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
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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
Journal of Business & Entrepreneurship
Fall 2014 Special Issue
1
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
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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
Fall 2014 Special Issue
3
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
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Journal of Business & Entrepreneurship
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
Fall 2014 Special Issue
5
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
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Fall 2014 Special Issue
Journal of Business & Entrepreneurship
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
Fall 2014 Special Issue
7
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
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Journal of Business & Entrepreneurship
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.
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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
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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),
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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
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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
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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
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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
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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
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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
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Journal of Business & Entrepreneurship
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
Fall 2014 Special Issue
27
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.
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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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37
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
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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
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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
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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
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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
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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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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.
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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)
*p<.05 **p<.01
diagonal values = item mean and sd
Before we were able to compare the competing models of antecedents to
entrepreneurial actions (Figure 2), we conducted two step-wise hierarchical
regression analyses with entrepreneurial intentions and entrepreneurial selfefficacy as dependent variables respectively.
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Table 2
Hierarchical regression analysis with intentions as dependent variable
Model 1 Model 2 Model 3 Model 4
Intercept
4.013**
(.467)
3.476**
(1.05)
2.658
(.467)
2.742*
(1.04)
Start-up Experience
.506
(.299)
.521
(.302)
.316
(.293)
.312
(.299)
Gender
-.235
(.239)
-.223
(.241)
-.220
(.228)
-.222
(.230)
Prior Exposure
.386
(.236)
.350
(.245)
.310
(.227)
.315
(235)
Age
.046**
(.016)
.047**
(.016)
.034*
(.016)
.034*
(.016)
.088
(.155)
Outcome Expectations
Entrepreneurial Self-efficacy
N
R squared
Adjusted R squared
R squared change (1->2->4)
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**
*p<.05 **p<.01
Table 2 summarizes the results of the hierarchical regression analysis
with entrepreneurial intentions as the dependent variable. The results show that
across all four models, start-up experience, gender, prior exposure and outcome
expectations do not significantly predict entrepreneurial intentions. Age, on the
other hand, is a significant predictor of entrepreneurial intentions across all four
models. Further, it can be seen that self-efficacy is the strongest predictor (Model
3: β = .331, p < .01; Model 4: β = .334, p < .01) of entrepreneurial intent.
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Table 3
Hierarchical regression analysis with self-efficacy as dependent variable
Model
Model
Model
Model
5
6
7
8
**
**
**
4.087
2.193
2.873
1.191*
Intercept
(.602)
(.466)
(.979)
(1.00)
Start-up Experience
.574
(.286)
.627*
(.280)
.421
(.278)
.477
(.274)
Gender
-.045
(.228)
-.002
(.223)
.027
(.219)
.062
(.215)
Prior Exposure
.229
(.225)
.104
(.227)
.112
(.219)
.003
(.221)
Age
.037*
(.015)
.039*
(.015)
.023**
(.016)
.025*
(.015)
.311*
(.144)
Outcome Expectations
Entrepreneurial Intent
N
R squared
Adjusted R squared
R squared change (5->6->8)
R squared change (5->7->8)
*p<.05 **p<.01
.285**
(.138)
.303**
(.106)
.288**
(.104)
79
.141*
(.973)
79
.193*
(.950)
79
.227**
(.929)
79
.271**
(.909)
. 095
.138
.037*
. 174
. 210
.079**
.043*
.086**
Moreover, both Model 3 (R2 = .26, p < .05) and Model 4 (R2 = .26, p <
.05) have the highest levels of explained variance where outcome expectations
do not add additional predictive value to the overall model. These findings are
consistent with previous research findings where entrepreneurial self-efficacy
was found to mediate the relationship between personal and contextual variables,
and entrepreneurial intent (Zhao et al., 2005).
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Table 3 summarizes the results of a hierarchical regression analysis with
entrepreneurial self-efficacy as the dependent variable. Similar to the previous
analyses, the results show that age is a significant predictor in all four models
(Models 5-8). While start-up experience and prior exposure are not significant
predictors, start-up experience (β = .627, p < .05) significantly predicts
entrepreneurial self-efficacy in Model 6, where outcome expectations is the only
mediating variable in predicting entrepreneurial self-efficacy. Moreover, both
outcome expectations and entrepreneurial intent are significant predictors of
entrepreneurial self-efficacy across all models (Models 6-8). Lastly, Model 8 has
the highest levels of explained variance across all four models (R2 = .71, p < .01)
with age (β = .025, p < .05), outcome expectation (β = .285, p < .01) and
entrepreneurial intent (β = .288, p < .01) as significant predicators of
entrepreneurial self-efficacy.
In subsequent analyses, we tested the main hypothesis by comparing the
competing models of antecedents to entrepreneurial action (Figure 1) using
LISREL 9.1 (Jöreskog & Sörbom, 2012). Due to the extensive number of
parameters that needed to be estimated (e.g. self-efficacy is comprised of 20
factor loadings) and sample size limitations, we were not able to specify
structural equation models (SEM) to test our main hypothesis. Instead of
estimating relationships between latent variables, path analyses were conducted
using average scores variables to represent each construct.
The competing models of antecedents to entrepreneurial action were
compared to determine the relationship between personal and contextual factors
and entrepreneurial intent and entrepreneurial self-efficacy. We hypothesized
that the model with entrepreneurial intent as a mediator between personal and
contextual factors, and entrepreneurial self-efficacy would show a stronger
relationship than the model with entrepreneurial self-efficacy as a mediator
between personal and contextual factors, and entrepreneurial intent. In a first
step, we looked at the direct relationship (not accounting for entrepreneurial
outcome expectations) between entrepreneurial intent and self-efficacy by
comparing the competing models 3 and 7, respectively.
The first model under investigation, Model 3, looked at entrepreneurial
self-efficacy as a mediator between personal/contextual factors and
entrepreneurial intent. The path diagram with factor loadings can be seen in
Figure 3a and a summary of goodness-of-fit measures in Table 4. The analysis
revealed that age (λ = 0.27, p = 0.015) and prior start-up experience (λ = 0.22, p
= 0.043) show significantly positive loadings on entrepreneurial self-efficacy; as
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well as a significantly positive loading of entrepreneurial self-efficacy on
entrepreneurial intent is (λ = 0.42, p < 0.001). Overall, the model did not meet
the criteria for good fit: χ2(4, N = 72) = 8.56, p = 0.073, RMSEA = 0.120.
Figure 3a: Model 3 Path Diagram. * p< .05. ** p < .01.
Figure 3b: Model 7 Path Diagram. ** p < .01.
Figure 3: Competing path models of antecedents to entrepreneurial actions
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In comparison, the results of Model 7 with entrepreneurial intent as a
mediator between personal and contextual factors, and entrepreneurial selfefficacy showed an acceptably good fit for the data, χ2 (4, n = 72) = 5.18, p =
0.270, RMSEA = 0.061. The path diagram with factor loadings can be seen in
Figure 3b with associated goodness-of-fit measures in Table 4. The overall
model further showed that only age had a significantly positive loading on
entrepreneurial intent, with older students reporting greater levels of intent (λ =
0.31, p = 0.004). Conversely, gender (λ = -0.11, p = 0.322), start-up experience
(λ = 0.13, p = 0.089), and prior exposure (λ = 0.18, p = 0.101) were not
significant. Equivalent to Model 3, Model 7 shows a significantly positive
loading of entrepreneurial intent on entrepreneurial self-efficacy (λ = 0.42, p <
0.001).
Table 4
Goodness-of-Fit Indices for Path Models
Model
3
7
χ2 (df)
8.56 (4)
5.18 (4)
AGFI
.826
.891
CFI
.862
.965
NFI
.822
.892
SRMR
.061
.048
RMSEA
.120
.061
Note: AGFI = adjusted goodness-of-fit index; CFI = comparative fit index;
NFI = normed fit index; SRMR = standardized root-mean-squared residual; RMSEA = rootmean-square error of approximation.
The stronger fit of Model 7 (Table 4) where intent mediates the
relationship between personal and contextual factors, and self-efficacy suggests a
better explanation of the relationship between these constructs. A subsequent
analysis of path models that also included outcome expectations (models 4 and
8) as a mediator between personal and contextual variables, and entrepreneurial
self-efficacy and entrepreneurial intent, respectively, did not produce any
acceptable model fits.
DISCUSSION
The present study is consistent with earlier research on entrepreneurial
intent and its relationship to entrepreneurial self-efficacy (Boyd & Vozikis, 1994;
Sequeira et al., 2007; Souitaris, Zerbinati, & Al-Laham, 2007; Zhao et al., 2005).
While these models have been widely used to explain antecedent behavior to
entrepreneurial action, they remain static in nature and do not account for the
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developmental, iterative and self-regulatory nature of entrepreneurial learning
and development.
By proposing entrepreneurial intentions as an antecedent to actual
entrepreneurial behavior, the present study emphasizes self-efficacy’s properties
as a self-motivational construct during entrepreneurial forethought, and therefore
introducing it as a dynamic measure that is not static and may change over time
based on recursive feedback during self-regulatory learning cycles. Bandura
(2012) emphasizes that “the influential factors in the self-regulation of
motivation and behavior include, in addition to self-efficacy, goal systems,
outcome expectations, perceived environmental facilitators and enablers, and
environmental impediments” (p. 40). Consequently, entrepreneurial forethought
can only be understood within the context of self-regulation and associated
feedback that may be based on direct (e.g. mastery), social (e.g. observation) and
environmental (e.g. curricula) experiences.
As a result, the proposed (competing) model of entrepreneurial
forethought conceptually links entrepreneurial self-efficacy to entrepreneurial
actions by emphasizing the self-motivational properties that have the power to
initiate entrepreneurial behavior, and inform subsequent actions based on
feedback from engaging in these actions.
Of particular significance in this study is the important positive influence
of age on entrepreneurial intentions and self-efficacy among entrepreneurship
students. Contrary to previous research (Lévesque & Minniti, 2006) where
younger individuals are associated with higher levels of entrepreneurship, we
demonstrated that older students do not only show higher levels of
entrepreneurial intentions but also entrepreneurial self-efficacy. One
interpretation for our finding may be based on the nature and distribution of the
student sample (as opposed to a sample of actual entrepreneurs). For instance, it
may follow that older students that are enrolled in an entrepreneurship program
may arguably have more professional experiences than their younger peers, and
are thus showing higher levels of self-motivational beliefs to start a business as a
result of that. Further, older students may also have had more opportunities to
apply themselves in business and therefore may have had more opportunities to
learn (succeed or fail) from their actions and associated learning experiences
(through feedback).
Another important observation shows that prior start-up experience only
had a direct positive influence on entrepreneurial self-efficacy and not on
entrepreneurial intent. One interpretation of this finding could be that prior start54
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up experience may be attributable to a rich experiential feedback base that allows
entrepreneurs to make better judgments about their ability to start a business. By
definition, that phenomenon is captured when measuring entrepreneurial selfefficacy (McGee et al., 2009) and not entrepreneurial intent (Thompson, 2009).
Whereas the former is rooted in entrepreneurial forethought, which is based on
previous entrepreneurial self-regulatory feedback cycles; the latter is only
concerned about particular actions that could be taken towards starting a
business.
It should be noted that the results of this study are not meant to negate
prior research on entrepreneurial learning and intentions. Instead, we aim to
broaden the discussion about entrepreneurship as learned behavior that is
contingent on a continuous exploration and experientially based feedback cycles
(Cope, 2005, 2011; Zimmerman, 2000, 2005). Consequently, we conclude that
introducing self-efficacy as a key motivational construct of forethought during
entrepreneurial self-regulation may allow us to go beyond intention based
models, by looking at entrepreneurial learning and development as a process that
is contingent on and influenced by contextual, social and environmental
influences (Winkler, 2014).
Following Cope (2011), who emphasized the “learning journey” that
relies on self-reflection in order to turn “experiences into learning” (p. 15), this
paper is an invitation for a continuing discussion about how we might initiate
new lines of inquiry to understand self-regulatory processes within
entrepreneurship and entrepreneurial learning. Subsequent research may
emphasize the development of a broader self-regulatory framework of
entrepreneurial learning, which may require the development of more refined
models and associated measures. Of particular importance within this context
may be the consideration of how experiential feedback (negative or positive)
may elicit higher and more accurate levels of entrepreneurial self-efficacy, in
order to gain a better understanding of why and how individuals take action
towards starting and growing businesses.
Limitations and Suggestions for Future Research
There are several limitations to the study that can serve as invitations for
future research. First, the nature and size of the sample limits our ability to
generalize the findings to other groups of student entrepreneurs and contexts. In
order to control for the confounding effects of curricular influences, the study
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sample was comprised of undergraduate students at one of the largest
entrepreneurship programs in the United States. Overall, the response rate to the
online survey was acceptable, however, given the length of the overall survey 21
percent of the students who started the survey did not complete it. Future studies
may replicate a shorter version of the study by also comparing the proposed
models across different schools, regions or even countries.
The second limitation is the reliance on self-report measures. Future
studies may also incorporate behavioral measures to gain a better understanding
between entrepreneurship students’ belief systems and their associated
entrepreneurial actions and behavior.
A third limitation is that the lack of an underlying process of
entrepreneurial self-regulation only accounts for entrepreneurial forethought
during one of many possible cycles of entrepreneurial self-regulation. We
suggest developing a larger framework that would allow us to investigate
subsequent entrepreneurial actions and associated feedback during key moments
of entrepreneurial learning. Future studies may look at refined measures that
allow for a more dynamic investigation of entrepreneurial learning that is linked
directly to specific behavioral as well as contextual influences.
Lastly, experimental and quasi-experimental research may help to
investigate the impact of certain entrepreneurship pedagogies, methods or
interventions on student, nascent or actual entrepreneurs’ entrepreneurial selfregulation.
CONCLUSION
In conclusion, the present study highlights the importance of a more
dynamic approach to investigating antecedents to entrepreneurial actions.
Entrepreneurial self-regulation with entrepreneurial self-efficacy as the key
motivational construct during entrepreneurial forethought, may serve as a
promising step towards a better understanding of how student entrepreneurs and
actual entrepreneurs think, act and learn based on experiences they have and
opportunities they act upon.
Keywords: Entrepreneurial intent, entrepreneurial self-efficacy, entrepreneurial
self-regulation, social cognition
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CAREER IMPACTS OF ENTREPRENEURSHIP
EDUCATION: HOW AND WHEN STUDENTS INTEND TO
UTILIZE ENTREPRENEURSHIP IN THEIR PROFESSIONAL
LIVES
Nathalie Duval-Couetil
Purdue University
Ziyu Long
Purdue University
INTRODUCTION
In a recent opinion piece in Wall Street Journal, Carl Schramm, former
President and CEO of the Kauffman Foundation said that despite colleges
churning out entrepreneurially-minded students, the “teaching of
entrepreneurship gets an incomplete” due to a lack of evidence of benefits
(Schramm, 2014). Schramm highlights the growth in entrepreneurship educators,
yet a decline in new businesses created. He also points to the lack of meaningful
metrics to measure the value of entrepreneurship education stating that “there is
no employer demand for people trained in the ‘art’ of entrepreneurship, nor does
the training offer any recognized value in other jobs.” During Schramm’s tenure
at Kauffman, the Foundation invested millions of dollars in programs designed to
catalyze the growth of entrepreneurship education across campuses and academic
disciplines.
From an outcome standpoint, it is fair to say that the jury is still out on
the value of entrepreneurship education if the metric is short-term new venture
creation. While economic development is the premise for the creation of many
entrepreneurship education programs, research suggests that venture
development may not be a representative outcome in the near term, particularly
for undergraduates. In general, limited research has explored how
entrepreneurship is constructed as a career goal or professional identity among
the increasingly diverse students studying entrepreneurship. The purpose of this
study to is to examine career goals through narratives written by
entrepreneurship students to understand their motivations for studying
entrepreneurship, the manner in which they expect to utilize it during the course
of their careers, and their timelines associated with doing so.
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LITERATURE REVIEW
The growth in entrepreneurship education across the country and
increasingly around the world has been well recognized (Katz, 2003; Kuratko,
2005; Torrance, 2013). Over the past two decades, a proliferation of
entrepreneurship programs, credentials, experiential and co-curricular activities
have been made accessible to undergraduate students in a wide variety of
academic disciplines beyond those enrolled in business schools. Programs vary
widely, emerging from various academic units; employing tenured faculty, nontenured faculty, or practitioners; and taking the form of majors, minors, and
certificates (Duval, Shartrand, & Reed-Rhoads, in press; Shartrand, Weilerstein,
Besterfield-Sacre, & Golding, 2010). Engaging students from a wide variety of
academic disciplines has expanded the discourse surrounding the value of
entrepreneurship education beyond that of venture creation. Recognizing that
starting a company is not an immediate goal for many students, today
entrepreneurship programs tout associated benefits, including the development of
leadership, communication, business literacy and intrapreneurial skills, in order
to draw a broader audience to programs.
Schramm’s comments highlight the ambiguity around what meaningful
outcomes should be for contemporary entrepreneurship programs, as well as how
and when they should be measured. These challenges have been discussed
extensively in the literature (Duval-Couetil, 2013; Fayolle, Gailly, & LassasClerc, 2006; Pittaway, Hannon, Gibb, & Thompson, 2009; Rideout, 2012) and
the topic continues to stimulate active debate at meetings of entrepreneurship
educators. Within the academic field there is a lack of consensus in defining the
knowledge domain of entrepreneurship or how it should be taught – ranging
from a set of terms, skills and competencies that students acquire, to the
development of an “entrepreneurial mindset” enabling them to identify
opportunities and be more proactive (Haynie, Shepherd, Mosakowski, & Earley,
2010; Neck & Greene, 2011). Varied pedagogical approaches lead to ambiguity
related to how outcomes should be measured. A broad array of measures for
entrepreneurship education have been proposed, ranging from student awareness
and interest, to skills and knowledge, entrepreneurial intention, venture creation
innovation, growth and development of enterprises, and community impact
(Falkang & Alberti, 2000; Fayolle et al., 2006; Pittaway et al., 2009; Vesper &
Gartner, 1997; Wyckham, 1989). Scholars have discussed the need to tailor
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evaluation criteria to the educational level, program goals, target audience, and
stakeholders (Duval-Couetil, 2013; Fayolle et al., 2006).
This leads to the question of when outcomes should be measured. As
Fayolle states, “venture creation’ cannot possibly be measured during or after an
[entrepreneurship education program] since venture creation usually takes time.
On the other hand, the more delayed the measurement, the harder it is to isolate
the role played by a single factor regarding its impact on a specific outcome such
as venture creation” (p. 704). Due to challenges inherent in longitudinal research,
many studies rely on short-term measures of self-efficacy and career intention to
examine the impact of entrepreneurship education programs. Longitudinal
studies conducted have found positive outcomes in favor or entrepreneurship
education (Charney & Libecap, 2003; Lange, Marram, Jawahar, Yong, &
Bygrave, 2011). More recently, the Entrepreneurship Education Project
(Vanevenhoven & Liguori, 2013) is collecting longitudinal, cross-cultural
quantitative data over the next decade in order to follow students’ careers,
motivations and identities to offer insight into the impact of educational practices
on student outcomes.
With decreasing stability in the economy, work environment, and
growing needs for personal control and fulfillment at work, entrepreneurship has
been proposed as a viable alternative career model to traditional organizational
employment. Previous research has examined factors influencing intention to
become an entrepreneur, which include perceptions of entrepreneurs and
entrepreneurship, self-efficacy, differing motivations for pursuing
entrepreneurship as a career, as well as the influence of gender and family
background. This body of literature is summarized below.
Gender plays an important role in shaping individuals’ perceptions of
entrepreneurship as a career option. A number of studies have shown that men
have stronger intention to pursue entrepreneurial careers than women (for a
review see, Shinnar, Giacomin, & Janssen, 2012). Gupta and Turban (2009)
found that the gender imbalance of entrepreneurial intention can be partially
attributed to gender stereotypes. They argued that men and women in our society
are labeled with different stereotypical characteristics that are suitable for
different types of jobs (for a review on gender stereotypes see, Gupta, Turban,
Wasti, & Sikdar, 2009). In their empirical research, they found that individuals
who have high male-gender identification, compared to those who have low
male-gender identification, had higher intentions of starting a business.
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Entrepreneurship continues to be “a manly career” which discourages women
from participating (Gupta & Turban, 2009).
In addition, extensive research has studied how entrepreneurial selfefficacy influences entrepreneurial career preferences. Research suggested that
individuals with higher entrepreneurial self-efficacy have higher entrepreneurial
intentions (for a review, Wilson, Kickul, & Marlino, 2007). It also indicated that
the presence of a parent in an entrepreneurial career appears to increase
entrepreneurial self-efficacy (Scherer, Adams, Carley, & Wiebe, 1989). Gender
differences are also observed in the assessment of self-efficacy. Thébaud (2010)
in her study of the Global Entrepreneurship Monitor’s annual survey found that
that women were about half as likely as men to think they had the ability to be an
entrepreneur in the U.S. although women and men have approximately equal
amounts of human, social, and financial capital.
Furthermore, research has employed motivation theory to understand
individuals’ career decisions to become entrepreneurs. Based on perceived
benefits and cost, individuals are either pulled or pushed toward a career in
entrepreneurship (for a review, Schjoedt & Shaver, 2007). Schjoedt and Shaver
(2007) analyzed whether the potential for increased life satisfaction pulled, or job
dissatisfaction pushed individuals toward entrepreneurial careers. They found
that nascent entrepreneurs were not pushed to entrepreneurship by low job
satisfaction but instead chose to become entrepreneurs to create life and job
satisfaction. Other motivations to become an entrepreneur include market
opportunities, family commitments, career frustrations, dissatisfactions,
flexibility, achievement, need for independence, or a feeling of not having other
alternatives (Cabrera, 2007; Patterson & Mavin, 2009).
Extant research provides limited insights about students’ motivations for
studying entrepreneurship, the manner in which they expect to utilize it during
the course of their careers, and the timeline associated with doing so. Schramm’s
comments imply that entrepreneurship education should accelerate near term
venture creation and economic development. Leading to interesting questions
such as: When can we expect a payoff from entrepreneurship education? Will
entrepreneurship education decrease the average age of entrepreneurs? And, if
entrepreneurship education is not resulting in accelerated involvement in venture
development, why are students studying it and how do they intend to use it?
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METHODS
The purpose of this study is to explore why students are studying
entrepreneurship and how and when they intend to use it. The research questions
are the following:
-
What are entrepreneurship students’ goals post-graduation?
-
In what manner and when do students expect to utilize entrepreneurship
education in their careers?
-
To what extent to gender and family background influence students’
perceptions of entrepreneurship as a career goal?
To address these questions, a two-phase, sequential, explanatory design
model was used (Creswell & Clark, 2007). In this exploratory research,
quantitative content analysis followed by qualitative thematic analysis were used
to examine the written narratives from 110 undergraduate students about their
career goals. As Creswell (2003) noted, combining qualitative and quantitative
methods allows a researcher “to better understand a research problem by
converging (or triangulating) both broad numeric trends from quantitative
research and the detail of qualitative research” (p. 100).
Sample and Data
The source of these data were narratives referred to as “personal business
plans” which were a required assignment in an undergraduate entrepreneurship
capstone course from fall 2011 to spring 2013 (n=110, 31 female, 79 male
participants). Students in the class had taken at least three entrepreneurship
classes and were from a wide variety of academic disciplines. The intent of the 23 page assignment was to have students, who were close to graduation, reflect on
and articulate a path for their short-term and long-term career and life goals in an
essay. As part of the assignment, students were also required to to meet with a
professional from a field or position that aligned with their goals, to obtain
feedback that could be integrated into their essays. The narratives were stripped
of all identifiable information. Each personal business plan was read carefully
prior to beginning analysis in order to develop the coding schemes necessary for
quantitative and qualitative analysis.
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Quantitative Analysis
Content analysis techniques were used in the first round of data analysis
to develop a quantitative coding scheme. A coding spreadsheet was created to
record the following overarching categories of data: 1) demographic information,
including gender, major, ethnicity, and year in college; 2) participants’ current
involvement in entrepreneurial activity and family entrepreneurial status; and 3)
participants’ immediate, short-term, and long-term career goals. Representative
quotes were also highlighted during this round of analysis.
Qualitative Thematic Analysis
Qualitative data analysis employed thematic techniques suggested by
Owen (1984, who stated that interpretive thematic analysis is especially well
suited to studies that require an open analysis that does not impose a unit of
analysis. As such, repetition of terms, recurrence of ideas, and forcefulness were
leveraged as criteria to identify themes. Analysis focused on participants’
perceptions of entrepreneurship, and their constructions of career plans. Through
constant comparison, open coding was employed where as many categories as
possible were coded (Lindlof & Taylor, 2002). Axial coding techniques were
then employed to establish linkages between constructs that emerged from open
coding. As a result, new categories or/and overarching themes, such as
entrepreneurship as ultimate and idealized career goals, were created (Lindlof &
Taylor, 2002).
RESULTS
For clarity, we present findings from each of the quantitative and
qualitative and analysis separately, noting the connections.
Quantitative Findings Based on Content Analysis
Three common career goals emerged from the student narratives,
including: 1) obtaining paid employment in an existing company, 2) starting
one’s own company, and 3) applying for graduate school. The content analysis
revealed that 97 participants (88%) planned to pursue paid employment in
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corporate settings, 49 participants (44.5%) were interested in pursuing graduate
education, and 71 participants (64.5%) were interested in starting up their own
company after graduation.
These data show that students had career goals and orientations that
integrate multiple paths or activities (Table 1).
Table 1
Students’ Multiple Career Goals and Paths
Career Goals and Paths
Entrepreneur
-ship
Yes
Graduate
Education
Yes
Percentage Percentage of
of all
students who
students
plan to
become
entrepreneurs
29%
45%
Corporate
Work
Yes
2
Yes
No
Yes
24%
37%
4%
8%
23%
6%
12%
-
12%
-
6
Yes
Yes
No
Yes
No
No
No
No
Yes
6
No
Yes
Yes
3
Among those who intended to become entrepreneurs, 58 students (83% of
those who were interested in entrepreneurship) reported that they expected to
start their own company after they had spent a number of years gaining
experience in a corporate setting. Thirty-two students (45% of those who are
interested in entrepreneurship) planned to start their venture after they had
worked in the industry and obtained a graduate degree. Finally, 36 students (51%
of those who were interested in entrepreneurship) planned to get an MBA degree
before starting their own ventures.
As shown in previous studies, female students tended to be less likely to
demonstrate a strong interest in an entrepreneurial career (Table 2).
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Table 2
Gender and Ultimate Career Goals
Gender
Entrepren
eurship
Corporat
e Work
Female
Number (Total=31)
Percent
14
20%
17
44%
Male
Number (Total=79)
Percent
57
80%
22
56%
71
65%
39
35%
Total
To further investigate whether intention differed significantly for female
and male undergraduate students, a Chi-square test was conducted crossing the
variables gender (female, male) and intention to start one’s own business (yes,
no). Results revealed a statistically significant difference, X2 (1) = 7.087, p =
.008, Φ = .25, reflecting that a larger percentage of male students (57 of 79 male
students, or 72.2%) planned to start their business compared to their female
counterparts (14 of 31 female students, or 45.2%). Thus, gender had a
statistically significant, medium impact or effect on whether participants actually
considered starting up their own business as a career goal.
Qualitative Findings Based on Thematic Analysis
For most of the students who intended to pursue it, entrepreneurship was
positioned as a longer term goal, with only a small minority considering it
immediately after graduation. Most planned to start a business after spending a
number of years working for an existing company, and/or after having received
an MBA. Themes and benefits associated with entrepreneurship education
beyond startup activity were intrapreneurship, transferrable skills, life skills, and
choices. These are discussed in the following sections.
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The Value of Entrepreneurship Education to Students
Among the sample, only five students had already started a venture.
These were at an early stage and were in the fields of technology and
construction. Two of the five indicated that they planned to have a long-term
entrepreneurial career, intending to sell their current business, and become a
serial entrepreneur or venture capitalist. Family and financial support contributed
to making entrepreneurship an accessible career option in the short-term:
“College is the right time to start doing something on my own, for
example starting my own business. The reason for this is that we learn a lot of
new things both practical and theoretical in college, so we can use them to
create new opportunities as most of the people are not utilizing the new
technologies and discoveries that have been made. Another reason for me is that
I can afford to make mistakes while I am in college as my father is there to
support me if something fails. Also for the initial financing for my business I
don’t have to go to anyone else since my father has agreed to finance me.”
(1123)
In sharp contrast, over a third of entrepreneurship students had no
intention of starting a business. These students were determined to pursue
corporate careers and wrote about using the knowledge learned from the
entrepreneurship educational program to enhance their competitiveness in the
professional world. They recognized the transferable values and skills that they
acquired through entrepreneurship education.
"I hope to achieve a stable financial career in the field of sales
management, along with using my entrepreneurial skills to help enhance my
opportunities in the business world." (1214)
“My strong marketing and management degree, accompanied with my
entrepreneurial skills will hopefully put me in a position to choose between a few
companies.” (1219)
Another student also wrote that although he did not plan to become an
entrepreneur, he found entrepreneurship education highly valuable to his career
and life in general.
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“Receiving my [credential in entrepreneurship] is very important to me
because I believe that we are all entrepreneurs even if we do not start our own
company – we are all the CEO’s of our own lives and these courses have helped
me become aware of important characteristics needed to not only succeed in life
as an entrepreneur, but simply succeed in whatever we choose to do.” (1104)
The other two-thirds of students viewed entrepreneurship as a career
possibility in the future. Participants wrote that exposure to entrepreneurship in
their undergraduate education had broadened their spectrum of career choices
and self-efficacy.
“I do know that I either want to own my own business or climb the
corporate ladder in an enjoyable company that shares the same values and
beliefs as me…Since I have been taking entrepreneurship classes, it has allowed
me to see that there is much more available than working for a large
corporation." (1209)
“Combined with what I've learned in the entrepreneurship program, I
feel capable of creating a sustainable business, which will empower people to be
creative and innovative through technology…I expect to bootstrap my way into a
niche market and attempt to procure outside funding. I think that at this point,
my degrees and work experience will improve my chances of funding
significantly.” (1220)
“[My first entrepreneurship class] showed me that it was possible to be
an entrepreneur. It showed me that it was a viable career and path and it gave
me some guidance on how to get started.” (1233)
Entrepreneurship as a Long-term Career Goal
For many students, entrepreneurship was positioned as a long-term career
goal, which was illustrated in students’ projected career trajectories over the next
5-20 years.
“My personal goals that I aim to achieve in the next 5-20 years are to
graduate from college, be financially independent, get married, and start my own
business."(1220).
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“1. Graduate from [X University] – December 2012
2. Working in industry for 1/1.5 years – May 2014
3. Get into MBA school and graduate – May 2016
4. Full time focus on the business venture
5. Buy a house (property:fixed asset) within approximately 2 years - 2018
6. Get rid of all loans (educational / for business) within approximately 2
years – 2020
7. Get married and grow the business.” (1234)
Entrepreneurship was positioned as a long-term goal because most
students perceived that they had to perfect their skills, expand their competency,
and accumulate social and financial capital before they could be successful
entrepreneurs. Generally speaking, participants viewed employment and
corporate working experience as a way to improve their professional capital
(industry knowledge and social network). In addition to improving one’s
professional skills to be able to operate independently, students wrote about
working for others to gain a clientele before launching their own businesses.
"I plan to work my way up from assistant designer positions to head
designer positions, and one day I will have my own fashion line." (1204)
“Once in the advertising profession, I plan on moving myself up through
the ranks until I receive a position where I have clientele under my supervision
and I have full driving force upon the creativity involved in their advertising
campaigns. As I become more successful with my campaigns and receive more
responsibility, I will have developed credibility among my peers and in the
advertising profession. This is where I will implement my entrepreneurial
experience.” (1115)
Similarly, the following participant talked about developing
professionally in a corporate job before taking over and reinventing his family
business.
“After I graduate in May I want to go work for an industrial chemical
company on the West Coast. The size of the chemical company does not matter to
me because it is not going to be a permanent job. I plan to work for that
company for a couple years and learn all about industrial lubricants and
cleaners. Then I plan on heading back to [town] to take over my dad’s business.
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I then would like to expand my dad’s already growing company. I’m not sure
exactly how I will do that but by that point I should have enough experience to
start developing my own formulas. I would run the company until I plan on
retiring or until I feel as though I have nothing more to offer. I will then pass it
on to either the most qualified employee or to one of my kids.” (1107)
In the following description of his future career as a doctor, a student
described his plans to perfect his skills through employment in different settings,
and start his own practice when he has achieved “high prestige.”
“I hope to land a spot in a residency in cardiology which will last for
three years before practice. Residency is a place in which I perfect my skills
before I start independently practicing. This is a time period in life that I want to
spend in Chicago, where I know I will be able to enjoy life while simultaneously
working long shifts as a hospital resident. Afterwards, after ten years, I aim to
work as a cardiologist in a hospital setting…After twenty years, I hope to be in a
position of high prestige running my own private practice in cardiology.” (1302)
Furthermore, participants framed receiving formal education in business,
such as an MBA, as an important step on the path to becoming an entrepreneur.
“By having a Master’s degree, I could understand more about the
financial and business industry besides expanding my network which could
absolutely help my future business.” (1307)
“Looking about five years down the road, I want to be settled into a job
that has opportunities for career growth. Along with that, if I hadn’t already
done so, I would want to pursue my MBA. I’ve decided that I would take time off
from school after I graduate so I could settle into a new home and life, but I do
plan on earning my MBA within the next five years, or at very least be on the
path to earning it. I want to find a company that would support me financially
through school so I can minimize my cost of going back to school and hopefully
open some career doors.” (1106)
Many participants also talked about the financial aspects of starting a
business early in their careers. The consensus among participants was that they
could only start their own ventures after they had accumulated enough start-up
capital. A senior in building construction management, talked about taking a job
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in an established company. He viewed this job as providing the foundation he
needed to secure the financial capital (loans) for his venture:
"My goal is to work for five years in industry to become financially
stable. This in turn will allow me to more susceptible to receiving loans for my
future business startups." (1207)
Another student addressed the need for capital and the right opportunity
to start his venture, instead of rushing to it.
“The faster I can save up my money, the sooner I will be able to invest in
a company or begin my own. I have a friend who plans to do the same, and we
are eventually going to become partners on a business venture of some kind.
Ultimately my goal is to own my business. I have always wanted a sports bar or
restaurant. However, this is the area that I am most flexible. I know that opening
a restaurant could be dangerous because many of them fail. I will wait for the
right opportunity and jump on it. I would never pass down a good opportunity if
it led me in another direction.” (1231)
Students viewed their paid employment in the beginning years as an
important source of income to make entrepreneurship possible. Others wrote that
the lack of capital or the fear of financial risks involved in the venture creation
have made them wondering whether entrepreneurship can be an attainable career
option.
"While it is a goal to start an entrepreneurial venture, I’m constantly
questioning financial feasibility and sustainable without putting a certain amount
of my own money into a venture." (1211)
Entrepreneurship as an Idealized Career Goal
In students’ descriptions of their aspirations, entrepreneurship appeared to
be not only an ultimate career goal that requires preparations, but also an
idealized career to which they are pulled. This is evident in students’ perceptions
of entrepreneurship as a means for them to realize their dreams and aspirations,
enjoy the autonomy as their own bosses, follow their passions, and make a
difference.
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“In twenty to thirty years is when I plan on executing my entrepreneurial
dreams. I would love to have a small family business to pass on to my kids or
have them grow up working there. The goal is to still have a business to run after
I retire from my regular job so I can stay active after I am done working the
normal nine to five.” (1106)
“I don’t know what I want to start yet, nor do I have any ideas. I just
know that there’s something I’ve kept inside my head that I when I plan to retire,
I plan on retiring solely on the fact that I have sustained my retirement through
money I’ve made being my own boss…I plan on starting this business based on a
problem that I want to solve for the greater good. This is the reason I am not
sure about what exactly my business will be. I want to wait until I feel that I am
financially and personally stable before identifying something in my life that I
want changed that will also provide me income.” (1110)
As illustrated in these quotes, the student assigned meaning to
entrepreneurship beyond its economic value. In this case, it is framed as ways to
nurture the next generation and enrich life after retirement. Interestingly, some
students also perceived holding a full-time “regular” job and being an
entrepreneur as something they could do concurrently.
“If I go the part-time job and full-time start up route I feel I will be
happier and I will dedicate days I have off to working regular independent hours
on my own. The part time job would be retained as long as it did not risk my
image at the company I was starting or until my new company could afford to
give me a better benefits plan. My real hope is to come up with an innovation,
invention, or unique product line that I can sell for a large payoff or that I can
continue to expand and sell for my lifetime. This is a common dream but a rare
success I believe I am truly capable and I have always been told I can
accomplish. Retirement is not out of the question but I do not see myself doing
nothing because I do not like to sit still or waste time.” (1117)
Some framed venture creation as an activity one can pursue after they
retire. Starting one’s own business is an active and interesting way to “pass the
time.”
“Start a small business in my mid 50’s while maintaining my current job
(long-term). The location for this small business would be relatively close to the
location of my permanent residence. My reason for this goal is because if I were
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to get bored with my current job later on in life, I will want to start up a small
business in order to help me pass the time.” (1241)
In these excerpts, students talked about making a difference through
entrepreneurship. Similar to others, they planned to embark on the
entrepreneurial journey when they are “qualified” and “financially and
personally” stable. Again, this highlights students’ perception that one needed to
have a certain level of stability in their life to weather risks and ambiguities
associated with the entrepreneurial process.
Gender Differences in Career Aspirations
Consistent with prior research, and content analysis associated
with this research, gender differences were pronounced in participants’ personal
business plans. Female participants tended to choose a corporate career path and
aimed to achieve a managerial positions. Fewer female participants considered
starting their own businesses than their male counterparts. The following
narratives were very representative of those of female participants.
“The position I ultimately would like to have in seven years is to be a
manager of a major account in a mid to large-sized public relations firm. With
over seven years of job experience, I feel that I would have enough knowledge in
the field to start at that high of a position. I will keep on adding to my
professional network to look for jobs in that position to apply to. Moving to other
agencies and other companies in general will help keep my job fresh, new, and
exciting.” (1248)
“My objective for the next three years is to get into the real world with
either of these jobs, gain a fair amount of real life work experience and to start
making a name for myself in one of these two companies. After my initial three
years I plan on climbing the corporate ladder at either of these companies and
eventually running my own portion or branch somewhere. I know I will succeed
in whichever I choose because I am an honest, diligent person that values hard
work and loyalty above all else.” (1111)
The majority of the young women constructed climbing up the corporate
ladder as their primary career goal and explained it explicitly. This was echoed
by a few participants.
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“I would gain the skills necessary to accomplish my goal of transferring
to a company that specializes in pharmaceuticals. I plan spending five to ten
years gaining experience before trying to advance into a segment that is so
competitive. My dream job would be to work for a company like Eli Lilly as a
sales representative.” (1250)
“My life career goal has always been to work for ESPN as an analyst or
sideline reporter. I am well aware that in order to achieve that goal I have to
start in a small market and work my way up to the ESPN market. (1254)
However, there were exceptions. One participant planned to start her own
law firm after gaining significant experience in her family’s firm.
“I will gain fifteen years of experience by working closely with other
lawyers in a family law firm. Once I have enough money saved and enough
experience to do it on my own, I will start my own practice. I will find a small
office space in [town] and rent it. I will grow the firm from there.” (1317)
Another female student planned to work for a company in the near term
but would consider starting her own business, which was not closely related to
the degree she was pursuing in college.
“I really want to continue learning and hopefully explore my interest in
HR and become either a full or part-time recruiter for [Company] as well.
During this period I also want to be taking night classes to obtain my
cosmetology license. My ten year goal is to have started a family and be either in
upper management with XX company or on my way to opening my own business.
The business I want to start is a salon. I have a passion for creativity and
cosmetology, but I wanted to get a solid bachelor’s degree and some working
experience before going to cosmetology school.” (1319)
Family Influence in Career Aspirations
Lastly, we found that those whose parents are/were entrepreneurs leaned
strongly toward an entrepreneurial career path.
“In the long-term, I plan to start my own venture. I hope to emulate my
father in terms of the decisions he made before and during the start of his
venture. He started his own export business of shoes and other apparel… He has
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been my role model throughout and I hope I can reach the level of success he has
envisaged for me. Starting my own venture is something I have always wanted to
do right from when I was in middle school. I have a few ideas, which I plan, to
research on in the upcoming years. In every situation, I take the advice of my
father very seriously and plan to work very hard in order to not disappoint him.”
(1330)
Some reflected on the experience they gained in growing up around
entrepreneurs, which strongly influenced their goals.
“I realize that many venture capital firms focus on large margins and
strong growth, but forget about the importance of the knowledge the instill in
their start-up companies. I have always had a strong desire to help others
succeed and want to be able to not only help them fund their venture, but to also
work with them and not only suck every penny out of them possible. Having
grown up around many successful business owners I have come to learn and
respect that some of the best businessmen are ones who care about what they do.
Touching back on who I am today, I want to work with people that like what they
do, since that is the whole reason I studied business in the first place.” (1124)
A participant also shared how his family experience shaped his goals.
“My professional story began in [city] where my father had left his job as
an engineer at [Company] and opened his own consulting firm. I am tied into the
story because this is where I grew fond of the entire concept of having one’s own
business. My parents organized the company together and I was alongside them
through the whole tedious process. I actively participated in the managing the
company as much as I could as a teenager and as high school came around. I
became my father’s right hand man. I came to college and although I wanted to
pursue medicine, opening my own private practice was my dream.” (1302)
Taken together, the findings of the data expand our understanding of how
undergraduate students from across disciplines articulate their career goals and
the role of entrepreneurship education within them. Examining these data can
offer insights into the value students place on entrepreneurship education and
when and how they intend to utilize it in their careers.
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DISCUSSION
The purpose of this study was to examine the career goals and narratives
of students to understand their motivations for studying entrepreneurship, the
manner in which they expect to utilize it during the course of their careers, and
their timelines for doing so. From the analysis it is clear that with few
exceptions, most students consider starting their own business a long-term goal.
Despite this, students in the sample had chosen to take multiple entrepreneurship
courses during their undergraduate programs, suggesting that they had clearly
received the message that entrepreneurship education could be valuable to their
near term career paths and lives in general.
Unlike the “image” of contemporary student entrepreneurs who start
ventures right out of school, when they have minimal responsibilities and
relatively little risk, most students felt that entrepreneurship was something that
was more feasible after they gained experience and perfected their skills working
for others. This finding is supported by data reporting that the average age of an
entrepreneur is 40 and high growth startups are almost twice as likely to be
launched by people over 55 as by people 20-34 (Wadhwa, Aggarwal, Holly, &
Salkever, 2009), suggesting that it may be too early to assess the benefits of the
past two decades of growth in the field of entrepreneurship education if
measured solely on the basis of venture creation. However, it also suggests that if
the goal of entrepreneurship education is to accelerate the formation of new
ventures, and decrease the age at which graduates become entrepreneurs, it may
not be achieving its goals. Hence, the effectiveness of specific pedagogy and/or
experiential learning activities in shortening time-to-venture should be examined.
Similarly, instead viewing entrepreneurs as young risk-takers, student
narratives positioned the “ideal entrepreneur” as highly educated, wellnetworked, and elite. Financial stability prior to pursuing entrepreneurship was
considered a requirement for many. While students felt strongly that
entrepreneurship education would provide them a competitive advantage in the
workplace, many also felt that an MBA would better prepare them to be an
entrepreneur. This implies that some students see entrepreneurship education as
an introduction to business but insufficient in fully developing their self-efficacy.
Throughout the narratives, it is clear that students are balancing experience,
financial stability and timing in deciding when to become an entrepreneur.
Interestingly, these students rejected the notion that the ideal entrepreneur
should be young and in the field of high tech. Instead, they talked about taking
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over and expanding family businesses, starting a hair salon, launching a fashion
line, and becoming doctors and lawyers. While a few students mentioned social
entrepreneurship, most focused on for-profit ventures. These findings could be
due to the particular program and sample of students studied, however, it is
reflective of the diversity of students increasing enrolled in contemporary
entrepreneurship programs. The range of entrepreneurial interests highlights the
value of interdisciplinarity but also the challenges associated with meeting the
interests and needs of a wide variety of backgrounds and career interests, which
has implications for curriculum and pedagogy.
Interestingly, students idealized an entrepreneurial career, equating it
with freedom and quality of life in addition to economic benefits. Clearly,
students are pulled to entrepreneurship by opportunity rather than by necessity.
Despite having been fully exposed to the challenges and time commitment
associated with launching a startup through their courses, some students
expressed the desire to hold a “regular job” while starting a company. This may
be due to naiveté, a lack of professional experience, or perhaps due to their
exposure to entrepreneurship education which has made this career path appear
very accessible. Generally speaking, student narratives seldom mentioned
barriers and potential negative effects of starting companies.
Similar to previous research, family influence was a very strong factor in
students’ desire to pursue an entrepreneurial career. Through the narratives, it is
clear that instead of being a deterrent, watching their parents struggle in
entrepreneurial pursuits appears to have inspired students to choose this path and
they expressed deep respect for them. This suggests that the more “real world”
experiences that can be delivered through entrepreneurship education, the more
inspired students might be.
The lower level of interest female students had in entrepreneurial careers
reinforce the importance of creating experiences that resonate with a more
diverse audience. The lack of female role models in entrepreneurship has been
well documented. Despite some progress, male protagonists are more commonly
highlighted in books, cases, videos, and other media associated with
entrepreneurship education (Gatewood, Brush, Carter, Greene, & Hart, 2004).
Programs must be proactive in addressing this issue to reach the untapped
economic potential of this population.
The expansion of entrepreneurship education beyond business schools is
likely to add complexity to assessing the value of entrepreneurship education. As
these narratives suggest, students have a very wide variety of career goals and
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interests requiring very different timelines to gaining the experience necessary to
pursue an entrepreneurial career. In past decades, when the delivery of
entrepreneurship education was limited primarily to business students (MBA
students with professional experience, in particular), it likely attracted a subset of
students who had a strong interest in venture creation in the near term.
Delivering entrepreneurship education to undergraduate students, with limited
professional experience, and with career aspirations in areas such as medicine
and engineering, adds complexity to understanding its value and measuring its
returns over time. Further, the expanding discourse around the benefits of
entrepreneurship beyond venture creation (e.g., leadership, intrapreneurship,
business literacy), which is necessary to appeal to a wider cross-campus
audience, may be attracting students with lower interest in venture creation. This
leads to interesting questions such as: Does wider delivery of entrepreneurship
education to a broader audience dilute its standing as an academic discipline?
And, is entrepreneurship becoming the “new” business education and business
literacy that all students need to be successful in the contemporary economy?
The primary contributions of this research are two-fold. First, the study
provides more nuanced and situated insights of students’ perceptions of an
entrepreneurial career. These insights help answer questions of important
theoretical and practical value having to do with why students choose
entrepreneurship as a career path, when they plan to become entrepreneurs, and
what path will they take to get there. In analyzing students’ narratives, we are
able to identify how they assess feasibility and obstacles related to becoming
entrepreneurs. Second, our research privileges students’ words about the role
entrepreneurship education plays in influencing their career self-efficacy,
expectations, and goals. Such an exploratory study provides the first steps in
articulating what entrepreneurial education affords to students, using a grounded,
bottoms-up approach to generate insights from data, as opposed to a top-down
one.
These findings have important implications for pedagogy and assessment.
They suggest that a one-size-fits-all approach to entrepreneurship may not be
appropriate given students’ differing career interests. It is clear that more
research on the background, entrepreneurial experiences, and career goals of
students is necessary in order to develop archetypes among students studying
entrepreneurship. This could be useful in aligning student interests with courses
and programs that meet their short and long-term entrepreneurial interests (e.g.
venture creation versus intrapreneurship). However, the movement to more
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diverse students and programs, with goals beyond venture creation could add
significant complexity to the assessment of programs. While being an
intrapreneur and a more productive employee due to entrepreneurship education
can clearly have positive economic outcomes, measuring them will never be as
straightforward as counting startups.
CONCLUSION
As the comments from Carl Schramm point out, the economic value of
entrepreneurship education in terms of venture creation has not yet been
demonstrated. This examination of undergraduate entrepreneurship students’
career goals shows that few intend to pursue entrepreneurship immediately after
graduation and some intend to utilize entrepreneurial skills to accelerate their
paths to leadership in existing organizations, and establish the financial stability
they prefer to have before becoming an entrepreneur. This leads to interesting
questions such as: Given the average age of entrepreneurs, is it just a matter of
time before the returns are realized? How well will students’ career goals map
with their actual career paths? Is the growth of entrepreneurship education to
wider audiences enhancing or diluting its effects as a driver of venture creation?
And, are we teaching entrepreneurship in a manner that it drives venture creation
and resonates with diverse populations? These are all questions that warrant
further investigation.
The variety of potential outcomes associated with entrepreneurship
education make its value difficult to measure. This further challenges a field
which has struggled to define its body of knowledge, its role as an academic
discipline, which at its core is about venture creation. It is clear that the discourse
involved in promoting the value of entrepreneurship education to wider
populations of students can be both a blessing in terms of attracting more interest
and people to the field, but also a curse in that it risks diluting its core premise.
This suggests that the confounding outcomes of being an entrepreneur (venture
creation) and being entrepreneurial (the “art” of entrepreneurship) should be
addressed distinctly in research and pedagogy.
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Wyckham, R. (1989). Measuring the effects of entrepreneurial education
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A COMPREHENSIVE FRAMEWORK FOR
ENTREPRENEURSHIP EDUCATION
Dave Valliere
Ryerson University
Steven A. Gedeon
Ryerson University
Sean Wise
Ryerson University
ABSTRACT
We report on the application of a novel and comprehensive framework for the
assessment and development of entrepreneurship education programs. By
building on models available in the current literature, and by incorporating key
constructs from the Theory of Planned Behaviour and from Stakeholder Theory,
we present a framework that places the design of an entrepreneurship education
program into a broad context where decisions of program content and pedagogy
are driven by considerations of the role of the program in the social, economic,
and institutional environment. This situating of design into a broader context
results in programs that are more responsive to environmental circumstances
and stakeholder needs and aspirations, and that exhibit greater coherence in
performance measurement. We illustrate the application of this framework
through a review of the design of two entrepreneurship programs, one in Canada
and one in Germany.
INTRODUCTION
New venture creation is a vital contributor to a healthy economy. New
ventures contribute to economic growth by commercializing innovation, bringing
forth novel resource combinations, and driving the production of markets
through new competitive pressures (Wong, Ho, & Autio, 2005). The
entrepreneurial actions of new ventures leads to discovery (Webb, Ireland, Hitt,
Kistruck, & Tihanyi, 2011) and increased productivity (Martin & Osberg, 2007),
and thence to broad social and economic progress (Wennekers & Thurik, 1999).
Policymakers in most Western countries therefore believe that greater levels of
entrepreneurship are required to reach higher levels of economic growth and
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innovation (Oosterbeek, van Praag, & Ijsselstein, 2010; Williams, Baláž, &
Wallace, 2004). Donald Kuratko called entrepreneurship “the most potent
economic force the world has ever experienced” (2005: 577). Despite this, levels
of entrepreneurship remain uneven across countries, societies, and communities
(Xavier, Kelley, Kew, Herrington, & Vorderwulbecke, 2012).
In response to the perceived need for more entrepreneurs, there has been
a dramatic rise in entrepreneurship education at a post-secondary levels
(Kuratko, 2005; Mars & Rios-Aguilar, 2010; Solomon, 2007; Vesper & Gartner,
1997). Charney and Libecap (2000) suggest that the reasons for such sudden
growth of entrepreneurship education at universities are economic shifts, a
growing demand from students, an increase in the funding for entrepreneurship
education, and a desire to increase technology transfer and innovation generation
at the post-secondary level. The benefits of entrepreneurship education include
positive student benefits and economic outcomes (Charney & Libecap, 2000),
and significant institutional benefits (Finnilä, 2006). These benefits result in
increased innovation, increased new venture creation, a propensity for selfemployment, higher annual incomes, and higher job satisfaction.
The rise in demand for post-secondary entrepreneurship education has led
to the emergence of new programs at existing educational institutions, expansion
and renewal of existing programs, and the creation of entirely new institutions
dedicated to entrepreneurship (e.g., the Founders Institute). Yet it is not clear
that these efforts towards education are very effective. For instance, a recent
paper by Rideout and Gray (2013) reviewed a decade’s worth of empirical
studies on the topic and found the majority of entrepreneurship education
programs lacked methodologies robust enough to yield reliable results. And
some studies have even found evidence that the effects of entrepreneurship
education can even be negative (Nabi, Holden, & Walmsley, 2010; Oosterbeek,
et al., 2010; von Graevenitz, Harhoff, & Weber, 2010).
There has been surprisingly little research on the performance of
entrepreneurship education programs. Relatively few studies have examined the
influence of such programs on student attitudes, goals, competence, and
behaviours (Duval-Couetil, 2013; Peterman & Kennedy, 2003). Most research on
entrepreneurship education has been focused on program design and
implementation, not on performance assessment (Dickson, Solomon, & Weaver,
2008; Garavan & O'Cinneide, 1994; Gorman, Hanlon, & King, 1997; Pittaway,
Hannon, Gibb, & Thompson, 2009).
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From the above, there is a greater demand for entrepreneurship education,
but little established research on the successful design of such. This suggests that
there may be a great opportunity to bring more design rigor to the process, in an
effort to generate better outcomes. That is the goal of this paper.
LITERATURE REVIEW
The prevailing theoretical underpinning for many entrepreneurship
education programs is the Theory of Planned Behaviour (TPB). This theory,
developed by Ajzen (1991) and built on the foundations of the previous Theory
of Reasoned Action (Fishbein & Ajzen, 1975), provides a valuable perspective
on the causal antecedents for a wide range of human actions, including economic
choices, health-related behaviours, and environmental psychology. Early in the
millennium entrepreneurship scholars began to employ this theory to better
understand the factors that lead to a range of specific entrepreneurial behaviours,
such as new venture creation (e.g., Krueger, Reilly, & Carsrud, 2000). TPB
proposes a causal chain from personal beliefs about the world, to attitudes about
possible future states, to intentions to try to bring about or prevent such states,
and then to behaviours performed. These core constructs further encompass
elements such as subjective norms about possible behaviours, and an individual’s
perceptions about their degree of control over selected behaviours.
Entrepreneurship educators have found great potential in this theory for
inculcating specific beliefs, attitudes, and intentions in students (Alain Fayolle &
Gailly, 2004; A. Fayolle, Gailly, & Lassas-Clerc, 2006).
The TPB model was further extended by Shapero and Sokol (1982) to
address the question of why entrepreneurial intentions (such as those formed in
students) sometimes did not directly lead to entrepreneurial behaviours (such as
launching new ventures). They proposed that the operationalization of intentions
was moderated by some form of “triggering event”, which may be either a
negative displacement (e.g., losing an existing job) or a positive displacement
(e.g., offer of resources from a prospective stakeholder in the new venture).
The Theory of Planned Behaviour provides a deterministic forwardcausality perspective on encouraging and predicting entrepreneurial behaviours.
But recently, entrepreneurship scholars have begun to explore other perspectives
that depend less on predictive causal logics. Entrepreneurial behaviours can also
be understood to result from non-deterministic processes of bricolage (Baker &
Nelson, 2005; Fisher, 2012), or from reverse-causal logics of effectuation
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(Sarasvathy, 2001). Such approaches assert a social constructivist ontology
towards entrepreneurship in which postmodern fluidities of meaning create value
(Valliere & Gegenhuber, 2014) and thereby provide a multitude of non-standard
approaches for educating prospective entrepreneurs.
While TPB provides a useful theoretical basis for program pedagogy, the
design and development of an entrepreneurship education involves much more
than just the decisions of pedagogy, and will involve many other parties than just
the designers; the program will have many different stakeholders. The literature
of Stakeholder Theory attempts to describe the relationship between a new
venture (such as a new educational program) and the various stakeholders that
have an interest in it. The stakeholder perspective argues that the development
champions must respond to the interests of more than just themselves (the
owner/shareholder perspective) or their suppliers, employees and customers (the
input/output perspective). Stakeholders in a new venture can include
governments, communities, and the larger society in which the venture operates.
The status of any individual or organization as a stakeholder depends on rightsholding, moral claims, ownership, agency, and resource contracting, as outlined
in Mitchell et al (1997). Program development champions must therefore attempt
to manage the demands of these stakeholders to access their resources and
achieve their goals (Donaldson & Preston, 1995), since these relationships
moderate the effects of strategy on performance (Berman, Wicks, Kotha, &
Jones, 1999). In return, the various stakeholders negotiate for a share of value
created, in the form of satisfaction of their individual goals. They can exert
power by withholding a needed resource or by providing resources that are
contingent on agreed conditions. For example, in the case of an entrepreneurship
education program, the challenge of engaging faculty members may be addressed
by the inclusion of communicative and relational aspects into the program
activities that achieve faculty objectives (Walker, 1990). Collectively, the
stakeholders can also appropriate a larger share of value created through the
degree of unity of their action, their control of information needed by the firm,
and their threats of abandoning the venture.
Against this background context, the literature of entrepreneurship
education offers a couple of models for program design that share many essential
features in calling for the explicit specification of who, what, why and how, and
the critical role of an ontology of entrepreneurship education. Fayolle and Gailly
(2008) propose a “teaching model framework for entrepreneurship education” in
which the ontological level is clearly delineated from the educational level. Their
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model strives to provide a basis of scientific legitimacy for the educational
design process, and combines the perspectives of teaching models and learning
processes. But this model is difficult to apply because it does not clearly lay out
the directional influences by which information from one aspect can be used to
inform the design choices of another aspect. All constructs exist on par, and
interact in some causally ambiguous manner.
Gedeon (2014) expands on this model by shifting the central orientation
away from the statement of program objectives and towards a process of making
practical content design decisions, and by introducing the resource implications
of the surrounding environment. His “entrepreneurship education program design
framework” model provides a much clearer set of causal influences among the
key constructs, improves the environmental contextualization of the program,
and emphasizes the means by which desired results are achieved. But despite
these improvements, the revised model still lacks some important and potentially
useful characteristics. The new environmental considerations are somewhat
underdeveloped, and the model does not reflect the dynamic nature of design and
delivery, and the learning processes that result from this.
Therefore, through experience with the design of entrepreneurship
education programs we sought to further extend these models into a framework
that addresses the requirements of the program design and delivery process, that
is solidly grounded in well-established theory, and that would be of pragmatic
value in a wide range of institutional settings. In the following section we outline
the development of a suitably extended framework that may be useful for the
design of entrepreneurship education programs. We then illustrate its application
by using it to present and assess the recent design of two very different
entrepreneurship education programs – an existing undergraduate program and a
new graduate-level program.
FRAMEWORK DEVELOPMENT
This section outlines the essential aspects of a framework for
entrepreneurship education programs, and proposes the necessary relationships
among these aspects. This explication is followed by the description of a twelvestep process to operationalize the framework as a set of sequential design
decisions.
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Context
A comprehensive framework begins with a broad assessment of the
context in which program development and delivery will occur and, following
Fayolle and Gailly (2008), rests on an ontological foundation that provides a
precise definition of the two essential constructs: entrepreneurship and education.
It is only by having taken a deliberate and formal step to define these key terms
that the myriad design decisions that will follow in the process can be taken. For
example, the ontological issues of whether entrepreneurship is the same as, or
different to small-business management, or whether it perforce involves the
creation of some form of new venture will have significant effects on the
specification of goals and objectives (discussed in the Why section below) and
on the selection of a target audience (discussed in the Who section below).
Similarly, the ontological issue of the relationship between education, training,
and mentoring will have significant effects on Why and Who, and also on the
pedagogical aspects of design (discussed in the How section below). Efforts at
program design or assessment that neglect to address these ontological issues run
the risk of misspecification and of failing to achieve any meaningful purpose or
objective. For example, a narrow perspective on entrepreneurship that
encompasses only for-profit businesses, based on radical technology innovations,
accompanied by the creation of the new start-up, may be suitable for a program
tailored to engineering students motivated by the chance of financial gain. But
such ontology may not be appropriate for students in other Faculties who may be
more interested in social innovation or personal empowerment. In such a case,
formally adopting a broader definition of entrepreneurship will guide the
subsequent design and implementation of a program more suitable for these other
students.
The second contextual factor to be considered is the environment in
which the program will be created and operated. By environment we mean to
include the entrepreneurial ecosystem in which the education will be embedded,
the marketplace dynamics, and the various stakeholders that have a legitimate
interest in the program. The ecosystem is significant due to the resource
munificence that it provides. A munificent ecosystem may provide ready access
to a wide range of supports for the educational process, such as expert speakers
and mentors, suitable placements for internships, role model entrepreneurs, and
access to support services for experiential learning activities (such as incubators,
accelerators, or early-stage capital providers).
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The market environment also creates opportunities and demands on the
design of a program. Market demographics and the competitive pressures of
other educational programs must be taken into consideration in designing a
program likely to have market appeal and thus be capable of generating the
revenues needed to be sustainable under increasingly challenging university
funding models. Moreover, the rapid globalization of the educational market has
led to increased competitive pressures on programs, due to the globalization of
supply that is enabled through e-learning delivery technologies and through nontraditional delivery modes (such as university online course materials and
competing MOOCs and businesses like Udacity). Globalization creates potential
globalization of demand, with the opportunity for programs to be designed to
deliver value to students anywhere in the world.
Finally, the environment also comprises the perspectives and demands of
the full range of stakeholders in the university enterprise, beyond just the
students. Taking these factors into account will necessitate examining the
specific policy objectives of different levels of government, the broad societal
need that the program is meant to address, the labour market for academics able
to create and deliver education, and the absorptive capacity of the markets into
which the students will graduate.
Why
Having established the broad Context relevant to the development of an
entrepreneurship education program, attention shifts to the specific objectives of
this particular instance. This is to say, we attempt to explicitly and
comprehensively state the purpose of the program – why it exists. Here we begin
by establishing a clear and meaningful vision for the program. While “vision”
remains a somewhat difficult construct to pin down in the literature (Larwood,
Falbe, Kriger, & Miesing, 1995), it is usually understood to be some kind of
aspirational statement of an idealized future state to which an organization or
program may contribute. As such, it paints a clear and compelling picture of a
desirable future state that is possible within the environmental context, and thus
serves as a guiding principle for the development of specific program objectives
and design goals.
Following from the vision, a mission statement is established to clearly
set out how the educational program will contribute to the organization’s pursuit
of the vision. By placing the program into the context of a broader vision, the
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mission statement links the specific goals and objectives of the program to
organizational progress toward achieving the vision. It shows why the
achievement of those goals and objectives is important to the organization.
From the established mission statement, a detailed range of qualitative
and quantitative goals can then be developed. These goals represent
multidimensional assessments of program performance towards the completion
of the mission (both in terms of efficacy and efficiency). It is appropriate to
develop these goals during the Why aspect of program design so as to ensure that
we are assessing the success of the operational program against the original
rationale and purpose of the program, and not against localized sub-objectives or
design parameters that may arise later in the detailed design or implementation
phases.
This development of the Why aspect of a program (vision, mission, and
goals) is influenced by the contextual analysis of stakeholder environment. In the
design and delivery of any new program, the university must strike an
appropriate balance among competing stakeholder demands and priorities. In the
case of Why, this means understanding and valuing what different stakeholders
think the university is for, such as the balance between the discovery of new
knowledge and the dissemination and mobilization of existing knowledge, or the
balance between the development of individuals with career skills appropriate to
the existing economy and the development of individuals capable of dealing with
the demands of an unknown and uncertain future economy. Competing
stakeholder interests on issues such as these must be resolved as part of
designing the Why aspect of a new program.
Who
Having established the Why rationale for the program, attention shifts to
clearly specifying the prospect students the program will be meant for. The
selection of a target audience of prospective students involves choices of level
(e.g., undergraduate, graduate, non-credit continuing education), entrance
requirements (e.g., prior work experience or education), specific communities of
interest (e.g., immigrants, small business managers, women entrepreneurs), and
industry sectors (e.g., reinvigorating local manufacturing, globalizing the
potential of a service sector, launching new high-tech “gazelle” firms). These
choices are obviously influenced by the Why of the program design, such as
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exploiting local resources and capabilities, creating jobs, ameliorating other
social pressures, or generating wealth to expand the tax base.
Design choices of Who can have significant effects on the sustainability
of the business model of the new program. By defining the target customer, the
choice of Who also defines the market (size, growth rate, projected trends, etc.)
and the competition for these same students (and the resulting effects on
recruitment rates and program size). For programs of significant duration (i.e.,
not single modules or events), the choice of Who may also directly impact
retention rates and student attrition, and the resulting effects on the business
model. For example, a program that targets a community with life circumstances
that create serious competing time demands and inflexibilities may expect high
attrition rates and should therefore be designed to be sustainable with low
enrollments in the upper-level courses, or without tight coupling between courses
and with multiple midstream re-entry points.
Selection of the target audience should reflect contextual information
about market demand (are there enough people who want to be educated in
entrepreneurship?) and competitive environment (is there unserved demand, or
will the program have a competitive advantage?). It should also reflect the
balance of stakeholder demands analyzed in the design of Why (e.g., local
government may specifically desire the entrepreneurial education of unemployed
individuals displaced by an economic shift).
How
Having established both a Why rationale for the program and a Who
target audience, attention turns to the means by which the overall mission may be
achieved for this audience. This is to say, we adopt a pedagogical stance that is
likely to achieve the desired mission by providing entrepreneurial education to
this specific audience. This pedagogical stance may include the degree to which
the program will embrace experiential educational methods and/or the
development of deep theoretical knowledge. In recent years the value of
experiential methods to the development of entrepreneurial capabilities in
individuals has gained increased recognition. At the same time, there has also
been an increasing recognition that entrepreneurship education comprises more
than just practical techniques and skills, and that some knowledge of relevant
theory and an ability to apply it is also beneficial. As Fiet noted, “…theory still
offers the most promise as course content for students” (2000: 1).
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The design choices of How will be influenced by the Context ontology of
the program, as the definition of entrepreneurship adopted will necessarily shape
the choice of pedagogy employed. For example, if entrepreneurship is seen as
Schumpeterian creative destruction (Schumpeter, 1961) and not simply Kirzner’s
equilibrating arbitrage (Kirzner, 1997), then pedagogy should emphasize
innovation and the subjectivist reconceptualization and re-enactment of resources
and markets. If entrepreneurship is Gartner’s behaviorism (Gartner, 1989), then
pedagogy should emphasize new venture creation and experiential role
enactment. And if entrepreneurship is Baron’s set of cognitive traits (Baron,
1998), then pedagogy should emphasize problem-solving skills and rote
reinforcement of cognitive schemata (Valliere, 2013).
The design choices of How are also influenced by the Context resource
environment of the program, as the pedagogy must be feasible. For example,
experiential internships and intensive mentoring will require a ready supply of
suitable site companies and willing senior entrepreneurs. Similarly, the demands
of the program cost structure (e.g., regulation or price elasticity of tuition fees)
will determine the affordability to the target audience and the resulting
sustainability of the business model.
The Why aspects of the program manifest indirectly as the set of guiding
values held by the institution and individuals responsible for the design of the
program. Although derived from the vision and mission considerations of Why,
these values are distinct from them. Values specify the constraints on how the
mission may be pursued, consistent with the ethical beliefs and priorities of the
institution. They act as promoters and constraints on pedagogical choices –
encouraging and supporting some approaches and discouraging or prohibiting
others. For example, experiential approaches may be particularly appropriate at
institutions that highly value community participation and the privileging of
marginalized perspectives.
Finally, some aspects of the How design of a program will also be
influenced by the needs, abilities, and preferences of the selected target audience.
Pedagogy should be suited to the cognitive needs and abilities of the audience
(e.g., their assumed background knowledge and learning styles), to their physical
and logistical constraints (e.g., their location and physical/environmental
requirements), and to their sociocultural context (e.g., the language of instruction
and the perceived legitimacy of the instructors).
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What
It is only having established Why, Who, and How that attention finally
turns to the “nuts and bolts” of program design – the planning of instructional
sequences, individual course/module objectives and structures, and individual
activities, exercises, and assignments to be done by students. This is the aspect of
program design that has usually received the greatest attention by
entrepreneurship educators. So there is a considerable body of knowledge to
draw upon in identifying options and alternatives for program content, and for
leveraging the experiences and artefacts created by existing programs. It is here
that we plan where desired attitudes, skills, and knowledge will be first
introduced to students, will be reinforced and interconnected, and will be
assessed for mastery. And it is here where we capitalize on best practices shared
by our colleagues in the academy. By using the new proposed framework this
content development is performed in a much broader setting, informed generally
by ontology and context, and more specifically by Why, Who, and How. For
example, the inclusion of student cognitive and attitudinal transformations as
desired learning outcomes permits the design of a What that includes the
psychocognitive, sociocognitive, and ethical dimensions that Bechard and
Gregoire (2005) have noted as largely absent from many entrepreneurship
education programs.
Earlier design decisions of Why become manifest in determining the
scope of the program content (both breadth and depth). The newly developed
What content must have sufficient coverage to achieve the Why objectives – to
encourage and equip program graduates to act in the desired fashion and achieve
the desired outcomes. Earlier design decisions of Who become manifest as
assumptions about the level of baseline knowledge that students will come in
with. Choices about Who are equivalent to establishing program recruitment and
entry criteria, and form the foundation on which the program attitudes, skills, and
knowledge can be added. And earlier design decisions of How, being values and
pedagogical stance, become manifest as decisions about specific methods and
tools to be used at various points in the program (e.g., readings, lectures, flipped
classrooms, group discussions, close mentoring, field experiences, and personal
reflections).
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Results
The final aspect of the framework refers to establishing meaningful
dimensions for the learning outcomes that may be achieved through the delivery
of the program, and the design of appropriate metrics for assessing these learning
outcomes. Formally assessing results is important because there is a clear line of
accountability from these metrics back to the Why rationale for which the
program was created. The program must reasonably meet the objectives of the
interested stakeholders, including the learning goals of participating students, the
teaching goals of instructors, the financial and reputational goals of the
university institution, and the development goals of the larger society in which
the program is embedded. And it is only through the capture and assessment of
specific measures that performance against these objectives can be known.
The specific measures to be adopted in a particular program must therefore
necessarily reflect all of the goals and objectives of that program. But, based on
the assessment framework recommended by Eseryel (2002) and Kirkpatrick
(1998), we suggest that there are four dimensions of program results that should
each be translated into meaningful, program-specific metrics:
 Transfer of knowledge. Outcome measures should be able to demonstrate
the effective transfer of knowledge to the participant students. We
suggest this is best done by establishing measures that correspond
directly to the goals established in the Why aspect of the program design,
as this connection is essential for schools with formal external
accreditations, such as AACSB or EQUIS.
 Development of skills and competencies. Outcome measures should also
call upon students to confirm their learning by demonstrating mastery of
the practical application of the new knowledge in a variety of situations
and contexts.
 Changes in beliefs, attitudes, and intentions. Since the primary theoretical
underpinning for much entrepreneurship education is TPB, it is essential
to measure and assess each of the key constructs in the causal chain in
order to identify the stage at which the most significant challenges occur.
Changes in behaviours most commonly occur after graduation, and would
therefore necessitate measures of career outcomes with alumni. But
changes in beliefs, attitudes, and intentions can be measured within the
program itself.
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
Stakeholder satisfaction for participants and for others. If the various
program stakeholders are not satisfied with the results produced by the
program they are likely to withdraw their support – prospective
entrepreneurs will not enroll or will drop out part way through, funders
and partners will withdraw their resource support, and universities will
withdraw their institutional support and legitimacy. And so it is important
that satisfaction be directly measured, independent of the foregoing
objective measures of knowledge transfer.
The capture of metrics such as these enables two distinct feedback loops
within the framework. The feedback from Results to How provides the
information needed to make ongoing refinements to the approaches being used,
and thereby to employ continuous improvement methods to make the program as
effective as possible. The feedback from Results to Why represents a periodic
confirmation that the mission is still valid and appropriate, and that it has not yet
been completed. While many educational programs target a never-ending supply
of young people with entrepreneurial aspirations, others may be more tightly
focused on an acute issue in a specific community, which is a mission that can
actually reach completion and thereby necessitate a re-examination of the
program rationale and future direction and a need to potential adopt a new
mission.
Figure 1 gives a visual representation of this overall analysis and design
framework, and shows how the broad conceptual aspects are connected into a
process of successively finer and more detailed design decision-making. It shows
how ontology and environmental consideration broadly inform program design
through various decisions of Why, Who, and How the program will operate.
These three aspects come together to influence the detailed design of the specific
activities that constitute delivery of the program. And this delivery is then
monitored through the measurement of appropriate results, which are fed back to
the earlier aspects of the framework in a process of assessment and continuous
improvement.
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Figure 1: The Proposed Framework
Strong parallels can be observed between this proposed framework and
models of Fayolle and Gailly (2008) and Gedeon (2014) on which it is based. All
three perspectives share a focus on specific and assessable Results and share the
connection between the design parameters of Why, Who, and How, and the
implementation details of What. They also share the ideal of a contextual
element that includes ontology (and possibly other factors). But the new
framework differs from its predecessors in several important ways. Like the
Gedeon model, this framework differs from the original proposal of Fayolle and
Gailly by emphasizing that Results are dictated primarily through the content
decisions of What, and that this mediates the influences of all of the other
aspects. This framework provides a clearer and more intuitive view of the
relationships among these aspects, in that it specifically outlines the sequential
relationship between vision, mission, values, and pedagogy. It also provides a
more complete reflection of the theoretical implications of TPB, by taking at par
all of beliefs, attitudes, intentions, and behaviours as a source of program goals
and as appropriate dimensions of results and the associated performance metrics.
Furthermore, this framework encompasses a deeper and more
comprehensive perspective on the factors that go into program design. It
explicitly takes into account a wider view of stakeholders and their influence on
design questions of Why, Who, and How. Finally, it recognizes that program
design and delivery takes place within the economic context of the university
business model – the effects of which are not simply limited to resource
availability. Program design may be expected to address institutional concerns
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about student recruitment and retention, and to do so in the context of an
increasingly competitive and globalized educational marketplace.
Finally, the framework differs in the degree to which it embraces
feedback control and continuous improvement. It does this by explicitly outlining
two feedback loops – one which adjusts and improves methodological design
decisions to achieve better results, and one which performs higher-level
monitoring of the mission that the program is meant to support.
But, despite these modest improvements that the proposed framework has
over previous versions, its relevance and value can only be confirmed through
application to the design and delivery of actual entrepreneurship education
programs. Accordingly we now look at two examples of a process for putting the
framework into practice: one in the renewal and redesign of a well-established
undergraduate program, and one in the initial design of a completely new
graduate program.
THE FRAMEWORK APPLICATION PROCESS
Application of a framework ideally follows the left-to-right explication
given above. But the framework proposed in figure 1 is robust to a variety of
entry points, so considerable flexibility is available to program designers. It is
possible to start with whichever framework aspect is best suited to current
institutional culture and priorities and then move from there to address the other
aspects, bearing in mind that subsequently addressing the design of antecedent
aspects may necessitate iteration and changes to initial design decisions. For
example, an institution that commences the design of a new entrepreneurship
program by obtaining outlines for courses offered at other similar institutions,
with the intent of replicating these courses with only minor modification, runs
the risk of discovering later in the design process (or worse, during
implementation and delivery) that the two institutions attract students of very
different backgrounds and very different career aspirations and desires for
specific entrepreneurship skills – a situation that may require very substantive
changes to course designs and program structures.
For this reason, we argue for application of the framework in the following
sequence:
1. Identify stakeholders, their interests, and their objectives. Where these
interests may conflict, program designers must negotiate based on the
power, the legitimacy, and the urgency of individual stakeholder claims.
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2. Establish an ontological basis for the institutional definitions of
entrepreneurship education, one which appropriately reflects the
perspectives of stakeholders.
3. Estimate the market demand for the program, the degree of competitive
overlap, and the likely competitive reaction.
4. Assess the availability of resources, keeping in mind the potential for
novel use of existing resources and the potential to access additional
resources through partners in the ecosystem.
5. Create the vision for the institution and the specific mission that the
program is meant to achieve. Translate this mission into a set of detailed
goals to be achieved.
6. Identify the key characteristics of the specific target audience for the
program, including demographics, prior education, prior
entrepreneurial/business experience, and goals and aspirations.
7. Articulate the set of values that the institution professes, and translate
these into supports and constraints on subsequent design decisions.
8. Choose the overall pedagogy to be employed in the program, which will
meet the definition of entrepreneurship education, attract the target
market, achieve the goals, operate within the resource constraints, and
respect the articulated values.
9. Develop the detailed program content, including delineating courses and
modules, establishing sequence dependencies, specifying course-level
objectives and learning outcomes, selecting course-level pedagogy and
methods, and creating detailed course contents.
10. Define specific assurances of learning for individual courses and for the
entire program of study, including measures of relevant knowledge,
competencies, beliefs, attitudes, intentions, behaviours, and satisfaction.
Best practice is to take pre and post measures of these.
11. Establish performance targets for the assurances of learning – whether as
absolute levels to be achieved, or as pre/post increments to be achieved.
12. Establish periodic feedback control from the assurances of learning to
enable ongoing monitoring and improvement to the program.
Application to an Existing Undergraduate Program
The first example of the application of this framework is the current
renewal of the undergraduate B.Com degree in entrepreneurship provided at
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Ryerson University in Toronto. Ryerson was founded as a polytechnic institute
in 1948, with a focus on delivery of technology-centric programs with immediate
practical relevance. In 1993 its status was upgraded to a full degree-granting
university, and it now has over 40,000 students in over 100 undergraduate and
graduate degree programs.
The entrepreneurship program at Ryerson began as a specialization in
Management Development in 1985. Through long experience and gradual
experimentation and growth, this program has evolved to include an
undergraduate major and minor, graduate specializations, and a wide range of
service courses available to other programs at the university. The Ryerson
entrepreneurship program is among the oldest, largest and most respected in
Canada.
In 2011 the Ted Rogers School of Management, which houses the
entrepreneurship program, was accredited by AACSB in a process that has had
significant and ongoing positive effects on program assessment and design
evolution. In particular it has led to a greater degree of rigour and formalization
of the objectives, design decisions, and assessment methods for all academic
programs in the Faculty. Moreover, in recent years there has been a dramatic
increase in the sophistication and development of sound academic underpinnings
for entrepreneurship education, which is clearly no longer simply the passing on
of “tips from the trenches” from successful entrepreneurs. And still further,
Ryerson has experienced dramatically increased demand for entrepreneurship
education, both as increased applications to the B.Com degree and the masterslevel specialty courses, and as demand for new courses and content delivery
modes from other programs across the entire university.
Also in 2011 Ryerson launched its Digital Media Zone (DMZ)
accelerator. Partly based on the accelerator examples of Y Combinator (Miller &
Bound, 2011) and Techstars (Cohen & Hochberg, 2013), the DMZ is unique in
providing a collaborative experience that involves founders, researchers,
educators, and student in experimenting with entrepreneurial innovations to the
digital media industry. The DMZ currently occupies 40,000 sq. ft. with more
than 70 new student-led ventures underway. This has been used as an
experimental test bed for innovative educational pedagogy in entrepreneurship,
technology commercialization, and finance.
The combined effect of all these significant changes was a compelling
impetus to revisit the goals, methods, and effects of the existing entrepreneurship
education program with the view to establishing an improved fit to changed
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circumstances and a better process for ensuring ongoing accountability to
stakeholders. As a result, a project was launched in 2013 to undertake a
comprehensive review of the overall program design and the detailed curriculum
to ensure Ryerson is able to maintain its leadership position in entrepreneurship
education in Canada. Led by faculty members with expertise in program design
and entrepreneurship pedagogy, and with the guidance of AACSB supports, this
ongoing project is significantly revamping the entrepreneurship major for
business students as well as creating novel approaches to providing additional
approaches to entrepreneurship education for other degree programs and noncredit audiences. Table 1 summarizes some of the changes that are being
explored through the application of the ideas inherent in the framework.
Table 1: Summary of Redesigned Undergraduate Program
Design Features
Ontology
Entrepreneurship
Value creation through the creative application of
Mind that applies to all degree programs across
campus.
Education
Experiential student-centric learning is our central
educational ontology. Evolving from teacher-centric to
more student-centric.
Environment
Stakeholders
A wide array of stakeholders including university
administration, other faculties, students and employers.
Re-designing the curriculum is a complicated process
involving the curriculum committee, department,
department council, school, and university senate.
Potential for entrenched interests and politics, but in
general good collaboration.
Market/competition Students choosing on a broader offering of
entrepreneurship services (whole product).
Tremendous demand from non-business students.
Competing universities have begun to realize the
importance of an entrepreneurship offering, plus new
competition from non-university programs.
Resources
Sufficient resources to broaden the range and number
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of courses. Good administrative support to further
increase our resources as needed. However, overall
financial restrictions drive larger average class sizes.
Why
Vision
Mission
Goals
Who
Target audience
Recruit/retain
How
Values
Pedagogy
Graduates who can think and act entrepreneurially in
any context (e.g., start-ups, intrapreneurship, social
enterprises, non-commercial activities, public policy).
Provide students with a deeply experiential and
transformative learning experience in a vibrant urban
environment. Empower students with a philosophy of
entrepreneurial thinking, passion, and actionorientation. Provide access to world-class support and
funding for our student’s new ventures embedded
within our community.
Meet AACSB accreditation with formalized and
articulated outcomes for program with periodic
reviews.
Continue to target B.Com undergrads and direct entry
(college graduates admitted to 3rd year). Service
courses for other degree programs. Adding more noncredit offerings for adult learners.
Soft employment markets are driving a return to
school. Increased reputation permits more selective
entry criteria. Direct entry backfills attrition due to
high academic standards in senior years. Lack of
subsidy for foreign students.
Flexibility and student choice, but driven by student
initiative and locus of control. Student obligation to
become proactive change-makers.
Shift from teaching to learning is gradual over the 4year duration. Creation of additional Zones in social
innovation, engineering tech, design, fashion,
community ventures, etc.
What
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Scope
Methods
Courses
Sequencing
Separation of core entrepreneurship (opportunities,
business models, resources) from expanded contexts
(new venture, corporate, social, industry verticals).
Significant emphasis on teamwork and experiential
methods (lean methods, flipped classrooms, capstone
field project). Assignments designed to embed students
within their local ecosystem (integration of cocurricular opportunities). Significantly increased theory
components and application.
Separate courses for Entrepreneurship majors to reduce
class sizes and increase exposure to advanced
techniques. Some current courses will become service
courses offered only to other majors. Addition of more
context-specific courses (e.g., family business, social
innovation).
Rigorous interconnection and articulation of learning
objectives across courses.
Results
Knowledge transfer Core theoretical concepts to be tested in the earlier
courses using standard assessment techniques.
Skills and
B.Com competencies: communication, ethics, critical
competencies
thinking, teamwork, synthesis, IT, finance. Program
competencies: opportunity identification, business
planning, selling.
Beliefs, attitudes,
Measured by a formal survey of students’ selfand intentions
perceptions based on Theory of Planned Behavior.
Includes desirability, feasibility, internal locus of
control, entrepreneurial intent, self-efficacy, and social
norms.
Satisfaction
Measured using standard university-wide satisfaction
survey.
The emerging design of the renewed program exhibits several changed
aspects that can be attributed to the comprehensive perspective that the new
framework engenders. These include:
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
Ontology – Expanding the definition of entrepreneurship by separating
entrepreneurial thinking and behaviours from the specific context in
which they are done.
 Who – Expanding the target audience to non-business students and nonstudents in the community.
 Who – Providing more program entry points for non-traditional learners.
 How – Developing Zone Learning models of non-credit delivery (e.g.,
supporting entrepreneurship education in the Digital Media Zone).
 What – Increased experiential content and flipped classroom techniques,
focused on practical application of new attitudes, skills, and knowledge.
 What – Increased diversity and depth of coverage of relevant theoretical
perspectives, to provide more sophisticated and nuanced conceptual tools.
To-date the feedback from faculty members on this program renewal process
has been very positive, as they see in it an opportunity to revisit and test
fundamental assumptions of program rationale and purpose, and a vehicle for
make quantum improvements to the methods used inside and outside the
traditional classroom. The anchoring of the design process in considerations of
basic ontology and environmental conditions has also meant that the process is
getting a high level of support from the university institution and buy-in from
many different stakeholders.
Application to a New Graduate Program
Our second example of the application of this framework is the creation
of a new MBA degree program in central Germany by the Brunswick European
Law School (BELS) and the Entrepreneurship Center at Ostfalia University of
Applied Sciences. BELS houses four institutes as well as an entrepreneurship
center that is tasked with delivering entrepreneurship courses, certificate
programs, summer courses, coaching and an on-campus incubator. Ostfalia has a
robust applied education program across four campuses with undergraduate
majors in law and business as well as graduate programs in law and strategic
management.
In 2011, a group comprising BELS, the Ostfalia Entrepreneurship center,
and Ostfalia’s regional training centre “Trainings- & Wieterbildungszentrum
Wolfenbüttel” (TWW), were contracted by the German government to create and
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deliver a new MBA in entrepreneurship. Outreach and marketing were to be
provided by TWW, program management and delivery by the entrepreneurship
centre, and accreditation, registrar services, and degree granting by BELS.
Unlike most other graduate programs in Germany, this program was expected to
charge tuition and be financially self-sustaining once the initial government seed
funding expired.
As a multi-party delivery system with faculty from different campuses, it
was essential to design the program using a formal design process methodology.
The new MBA in Entrepreneurship and Innovation Management was officially
launched in October 2013 with its first cohort of ten part-time students. Table 2
summarizes some of the major program aspects addressed during the design and
accreditation of the program.
Table 2: Summary of New Graduate Program
Design Features
Ontology
Entrepreneurship
Entrepreneurship must be broader than starting a
business and must encompass innovation management
and intrapreneurship.
Education
Program is designed with flexibility, self-directed
learning, and hybrid on-line education.
Environment
Stakeholders
A great degree of autonomy for designing the program
with few entrenched interests. Government is a major
stakeholder since they are paying for program
development and seed funding. TWW’s active
participation also ensures stakeholder engagement with
local businesses.
Market/competition Most other graduate programs in Germany are free, so
charging tuition will likely reduce the number of
students and require a high level of differentiation.
Resources
Program must be financially self-sufficient, so program
delivery costs must be contained.
Why
Vision
Help drive future national innovation and economic
prosperity through promoting the culture of an
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Mission
Goals
Who
Target audience
Recruit/retain
How
Values
Pedagogy
What
Scope
Methods
Courses
Sequencing
entrepreneurial mindset and intrapreneurship.
Self-sustaining boutique MBA program that offers
small class sizes, flexibility, and a hybrid on-line
experience.
Student-centric goal framework created. Designed to
meet EQUIS accreditation requirements. Eight learning
outcomes identified.
Primarily employed engineers working in large
companies but paying their own tuition. However, also
the self-employed and those who have started their
own companies.
TWW provides all program marketing. Planning
assumption is full retention.
Relevance to current employment and flexibility.
Heavy emphasis on self-directed learning in the hybrid
on-line program. Ratio of self-study to classroom
instruction is 10:1.
Traditional broad management foundation courses with
somewhat more law-related courses than most
programs. Embedded within the students’ existing job
experiences.
Master’s thesis required to allow the student to directly
apply the theories learned to their current jobs.
Fourteen courses identified. Each course is designed to
ensure all relevant theories and competencies learned
over the duration of the program.
Flexibility of sequence is important. There is a
suggested sequence, but there is only one prerequisite
relationship in the entire program.
Results
Knowledge transfer Measured in class with formal testing methods.
Skills and
Eight competencies measured: communication,
competencies
teamwork, guerilla skills, self-directed learning,
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Beliefs, attitudes,
and intentions
Satisfaction
creativity and innovation, motivational skills and
entrepreneurial thinking.
Measured by a formal survey of students’ selfperceptions based on TPB. Includes desirability,
feasibility, internal locus of control, entrepreneurial
intent, self-efficacy, and social norms.
Measured using standard university survey and thirdparty (magazine) satisfaction ranking.
One of the most critical aspects of the design process arose from the Who
aspect of the framework. Students must pay tuition for this program, instead of
attending the wide array of free graduate educational programs available in
Germany. So the first phase of the design was to perform a target market
analysis.
TWW contacted a wide array of local businesses to assess their interest in
paying for their employees to obtain the MBA, and through this to better
understand these stakeholder expectations. In addition, alumni and current
students at regional universities were sent an on-line survey to assess their
interest in such a program. Over one thousand on-line survey responses were
received and used along with the qualitative employer interviews to assess the
Who aspect.
We found that prospective students with the most interest were
predominantly from the engineering, science and math programs. In contrast,
graduates of the law and business programs did not show much interest.
Prospective students showed the most interest in content related to management,
innovation, commercialization and entrepreneurial mindset but less interest in
starting their own new ventures. Most of these prospective students were
employed. Most of the employers did not show much interest in paying for their
employees to attend the program.
These findings resulted in the name and emphasis of the MBA program
being changed from “Entrepreneurship” to “Entrepreneurship and Innovation
Management”. The fact that prospective students would have to pay for their
own tuition while being fully employed meant that flexibility would have to be a
key mission for the program, and that the How aspect would have to include set
class times on Friday evenings and weekends, as well as set the tuition fees at the
low end of the scale. The fact that most students would have no undergraduate
education in business necessitated the development and inclusion of an
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introductory business course, in addition to the advanced education expected of a
Master’s program.
DISCUSSION
Designing or re-designing a curriculum is always a complex multidimensional process with high potential for conflict. Curriculum committees are
often tempted to pick easy solutions (e.g., add a course or two) rather than
explore more drastic approaches (e.g., eliminating courses, reducing flexibility,
changing faculty workload). This problem can be mitigated by using a formal
design methodology that conforms to accreditation requirements.
Faculty members can often agree on aspirational vision and mission
sentiments, even if it is difficult to achieve consensus on the actual wording. A
solution is often to agree to a “draft” vision or mission for the purposes of
driving the design process forward. Similarly, achieving consensus on the precise
wording of a definition of entrepreneurship and education ontology might be
equally difficult. However, a draft consensus is often fairly easy to achieve on
the overall sense that entrepreneurship is bigger than just opportunity spotting,
starting a business, business planning, and acquiring resources. In particular, it is
often easier to adopt existing definitions from the literature that the committee
members feel are reasonably close, even if not perfect.
Academics are frequently tempted to obsess over what the difference is
between a vision and mission statement or over the detailed wording of
definitions, ontologies, mission statements and visions. But that misses the point.
The goal is to achieve sufficient consensus in order to move on to the next step
of the process, rather than getting bogged down over details that do not
practically matter.
This is also where the concept of continuous process improvement
becomes critically important. In most cases, faculty members cannot know with
certainty which courses, pedagogies, assignments and instructors will best
achieve the desired program goals. So committees can agree on a course of
action that seems appropriate, run the experiment for some time, collect data on
the actual results achieved, and then revise the curriculum in a new next iteration.
Committees do not need all the answers up front – they just need to set up a solid
measurement system and then continuously learn from it how to improve.
The biggest change we have seen from implementing the proposed design
framework in two different universities is the change in mindset of the faculty
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members and students. Prior to engaging in the process, individuals often had
strong opinions about what was best and would strenuously argue their points of
view. After going through the process, however, their mindsets shifted to more of
a curiosity-based focus on discovering what actually works best in practice.
Instead of fearing change, the focus shifted to a mindset of “let’s give it a try,
measure the results, and then iterate”. This approach is much more successful.
CONCLUSIONS
In this paper we have tried to achieve two things: the presentation of a
comprehensive and improved framework for the design and assessment of
entrepreneurship education programs, and the illustration of its practical
application through a twelve-step implementation process. The framework, like
those of Fayolle and Gailly (2008) and Gedeon (2014), is based on the causal
implications of the Theory of Planned Behaviour and the contextual influences of
ontology and environment. But it develops these ideas into a more complete
conceptual framework by incorporating the additional perspectives offered by
Stakeholder Theory. By adopting this greater breadth we are able to bring in a
more encompassing view of the many diverse program objectives and goals, and
thereby support the design of programs that provide value to all their
stakeholders. And by explicitly incorporating elements of market supply and
demand we better connect the pedagogic design process with the practical
business dimensions and resource constraints that are often ignored in more
idealized approaches to program design. Finally, this new framework provides a
more specific and delineated model of the causal relationships among the key
constructs and aspects, so that designers can better understand how design
decisions in one will be reflected in the choices available to other areas.
The illustrative applications in two university-level program design
exercises show that the framework can be useful in practical situations of
renewing an existing program or designing a new program. The 12-step design
process that we outline gives a structured mechanism for bringing together all of
the diverse elements and perspectives at the appropriate times. By adhering to
such a process, designers can be assured that nothing will be overlooked, and that
each element will be brought to bear at the appropriate time and in the
appropriate context so that program design objectives can be achieved.
At the start of this paper we argued that there is a strong and enduring
demand for entrepreneurship educations program but that existing program may
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suffer from designs that are overly focused on details of What, without adequate
attention being given to Why, Who, or How. And these designs may not be
taking full account of environmental opportunities and constraints. As a result,
these programs may not be achieving their full potential for developing more
entrepreneurs within a society. By proposing this new extended framework, we
hope to provide an approach to the design of entrepreneurship education that will
be more effective in achieving intended goals and outcomes because it is more
attentive to clearly specifying what those goals and outcomes are, more inclusive
of contextual factors, and more aware of the interdependency effects of the many
aspects of program design.
Despite the many advantages we suggest the approach to program design
brings, it should also be recognized that it has some limitations as well. In
particular, the framework is supported by entirely theoretical arguments, albeit
theories that have been well-established. For this reason experimentation with
this and other approaches should continue, to confirm that the framework
accurately captures the effectual relationships among the constructs, and that the
application process works in a wide range of situations and contexts. The field of
entrepreneurship education has a real need for best practices information that has
been empirically validated by real-world application to new and existing
programs.
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EXPECTANCY THEORY AND ENTREPRENEURIAL
MOTIVATION: A LONGITUDINAL EXAMINATION OF THE
ROLE OF ENTREPRENEURSHIP EDUCATION
Dan K. Hsu
Appalachian State University
Rachel S. Shinnar
Appalachian State University
Benjamin C. Powell
Appalachian State University
ABSTRACT
Can entrepreneurship education strengthen students’ motivations to pursue
entrepreneurial careers? By applying Vroom’s (1964) expectancy theory in a
longitudinal study, we demonstrate that entrepreneurship education can increase
students’ entrepreneurial motivation and intentions. More specifically, we
employ a pre- and post- research design to examine university students enrolled
in an introductory entrepreneurship course and find that that expectancy,
instrumentality and valence enhance entrepreneurial motivations. Our results
support the supposition that expectancy theory may be useful in predicting
entrepreneurial intentions. In addition, our findings show that students’
participation in an entrepreneurship course strengthened their expectancy and
desirability, leading to stronger motivation and intentions. These findings have
significant implications for research and practice, which are discussed.
INTRODUCTION
Why individuals become self-employed is one of the most important
research questions in the field of entrepreneurship in part because it may be
possible to use a better understanding of entrepreneurs’ motivations to enhance
the effectiveness of entrepreneurship education in increasing the rate of
entrepreneurship and increasing entrepreneurs’ effort and performance.
Increased quantity and better quality entrepreneurial activity in turn magnifies
the potential benefits that society accrues from entrepreneurship, especially
greater employment and innovation. Consistent with its importance,
entrepreneurial motivation has been extensively examined in the
entrepreneurship literature. However, most of the research investigating
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individuals’ motivations for becoming self-employed has employed the same
theoretical perspective: that of Ajzen’s (1991) theory of planned behavior
(Renko et al., 2012). The applicability of other motivation theories to selfemployment has not been as widely explored. More specifically, Kuratko et al.
(1997) highlighted a lack of empirical research on entrepreneurial motivations,
and Edelman et al. (2010) point to expectancy theory as a relevant model for
examining entrepreneurial motivation. Likewise, Renko et al. (2012) encouraged
“further research on expectancy theory in entrepreneurship” (p. 683).
Responding to these recommendations, we apply Vroom’s (1964) expectancy
theory to identify the drivers of entrepreneurial motivation in the context of
entrepreneurship education. We propose that expectancy, instrumentality and
valence increase entrepreneurial intentions. We also propose that
entrepreneurship education will strengthen these positive relationships.
Expectancy Theory
Expectancy theory (Vroom, 1964) has been successfully applied to
explain motivation in a wide variety of organizational contexts (Burton et al.,
1992; Chou & Pearson, 2012; Julian & Ofori-Dankwa, 2008; Lynd-Stevenson,
1999; Tyagi, 2010; Van Eerde & Thierry, 1996). An exception to this widespread
application of expectancy theory is entrepreneurial motivation, a context in
which the theory of planned behavior (Ajzen, 1991) has been much more
frequently applied. The theory of planned behavior proposes that an individual’s
intentions to engage in specific behaviors are driven by three antecedents: the
attitude toward the behavior, subjective norm, and perceived behavioral control
(Ajzen, 1991). While this model has been shown to be powerful in predicting
entrepreneurial intentions (Krueger et al., 2000), several empirical studies
(Krueger et al., 2000; Li, 2007) have questioned the role of subjective norm in
influencing entrepreneurial intentions. Because of the paucity of research
applying expectancy theory to entrepreneurial motivation, the promise of such
research, and potential weaknesses in the application of the theory of planned
behavior to the subject, we explore expectancy theory (Vroom, 1964) as a
complement to, and extension of, prior research on entrepreneurial motivation, in
effect following Locke and Baum’s (2007) assertion that “expectancy theory
provides a framework for understanding why and how someone people choose to
be entrepreneurs” (p. 94).
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Expectancy theory (Vroom, 1964) identifies three antecedes that motivate
individuals to put forth effort in order to attain an outcomes. These are
expectancy, instrumentality, and valence. Expectancy refers to an individual’s
belief that putting forth effort will result in high performance. Instrumentality
describes the belief that this performance is necessary to attain a specific goal or
outcome. Finally, valence relates to the evaluation of these goals and outcomes
(positive, neutral or negative valence). Thus, “if the outcomes are attractive,
instrumental toward achieving other goals, and expected via attainment of the
goal …then the individual will be highly motivated to achieve the goal”
(Kenworthy-U’Ren, 2000, p. 32). The motivational force, as defined in
expectancy theory, is the amount of effort a person will put forth in trying to
attain a specific goal. It is often computed using a multiplicative function of
valence, instrumentality and expectancy (Van Eerde & Thierry, 1996).
Many studies have tested expectancy theory in the domain of work
motivation. Indeed, a meta-analysis of seventy-seven studies indicated that
expectancy theory significantly predicted performance, effort, intentions,
preference, and choice (Van Eerde & Thierry, 1996). For example, Burton et al.
(1992) found that employees’ motivation to use a new expert system was
influenced by the level of the system’s anticipated attractiveness. Subsequent
research in other domains has identified the usefulness of expectancy theory in
predicting employee motivation, future employment status (Lynd-Stevenson,
1999), strategic decision making (Julian & Ofori-Dankwa, 2008), intentions to
engage in organizational citizenship behaviors (Chou & Pearson, 2012) and
motivation to socially loaf when working on group projects (Tyagi, 2010).
In the context of entrepreneurship, expectancy theory would predict that
an individual will be motivated to invest the effort necessary to start a business if
he/she believes that high input of effort will make it feasible for him/her to attain
desirable goals through business ownership (e.g., make more money, be
independent, gain high social status, etc.). This proposition is further developed
in the following section.
Expectancy Theory and Entrepreneurship
Expectancy is the belief that putting forth significant effort will result in
high performance. Thus, high expectancy is likely to motivate individuals to
engage in specific behaviors. Indeed, Shaver et al. (2001) found that
entrepreneurs who believe in their skills and abilities are motivated to put forth
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the necessary effort. Similarly, De Clercq et al. (2009) argued that entrepreneurs’
“belief in their ability to bring the start-up to fruition positively influences their
motivation to mobilize efforts to achieve the goal” (p. 134). This is closely
related to the concept of self-efficacy which is defined as an individual’s belief in
his or her ability to succeed in a specific task. Indeed, a significant body of
research has examined entrepreneurial self-efficacy (ESE) and its role in shaping
entrepreneurial intentions. Furthermore, a few studies examining expectancy
theory in the context of entrepreneurship have used ESE as a proxy for
measuring expectancy (De Clercq et al., 2009; Fitzsimmons & Douglas, 2011;
Krueger & Brazeal, 1994; Krueger et al., 2000; Renko et al., 2012; Segal et al.,
2005). As Segal et al. (2005) wrote, “expectancy is analogous to measures…[of]
self-efficacy used in other models predicting entrepreneurial intentions” (p. 44).
Expectancy theory, however, includes more than simple expectancy. It
encompasses two additional elements - instrumentality and valence. These refer
to the belief that achieving a certain level of performance in necessary in order to
attain individual goals (instrumentality) and the value placed on these goals by
the individual (valence). For example, if an individual views independence as an
outcome with high positive valence, and he or she believes that independence
can be best accomplished by owning a business, he or she will be strongly
motivated to pursue business ownership. Indeed, Holland (2011) examined
entrepreneurs’ motivations to persist in existing businesses and found that “when
the outcome valences are high, the motivation to persist is likely to be high” (p.
347). Thus, when individuals place high positive valence on the expected
outcomes of being an entrepreneur, they perceive this to be a desirable career
choice. Krueger et al. (2000), for example, argued that the intention to become an
entrepreneur is driven partly by perceived desirability. Indeed, perceived
desirability of business ownership has been identified as an antecedent of
entrepreneurial intentions (De Clercq et al., 2009; Holland, 2011; Krueger &
Brazeal, 1994; Krueger et al., 2000). Fitzsimmons and Douglas (2011) found a
significant and positive relationship between perceived desirability and
entrepreneurial intentions. In the same vein, Douglas and Shepherd (2000)
suggested that a person’s decision to become an entrepreneur is guided by a
utility function, reflecting perceptions of anticipated income, anticipated amount
of work effort to achieve this income, risk level, desire for independence, etc.
Similarly, De Clercq et al. (2009) found that “the attractiveness of
entrepreneurship as a career choice, based on personal preferences,… influences
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nascent entrepreneurs’ willingness to invest energy in setting up a business” (p.
134).
When studying the outcomes and/or goals that motivate entrepreneurial
action, studies have identified great diversity. Edelman et al. (2010) drew up a
list of these outcomes and/or goals based on the entrepreneurship literature that
includes: the desire for self-realization, achievement of financial success,
recognition, becoming a role model, being innovative, and becoming
independent. In fact, in her interviews with entrepreneurs, Kenworthy-U’Ren
(2000) reported an average of over 30 different goals for each entrepreneur. In
addition, each individual differs in the outcomes he or she hopes to achieve as a
result of business ownership. As Holland (2011) argued, “one entrepreneur may
consider personal wealth, independence, and public recognition as potential
outcomes of a particular opportunity while another focuses on family security
[or] the challenge of building a business” (p. 339). Therefore, in this paper,
perceived desirability was assessed in terms of both financial and non-financial
outcomes such as independence and the satisfaction of a need for achievement.
Based on the preceding discussion of expectancy theory and the
expectancy-instrumentality-valence model, we propose that:
H1 Students’ expectancy, instrumentality and valence of business
ownership will predict entrepreneurial intentions.
The Role of Entrepreneurship Education
As noted previously, the expectancy construct is closely related to selfefficacy. According to social cognitive theory, self-efficacy beliefs are developed
and strengthened in four ways: (1) enactive mastery; (2) vicarious experience
(role modeling); (3) subjective norm (social persuasion) and (4) physiological
states (Wood & Bandura, 1989). Building on social cognitive theory,
entrepreneurship education would be expected to strengthen individual ESE in
several ways. First, entrepreneurship education offers an opportunity to
repeatedly engage in a task and develop confidence in one’s ability to perform
such a task successfully in the future. For example, by conducting a market
analysis, pitching an idea, or writing a business plan as part of an
entrepreneurship course assignment, students may develop more confidence in
their abilities to perform such entrepreneurial tasks. Second, entrepreneurship
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education involves exposure to role models through guest speakers or case
studies of real entrepreneurs. Third, entrepreneurship education provides social
persuasion via feedback from others (instructors or peers) on in-class activities or
performance on course assignments. Indeed, Gatewood et al. (2002) studied the
impact feedback has on individual perceptions of entrepreneurial abilities and
expectancies. In their sample of undergraduate students, these researchers found
that feedback positively affects “expectancies for future entrepreneurial
performance” (p. 202).
Based on these theoretical and empirical arguments, numerous studies
have sought to examine the impact of entrepreneurship education on self-efficacy
perceptions (Bergman et al., 2011; Florin et al., 2007; Oosterbeek et al., 2010;
Peterman & Kennedy, 2003; von Graevenitz et al., 2010; Wilson et al., 2007;
Zhao et al., 2005). While results are not always consistent, many studies found
entrepreneurship education to positively impact perceptions of entrepreneurial
self-efficacy (Peterman & Kennedy, 2003; von Graevenitz et al., 2010; Zhao et
al., 2005). For example, in their study of Australian youth, Peterman and
Kennedy (2003) found that an enterprise program positively impacted both the
perceived feasibility and perceived desirability of an entrepreneurial career. Also,
Zhao et al. (2005) argued that entrepreneurship related learning has a strong and
positive influence on self-efficacy. We would also expect entreprenurship
education to influence individual perceptions of instrumentality when students
are exposed to the benefits as well as the challenges associated with business
ownership throughout the course of a semester. For example, in their
examination of science and engineering students at two major European
universities, Souitaris et al. (2007) found that “entrepreneurship programmes are
a source of trigger-events, which inspire students (arouse emotions and change
mindsets); inspiration is the programme-derived benefit that raises
entrepreneurial attitudes” (p. 585).
Entrepreneurship education was also found to have a positive impact on
entrepreneurial intentions (Fayolle et al., 2006; Kolvereid & Moen, 1997;
Souitaris et al., 2007; Vaizler, 2011; Yar Hamidi et al., 2008; Zhao et al., 2005).
For example, Vaizler (2011) found that the inspiration to become an entrepreneur
can be triggered in an entrepreneurship course and act as the main antecedent for
nascent entrepreneurial behavior. Fayolle et al. (2006) similarly found
entrepreneurship programs to have a strong, measurable impact on students’
entrepreneurial intentions. Similarly, Kolvereid and Moen (1997) compared the
behaviors of business graduates with a major in entrepreneurship with those of
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graduates with other majors from the same Norwegian business school; they
found that the graduates with an entrepreneurship major had stronger
entrepreneurial intentions and were more likely to start new businesses than other
graduates. Finally, Yar Hamidi et al. (2008) found high performance in a
‘creativity in entrepreneurship’ course to be positively associated with
entrepreneurial intentions. We therefore expect entrepreneurship education to
increase individual entrepreneurial motivations and propose that:
H2 Entrepreneurship education causes expectancy, instrumentality,
and valence to predict entrepreneurial intentions better.
Figure 1
Conceptual Model
Expectancy
Entrepreneurial Intentions
Instrumentality
Desirability
Valence
METHODOLOGY
Sample and Procedure
Surveys were administered to all students in 33 sections of an
introductory entrepreneurship course delivered between the Fall 2009 and Spring
2012 semesters (inclusively). A pre- and post-intervention design was used as
recommended by Fayolle and Liñán (2014). The first survey (Time 1) was
administered during the first session of the course before any instruction had
taken place. The second survey (Time 2) was administered during the last session
before final exams were taken. Both surveys were administered during class time
and, while participation was not mandatory, 740 complete surveys were collected
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at the beginning of the semester (Time 1) with a response rate of 98%. A number
of surveys were unusable due to incomplete data, resulting in a final sample of
619 for Time 1. Some attrition occurred between Time 1 and Time 2 because a
few students had dropped the class or were absent on the last day of the semester
when surveys were administered. Therefore, the sample at Time 2 consisted of
629 surveys, 503 of which contain complete data and were usable. When both
data sets were combined (Time 1 and Time 2), there were a total of 433 usable,
paired surveys with complete data. The sample descriptive statistics and the
correlation matrix of the 433 usable paired surveys are presented in Table 1.
Study participants were undergraduate students, with the large majority
taking the introductory entrepreneurship course as a required course. This
significantly reduces the possible bias that may be introduced when samples
consist of students participating in elective entrepreneurship courses because
such students are likely to have some level of predisposition toward
entrepreneurship (Fayolle & Gailly, 2013). A total of 227 of the original 740
respondents were female (31%), 333 (45%) had a parent who previously started a
business, 509 (69%) had worked for a small or new company, and 74 (10%) had
started a business.
Table 1
Descriptive Statistics and Correlations
Variable
Min
Max
1
Prior
Exp.
0
1
2
Gender†
3
4
5
ESE
(T1)
ESE
(T2)
Desir.
(T1)
Mean
S.D.
1
.10
.307
1.75
0.46
.133
2
3
4
4
20
15.02
2.75
.163
.008
7
20
15.81
2.44
.083
.030
.504
10
100
55.17
16.07
.053
.066
.328
.193
5
6
6
Desir.
(T2)
14
100
56.69
16.19
.102
.048
.336
.380
.646
7
EI (T1)
5
25
17.11
4.27
.213
.136
.426
.389
.422
.426
8
EI (T2)
5
25
17.55
4.44
.151
.139
.362
.481
.352
.531
7
0.729
N = 433; Coefficient ≥ .083 is significant at .05; Coefficient ≥ .133 is significant at .01
† Gender was coded “1” for female and “2” for male; the sample is 75% male.
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Measures
Central to the research question in this study are the constructs of
entrepreneurial self-efficacy (ESE), desirability and entrepreneurial intentions
(EI). Entrepreneurial self-efficacy was captured at both Time 1 (the beginning of
the course) and Time 2 (the end of the course) using Zhao et al.’s (2005) four
items measuring confidence in successfully engaging in entrepreneurial tasks;
each of the four items used a five-point Likert scale ranging from “1 = no
confidence” to “5=complete confidence.” This scale was chosen because it has
been shown to have high correlations with other available ESE scales (Zhao et
al., 2005). Cronbach’s alpha was acceptable at 0.79 (Time 1) and 0.77 (Time 2).
Valence and instrumentality were measured using Segal et al.’s (2005) eight-item
scale. The scale consists of four two-item pairs measuring: (a) perceived
importance of an outcome (valence) and (b) the probability of achieving that
particular outcomes through business ownership (instrumentality), for each of
four different outcomes (making money, having financial security, being
independent and satisfying a need for achievement). Reponses were measured on
a five-point Likert scale ranging from “1 = Not at all important” to “5 =
extremely important” for valence and “1 = 0-20%” to “5 = 81-100%” for
instrumentality. Cronbach’s alphas for instrumentality were 0.53 (Time 1) and
0.58 (Time 2). Although the alphas were relatively low, factor analysis showed
that the four items loaded onto a single factor at both times, indicating that the
four items comprehensively reflected a single factor. A confirmatory factor
analysis was then performed to further test scale validity (presented in a later
section of this paper). For the valence scale, Chronbach’s alphas were acceptable
at 0.76 (Time 1) and 0.77 (Time 2). The desirability variable was computed by
multiplying each pair of valence and instrumentality measures as done by Segal
et al. (2005).
Degree of motivation was assessed through intentions to engage in goal
directed behavior. Indeed, motivation is defined as a “psychological process that
cause[s] the arousal, direction, and persistence of voluntary actions that are goal
directed” (Mitchell, 1982, p. 81). In the context of entrepreneurship these would
be entrepreneurial intentions (EI), which were measured using Krueger et al.’s
(2000) five-item, five-point Likert scale, with each item ranging from “1=very
unlikely” to “5=very likely.” Cronbach’s alphas for EI were acceptable at 0.85
(Time 1) and 0.88 (Time 2).
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Control Variables
According to Ajzen (2001), prior experience with entrepreneurship is
expected to influence intentions to become an entrepreneur. In fact, Fitzsimmons
and Douglas (2011) suggested that “prior entrepreneurial experience is the most
important human capital variable in the determination of entrepreneurial
intentions” (p. 437). Prior entrepreneurial experience (both direct and vicarious)
was therefore included in the model as a control variable by asking the students
“Have you ever started a business?” Answers were recorded on a categorical
scale with “1=Yes” and “0=No.” Gender was also included as a control variable
because research suggests that women have lower ESE (Baughn et al., 2006;
Bergman et al., 2011; Wilson et al., 2007) and lower EI (Chen et al.; 1998, Zhao
et al., 2005) and because women have also been found to have different goals
when starting a venture (Manolova et al, 2008). Gender was coded “1” for
female and “2” for male.
Confirmatory Factor Analysis
Prior to testing our hypotheses, CFA was conducted on the variables of
interest at Time 1 and Time 2, independently, to examine the dimensionality of
our measures and scale validity. A three-factor model was specified, where five
items associated with EI loaded onto the first factor, four items associated with
ESE loaded onto the second factor, and the four-items associated with
desirability loaded onto the third. In Time 1 data, the model obtained an
acceptable fit (χ2 [62] = 404.73; p < 0.01; CFI = 0.909; RMSEA = 0.086). In
Time 2 data, the model obtained a good fit (χ2 [62] = 351.36; p < 0.01; CFI =
0.921; RMSEA = 0.079). These test results confirmed the reliability of our
scales.
Multiplicative Versus Component Approach
Vroom’s (1964) original proposition was that expectancy, instrumentality
and valence should be used in a multiplicative approach when assessing
motivational force. This was due to his belief that if either valence or expectancy
is not higher than zero, the person would not be motivated. The multiplicative
approach was used by Fitzsimmons and Douglas (2011) as well as Holland
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(2011). Others (Julian & Ofori-Dankwa, 2008; Renko et al., 2012), however,
have suggested that studies should examine the independent effects of the
antecedents. This is because, as Renko et al. (2012) found, “when a nascent
entrepreneur’s motivation is driven by financial success (valence), the intended
effort level remains high regardless of expectancy level” (p. 680). The authors
explain that necessity entrepreneurs, for example, may doubt their skills and
abilities (low expectancy levels), but still put a lot of effort into starting their own
business given the high valence they place on the financial rewards it could offer.
We chose to apply a combined approach, by assessing expectancy individually
and multiplying valence and instrumentality to yield a new variable which we
label desirability. In doing so, we follow Renko et al. (2012) and Julian and
Ofori-Dankwa (2008) suggestion, by examining expectancy and desirability
separately.
ANALYSIS AND RESULTS
OLS regressions were performed to test H1 with results reported in Table
2. Model 1 and Model 2 represent the regressions with the variables taken at the
beginning of the course (Time 1) and at the end of the course (Time 2),
respectively. The results showed that at both times ESE and desirability predict
entrepreneurial intention (ESE [Time 1]: β = .324, p < .01; Desirability [Time 1]:
β = .301, p < .01; ESE [Time 2]: β = .336, p < .01; Desirability [Time 2]: β =
.382, p < .01), supporting H1.
Table 2
Regression Models of ESE and Desirability
Standardized Coefficients
Model 1 (Time 1)1
Model 2 (Time 2)2
Control Variables
Prior Experience
.120**
.100**
Gender
Independent Variables
ESE
Desirability
.101**
.127**
.324**
.301**
.336**
.382**
R2
.306***
.406**
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Δ R2
1
.100**
2
n = 619; n = 503; Dependent variable: EI;
* Coefficient is significant at .05; ** Coefficient is significant at .01
As shown in Table 2, the R2 changed from .306 to .406. This means that
Model 2 explains more variance in the dependent variable (entrepreneurial
intentions) than Model 1. Model 2 appears to predict more of the variance in
entrepreneurial intentions than does Model 1. To examine whether this change in
R2’s is significant, the Fisher’s Z test was used to compare the two R2’s. A result
of z = 2.17 and p < .05 on a two-tailed test was obtained, indicating that the
change in R2 was indeed statistically significant. Model 2 predicted significantly
more variances in entrepreneurial intention, thereby indicating that the joint
predictability of ESE and desirability at Time 2 was stronger than those at Time
1, supporting H2.
To further examine this relationship, a post-hoc analysis was conducted
to examine whether the increase R2 came from ESE or desirability. The
unstandardized coefficient of ESE changed from .501 (S.E. = .056) to .607 (S.E.
= .067). These statistics were transformed into a Z-score (Cohan & Cohan, 1983)
of 2.88 (p < .01). The regression weight of ESE at Time 2 is significantly larger
than that at Time 1. A similar procedure was performed to test the difference
between the regression weights of desirability at Time 1 and Time 2. The
unstandardized coefficient of desirability changed from .079 (S.E. = .009) to .105
(S.E. = .010). These statistics were once again transformed into a Z-score
(Cohan & Cohan, 1983) of 5.96 (p < .01), which indicated that the regression
weight of desirability at Time 2 is significantly greater than that at Time 1.
Therefore, the predict power of both ESE and desirability increased from Time 1
to Time 2.
DISCUSSION
Our results make two main contributions to the literature. First, they offer
support for the predictive power of expectancy theory in the study of
entrepreneurial motivations. Expectancy, instrumentality and valence do in fact
predict individual motivations to pursue an entrepreneurial career. Regression
results show that 30.6% of the variance in entrepreneurial intentions was
explained by these variables at the beginning of the semester. Second, our
findings support the notion that entrepreneurship education has a positive impact
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on students’ perceived expectancy and desirability as they pertain to pursuing
entrepreneurship. The impact of entrepreneurial education is apparent in the
greater percentage of variance explained (40.6%) by the same three antecedents
at the conclusion of the semester. It would seem that, after taking a semester-long
entrepreneurship course, students perceived higher expectancy and desirability
which in turn translate into stronger motivation and intentions. This supports the
proposition that entrepreneurial skills can be taught and, once acquired, serve to
strengthen individual perceptions of competence and expectations for success.
It is important to note that the instructors teaching the introductory course
used in this research study placed emphasis on strengthening students’
understanding of the skills necessary to engage in entrepreneurial activities and
their ability to successfully apply those skills. Thus, the instructors focused on
strengthening students’ expectancy – their belief that they can successfully
complete entrepreneurial tasks. The instructors also focused on instrumentality –
students’ understanding of the importance of certain activities for their success as
entrepreneurs. The instructors did not, however, attempt to strengthen students’
valence, namely the value they place on business ownership. Entrepreneurship
was discussed as a career choice with its unique advantages and disadvantages.
Valence is therefore determined mostly by students’ individual perceptions of fit.
This fit refers to the individual’s perceived fit between his or her own values and
interests and the valence placed on an entrepreneurial career. While
entrepreneurship education can strengthen valence indirectly, this was not the
goal of the introductory course upon which this study is based.
Limitations
Data were collected through a survey instrument reported by the same
group of respondents. Therefore, any observed relationships may be in part a
result of the common method effect (Fiske, 1982). However, this limitation is
consistent with the limitations of prior empirical studies in this area and of most
survey research. A second limitation is that the study examined the effect of only
one entrepreneurship course; different courses at the same institution or at other
institutions could have a different effect. Replication studies are needed. A
related limitation stems from the fact that the data were collected from a single
U.S. university. Given national and regional variations in such a large and
diverse nation, this may limit the generalizability of our findings. A fourth
limitation stems from the gender imbalance in the distribution of our sample
which is about 70% male. This could have biased our results given males’ higher
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tendency to perceive strong ESE (Baughn et al., 2006; Bergman et al., 2011;
Wilson et al., 2007) and their stronger EI (Chen et al., 1998; Zhao et al., 2005).
Finally, while for the large majority of study respondents the course was a
required part of their major, a few may have chosen it as an elective. This may
have introduced some self-selection bias if the students taking this course as an
elective had some level of predisposition toward entrepreneurship (Fayolle &
Gailly, 2013).
Implications and Areas for Future Research
Our findings offer support for the importance of entrepreneurship
education as a vehicle for strengthening entrepreneurial motivations among
university students. Having participated in a semester-long entrepreneurship
course served to increase students’ expectancy. Overall, students were more
confident in their ability to successfully complete the tasks associated with
starting a business. In addition, students perceived entrepreneurial careers to be
more desirable. This means that students viewed entrepreneurship to be
instrumental in their ability to accomplish the goals on which they placed
positive valence. Indeed, along with the significant increase in expectancy and
desirability, our findings show a significant increase in intentions to pursue
entrepreneurial activities. The importance of understanding students’ career
choices is well explained by Krueger et al. (2000) who argued: “Students face an
immediate career choice [and] …starting a business may be a realistic option” (p.
425). Similarly, Hmieleski and Corbett (2006) “advocate the importance of
studying the intentions of students, who, through university…programs and the
increased infusion of entrepreneurship across educational curriculums,
experience increasingly lower barriers to starting their own businesses” (p. 59).
It is important to note here that not all students are motivated to start their
own businesses. Some may engage in entrepreneurial activities such as the
identification and exploitation of new opportunities on the behalf of their
employers. Entrepreneurship courses should thus not be limited to developing
business owners but rather should seek to develop students’ entrepreneurial skills
- skills that can be applied to both business ownership as well as to
entrepreneurial activities within organizations (i.e. corporate entrepreneurship).
Indeed as noted by Dess et al. (1999), “virtually all organizations—new startups, major corporations and alliances among global partners—are striving to
exploit product-market opportunities through innovative and proactive behavior”
(p. 85). Organizations increasingly view corporate entrepreneurship in its various
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forms as a “type of proactive behavior that can stimulate desired innovation”
(Kuratko et al., 2005, p. 699). Future research could differentiate between these
goals (i.e. entrepreneurial goals to be met through business ownership versus
corporate entrepreneurship) and assess whether these different types of goals
hold different valences for university graduates. A similar argument could be
made for social entrepreneurs who may apply an entrepreneurial skill set in
seeking to alleviate social problems.
Future studies could also examine whether the positive impact of
entrepreneurship education on students’ expectancy and desirability persist
across time. In this study, students’ attitudes were compared in two points in
time: at the beginning and at the end of a semester. It would be valuable to assess
whether the observed increase in students’ expectancy, desirability and intentions
persist post-graduation and later in to the future. This would help educators
understand whether the higher motivations identified among students at the
conclusion of the course eventually translate into actual entrepreneurial behavior.
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THE EDUCATION OF ENTREPRENEURS: AN
INSTRUMENT TO MEASURE ENTREPRENEURIAL
DEVELOPMENT
Kenneth F. Newbold, Jr.
James Madison University
T. Dary Erwin
James Madison University
ABSTRACT
Entrepreneurship education programs have expanded across post-secondary
education in the past thirty years, leading to an increased need in instruments
that can evaluate the impact of entrepreneurship education. An instrument in
entrepreneurial development with sub-scores in Entrepreneurial Intent,
Entrepreneurship Self-Efficacy, Entrepreneurship Outcome Expectations, and
Goal Directed Activity was revised over three related studies to investigate the
effect entrepreneurship education has on entrepreneurship development. In
three separate samples, this instrument differentiated between students, existing
entrepreneurs, and alumni individuals who had entrepreneurial coursework
versus individuals who did not participate in entrepreneurial education.
INTRODUCTION
With the rise of global economic competition, evolving business markets,
and international economic uncertainty, many nations have looked for solutions
to stabilize fiscal conditions. One approach has been to focus on
entrepreneurship as a means of building sustainable business models upon which
new ventures will flourish. With growing trends towards innovation as an
economic driver, entrepreneurship has become a commonly referenced term in
the popular as well as academic press and has been identified by policy leaders
as a crucial element to the global marketplace. Approximately four million new
businesses are created annually contributing the majority of new jobs to the US
economy (Haltiwanger et al, 2009) as an illustration of the impact
entrepreneurship has on economic development. Worldwide, an increased
emphasis has been placed on educating the current and future workforce in
aspects of entrepreneurship as a means of remaining globally competitive.
Business and government officials have called upon post-secondary education to
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help address the need for entrepreneurs and to develop the knowledge, skills and
abilities individuals require to successfully implement new business ventures.
This study operationally refines the constructs of entrepreneurship development
including the further design of existing instruments to measure these constructs.
Moreover, these re-designed instruments are administered in three validity
studies to three different samples of: (1) undergraduate students who completed
an entrepreneurship course; (2) existing entrepreneurs; and (3) college graduates
who had completed an entrepreneurship course up to seven years ago versus
graduates who had not completed any entrepreneurship coursework. A review of
the existing literature is provided below to frame entrepreneurship education in
the present research, which builds upon previous study of entrepreneurial
education worldwide (Santos, 2013; Engle et al, 2011) and others.
Entrepreneurship education
Katz (2003) provides a historical context for the rise of entrepreneurship
education in American higher education, from the earliest courses found in 1876
to focused efforts at Harvard beginning in 1947 and an increase in programs
being offered in the 1970s. Today, over 1,600 US institutions of higher learning
offer entrepreneurship-related courses with more than 275 endowed faculty
positions and close to 50 refereed journals dedicated to the field of
entrepreneurship (Katz, 2003). Gibb (1993) studied the growth of
entrepreneurship education programs in the United Kingdom, illustrating a
growth in the number of programs since the 1980s. The growth in
entrepreneurship education programs has not been limited to the United States,
as other nations around the globe have also looked to develop programs
including Canada (Myrah, 2006), Portugal (Silva, et al, 2012), and the European
Union (Turnbull, 2012). Despite the growth in entrepreneurial education
programs, little has been done to measure the impact of entrepreneurship
education on entrepreneurship development.
The ability for an individual to learn entrepreneurship skills has been
questioned in the popular and academic literature. Wasserman (2012) argued,
“founders of startups clearly believe they can learn” and Torrance (2013) held
that it is not if entrepreneurs can be taught, but how to teach entrepreneurs. It
has been shown that education relates positively to the economic performance of
start-ups (Gimeno et al., 1997) yet the role that entrepreneurship education plays
in entrepreneurship development remains a nascent field of research.
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Social cognitive career theory
Social Cognitive Career Theory (SCCT) holds that an individual’s
occupational considerations are partially a function of self-efficacy beliefs and an
individual’s intent, expected career outcomes and goals. As put forth by Lent,
Brown, and Hackett (1994), SCCT describes interrelated and dynamic models of
career and academic interest development, choice, and performance. This theory
is based upon Bandura’s (1986) Social Cognitive Theory. The present research
is grounded within SCCT and focuses on the area of entrepreneurship upon
which an individual develops along the constructs of Entrepreneurial Intent,
Entrepreneurship Self-Efficacy, Entrepreneurship Outcome Expectations, and
Goal Directed Activity.
Research focus
In investigating entrepreneurship development, the following research
question serves as the fundamental pursuit of the present inquiry: “Does
participation in an entrepreneurial educational experience increase an
individual’s development and likelihood to pursue entrepreneurial ventures?”
Data gathered from these studies provides insight into ways in which
entrepreneurship education impacts an individual’s development by comparing
those who participated in an educational experience and those who did not
engage in entrepreneurship education.
Entrepreneurship and Entrepreneurial Development: Conceptualization
and Constructs
Entrepreneurship as an area of development has been previously studied
with evidence supporting positive impacts of educational experiences (Kuratko,
2003). The following review of the literature is structured into three sections,
definitions and constructs, educational interventions, and research methodology.
Definitions of Entrepreneurship
Forming a common definition for the terms of entrepreneur and
entrepreneurship is necessary as these concepts serve as the core focus and are
discussed throughout this research. The literature provides a series of definitions
for these terms but, for the purposes of the present research, the investigators
have established a set of definitions to further refine widely used concepts within
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the context of this research. Definitions of key terms as conceptualized by the
investigators and used in the present research are provided at the conclusion of
this section of the literature review.
In the current economic environment, the terms entrepreneurship and
entrepreneur have been widely used in the popular and academic literature. As
institutions of higher education implement new programs in the area of
entrepreneurship, it is important to frame how the term is conceived for the
purpose of studying the development that individuals experience as a result of
participating in entrepreneurship education. The existing literature provides
definitions for the term entrepreneurship (Shane and Venkataraman, 2000;
McMullen and Shepherd, 2006; Mars and Rios-Aguilar, 2010) along with
entrepreneur (Thornton, 1999; Mars and Rios-Aguilar, 2010; Isenberg, 2013). In
building upon definitions found in the existing literature, the present research
operationalizes the term entrepreneurship as an action-based process of creating
a venture, which provides market value. Similarly, this study focuses on
entrepreneurs as risk-taking individuals engaged in starting new business
ventures through creation, invention, and action to meet a market need, rather
than individuals who invest or manage start-up companies. For the purpose of
this research, the term entrepreneur has been framed around actions taken to start
a venture and build economic value in the market.
Constructs
A basis upon which to measure entrepreneurship development is
necessary as it relates to the theoretical as well as operational aspects of this
research. Social Cognitive Career Theory offers dimensions of development
within entrepreneurship through which this research will explore the impact
education that has on entrepreneurship development.
Concepts of entrepreneurship development
Kuratko (2003) held that “entrepreneurship, or certain facets of it, can be
taught…and business educators and professionals have evolved beyond the myth
that entrepreneurs are born, not made” (11). Similar to the study of leadership,
early research into entrepreneurship focused on individual traits possessed by
successful entrepreneurs. As inconsistency in research findings was detected in
both fields, scholars shifted from studying traits and situational factors to a
dynamic learning process through which entrepreneurs engage in an evolutionary
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process or what will be referred to in this study as entrepreneurial development
(Cope and Watts, 2000; Rae and Carswell, 2000; Swiercz and Lydon, 2002;
Young and Sexton, 2003; Cope, 2005; Kempster, 2006; Rae 2006; Kempster and
Cope, 2010). From this literature, several dimensions of entrepreneurship
development have evolved and will be described below: entrepreneurship selfefficacy, entrepreneurial intent, entrepreneurship outcome expectations, and goal
directed activity. These four dimensions serve as the areas of focus for the
present research including measurement scales refined by the authors to study the
effect of education on entrepreneurship development.
Scholars have examined curricular activities to determine if
entrepreneurship is a discipline and thus can be learned. These efforts have
expanded as programs have proliferated with research being done in increasing
quantity and quality around the globe (Drucker, 1985; Henry et al 2005; Kuratko,
2005). As entrepreneurship and innovation have been recognized as critical
drivers of sustainable economic development and competitive advantage in the
U.S. and internationally (Birch, 1987; Sine and Lee, 2009), Katz (2003); Matlay
(2008); and Solomon et al. (2002) have made calls to produce and deliver highquality entrepreneurship education. Entrepreneurship self-efficacy
The literature shows self-efficacy as a highly appropriate measure for the
study of entrepreneurs. According to Chen, et al. (1998), the relationship
between self-efficacy and behavior is best demonstrated in challenging situations
of risk and uncertainty, which are believed to be characteristics of entrepreneurs.
In this study, the authors defined entrepreneurial self-efficacy as the strength of a
person’s belief that he or she is capable of successfully performing the various
roles and tasks of entrepreneurship. Chen et al. (1998) developed five factors,
“marketing, innovation, management, risk-taking, and financial control” (304) in
relation to one’s entrepreneurial self-efficacy. From the results, the authors
report Cronbach’s alpha of .89. Results from this research showed scores on
entrepreneurial self-efficacy differentiated entrepreneurship students from
students of both management and organizational psychology. Additionally,
entrepreneurship self-efficacy was found to be positively related to the intention
of setting up one’s own business indicating that those who reported higher selfefficacy scores were more likely to start a company. The results of this study
indicate the potential of entrepreneurship self-efficacy as a distinct characteristic
of an entrepreneur.
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Entrepreneurial intent
Researchers have investigated individual intentions to start new business
ventures as a construct of entrepreneurship (Bird, 1998; Carr and Sequeira, 2007;
Krueger, 2000; Webster, 1977; Wilson et al., 2007) and to explore
entrepreneurial intentions post-graduation (Galloway and Brown, 2002;
Galloway and Levie, 2001). Previous research has indicated entrepreneurial
intent to be an important and continuing construct in entrepreneurship theory and
research (Carr and Sequeira, 2007; Hmieleski and Corbett, 2006; Wilson et al.,
2007). However, Shook et al (2003) found no common definition or
measurement of entrepreneurial intent. Autio et al. (1997) stated this construct
lacked a psychometrically-validated measurement scale. This lack of a uniform
understanding and measurement offers an opportunity for the present research to
further investigate the construct as it relates to an individual’s entrepreneurship
development.
Entrepreneurship outcome expectations
The construct of Entrepreneurship Outcome Expectations as it relates to
vocational interests was originally put forth in the model developed by Lent,
Brown and Hackett (1994). Self-efficacy has been researched more extensively
across academic disciplines than the construct of outcomes expectations, but
initial research indicates the potential for broader use in the study of occupational
choice. Bandura (1977) defined the construct of outcome expectations as the
expected results or outcomes of intentional actions in which an individual
chooses to engage.
Gore and Leuwerke (2000) conducted a study using a sample of 93
college students to explore the relationships among self-efficacy beliefs, outcome
expectations, congruence, and occupational considerations to predict an
individual’s career choice. Using the Strong Interest Inventory (Harmon et. al,
1994), the authors reported reliability scores ranging from .91 to .96 across the
dimensions of the instrument. Participants indicated the degree to which they
would get what they wanted from each of the 84 occupation titles listed on the
instrument using a 9-point scale ranging from 1 (not very much) to 9 (very
much). These authors hypothesized “outcome expectations would account for
additional unique variance in occupational considerations” (240). Through
regression analysis, this research indicated outcomes expectations predicted
occupational interests (r2=.20, F = 20.45, p <. 05). Although the sample was
limited, this study attempted to further the empirical understanding of the
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construct of outcomes expectations to better assess the role this measure plays in
an individual’s occupational choice. Goal directed activity
According to Elliot, Sheldon, and Church (1997), this idea is defined as
“consciously articulated, personally relevant objectives” that provide a sense of
purpose and direction to one’s behavior (915). Bandura (1977), Deci and Ryan
(1987), Eccles and Wigfield (2002), and Schunk (1991) have examined
individual goal directed activity as an element of psychological theories aimed at
understanding human motivation and development.
Hechavaria et al. (2012) looked to develop a predictive model for the
likelihood of creation of a new firm among nascent entrepreneurs based upon
one’s goal orientation. Data for this study came from the Panel Study of
Entrepreneurial Dynamics I, a longitudinal study of over 31,000 individuals. A
sample of 830 nascent entrepreneurs was identified in this data set for this
longitudinal study. Results suggest formalized goal setting through tools such as
a business plan lead to greater probability of continuing a start-up venture over
abandoning the new business. The impact goal setting and action upon set goals
on entrepreneurial ventures is evidenced through this study. While this work
focused on emerging entrepreneurs, further research examination of the impact
education has on entrepreneurship development along goal directed activities
will provide additional insight into the importance entrepreneurs place upon the
use of goals.
A study by Culbertson et al; (2011) looked to assess the influence of goal
orientation and self-efficacy in predicting entrepreneurial and managerial
development. In this study, data were collected from 158 college students using
VandeWalle’s (1997) Goal Orientation Inventory. Results of Culbertson’s study
indicated learning goal orientation and performance-prove goal orientation
predicted entrepreneurial aspirations when coupled with high self-efficacy.
Evaluating entrepreneurial education
In their examination of existing entrepreneurship programs, the Kauffman
Foundation (2008) found the following: “Education in entrepreneurship must be
about the entrepreneur, the practitioner.” (8) In recommending avenues for
entrepreneurship education, the Kauffman Foundation study suggests
entrepreneurship is a natural fit in general education as it draws connections
between various academic disciplines and should be offered as a major or
concentration in order to build upon established bodies of research and practice
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and opportunities for co-curricular programs must also be available given the
applied nature of the subject.
Sanchez (2013) examined the effects of an entrepreneurship program
using a quasi-experimental control-group design in seeking to provide evidence
of the effects of an entrepreneurship education program on entrepreneurial
competencies and intention. Using a sample of students participating in an
entrepreneurship education program in Spain, Sanchez found post-test scores for
the constructs studied (self-efficacy, proactiveness, risk taking, and intention of
self- employment) are significantly higher when compared to the pre-test. This
result illustrates student development along these constructs following an
educational intervention. Findings from this study provide further evidence of
the impact of entrepreneurship education and offer the opportunity for future
research to continue to investigate educational development along these and
other constructs.
Gender
A review of the existing literature (Miner, 1993; Ardichvili et al., 2003;
Ciavarella et al., 2004; Zhao et al, 2005) indicates differences in the rate of
entrepreneurship between men and women, with women generally displaying
less entrepreneurial activity than men. In exploring the difference in motivation
and performance of female entrepreneurs, Klapper and Parker (2010) concluded
that external factors including business environment, access to finance, and
work-family conflicts only partially explain the gender gap in entrepreneurship.
Zhao and Seibert (2006) and Zhao et al. (2010) focused on investigating the
relationship between personality characteristics and entrepreneurship and
confirmed a significant correlation between personality characteristics and
entrepreneurial behavior.
Sowmya et al. (2010) investigated the attitudes of first year business
students at a university in the United Arab Emirates towards new venture
creation, and to derive recommendations on how to better promote and improve
entrepreneurship education as part of a business curriculum. A sample of 110
female business students in their first year responded to the same questionnaire.
Results from this study indicate positive effects of entrepreneurship education on
female students as entrepreneurial intentions increased after participation in a
course and self-efficacy towards starting a new venture was greater. This
research indicates a positive change in intentions and self-efficacy but the sample
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of only having female student participants limits the generalizability of these
results and does not permit comparison of the rate of change between male and
female students following an educational intervention. These studies illustrate
that gender should be considered in any study of entrepreneurial development.
Using the existing literature as the theoretical basis of developing the
present research, this article describes an effort to refine measurement scales and
research conducted to further investigate educational experiences on
entrepreneurship development. A full description of the framework and
methodology of the present research follows.
METHODOLOGY
Building upon the existing literature, the present research offers further
exploration into the examination of individual development along the constructs
of Entrepreneurial Intent, Entrepreneurship Self-Efficacy, Entrepreneurship
Outcome Expectations, and Goal Directed Activity from Social Cognitive Career
Theory. Following the belief that entrepreneurship skills can be developed, this
research contributes to the measurement of entrepreneurial development by
modifying current survey instruments. In addition, this study investigates
entrepreneurship educational impacts during and after one’s participation in an
educational intervention. Table 1 briefly outlines the three studies and their
respective samples used in this research. A more detailed explanation of the
methodology used in the present research follows.
Table 1
Present Research Studies
Study
Sample
One
Current Undergraduate Students Course
Co-curricular Activity
Existing Entrepreneurs
Formal Educational Experience
Alumni
Academic Major
Two
Three
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Fall 2014 Special Issue
149
Participants
A series of three studies were conducted to gather data for this research.
Participants were selected based either on their participation in specific courses,
on identified entrepreneurial experience, or behavior due to prior coursework.
Participation in each study was voluntary. Surveys were distributed to
participants electronically via web-based software.
Study One – Entrepreneurial Course
The first study involved current undergraduate student participants from a
mid-sized state supported institution in the mid-Atlantic region. Study one was
conducted to determine if change along dimensions of entrepreneurship
development occurs as the result of participating in an undergraduate
entrepreneurship course or participation in a student organization that focused on
entrepreneurship. Students in the treatment control completed either of two upper
level management elective courses, called Venture Creation or Entrepreneurship.
Students in the control group also majoring in management but not enrolled in
either of the two entrepreneurship courses. The survey was distributed to 66
students in the treatment group and 34 in the control group totaling 101 students
in Study One.
Study Two – Existing Entrepreneurs
A second study involving a group of identified established entrepreneurs
was conducted to investigate the role curricular experiences and co-curricular
involvement had upon participation in creating a start-up business. Data were
collected through a survey distributed to a sample of 440 entrepreneurs. The
sample of entrepreneurs identified to serve as participants in this study was based
upon one or more of the following:
 a regional small business development center’s client list,
 individuals recognized as leading entrepreneurs by a state-wide
economic development organization,
 participants in regional start-up programs, and
 the professional network of the researcher.
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In addition to the existing entrepreneurs participating in this study, a group of
professionals in non-entrepreneurial careers served a comparison group. The
comparison group consisted of individuals employed in non-business fields
including government and education. Participants in this study represent a broad
cross-section of economic sectors and entrepreneurs from companies of various
sizes, allowing for a generalizable result given the heterogeneous nature of the
sample.
Study Three – Entrepreneurship Coursework Alumni
The third study sought to gain understanding of the impact that education
has on entrepreneurship development on a group of graduates and their prior
entrepreneurial coursework. Two groups of alumni from a mid-Atlantic US
university were surveyed in this study: participants in the intervention group
having majored in Management, and participants in the control group majored in
applied science and Computer Science majors. The alumni from the
Management program completed a course exposing them to entrepreneurship
during their undergraduate experience. Those in the comparison group did not
take an entrepreneurial course. Alumni participants in this study graduated
between the years of 2005-2012 from a mid-sized state supported institution in
the mid-Atlantic region. The survey was distributed to 1,172 participants in the
Management alumni group and 490 in the non-Management group.
Gender differences were also explored in each of these studies to
investigate if differences existed between males and females in the study.
Instruments
The present research follows the framework established by the
Entrepreneur Education Program designed in 2009 by Winkel and
Vanevenhoven to gather longitudinal, data-driven insights into the impact of
entrepreneurship education on (1) the motivational processes underlying
students’ road to entrepreneurship, and (2) the process of identity transformation
from student to entrepreneur. Currently over 18,000 student responses
representing 400 universities in 70 countries have been received (Vanevenhoven,
2013). Grounded in Social Cognitive Career Theory, the Entrepreneurship
Education Project provided a framework upon which the research presented here
was modeled. Additionally, this research utilized elements of an instrument
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Fall 2014 Special Issue
151
created by the researchers associated with the Entrepreneurship Education
Project. The work of Winkel and Vanevenhoven begins to answer key questions
in measuring the impact of entrepreneurship education in a quantitative fashion
through a longitudinal approach. A survey used by Winkel and Vanevenhoven
(2010) in gathering data for the Entrepreneurship Education Project was
modified to create a survey instrument, the Entrepreneurship Development
Questionnaire (EDQ). The survey used by Winkel and Vanevenhoven was based
upon instruments designed by McGee et al. (2009), Thompson (2009), Krueger
(2000), Farmer, Yao and Kung-McIntyre (2011), and Carr and Sequeira (2007).
Permission to use and modify the Entrepreneurship Education Project Survey
was obtained by the researcher from the authors. The researchers modified and
implemented these previous instruments that will be referred to here as the
Entrepreneurial Development Questionnaire (EDQ) with four subscales of
Entrepreneurship Self-Efficacy, Entrepreneurial Intention, Entrepreneurship
Outcome Expectations, and Goal Directed Activity.
Entrepreneurship self-efficacy sub-scale
To measure Entrepreneurship Self-Efficacy, the researchers used 26items across three responses of no confidence, moderately confident and
completely confident. McGee (2009) reported a Cronbach’s alpha of internal
consistency to be .80 for the dimension of entrepreneurial self-efficacy. A threepoint Likert scale was chosen over the previously used 100-point basis to reduce
self-rater error. A measurement scale of 100 points is too broad and does not
allow for easily interpretable analysis, as participants may not respond
consistently over such a broad range of possible responses. Also, respondents
are more familiar and comfortable with Likert rating scales. A sample item for
this subscale is: “Come up with a new idea for a product or service on your
own.”
Entrepreneurial intent sub-scale
The investigator modified the 10-item entrepreneurial intention scale
designed by Thompson (2009) that was included in the omnibus
Entrepreneurship Education Project Survey. Reliability using Cronbach’s alpha
for the items developed by Thompson (2009) was found to be .89. The items
previously used were measured on a seven-point Likert scale ranging from very
untrue to very true. Building upon these items, the researcher added eight items
to further explore one’s development along the construct of entrepreneurial
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intention following an educational intervention. Additionally, previously used
items used absolute and less realistic terms such as never that could confusing to
participant’s response. Moreover, the number of Likert response options was
decreased from seven to four for two reasons. First, four is a more manageable
number than seven, which requires too fine discrimination for the untrained
respondent. Second, four options allow for more meaningful responses forward
directionality instead relying on a middle undecided option (DeMars and Erwin,
2004). The response options used were a four-point Likert scale of very untrue,
untrue, true and very true in order to explore how they engage in various
activities or have certain plans related to entrepreneurial intention. An example
of item for this subscale is: “Increase Personal Income.”
Entrepreneurship outcome expectations sub-scale
A third subscale of entrepreneurship development, Entrepreneurship
Outcome Expectations, was measured in this research also using items based on
a scale inspired by Krueger (2000). Krueger cited a Cronbach’s alpha of .80 for
these items. As the previous instrument contained only six items for this
measure, the survey was expanded to 29 items modified from a seven to four
point Likert. The present survey asked participants to rate their intention on a
four point Likert scale of not at all, very little, a good deal and very much, on the
extent to which they expected to achieve the following outcomes by starting their
own venture. One item for this subscale is: “Spend time learning about starting a
new venture.”
Goal directed activity sub-scale
Farmer, Yao and Kung-McIntyre (2011) measured the construct of Goal
Directed Activity using six-items on a five-point Likert scale with a Cronbach’s
alpha of .95. In an attempt to increase the strength of this subscale, researchers
added 20 items measured along a four-point Likert scale of strongly disagree,
disagree, agree and strongly agree. Participants were asked to respond to items
on this subscale such as: “I often think about becoming an entrepreneur.”
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153
Procedure
Study one – entrepreneurial course
A pre-test-post-test design was used to examine the impact of an
entrepreneurial course on entrepreneurship development during one academic
semester. The pre-test was distributed during the first week of classes during the
Fall 2013 Semester and a post-test was administered during the last week of the
fall term. Gender information was also requested to further explore differences
along the construct of entrepreneurship development between male and female
students.
Using the EDQ, Study One seeks to investigate the following hypotheses:
H1
After participating in an entrepreneurial education course over one
academic semester, men and women will have improved Entrepreneurship SelfEfficacy, Entrepreneurial Intent, Entrepreneurship Outcome Expectations and
Entrepreneurship Goal-Directed Activity with female students will demonstrate
greater average scores.
Study two – existing entrepreneurs
H2
Established entrepreneurs will demonstrate greater average scores on
Entrepreneurship Self-Efficacy, Entrepreneurial Intent, Entrepreneurship
Outcome Expectations and Goal Directed Activity with female participants
scoring higher than males.
Study three – entrepreneurship coursework alumni
H3
Male and female alumni with a degree in Management will demonstrate
greater average scores on Entrepreneurial Self-Efficacy, Entrepreneurial Intent,
Entrepreneurship Outcome Expectations, and Entrepreneurship Goal-Directed
Activity than male and female non-Management alumni and will differ by
gender.
RESULTS
The researchers administered the EDQ to 520 individuals over three
separate studies as a means of investigating the impact of post-secondary
education on entrepreneurial development. A summary of participants can be
found in Table 2.
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Table 2
Frequency of Participants by Study and Gender
Treatment
Control
Study
One
Two
Three
Male
29
120
127
Female
17
34
68
N
46
154
125
Male
14
74
49
Female
5
32
21
n
19
106
70
Total N
65
260
195
Reliability of the Revised EDQ
The initial analysis of the EDQ was to improve the reliability or internal
consistency of the subscales of Entrepreneurial Intent, Entrepreneurship SelfEfficacy, Entrepreneurship Outcome Expectations, and Goal Directed. See
Table 3 for the former and revised reliability estimates of the EDQ subscales.
Cronbach’s alpha coefficients of internal consistency were calculated for the four
subscales of the revised instrument: Entrepreneurial Intent with 18 items (α =
.93), Entrepreneurship Self-Efficacy with 26 items (α = .93), Entrepreneurship
Outcome Expectations with 29 items (α = .93), and Goal Directed Activity with
20 items (α = .95). The inclusion of these new items improved the reliability of
the prior instrument, and the revised EDQ will be used in the three validity
studies that follow.
Table 3
Summary of Reliability Coefficients of Internal Consistency for Prior
Instruments and the Entrepreneurship Development Questionnaire
Prior
Revised EDQ
Subscale
Instrument
(N = 520)
Entrepreneurial Intent
Entrepreneurship SelfEfficacy
Entrepreneurship Outcome
Expectations
Goal Directed Activity
Journal of Business & Entrepreneurship
.89
(Thompson, 2009)
.80
(McGee, 2009)
.80
(Krueger, 2000)
.95
(Farmer and KungMcIntyre, 2011)
Fall 2014 Special Issue
.93
.93
.93
.95
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Study one – entrepreneurial course
The EDQ was used to investigate the impact that participation in an
undergraduate course has on students at two points in time: at the beginning and
end of one academic semester.
Three students dropped the course between administrations of the survey
and one case was deleted as an outlier for a total response of 46. A sample of 19
participants that were not enrolled in the entrepreneurship course served as a
control group. Of the total 65 participant, 43 males and 22 females participated in
this study. Descriptive statistics for the independent variables by each dependent
variable used in this study can be found in Tables 4-7.
Table 4
Means and Standard Deviations of Pre-test and Post-test Scores on the
Subscale of Entrepreneurial Intent
Entrepreneurial
Pre-test
Post-test
Intent
(N = 65)
Coursea
(n = 46)
Male
(n = 29)
Female
(n = 17)
a
Entrepreneurial Course
156
M
(SD)
48.48
(11.83)
45.64
(10.13)
No
Course
(n = 19)
M
(SD)
46.35
(8.41)
39.60
(6.18)
Fall 2014 Special Issue
Course a
(n = 46)
No Course
(n = 19)
M
(SD)
52.93
(12.78)
51.18
(11.67)
M
(SD)
40.21
(8.17)
37.80
(9.28)
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Table 5
Means and Standard Deviations of Pre-test and Post-test Scores on the
Subscales of Entrepreneurship Self-Efficacy
Entrepreneurship
Pre-test
Post-test
Self-Efficacy
(N = 65)
Male
(n = 29)
Female
(n = 17)
a
Entrepreneurial Course
Course a
(n = 46)
M
(SD)
63.10
(10.67)
57.88
(10.97)
No Course
(n = 19)
M
(SD)
61.42
(10.85)
56.80
(7.62)
Course a
(n = 46)
M
(SD)
68.34
(9.60)
69.11
(10.40)
No Course
(n = 19)
M
(SD)
58.21
(8.65)
55.40
(9.34)
Table 6
Means and Standard Deviations of Pre-test and Post-test Scores on the
Subscales of Entrepreneurship Outcome Expectations
Entrepreneurship
Pre-test
Post-test
Outcome
Expectations
(N = 65)
Course a
(n = 46)
Male
(n = 29)
Female
(n = 17)
a
Entrepreneurial Course
M
(SD)
85.72
(20.22)
81.05
(14.92)
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No
Course
(n = 19)
M
(SD)
86.85
(10.13)
82.20
(6.37)
Fall 2014 Special Issue
Course a
(n = 46)
No Course
(n = 19)
M
(SD)
92.41
(16.25)
87.35
(11.34)
M
(SD)
79.57
(12.05)
76.60
(24.86)
157
Table 7
Means and Standard Deviations of Pre-test and Post-test Scores on the
Subscale of Goal Directed Activity
Goal Directed Activity
Pre-test
Post-test
(N = 65)
Course a
(n = 46)
Male
(n = 7)
Female
(n = 16)
a
Entrepreneurial Course
M
(SD)
56.58
(13.95)
53.47
(11.17)
No
Course
(n = 19)
M
(SD)
54.00
(13.94)
46.00
(10.97)
Course a
(n = 46)
M
(SD)
60.27
(13.95)
61.41
(8.95)
No Course
(n = 19)
M
(SD)
51.21
(14.54)
45.20
(11.56)
A within-subjects multivariate analysis of variance (MANOVA) was
used to analyze data collected in Study One. To test the two hypotheses set forth
in the methodology section for Study One, scores from the pre and post-test (N =
65) administrations of the EDQ were used to explore differences over time
between participants who had completed an entrepreneurial course (n = 46)
versus a control group of students who had not taken a course (n = 19).
There were no univariate or multivariate within-cell outliers at p < .001.
The assumption of homogeneity was met with Box’s M = 97.17, p > .05 which
was interpreted as non-significant. Mauchly’s Test of Sphericity was statistically
significant, χ2 (27) = .05, p < .001, indicating the assumption of sphericity had
been violated. To address this violation, Greenhouse-Gasser correction was
used, ε = .49. The assumption of equal variance was met through a nonstatistically significant Levene’s test for each of the dependent variables:
Entrepreneurial Intent (F = .79, p > .05), Entrepreneurship Self-Efficacy (F =
.28, p > .05), Entrepreneurship Outcome Expectations (F = 2.34, p > .05), and
Goal Directed Activity (F = 1.37, p > .05). Table 8 provides a summary of the
MANOVA with follow-up ANOVA results for statistically significant main
effects.
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Table 8
Multivariate Analysis of Variance of Group, Gender and Time on the
Measures of Entrepreneurial Intent, Entrepreneurship Self-Efficacy,
Entrepreneurship Outcome Expectations and Goal Directed Activity with
Analysis of Variance Follow-up
df
SSQ
MS
F
η2
p
Time
3 73335.41 10476.48 87.26 .58 .001*
Time*Group
3 2440.38 705.67
2.90
.04 .02***
Entrepreneurial Intent
1 1141.91 1141.91
6.05
.09 .01**
Entrepreneurship Self1 1672.31 1672.31
10.38 .15 .01**
Efficacy
Entrepreneurship
1 2059.00 2059.00
4.18
.06 .04***
Outcome Expectations
Goal Directed Activity
1 704.47
704.47
2.41
.03 .12
Time*Gender
3 196.65
56.86
.23
.01 .89
Time*Group*Gender
3 195.89
56.64
.23
.01 .89
*p < .001, ** p < .01, ***p < .05
In the first hypothesis, the researcher tested to see if participation in an
entrepreneurial education course over one academic semester would positively
differentially impact men or women in the course with greater scores on the
subscales of Entrepreneurial Intent, Entrepreneurship Self-Efficacy,
Entrepreneurship Outcome Expectations, and Goal-Directed Activity than those
in the control group.
Testing this hypothesis using the Greenhouse-Gasser correction as the
MANOVA statistic, F (3,1) = 2.90, p < .05, η2 = .04, a statistically significant
interaction was found for time and group indicating participation in a class
impacted an individual’s score over the course of an educational experience. No
differences were found for men or women in the course or no course over time.
In follow- up ANOVAs for the interaction of group membership by time,
statistically significant effects were found for three of the DVs: Entrepreneurial
Intent F (1, 61) = 6.05, p < .01, η2 = .09, Entrepreneurship Self-Efficacy F (1, 61)
= 10.38, p < .01, η2 = .15, and Entrepreneurship Outcome Expectations F (1, 61)
= 4.18, p < .05, η2 = .06. A statistically significant main effect was found using
Greenhouse-Gasser correction as the MANOVA statistic, F (3,1) = 87.26, p <
.001, η2 = .58, for time indicating a difference between scores on the pretest and
posttest. The results reflected a modest impact of time on the combined DVs,
partial η2 = .58. The results of the within-subjects MANOVA supported the
Journal of Business & Entrepreneurship
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159
researcher’s hypothesis that those who participated in the course scored higher
on the four areas measured after this entrepreneurship education experience.
Study two - existing entrepreneurs
Data gathered through the administration of the EDQ to 154 existing
entrepreneurs and 106 non-entrepreneurs was used to test three hypotheses in
Study Two (N = 260). Using a between-subjects multivariate analysis of
variance, the researcher explored if differences between existing male and female
entrepreneurs and non-entrepreneurs existed on the subscales of Entrepreneurial
Intent, Entrepreneurship Self-Efficacy, and Entrepreneurship Outcome
Expectations.
There were no univariate or multivariate within-cell outliers at p < .001.
The assumption of homogeneity was met with Box’s M = 105.40, p > .05 which
was interpreted as non-significant. The assumption of equal variance was met
through a non-statistically significant Levene’s test for each of the dependent
variables, Entrepreneurial Intent (F = 3.10, p >.05), Entrepreneurship SelfEfficacy (F = 1.59, p > .05), and Entrepreneurship Outcome Expectations (F =
1.99, p > .05). Means and standard deviations are reported for combined
independent variables by each dependent variable in Table 9 (Entrepreneurial
Intent), Table 10 (Entrepreneurship Self-Efficacy), and Table 11
(Entrepreneurship Outcome Expectation).
Table 9
Means and Standard Deviations for Group by Gender for Entrepreneurial
Intent
Entrepreneurial Intent
Existing
Non-Entrepreneurs
Entrepreneurs
(n = 106)
(n = 154)
M
M
(SD)
(SD)
Male
45.19
37.66
(n = 194)
(6.67)
(10.16)
Female
44.08
33.03
(n = 66)
(8.82)
(10.45)
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Table 10
Means and Standard Deviations for Group by Gender for Entrepreneurship
Self-Efficacy
Entrepreneurship SelfExisting
Non-Entrepreneurs
Efficacy
Entrepreneurs
(n = 106)
(n = 154)
M
M
(SD)
(SD)
Male
70.09
58.72
(n = 194)
(7.29)
(9.29)
Female
70.58
56.53
(n = 66)
(9.42)
(9.21)
Table 11
Means and Standard Deviations for Group by Gender for Entrepreneurship
Outcome Expectations
Entrepreneurship Outcome
Existing
Non-Entrepreneurs
Expectations
Entrepreneurs
(n = 106)
(n = 154)
M
M
(SD)
(SD)
Male
84.67
80.29
(n = 194)
(13.29)
(15.77)
Female
77.91
72.90
(n = 66)
(11.54)
(15.87)
A summary of MANOVA results along with follow-up ANOVA results
for statistically significant effects can be found in Table 12. These results are
explored further for hypotheses four and five as follows.
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Table 12
Multivariate Analysis of Variance of Group and Gender on the Measures of
Entrepreneurial Intent, Entrepreneurship Self-Efficacy and
Entrepreneurship Outcome Expectations with Analysis of Variance Followup
Scale
N=
df
SSQ
MS
F
η2
p
260
Group
3,248
45.60
.35
.001*
Entrepreneurial
1
4186.92
4186.92
57.02
.18
.001*
Intent
Entrepreneurship
1
7830.96
7830.96
110.15 .30
.001*
Self-Efficacy
Entrepreneurship
1
1067.09
1067.09
5.31
.02
.02
Outcome
Expectations
Gender
3,254
4.62
.04
.05***
Entrepreneurial
1
398.53
398.53
5.42
.02
.02
Intent
Entrepreneurship
1
35.10
35.10
.49
.01
.48
Self-Efficacy
Entrepreneurship
1
2428.15
2428.15
12.09
.04
.001*
Outcome
Expectations
Group*Gender
3,254
.99
.01
.39
*p < .001, ** p < .01, ***p < .05
In the second hypothesis, the researcher hypothesized that established
male or female entrepreneurs would demonstrate greater scores for
Entrepreneurial Intent, Entrepreneurship Self-Efficacy, and Entrepreneurship
Outcome Expectations than the control group. With the use of Roy’s Largest
Root, a statistically significant main effect was found for group membership, F
(3, 248) = 45.60, p < .001, η2 = .35. In a follow-up ANOVA, statisticallysignificant effects for the group membership (existing entrepreneur or nonentrepreneur) variable were found for two of the DVs: Entrepreneurial Intent, F
(3,254)= 57.02, p < .001, and Entrepreneurship Self-Efficacy F (3,254) = 110.15,
p < .001. These results confirm the researcher’s hypothesis of a difference
between the groups participating in this study.
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Study three - entrepreneurship coursework alumni
In Study Three, the researcher received responses to the EDQ from 195
alumni from a mid-sized state supported institution in the mid-Atlantic region of
the US. 125 were former Management majors who had taken an entrepreneurship
course, 70 were applied science and a computer science majors.
There were no univariate or multivariate within-cell outliers at p < .001.
The assumption of homogeneity was met with Box’s M = 24.77, p > .05 which
was interpreted as non-significant. The assumption of equal variance was met
through a non-statistically significant Levene’s test for each of the dependent
variables: Entrepreneurial Intent (F = .60, p > .05), Entrepreneurship SelfEfficacy (F = 1.74, p > .05), and Entrepreneurship Outcome Expectations (F =
2.12, p > .05). Descriptive statistics including means and standard deviations are
reported for the independent variables by each dependent variable in Table 13
(Entrepreneurial Intent),
Table 14 (Entrepreneurship Self-Efficacy), and
Table 15 (Entrepreneurship Outcome Expectation) for the scores for Study
Three.
Table 13
Means and Standard Deviations for Group, Gender and Extracurricular
Activity for Entrepreneurial Intent
Entrepreneurial
Management Alumni
Non-Management Alumni
Intent
(n = 125)
(n = 70)
M
M
(SD)
(SD)
Male
36.33
36.55
(n = 127)
(9.94)
(10.53)
Female
32.19
31.61
(n = 68)
(10.52)
(12.16)
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Table 14
Means and Standard Deviations for Group, Gender and Extracurricular
Activity for Entrepreneurship Self-Efficacy
Entrepreneurship
Management Alumni
Non-Management Alumni
Self-Efficacy
(n = 125)
(n = 70)
M
M
(SD)
(SD)
Male
58.75
57.83
(n = 127)
(10.05)
(9.19)
Female
54.31
54.47
(n = 68)
(12.60)
(9.60)
Table 15
Means and Standard Deviations for Group, Gender and Extracurricular
Activity for Entrepreneurship Outcome Expectations
Entrepreneurship
Management Alumni
Non-Management Alumni
Outcome
(n = 125)
(n = 70)
Expectations
Male
(n = 127)
Female
(n = 68)
M
(SD)
76.65
(15.58)
68.36
(12.52)
M
(SD)
77.65
(16.45)
66.85
(15.88)
In the third hypothesis, the researcher hypothesized that alumni that
participated in the entrepreneurship course would demonstrate higher scores by
gender on Entrepreneurial Intent, Entrepreneurial Self-Efficacy, and
Entrepreneurship Outcome Expectations. A between-subjects multivariate
analysis of variance was performed on three dependent variables: Entrepreneurial
Intent, Entrepreneurship Self Efficacy, and Entrepreneurship Outcome
Expectations.
No statistically-significant interaction effect was found of prior
entrepreneurial coursework versus no coursework by gender, as Roy’s Largest
Root was F (3, 189) = .24, p > .05, so no follow-up was needed. A statistically
significant main effect was found for gender as Roy’s Largest Root was F
(3,189) = 5.33, p < .001. In a follow-up ANOVA for gender, statistically
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Fall 2014 Special Issue
Journal of Business & Entrepreneurship
significant effects were found for the three DVs: Entrepreneurial Intent F (3,189)
= 7.33, p < .001, Entrepreneurship Self-Efficacy F (3,189) = 5.41, p < .01, and
Entrepreneurship Outcome Expectations F (3,189) = 15.50, p < .001. A
summary of MANOVA results can be found in Table 16. Males in this sample
scored higher along the subscales than females.
Table 16
Multivariate Analysis of Variance of Group and Gender on the Measures of
Entrepreneurial Intent, Entrepreneurship Self-Efficacy and
Entrepreneurship Outcome Expectations with Analysis of Variance Followup
df
SSQ
3,189
3,189
1
806.21
Group
Gender
Entrepreneurial
Intent
Entrepreneurship
1
595.40
Self-Efficacy
Entrepreneurship
1
3567.75
Outcome
Expectations
Group*Gender
3,189
*p < .001, **p < .01, ***p < .05
η2
MS
F
806.21
.01
5.33
7.33
0
.07
.03
.99
.001*
.01**
595.40
5.41
.02
.02***
3567.75
15.50
.07
.001*
.24
.01
.86
p
DISCUSSION
The issue of whether entrepreneurial development could be learned for
the main focus of this study. The concept of entrepreneurial development was
refined, and existing instruments in the field of entrepreneurship were revised to
improve their reliability. Furthermore, three validity studies were conducted with
three samples of students who took or did not take an entrepreneurial course, of
entrepreneurs versus entrepreneurs in the business, and of college alumni who
had or did not take prior college coursework in entrepreneurship.
Support for the Revised EDQ showed that students completing an
entrepreneurship course scored on the average in three subscales of
Entrepreneurial Intent, Entrepreneurship Self-Efficacy, and Entrepreneurship
Outcome Expectations than students not completing an entrepreneurship course.
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165
No differences occurred between male and females. These results represent a
preliminary finding of the positive impact of an educational experience on
entrepreneurship development. The positive impact of a curricular experience on
entrepreneurship development along the subscales exhibited through Study One
of the present research supports the claims in the literature (Dickson et al, 2006)
that entrepreneurship can be developed through education.
Although the researcher’s other hypothesis was not supported by the data,
the testing and measurement of these constructs offers additional research into
other factors that may impact development.
As various policy and business leaders have called for increasing the
number of entrepreneurs in the workforce, the finding in the present research
offers evidence that post-secondary education can positively impact an
individual’s entrepreneurship development and potentially foster an individual’s
interest in engaging in entrepreneurship following a formal educational
intervention focused on entrepreneurship. Continued research into successful
models of entrepreneurship education is needed, but preliminary evidence
suggests that development can occur as a result of formal educational
experiences. However, additional study is needed to determine the nature of
educational experiences because not all institution’s entrepreneurial courses are
the same.
Existing entrepreneurs surveyed scored higher on the average in the
Revised EDQ than a group of non-entrepreneurs on the subscales of
Entrepreneurial Intent, Entrepreneurship Self-Efficacy, and Entrepreneurship
Outcome Expectations, regardless of whether they were men or women. These
findings support the researcher’s expectation that existing entrepreneurs would
have greater intention to engage in entrepreneurial activities and higher selfefficacy than non-entrepreneurs. Drawing a conclusion from these results, one
can conceive that existing entrepreneurs have identified strengths along
Entrepreneurial Intent and Entrepreneurship Self-Efficacy as reflected by the
differing average scores between entrepreneurs and non-entrepreneurs. One
potential action from this finding would be to expand educational programs to
focus on these areas as a means of developing future entrepreneurs.
With this finding, further research is needed into entrepreneurship
educational experiences that can be shaped to prepare females to pursue
entrepreneurship. As entrepreneurship is commonly held as a male-dominated
field, the results from this study do not differ from current economic conditions
but suggest the subscales of Entrepreneurial Intent, Entrepreneurship Self166
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Journal of Business & Entrepreneurship
Efficacy, and Entrepreneurship Outcome Expectations are areas upon which to
focus educational programs as statistically-significant differences were not found
by gender in this sample. Additional investigation of these differences on other
subscales would benefit the body of knowledge and potentially influence
entrepreneurship education programs by expanding curriculum to increase
female achievement across these subscales as a means of encouraging greater
engagement in entrepreneurial activities by females.
Participants in this study represented one of two groups of college
graduates: those alumni of an undergraduate Management program who had
taken entrepreneurial college coursework and a second alumni group consisting
of graduates from an applied science and a computer science program with no
prior entrepreneurial coursework. The former management majors with prior
entrepreneurial coursework had higher average scores on Entrepreneurial Intent,
Entrepreneurship Self-Efficacy, and Entrepreneurship Outcome Expectations
than the comparison group. Males in this sample scored higher along the
subscales than females.
The alumni participants in the treatment group were all exposed to
entrepreneurship material as part of a course, but all had not participated in a
designated entrepreneurship course. Although members of the group of nonentrepreneurs were not enrolled in the same course as the treatment group, the
nature of careers pursued by alumni of the applied science and computer science
programs may lead to pursuit of entrepreneurial endeavors. The differences in
course content and career paths of participants in the sample make it difficult to
generalize the results of this study, as more in-depth research is needed with a
sample consisting of graduates of a focused entrepreneurship education program.
However, findings from this study do hold that gender differences exist in this
sample, indicating an opportunity to offer educational experiences focused on
females designed to increase their development along the measures of the
Revised EDQ.
In summary, reliability and validity evidence for the Revised EDQ shows
potential as a viable evaluation tool to measure entrepreneurial development.
Internal consistency of the instrument is higher than prior efforts by multiple
authors. In addition, the instrument is sensitive: to college coursework in
entrepreneurial education expected to produce change; to differentiating between
existing entrepreneurs in the field versus non-entrepreneurs; and to
differentiation of college graduates who had taken entrepreneurial coursework
years earlier during college. This evidence meets at least four long-standing
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Fall 2014 Special Issue
167
definitions of validity: 1. evidence based on test content – test items were
generated by multiple experts in the field; 2. evidence based on internal structure
as determined by internal consistency; 3. external evidence of the EDQ’s ability
to discriminate between students receiving or not receiving an educational
intervention; and 4. evidence based on generalizability of the EDQ to
differentiate between existing entrepreneurs and non-entrepreurial business
people (American Educational Research Association, American Psychological
Association, & National Council on Measurement in Education, 1999; Messick,
1995). Future studies should study further internal structures using, for instance,
factor analysis, and compare Revised EDQ scores with other scores on similar
and dissimilar instruments.
Limitations
As any study, the present research had several limitations. Data were
collected in Study One from students from a single university with a small
number of participants in an entrepreneurship education experience. This sample
produced useful results for this study, but additional participants from other
universities would allow for greater generalization to a broader population.
Future research would benefit from a survey of students from multiple
institutions, which would allow for comparison across universities and a larger
sample upon which to draw students with entrepreneurship education
experiences including extra-curricular activities.
Study Two utilized a sample drawn from a pool of existing entrepreneurs
available to the researcher through professional contacts. This sample of
convenience can be expanded to include a larger number of existing
entrepreneurs along with a more random sample of individuals in the group of
non-entrepreneurs. This study would generate a more diverse sample upon
which conclusions could be drawn and comparisons made. Geographic diversity
of the sample could also be improved, as a majority of the participants were
drawn from one region of the country. The inclusion of additional geographic
locations would enhance the perspectives and experiences in the study.
Finally, Study Three sampled alumni from a single institution. An
expanded sample from multiple universities would enhance future research by
enlarging the pool of participants and affording the opportunity to compare
results between programs. Participants from a program with a specific focus on
entrepreneurship education would offer a more direct perspective on educational
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impacts on entrepreneurship development. Additionally, alumni from other
academic majors could serve as a control group, which may offer other analysis
from contrasts between groups.
In addition to limitations in the samples used across the three studies
comprising the present research, the instrument used was modified based upon
prior research and required reliability and validity analysis. This research sought
to further develop the survey instrument and measurement scales through the use
of this survey. Future application of this instrument is needed to further assess
its use in measuring entrepreneurship development. In additional use with larger
samples, the instrument can continue to be refined to best gather data from
students, entrepreneurs and alumni.
CONCLUSION
Entrepreneurship has been a focal point of economic development
worldwide in the popular as well as academic press. The attention given to
entrepreneurship across a variety of media outlets has produced numerous
definitions of the term and strategies to increase the number of entrepreneurs.
The present research offers a definition of entrepreneurship as an “action based
process of creating a venture, which provides market value” upon which to
investigate educational interventions designed to further an individual’s
Entrepreneurship Development. It was the intent of the researchers to clarify an
operational definition upon which the impact of educational experiences could be
measured. This definition served as the basis upon which refinement of
psychometric analyses using classical test score theory was conducted in the
present research. This study offers evidence that entrepreneurship development
can be reliably measured and produced valid interpretations in this study in
typical uses for other institutions.
Through the enhancement of the survey instrument in these three studies,
the current research contributes to the existing body of knowledge of
entrepreneurial education in meaningful and practical ways. Calls for greater
numbers of entrepreneurs have been made by policy leaders, many of which look
to post-secondary education as a means of producing the necessary workforce.
Previous research examined the role that the field of higher education can take in
addressing these calls, and the present research suggests that higher education
can make an impact by offering educational opportunities for students in the area
of entrepreneurship. Results from Study One include the support of the first
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169
hypothesis, indicating that participation in an entrepreneurship course positively
impacts an individual’s development along the constructs measured by the
instrument when compared to a control group not enrolled in a course.
The second study illustrated that existing entrepreneurs scored higher on
average on the measures of Entrepreneurial Intent, Entrepreneurship SelfEfficacy, and Entrepreneurship Outcome Expectations, indicating current
entrepreneurs possess strengths in these areas. Additional work is needed to
investigate how entrepreneurs with educational experiences are translating these
strengths into practice.
Study Three did not produce statistically-significant results by group or
gender upon which to generalize differences between the alumni participants.
Although these findings were not statistically-significant, opportunities exist for
further exploration into impacts of entrepreneurship education beyond
graduation.
Gender served as an independent variable across all three studies in this
research and produced consistent results of the differences between males and
females on participant scores along the subscales measured. In all three studies,
no statistically significant difference was found between males and females in
the sample. These findings can be explored further using other educational
interventions to investigate if the specific educational experience could impact
differences in scores or what other factors contribute may generate differences
between males and females. From these results, the possibility of expanding
educational programs focusing on the entrepreneurship development of females
as a means of increasing the number of female entrepreneurs exists. Similar
efforts have been made in fields such as science, engineering and mathematics to
address gender differences in the professions. Further research into educational
impacts on female students in the area of entrepreneurship is needed to refine
curricular approaches in addressing gender differences. As the dataset used in
this research includes a diverse set of participants at various points in their
careers along a common set of measures, future research can build upon the
study of gender differences to investigate other educational interventions and
measures of entrepreneurship development.
The data gathered through the survey of the existing entrepreneurs in this
study offers a rich source to further explore educational impacts at various points
in an individual’s entrepreneurial pursuits. The researchers worked with the
leadership of a local small business development center in surveying existing
entrepreneurs and will be sharing the results of this research with those involved
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Journal of Business & Entrepreneurship
in developing educational programs offered through the small business
development center as a means of creating educational experiences that would
benefit entrepreneurs currently in the workforce. Additional data can be
collected from entrepreneurs participating in these future educational programs
and be further analyzed to continue studying impacts of education on an
individual’s entrepreneurship development.
Scholars and practitioners have debated if entrepreneurship could be
defined and developed. The research began with this question and offered a
refined definition in an attempt to clarify a collection of complex definitions
present in the literature. From this definition, the researcher refined a
measurement instrument and analyzed data to investigate characteristics of
entrepreneurship development. Based upon the findings of this research,
entrepreneurship development can be advanced, and post-secondary education
can offer experiences to build talent in this area in an attempt to help address
workforce needs.
Keywords
Entrepreneurship, education, instrument development, social cognitive career
theory
Acknowledgement
This work would not have been possible without the assistance of Drs. Winkel
and Vanevenhoven through their willingness to allow the researchers access to
the survey instrument utilized in the Entrepreneur Education Program.
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A MODEL FOR EXPERIENTIAL ENTREPRENEURSHIP
EDUCATION
Thomas G. Pittz
New Mexico State University
ABSTRACT
Courses in entrepreneurship are vital components of a business school
curriculum and typically contain experiential learning techniques in concert with
traditional teaching methods. Empirical studies of the effectiveness of these
entrepreneurship courses at developing future entrepreneurs, however, have
found mixed results. This paper makes the case that two important aspects of
experiential learning, a whole person focus and contact with the environment, are
too often neglected in the pedagogy. Incorporating these two oft-neglected
aspects results in a five-step model of experiential entrepreneurship education
that has shown promise in developing future successful entrepreneurs.
INTRODUCTION
Entrepreneurial organizations are understood to be important actors in
capitalist economies. They play a vital role in the renewal process that defines
market economies and are dynamic organizations that drive innovation, change,
and productivity growth. Van Praag and Versloot (2007) identify four economic
benefits of entrepreneurship: job creation, innovation, productivity and growth,
and the potential to increase the “utility” of people by increasing satisfaction or
income. The Small Business Administration (SBA) calls entrepreneurship the
“social glue” that binds together both high-tech and “main street” activities
(SBA, 1998). Entrepreneurial organizations are about prospects for the future,
not about the inheritance of the past (Kuratko & Hodgetts, 2004). They represent
hope, equal opportunity, and upward mobility.
Given the widely accepted notion that entrepreneurial ventures are the
key to innovation, productivity, and effective competition (Plaschka & Welsch,
1990), the question is whether entrepreneurship can be taught. Most business
educators and professionals have evolved beyond the idea that entrepreneurs are
born, not made. Peter Drucker, recognized as one of today’s leading
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179
management thinkers, has said, "The entrepreneurial mystique? It's not magic,
it's not mysterious, and it has nothing to do with the genes. It's a discipline.
And, like any discipline, it can be learned" (Drucker, 1985, p. 18). Additional
support for this view comes from a 10-year (1985 to 1994) literature review of
enterprise, entrepreneurship, and small business management education that
reported, "most of the empirical studies surveyed indicated that entrepreneurship
can be taught, or at least encouraged, by, entrepreneurship education" (Gorman,
Hanlon, & King, 1997, p. 63).
If entrepreneurs can be taught, does the current iteration of
entrepreneurial education really work to create new business ventures? The
answer to this question is mixed. For instance, a recent review and
methodological critique of the empirical literature regarding the effects of
entrepreneurship education demonstrated a variety of methodological
weaknesses in current research that cast doubts on whether entrepreneurial
education can, in fact, produce entrepreneurship (Rideout & Gray, 2013).
Another common criticism is that research in the field of entrepreneurship has
tended to run ahead of theoretical developments (Henry, et al., 2005). On the
other hand, recent studies have also found a significant relationship between
entrepreneurial education and both human capital assets and entrepreneurship
outcomes (Martin, et al., 2013). One important aspect in common with most
empirical studies of entrepreneurial education is the finding that pedagogical
technique matters.
Ronstadt (1987) proposed that entrepreneurial programs should be
designed so that potential entrepreneurs become aware of barriers to initiating
their entrepreneurial careers and devise ways to overcome them. He proposed a
continuum that suggested that success in entrepreneurship is dependent not only
on personal knowledge but on the network of individuals with whom an
entrepreneur is connected. He contended that an effective entrepreneurship
education program should show students both how to behave entrepreneurially
and should introduce them to people who might be able to facilitate their success
(Ronstadt, 1987).
In one of the most comprehensive analyses to date on entrepreneurship
education, Solomon, et al., (2002) stated: “entrepreneurial education must
include skill-building courses in negotiation, leadership, new product
development, creative thinking, and exposure to technological innovation
(McMullan & Long, 1987: Vesper & McMullen, 1988). Other areas identified as
important for entrepreneurial education included awareness of entrepreneur
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career options (Donckels, 1991; Hills, 1988), sources of venture capital (Vesper
& McMullen, 1988; Zeithaml & Rice, 1987), idea protection (Vesper &
McMullen, 1988), ambiguity tolerance (Ronstadt, 1987), the characteristics that
define the entrepreneurial personality Hood & Young, 1993; Scott & Twomey,
1998), and the challenges associated with each stage of venture development
(McMullan & Long, 1987; Plaschka & Welsch, 1990).” More importantly,
Solomon et al., (2002) found that the use of experiential learning is widespread
and diverse in its application from the literature. This paper builds on the
findings of Solomon et al., (2002) and suggests that a refocusing on two
particular aspects of experiential learning, contact with the environment and a
whole person approach, are key to an entrepreneurial education program that
achieves greater success in spawning new venture creation.
Experiential Learning
The effectiveness of experiential learning can be expressed through the
following quote attributed to Confucius, “I hear and I forget. I see and I
remember. I do and I understand.” John Dewey discussed “learning by doing”
(Dewey, 1915) and Wolfe and Byrne used the term “experience-based learning”
(Wolfe & Byrne, 1975). The AACSB Task Force has further defined applied
experiential learning as “a business curriculum-related endeavor, which is
interactive (other than between teacher and pupil) and is characterized by
variability and uncertainty” (Carter, et al., 1986, p. 3). Contact with the
environment is another key component of the AACSB’s conception of
experiential education.
A structure of experiential learning proposed by Wolfe and Byrne (1975)
includes four phases: design, conduct, evaluation, and feedback. The design
phase sets the stage for the experience and includes outlining learning objectives
and selecting activities in concert with the students. This phase is necessary for
the applied aspect of experiential learning so that the student can view the
experience in proper context. The conduct phase involves controlling the design
so that the experience can be structured and closely monitored. The evaluation
phase is important to involve both the student and instructor regarding what has
been learned from the experience. Finally, the feedback phase is an ongoing
process that includes fostering positive aspects of the experience while still
allowing for the opportunity for students to fail.
While Wolfe and Byrne’s process remains useful for structuring an
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entrepreneurial course, true experiential learning should not be described simply
as a cognitive endeavor. Perhaps the most widely cited definition of experiential
learning states, “Experiential learning exists when a personally responsible
participant cognitively, affectively, and behaviorally processes knowledge, skills
and/or attitudes in a learning situation characterized by a high level of active
involvement” (Hoover & Whitehead, 1975, p. 25). Embracing this idea of a
multi-layered connection with the material is a particularly important lesson for
entrepreneurship education.
Given the problem-solving orientation of most management education,
there is a natural tendency among business faculty to emphasize the cognitive
dimensions of the subject matter. Considering the importance of interpersonal
skills, determination, personal risk tolerance, and lifestyle choices to potential
entrepreneurs, a whole person emphasis is paramount. Experiential learning
approaches (as opposed to traditional lecture and class discussion formats) are
extremely useful in identifying and growing personality traits that enhance
entrepreneurial success.
In order to foster a whole person approach to education, entrepreneurship
teachers must be more than cheerleaders. We must be more than naysayers. We
must endeavor to recognize the unique characteristics of our students and tailor
our pedagogy to meet individual needs. Is the student an unabashed optimist
with utter confidence in his/her idea? The teacher’s goal in this case could be a
realistic discussion of potential obstacles, risks, and challenges without
diminishing the enthusiasm of the budding entrepreneur. Is the student risk
averse? The teacher’s goal is very different in this case since the student likely
possesses a sober view of the risk/reward criteria. Encouragement coupled with
a thorough overview of the business prospects and likely obstacles is a more
appropriate tact.
Entrepreneurship educators must also attempt to introduce students to the
entrepreneurial environment in which they will operate. Contact with the
ecosystem is missing in traditional teaching methods and is a critical component
of effective entrepreneurship education since “real world” experience informs
budding entrepreneurs about their likely responses and reactions to
environmental cues. This “real world” contact is difficult to duplicate with
simulation games, role-playing exercises, or case studies. Even business
internships can fail the “real world” test since they typically fall short of giving
the students actual decision-making authority or allow the students to experience
genuine risk.
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A Model for Experiential Entrepreneurial Education
A five-step teaching model was developed in an effort to create an
entrepreneurship education pedagogy that fully embraces the lessons of
experiential learning. This model was originally conceived of during work at the
Small Business Development Center (SBDC) and has been used to teach students
at New Mexico State University (NMSU). The five steps of the model build
from a foundation of the two most commonly neglected aspects of experiential
learning: a whole person approach and contact with the environment.
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This entrepreneurship education model describes a process that allows
students to confront the stress, competition, and risk inherent in entrepreneurship
and provides them with a sober view of the work required in starting a business.
While a dose of reality may serve as a hindrance for some budding
entrepreneurs, most students report that discovering their own innate capacity for
creativity and problem solving significantly enhances their excitement for the
project. The five aspects of an effective experiential education in
entrepreneurship will be discussed in detail in the subsequent section of the
manuscript.
1. Enhancing self-awareness and developing intellectual capital
2. Networking
3. Determining the target industry
4. Business Selection
5. Developing a marketing system.
Enhancing self-awareness and developing intellectual capital
Perhaps the most critical step in the process is conducted as the outset in
order to challenge the entrepreneurship student to go beyond a rational
assessment of a potential business opportunity in the quest to become an
entrepreneur. The student is asked to reflect about his or her own capabilities,
desires, weaknesses, and talents in order to assess intellectual capital.
Intellectual capital can be defined as the ability of an individual to add value to
an activity, organization, business, or enterprise. Simply measuring academic
credentials or work experience is not sufficient to determine the ability to add
value since factors such as personality, likes and dislikes, and temperament each
affect creativity and interpersonal skills.
The process of enhancing a student’s self-awareness and developing
intellectual capital is what introduces the whole person approach to
entrepreneurial education. It helps to identify the skills and experiences that
would be helpful to that student in running a business but also goes beyond the
cognitive to an ontological assessment of fit to the business. It allows the student
to identify the type of business that accommodates his or her particular lifestyle
choices and latent strengths. It simultaneously widens the student’s creative
horizon to increase possible opportunities and illuminates the expertise needed to
achieve those opportunities.
A first-order pedagogical technique that has been used effectively to
assist in enhancing self-awareness is a personal assessment. A personal
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assessment is a review of the student’s life experiences from the perspective of
starting and operating a business. It works to identify specific industry
knowledge and establishes life preferences that can be measured against the
choices of business. It also works to define the functional business skills and
personality characteristics to be strengthened during the course of the
entrepreneurial venture.
Another technique that takes this assessment further builds from the
foundation of resume creation. Students are simply asked to complete a
thorough resume outlining the skills, experience, and abilities they possess for a
job in their chosen industry. They are then instructed to eliminate all identifying
characteristics so that the resume is completely anonymous. Resumes are then
shared randomly among classmates who discuss the perceived personal qualities
of the person highlighted on the resume. This has been a remarkably instructive
exercise for demonstrating how the student is presenting him or herself to others.
Since business ultimately involves selling in some capacity, it shows the students
how they are selling themselves. Additionally, it serves to illuminate those blind
spots where self-perception does not equate to another’s objective view.
Networking
A critical aspect of experiential education is contact with the
environment. In entrepreneurship education, this translates to direct contact with
current customers, competitors, and stakeholders residing within or on the
periphery of the chosen industry. It is of vital importance for students gain
relevant industry experience to augment their business skill set. They should be
encouraged to seek out immersion opportunities within competing businesses
whether through internships, apprenticeships, part-time jobs, or volunteer
opportunities.
Another important facet of the networking phase is for the students to
seek out counsel that can be utilized during the business start-up stages.
Teachers can arrange opportunities for students to visit with the SBDC or the
Service Corps of Retired Executives (SCORE) consultants at the Chamber of
Commerce to gain valuable insights and connections. Experienced
entrepreneurs, business bankers, and angel financiers should all be sought by the
teacher of an entrepreneurial course to assist the students in making contact with
their future entrepreneurial ecosystem.
In addition to the traditional “pounding the pavement” means of
networking, a vast array of social media opportunities exist for budding
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entrepreneurs. Websites such as Entrepreneur Connect, PartnerUp.com, Start-Up
Nation, Young Entrepreneur, Cofoundr, and Perfect Business provide valuable
opportunities for students to connect with other prospective entrepreneurs,
potential funders, programmers, web designers, and executives. Utilizing these
networking opportunities encourages students to not only share ideas with other
professionals but also to improve their business sales pitch and develop or
enhance their social media presence.
Industry Choice
If the two previous steps in the model were developed to achieve the aspects
of experiential learning that are often missing in traditional entrepreneurial
education, then the final three steps are used to shift the students to the pragmatic
nuts and bolts of starting a business. The enhanced self-awareness gained by
students completing the first phase of the course typically brings with it a
relatively concise determination of the industry within which a student would
consider a business opportunity. The most important criteria for choosing an
industry are the student’s own passions, strengths, and intellectual capital and a
teacher should endeavor to encourage those decision points. Beyond internal
characteristics, however, several external factors should be considered when
making the industry choice:
 Projected industry growth rate
 Barriers to entry
 Fragmentation
 Recent legislative changes
 Tax breaks and government investment
 Appeal to capital investment
There are many ways to approach the question of industry choice with
students and the strategic marketing literature is quite useful in this regard.
Demonstrating examples of market segmentation such as Campbell Soup’s
spicier version of nacho cheese and Burger King’s breakfast burrito that are
targeted exclusively for the Southwest provide valuable insight into
understanding the competitive environment. Walking students through product
positioning exercises to identify an under-served niche also encourages a
strategic mindset that helps students acknowledge where their product or service
fits into the larger marketplace.
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Business Selection
Students should be encouraged at this stage to conduct an in-depth review
of the prospective competitive advantage of their business. Will they be using an
alternative different distribution channel to their competitors? Will they by
adding special product features? Do they have a pricing strategy? Are they
implementing innovative products or processes? Does their business add
convenience or speed? Are they improving packaging, advertising, or service
features? Market niche and distinctiveness should be well thought out during
this stage.
It is important to re-emphasize that selecting a business is more than
finding the next revolutionary idea, chasing the “hot” industry. Instead, students
ought to focus on a business that piques their interest and meshes well with their
past experience and identified talents. Switching industries away from an area of
expertise to focus on the prospect of profitability available in another industry
will likely only result in new frustrations that the student is ill prepared for.
The goal in selecting an entrepreneurial venture should be to take
advantage of the full spectrum of a student’s intellectual capital, including
personality, likes and dislikes, and lifestyle choices. The student should focus on
a business that has the prospect of remaining challenging and interesting in both
the short and long run. It is important to take financial means to handle start-up
costs into consideration at this stage as well. Once those criteria are met,
encourage the students to consider a business that they can realistically initiate
within the next 6 months. This will encourage the students to contemplate
practical entrepreneurial opportunities, whether they get off the ground in that
timeframe or not.
Developing a Marketing Strategy
The final stage of the experiential entrepreneurial education model is the
creation of a marketing strategy. An effective entrepreneurial marketing strategy
demystifies the customer acquisition process, requires little capital, and begins
with a survey of the prospective marketplace. The reason why franchises are so
popular is that one aspect of starting a business that frightens prospective
entrepreneurs is the marketing problem.
It is useful to begin by describing what an effective entrepreneurial
marketing system is not. It is not akin to the marketing plan touted by most
marketing textbooks: a rigid document that treats marketing as an activity
accomplished by professional sales staff and which often results in a list of
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activities and sales tools that the business will use to tell its story through an
advertising medium. Most marketing plans do not incorporate an understanding
of the different dynamics of newly formed businesses as opposed to those that
have a track record and some degree of market penetration. Unlike these
marketing plans, the marketing strategy used for entrepreneurial ventures must
assume that very limited funds are available to spend on advertising.
It is also important to note that an effective entrepreneurial marketing
strategy is non synonymous with word of mouth or guerrilla tactics. Word of
mouth referrals originate from customers who have informed others of their own
positive experiences with the business and, thus, are the result of simply serving
customers well, not the successful implementation of a marketing strategy.
Conversely, while guerrilla marketing can be successful in driving curiosity to a
business, the link to sales is speculative and it should be used as a tactic within a
robust marketing strategy as opposed to the sole technique implemented.
An effective entrepreneurial marketing strategy does not start by lauding
the praises of a product or service but rather starts with the expertise that will be
converted into solutions for customer’s current and potential problems. The goal
is to create a dialogue with each customer that focuses on needs and whether the
business can address them sufficiently. The ability of a business owner to solve
a customer problem is an apt example of the use of the intellectual capital
developed in earlier exercises. As the entrepreneurial organization grows, its
policies, procedures, and training materials will enable other employees to
achieve sales and marketing goals as they begin with an intangible asset that a
prospective customer will value.
The first step in crafting a marketing strategy is to engage a normative
process. The goal is to gather and document information about what competitors
are doing to acquire and serve customers. This encourages students to reexamine
fundamental assumptions about their product or service relative to the market
place. It also reinforces the importance of continually reflecting on the business.
The second component of the marketing strategy is analytical and
involves the collection of market data. Most business owners, when pressed,
cannot explain how they receive referrals or new business nor can they cite
specific activities that may have created them. During this stage, the
entrepreneur should gather all relevant demographic, competitor, and customer
data and then develop a system by which to routinely analyze it to seek out
trends, changes, and market opportunities. It is often the case at this stage that
determining what data to collect is more difficult than the data collection process
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itself.
Third, the student needs to define the distinctive attributes of the business
that address customer’s needs. These definitions should be precise and clearly
indicate a perceived benefit of the product or service offered. Generic terms
such as “high quality” or “convenient” should be replaced by specific
characterizations of the customer solution. Who is your ideal customer and what
specific characteristics of your business appeal to him/her?
The final component of the marketing strategy consists of detailed tactics
that take advantage of the information gathered in the first three steps. The
following is by no means a complete list and various tactics can be supplemented
at will: a written description of the methodology used to obtain contact
information for the most desired customers, specific activities and events
designed to make contact with prospective customers, a budget that allocates
time as well as expense for each marketing activity, and a tracking system to
record results.
CONCLUSION
Entrepreneurship is the mechanism by which millions of people access
the pursuit of economic success. “Entrepreneurship is a dynamic process of
vision, change, and creation. It requires an application of energy and passion
towards the creation and implementation of new ideas and creative solutions.
Essential ingredients include the willingness to take calculated risks--in terms of
time, equity, or career: the ability to formulate an effective venture team; the
creative skill to marshal needed resources: and fundamental skill of building
solid business plan: and finally, the vision to recognize opportunity where others
see chaos, contradiction, and confusion” (Kuratko & Hodgetts, 2004, p.30). The
experiential entrepreneurship education model discussed in this paper has proven
to be effective at creating realistic expectations for prospective entrepreneurs
while simultaneously enhancing excitement among students.
By the end of this experiential entrepreneurship course, many students
have typically chosen to work or intern at companies with whom they have either
directly networked or with other companies within the same industry. Most plan
to start their own venture within 6 months but realize that they should first
acquire more specific industry experience. Students also report that they have
experienced some of the stress of starting a business through the coursework and
have an entirely new understanding of business from the perspective of
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ownership. Perhaps most importantly, students speak of being emboldened by
the excitement derived from discovering their capacity for innovation and
creativity.
Keywords: Entrepreneurship, Experiential Learning, Pedagogy
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THE SOCIAL BUSINESS CHALLENGE:
EXPERIENCING MISSION DRIVEN ENTREPRENEURSHIP
Caroline Glackin
Shepherd University
ABSTRACT
The Social Business Challenge is an innovative, extended experiential program
that immerses students in the entrepreneurial process from idea to harvesting
while including a philanthropic purpose. Undergraduate students learn by
analyzing, synthesizing, and evaluating while applying knowledge, skills, and
abilities to the work to create and operate a social business on time-delimited
basis. The Social Business Challenge is part of an introductory course in
entrepreneurship and is intended to increase the value of entrepreneurship
education for students and benefit the community as a service learning activity
through its innovative pedagogy. This active learning process becomes a
reference point for further learning in entrepreneurship.
INTRODUCTION
Rationale
The Social Business Challenge (SBC) is an innovative experiential
program that engages students in the entrepreneurial process from start to finish
including a philanthropic purpose. It is a method for undergraduate students to
learn material introduced in the classroom by thinking and doing the work to
create and operate a business for a limited time. The purpose of the Social
Business Challenge is to increase the value of the University’s entrepreneurship
education for students and the community by innovating in pedagogy. It is
designed to assist in the development of the necessary knowledge, skills and
abilities for students to excel.
While many courses rely heavily upon the traditional “chalk and talk”
approach to teaching and learning, entrepreneurship and small business
management is a subject that frequently involves some, if not many, forms of
experience-based learning. Among the common pedagogies are entrepreneur
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interviews, guest speakers, business plan competitions, and elevator pitch
competitions. Neck and Greene (2011, p. 59) observe that “Though the business
planning process is an attractive and powerful learning process, a
disproportionate amount of time is spent honing secondary research skills than
actually taking smart action in the real world.” The SBC is another way of
encouraging students to “take smart action in the real world” while in a course.
Increasingly, educators are recognizing the importance of collaborative
learning (Drummond, 2012; Tapscott and Williams, 2010) and assisting students
in learning through doing (Ǻsvoll and Jacobsen, 2012; Neck and Greene, 2011).
Those involved in entrepreneurship education have suggested a number of
strategies, primarily experiential in nature (Alberti, Sciascia and Poli, 2004;
Bruton, 2010; Cope, 2003; Cope and Watts, 2000; Kuratko, 2004; Sherman,
Sebora, and Dingman, 2008). Some have addressed the use of business or
venture models (Hamermesh, Marshall and Pirmohamed, 2002; Morris,
Schindehutte and Allen, 2005) while other focus on design thinking
methodologies (Blank et al., 2012; Bruton, 2010 and 2012). Recent conference
sessions and papers have addressed establishing businesses in the university
setting (Martin and Malach, 2012; Plumly, Wayne, Marshall et al., 2008; Yang,
2012).
Pittaway and Cope (2007, p. 214) suggest that the following key features
are “required when simulating entrepreneurial learning:
Financial and emotional exposure (Cope, 2003); action-oriented
and proactive behavior (Rae and Carswell, 2000; Young and
Sexton, 1997); discontinuous events, crises, failure (Cope and
Watts, 2000; Cope, 2003; Deakins and Freel, 1998); socially
situated learning, learning as co-participation (Hamilton, 2004;
Taylor and Thorpe, 2004); and habitual learning (Costello,
1996).”
The Social Business Challenge includes all of the features identified by Pittaway
and Cope as they identify opportunities, determine target markets, create
products or services and bring them to market.
Also, in recent years, some faculty has created and implemented
programs to foster the development of highly innovative and feasible ventures,
including Stanford University’s Lean Launch Pad (Blank et al., 2012) and Mount
Royal University’s Venture Design Studio (Bruton, 2010).
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All of the above-mentioned experiences provide insights and potential
inspiration for students, but the SBC experience goes several steps farther with
the actual planning and operation of a business, closing it, and reflecting upon
the experience. It is a pedagogy that is well-suited to an introductory
undergraduate course in entrepreneurship or small business management (no
prior business courses required).
The original concept was derived from the now-defunct Gumball
Challenge and has been modified, essentially beyond recognition, based upon
additional faculty learning and student feedback. The Gumball Challenge was a
one-week challenge that originated as a class project at Stanford University.
Student teams would use $27 and 27 gumballs to create a product or service
business and operate it with proceeds going toward the associated not for profit
and used for microfinance (Tuilentine, 2011). The number 27 represents the
original financing by Grameen Bank for women in Bangladesh. The gumballs
have several meanings:
Ending poverty is like a gumball machine: helping one gumball
out makes everyone closer to the exit. Gumballs are flexible…the
Challenge turns creative, passionate students into entrepreneurs
tackling the world’s toughest problems. Entrepreneurship is like
a gumball machine: you need a good, chewy idea that everyone
wants more of and a machine that runs without jams.
Among the higher education institutions with participating teams were
Boston College, Princeton University, Stanford University, and the University of
Maryland. A total of 76 schools and 300 students participated raising $22,000
according the Gumball Challenge website. The SBC retains the team concept,
the contribution to a charitable beneficiary, and time limited participation, but
has changed the purpose and process almost completely.
Concepts/Theories
Students are guided to learn a number of concepts and gain awareness of
their own priorities, strengths and challenges throughout the SBC. Among the
concepts involved are:
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General Topic
Markets & Marketing
Management
Operations
Finances & Financing
Other
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Specific Topics
Idea generation and opportunity identification
Market research and analysis
Target market identification
Pricing strategy and structure
Promotional plan development and
implementation
Site selection/channel(s) of distribution
Assessment of the competitive environment
Development of competitive advantage
Selling skills
Exploration of personal values and cultures
Team formation
Negotiation
Communications
Management of difficult people
Planning, organizing, leading, and controlling
Team scheduling and other operating details
Production planning and implementation,
including inventory management
Acquisition of start-up capital
Record keeping and financial statement
generation
Business Model development
Feasibility analysis
Legal and regulatory compliance
These concepts are addressed in the text used in the course (Mariotti and
Glackin, 2013) and are brought home through the multiple weeks of the SBC.
Student teams are given an added incentive (beyond the experience, the
opportunity to support a charitable organization, and the grades earned) of
attaining up to five percent added to their course grades for members of the team
with the highest net proceeds from the challenge.
Much like the students in Plumly et al. (2008), many of the students in
the Social Business Challenge, “[A]pplied course knowledge, exercised their
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analytical skills, learned to communicate effectively, utilized their negotiation
skills, worked effectively in teams, complied with legal requirements, and
utilized creative through processes to solve business issues…Through this
‘entrepreneurial experience’ the students developed entrepreneurial
competencies.” In the case of the SBC students, the exercise in entrepreneurial
competencies is combined with entrepreneur interviews, business models, guest
speakers, and a series of case studies, in-class exercises, and traditional course
material.
EXERCISE COMPONENTS AND INSTRUCTIONS
The parts of the exercise include the initial assignment; team formation
and charity and business model selection; proposal development; acquisition of
permissions; reflective journaling; an in-class quick drill; donation of net
proceeds; peer evaluation; final reflective paper, and final presentation. In
addition, there are grading rubrics for the final paper and presentation. Each of
the documents distributed to students is included in Appendix A.
INSTRUCTIONS FOR PRESENTING THE SOCIAL BUSINESS
CHALLENGE
The Social Business Challenge can be introduced multiple times within a
semester-long course with increasing levels of detail. On the first day of class,
the SBC should be briefly described as a major part of the course with an
explanation of the importance of engaging in an entrepreneurial experience
rather than simply reading about it or hearing stories.
In the second week of classes, an introduction of the topics of social
business and social entrepreneurship and a brief overview of the project is
appropriate. Provide the explanation of social entrepreneurship (Dees, 2001, p.
4) as “Social entrepreneurs play the role of change agents in the social sector by:
 Adopting a mission to create and sustain social value (not just
private value),
 Recognizing and relentlessly pursuing new opportunities to
serve that mission,
 Engaging in a process of continuous innovation, adaptation, and
learning,
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Acting boldly with being limited by resources currently in hand,
and
Exhibiting heightened accountability to the constituencies
served and for the outcomes created.”
Also, describe the concept of a social business as defined by Muhammad
Yunus (2007) as a “non-loss, non-dividend company designed to address a social
objective within the highly regulated marketplace of today.” If there is sufficient
time, a brief YouTube video regarding Grameen Danone could be shown or the
Harvard Business School case study on the same could be included. Students
should be given the opportunity to discuss reasons to create a social business
rather than a traditional for profit in the context of the current course. At this
point provide information about team formation and charitable organization
selection perhaps incorporating the questions indicated later in this document.
A detailed introduction with the formal assignment, forms and rubrics
should be provided approximately five weeks prior to the desired end date of the
SBC. All materials to be used by the students should be posted to any available
course management system such as BlackBoard, WebCT, Moodle, or Sakai at
the beginning of the semester with all due dates noted on the syllabus and in the
Assignments section of the course management system. This introduction
includes the purpose and goals of the SBC, the components and requirements,
assessment methods, and peer evaluation process. All parts of the assignment
and the anticipated deliverables are discussed. This instructor allocates one class
period for this full introduction and has students meet with their teams to
brainstorm product/service ideas and target markets, as well as to map out their
division of labor and schedules. The kick-off is a bit of a celebration.
In week nine, there is an opportunity to share progress with classmates
through a quick drill (two minutes per team) where they are asked to provide the
team name, charitable organization, team member names, business model, and
status update. This is a chance for feedback from the class and reinforces the
teams’ clarity of purpose and process.
Throughout the Social Business Challenge, the instructor can inject
questions and examples into the class discussions and encourage the students to
make connections between what they are experiencing in the SBC and what they
are learning about in the classroom.
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Learning Goals
The student learning goals through the SBC may vary, but are generally:
 Increasing the value of entrepreneurship education through the
experience of an authentic entrepreneurial business with a real product or
service. (Application, analysis, synthesis, evaluation)
 Assisting students in learning through doing. (Application)
 Reinforcing and expanding upon the concepts identified above.
(Identification, tabulation, prediction, application, modification,
experimentation, analysis, creation, assessment)
 Exploring individual values, skills and attributes and reflecting upon
them. (Examination, reflection, synthesis)
 Demonstrating the knowledge, skills and abilities required to develop a
business concept and implement the concept. (Application)
 Simulating entrepreneurial learning (Pittaway and Cope, 2012)
 Financial and emotional exposure
 Action-oriented and proactive behavior
 Discontinuous events, crises and failure
 Learning as co-participation.
In addition, the SBC gives students an opportunity to provide financial support to
a charitable organization through the net proceeds and it exposes increased
numbers of students, faculty, staff, families, and community members to the
university’s entrepreneurship program and social entrepreneurship.
Timing
The SBC currently runs as a 12 week project with the majority of the
effort expended toward the middle 5 weeks of the semester. It may be
compressed into as few as 2 weeks or expanded to 14 weeks depending upon
instructor preferences. The amount of in-class time devoted to the SBC is
relatively small with the introduction, group formation, quick drill, and final
presentations requiring from 5 to 10 course hours per section depending upon the
number of teams. It seems best implemented after students are introduced to the
concepts of opportunity recognition, target markets, and strategy. If there is a
university break or a major fundraising effort such as Relay for Life, it also
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seems best to include the break in the selling weeks and complete the SBC at
least two weeks before the major fundraising effort.
A recent variation on the SBC is the selection of teams and charities
during the second week of classes. Students in multiple sections recommended
keeping the “official” planning and preparation windows and sales period at
about five weeks, but suggested introducing the Challenge in greater detail
earlier in the semester so that they could begin thinking about it earlier. The
most successful team to date was headed by a student who was engaged by the
SBC concept in the first class and began thinking of opportunities immediately.
By moving the team and charity selection earlier, there is no increase in
classroom time required, it is simply redistributed.
As currently implemented the timing is as follows:
Week of SBC
Activity/Milestone
1
2
6
8
Brief introduction and discussion on day 1
Team and charitable beneficiary selection
Full introduction of the SBC
Proposals and permissions due
Proposals accepted/rejected/or revisions requested (by
Sunday night)
Sales begin
Business model presented as a quick drill in-class (beginning
of week).
First reflective journal entry due (end of week)
Second reflective journal entry due.
Sales end (for a total of two weeks of selling time).
Funds checked against records.
Winners announced in-class.
Third reflective journal entry due.
Presentations and papers due.
Discussion of student recommendations.
9
10
11
12
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Participants, Appropriate Level and Materials Needed
The Social Business Challenge is designed for undergraduate students,
generally in their third or fourth year of university studies, with or without prior
business courses. As a team exercise, this instructor recommends teams of three
or fewer students. However, as a practical matter, in courses with larger than 30
students per section, teams of up to 5 students each may be necessary. Because
students often elect to operate their businesses on the university campus,
depending upon the physical size and student, faculty and staff population, it
may be prudent to schedule the deadlines differently in various sections.
However, doing them simultaneously creates more competition and additional
learning. With an average of 30 students per semester, the SBC operates with
approximately 10 teams and has resulted in top earnings of $174 to over $2,100
in various semesters. Each semester there has been a team which has learned
about business failure by either losing part of their initial investment (one team
lost $20) or never earning any revenue.
The materials needed for the Social Business Challenge are limited to the
items included in Appendix A for the instructor and a variety of materials for the
teams. Each team must source its initial investment in inventory and marketing
costs. The amount of investment is presently limited to $81 per team with most
teams having three members, after we tried the $27 cap of the Gumball
Challenge, $50 per team, $27 per team member, and discussed the viable number
with students. Instructors may wish to establish lending programs for startup
funds; however, this may be a challenge within the university system. Students
may have materials donated to them, such as the team that produced calendars
for the local Humane Association and had the paper, printing and binding
donated by a local company. Students also must have access to computers for
their presentations, if a PowerPoint or Prezi presentation is required.
Student and Instructor Preparation
Preparation for students and instructors is quite different. Students do not
have any academic prerequisites other than class standing for enrolling in the
course that includes the Social Business Challenge. In order to be successful in
acquiring significant net proceeds, they need to: successfully form and work with
a team; identify a charitable organization that resonates with them and their
target market; match the target market and product or service, place, price and
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promotion; negotiate the rules of the SBC and the university; communicate well;
match inventory requirements to sales; sell, and be flexible.
Instructors have two types of preparation for the Social Business
Challenge. The first is the upfront preparation and the second is the work during
the challenge itself. Determining the timing and desired learning goals is upfront
and the timing may vary somewhat from semester to semester. Working within
the university structure, policies and procedures is perhaps the most timeconsuming upfront effort required. It may involve contacting the legal
department, student affairs, facilities management, and deans or department
chairs, as well as other units. Sandra Martin and Rob Malach of the University
of Calgary presented an excellent workshop on “Experiential Entrepreneurship
Education – Managing the Attendant Regulatory and Risk Management Issues”
at the 2012 United States Association for Small Business and Entrepreneurship
(USASBE) conference. Their recommendations have been incorporated into the
documents included in Appendix A. The university is supportive of the SBC and
recently included it as a model program in service learning. Once the “rules” and
any other parameters are defined, the actual operation of the SBC is relatively
straightforward. All of the forms and instructions must be created and vetted as
required.
During the SBC, the instructor primarily acts as the “regulator” as well as
providing guidance and feedback. Preparation for this phase is primarily in the
knowledge base of the instructor and his/her networks. The instructor should
anticipate spending time reading the journal entries and touching based with the
teams. It is also a good idea to visit the teams during their on campus selling
times or to have colleagues do so to encourage students and confirm that they are
complying with the SBC requirements.
TEACHING NOTES
Questions for the Instructor to Ask
The questions arise at multiple points within the Social Business
Challenge and are intended to foster self-directed student learning by doing.
These have been modified each semester and continue to evolve with the
experiential project.
Selection of Teams and Charitable Beneficiaries – Week 2
1. Who would you like on your SBC team?
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2. What are you most passionate about in society? For example: public
policy, health issues, and the environment. List your top 5 items.
3. What are your hobbies and interests? List your top 5 of them.
4. Which items on your list correspond with your team members?
5. What do you agree is the priority on which your team would like to
focus? (Share with the class to see whether people wish to merge or
switch teams.)
6. Which charitable organizations address your interests/concerns (local,
regional, national, or international)? Feel free to do online searches.
7. To which charitable organization would you like to donate your SBC
proceeds?
Official Kick-Off of the Pre-Venture Phase – Week 6
1. What is your target market? Be specific and define it in terms of
demographics, psychographics, and the like.
2. Brainstorm the types of products and/or services that would appeal to
your target market.
3. Sort through the ideas for feasibility. Bear in mind the financial
constraint ($81 per team) and the rules of the SBC. Be creative.
Remember, if the lead time is short enough, you can sell items and
replenish your inventory.
4. What business model do you propose?
Reflective Journal Entries – Weeks 9, 10 and 11
1. What has happened with respect to your team and yourself thus far in the
SBC?
2. How do you feel about the events?
3. Reflect on the process and what might be improved upon as the SBC
continues.
4. How can you contribute to the team’s success?
Final Paper, Final Presentation, and Wrap-Up – Week 12
1. Would you recommend that we continue to do the SBC in future classes?
Why or why not?
2. What specific activities or requirements, if any, would you change?
How?
3. How, if at all, would you change the timing of the SBC? Why?
4.
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Hints on Ways to Make the Exercise Work Effectively
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Present the SBC clearly and with genuine enthusiasm.
Guide students in understanding the benefits of the process.
Have students select their own teams. Do not assign students to teams.
Keep the teams small (3 each), if possible.
Encourage students to work with their charitable beneficiary
organizations to maximize revenue generation.
Include brief reflective journal entries during the operating phase.
Do not proceed with the SBC without administrative approval and
support.
Be certain that students are not interfering with the commerce in your
town/location.
Actively work with the Service Learning team at the institution to create
greater value.
Summary of Student Reactions
The Social Business Challenge includes formal reflections (journal
entries, papers, and presentations) as well as in-class and anecdotal information.
Some highlights of the written reactions follow.
General Reactions
Many students have reported that participating in the Social Business
Challenge (or its predecessor Social Enterprise Challenge) is the best academic
experience they have had. A few have been overwhelmed by the process,
frequently citing conflicting school, family and work obligations. Either way,
they have learned about the reality of the entrepreneurial experience. Several
student observations follow:
“There was no better assignment…to give our small business
management class the hands on experience we needed to apply
the material learned in class. The idea was a good one, but we
were no in an area where we could be successful. Overall, it was
a great experience and I’m happy how it turned out.”
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“All in all, we made more than twice as much as our original
goal, so we were quite excited about that.”
“It takes time, work, thought, and compromise to start a business,
especially when an entire group is involved.”
“All group members did not feel like they were in communication
well enough to have product sold at the time they
needed…communication is key.”
“Communication is very important; if we had not communicated
as well as we did, we would not have been as successful as we
were.”
“With a limited time frame, our business did not skyrocket as we
expected…We also had a taste of a small business operation
opportunity under significant circumstances such as a time limit
and schedule variations.” This group included lessons learned
of: picking the right demographic location; taking advantage of
every opportunity; having strong, creative marketing ideas, and
the importance of good packaging, projecting production and
hidden costs, and inventory management.
“We noted that assigning roles in the beginning and holding team
members accountable for their assignments is very important to
the success of the project…instead of trying to get everyone
involved, sometimes it is best to break things into parts and have
people do certain jobs.”
“Marketing is a must and word-of-mouth works wonders.”
“The biggest lesson we all learned was to generate a product that
would effectively sell…provide higher quality.”
“We found that it was easier to sell the product to friends and
family than it was to sell to the student body.”
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“Overall, we did not have very high expectations and felt that this
was going to be a very difficult process, but it turned out to be
fun, entertaining and educational on many different levels.”
“We feel that even though nothing went as planned for our group,
this was still an important lesson for us to learn. We realized to
be successful it takes more than what you think should happen.
Being successful and making a profit, whether for a business or
class project, takes planning, organization and the ability to reach
consumers’ pockets and give them a product they fell worth
purchasing…This was a humbling experience for both of us and
really opened our eyes to what it takes to make something go right
in the business world.”
What Could Be Expected when Running the Exercise
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Students can be creative, energetic and enthusiastic and they may need
prodding.
Weather related operational challenges will happen.
Teams become dysfunctional.
Students underestimate how difficult it is to sell products and/or services,
even when sales are for a charitable beneficiary.
Some students discover that they like to sell and others find the opposite.
There will be significant variation in the level of effort, nature of
products/services and net proceeds.
Students will be frustrated by such factors as limited selling times (if
place based), coping with competition and complying with rules.
Teams may decide to change their business model due to problems with
the initial model. This is to be embraced as students are recognizing the
need to adapt and change.
Inventory may not be available when planned or components may not
perform as anticipated.
Possible Variations in the Use of the Exercise
There are many variations available, from course placement, timing and
regulations to charity selection, focus, and investment. The critical aspect is to
have student go beyond planning into doing.
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Social Business versus For-Profit Enterprise – It is possible for the Challenge
to be operated as a for profit business challenge at the instructor’s discretion.
This is likely to generate greater concerns with university administrators and may
create increased incentives for student misconduct. If students are able to receive
the profits, the university may consider them as operating businesses on the
campus and may have any number of issues with that. In addition, for students
on financial aid, the administration may want reporting of earnings. There are
certainly ways to make it work. This instructor teaches that Philanthropy is the
Fifth “P” of marketing and believes that exposure to social business makes sense
within the context of the course and as a way of expediting the process.
Duration – The SBC could reasonably be condensed to three weeks or expanded
to a full semester. The choice of duration depends upon the depth of experience
that is desired and the financial impact intended. This instructor has varied the
length of each component and found that if it is too short, students do not
recognize what they have done and internalize it. If the selling period is too
long, students weary of it and are not markedly more productive.
Course Placement – The Social Business Challenge could be included in an
advanced entrepreneurship class rather than the introductory one where it is
presently placed. Students might find that they are more adept at identifying the
direct relationship between classroom learning and the experiential learning.
However, the interest and enthusiasm created by the SBC seems to encourage
students to pursue additional entrepreneurship studies and is well suited to the
introductory class. The SBC also could be a co-curricular activity which is
included in a university’s service learning programs.
Charity Selection – There are several alternative methods of selecting the
charitable beneficiaries that are worth consideration and probably many more
possible. For example, the instructor might decide to give all funds to the
university or university foundation for student scholarships or the like.
Alternatively, all net proceeds could go to a local microfinance organization or
through ACCION or Kiva.org. The value in these options is that they remove
the time and effort of deciding upon charitable beneficiaries. However, they may
also substantially reduce student motivation for those not interested in the
selected charity.
Students could go through a classroom exercise to select a single charity
for the entire section. This may mean greater impact for a single organization,
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but part of the learning is discovering how much of a role the beneficiaries and
their brands have in the success of the endeavor. This can be direct impact such
as when students partner with the charitable organization in opportunity
identification and operations (such as the pet calendars for the local humane
society or a fundraising dance and silent auction for the Juvenile Diabetes
Research Foundation). It can also be indirect with students learning that there is
a mismatch between their charity and their target market.
Another option is for the instructor to assign students to teams and then
do the charitable selection process. This did not work well for two class sections
in a prior semester. Students argued that they would pick their teams in a
business start-up and that they were compelled to work with either students they
did not know or would not have selected.
Finally, the types of charitable organizations and/or the issues which they
address may be proscribed by the instructor. For example, the faculty member
may require that the students work with a local charitable organization or the
local affiliate of a national or international organization. By doing so, direct
contact with staff and volunteers at the local level is far easier to facilitate and
creates a greater service learning opportunity. However, if the students are
highly motivated to work with an organization that does not have a local
presence, they may be compelled to work with a second or third choice. Also,
some institutions are faith-based or have other concerns that will limit student
options. These should also be considered.
Student Investment – This can vary significantly depending upon instructor
goals, duration of the project and preferences. The $27 specified in the Gumball
Challenge proved to constrain student business choice such that they were
essentially soliciting donations. Subsequently, this instructor raised the limit to
$50 per team regardless of team size. The current level is $81 per team at the
maximum, so that it ties back to the microfinance example but creates a
relatively small individual investment and greater options for the student teams.
Debt - Faculty may want to consider lending start-up capital to the teams, either
from personal resources or through departmental or university sources. This, of
course, encourages debt, both adding one more realistic factor and increasing the
risk for the students, faculty, and even the university. This instructor does not
offer loans due to risk factors and university concerns (particularly at a state
supported institution). However, including a requirement for students to secure
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debt or equity capital from an outside source (i.e. friends and family), does add a
level of realism and the sense of responsibility.
Determination of “Winning” Team – Currently, the winning team is determined
solely on the basis of the greatest net proceeds. This could vary in many ways.
For example, a Return on Investment calculation could be used or there could be
awards for creativity, marketing or other things. The calculation of the average
individual return generally aligns with the highest overall productivity for the
team.
Grading - Grades are awarded according to the rubrics in Appendix A with
adjustments based upon peer evaluations. Certainly, the criteria could be
modified in any way that the instructor deems fit. Also, grades could be based
upon the net proceeds rather than the criteria currently used. The bonus system
for the top performing teams is an incentive that students have embraced and
they have become quite competitive about it.
The Social Business Challenge is an experiential learning project that
gives undergraduate students the opportunity to “live” the start-up and operations
of a business with a social purpose. They learn essential skills and gain
knowledge through doing.
Key Words: Entrepreneurship, Entrepreneurship Education, Experiential
Education, Social Business
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APPENDIX A -
SOCIAL BUSINESS CHALLENGE –
SPRING 2014i
Project Kick-Off: January 23
Permissions & Proposal:
February6
Presentation & Paper: March 6
Operations: February 11 – 27
The Social Business Challenge (SBC) provides the authentic, hands-on
experience of starting a business with a social mission. You will work in teams
turning an idea into a social business.
The student learning goals of the SBC are:
 Increasing the value of entrepreneurship education through the
experience of an authentic entrepreneurial business.
 Assisting students in learning through doing.
 Reinforcing and expanding upon the concepts introduced in the
classroom.
 Exploring individual values, skills and attributes and reflecting upon
them.
 Demonstrating the knowledge, skills and abilities required to develop a
business concept and implement the concept.
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 Simulating entrepreneurial learningii
 Financial and emotional exposure
 Action-oriented and proactive behavior
 Discontinuous events, crises and failure
 Learning as co-participation.
The SBC is a competitive team endeavor and is one of the three main
experiential projects for this course. Students will select 3 to 5 person teams
from those in their class. Each team must work together through the final paper
and presentation. How the work is organized is entirely up to you. The
following rules and regulations apply:
 Teams will operate the businesses for the period of time stipulated above.
All transactions must be complete by the final day of operations.
 Students must conduct their businesses in accordance with the guidelines
set up for this assignment and conditions imposed by the instructor.
 Maximum start-up capital is $81 per team. Some teams may not need
any capital. No debt transactions are allowed.
 Ethical behavior and honesty are expected in the conduct of the social
business and in the presentation. Inappropriate or unethical behavior in
the conduct of the business will be penalized at the instructor’s discretion.
 Proposals that include an business model focusing on food (excluding
prepackaged items) for human consumption, alcohol, drugs, gambling, or
pornography, or that conflict with university/faculty policies or that in the
instructor’s sole opinion are not appropriate will not be approved.
 All proposals that will have physical selling locations must have
completed written permissions for the rights to use the locations during
the specified selling periods prior to the start of sales. See Part A.
 Students are advised that the proposals may be reviewed by the
University to ensure compliance. All decisions to reject a proposal are
final.
PART A – Social Business Challenge - Proposal and Permissions (50 points)
Teams must submit a Social Business Challenge Proposal (through Moodle) and
appropriate permission forms (in person) by the data and time specified.
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The Social Business Challenge proposal shall at least contain the following (see
the attached sample for Team Humane):


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


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Team name
Brief summary of intentions
Team members’ names and contact information
Primary contact available during the review period
Proper name of the charitable beneficiary and target contribution amount
($).
Complete description of the products or services
Target market
Location of events and points of sale. Note, selling will only be allowed
in these locations.
Sales method
Advertising and other promotional methods (examples or photos are
welcome)
The completed Social Business Summary Table
Signed, completed permission forms for any locations (submit in person).
If a project is not approved, students must prepare an alternative Social Business
Challenge proposal for approval prior to commencing operations. In that case,
the alternative proposal will be reviewed as expeditiously as possible. If a
project is conditionally approved, students must fulfill the condition(s) prior to
the commencement of operations.
PART B: Presentation (100 points)
Teams will make 10 minute in class presentations using visual aids to include the
following:
 Cover
 Team Name
 Proper Name of Charitable Beneficiary
 Names of Team Members
 The Idea
 Description
 Source
 Discarded Ideas
 Unique Selling Proposition
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




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 Evolution
The Opportunity
 Target Market
 Suppliers
 Channels of Distribution
 Operations
The Environment
 Competition
 Rules/Laws
 Barriers to Entry
The Division of Labor
 Team Member Roles
 Process Used to Decide Roles
 Changes in Roles During the Competition
The Financial Information
 Goals
 Actual Performance
 Investment – Sources & Amounts
 Profit Margin
 Financial Issues/Challenges
Expectations Versus Reality
Lessons Learned
PART C: Project Paper (150 points)
Each team participating in the Social Business Challenge must submit a team
paper on or before the deadline. The paper must include the elements listed
below, but teams may add other information that they deem pertinent. All papers
shall be written in essay form with appropriate subheads, grammar, punctuation,
usage, and structure. There is no page minimum or maximum for this
assignment, but a range of 7 to 15 pages is anticipated. All papers are to
typewritten using a 12 point font and have one inch margins all around with
numbered pages. Photographs of products and samples of marketing materials
may be included and are encouraged.
 Cover page
 Name of team
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




216
 Legal name of charitable beneficiary
 Names of team members with titles (if titles chosen)
Executive Summary (200 words maximum)
The Idea
 Describe the business idea you decided to implement. You are
welcome to include photos or print examples.
 What was the source of the idea? Refer to Mariotti and Glackin
(Chapters 1 and 3) where the process of idea generation and
opportunity selection is described in multiple ways.
 What other ideas were suggested and discarded? Why?
 What is the Unique Selling Proposition for the idea that you
determined was an opportunity?
 How, if at all, did your original business idea evolve?
The Opportunity
 Target market – Describe your intended target market in
demographic, psychographic, geographic, and behavioral terms.
 Charitable beneficiary – What, if any, was the involvement of
your charity in opportunity identification?
 Suppliers – Where, if at all, did you get the necessary materials
and supplies? How did you decide upon these particular sources
(i.e., price, convenience, and credit terms)?
 Channels of distribution – How did you get your products or
services to your end customers (i.e., wholesale, retail, internet)?
 Operations – Describe the operations of your company, including
days and hours of operation, production processes, and logistics.
The Environment
 Competition – Describe your competition, both direct and
indirect. How do you compare along key customer dimensions?
You may want to use a chart like the one in the Mariotti and
Glackin text (p. 104) to create a visual representation of the
competitive environment.
 Rules and laws – What was their role in your business? This can
be in constraining the type of business you started or in affecting
your operations…whatever is applicable.
 Barriers to entry – Are there any barriers to entry that you
encountered and/or could create? If so, what are they?
The Division of Labor
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
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Roles – What were the roles of each team member? Any
additional volunteers?
 Process – How did team members end up in these roles?
 Changes – Were any of the roles changed during the project? If
so, how? Why?
The Financesiii
 Goal(s) – What profitability goal(s) did you set at the beginning?
What assumptions did you make?
 Results – What were the actual results as of the end of the
challenge? Illustrate these using an income statement and balance
sheet.
 Receipts for the purchase of any supplies or inventory. Copies of
receipts issued to customers (for larger sales) or a record of daily
cash (for multiple, small sales).
 Investment – How much did team members invest in the
company? How did this affect your capacity to generate sales and
profits, if at all?
 Financial challenges – What, if any, financial challenges did you
encounter? What did you do to overcome them?
Expectations versus Reality
 What did you expect to have happen?
 What happened?
 How did your expectations vary from reality?
 What are your feelings about the differences?
Lessons Learned – Identify the top 5 to 10 lessons learned.
Suggestions for Future Competitions – What, if anything, should be
changed? How?
PART D: Bonus Points Available (Additions to Semester Grades)
This portion of the grade will be based on the net proceeds of the team’s social
business. Net proceeds are calculated from earned revenue (for products/services
completed) plus any donations minus expenses incurred (all expenses incurred
for operating the business with no wages or salaries paid to anyone) and the
repayment of initial investments.
(Earned Revenue + Donations) – (Expenses + Initial Investment) = Net
Proceeds
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The bonus points for this portion will be allocated between all course sections.
However, the instructor reserves the right to deviate from the following system
should a lower or higher bonus be warranted.
 1st place
 2nd place
 3rd place
=
=
=
50 points
30 points
10 points
=
=
=
5%
3%
1%
BEST WISHES FOR A FUN AND VALUABLE EXPERIENCE!
SAMPLE
TEAM HUMANE: Social Business Proposal – February 6, 2014
Team Humane would like to sell note cards from February 11 to February 27,
2014 for the Social Business Competition. Our team members include Giovanni
Cedilla (gcedil01@rams.university.edu), Glenn Clowser
(gclows03@rams.university.edu), and Gloria Church
(gchurch04@rams.university.edu) and Gloria will serve as the primary contact at
304-876-9999.
Team Humane’s product-based business will operate as follows:
1. Charitable Beneficiary
a. Humane Society of Berkeley County
b. Goal of $600 in net proceeds
2. Products and Pricing
a. Note cards and envelopes
i. Various designs (3) to choose from featuring puppies and
kittens
ii. Designed in-house by a team member
iii. Will pay to print cards and purchase envelopes; then will
charge price to customers to reflect at least a full (100%)
markup
iv. Anticipated costs will be $0.40 per note card and envelope
v. Pricing will be $1.50 per card, $6.00 per half-dozen and
$10.00 per dozen
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vi. Team Humane will accept cash, checks and PayPal for
purchases.
vii. We will order 50 cards of each design to start and will reorder as needed, as the printer has 4 day turn around.
viii. If printing can be secured at a reduced rate, we will print
additional cards prior to the selling period.
3. Target Market
a. We will market to several categories of customers who will be
interested in purchasing our note cards
i. Local small businesses within 25 miles of campus
ii. Our families and other personal contacts
iii. Students, faculty and staff who are interested in the
Humane Society or simply like the cards
iv. Visitors to the Humane Society of Berkeley County shelter
v. People attending the Humane Society’s Annual
fundraising luncheon
vi. Facebook friends through online ordering.
4. Locations
a. We will be selling our greeting cards at on-and off-campus
locations and online
i. On-campus will be White Hall, the Student Center, the
Wellness Center, in front of the Scarborough Library
ii. Off-campus will be the Humane Society shelter and the
Clarion Hotel (for the fundraiser) and family and friends
iii. Online requests will come through Facebook and email.
5. Advertising and Sales Methods
a. We will employ several advertising methods in order to market
our products, including various social media outlets, email, wordof-mouth, and posters.
b. The team will focus on a personal sales method, involving one-toone sales to personal contacts and other interested buyers.
c. Customers will be shown the products and will make a purchase.
d. We will collect payment in full and immediately deliver the cards
if available.
e. If customers place orders for inventory that requires re-ordering,
we will create a purchase order and will re-order from our
supplier at the end of the first week.
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f. We will provide delivery of the cards to our customers.
TEAM HUMANE SOCIAL BUSINESS PROPOSAL – SUMMARY
TABLE
Product/Service
Note Cards
220
Sale
Locations (If
on campus,
dates &
times
required)
Feb. 11, WH,
10 – 2
Feb. 12, WH,
11-3
Feb. 13,
Student
Center, 10-2
Feb. 14,
Wellness
Center 10 –
2,
Feb. 18,
Scarborough
Library,
11 – 4
Feb. 11 – 27,
Human
Society
Shelter
Feb. 14,
HSBC event
Personal
Networks
Advertising
Methods &
Locations
Word-ofmouth, email,
social media,
posters.
Posters in
dormitories
and on school
bulletin
boards after
university
approval.
Humane
Society shelter
and event
displays.
One Member Contact Info
(mobile & email)
Gloria Church
gchurch04@rams.university.edu
304-876-9999
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Social Business Challenge
Permission for Facilities or Space Useiv
The following students are hereby authorized to use the listed space and/or
facilities to promote the identified products/services for the benefit of
_______________________________ (charitable organization).
Students:
Name
Email Address
Locations, Dates, and Times:
Location
Date
Time
Product/Service:
________________________________________________________________
_________________________________________________________________
_____________
_________________________________________________________________
_____________
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Special Notes/Restrictions:
_______________________________________________________
_________________________________________________________________
____________
_________________________________________________________________
____________
__________________________
______________________
(Signature)
______________________
(Title)
(Date)
__________________________
_______________________
(SBC Team Representative)
(Date)
Simplified Grading Rubricsv
Social Business Challenge Paper
Topic
Cover page
Executive summary
Idea
Opportunity
Environment
Division of labor
Finances
Expectations versus reality
Lessons Learned
Quality of writing
Total
222
Potential Points
5
10
15
20
20
20
20
10
20
10
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Fall 2014 Special Issue
Points Earned
Journal of Business & Entrepreneurship
Social Business Challenge Presentation
Topic
Potential Points
The Idea
10
The Opportunity
10
The Environment
10
The Division of Labor
10
The Financial
Information
Expectations v. Reality
10
Lessons Learned
10
Quality of Visuals
10
Quality of Answers
10
Professionalism
10
Total
100
Points Earned
10
i
ii
Pittaway, L., & Cope, J. (2007). Simulating entrepreneurial learning: Integrating experiential
and collaborative approaches to learning. Management Learning, 38(2), 211 - 233.
The financial statements and any other representations are subject to the instructor’s audit and
any inaccuracies or false information is treated as academic misconduct.
iv
Students may substitute standard forms used by the locations they have selected in lieu of this
form.
v
Full rubrics are available upon request. They are not included here due to space
considerations.
iii
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