Entrepreneurial Education Editorial Staff

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from the United States Local Heroes in the Global Village (pp. 67-89): Springer. ...... E.P. Dutton &. Company. The Knickerbocker Press, New York. Donckels, R.
Volume 26, No. 1 Fall 2014 Special Edition: Entrepreneurial Education

Editorial Staff Managing Editor

Editor

Associate Editor

William T. Jackson

Mary Jo Jackson

Daniel James Scott

Special Guest Editors Eric Liguori

Jeff Vanevenhoven Dean Koutroumanis

The Journal of Business and Entrepreneurship is published by the Association for Small Business and Entrepreneurship (ASBE) and the University of South Florida St. Petersburg. All ASBE members receive one copy of the publication. Subscribe, order back issues or single copies at http://asbe.us/jbe. Submission guidelines can also be found at this site.

ISSN: 1042-6337

©2014 Association for Small Business and Entrepreneurship

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Table of Contents Volume 26, No.1 Fall 2014 Special Edition: Entrepreneurial Education

A Review of the Entrepreneurial Ecosystem and the Entrepreneurial Society in the United States: An Exploration with the Global Entrepreneurship Monitor Dataset Diana M. Hechavarria and Amy Ingram ............................................................................ 1

Chicken or Egg: Entrepreneurial Self-Efficacy and Entrepreneurial Intentions Revisited Christoph Winkler and Jennifer R. Case ........................................................................... 37

Career Impacts of Entrepreneurship Education: How and When Students Intend to Utilize Entrepreneurship in Their Professional Lives Nathalie Duval-Couetil and Ziyu Long ............................................................................ 63

A Comprehensive Framework for Entrepreneurship Education Dave Valliere, Steven A. Gedeon, and Sean Wise .............................................................. 89

Expectancy Theory and Entrepreneurial Motivation: A Longitudinal Examination of the Role of Entrepreneurship Education Dan K. Hsu, Rachel S. Shinnar, and Benjamin C. Powell ............................................... 121

The Education of Entrepreneurs: An Instrument to Measure Entrepreneurial Development Kenneth F. Newbold, Jr. and T. Dary Erwin ................................................................... 141

A Model for Experiential Entrepreneurship Education Thomas G. Pittz ................................................................................................................ 179

The Social Business Challenge: Experiencing Mission Driven Entrepreneurhip Caroline Glackin ............................................................................................................... 193

----2014-2015 Officers---Association for Small Business & Entrepreneurship Eugenie Ardoin, University of Louisiana at Monroe President Henry Cole, University of Louisiana at Monroe President Elect Daniel James Scott, University of South Florida St. Petersburg Vice President – Programs Carl Kogut, University of Louisiana at Monroe Vice President – Membership Courtney Kernek, Southeastern Oklahoma State University Treasurer & Secretary Lauren Babin, University of Louisiana at Monroe Past President

Dear JBE Readership: We are delighted to introduce this special issue of Journal of Business and Entrepreneurship focused on entrepreneurship education and ecosystems. The purpose of this special issue is to develop a deeper understanding of the concept of the entrepreneurship mindset through theory building as well as empirical studies in the context of ecosystems. We hope to encourage, develop, and expand discussions regarding entrepreneurship education and entrepreneurial ecosystems. The phenomena of building and strengthening ecosystems through entrepreneurship education have been attracting considerable attention in recent years as seen by the increase of peer-reviewed publications covering various aspects of the topic. In two studies, Katz (2003) and Solomon and Weaver (1994) the growth of entrepreneurship education was measured and shown to have grown significantly from a handful of programs in 1970 to over 1000 in 2003. This exponential growth in programs points to increased legitimacy and acceptance of the discipline as a research domain (Pittaway and Cope, 2007). This growth domestically continues to fuel international development in entrepreneurship education and research on ecosystems. The special issue purposefully did not narrowly define “entrepreneurship education” or “ecosystems” and left the interpretation to the submitting authors. This allowed for a much broader scope of submissions as the call actively avoided a priori definitions and descriptions of the key topics. The genesis for this special issue evolved out of the Entrepreneurship Education Project (EEP) led by Drs. Doan Winkel, Jeff Vanevenhoven, and Eric Liguori. The Entrepreneurship Education Project was first formally introduced in a Journal of Small Business Management (2013) special issue as a brief overview; its purpose is to serve as a global research initiative “through which university students offer entrepreneurship educators and researchers datadriven insights into the impact of entrepreneurial education” (Vanevenhoven and Liguori, 2013). This is done by addressing two main research questions: first, what are the motivational processes underlying the students' road to entrepreneurship and through the entrepreneurial process, and second, what is the process of identity transformation from student to entrepreneur. Grounded in Social Cognitive Career Theory the EEP dataset is the largest, most comprehensive study of entrepreneurship education to date. Phase I data consist of over 18,000 student responses, spanning over 70 countries and 400 universities. Resulting from the EEP and the JSBM special issue, we sought to further explore the relationships of the EEP data including those from a more broad scope within entrepreneurial ecosystems. We held the inaugural EEP conference in March of 2014 at The University of Tampa (Florida, USA). The purpose of the conference was to work in two related domains: entrepreneurship education and entrepreneurial ecosystems, and work at the intersection of these two domains (viz., University Roles in Entrepreneurial Ecosystems). We encouraged papers relating to the theory or practice of either domain, broadly defined. Also solicited for contribution were non-author attendees with expertise in related areas to attend and participate in the dialogue. All paper submissions were blind reviewed, and the

most promising and provoking papers were invited to submit to this special issue (subject to JBE’s normal double-blind peer review process). Due to the deliberate openness of the call, we could not predict what large or common themes would emerge from the collection of papers in this special issue. What the authors found in common is recognition that there is still much work to be done, and the merits of such efforts are critical to our continued success both in the classroom and in the global economic environment. This may be due to the difficult economic recovery found globally in our current context. Often people look to entrepreneurship and innovation as an antecedent to improved economic recovery and development. The fact is that economic development is a complex issue, and the solution to economic recovery is equally complex. One of the most popular ways to encourage this behavior is to have business outreach services, and impactful entrepreneurship education. Unfortunately, for one of the most discussed topics in economic development, entrepreneurship, and its effectuation through education is still in an early stage of understanding. While there are a number of studies currently taking place, there are many areas that are not getting the attention deserved. The domains of entrepreneurship education and ecosystem development drove the call for this special issue. Knowing that entrepreneurship can help in long-term economic recovery and growth, we find it important to better understand how entrepreneurship is taught and how we can become more informed on the elements of ecosystem development. So why would any organization spend so much effort in researching entrepreneurship education? How can we justify the growth in academic programs, increased government support, and the attention from private industry? As the papers in this issue show, creating an entrepreneurial mindset and culture is critical to meaningful entrepreneurship and innovation within an ecosystem. An entrepreneurial mindset can be developed through training and practice. This training and practice needs to transcend learning institutions and the realization of that learning is the responsibility of the learning institutions. It is our sincere hope that the collection of articles comprising this special issue contribute to our understanding of how to increase the efficacy of students’ entrepreneurial mindsets, and that as a result continued economic development and prosperity results. Lofty hopes, perhaps, given this is academia, but at the end of the day we were told we could never get 10,000 global respondents, and we nearly doubled that; we were told we’d never gain critical mass as an initiative, and here we are, so let us keep pushing the envelope and working towards meaningful research that contributes to theory and informs practice. Sincerely, Dr. Eric Liguori, Guest Editor Dr. Jeff Vanevenhoven, Guest Editor Dr. Dean Koutroumanis, Guest Editor Dr. William Jackson, Editor-In-Chief

----Editorial Review Board---Joshua Abor University of Stellenbosch

Donald W. Garland New Mexico State University

Joe Ballenger Stephen F. Austin State University

William C. Green Sul Ross State University

Jurgita Baltrusaityte-Axelson Stockholm School of Economics

Walter E. Greene Greene and Associates

Stephen S. Batory Bloomsburg University

Marko Grünhagen Eastern Illinois University

James A. Bell University of Central Arkansas

Robert D. Gulbro Athens State University

Thomas M. Box Pittsburg State University

Stephen C. Harper University of North Carolina ~ Wilmington

Susan Boyd University of Tulsa

E. Alan Hartman University of Wisconsin ~ Oshkosh

Steve Brown Eastern Kentucky University

Diana M. Hechavarria University of South Florida

Kent Byus Texas A&M ~ Corpus Christi

Marilyn M. Helms Dalton State College

Thomas M. Cooney Dublin Institute of Technology

Colin Jones University of Tasmania

James A. DiGabriele DiGabriele, McNulty & Co. LL

Minjoon Jun New Mexico State University

Paul Dunn University of Louisiana ~ Monroe

M. Riaz Khan University Massachusetts Lowell

João J. M. Ferreira University of Beira Interior

Naresh Kumar NESH Training and Consultancy

Charles Fischer Pittsburg State University

Vaidotas Lukosius Tennessee State University

Keishiro Matsumoto University of the Virgin Islands

Harriet Stephenson Seattle University

Shaun McQuitty Athabasca University

Tulus Tambunan University of Trisakti

Teresa V. Menzies Brock University

Leslie Toombs Texas A & M Commerce

Jay Nathan St. John’s University

Raydel Tullous University of Texas ~ San Antonio

Barbara R. Oates Texas A&M ~ Kingsville

Jude Valdez University of Texas ~ San Antonio

Linda Ann Riley Roger Williams University

Jeff Vanevenhoven University of Wisconsin Whitewater

Christopher M. Scalzo Morrisville State College

Rebecca J. White University of Tampa

Mark T. Schenkel Belmont University

Densil Williams University of West Indies Mona

Philip Siegel Florida Atlantic University

Phillip H. Wilson Midwestern State University

Joseph F. Singer University of Missouri Kansas City

Marilyn Young University of Texas ~ Tyler

A REVIEW OF THE ENTREPRENEURIAL ECOSYSTEM AND THE ENTREPRENEURIAL SOCIETY IN THE UNITED STATES: AN EXPLORATION WITH THE GLOBAL ENTREPRENEURSHIP MONITOR DATASET Diana M. Hechavarria University of South Florida

Amy Ingram Clemson University ABSTRACT

Recently scholars have paid increasing attention to the importance of the entrepreneurial ecosystem in advancing an entrepreneurial society. One important subsystem of the ecosystem is public policy because of its role in shaping entrepreneurial outcomes. Subsequently, this paper explores how entrepreneurial thought has shifted public policy from a managed economy towards an entrepreneurial society. To unpack the relationship between the entrepreneurial ecosystem, entrepreneurship policy and the impact on entrepreneurial activity, we explore the entrepreneurial society further by conceptualizing the entrepreneurial ecosystem and its dimensions. We then lever the GEM data, to empirically examine the entrepreneurial ecosystem, from 2001-2012. Our findings highlight that several aspects of the entrepreneurial ecosystem are diminishing. Further, the rate of early stage entrepreneurial activity has been declining and there has been an increase in the rate of business deaths. We find preliminary evidence that the entrepreneurial ecosystem has weakened. INTRODUCTION An entrepreneurial society (Audretsch, 2007) is based on people advocating individually driven values that promote innovative venturing as a desirable career option. It is the pervasive socio-economic mindset of thinking in terms of opportunities (Thurik, 2008). In turn, this society recognizes the pivotal role entrepreneurship plays in fueling economic growth (Audretsch, 2007). Yet, there are only practical, if imperfect, road maps to jumpstart venturing activities, and governments play a pivotal role in cultivating such environments, or ecosystems, that nurture and sustain entrepreneurship (Isenberg, 2010). The ecosystems approach highlights the complex inter-linkages among a variety of participants in an entrepreneurial society (e.g., entrepreneurs, educators, corporations, the media and a

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diverse set of government ministries) and the importance of the incentives the various actors encounter as they push towards an entrepreneurship-friendly environment (Wessner, 2004). As a result, the desire to foster an entrepreneurial society among practitioners and academics, alike, has reinforced the significance of entrepreneurial ecosystems in linking multiple stakeholders to foster and sustain venturing. A key component of the entrepreneurial ecosystem is public policy. Public policies are designed and implemented to address specific problems. Lundstrom and Stevenson (2005) define entrepreneurship policy as measures taken to stimulate entrepreneurship; that are aimed at the pre-start, the start-up and post-start-up phases of the entrepreneurial process; designed and delivered to address the areas of motivation, opportunity and skills; with the primary objective of encouraging more people to start their own businesses. Thus, entrepreneurship policy covers measures undertaken to establish entrepreneur-friendly legal and regulatory frameworks intended to foster the process of entrepreneurship in an economy. Incremental changes in policy are then made to entrepreneurship policies as new challenges arise. However, instances occur when significant new challenges appear that established systems of managing them are judged inadequate. Fortunately, a main aspect of public policy is to capture and promote such changes during these challenges. This process coincides with an ecosystems perspective of entrepreneurship. An ecosystem approach suggests that, first, a system is not fixed but evolutionary, growing and evolving according to new needs and new circumstances. Secondly, a system is susceptible to change as a result of new policy initiatives. The ecosystems concept is useful because it highlights both the changes that take place in an entrepreneurial system and the need for policy to address the complex challenges faced by entrepreneurs. Since a myriad of factors contribute to fostering a healthy ecosystem that supports an entrepreneurial society, scholars note the importance of historical development to understand how public policy supports or hinders changing aspects of the entrepreneurship phenomena (Aldrich and Wiedenmayer, 1993; Gartner and Shane, 1995). Indeed, whether entrepreneurship increases or decreases in a society at any one particular moment in time depends on events and factors preceding it. Moreover, what happens today sets the groundwork for the possibilities of tomorrow. Due to the fact that public policy is a fundamental aspect of the entrepreneurial ecosystem, we review the context of public policy in the United States since the 1980s to understand the historical development of the entrepreneurial society. We focus on the period after 1980 because it coincides with the decline of the managed economy, and the shift toward the entrepreneurial economy in the United 2

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States (Audretsch and Thurik, 2000). The managed economy is defined as an economy where economic performance is positively related to firm size, scale economies and routinized production and innovation. Conversely, the entrepreneurial economy is an economy that is innovation-driven, characterized by knowledge spillovers and increased competition (Acs and Amoro´s, 2008; Audretsch and Thurik, 2004;). Indeed, the trend away from large enterprises towards the reemergence of small business in the United States during the 1980s coincides with a shift in priorities among policymakers to small-medium sized enterprises. The prioritization of the entrepreneurial economy stems from the widespread belief that entrepreneurship is perhaps the most important and scarcest input factor of modern highly developed economies (Audretsch and Thurik, 2004). Correspondingly, entrepreneurial policy enactments have aimed at promoting the capacity and desire among the population to engage in and generate entrepreneurial activity, thus encouraging an entrepreneurial society (Audretsch, 2009). Reviewing the historical basis of public policy, there is considerable evidence of initiatives that reinforced this shift away from big business. Specifically, initiatives that constraining the freedom of firms to contract through regulation, public ownership and antitrust were minimized. Resulting in a new set of enabling policies which encouraged the creation and commercialization of new knowledge instrumental to the entrepreneurial society in the United States (Audretsch and Thurik, 2001) Because of the importance of the entrepreneurial society driving entrepreneurial activity and stimulating this vast economic development, this paper seeks to describe how public policy in the United States since the 1980s has reflected the shift from the managed economy to the entrepreneurial economy. Secondly, we aim to explore if the state of the entrepreneurial ecosystem, the key facilitators of an entrepreneurial society in the United States, has been improving or declining. Finally, we also examine how the entrepreneurial society is manifesting itself in the United States via different kinds of venturing activities. To do this, we unpack the evolution of entrepreneurial thought and policy in the United States over the last few decades. Using the application of history (Goodman and Kruger, 1988) to unify the existing and wide-ranging concepts underlying entrepreneurship, we contextualize how different perspectives in entrepreneurial scholarship have been used to justify entrepreneurship policy in the United States. Therefore, this paper highlights how different traditions of entrepreneurial thought have shaped the development of entrepreneurial policy, and prioritized different kinds of entrepreneurial activity at different points in time, ultimately leading to the current focus on entrepreneurial society in the United States. Journal of Business & Entrepreneurship

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Rather than focusing on the effectiveness of an individual government policy, our focus is about examining the development of public policy aimed at fostering an entrepreneurial society in the United States. In addition, we intend to describe the state of the entrepreneurial ecosystem that is essential in maintaining and fueling the entrepreneurial society in the United States. Our results highlight that while the rate of informal business angel financing and established business ownership has been increasing in the United States, the rate of total early stage entrepreneurial activity has been declining between 2001-2012. Coupled with an increase in the rate of business deaths, this illustrates a very volatile picture of current entrepreneurship activity in the United States. Furthermore, we find a decrease in innovative venturing activity might indicate that the United States is struggling to preserve a knowledge-based entrepreneurial economy. Overall, we find that several components of the entrepreneurial ecosystem are declining, likely contributing to the decline in entrepreneurial activity in the United States. Our work contributes to entrepreneurship literature by contextualizing the historical narrative of public policy in the United States since its shift to an entrepreneurial economy. We demonstrate how entrepreneurship theory has impacted past entrepreneurial policy frameworks, and has brought about the field’s current focus on the entrepreneurial ecosystem as a means to promote and support the entrepreneurial society. We also provide exploratory analysis of structure and mechanisms associated with an entrepreneurial society and entrepreneurial ecosystem that will help inform future research intersecting between these domains. The paper proceeds as follows: first, we contextualize how key entrepreneurial research and thought has coincided with different kinds of entrepreneurial policy in the United States. Next, we discuss the entrepreneurial society, entrepreneurial ecosystem and embedded entrepreneurial activity, and attitudes. Then, we empirically examine the entrepreneurial ecosystem using data from the Global Entrepreneurs Monitors National Expert Individual Population database, highlighting how several aspects of the entrepreneurial ecosystem are diminishing. Finally, we provide directions for future research at the intersection of these two domains that merit serious attention in the field of entrepreneurship. THE RISE OF THE ENTREPRENEURIAL ECONOMY The managed economy, which dominated the United States until about the 1980s, was based on relative certainty in outputs, which consisted mainly of manufactured products and which were brought forward by the traditional inputs of 4

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labor, capital and land (Thurik, 2008). The major public policy issues addressed in the managed economy model centered on concerns about excess profits and abuses of market dominance. Therefore, the managed economy model emphasized constraining market power through regulation (Audretsch and Thurik, 2004). As a result, business public policy was largely aimed at fostering an economy characterized by large-scale production, reflecting the predominance of capital and unskilled labor as the sources of economic performance. Accordingly, large firms dominated the managed economy while small firms and entrepreneurship were viewed as a luxury (Thurik, 2008). However, several studies began to show a trend away from large firms in the United States beginning in the late 1970s, and the emergence of small business (Brock and Evans, 1989; Loveman and Sengenberger, 1991; Acs and Audretsch, 1993). This change led to the entrepreneurial economy, an economy where economic performance is related to distributed innovation and the emergence and growth of innovative ventures (Audretsch and Thurik, 2010). The entrepreneurial economy is characterized by flexibility, turbulence, diversity, creativity and novelty (Thurik, 2007). Under the entrepreneurial economy model, the focus on business policy was aimed at stimulating firm development and performance through enabling policies (Audretsch and Thurik, 2004). Such enabling business policies target the promotion of international competitiveness, growth, and job creation via new firms. Consequently, the capacity to engage in and successfully generate entrepreneurial activity is the objective of business public policy in the entrepreneurial economy. Indeed, Kayne (1999) claims that, “states – through their laws, regulations, investments, and programs – have considerable impact on where entrepreneurs choose to establish new enterprises and the probability that those enterprises will succeed” (p.2). Others argue that if governments can take supporting measures in the interest of a more favorable climate, a more “entrepreneurial” attitude is demanded of the knowledge centers and firms themselves (Van Looy, Debackere &Andries; 2003). The primary responsibility in developing an entrepreneurial ecosystem and enforcing the legal and regulatory framework rests with the government. This can be achieved through apt policy initiatives and other specially designed programs (Bhat and Khan, 2014). While entrepreneurs undertake a definitive action by starting a new business, this action cannot be viewed in a vacuum devoid of context. Entrepreneurship is shaped by a collection of forces and factors, which include legal, institutional and social, among others (Verheul, Wennekers, Audretsch, and Thurik, 2002). As a result, we review how public policy in the United States has reflected particular attention to different entrepreneurial perspectives by informing policy goals and outcomes. Journal of Business & Entrepreneurship

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Entrepreneurship Public Policy in the United States Since 1980 Using the views of entrepreneurship proposed by Schumpter (1949), Knight, (1971), Kirzner (1973) and Venkataraman (1997), it is possible to trace the distinct evolution of the entrepreneurial economy over the last few decades towards the entrepreneurial society perspective. This transition corresponds with distinct ideologies that have influenced the progression of entrepreneurship public policy from outcomes associated with innovation, growth, business creation, self-employment, risk associated with venturing, and finally now an entrepreneurial society. This ideological shift towards the entrepreneurial society corresponds with the interest in the ecosystems framework because it captures the various stakeholders and socially constructed aspects of which new firms are embedded in (CITE). Furthermore, scholars note that the concept of the entrepreneurial economy is so broad that the entrepreneurial society better captures the various social and economic dynamics that influence venturing (Bonnet, Dejardin, and Madrid-Guijarro, 2012). Thus, we examine the entrepreneurial society rather than entrepreneurial economy. Overall, the evolution of entrepreneurial thought has influenced public policy; thus, it prioritizes the entrepreneurial society. Many in the policy domain apply Schumpeter’s (1949) work when promoting innovation and growth. Accordingly, development of entrepreneurial policy that encouraged extensions of small and medium enterprise (SME) policy followed the Schumpeterian logic of entrepreneurial growth and innovation (Lundstrom and Stevenson, 2005). Since research generally found SMEs were less efficient than larger firms and marginally involved in innovative activity during the post-war economies in North America and Western Europe, entrepreneurial policy following the Schumpterian tradition focused on principals of efficiency associated with high growth and innovation. Therefore, ensuring access to finance for innovation has been the main driver behind policy enactments following the Schumpeterian tradition. For instance, the democratization of credit markets has supported growth for many new firms without access to other sources of wealth (Blanchflower, Levine, and Zimmerman, 2003; Acs and Stough, 2008). Entrepreneurial policy initiatives following the SME framework were typical during the Carter Administration in the United States (1979-1981). The Carter administration favored deregulating industries under the premise that deregulation would spur innovation and increased flexibility that comes from opening up these industries to competition (Le, 2008). Carter’s tenure has been classified as an 6

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entrepreneurship policy agenda spurring innovative actives by improving the government’s effectives at transferring innovative technologies from the government to the private sector (Le, 2008). As a result, since efficiency and innovation were the goals under his administration, it clearly falls within the SME framework of public policy. However, entrepreneurial policy should be different than tactics utilized in SME policy because new ventures are different than small business ventures (Hart, 2003). As a result, the focus of entrepreneurial policy shifted to business creation, and subsequently drew on the work of Knight (1971). Another common definition levered from foundational entrepreneurial research is based Knight´s work. His work is often referenced when the policy objective is to create businesses through self-employment (Knight, 1971). Knight emphasized that an entrepreneur is a risk-taking and business ownership (Knight, 1921). Thus, extensions of entrepreneurial policy following this tradition focused on easing business creation by minimizing risks associated with new business creation. Entrepreneurs cannot be expected to take the plunge, so to speak, unless it is easy and inexpensive to do so (Acs and Stough, 2008). Therefore, public policy aimed at facilitating business creation, intends to minimize the uncertainty and risk associated with entrepreneurship, thereby promoting self-employment. Consequently, entrepreneurial policies that promote incentives to enterprise are advocated. For example, policy makers have attempted to increase the attractiveness of entrepreneurship as a career choice by lowering the tax rate for new firms (Lundström & Stevenson, 2002). The Ronald Regan era (1982-1989) in the United States followed this framework of entrepreneurial public policy. The Regan Administration supported increasing efficiency maximization and innovation among entrepreneurial ventures, and focused on minimizing the risk and uncertainty associated with the process. Specifically, the Regan Administration believed that taxes primarily affected individuals and business economic incentives; therefore, they orchestrated tax reforms designed to increase economic incentives for business investment, new venture creation, and savings (Le, 2008). As a result the entrepreneurial policy agenda under the Regan Administration captured elements of both the past SME policy framework of efficiency, growth, and innovation, yet also focused on the new business creation perspective. Furthermore, other policy enactments in North America and Western Europe have included personal income tax incentives and fiscal incentives, easing administrative red tape, as well as deregulating labor market and bankruptcy legislations (Huffman 2010). However, businesses just do not appear spontaneously. The advent of the knowledge economy dramatically shifted the priorities among Journal of Business & Entrepreneurship

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policy makers from investing in physical capital to investing in knowledge (Audertsch, 2009). Consequently, the focus among policy makers shifted toward facilitating the discovery process among potential entrepreneurs, rather than business creation. This discovery process coalesces with Kirzner’s (1973) definition which focuses on alertness to profit-making opportunities where entrepreneurs discover opportunities from inherent market inefficiencies and act upon them. Policy enactments utilized among North America and Western Europe that support the advent of alertness to opportunities include well-defined and enforced property rights, freedom of contract and its enforcement, limited interference from government with market outcomes, low barriers to market entry, access to foreign markets, and ease of technology transfer (Hoffman, 2010). The George H.W. Bush administration (1989-1993) followed an agenda akin to entrepreneurship policy promoting opportunity recognition among potential founders. The Bush administration believed the private sector, not the government, created economic growth and favored entrepreneurial policy that promoted competition and free markets. Particularly, the North American Free Trade Agreement (NAFTA) initiated by Bush is a principal example of how entrepreneurial policy was moving from efficiency maximization directed at prompting entrepreneurial behavior. NAFTA eliminated barriers to trade and commerce in North America. According to a 2003, Congressional Budge Office (CBO) study, U.S. exports to Mexico increased by $1.1 billion dollars in 1994, and $10.3 billion by 2001 (Le, 2008). However, the ability to recognize opportunities more readily alone does not ensure exploitation. Knowledge is a key factor of production, but there is also a contextual component that can influence an individual’s propensity to venture. As a result, the current evolution of entrepreneurship ecosystem takes a more holistic approach to understanding this social phenomenon. Following Venkataraman (1997), we define entrepreneurship broadly as the discovery, evaluation, and utilization of future goods and services. This perspective of entrepreneurship is multidisciplinary and draws from the discipline-based areas of economics, sociology, psychology, marketing, management, and economics (Murphy, Liao, Welsch, 2006). Such multidisciplinary contributions are the principal drivers of the entrepreneurship field’s development into its current state. This approach emphasizes all facets of the entrepreneurial process, from discovery, exploitation and growth. Furthermore, we believe this multidisciplinary perspective coincides with the current state of policy which is aimed at sustaining and fostering entrepreneurial values within our society, also known as the “entrepreneurial society” (Acs and Audrestch, 2003). An entrepreneurial society is a society who is globally competitive 8

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on the basis of knowledge. The cultural norms that support venturing, and reward such activity are imperative to sustain an entrepreneurial society. In other words, the goal is not to reproduce the entrepreneurial economy, but to foster a society that values venturing activity, and has a high propensity to engage and assist in facilitating it. A large body of research argues that policy enactments should focus on developing an entrepreneurial society by targeting knowledge, encouraging cultural values, promoting and rewarding entrepreneurship (Acs and Stough, 2008; Audretsch, 2007). The training and education of the entrepreneurial mindset among potential entrepreneurs is the first step to creating a competitive knowledge economy. Specifically, new knowledge that universities produce is more important than it was in the early 20th century. For instance, knowledge spillovers from universities can lead to radical innovation and radical innovation accounted for significant acceleration in the United States’ productivity growth (Acs Audretsch, 1989), particularly over the last decade. Policy enactments in North America that support an entrepreneurial society via knowledge often focus on creating competitive communities by promoting regional innovative clusters. For example, the Barack Obama Administration (2009-2016) allocate $50 million in regional planning and matching grants with the Economic Development Administration (EDA) to support the creation of regional innovation clusters that leverage regions’ existing competitive strengths. This allocation also launched a $50 million initiative in the EDA that created a national network of business incubators to encourage entrepreneurial activity. In addition, an entrepreneurial society also needs to stimulate cultural norms that value venturing activity to be competitive. Particularly, positive attitudes towards entrepreneurs, risk attitudes in society and the desire for business ownership are key cultural values of an entrepreneurial society (Ahmad and Hoffman, 2008). The United States, in particular, is often singled out as a country with an inherently large number of people who are keen to start firms. For example, in a survey, Blanchflower, Oswald, and Stutzer (2001) found that a large number of people in the United States would prefer to be self-employed rather than be employed by the labor market. Policy enactments pursued in North America that support an entrepreneurial society via cultural values often focus on mentorship. For example, the Barack Obama Administration facilitated training and mentorship for entrepreneurs by providing additional resources to the Small Business Administration, community colleges, universities and philanthropic organization to deliver more mentoring services to aspiring entrepreneurs to create new businesses.

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Taken together, the entrepreneurial society illustrates the shift in preferences from the managed economy to the preference for an entrepreneurial economy in the United States. Moreover, it supports Baumol’s (1993) position that the entrepreneurship mechanism is always present in communities and societies, but its manifestation is contingent on varying dominant logics and reward systems. Therefore, the goal of the entrepreneurial society is to promote the capacity and desire among the population to engage in and generate entrepreneurial activity. Considering the ideology of the entrepreneurial society suggests that a considerably broader policy approach may be more effective, and in particular, one that re-orients all institutions towards promoting entrepreneurial behavior (Stam and Nooteboom, 2011). Accordingly, policymakers are beginning to recognize the merit of a more systemsbased form of support for an entrepreneurial society (Mason and Brown, 2013). This represents a shift away from firm-specific interventions of the entrepreneurial economy, towards more holistic activities which focus on developing networks, aligning priorities, building new institutional capabilities and fostering synergies between different stakeholders (Rodriguez-Pose, 2013). One emerging approach is the focus on entrepreneurial ecosystems (Zacharakis, Shepard, Coombs, 2003; Isenberg, 2010, Malecki, 2011; Kantis and Federico, 2012; Feld, 2012). It is argued that in dynamic ecosystems new firms have better opportunities to grow and create employment, in turn nurturing an entrepreneurial society (Rosted 2012). Consequently, we utilize the GEM Adult Population and Expert Databases to identify how the entrepreneurial society and entrepreneurial ecosystem has manifested and changed between 2001-2012. Cultivating an Entrepreneurial Society: Entrepreneurial Ecosystems, Activity and Attitudes in the United States The entrepreneurial society refers to places where knowledge-based entrepreneurship has emerged as a driving force for economic growth, employment creation and competitiveness in global markets (Audretsch, 2009). This society facilitates entrepreneurial driven economic growth through an institutional context that is conducive to entrepreneurial activity (Audretsch, 2014). It is the pervasive socioeconomic mindset of thinking in terms of knowledge as a source of competitive advantage rather than in terms of resources (Thurik, 2008). It is based upon ideas and knowledge as opposed to investments creating more of the same. It is based upon persons rather than on organizations. The goal of the entrepreneurial society is not just

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to promote technology transfer and increase the number of startups, but to promote change. Two aspects are particularly important in evaluating the effectiveness of the existing entrepreneurship ecosystem in cultivating an entrepreneurial society. First, measures of entrepreneurial activity examine the current entrepreneurship levels in the country, and serve as a gauge for ongoing economic growth. Second, entrepreneurial attitudes and intentions provide measures of the potential for additional entrepreneurial activity and associated economic growth (Regele and Neck, 2012). A cursory examination of data from the GEM suggests that the United States entrepreneurship is not as dominant in either activities or attitudes as is commonly believed. The United States scores on GEM’s primary measure of entrepreneurial activity, Total Entrepreneurial Activity (TEA), have been declining over time. Currently, the United States ranks only 26th out of 70 countries on this measure (Amorós, Bosma, and Levie, 2013). Examining entrepreneurial activity Reviewing the rate of nascent entrepreneurship, baby new businesses and established businesses, we can discern an identifiable pattern over the twelve-year period analyzed.i There is a clear negative linear trend for nascent venturing activity from 2001 to 2010, with nascent activity peaking at 8.3% in 2005 (see Figure 1). However it should be noted, that in 2011 nascent venturing activity peaked again at about 7.8%, and 8.5% in 2012, signaling that nascent venturing activity in the United States maybe on the rise again (Kelley, et al., 2011; 2012). Likewise, baby business rates display a negative linear trend over time, considerably in 2005 from 4.25% to about 1.9% in 2012 (see Figure 1). Reynolds (2007) found that the two main factors impacting actions towards the creation of a new firm were education and experience. According to Middleton (2010), environmental factors that facilitate venturing activity are based on the concept of a learning space (Kolb and Kolb, 2005) because it enables interactive learning. Consequently, creating an interactive space for entrepreneurship education and experience will help prospective entrepreneurs gain legitimacy and reduce uncertainty and ambiguity surrounding the act of venturing. Environmental factors that shape a learning space in which entrepreneurial behavior development can take place include structural components such as policy or legal requirements, physical resources, and/or technology. The factors of the environment with social components that influence a learning space include: networks of actors with knowledge, networks of actors who provide support, mentors or role models and/or competitors. Journal of Business & Entrepreneurship

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Established business ownership rates showed considerable stability overtime, with the exception of 2005 and 2007, and peaked in 2011 at about 9.0% (see Figure 1). Although the United States shows increasing rates of established businesses, we must continue focusing on knowledge spillovers via entrepreneurship to remain competitive (Audretsch, 2009). Investment in new knowledge is crucial, especially for economies whose competitiveness is derived from ideas, creativity and knowledge, like the United States. Data for death rates, or business closures, shows stability overtime. Moreover, business closures have implications for the entrepreneurial ecosystem, specifically in regards to business churning. Business churning is the sum of birth and death rates of firms, and indicates how frequently new firms are created compared with how often existing enterprises close down (Ahmad, 2008). The indicator reflects a country's degree of "creative destruction" (Schumpeter, 1942). Moreover, it indicates the contribution of churning to aggregate productivity and economic well-being. Vibrant economies have one thing in common: business churning (Scarpetta and Tressel, 2002) Geroski (1995; p. 424) argues that “…entry and exit seem to be part of a process of change in which large numbers of new firms displace large numbers of older firms without changing the total number of firms in operation at any given time by very much.” Therefore, business death is part of the firm life cycle, which should also be taken into consideration when developing an entrepreneurial ecosystem to promote an entrepreneurial society. It is hard to estimate the optimal ratio of new entry to business deaths. However, one could argue that ideally, net nascent and new business entry should outpace business deaths. In 2007, the rate of business deaths outpaced the rate of baby businesses (see Figure 1). In other words, the level of business deaths kept growing along with the overall level of businesses in the economy, but the level of new baby business births did not. Baby Businesses held relatively steady before dropping considerably in the recent 2007 downturn. In fact, business deaths now exceed business births for the first time in the thirty plus-yearhistory of data (Hathaway and Litan, 2014). However, the average rate of nascent venturing activity still outpaces the average rate of business deaths; therefore, the aggregate rate of would-be-entrepreneurs is still 1.8 times larger than the aggregate rate of business deaths in 2012. Comparatively, there are 0.42 new baby businesses for every business closure in the United States for 2012. Finally, informal investing in the United States peaked in 2006 at 6.1% and in 2010 at about 5.9% (see Figure 1). In regard to informal investment, via business angel financing, the United States is positioned strongly. So much so, there were more 12

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business angels per 100 in the population than nascent entrepreneurs or baby business owners in 2010. Although there has been a significant decline in the perceived availability of funding, as reported by GEM experts, the fact of the matter is that informal financing sector in the United States is very active. During the period of 1999 to 2012, the average amount of informal financing in the United States was about $38,453 per business angel. Government can play an important catalytic role in helping improve both the perception and availability of financing for entrepreneurs, but the key is to provide incentives for private investors, both individual and institutional, to come into the market. Crowd funding, in light of the new JOBs Act in the United States which will allow equity crowd funding, is an example of one such initiative aimed at incentivizing private investors. Figure 1. Venturing Activity in the United States: 2000-2012 Weighted by US Population

The entrepreneurial society in the United States has experienced a considerable period of volatility and change during the last decade. This is particularly due to the 2007 financial crisis, which did not originate in, but was merely revealed by the socalled "credit crunch" (O’Regan and Maclean, 2009). According to Audretsch (2009), Journal of Business & Entrepreneurship

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the financial crisis is actually a symptom and not a cause of a more underlying deeper structural problem; societies have become addicted to looking for higher returns from financial investments rather than from innovative activity. Although the popular press portrays the typical entrepreneur as someone like Bill Gates of Microsoft, or Mark Zuckerberg of Facebook, in fact, the overwhelming majority of entrepreneurs are people starting “reproducer” organizations. Reproducer organizations are defined as those organizations started in an established industry that are only minimally, if at all, different from existing organizations in the population. In contrast, the number of entrepreneurs creating innovative new firms that could potentially open up new niches or even entirely new industries is very small (Aldrich and Kenworthy, 1999). We subsequently use the term “innovator” organizations to refer this type of early stage of entrepreneurial activity in GEM. We use three criteria to capture innovator TEA: (1) the venturing activity in which all or some of the venture’s potential customers consider this product or service new and unfamiliar; (2) there are few or no other businesses offering the same products or services to potential customers; (3) and the technologies or procedures required for the venture’s product or service have been available for less than five years. Examining the available data from GEM, we can see that 16.2% of TEA activity was considered to be innovative, versus 83.8% of all venturing activity to considered reproducer-oriented (see Figure 2). Since 2002, there has been a slow decline in innovator-oriented venturing activity, until 2011, where there was about a 29% increase in innovator-oriented venturing from 2010. Innovation benefits society through new and improved products and services. Innovative and reproducer forms of entrepreneurship co-exist in all countries. No country is characterized by only imitative or innovative new business ventures. Additionally, the distribution of innovative and imitative forms of entrepreneurship varies significantly across countries (Koellinger, 2008). According to Kelley, Singer and Harrington (2011), many of the innovation-driven economies with the highest total early stage entrepreneurial activity rates, like the United States, show moderate proportions of innovativeness, indicating that there may be a trade-off between quantity and quality dimensions in their entrepreneurial activities.

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Figure 2. Innovative and Non-innovative Venturing Activity in the United States: 2002-2011 Weighted by US Population

While the United States, as a whole, reported an overall entrepreneurship rate of 12.3% in 2011, the size and diversity of this country may imply some differences among regions (Kelley, 2012 et al., 2013). Therefore, we analyzed ten regions, following the United States Small Business Administration’s classification of states into regions, and investigated how these U.S. regions vary in terms of nascent, baby business and established businesses.ii We pooled data collected between 2001-2010 to have sufficient cases in each region. The Mountain Plains and Pacific Northwest regions show the highest average rates of established business ownership rates (see Figure 3). In regard to new or baby business ownership, the Mountain Plains and the Pacific Southwest have the highest average rates. For nascent entrepreneurial activity, the Mountain Plains and New York/New Jersey region have the highest average rates. The Mountain Plains and the Pacific Southwest also have the highest rates of average business closures. Finally, informal investing activity is again also highest on average in the Mountain Plains and the Pacific Southwest. Put simply, Figure 3 shows that the broad decline in business dynamism occurring during the last decade nationally is not isolated to a few regions. In fact, the data show that it is a pervasive force evident in Journal of Business & Entrepreneurship

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nearly all corners of the country. All SBA regions, with the exception of New England, have higher average rates of business deaths than nascent or baby business births between 2001 and 2010. Figure 3. Average Venturing Activity in Ten United States Regions Weighted by US Population

Examining entrepreneurial attitudes and intentions On entrepreneurial attitudes, the United States has already fallen behind efficiency-based economies in that individuals in these countries are more likely to perceive good opportunities for starting a business than those in the United States. Even on measures where the United States remains ahead of efficiency driven economies, namely, its people are still more confident in their ability to capitalize on entrepreneurial opportunities and less afraid of the consequences of failing in these endeavors, the gap has been narrowing quickly (Arenius and Minniti, 2005; Kelley, et al. 2012). Figure 4 illustrates these findings. For instance, the perceptions of one’s own skills and experience have remained rather stable over the observed twelve-year period. Perceiving opportunities had a sharp drop among the United States population in 2006 and 2009, but has been steadily increasing. However, fear of failure among the United States population has steadily been rising since 2007. Some scholars suggest that GEM results indicate that the position of the United States as an

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entrepreneurial leader maybe diminishing (Regele and Neck, 2012). In concert, there has been a consistent decrease in the percentage of the United States population that knows an entrepreneur (see Figure 4). This statistic is one of relative concern. A report by the Kauffman Foundation (2013) quantifies the importance of such connections and shows that there is a strong link between knowing an entrepreneur and being one. More than one in three survey respondents who knew an entrepreneur were entrepreneurs themselves. Therefore, experiential learning and learning by doing, particularly through co-participation, can develop entrepreneurial behavior. This reinforces what many of us already believed to be true, that entrepreneurship is behavior learned in part through imitation. Figure 4. Entrepreneurial Intentions and Attitudes in the United States: 20012012 Weighted by US Population

Another relevant concept of importance is that of latent entrepreneurship, or the desire to be self-employed, whether or not they are actually planning to do so (Brixy, Sternberg and Stüber, 2012). Latent entrepreneurship comprises everyone who Journal of Business & Entrepreneurship

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in principle would prefer to be self-employed than employed in the labor force. In this manuscript, we follow Brixy, Sternberg and Stüber (2008) and use the respondents in GEM who have the expectation to start, either alone or with others, a new business within the next three years. This definition is more specific than the concept of latent entrepreneurship proposed by Blanchflower, Oswald, and Stutzer (2001) and Grilo & Irigoyen (2006) since it still captures an intention, but not concrete behavior. According to data available from GEM, about 15% of the United States population in 2002 expected to start a business in the next three years. This figure steadily declined to about 10% in 2010, and then subsequently increased to about 16% in 2012 (see Figure 5). Figure 5. Latent Venturing Intentions in the United States: 2002-2012 Weighted by US Population

We subsequently explore how the entrepreneurial ecosystem in the United States has evolved from 2001-2010, and identify what challenges, if any, have occurred in the ecosystem at the national level. We then present data from the United States GEM National Expert database to identify how the entrepreneurial ecosystem is

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manifesting itself, and if the entrepreneurial ecosystem is in turn creating a positive climate for venturing in the United States. The entrepreneurial ecosystem The term ecosystem was first coined by James Moore in an influential article in Harvard Business Review published during the 1990s. Moore (1993) claimed that businesses don’t evolve in a vacuum, and noted the relationally embedded nature of how firms interact with suppliers, customers and financiers. Therefore, we follow Mason and Brown (2013, p. 5) and define an entrepreneurial ecosystem as a set of “interconnected entrepreneurial actors (both potential and existing), entrepreneurial organizations (e.g., firms, venture capitalists, business angels, banks), institutions (e.g., universities, public sector agencies, financial bodies) and entrepreneurial processes (e.g., the business birth rate, numbers of high growth firms, levels of ‘blockbuster entrepreneurship,’ number of serial entrepreneurs, degree of sell-out mentality within firms and levels of entrepreneurial ambition) which formally and informally coalesce to connect, mediate and govern the performance within the local entrepreneurial environment.” Scholars note that new policies and programs focused on entrepreneurship by themselves may in fact be appropriate for a specific purpose, but in reality, they are developed within and constrained by the national institutional and policy framework, which embodies the entrepreneurial ecosystem (Petty and Bonardi, 2012). Researchers have cautioned that one size does not fit all when it comes to developing national level entrepreneurship programs (Bosma and Harding, 2007; Minniti, 2008). Any country may initiate policies and programs developed in another country and succeed in attracting entrepreneurs, but if the individual institutional environments are not considered then, ultimately, they may fail to establish a sustainable entrepreneurial environment that benefits the economy over the long term. In the absence of a deliberate strategy, policy makers run the risk of creating unintended negative consequences for entrepreneurs and the wider economy, including but not limited to, investment gaps, misallocation of resources, excessive churn, and market bubbles (Petty and Bonardi, 2012). Therefore, it is of relative interest to examine how the United States entrepreneurial ecosystem has been evolving over time. Policymakers need to have an understanding of entrepreneurial ecosystems in order to intervene effectively. This requires that entrepreneurial ecosystems are measured (Mason and Brown, 2013). As Vogel (2013b: 9) argued, “if we do not measure the effectiveness of the various components in an ecosystem, we will not be able to improve existing programs and put in place new and complementary sources.” Metrics Journal of Business & Entrepreneurship

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can help to determine the strengths and weaknesses of individual ecosystems, which in turn can help to interpret its special qualities or deficiencies and the strength of the ecosystem over time. Accordingly, we review the ecosystem model proposed and measured by GEM over time to highlight aspects of the United States entrepreneurial ecosystems that may be underdeveloped so policymakers can structure adequate interventions aimed at sustaining an entrepreneurial society. Examining the ecosystem through the GEM model Global Entrepreneurship Monitor (GEM) created and validated a conceptual ecosystems model (Reynolds, Bosma, Autio, and Hunt, 2005) based on the theory of entrepreneurship and economic development (Leibenstein 1968, 1978, 1995). This model suggests that established business activity at the national level varies with General National Framework Conditions, which captures the general business ecosystem, and is measured by the Global Competitiveness Index (Schwab and Sachs, 1998). Conversely, entrepreneurial activity varies with Entrepreneurial Framework Conditions, which captures factors directly related to the entrepreneurship ecosystem that were developed by GEM (Reynolds et al., 2005).iii The General Framework Conditions associated with established business include: openness to external trade, the role of government in business, efficiency of financial markets, intensity and level of R&D transfer, physical infrastructure, management skills, flexibility of labor markets, and unbiased institutions. The Entrepreneurial Framework Conditions associated with the entrepreneurship ecosystem are: access to entrepreneurial finance, government support and policies, the presence of government based entrepreneurship programs, entrepreneurship education, policies conducive to R&D transfer, legal and commercial infrastructure, market dynamics associated with change and openness, ease of entry regulations to start a business, and protection of intellectual property rights (see Table 1)iv. Overall, the GEM ecosystem model suggests that entrepreneurial activity responds to a different set of environmental parameters than established business activity, and that both of these ecosystems are interrelated. We reproduce the GEM conceptual model as shown in Acs et al. (2004) to illustrate the relationship between ecosystems, venturing activity, and economic growth (see Figure 6). And we subsequently focus on examining the GEM Entrepreneurial Framework Conditions since Levie and Hunt (2007) have found these conditions significantly influences entrepreneurial activity.

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Table 1. Entrepreneurial Framework Conditions from Expert Questionnairev Dimension

Description

Item Name

# of Items

Financial Environment

General funding and private equity

KIASUM*

6

Government Policy & Support

Support for entrepreneurship

KIBSU1

3

Government Policy & Taxes

Regulations support entrepreneurship

KIBSU2

3

Government Programs

Support entrepreneurship

KICSUM

5

Entrepreneurial Education

Primary, secondary, universities, management education

KIDSUM*

5

R&D Transfer

Access for new, growth firms

KIESUM

5

Commercial Infrastructure Access

Business services available for entrepreneurs

KIFSUM

5

Internal Market Dynamics

Market changes and shifts in structure and goods

KIGSU1

2

Internal Market Burdens

Access for new firms and market openness

KIGSU2

4

Physical Infrastructure and Services

Access for new firms

KIHSUM

5

Cultural, Social Norms Supportive

Value independence and accept career uncertainty

KIISUM*

5

Intellectual Property Rights

Protection for new firms

KIFNUM

5

Figure 6. GEM Conceptual Model

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Figure 7 illustrates the average values for the entrepreneurial ecosystem reported by national experts in the United States between 2001-2010. We subsequently focus on reviewing the Entrepreneurial Framework Conditions of the entrepreneurial ecosystem in the United States from 2001-2010. Figure 8 illustrates the changes in the Entrepreneurial Framework Conditions, or the entrepreneurial ecosystem, over a ten-year period in the United States. Using the data reported by national experts in the United States, we computed the compound annual growth rate (CAGR) and the percent change from 2001 to 2010. Since 2001, entrepreneurial ecosystem has demonstrated a considerable decline. According to expert reports, the financial environment for venturing has been the most adversely affected, with a 47.9% decrease since 2001. Conversely, the cultural norms that support entrepreneurship were least adversely affected, with only 4.86% decrease since 2001 (see Figure 8). Computing the compound annual growth rate on the yearover-year change in the entrepreneurial ecosystem, among the various dimensions, also finds evidence to suggest that the environment for venturing has become more unfavorable in the United States. Again, the financial environment for entrepreneurship has decreased on average 6.99% per year since 2001, whereas the cultural norms that support entrepreneurship have only decreased about 0.55% per year (see Figure 8). Figure 7. Average Rating of United States Entrepreneurial Ecosystem Between 2000-2010

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Figure 8. Changes in United States Entrepreneurial Ecosystem 2000-2010

DISCUSSSION This paper sought to demonstrate the recursive interdependent relationship between the development and maintenance of entrepreneurial policy, the ecosystem and the entrepreneurial society. Historically, entrepreneurial thought, as demonstrated via key entrepreneurial theories, drives the entrepreneurial policy by influencing key outcomes of policy interventions. Currently, the integrated approach advanced by scholars to sustain an entrepreneurial economy aims at a public policy framework that fosters an entrepreneurial society (Audrestch, 2009). The best framework available to structure policy interventions aimed at promoting an entrepreneurial society is based on a holistic and evolutionary understanding of entrepreneurial ecosystems, or how economic activity comes into being from a wider ecological environment in which firms operate (Mason and Brown, 2013). Using GEM data, we explored specific ecosystem factors from 2001-2010 and found that these factors were generally declining in the United States. Further, entrepreneurial engagement was also declining during 2001 to 2010. The decline in the United States entrepreneurial ecosystem is concerning for entrepreneurship, due to the fact that prior research has found a positive relationship between the entrepreneurial ecosystem and venturing activities and attitudes. For instance, Levie Journal of Business & Entrepreneurship

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and Autio (2007) have found significant support linking the GEM ecosystem model to venturing activity. Although fostering entrepreneurship is not new, this dominant societal focus on the entrepreneurial society today represents a shift away from the economic interventions of the managed economy that dominated among policymakers in previous decades, where it was common to try to attract large firms by providing substantial incentives (Chatterji, Glaeser, and Kerr, 2013). Thus, the new economic challenge for the United States in the twenty-first century transitioning from the managed economy to the entrepreneurial economy is to stimulate and maintain an entrepreneurial society (Audretsch, 2009). The main purpose of the entrepreneurial society is to reap the advantages stemming from a knowledge-based society brought about by the diffusion of information and communication technologies to exploit economic growth (Santarelli, 2006). Over the last half-century, advanced economies have been forced to deal with unprecedented levels of change and related challenges due to globalization (Stam, 2008). In the midst of such upheaval, attention has been drawn to the importance of creating enabling environments conducive to the emergence of opportunities for entrepreneurs (Baumol, 1996; Shane and Venkataraman, 2000), such as entrepreneurial ecosystems to help cultivate an entrepreneurial society. The power of an entrepreneurial society to collectively shape the economic destiny of a location can be exemplified by the entrepreneurial ecosystems of Seattle, Washington, Detroit and Michigan. Seattle and Detroit were both dominated by large local manufacturers during the managed economy in the 1960s, and the big firms in both cities (e.g., Boeing and General Motors) showed subsequent employment declines. However, today Seattle is thriving, unlike Detroit, because of local entrepreneurs, some of who grew up in the city (e.g., Bill Gates) and others of who were attracted to the city from outside (e.g., Jeff Bezos) (Chatterji et al., 2013). In the Seattle context there is at least one, and usually several, large established businesses that help cultivate an ecosystem that supports or inhibits an entrepreneurial society, compared to the situation in Detroit, where such an environment is lacking. When a successful entrepreneurial firm has grown to an exceptional size and has created significant wealth for its founders, investors, senior management and employees, it creates a spillover effect in terms of role models, serial entrepreneurs, angel investors, venture capitalists, board members, advisors and mentors (Isenberg, 2010). These individuals, in turn, maintain an ongoing involvement in the ecosystem, reinvesting their experience and wealth as mentors, investors and serial entrepreneurs. The Seattle start-up ecosystem is vibrant, and growing rapidly because of such contributions. A 24

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great example of this process is the role played by Microsoft in developing Seattle’s dynamic ecosystem. During the 1990s, employment in computer and processing sector grew six fold from 11,800 to 60,800, driven by around 148 Microsoft-related spin-offs in Seattle (Mayer, 2013). Another example can be found in Jeff Bezos’ (founder of Amazon) Bezos Center for Innovation, an attempt to explore the idea that innovation is a key part of the city’s identity. Both contributions had considerable impact in fostering an entrepreneurial society via knowledge spillovers in Seattle and sustaining Seattle’s entrepreneurial ecosystem. On the other hand, Detroit’s demise as an entrepreneurial city stems from a failure to adapt, as seen in its preference to invest in things rather than people, and thus failed to adequately create the knowledge spillovers needed for an entrepreneurial society. For instance, it is interesting to note that just one automaker, General Motors, chose to have its headquarters in Detroit. Chrysler and Ford are headquartered outside Detroit’s city limits. Additionally, the anti-competition mentality of the managed economy drove away foreign automakers in the 1970s seeking a United States headquarters to California, again inhibiting the opportunities for potential knowledge spillovers (Hennesy, 2013). In short, the presence of a homegrown start-up that became a global force is a vital narrative in the community; it shows the possibilities of entrepreneurship and the potential rewards of leaving a stable job for the risks of starting your own company (Mason and Brown, 2013). Indeed, as Isenberg (2013) states, “you simply cannot have a flourishing entrepreneurship ecosystem without large companies to cultivate it, intentionally or otherwise.” However, for these benefits to occur, it requires the businesses to be open and collaborative. Therefore, the multiple stakeholders in an entrepreneurial ecosystem need to be inclusive and embrace other members of the start-up community who want to be involved (Mason and Brown 2013). Hence, entrepreneurial ecosystems should concentrate on bridging assets that serve to connect people, ideas and resources. These bridging assets are often embodied as individuals whose mission is to connect the dots and have a considerable role in facilitating the knowledge spillovers needed to create an entrepreneurial society. The entrepreneurial society perspective is a key driver of economic growth (Audretsch, 2009). Consequently, the entrepreneurial ecosystem can not only act as a catalyst in speeding up the economic progress of stable economies, but also can also act as the prime mover when it comes to rescuing economies that have faced a sharp decline. Future Directions

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Our findings highlighted several important entrepreneurial attitudes, that drive entrepreneurial engagement, were showing negative trends. These attitudes are likely impacted by the declining features of the ecosystem. Two specific entrepreneurial attitudes showing negative trends that need further attention are: knowing other entrepreneurs, and fear of failure. First, since 2008, GEM respondents reported knowing fewer business owners. This is important because extant research has found that when persons know someone who has founded a business, they are more likely to engage in entrepreneurial activity (De Clerq and Arenius, 2006) Thus, knowing other entrepreneurs likely offers sources of ideas, opportunities, inspiration, a role model and possible mentor. Second, traditionally, as noted, United States entrepreneurs report that they are more confident in their ability to capitalize on new ventures and less afraid of the consequences of failure; yet, our examination of the GEM data revealed that this trend is changing. Particularly, there has been a sharp increase since 2006 among the United States populations’ fear of failure. This is ironic, as the entrepreneurial rhetoric embraces failure more than ever, normalizing failure as a part of the process. For example, embedded in entrepreneurial training and education is the rhetoric that the new venture creation process involves failure as a learning process and the ultimate ironic path to success (e.g., Mullins & Komisar, 2009; Osterwalder & Pigneur, 2010). Concurrently, during the same time period, there was a decrease in the total entrepreneurial activity of the United States, so it is plausible that the fear of failure might be influencing this lack of activity, in addition to other factors. Thus, although entrepreneurs actively engaged in the entrepreneurial process praise failure, the general population does not view failure in such as positive light. Therefore, questions loom around how educators and policy makers normalize the feelings and attitudes of failure and help minimize the impact of failure for potential entrepreneurs. Although these attitudes are very important in fueling entrepreneurial behavior, what specific elements in the ecosystem are fueling the drop-off in these attitudes if there is a general decline in all components in the ecosystem framework? The financial environment suffered the sharpest decline in the ecosystem, which is an essential resource for entrepreneurial activity, coupled with R&D transfer decline, internal market burdens, government sub systems such as policy support and entrepreneurial education declines, among others. Thus, many key areas that support entrepreneurial attitudes and activity in the ecosystem are declining, and future research should address what is causing these declines and how we can overturn these trends. Specifically, in the area of finance, how do sub-systems within the ecosystem start to work together to reverse these declining trends? For instance, how can education and policy work together to create novel financing alternatives, like the 26

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advent of crowd funding? Further, why is there a sharp R&D transfer decline in a knowledge-based economy with such an emphasis on technology transfer in the United States? How can government policy encourage R&D transfer? Moreover, much of the data on entrepreneurial ecosystems is only available at the country scale, making it potentially difficult to apply at the sub-national scale. Future research should aim at standardizing ecosystem metrics to assess and compare regional ecosystems in the United States. Prior studies that have addressed nascent venturing have given little attention to environmental factors (Liao and Welsch, 2008), such as the ecosystem. The factors that drive changes in the rate of entrepreneurship are not likely to manifest over short time periods. Changes in values, attitudes, technology, government regulations, and world economic and social changes have a significant influence on changes in entrepreneurship over time. We believe that the ability to predict trends, or to state with confidence the specific role of entrepreneurship in an economy, requires more types of longitudinal data that examines the many factors associated with the entrepreneurship ecosystem over much longer periods of time. A key take away from this review, is the need for cooperation and relationship-building between individuals and institutions, particularly between those producing knowledge and those developing new products and services. We contend that policies can create entrepreneurial opportunities, but stress the need for clarity in the desired outcomes. Policy decisions need to be targeted and understood in terms of what they enable or promote, rather than constrain, in order to create an entrepreneurial society. CONCLUSION Over the last sixty years there has been an evolution in the manner in which governments in advanced countries have undertaken industrial and enterprise policies (Warwick, 2013). Indeed, the evolution of how we have conceptualized the entrepreneurial phenomenon has given rise to different enactments of entrepreneurial policy. Traditionally, policy references to entrepreneurship equate it with SMEs initiatives in general, or even numbers of self-employed (Hoffmann, 2007). Neither of which fully captures the totality of entrepreneurship, as Reynolds (2007) shows survey-based measures more accurately reflect venturing activity than data from business registries.vi We contend that globally, for the United States economy to remain competitive, stakeholders involved in the entrepreneurial ecosystem must employ an entrepreneurial society position toward public policy. A long-term, integrated regional action plan for bringing about cultural change and promoting an Journal of Business & Entrepreneurship

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entrepreneurial society, encompassing initiatives in education, training, administration, society, businesses, and the media is needed. Such policies like improved tax incentives for businesses to invest, creation and support of institutions to implement the upgrading of the business environment, cultural initiatives, launch and support of cluster initiatives, creation of technology parks, and aggressive participation in federally funded science and technology programs are efforts that could advance the United States towards a stronger entrepreneurial society. In its essence, entrepreneurship is about a proactive mindset that takes ownership of surrounding problems in society, sees them as opportunities, and embraces the risks and failures involved in finding a solution. Moving forward, governments in the region and others working on creating an entrepreneurial ecosystem should leverage this change to empower citizens to become entrepreneurs that find organic and culturally-sensitive solutions to the problems facing us today. Keywords: entrepreneurial society, entrepreneurial ecosystems, entrepreneurial economy, entrepreneurship policy, Global Entrepreneurship Monitor. REFERNCES Acs, Z. J., & Amorós, J. E. (2008). Entrepreneurship and competitiveness dynamics in Latin America. Small Business Economics, 31(3), 305-322. Acs, Z. J., & Audretsch, D. B. (1993). Small firms and entrepreneurship: an EastWest perspective: Cambridge University Press. Acs, Z. J., & Audretsch, D. B. (2003). Introduction to the handbook of entrepreneurship research Handbook of entrepreneurship research (pp. 3-20): Springer. Acs, Z. J., Desai, S., & Hessels, J. (2008). Entrepreneurship, economic development and institutions. Small Business Economics, 31(3), 219-234. Acs, Z. J., & Stough, R. R. (2008). Public policy in an entrepreneurial economy: creating the conditions for business growth (Vol. 17): Springer. Ahmad, N. (2008). A proposed framework for business demography statistics: Springer. Ahmad, N., & Hoffman, A. (2008). A Framework for Addressing and Measuring Entrepreneurship: OECD Statistics Directorate Working Paper. STD/DOC (2008), 2. 28

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Aldrich, H. E., & Kenworthy, A. (1999). The accidental entrepreneur: Campbellian antinomies and organizational foundings. Variations in organization science: In honor of Donald Campbell, 19-33. Aldrich, H. E., & Wiedenmayer, G. (1993). From traits to rates: An ecological perspective on organizational foundings. Advances in entrepreneurship, firm emergence, and growth, 1, 145-195. Amorós, J. E., Bosma, N., & Levie, J. (2013). Ten years of Global Entrepreneurship Monitor: accomplishments and prospects. International Journal of Entrepreneurial Venturing, 5(2), 120-152. Arenius, P., & Minniti, M. (2005). Perceptual variables and nascent entrepreneurship. Small Business Economics, 24(3), 233-247. Audretsch, D. B. (2007). The entrepreneurial society. OUP Catalogue. Audretsch, D. B. (2014). From the entrepreneurial university to the university for the entrepreneurial society. The Journal of Technology Transfer, 39(3), 313-321. Audretsch, D. B., & Thurik, A. R. (2001). What's new about the new economy? Sources of growth in the managed and entrepreneurial economies. Industrial and corporate change, 10(1), 267-315. Audretsch, D. B., & Thurik, A. R. (2004). A model of the entrepreneurial economy: Papers on entrepreneurship, growth and public policy. Audretsch, D. B., & Thurik, A. R. (2010). Unraveling the shift to the entrepreneurial economy: Tinbergen Institute Discussion Paper. Audretsch, D. B., & Thurik, R. (2001). Linking entrepreneurship to growth: OECD Publishing. Baumol, W. J. (1993). Formal entrepreneurship theory in economics: Existence and bounds. Journal of Business Venturing, 8(3), 197-210. Baumol, W. J. (1996). Entrepreneurship: Productive, unproductive, and destructive. Journal of Business Venturing, 11(1), 3-22.

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Bhat, S. A., & Khan, R. A. (2014). Entrepreneurship Education Ecosystem: An Assessment Study of J&K State. International Journal of Economics, Commerce and Management, 2(4). Blanchflower, D. G., Levine, P. B., & Zimmerman, D. J. (2003). Discrimination in the small-business credit market. Review of Economics and Statistics, 85(4), 930-943. Blanchflower, D. G., Oswald, A., & Stutzer, A. (2001). Latent entrepreneurship across nations. European Economic Review, 45(4), 680-691. Bosma, N., & Harding, R. (2007). Global entrepreneurship monitor: GEM 2006 results. Brixy, U., Sternberg, R., & Stüber, H. (2008). From potential to real entrepreneurship: IAB discussion paper. Brixy, U., Sternberg, R., & Stüber, H. (2012). The selectiveness of the entrepreneurial process. Journal of small business Management, 50(1), 105-131. Brock, W. A., & Evans, D. S. (1989). Small business economics. Small Business Economics, 1(1), 7-20. Chatterji, A., Glaeser, E. L., & Kerr, W. R. (2013). Clusters of Entrepreneurship and Innovation: National Bureau of Economic Research. De Clercq, D., & Arenius, P. (2006). The role of knowledge in business start-up activity. International Small Business Journal, 24(4), 339-358. Feld, B. (2012). Startup communities: Building an entrepreneurial ecosystem in your city: John Wiley & Sons. Gartner, W. B., & Shane, S. A. (1995). Measuring entrepreneurship over time. Journal of Business Venturing, 10(4), 283-301. Geroski, P. A. (1995). What do we know about entry? International Journal of Industrial Organization, 13(4), 421-440. Goodman, R. S., & Kruger, E. J. (1988). Data dredging or legitimate research method? Historiography and its potential for management research. Academy of management review, 13(2), 315-325.

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Grilo, I., & Irigoyen, J.-M. (2006). Entrepreneurship in the EU: to wish and not to be. Small Business Economics, 26(4), 305-318. Hart, D. M. (2003). The emergence of entrepreneurship policy: governance, start-ups, and growth in the US knowledge economy: Cambridge University Press Cambridge. Harvard University. Research Center in Entrepreneurial, H., & Schumpeter, J. A. (1949). Change and the Entrepreneur: Postulates and Patterns for Entrepreneurial History: Harvard University Press. Hathaway, I., & Litan, R. E. (2014). Declining Business Dynamism in the United States: A Look at States and Metros. Brookings Institution. Hennesey, Ray. (2013). The Real Demon of Detroit. Entrepreneur Magazine. Hoffman, R. C. (2007). Corporate social responsibility in the 1920s: an institutional perspective. Journal of Management History, 13(1), 55-73. Isenberg, D. (2013). Worthless, Impossible and Stupid: How Contrarian Entrepreneurs Create and Capture Extraordinary Value: Harvard Business Press. Isenberg, D. J. (2010). How to start an entrepreneurial revolution. Harvard business review, 88(6), 40-50. J Acs, Z., & Audretsch, D. B. (1989). Patents as a measure of innovative activity. Kyklos, 42(2), 171-180. Kantis, H. D., & Federico, J. S. (2012). Entrepreneurial Ecosystems in Latin America: the role of policies. International Research and Policy Roundtable (Kauffman Foundation), Liverpool, UK. Kelley, D. J.,Abdul, A., Candida, B, Andrew C., Mahdi, M., Rogoff, E.J., (2013) “The Global Entrepreneurship Monitor: 2012 United States Report.” Kelley, D. J., Abdul, A, Rogoff, E. J., Brush, C., Corbett, A., Majbouri, M., Hechavarria D. 2012. “The Global Entrepreneurship Monitor: 2011 United Knight, F. H. (1921). Risk, uncertainty and profit. New York: Hart, Schaffner and Marx. Koellinger, P. (2008). Why are some entrepreneurs more innovative than others? Small Business Economics, 31(1), 21-37. Journal of Business & Entrepreneurship

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Kolb, A. Y., & Kolb, D. A. (2005). Learning styles and learning spaces: Enhancing experiential learning in higher education. Academy of management learning & education, 4(2), 193-212. Le, L. (2008). Entrepreneurship and Small Business Policies under the Presidential Administrations of Presidents Carter, Reagan, Bush and Clinton: 1977 to 2001 Public Policy in an Entrepreneurial Economy (pp. 23-65): Springer. Leibenstein, H. (1968). Entrepreneurship and development. The American Economic Review, 72-83. Leibenstein, H. (1978). General X-efficiency theory and economic development: Oxford University Press. Leibenstein, H. (1995). The supply of entrepreneurship. Leading issues in economic development, 273-275. Levie, J., & Autio, E. (2007). Entrepreneurial framework conditions and nationallevel entrepreneurial activity: Seven-year panel study. Liao, J. J., & Welsch, H. (2008). Patterns of venture gestation process: Exploring the differences between tech and non-tech nascent entrepreneurs. The Journal of High Technology Management Research, 19(2), 103-113. Looy, B. V., Debackere, K., & Andries, P. (2003). Policies to stimulate regional innovation capabilities via university–industry collaboration: an analysis and an assessment. R&D Management, 33(2), 209-229. Loveman, G., & Sengenberger, W. (1991). The re-emergence of small-scale production: an international comparison. Small Business Economics, 3(1), 1-37. Lundström, A., & Stevenson, L. (2005). Entrepreneurship policy: Theory and practice (Vol. 9): Springer. Malecki, E. J. (2011). Connecting local entrepreneurial ecosystems to global innovation networks: open innovation, double networks and knowledge integration. International Journal of Entrepreneurship and Innovation Management, 14(1), 36-59. Mason, C., & Brown, R. (2013). Entrepreneurial ecosystems and growth oriented entrepreneurship.

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Mayer, H. (2013). Entrepreneurship in a Hub-and-Spoke Industrial District: Firm Survey Evidence from Seattle's Technology Industry. Regional Studies, 47(10), 17151733. Minniti, M. (2008). The role of government policy on entrepreneurial activity: productive, unproductive, or destructive? Entrepreneurship Theory and Practice, 32(5), 779-790. Moore, J. F. (1993). Predators and prey: a new ecology of competition. Harvard business review, 71(3), 75-86. Mullins, J. & Komisar, R. (2009). Getting to Plan B. Boston: Harvard Business Press. Murphy, P. J., Liao, J., & Welsch, H. P. (2006). A conceptual history of entrepreneurial thought. Journal of Management History, 12(1), 12-35. O'Regan, N., & Maclean, M. (2009). What we need is an “entrepreneurial society”: An interview with Professor David Audretsch. Journal of Strategy and Management, 2(1), 110-114. Osterwalder, A. & Pigneur, Y. (2010). Business Model Generation. New York: Wiley. Petty, J. S., & Bonardi, J.-P. Public Policy: Moving Beyond Firm Creation. Regele, M. D., & Neck, H. M. (2012). The Entrepreneurship Education Subecosysterm In The United States: Opportunites To Increase Entrepreneurial Activity. Journal of Business and Entrepreneurship, 23(2), 25-47. Reynolds, P., Bosma, N., Autio, E., Hunt, S., De Bono, N., Servais, I., . . . Chin, N. (2005). Global entrepreneurship monitor: Data collection design and implementation 1998–2003. Small Business Economics, 24(3), 205-231. Reynolds, P. D. (2007). Entrepreneurship in the United States: The future is now (Vol. 15): Springer. Rodríguez-Pose, A. (2013). Do institutions matter for regional development? Regional Studies, 47(7), 1034-1047. Rosted, J (2012) Understanding Business Ecosystems, FORA Group.

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Sachs, J. D., & Schwab, K. (1998). The Global Competitiveness Report 1998. Santarelli, E. (2006). Entrepreneurship, growth, and innovation: the dynamics of firms and industries (Vol. 12): Springer. Scarpetta, S., & Tressel, T. (2002). Productivity and convergence in a panel of OECD industries: do regulations and institutions matter? : OECD Publishing. Shane, S., & Venkataraman, S. (2000). The promise of entrepreneurship as a field of research. Academy of management review, 25(1), 217-226. Stam, E., & Nooteboom, B. (2011). 26 Entrepreneurship, innovation and institutions. Handbook of research on innovation and entrepreneurship, 421. Thurik, A. R. (2008). Entrepreneurship, economic growth and policy in emerging economies: ERIM Report Series Research in Management. Thurik, A. R. (2009). Entreprenomics: entrepreneurship, economic growth and policy. Entrepreneurship, growth, and public policy, 219-249. Thurik, R. (2007). Entreprenomics: Entrepreneurship, Economic Growth and Policy, edited by DB Audretsch and R. Strom: Cambridge University Press. Venkataraman, S. (1997). The distinctive domain of entrepreneurship research. Advances in entrepreneurship, firm emergence and growth, 3(1), 119-138. Verheul, I., Wennekers, S., Audretsch, D., & Thurik, R. (2002). An eclectic theory of entrepreneurship: policies, institutions and culture Entrepreneurship: Determinants and policy in a European-US comparison (pp. 11-81): Springer. Vogel, P. (2013). The employment outlook for youth: Building entrepreneurial ecosystems as a way forward. Warwick, K. (2013). Beyond Industrial Policy: emerging issues and new trends: OECD Publishing. Wessner, C. W. (2005). Entrepreneurship and the innovation ecosystem policy lessons from the United States Local Heroes in the Global Village (pp. 67-89): Springer. Williams-Middleton, K. (2010). Developing entrepreneurial behavior: Facilitating nascent entrepreneurship at the university. Published doctoral dissertation, Chalmers University of Technology. 34

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Zacharakis, A. L., Shepherd, D. A., & Coombs, J. E. (2003). The development of venture-capital-backed internet companies: An ecosystem perspective. Journal of Business Venturing, 18(2), 217-231. i

The total sample of respondents is weighted according to census adult labor force population (18-64) data for respective year. ii

SBA regions: http://www.sba.gov/about-offices-list/3 1. New England: Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island and Vermont 2. Atlantic: New York, New Jersey (Puerto Rico, and U.S. Virgin Islands not sampled) 3. Mid-Atlantic: Delaware, Maryland, Pennsylvania, Virginia, Washington, DC, and West Virginia 4. Southeast: Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, and Tennessee 5. Great Lakes: Illinois, Indiana, Michigan, Minnesota, Ohio, and Wisconsin 6. South Central: Arkansas, Louisiana, New Mexico, Oklahoma, and Texas 7. Great Plains: Iowa, Kansas, Missouri, and Nebraska 8. Rocky Mountains: Colorado, Montana, North Dakota, South Dakota, Utah, and Wyoming 9. Pacific Southwest: Arizona, California, Hawaii, and Nevada (Guam not sampled) 10. Pacific Northwest: Alaska, Idaho, Oregon, and Washington iii To create the Entrepreneurial Framework Conditions, GEM used independent procedure to based on informed judgments of national experts regarding the status of entrepreneurship in their own countries. Experts were selected on the basis of reputation and experience; these groups are technically samples of convenience. Using both of the face to face interviews and questionnaires, experts were queried on their views of national contributions (strengths) and limitations (weaknesses) as a context for entrepreneurship, and what policy or program changes would enhance the level of entrepreneurship in their country. See Reynolds et al., (2005) for a complete methodological overview. iv See Reynolds et al., (2005) for a complete overview on operationalization of variables and reliability measures. v Items with asterik have been calculated diffrently in some years. For consistency, authors adapted computation to align with the latest year of calculaiton for the scale in the GEM 2010 expert database. Please refer to Reynolds et al. (2005) for extended details on scale development. vi Reynolds (2007) highlights the fundamental issue inherent when comparing findings based on the different measures previously discussed. Comparing statistics from household population surveys (CPS and GEM’s TEA index) to data from business registries (Census and BLS) a different pattern emerges when estimating entrepreneurship at the national level in the United States. The patterns reveal that both survey-based measures are much higher, by about factors of 5-10 than the two measure based on new tax registrations (Reynolds, 2007). These differences are the result of units of analysis (e.g., the individual versus the firm with employees).

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CHICKEN OR EGG: ENTREPRENEURIAL SELF-EFFICACY AND ENTREPRENEURIAL INTENTIONS REVISITED Christoph Winkler Baruch College, CUNY

Jennifer R. Case The Graduate Center, CUNY ABSTRACT

Based on social cognitive theory, this study looks at how entrepreneurship students’ personal (age and gender) and contextual characteristics (prior exposure to entrepreneurship and start-up experience) influence students’ entrepreneurial outcome expectations, self-efficacy and intentions. The paper takes a first step towards a more dynamic understanding that utilizes entrepreneurial self-efficacy as a key-motivational construct during entrepreneurial self-regulation. Entrepreneurial forethought and its underlying processes are suggested to predict entrepreneurial action at a higher level than traditional static measures of entrepreneurial intent. INTRODUCTION While entrepreneurship education and associated programs have grown exponentially over the past four decades (Katz, 2003; Kuratko, 2005; Solomon, 2007), there seems to be little evidence on its impact on students’ actual success (Griffiths, Kickul, Bacq, & Terjesen, 2012; Rideout & Gray, 2013). The problem of gaining a better understanding of student learning is partially rooted in the methodological diversity and scale of academic programs. Entrepreneurship education may be limited to a single course, but it may also transcend every aspect of a student’s college experience. In addition, entrepreneurship education reaches beyond the academic structure that scaffolds entrepreneurship curriculum and degree programs by also including (but not limited to) cocurricular offerings, immersive programs, business plan competitions, networking opportunities, or entrepreneurial internships (Kauffman, 2013). Research on the impact of entrepreneurship education is diverse in nature and often ignores (or lacks) the most desired dependent variable, namely, the actual launch of a business. The reason is based on the fact that most entrepreneurship students do not necessarily start a business during school,

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college or immediately thereafter (Lang, Marram, Jawahar, Yong, & Bygrave, 2011; Peterman & Kennedy, 2003). For instance, Lang et al. (2011) demonstrated that taking two or more core elective entrepreneurship courses had a significantly positive influence on starting a business after graduation. The actual event of starting a business is mostly delayed and therefore difficult to capture without longitudinal research frameworks. As a result, intention models (Bird, 1992; Boyd & Vozikis, 1994; Shapero & Sokol, 1982) emerged in order to gain a better understanding of antecedent processes, since intentions are the single best predictors of planned behavior (Bagozzi, Baumgartner, & Yi, 1989), and are important mediating variables that help explain the relationship between the venture creation process by the entrepreneur and external factors that may impact on that process. One of the early theoretical frameworks employed within this context is Ajzen’s (1991, 2002) Theory of Planned Behavior (TPB) which offers an explanation into behavior that is not always immediate or is difficult to observe (Krueger, Reilly, & Carsrud, 2000). To date, research has established a good understanding of antecedents and the moderating boundaries of contextual influences as mediators on entrepreneurial intentions in a pre-volitional stage (Schlaegel & Koenig, 2014). The same applies to research on the relationship between entrepreneurship education and associated entrepreneurial intentions. Most recently, Bae, Qian, Miao, and Fiet (2014) meta-analytically found a small, yet significant, relationship between entrepreneurship education and entrepreneurial intentions. The effect, however, was not significant when accounting for preintervention entrepreneurial intentions. Moreover, there is little evidence of the impact of entrepreneurship education in higher education on the theorized link between intention based models and actual entrepreneurial actions (Rideout & Gray, 2013). More prominently, social cognitive models (Bandura, 1986, 2001) and associated constructs have gained popularity among the research community in order to explain entrepreneurship as a learning process (Cope, 2005). Central to entrepreneurial learning within a social cognitive framework are self-efficacy beliefs, which are a person’s perceived ability to perform a particular task at designated levels (Bandura, 1986, 1997). While research has found a mediating relationship of entrepreneurial self-efficacy on entrepreneurial intentions (Boyd & Vozikis, 1994; Zhao, Seibert, & Hills, 2005), research has not considered the innate properties of self-efficacy as a dynamic measure, where self-efficacy 38

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beliefs may change based on self-regulatory feedback loops during subsequent performance (Bandura, 2001, 2012; Zimmerman, 2001). When applying this notion with regards to existing research in entrepreneurship education, antecedent variables (e.g. self-efficacy and intentions) are mostly interpreted with regards to events in the future (e.g. starting a business) and often ignore the timeframe when entrepreneurial learning and development takes place. As a consequence, self-efficacy has emerged as a mediating variable that influences entrepreneurial intentions, and not vice versa. Building on the empirical and theoretical work on social cognition and selfregulation (Bandura, 2001, 2012; Schunk, 2001; Zimmerman, 2005, 2011), we propose entrepreneurial self-efficacy as a self-motivational construct that explains entrepreneurial actions based on self-reflection and associated selfregulatory feedback cycles. THEORETICAL FRAMEWORK Cope (2005) proposed a dynamic and contextualized learning view of entrepreneurship that underscores the importance of direct experiences and selfreflection in order to be able to perceive progress and growth as an entrepreneur. Similarly, entrepreneurial learning from a social cognitive perspective refers to a person’s competencies (cognitive, behavioral and social) that are acquired through modeling and mastery experiences, in order to effectively use his or her capabilities within a self-motivational framework that is based on goal systems (Bandura, 1986; Boekaerts, Maes, & Karoly, 2005; Wood & Bandura, 1989). Effective modeling and mastery experiences require observational learning where the learner compares actions to conceptual models. These actions lead towards a change in subsequent behavior as well as the underlying motivational processes. Important within this context are self-evaluations that help the learner to regulate which “observationally learned activities they are most likely to pursue” (Wood & Bandura, 1989, p. 363). Observational learning in entrepreneurship education may be achieved through guest lectures, simulations, group activities with students who already started a business, or internships in start-ups, to name a few. Since entrepreneurship is not a linear but an iterative process (Neck & Greene, 2011), entrepreneurship pedagogies and methods should provide students with mastery experiences in changing circumstances where they can practice entrepreneurship by receiving continuous feedback about their entrepreneurial learning experiences. Therefore, learning Journal of Business & Entrepreneurship

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requires cognitive, metacognitive and externally scaffolded support mechanisms that allow students to continuously monitor their progress towards their own entrepreneurial development and subsequently adjust their goal system based on the actions observed (Zimmerman, 2005). Wood and Bandura (1989) postulate that “much of human learning is aimed at developing cognitive skills on how to acquire and use knowledge for different purposes” (p. 363). This illustrates the importance of an understanding of the perceived usefulness of the learned behaviors and skills, and the ability to transfer these to new situations. It has often been observed that students and nascent entrepreneurs take actions towards launching a business, however, perceived failure for certain courses of action may have resulted in abandoning a particular course of action. Conversely, if students are able to reflect on their actions taken through feedback and self-reflective practice, they may demonstrate agency to adjust their beliefs about their abilities and continue to engage in subsequent behavior (Bandura, 2001). Therefore, a social cognitive view puts less emphasis on intentions as a static antecedent to predict behavior or actions; instead, it emphasizes self-efficacy as a self-motivational construct that is self-regulatory and goal-driven in nature (Zimmerman, 2007). Social cognitive theory (Bandura, 1986, 2001) suggests that self-efficacy can be strengthened through mastery experiences, where performance (positive or negative) directly impacts on self-belief systems; vicarious experiences, which are rooted in observing models and social comparison; social persuasion, which are realistic encouragements to help sustain efforts and subsequent success; and physiological states (e.g. fatigue, aches, pain), which can have negative influences on a person’s desire to pursue a particular course of action. Research has shown that self-efficacy beliefs are strong predictors of task choice, effort, persistence, and achievement (Bandura, 2001; Zimmerman, 2005). Entrepreneurial Self-Regulation and Motivation People’s self-regulation of performance and motivation is governed by self-efficacy beliefs in order to exercise control over their lives. Deeply rooted in the foundations of social cognitive theory, Zimmerman (1998, 2000, 2005) developed a widely applied and researched cyclical model of self-regulation, which emphasizes the importance of feedback from prior performance in order to be able to adjust one’s subsequent actions to attain a specific goal. An individual’s success is therefore contingent on his or her ability to make these 40

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adjustments during phases of learning and performance under ever-changing personal, social and environmental influences.

Figure 1: Phases and subprocesses of self-regulation According to Zimmerman (2000) “self-regulation refers to self-generated thoughts, feelings and actions that are planned and cyclically adapted to the attainment of personal goals” (p. 14). Zimmerman’s model (see Figure 1) explains self-regulation through open triadic feedback loops, which are comprised of forethought phase, performance control phase, and self-reflection phase: (1) the forethought phase includes subprocesses task analysis (e.g. goal setting) and self-motivational beliefs (e.g. self-efficacy, outcome expectations) that influence and precede efforts to take action and set the stage for it; (2) the performance (or volitional) control phase involves subprocesses self-control (e.g. task strategies) and self-observation (e.g. meta-cognitive monitoring) that are directly related to actual performance efforts, and affect attention and action; and lastly, (3) the self-reflection phase concerns processes that follow performance efforts and influence a person’s response to that experience. During this phase, self-reaction (e.g. self-satisfaction/affect) and self-judgment (e.g. selfevaluation) bring the self-regulatory cycle to a close and influence the Journal of Business & Entrepreneurship

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subsequent forethought phase with regards to future performance efforts. Zimmerman (2007) posits self-regulatory cycles may vary in duration (from minutes to even years) based on a person’s goals and other self-regulatory processes. Self-efficacy during entrepreneurial forethought Since the process of starting a business (from a goal setting perspective) has been researched through the lens of intention-based models (Krueger & Carsrud, 1993; Krueger et al., 2000), proximal process oriented, and feedback oriented entrepreneurship goals have presently been rarely touched upon. Conversely, a model of entrepreneurial self-regulation emphasizes the importance of goal setting during forethought, which directly impact on a person’s self-efficacy beliefs (Zimmerman, 2001, 2005) and subsequent behavior. Self-efficacy beliefs trigger judgments that are analytic in nature and may facilitate a visualization of success scenarios in pursuit of a particular goal (Bandura, 1986; Wood & Bandura, 1989; Zimmerman, 2001). Once an individual engages in a course of action, feedback control is required in order to continuously monitor one’s progress and make adjustments to one’s actions accordingly. It could be argued that nascent and actual entrepreneurs alike continuously set goals, take appropriate actions and readjust (or “pivot,” as popularly referred to within the entrepreneurship community) their behavior in a similar, cyclical fashion in order to meet the desired ultimate goal of starting or growing a business. Consequently, the self-efficacy beliefs within a selfregulatory framework are motivational, since they are tied to a specific goal or standard (Locke & Latham, 1990) to which a person commits behaviorally. The cyclical and adaptive interplay of goals and behavioral feedback is mediated by self-efficacy beliefs, which may change depending on whether goals are attained, or not (Zimmerman, 2007). While some research on entrepreneurship started to investigate selfefficacy and related motivational constructs from a goal setting perspective (Hechavarria, Renko, & Matthews, 2012), there has been little or no consideration of entrepreneurship research as a process that accounts for varying degrees of motivational factors during specific steps in the entrepreneurial process (Shane, Locke, & Collins, 2003). The same applies to research on entrepreneurship education, which has yet to look at entrepreneurial learning as a dynamic and self-regulatory process (Hmieleski & Baron, 2009), in order to

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better explain varying degrees of self-motivational constructs, such as entrepreneurial self-efficacy. Outcome expectations during entrepreneurial forethought Another important motivational factor during forethought are outcome expectations, which are a person’s judgment about the consequences that result when engaging in a certain behavior (Pajares, 2007). Outcome expectations are similar to what Wigfield and Eccles (2000) referred to as “utility value,” links a particular task to a person’s future plans (Zimmerman, 2011). Unlike selfefficacy, outcome expectations are not concerned about how well a person believes he or she can perform a particular task (e.g. start a business). Instead, they emphasize one’s beliefs about the consequences of that task (e.g. “I will be rich, if I start a business.”). This notion may be inconsistent with and in contrast to self-efficacy since, for instance, high outcome expectations may result in low levels of self-efficacy. To illustrate that point, an aspiring entrepreneur may associate high wealth with entrepreneurship, but may not believe that he or she may be capable of actually starting a business. Therefore, outcome expectations may have less dynamic properties than self-efficacy since they may not necessarily change based on one’s actions taken. Contextual and personal influences of entrepreneurial self-regulation Entrepreneurial learning and self-regulation do not happen in isolation and also require the consideration of personal and contextual (environmental) influences. Sarasvathy and Venkataraman (2011) underlined the importance of considering different sources of human behavior in entrepreneurship research that account for heterogeneity, developmental change and contextual influences. Of particular importance within this context are age, gender, prior exposure to entrepreneurship and actual entrepreneurial experience. Wood and Bandura (1989) noted that women, despite no differences in abilities compared to men, may limit their engagement in male dominated domains due to lower levels of beliefs about their capability. Prior research showed that women show lower career intentions and that gender is not mediated by self-efficacy beliefs (Zhao et al., 2005). In addition, perceived skills levels are more dominant than actual levels (Wilson, Kickul, & Marlino, 2007). Especially the latter finding emphasizes the importance of skills calibration efforts (e.g. modeled or vicarious experiences) in order to make up this gap.

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Other research has shown that age has been associated with entrepreneurial activity (Mathews & Moser, 1995). Conversely, Lévesque and Minniti (2006) suggest a negative relationship between age and attitude towards entrepreneurship. Given the typically homogeneous age compositions of educational environments, to our knowledge, age has not been given the appropriate attention within entrepreneurship education research. Another important consideration is how prior entrepreneurial experience impacts on students’ underlying cognitive belief systems when planning to start a business. While previous research compared nascent to actual entrepreneurs, there is limited evidence on cognitive and behavioral differences between entrepreneurship students who are already operating businesses with those who are not. Lastly, vicarious and modeled learning experiences influence selfefficacy beliefs (Bandura, 1986; Wood & Bandura, 1989). Similarly, prior exposure to entrepreneurship has proven to have a positive impact on entrepreneurial intentions and is mediated through entrepreneurial self-efficacy (Carr & Sequeira, 2007). It is important to note that these phenomena and associated behaviors should be understood as a reciprocal function of environmental influences (e.g. education) as well as personal factors (e.g. gender, age). Conceptual Model and Hypotheses In order to establish a social cognitive self-regulatory framework we propose a dynamic understanding of how self-efficacy beliefs are formed within an entrepreneurial context. To date, most measures and associated research (McGee, Mueller, Peterson, & Sequeira, 2009; Sequeira, Mueller, & McGee, 2007; Zhao et al., 2005) look at self-efficacy as a static phenomenon that mediates the relationship between personal variables and entrepreneurial intent. While this relationship has been well established, a more fine grained analysis of how these beliefs are formed, developed and linked to actual performance – especially within an entrepreneurship educational context – have not been investigated. Rationally, it follows that a goal-driven and dynamic view of selfefficacy may actually be the consequence and not a mediator of intentions. In order to establish such a dynamic and cyclical model of entrepreneurial self-regulation, forethought (Zimmerman, 1998, 2000, 2011) and its underlying 44

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cognitive processes (with entrepreneurial self-efficacy at the key motivational construct during entrepreneurial forethought) are suggested to better predict and explain entrepreneurial action compared to traditional static measures of entrepreneurial intent. The goal is to take the first step towards a more dynamic understanding that utilizes entrepreneurial self-efficacy as a key-motivational construct during entrepreneurial self-regulation.

Figure 2a: Static model of entrepreneurial intentions

Figure 2b: Self-efficacy-based model of entrepreneurial forethought

Figure 2: Competing models of antecedents to entrepreneurial actions Figures 2a and 2b compare a static model of entrepreneurial intentions, where entrepreneurial intentions (as dependent variable) are mediated by outcome expectations and self-efficacy, with a self-efficacy-based model of entrepreneurial forethought, where the relationship between personal and contextual factors and self-efficacy (as dependent variable) is mediated by

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entrepreneurial intentions and outcome expectations. We therefore, hypothesize that H1 The relationship between personal (age and gender) and contextual factors (prior exposure to entrepreneurship and start-up experience) and entrepreneurial self-efficacy (as mediated by entrepreneurial outcome expectations and intent) is stronger than the relationship between personal factors and entrepreneurial intent (as mediated by entrepreneurial self-efficacy and entrepreneurial outcome expectations). METHOD Sample and Procedure Data for the study was collected in fall 2012 as part of the second wave of an online survey, The Entrepreneurship Education Project (Vanevenhoven & Liguori, 2013). The survey, which was designed based on the theoretical principles of social cognitive theory (Bandura, 1986) and Social Cognitive Career Theory (Lent & Brown, 1996; Lent, Brown, & Hackett, 2000), was sent out via email to all undergraduate students (N=411) who were enrolled in entrepreneurship courses at a large urban public university in the northeastern United States. After removing 21 incomplete survey responses, 79 students (age: M = 25.72; SD = 7.27) were used for further analysis resulting in an actual response rate of 19.2%. The sample was comprised of 40 males (age: M = 24.83; SD = 6.47) and 39 females (age: M = 26.64; SD = 7.98). Twenty-seven (34.2%) students self-identified as a minority, 40 (50.6%) respondents did not identify as minorities, and 10 (12.7%) students indicated, “I don’t know” (2 students did not respond). The sample was further comprised of 15 students (19%) who were operating a business at the time they responded to the survey. In addition, 57 (72.2%) were full-time and 21 (26.6.9%) were part-time students (1 student did not respond).

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Fall 2014 Special Issue

Journal of Business & Entrepreneurship

Measures Entrepreneurial self-efficacy: This scale is based on a slightly modified version of McGee et al.’s (2009) measure (Vanevenhoven & Liguori, 2013). The original 19-item scale has been tested in a diverse sample that also included nascent entrepreneurs, and included five factors that correspond to a four-phase venture creation model; namely searching, planning, marshaling, and implementing. The modified 20-item scale was converted from a five-point Likert scale to a 0-100 confidence scale (0 = absolutely no confidence; 100 = completely confident). During the analysis of the data, the measure was recoded to a seven-point Likert scale. Cronbach’s alpha for the scale was .94. Entrepreneurial outcome expectations: Outcome expectations are distinctly different from self-efficacy since they are not concerned with one’s perceived ability to take a particular course of action. Instead, they are beliefs about the consequences of these actions. The measure, which was inspired by Krueger et al. (2000), was comprised of four items, where students had to indicate on a scale from 1 (= not at all) to 7 (= very much) the extent to which they expect particular outcomes (financial rewards, autonomy/independence, personal rewards, family security) to occur when starting a business. Cronbach’s alpha for the scale was .73. Entrepreneurial intent: The measure used was a modified version (removal of 4 decoy items) of the 10-item scale, which was developed and validated by Thompson (2009). Students were asked to respond to six questions (e.g. “Spend time learning about starting a new venture”) on a scale from 1-7, with 1 meaning very untrue, and 7 meaning very true. Half of the questions were reverse coded (e.g. “Never search for business start-up opportunities”). Cronbach’s alpha for the scale was .78. Start-up experiences: The measure used is a single item, where students were asked, whether they have ever started a business that is currently operating. The responses were dummy-coded with 0 = no and 1 = yes. Gender: At the end of the survey, students were asked to indicate their gender. Responses were dummy coded with male = 0 and female = 1. Age: Students were asked to self-report their age. Prior exposure: Students were asked if their parents or guardians ever started a new venture. The responses were dummy-coded with 0 = no and 1 = yes.

Journal of Business & Entrepreneurship

Fall 2014 Special Issue

47

RESULTS As can be seen from Table 1, entrepreneurial self-efficacy shows significantly positive Pearson correlations with entrepreneurial intent (r = .418, p < .01), start-up experiences (r = .256; p < .05), age (r = .279, p < .05) and entrepreneurial outcome expectations (r = .208, p < .05). Comparatively, entrepreneurial intent only shows significantly positive correlations with entrepreneurial self-efficacy, start-up experiences (r = .234, p < .05) and age (r = .299, p < .01), but not with entrepreneurial outcome expectations. Further, prior exposure shows a significantly negative correlation with gender (r = -.29, p < .05) and a significantly positive correlation with outcome expectations (r = .279, p < .05). Table 1 Correlation Matrix for Controls and Cognitive Factors 1. Entrepreneurial Intent

1 5.39 (1.09)

2

3

4

5

6

2. Start-up Experience

.234

*

.190 (.40)

3. Gender

.-.131

-.155

.49 (.50)

.161

-.023

-.190

.126

.126

-.101

25.72 (7.27)

-.083

-.128

.279

*

-.092

*

-.044

.084

4. Prior Exposure 5. Age 6. Outcome Expectations 7. Entrepreneurial Self-efficacy

.299

**

.077 .418

**

.256

*

7

.56 (.50)

.279

*

6.10 (.78) *

.208

5.26 (1.02)

*p4) R squared change (1->3->4)

-.016 (.153) .331** (.116)

.334** (.121)

79 .177** (1.01)

79 .181** (1.02)

79 .260* (.972)

79 .260** (.979)

.133

.125 .004

.209

.198 .079** .000

.083**

*p8) R squared change (5->7->8) *p