden

3.66

98.6

2

Social Democratic

Enmeshed Focused

Traditional (assumed)

Int’l Aid Per capitae (in US $) 51 2.9

Social Enterprise Country Model

Sustainable Subsistence Autonomous Mutualism

15

Source: Adapted from Kerlin (2013). a The Global Leadership and Organizational Behavior Effectiveness (GLOBE) Research Project is a study of 61 cultures/countries reported in, Culture, Leadership, and Organizations: The GLOBE Study of 62 Societies (House et al., 2004). The study examines culture through nine different dimensions each in terms of practices and values. This paper uses the study’s findings for In Group Collectivism in societal practices, which is “the degree to which individuals express pride, loyalty, and cohe siveness in their organizations or families” (p. 12) (on a scale of 1 7 where higher scores indicate greater In Group Collectivism in practice). b World Bank (2010a, 2010b) World Wide Governance Indicators 2010: Provides six governance indicators for 212 of the world’s countries and territories. Government effectiveness is the quality of public services, the capacity of the civil service and its independence from political pressures, and the quality of policy formu lation. (retrieved from http://info.worldbank.org/governance/wgi/index.aspx#reports). c 2010 2011 Global Competitiveness Report, in addition to a competitiveness ranking of 139 countries, provides a typology of stages of economic development largely based on GDP per capita (Sala i Martin et al., 2010). d Johns Hopkins Comparative Nonprofit Sector Project. Based on two decades of empirical research in over 40 countries, Salamon and Sokolowski’s (2010) models of civil society sectors distinguish five types based on differences in empirical data across five dimensions: workforce size, volunteer share, government support, philan thropic support, and expressive share. Zimbabwe was not included in the Johns Hopkins project; however, its civil society characteristics largely match other African countries that belong in the Traditional model thus Zimbabwe’s alignment with this model is assumed. e World Bank (2010a, 2010b) World Development Indicators. International aid data are from the Development Assistance Committee (DAC) of the Organization for Economic Co operation and Development (OECD), and population estimates from the World Bank. Data are from 2010. Notes: International aid per capita includes net official development assistance (loans and grants from DAC member countries, multilateral organizations, and non DAC donors) divided by the midyear popula tion estimate. Italy, United States, and Sweden did not receive international aid (data retrieved from the World Bank’s World Databank at http://databank.worldbank. org/ddp/home.do?Step=12&id=4&CNO=2).

The Macro-Institutional Social Enterprise Framework

Culture In group collectivisma

Common Form Variation in Types of Activities

Reliance on Commercial Revenue

Government Involvement

Civil Society Presence

Social Enterprise Country Model

SE policies/ subsidies Zimbabwea Individual Self Sustainability

Microfinance/ nonprofit

Low

High

No

Moderate (works w/intl aid)

Sustainable Subsistence

Argentinab

Group Self Sufficiency

Cooperative/ mutual benefit

Moderate

High

No

Strong

Autonomous Mutualism

Italyc

Social Benefit

Cooperative

Low

Moderate Low (reliant on govt subsidies)

High

Moderate (partnered w/govt)

Dependent Focused

United Statesd

Organizational Sustainability

Nonprofit/ business

High

Moderate (mixed w/ charity & govt revenue)

No

Strong

Autonomous Diverse

Swedene

Social Benefit

Cooperative/ businessf

Low

Low (very reliant on govt subsidies)

Very high

Low (highly Enmeshed Focused partnered w/govt)

Source: Adapted from Kerlin (2013). a Masendeke and Mugova (2009). b Roitter and Vivas (2009). c Borzaga and Santuari (2001) and Nyssens (2009). d Kerlin and Gagnaire (2009). e Stryjan (2001, 2004), Spear and Bidet (2005), Gawell, Johannisson, and Lundqvist (2009). f While government supported social cooperatives have been the dominant social enterprise form in Sweden, recently some businesses with a social purpose have appeared that are less engaged with government. See Gawell et al. (2009).

JANELLE A. KERLIN

Outcome Emphasis

16

Table 5: Social Enterprise Characteristics for Five Countries and Associated Social Enterprise Country Models.

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development. This model of social enterprise fits with the factor-driven stage of economic development because of the low GDP per capita that necessitates need-based entrepreneurialism and the Traditional Civil Society model that builds on traditional forms of social interaction in the small village group. The Autonomous Mutualism social enterprise model is characterized by a post-authoritarian emerging civil society that comes together to fill gaps left in the economy and state social welfare. Cooperatives, recuperated companies, and other mutual assistance activities that provide needed services and employment are predominant forms of social enterprise. More so than other models, social enterprises may participate in and be viewed as a form of social activism, in part because of a past tradition of civil society working in opposition to an authoritarian state coupled with present efforts to provide a form of social justice for those left behind by the market and state. This model fits with the efficiency-driven stage because entrepreneurial activities often take the form of small- and medium-sized businesses and, in the case of recuperated companies, are involved in larger scale manufacturing activities commonly attributed to this stage. With a higher GDP per capita, there is also more possibility for drawing on larger pooled resources for entrepreneurship, either formally or informally. The model also aligns with the deferred democracy model because social enterprises work autonomously from and sometimes in opposition to the state to address perceived deficiencies in state policies. Both the Dependent Focused and Enmeshed Focused social enterprise models are characterized by the large presence of the welfare state, leaving in the first instance a narrow space for the development of social enterprise activities. Although social enterprise ideas may develop in the civil society sphere to provide a unique service, once proven, they can become captured in state welfare policy and dependent on state funding for their activities. Thus, social enterprise runs the danger of only being associated with the narrow sphere of services popularized and supported by the state. There may also be occurrences of local municipalities running social enterprises or partnering with civil society organizations to do so. The difference between the two models involves the number, connection to public policy, and at times the origin of social enterprises. While both models rely on state subsidies for

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implementation, in the Enmeshed Focused model, there are fewer and less diverse kinds of social enterprises, many of which have close ties with specific public policies that may have spurred their development. Moreover, a small number of social enterprises have originated from the top down due to state privatization of sheltered workshop programs (Spear & Bidet, 2005). The two models fit with the innovation-driven stage because of the availability of a high degree of wealth necessary to support a large welfare state, as well as government policies and other institutions supportive of innovative entrepreneurship. They each fit their respective civil society models because social enterprise has assumed a relationship with the state that aligns with the relationship between social service nonprofits and the state in each case. The Autonomous Diverse model of social enterprise is characterized by a broader array of types of social enterprise activities in large part because of its autonomy from government due to a smaller welfare state. This autonomy from the state, in terms of the limited subsidies provided, also encourages the use of social enterprise as an income generator for organizations that at times is independent from programming for participants. There is also a highly supportive environment for innovative entrepreneurialism. Thus, this model fits with the innovation-driven stage due to the latter, but also due to the high level of wealth that supports private philanthropy for social enterprise. There may also be greater supply and demand for diverse social enterprise services due to a high-income society’s desire for them and ability to pay. The model fits with the liberal model of civil society because of its autonomy from the state.

Critiques of the Original MISE Framework Since its creation, the original MISE framework, though viewed as a positive step forward, has received a number of critiques which this book hopes to address. Most of these critiques fall along four lines of thought. First, it was seen by some as limited because it only captured social enterprise from a national level and overlooked sometimes large subnational regional variation in social enterprise (Young & Lecy, 2014). Second, there was

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commentary on how it failed to include forces below the country level that could also influence the development of social enterprise (Defourny & Nyssens, 2016). Third, it was clear that there were more country models for social enterprise that the framework had not yet uncovered. These included social enterprise models for Asian and Middle Eastern countries in particular. Finally, there was also the critique that the framework was static and only generated a snapshot in time overlooking the dynamic nature of the institutional forces at play that could be moving social enterprise into a new position even shortly after its use. There was also disappointment that the first quantitative analysis conducted to test the framework was unable to include the important macro-level institution of civil society (Monroe-White, Kerlin, & Zook, 2015). All four of these critiques are captured in the qualitative country chapters contained in this volume. Indeed, the authors of these chapters delved into these issues and others based on the actual circumstances surrounding social enterprise in their countries. In the process, they often showed the way for how the framework could be adjusted to address the issues they uncovered. They also provided the rich qualitative material needed to engage in a truly iterative analytic process, whereby theory and qualitative and quantitative empirical research worked to inform one another in a back and forth interplay. This process is seen in Chapter 2 when conducting and interpreting the updated quantitative analysis as well as in the concluding Chapter 11 which attempts a synthesis and application of the information in the book toward a revision of the MISE framework.

A Brief Overview of the Book In Chapter 2, An Updated Quantitative Assessment of the MacroInstitutional Social Enterprise Framework, Thema Monroe-White (VentureWell, USA) and Muhammet Emre Coskun (Georgia State University, USA) take on the challenge of quantitatively testing the framework and its results for social enterprise through multilevel regression analysis. Using data for 53 countries that reflect their government, economic, civil society, and cultural institutions, this chapter shows that variation in country-level institutions helps explain variation in social enterprise at a significant level. With a newly included indicator for civil society and analysis on culture, this updated quantitative analysis provides statistical support for

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the MISE framework originally based solely on theory and qualitative country case studies. In Chapter 3, South Korea: Government Directed Social Enterprise Development: Toward a New Asian Social Enterprise Country Model, Bokgyo Jeong (Kean University, USA) embarks on an in-depth study of the state and its relationship to the emergence of social enterprises in South Korea. He argues that the state’s proactive role in social and economic development helps explain its use of social enterprise as a policy tool to further its public policy agenda without creating a large welfare state. Given the uniqueness of the state’s historical path and its use of social enterprise, Jeong proposes extending Kerlin’s country models of social enterprise to include a sixth category, “Strategic Diverse.” In Chapter 4, China: The Diffusion of Social Enterprise Innovation: Exported and Imported International Influence, Tracy Shicun Cui (Georgia State University, USA) and Janelle A. Kerlin (Georgia State University, USA) examine the development of social enterprise in China from the perspective of imported and exported diffusion of innovation to China in the context of an authoritarian government regime and a regulated civil society. It discusses a prominent social enterprise incubator and foreign social enterprise actors and draws on original research into their activities and outcomes for social enterprise development. The chapter also introduces a modified Asian social enterprise country model to reflect the Chinese context, “Semi-Strategic Focused model.” In Chapter 5, Romania: Fostering Social Enterprise in a Post-Transitional Context: Caught between Social Enterprise Country Models, Mihaela Lambru (University of Bucharest) and Claudia Petrescu (Romanian Academy of Science) explore the posttransition context for social enterprise development in Romania focusing on the current civil society context and the supporting role and influence of the European Union. They also discuss the present domestic policy setting and efforts to move forward specific social enterprise-related legislation. Due to the dynamic nature of the setting for social enterprise in Romania, the authors propose that their country is currently caught between two social country enterprise models. In Chapter 6, Spain: Understanding Social Enterprise Country Models Across Time and Sub-Country Regions, Ramon Fisac-Garcia (Universidad Politecnica de Madrid, Spain) and Ana Moreno-Romero (Universidad Politecnica de Madrid, Spain) apply the MISE framework to two distinct periods of time in

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Spain’s history to show how the application of the framework in both historic and contemporary contexts can reveal a more dynamic picture of the ever-evolving concept of social enterprise on a country level. Equally important, they also show how the MISE framework can be utilized on country and regional levels to identify both an overarching country social enterprise model as well as differing regional social enterprise models that help capture social enterprise variation within a country. In Chapter 7, Chile: The Influence of Institutional Holdovers from the Past on the Social Enterprise Country Model, Sebastian Gatica (Pontificia Universidad Católica de Chile, Chile), through historical application of the MISE framework, considers the influence of prior socioeconomic contexts and social enterprise country models on the present social enterprise model in Chile. He argues that in countries where the socioeconomic context shifts rapidly due to political upheavals, organizational holdovers from the prior social enterprise country model may still be found in society but not be fully captured by the present country social enterprise model identified through a current application of the MISE framework. In Chapter 8, Sweden: Tracing Social Enterprise across Different (Social) Spheres: The Dynamic Interplay among Institutions, Values, and Individual Engagement, Malin Gawell (Södertörn University, Sweden) argues that there is ambiguity and paradoxes behind the aggregated data and intertextual consensus related to the social enterprise country models generated by the MISE framework. She argues that we need to look into, and partly beyond, these macro-institutional processes to grasp a deeper understanding of the dynamic interplay between institutions, values, and individual engagement to understand something as elusive as social enterprises. Her analysis is based on different types of socioeconomic data, world value studies as well as qualitative case studies including also narrative analysis. In Chapter 9, Rosemary Chilufya (University of Huddersfield, UK) and Janelle A. Kerlin (Georgia State University, USA) examine how rural social enterprises in Zambia utilize spatial resource legacies such as natural, historical, and cultural resources to enrich themselves and their local communities through value-creating activities that go beyond mere job creation and growth. Their chapter shows that rural social enterprise is about the meaningfulness of the local place, exploiting innate resources, prompting community support, and compelling local well-being and development through a mutual dependency approach. They also demonstrate

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that there is room for human agency in the “multiplicity and heterogeneity” of the pool of resources surrounding social enterprises which helps to offset the institutional focus of the MISE framework. In Chapter 10, Australia: Understanding Future Social Enterprise Country Model Development through IndividualLevel Policy Discourse Analysis, by Chris Mason (Swinburne University of Technology, Australia) and Joe Barraket (Swinburne University of Technology, Australia) argue that a combination of historical and discursive institutionalism is needed when examining country social enterprise models so that the influence of both macro-level institutions and micro-level discourses is considered. Specifically, they draw on the policymaking discourse around social enterprise in the Australian federal government to show how the Australian social enterprise model identified through the MISE framework may shift over time if policies resulting from such discussions are implemented. In Chapter 11, Conculsion: Revising the Macro-Institutional Social Enterprise Framework, the editor, Janelle A. Kerlin (Georgia State University, USA), summarizes the critiques of the preceding chapters with respect to the three overall ways they contribute to the MISE framework: additional influences to include in the basic framework, new ways to understand social enterprise country models including new models to add to the original five, and new applications of the framework. This chapter then applies the information in a revision of the framework and its associated social enterprise country models. New features include more attention to culture and micro- and meso-level forces as well as the introduction of optional framework components that address rarely occurring country situations and are applied on an as-needed-basis. Two new social enterprise country models are also added increasing their number to seven and new applications of the framework are detailed.

References Acemoglu, D., & Robinson, J. A. (2012). Why nations fail: The origins of power, prosperity, and poverty. New York, NY: Crown Business. Austin, J., Stevenson, H., & Wei Skillern, J. (2006). Social and commercial entrepreneurship: Same, different or both? Entrepreneurship Theory and Practice, 30, 1 20. Banerjee, A. V., & Duflo, E. (2011). Poor economics: A radical rethinking of the way to fight global poverty. New York, NY: Public Affairs.

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Baumol, W. J. (1990). Entrepreneurship: Productive, unproductive and destruc tive. Journal of Political Economy, 98(5), 893 921. Borzaga, C., & Defourny, J. (2001). The emergence of social enterprise. London: Routledge. Borzaga, C., & Santuari, A. (2001). Italy: From traditional co operatives to innovative social enterprises. In C. Borzaga & J. Defourny (Eds.), The emergence of social enterprise (pp. 166 181). New York, NY: Routledge. Bosma, N., & Levie, J. (2010). Global entrepreneurship monitor 2009 global report. Retrieved from http://www.gemconsortium.org/about.aspx?page=pub gem global reports Chell, E., Nicolopoulou, K., & Karata¸s Özkan, M. (2010). Social entrepreneur ship and enterprise: International and innovation perspectives. Entrepreneurship & Regional Development, 22(6), 485 493. Dacanay, M. (2004). Creating a space in the market: Social enterprise stories in Asia. Asian Institute of Management and Conference of Asian Foundations and Organizations, Makati City, Philippines. Dacin, P. A., Dacin, M. T., & Matear, M. (2010). Social entrepreneurship: Why we don't need a new theory and how we move forward from here. Academy of Management Perspectives, 24(3), 37 57. Defourny, J., & Kim, S. (2011). Emerging models of social enterprise in Eastern Asia: A cross country analysis. Social Enterprise Journal, 7(1), 86 111. Defourny, J., & Nyssens, M. (2010). Conceptions of social enterprise and social entrepreneurship in Europe and the United States: Convergences and diver gences. Journal of Social Entrepreneurship, 1(1), 32 53. Defourny, J., & Nyssens, M. (2016). Fundamentals for an international typol ogy of social enterprise models. ICSEM Working Papers, No. 33. The International Comparative Social Enterprise Models (ICSEM) Project, Liege. Doherty, B., Haugh, H., & Lyon, F. (2014). Social enterprises as hybrid organi zations: A review and research agenda. International Journal of Management Reviews, 16(4), 417 436. Estrin, S., Mickiewicz, T., & Stephan, U. (2013). Entrepreneurship, social capi tal, and institutions: Social and commercial entrepreneurship across nations. Entrepreneurship Theory and Practice, 37(3), 479 504. Franke, R. H., Hofstede, G., & Bond, M. H. (1991). Cultural roots of economic performance: A research note. Strategic Management Journal, 12, 165 173. Galera, G., & Borzaga, C. (2009). Social enterprise: An international overview of its conceptual evolution and legal implementation. Social Enterprise Journal, 5(3), 210 228. Gawell, M., Johannisson, B., & Lundqvist, M. (Eds.). (2009). Entrepreneurship in the name of society. Stockholm: Knowledge Foundation. Goldstone, J. (2003). Comparative historical analysis and knowledge accumula tion in the study of revolutions. In J. Mahoney & D. Rueschemeyer (Eds.), Comparative historical analysis in the social sciences (pp. 41 90). Cambridge: Cambridge University Press. Haugh, H. (2012). The importance of theory in social enterprise research. Social Enterprise Journal, 8(1), 7 15.

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Hazenberg, R., Bajwa Patel, M., Mazzei, M., Roy, M. J., & Baglioni, S. (2016). The role of institutional and stakeholder networks in shaping social enterprise ecosystems in Europe. Social Enterprise Journal, 12(3), 302 321. Hechavarría, D. M. (2016). The impact of culture on national prevalence rates of social and commercial entrepreneurship. International Entrepreneurship and Management Journal, 12(4), 1025 1052. doi:10.1007/s11365 015 0376 1 Hoogendoorn, B., & Hartog, C. (2011). Prevalence and determinants of social entrepreneurship at the macro level. Scales Research Reports H201022. EIM Business and Policy Research. House, R. J., Hanges, P. J., Javidan, M., Dorfman, P. W., & Gupta, V. (2004). Culture, leadership, and organizations: The GLOBE study of 62 societies. Keating, M. (2013). Rescaling the European state: The making of territory and the rise of the meso. Oxford: Oxford University Press. Kerlin, J. A. (2009). Social enterprise: A global comparison. Lebanon, NH: Tufts University Press. Kerlin, J. A. (2013). Defining social enterprise across different contexts: A con ceptual framework based on institutional factors. Nonprofit and Voluntary Sector Quarterly, 42(1), 84 108. Kerlin, J. A. (Ed.). (2015). Kerlin’s macro institutional framework. Social Enterprise Journal, (Special issue), 111(2). Kerlin, J. A., & Gagnaire, K. (2009). United States. In J. Kerlin (Ed.), Social enterprise: A global comparison (pp. 87 113). Lebanon, NH: Tufts University Press. Lepoutre, J., Justo, R., Terjesen, S., & Bosma, N. (2013). Designing a global standardized methodology for measuring social entrepreneurship activity: The global entrepreneurship monitor social entrepreneurship study. Small Business Economics, 40(3), 693 714. Lundstrom, A., Zhou, C., von Friedrichs, Y., & Sundin, E. (Eds.). (2014). Social entrepreneurship: Leveraging economic, political, and cultural dimensions. London: Springer. Mahoney, J. (2003). Knowledge accumulation in comparative historical research: The case of democracy and authoritarianism. In J. Mahoney & D. Rueschemeyer (Eds.), Comparative historical analysis in the social sciences (pp. 131 176). Cambridge: Cambridge University Press. Mair, J., Martí, I., & Ventresca, M. (2012). Building inclusive markets in rural Bangladesh: How intermediaries work institutional voids. Academy of Management Journal, 55(4), 819 850. Masendeke, A., & Mugova, A. (2009). Zimbabwe and Zambia. In J. Kerlin (Ed.), Social enterprise: A global comparison (pp. 114 138). Lebanon, NH: Tufts University Press. Monroe White, T., Kerlin, J. A., & Zook, S. (2015). A quantitative critique of Kerlin’s macro institutional social enterprise framework. Social Enterprise Journal, 11(2), 178 201. North, D. C. (1990). Institutions, institutional change and economic perfor mance. Cambridge: Cambridge University Press.

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Nyssens, M. (2006). Social enterprise: At the crossroads of markets, public poli cies and civil society. London: Routledge. Nyssens, M. (2009). Western Europe. In J. Kerlin (Ed.), Social enterprise: A global comparison (pp. 12 34). Lebanon, NH: Tufts University Press. Putnam, R. (1993). Making democracy work: Civic traditions in modern Italy. Princeton, NJ: Princeton University Press. Puumalainen, K., Sjogren, H., Pasi, S., & Barraket, J. (2015). Comparing social entrepreneurship across nations: An exploratory study of institutional effects. Canadian Journal of Administrative Sciences, 32, 276 287. Roitter, M., & Vivas, A. (2009). Argentina. In J. Kerlin (Ed.), Social enterprise: A global comparison (pp. 139 162). Lebanon, NH: Tufts University Press. Roy, M. J., McHugh, N., Huckfield, L., Kay, A., & Donaldson, C. (2015). ‘The most supportive environment in the world’? Tracing the development of an insti tutional ‘ecosystem’ for social enterprise. Voluntas, 26(3), 777 800. Rueschemeyer, D. (2009). Usable theory: Analytical tools for social and political research. Princeton, NJ: Princeton University Press. Rueschemeyer, D., Stephens, E. H., & Stephens, J. D. (1992). Capitalist develop ment and democracy. Chicago, IL: Chicago University Press. Sala i Martin, X., Blanke, J., Hanouz, M., Geiger, T., & Mia, I. (2009). The global competitiveness index 2009 2010: Contributing to long term prosperity amid the global economic crisis. In K. Schwab (Ed.), The global competitiveness report 2009 2010 (pp. 3 47). Geneva: World Economic Forum. Retrieved from http://www.weforum.org/pdf/GCR09/GCR20092010fullreport. Accessed on June 10, 2010. Sala i Martin, X., Blanke, J., Hanouz, M., Geiger, T., & Mia, I. (2010). The global competitiveness index 2010 2011: Looking beyond the global economic crisis. In K. Schwab (Ed.), The global competitiveness report 2010 2011 (pp. 3 55). Geneva: World Economic Forum. Retrieved from http://www3. weforum.org/docs/WEF GlobalCompetitivenessReport 2010 11.pdf. Accessed on October 1, 2010. Salamon, L., & Sokolowski, S. W. (2009). Bringing the ‘social’ and the ‘political’ to civil society: Social origins of civil society sectors in 40 countries. Paper pre sented at the 38th Annual Conference of the Association for Research on Nonprofit Organizations and Voluntary Action, 19 21 November, 2009, Cleveland, OH. Salamon, L., & Sokolowski, S. W. (2010). The social origins of civil society: Explaining variations in the size and structure of the global civil society sector. Paper presented at the 9th International Conference of the International Society for Third Sector Research, Istanbul, Turkey. Scott, W. R. (2005). Institutional theory: Contributing to a theoretical research program. In K. G. Smith & M. A. Hitt (Eds.), Great minds in management (pp. 460 484). New York, NY: Oxford University Press Scott, W. R. (2008). Institutions and organizations (3rd ed.). Thousand Oaks, CA: Sage Publications. Shane, S. (1992). Why do some countries invent more than others? Journal of Business Venturing, 7, 29 46.

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Shane, S. (1993). Cultural influences on national rates of innovation. Journal of Business Venturing, 8, 59 73. Shea, J. (2011). Taking nonprofit intermediaries seriously: A middle range the ory for implementation research. Public Administration Review, 71(1), 57 66. Skocpol, T. (1979). States and social revolutions. Cambridge: Cambridge University Press. Spear, R., & Bidet, E. (2005). Social enterprise for work integration in 12 European countries: A descriptive analysis. Annals of Public and Cooperative Economics, 76(2), 195 231. Stephan, U., Uhlaner, L. M., & Stride, C. (2015). Institutions and social entre preneurship: The role of institutional voids, institutional support, and institu tional configurations. Journal of International Business Studies, 46, 308 331. Stryjan, Y. (2001). Sweden: The emergence of work integration social enter prises. In C. Borzaga & J. Defourny (Eds.), The emergence of social enterprise (pp. 220 235). New York, NY: Routledge. Stryjan, Y. (2004). Work integration social enterprises in Sweden. Working Papers Series, No. 04/02. Liège: EMES European Research Network. Tiessen, J. H. (1997). Individualism, collectivism, and entrepreneurship: A framework for international comparative research. Journal of Business Venturing, 12, 367 384. World Bank. (2010a). World development indicators. Retrieved from http:// databank.worldbank.org/ddp/home.do?Step=12&id=4&CNO=2 World Bank. (2010b). World wide governance indicators. Retrieved from http:// info.worldbank.org/governance/wgi/index.aspx#reports Young, D. R., & Lecy, J. (2014). Defining the universe of social enterprise: Competing metaphors. Voluntas, 25(5), 1307 1332. Young, D. R., Searing, E. A. M., & Brewer, C. V. (Eds.) (2016). The social enterprise zoo: A guide for perplexed scholars, entrepreneurs, philanthropists, leaders, investors, and policymakers. Northampton, MA: Edward Elgar.

CHAPTER

2

An Updated Quantitative Assessment of Kerlin’s Macro-Institutional Social Enterprise Framework Thema Monroe-White and Muhammet Emre Coskun

Introduction The social enterprise sector shows variation in terms of shape and size across nations, making cross-country comparative research crucially important for our understanding of social organizations (Borzaga & Defourny, 2001; Chell, Nicolopoulou, & Karatas, 2010; Gidron & Hasenfeld, 2012). Among various attempts to explain this variance is the use of institutional theory (North, 1990), which proposes explanations for the current state and growth patterns of social enterprises based on formal and informal institutional contexts in each country (Defourny & Nyssens, 2010, 2016; Estrin, Mickiewicz, & Stephan, 2013; Kerlin, 2009, 2013; Puumalainen, Sjogren, Pasi, & Barraket, 2015; Stephan, Uhlaner, & Stride, 2015). Kerlin’s macro-institutional social enterprise (MISE) framework is a prominent example of the use of 27

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historical institutional theory to shed light on the inter-country differences of social enterprises (Kerlin, 2013). Kerlin’s (2013) MISE framework aims to establish a conceptual understanding of the social enterprise sector by examining how the national institutional context affects the development and current shape of social enterprise. To that end, she draws on the theory of historical institutionalism (Thelen, 1999), and proposes that formal and informal institutions create historical causal feedback loops, which both sustain the present setting and influence the formation of future institutions. The framework contains formal national institutional variables (economy, government, civil society) as well as informal ones (culture, social classes) to develop a comparative macro-level understanding of social enterprises across countries. The informal and formal institutions affect each other and together they shape the power structures that underlie the development of the social enterprise sector over time. Most of the assessments of the framework have been qualitative case studies such as those included in this volume. An early quantitative analysis of Kerlin’s MISE framework tested its implications by employing a hierarchical linear modeling technique with the 2009 Global Entrepreneurship Monitor (GEM) dataset along with country-level institutional variables (MonroeWhite, Kerlin, & Zook, 2015). It found that there is significant between-country variance in the size of social enterprise sectors, a fair amount of which can be attributed to the national institutional factors included in the analysis: economic competitiveness rank, size of welfare state, and collectivist culture to be specific (Monroe-White et al., 2015). A crucial limitation of this study was the exclusion of civil society from the empirical testing due to the lack of sufficient data. Moreover, the study only included two culture variables to capture the effect of informal institutions on variation in social enterprise, one of which had to be dropped from the original model and tested separately given the high correlation between them. Here, we build on this quantitative critique of Kerlin’s MISE framework. This study extends the former analysis by including a variety of additional culture variables to better test informal institutional effects on social enterprise variation across countries. We also update testing of formal institutional influences by including civil society with the help of newly available civil society data. Moreover, the previous study does not mention the interplay between the two types of institutions, formal and informal.

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Here, we improve the analysis to account for the relative effects of each of these institutional components, to test the importance of institutional configurations and how they relate to variation in social enterprise on a national level (Stephan et al., 2015). In particular, we find compelling evidence for the influence on social enterprise of the three main formal institutions in Kerlin’s MISE framework: government, economy, and civil society.

Methodology Similar to the early version of this study (Monroe-White et al., 2015), we use hierarchical linear modeling. This advanced type of regression analysis allows us to analyze the effects of higher level factors (institutional country characteristics) on the lower level variables (social enterprise organizations) where data are nested, meaning that organizations in the first level are clustered in countries at the second level of analysis. Likewise, we continue to use the same estimation method, logistic hierarchical generalized linear model, assuming a binomial distribution over the dependent variable, social enterprise, which was constructed as a binary variable. This logistic regression model uses binomial distribution to predict a binary response for the dependent variable at the lower level of analysis based on both lower and higher level explanatory variables. The hierarchical model used in the analysis consists of two levels, with social enterprise organizations assigned to Level-1 and countries to Level-2. In a multilevel model, it is suggested that there be at least 30 50 observations for each variable at Level-2 in order to obtain optimal results (Hox & Maas, 2002; Maas & Hox, 2004; Snijders & Bosker, 2012), because if Level-2 sample size is lower, one risks having hypothesis tests which are uninterpretable within the likelihood framework (Bowers & Drake, 2005). In the original study, although most of the country-level institutional variables had at least 40 observations, some institutional variables were problematic as they were missing values for several countries, thereby reducing the number of complete cases (i.e., n < 30). This problem was overcome by imputing values for the missing cases for the cultural variables. However, the civil society variable had to be removed from the empirical analysis due to a large number of missing cases (it had values for only 25 countries). Here, instead of using the civil society models, we approximate civil society via a civil society participation index produced by Varieties of Democracy

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(V-Dem) (Bernhard, Tzelgov, Jung, Coppedge, & Lindberg, 2015; Coppedge et al., 2016a, 2016b). Therefore, the current analysis is an improvement over the original by allowing us to test for the effect of civil society at the country level as it solves the problem of missing cases in Level-2 for that variable. Yet, we still have a low sample size problem with some culture variables introduced in the analysis. The updated analysis is based on the original dataset used in the initial version consisting of individual-level survey results to measure organizations and national-level institutional variables for 54 countries. Social enterprise activity, the dependent variable, is coded from the 2009 GEM Adult Population Survey, “which captures, among other things, existing national differences in entrepreneurial behavior and characteristics of the entrepreneurs aged 18 to 64” (Monroe-White et al., 2015). National-level independent variables come from various data sources, which are described below in detail.

Data1 DEPENDENT VARIABLE Social enterprise. In this study, social enterprise organizations are broadly defined as “the use of nongovernmental, market-based approaches to address social issues” (Kerlin, 2013, p. 84). In addition to legal distinctions (i.e., for-profit, nonprofit, and lowprofit), Figure 1 outlines a spectrum of organizational forms and

Figure 1: Alter’s Typology of Social Enterprises. Source: Alter (2007).

1

This section is for the most part excerpted from the initial version of this study published in the Social Enterprise Journal (Monroe-White et al., 2015).

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focus, where organizations vary according to their key objectives, mission, or goals (Alter, 2007). Although most enterprise research has focused on profit-maximizing firms where the bottom line is measured in terms of increasing profits, organizations with nonprofit or social goals using business principles are increasingly common. On the right side of the spectrum are for-profits including conventional for-profit organizations and firms practicing corporate social responsibility. On the left are nonprofit organizations including conventional nonprofits and nonprofits that generate earned income. For-profit firms have profitability (economic value creation) as their primary motive where they are under some obligation to redistribute that profit among shareholders. Nonprofits have social mission (social value creation) as their primary motive is dictated by their stakeholders. The value orientation (i.e., economic, social, and/or environmental) of an organization reflects the extent to which achieving impact in that area determines the success of the organization, and it is also what attracts and retains talent, customers, and investors (Hull & Lio, 2006; McDonald, 2007). Moving from left to right, organizations become increasingly reliant on market revenue (i.e., sales of goods and services). Using Alter’s (2007) spectrum and the 2009 GEM data, three types of organizations were identified: conventional business, social organization, and social enterprise. Five GEM variables were used to determine the organization type.2 These variables relate to the organization’s value orientation, ownership status, and amount of income generated through sales (Lepoutre, Justo, Terjesen, & Bosma, 2013). Conventional businesses are defined as those that sold goods and/or services without an explicit social purpose. Social organizations are defined as traditional nonprofits, nonprofit equivalents, or social organizations with an explicit social purpose, which do not generate revenue from sales (equivalent to traditional nonprofits in Alter’s spectrum; see Figure 1). Thirdly, social enterprises are organizations with an explicit social purpose that also generate revenue from sales. Using the definition of social enterprise from Kerlin (2013), an organization is defined as a social enterprise if the respondent indicated that their organization generated revenue from sales and that they are

2

The GEM variables used are sestart, seowndif, seonincm, seonsale, and ownmge.

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the current founder and/or owner manager of an existing organization with an explicit social purpose. In this way, responses from nascent entrepreneurs were excluded from the analyses. In the GEM data, social and/or environmental goal orientation is the primary indicator of social enterprise. Percent sales revenue is used as a secondary indicator of social enterprise because both for-profit firms and social enterprises could potentially generate up to 100% revenue from sales. These two measures were combined to determine if an organization is a social enterprise. To further clarify, there were two ways to classify social enterprise in the GEM data: implicit social enterprise and explicit social enterprise. Implicit social enterprise refers to any business entity (an organization that sells goods or services) with 50% or greater social and/or environmental goals. There were approximately 7,000 social enterprises under this classification. Explicit social enterprise, on the other hand, refers to all social organizations (defined as any kind of activity, organization, or initiative that has a particularly social, environmental, or community objective) that also generate sales revenue. There were approximately 1,200 social enterprises under this classification. We chose to restrict the dataset to explicit social enterprise to ensure that the organizations have a deliberate social mission. This operationalization also restricts “social enterprises” to the two or three categories on the left-hand side of Alter’s spectrum: nonprofit organizations with income-generating activity, social enterprise, and borderline social businesses (in instances where social and/or environmental goals are equal to 50%). In several instances, respondents either did not indicate if their social organization generated earned income, or the information provided was conflicting. If there was no way to confidently determine whether or not the respondent owned or managed a social organization or social enterprise, the organization was dropped from the sample. This resulted in the loss of approximately 300 unclassifiable social entities. Likewise, in the case of serial entrepreneurs, if respondents indicated that they currently owned-managed multiple businesses, they were asked to speak to the organization for which they were the most familiar. However, in a small number of cases, managers of existing social businesses were also managers of existing conventional businesses. If the two organizations were different or unknown, subsequent responses on sales revenue and goal orientation could have pertained to either the social or the conventional business; therefore, these entities were also excluded from the analyses.

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INDEPENDENT VARIABLES NATIONAL-LEVEL DATA The national-level predictor variables in this study come from the global indicators outlined by Kerlin (2009, 2013). The number of countries with available data varied between each indicator, making cross-country comparisons a challenge. Missing values were avoided as much as possible by using the closest available yearly data (prior to 2009). Three variables in this study derive from the World Bank’s World Development Index (WDI) (Lee, 2012). The WDI is the source of the World Bank’s annual compilation of data about development. Data are derived primarily from official registers, national accounts, or based on household, health, or labor force surveys. Additional sources include the World Economic Forum’s Global Competitiveness Index (GCI), the Global Leadership and Organizational Behavior Effectiveness (GLOBE) Research Program survey on culture, the V-Dem Institute’s civil society indicators, the Hofstede Centre, the World Values Survey (WVS), and the Organization for Economic CoOperation and Development (OECD), Development Assistance Committee’s (DAC’s) data on international aid by country. Civil Society The most significant improvement of this study over the original version is the inclusion of a civil society variable in the empirical analysis. In the earlier version, this important element of the macro-institutional framework had to be excluded from the analysis due to the lack of data. The preliminary data consisted of civil society model identification for 30 countries based on five categories created by Salamon and Sokolowski (2009). However, the number of countries with available data further decreased with the addition of each variable in the estimation models, which made multilevel modeling problematic. Therefore, the civil society variable had to be dropped from the analysis. Here, we restore a civil society variable to the empirical analysis by using a recently released dataset by the V-Dem Institute. The V-Dem project aggregates independent subjective ratings from country experts to measure latent (not directly measurable) country characteristics to produce indicators related to democratic governance and institutions. These experts’ ratings are aggregated into point estimates by employing Bayesian item response theory models to detect and correct for rater disagreement patterns and random error caused by the difference between raters’ perceptions and the true value of the variable or

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coding mistakes (Pemstein, Marquardt, Tzelgov, Wang, & Miri, 2015). The new V-Dem dataset (2016) contains 10 civil society indicators, each based on a distinct question measuring different aspects of civil society, which makes it possible to do comprehensive comparative analysis about the state and development trajectory of civil society between countries and over time (Bernhard et al., 2015). Information about each index, with its underlying question and corresponding responses described in detail, can be found in the V-Dem Codebook (Coppedge et al., 2016a, pp. 235 242). Among these 10 civil society indicators in the V-Dem dataset, we choose to use the civil society participatory environment indicator (v2csprtcpt) developed to measure the level of citizen involvement in civil society organizations (CSOs) in a country (Bernhard et al., 2015). We selected this citizen participation indicator particularly for our analysis because we expect that the level of public involvement in civil society reflects the strength of the civil society in a given country. We hypothesize a positive effect wherein the more participatory the civil society environment, the more social entrepreneurship activity, leading to a larger social enterprise sector. With the civil society participation indicator, the degree of citizen engagement in CSOs in a country is assessed by asking the experts to assign a rating from zero to three, with zero meaning most organizations are state-sponsored and participation is not completely voluntary and three indicating the existence of many diverse CSOs and citizens who occasionally participate in at least one of them (Bernhard et al., 2015). Detailed information about the indicator question and rating responses can be found in the appendix.3 Welfare State Two variables are combined to create the welfare state construct identified by Kerlin (2009, 2013): expenditure on public health and public education. Public education expenditure captures the percent of gross national income spent on public education

3

We chose to use this V-Dem civil society participation indicator rather than World Values Survey questions related to participation in associations because the V-Dem question differentiates between governmentbased associations and voluntary CSOs and attempts to capture both level of participation and diversity of CSOs (see Appendix on page 48).

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operating expenditures including wages and salaries at all levels of government. It also includes subsidies provided to households or private entities for education-related spending. These data come from the UNESCO Institute for Statistics and are gathered from ministries of education or related entities within each country. Public health expenditure is calculated as recurrent and capital spending including donations from international agencies or NGOs. Data on health expenditure come from the World Health Organization’s Global Health Expenditure Database. Economy The World Economic Forum’s GCI ranks countries according to a weighted system of pillars and indicators. They define competitiveness as “the set of institutions, policies, and factors that determine the level of productivity of a country” (Schwab & Sala-iMartin, 2011, p. 4). The GCI identifies 12 pillars which drive productivity: institutions, infrastructure, macroeconomic stability, health and primary education, higher education and training, goods market efficiency, labor market efficiency, financial market sophistication, technological readiness, market size, business sophistication, and innovation. These pillars are used to develop scores which are, in turn, used to determine three broad stages of national economic growth: factor-driven (FD), efficiency-driven (ED), and innovation-driven (ID) economies (Schwab & Sala-iMartin, 2011). FD economies are predominantly extractive in nature (mining, fossil fuels, etc.) and have low levels of infrastructure. Subsequently, entrepreneurship in FD economies is mostly necessity based, as workers create self-employment opportunities for survival. ED countries are characterized by their higher education focus and training of personnel, resulting in a large small- and medium-sized manufacturing industry. Lastly, the ID stage is characterized by greater amounts of wealth and by enterprises that compete through the introduction of innovative goods and processes. The lower the GCI rank, the more competitive a country is, which should promote social entrepreneurship, so we expect a negative coefficient for this variable. Culture The GLOBE database, developed by House, Hanges, Javidan, Dorfman, and Gupta (2004, p. 15), established nine dimensions of culture used to compare similarities and differences in norms, values, beliefs, and practices among various societies. The authors

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defined culture as “shared motives, values, beliefs, identifies, and interpretations of meanings of significant events that result from common experiences of members of collectives that are transmitted across generations.” In the case of multicultural countries, GLOBE researchers sampled the subculture with the greatest amount of commercial activity. However, in certain countries more than one subculture were surveyed. For example, in South Africa, both White and Black South Africans were surveyed. Although GLOBE identifies nine core dimensions of culture, Kerlin (2013) restricted the dimensions of culture to the two which appeared to be the most directly related to entrepreneurship: uncertainty avoidance (UNCRTA) and in-group collectivism. UNCRTA is defined as the extent to which a society, organization, or group relies on social norms, rules, and procedures to alleviate unpredictability of future events. In-group collectivism measures the degree to which individuals express pride, loyalty, and cohesiveness in their organizations or families (House et al., 2004). Since these two variables are highly correlated in the GLOBE dataset, they cause multicollinearity problems; so in the updated analysis, we replace the in-group collectivism variable with Hofstede’s (1980) individualism variable. In fact, the GLOBE ingroup collectivism variable shows a strong negative correlation with Hofstede’s (1980) individualism, justifying our decision. Here, we extend the culture component in our analysis by including two of the Hofstede’s (1980) six cultural dimensions specifically we use power distance (PDI) and individualism (IDV) versus collectivism data as published in Cultures and Organizations 3rd edition (Hofstede, Hofstede, & Minkov, 2010). The PDI index measures the attitude of members of a society who have a lower position in the power hierarchy and their views on the unequal distribution of power, that is, inequality in the society. The higher the PDI measure, the more hierarchically structured the social order in which everybody knows their position and nobody questions it. The lower this index is, a more equal distribution of power is desired in the society and inequalities need to be justified on some legitimate basis. The individualism versus collectivism index, on the other hand, measures preferences of members of a society in extending their care beyond themselves and their first-degree relatives. A higher IDV score indicates that individuals prefer to tend for themselves and their immediate family members in “a loosely-knit society.” A lower IDV score that indicates collectivism shows the opposite case where members of the society are expected to care for

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relatives beyond immediate families as well as particular group members, thus a “tightly-knit society” (Hofstede, 2001). We further investigate the culture aspect of the framework by including two additional variables from the World Values Survey (2013), namely postmaterialism and trust-in-others. The postmaterialism variable is calculated from the four-item version of Inglehart’s (1997) postmaterialist index as percentage of total cases identified as postmaterialist in each country. Similarly, the trust variable is calculated as the percentage of total cases in each country which have opted to say “Most people can be trusted” rather than “Need to be very careful” (WVS, 2013). We use the WVS Wave 5 data collected from 1995 through 2008 to compute these two variables. International Aid Net official development assistance per capita captures the flow of official and private financial contributions from the members of the OECD DAC to developing economies divided by mid-year population. DAC members report this information directly to the DAC secretariat. Official assistance includes aid from state, local, and executive agencies aimed at promoting economic development and welfare. Figures include resource flows through cash and commodities, including those aimed at augmenting the stock of human capital. Values do not reflect aid given by recipients to other developing nations and exclude aid for military assistance.

Analysis A multilevel mixed-effects binomial logistic regression was conducted to assess whether and to what extend national-level formal institutional variables, specifically economic competitiveness (GCI rank), welfare state, civil society, and international aid, as well as informal institutional variables, UNCRTA, IDV, PDI, postmaterialism (POSTMTR), and trust have an effect on the probability of an organization being a social enterprise, controlling for total country population. Given the small sample size (i.e., fewer than 100 country cases), a Satterthwaite4 approximation 4

A Satterthwaite approximation is useful when Level-2 units vary considerably in size. Specifically, it corrects for calculating degrees of freedom providing a more conservative estimate of standard errors.

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THEMA MONROE WHITE AND MUHAMMET EMRE COSKUN

was used, along with a robust estimation of the fixed effects, which is useful in smaller sample sizes (Heck, Thomas, & Tabata, 2012). The use of a multilevel model estimation method is justified by estimating an initial empty model which suggests that 46.7% of the variance in organization type can be accounted for by country differences.5 Thus, there is significant variance in the average probability of an organization being a social enterprise and therefore social enterprise does vary by country.

INFORMAL INSTITUTIONAL FIXED EFFECTS Given the variation in social enterprise from the empty model, we then examined if this variation could be explained by informal institutions only. A series of models with national-level culture predictors were estimated by considering each culture variable separately as well as in combinations. An estimation result is also provided showing all culture variables in one regression. In each of these models, culture effects are controlled for GDP and population, and all variables are centered around the grand mean (Enders & Tofighi, 2007). Estimation results for informal institutions in Table 1 show that the variation of the intercept is significant in all cases, meaning that there still remains between-country variance in organization type after controlling for the effect of culture variables. We see in the individual culture fixed-effect estimations that each culture variable, except PDI, by itself explains a significant amount of the variance in organization type among countries,6 though postmaterialism and trust are only significant when controlling for population. We observe that each unit increase in IDV by itself increases the likelihood of an organization being a social enterprise by a multiple of 1.029, whereas the similar effect of UNCRTA is a

5

In multilevel modeling, an empty (unconditional) model estimation is run to assess if any of the variance in the dependent variable (in this case organization type, that is, whether a business or organization is a social enterprise or not) is due to nesting by Level-2 clusters (in this case countries) (Raudenbush & Bryk, 2002). Results showed an estimate of 2.89 for the variance in the random intercept of the empty model, resulting in an intraclass correlation coefficient (ICC) of 0.467. 6 Because Level-1 variance is fixed at 3.29 for binary and ordinal logistic models, the percentage accounted for between two different models is not comparable. That is, the percentage is rescaled for each model.

Table 1: Informal Institutional Fixed-Effect Models.

GDP

UNC 1.000

IDV

IDV 1.000

PDI

POSa

1.000**

1.029**

PDI

.997

UNCRTA

IDV PDI UNC POS

IDV PDI UNC POS TRST

1.000

1.000

1.000

1.038**

1.029*

1.036*

1.020

1.014

1.026

.837

.747

.918

8217.9**

Trust

138.95 11.72*

popl.

.860

Intrcpt

Number of countries

IDV PDI UNC

.232**

POSTMTR

Variance in intercept

TRSTa

.844

.015*** 2.346 52

.888

.025*** 1.740 38

38

21.04

.953

.021*** 1.908

.815

.024*** 1.418 30

.018*** 1.705 30

1350.6

.327

.024*** 1.815 38

.820

.025*** 1.521 27

.025*** 1.512 27

Notes: Coefficients (Odds Ratio): >1 means positive effect, =1 neutral effect, 1 means positive effect, =1 neutral effect,