Cultivating Innovative Entrepreneurs for the Twenty-First Century: A Study of U.S. and German Students

Abstract

The purpose of this exploratory study was to examine the cultivation of innovative entrepreneurial intentions among students in three distinctive educational settings: a U.S. undergraduate four-year environment, a U.S. M.B.A two-year environment, and a German five-year business and technology environment. Results suggested that innovative entrepreneurial intentions varied based on educational setting. Implications for theory, research, and practice are discussed.

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The purpose of this exploratory study was to examine the cultivation of innovative entre-
preneurial intentions among students in three distinctive educational settings: a U.S.
undergraduate four-year environment, a U.S. M.B.A two-year environment, and a Ger-
man ve-year business and technology environment. Results suggested that innovative
entrepreneurial intentions varied based on educational setting. Implications for theory,
research, and practice are discussed.
Keywords: innovation, entrepreneurship, quantitative, college impact
A Study of U.S. and German Students
Engendered by media coverage of the Thiel Fellowship—an initia-
tive that pays emerging entrepreneurs to leave formal higher educa-
tion—and by stories of college-dropouts turned tech-billionaires, higher
education is being scrutinized and is often dismissed with regard to its
role in graduating students with the innovative entrepreneurial capaci-
ties needed to develop and implement solutions to the many problems
facing the twenty-rst century. Rather than being viewed as innovation
engines, uniquely designed to support students who want to learn how
Cultivating Innovative Entrepreneurs
for the Twenty-First Century: A Study of
U.S. and German Students
Matthew J. Mayhew
Jeffrey S. Simonoff
William J. Baumol
Benjamin S. Selznick
Stephen J. Vassallo
The Journal of Higher Education, Vol. 87, No. 3 (May/June 2016)
Copyright © 2016 by The Ohio State University
Matthew J. Mayhew is Associate Professor of Higher Education at the Steinhardt School
of Culture, Education, and Human Development, New York University matt.mayhew@
nyu.edu; Jeffrey S. Simonoff and William J. Baumol are Professors at the Leonard N.
Stern School of Business, New York University; Benjamin S. Selznick and Stephen J. Vas-
sallo are doctoral candidates at the Steinhardt School of Culture, Education, and Human
Development, New York University.

Innovative Entrepreneurship 421
to become innovative entrepreneurs equipped with the skills needed to
create new processes and products that could potentially lead to global
change (Mars, Slaughter, & Rhoades, 2008; Mayhew, Simonoff, Bau-
mol, Wiesenfeld, & Klein, 2012), colleges and universities are being
implicated as innovation threats (e.g., Wieder, 2011) or, at the very least,
criticized for graduating “excellent sheep” who are unable to engage
moral imagination, dened as “the capacity to envision new alternatives
for how to live” (Deresiewicz, 2014, p. 91).
In response, and albeit not explicitly, higher education stakehold-
ers are attempting to reposition innovative entrepreneurship as a cen-
tral rather than peripheral focus of higher education, both domestically
(Morris & Kuratko, 2014) and globally (Winkel, Vanevenhoven, Drago,
& Clements, 2013). For example, the Association of American Col-
leges and Universities has found that, across a wide range of industries,
“nearly all employers surveyed (95%) say that they give hiring pref-
erence to graduates with skills that will enable them to contribute to
innovation in the workplace,” and suggest that postsecondary educa-
tional environments focus on student development of these skills with
greater intent (AAC&U, 2013, p. 1). Other evidence of the shift towards
innovative entrepreneurship include: the recent U.S. News and World
Report (U.S. News & World Report, 2014) and Princeton Review (The
Princeton Review, 2015) rankings of institutions by entrepreneurship
programs, the proliferation of entrepreneurship centers on college and
university campuses (Global Consortium of Entrepreneurship Centers,
2014) and a greater focus on the role pedagogy plays in shaping innova-
tion, creativity, and entrepreneurship (Book & Phillips, 2013; James &
Brookeld, 2014; Vanevenhoven, 2013).
Yet, with this expansion of interest and opportunities also come more
complicated theoretical and practical questions: Can innovation be
taught? Or is innovation something that a student just has, through some
combination of personality and social capital? Furthermore, as the lan-
guage of entrepreneurship has expanded to reect theoretical nuances
associated with its study and practice (Baumol, 2010; Mars & Rhoades,
2012; Shockley, Frank, & Stough, 2008), new questions are emerging
about what types of entrepreneurship should be taught, where curricula
should be housed, and which students should pursue these educational
opportunities (see Kauffman Foundation, 2013; Mayhew et al., 2012).
These questions reect the need for empirical work that examines the
educational settings offered to help students acquire the entrepreneurial
skills needed to move new ideas from thought to action. Although recent
research has discovered a relationship between participation in higher
education and student intentions to engage in innovative entrepreneurial

422 The Journal of Higher Education
behaviors (Lange, Marram, Jawahar, Yong, & Bygrave, 2011; Mayhew
et al., 2012), differences in educational settings have not been examined
as they relate to innovative entrepreneurial intentions, despite a global
effort by educational and economic stakeholders to identify the postsec-
ondary environments that lead to the nancial and employment benets
accrued from new venture creation (e.g., van Praag & Versloot, 2007).
The purpose of this study was to examine three distinctive educa-
tional settings and their relationship to the innovative entrepreneurial
intentions of students from the United States and Germany. To unpack
these settings for their potential in inuencing innovative entrepreneur-
ial intentions, we decided to examine three groups of students: U.S.
undergraduate business students in a traditional four-year environment,
U.S. M.B.A students in a two-year environment, and German students
tracked into a ve-year business and technology program. As a caveat,
this research sought to understand the extent to which different educa-
tion settings may inuence innovative entrepreneurial intentions, not
to make empirical cross-cultural comparisons between students within
those settings.
Theoretical Framework
To conduct an inquiry into the relationship between education set-
tings and innovative entrepreneurship, we adopted an interdisciplinary
approach grounded in student learning theory, entrepreneurship educa-
tion, and economics. Upon reviewing the literature, we turned to schol-
arship that addressed the relationship between intention and behavior
(Ajzen, 1991, 2002) and that examined cross-cultural approaches to
entrepreneurship education (Liñán & Chen, 2009; Moriano, Gorgievski,
Laguna, Stephan, & Zarafshani, 2012). Finally, we used a college
impact framework (Astin, 1993) for situating innovative entrepreneurial
intentions as an educational outcome inuenced by personal inputs and
exposure to specic attributes of postsecondary educational environ-
ments, and for subsequently guiding variable selection.
Innovative Entrepreneurship
Furthering the work of Mayhew et al. (2012), this study attempted
to illumine the relationship between educational settings and innova-
tive entrepreneurial intentions. In contrast to replicative entrepreneurs,
who assume ownership over their iteration of a preexisting product or
service, innovative entrepreneurs generate a novel product, service, or
method and enter their creation into the marketplace for the primary

Innovative Entrepreneurship 423
aim of generating monetary value (Baumol, Litan, & Schramm, 2007;
Drucker, 1985).
Innovative entrepreneurship is frequently associated with a desire to
continually advance ideas, whether on one’s own or in collaboration
with others. As Baumol (2010) discussed in his work The Microtheory
of Innovative Entrepreneurship, “It is [innovative entrepreneurs’] job to
locate new ideas and to put them into effect. [Innovative entrepreneurs]
must lead, perhaps even inspire; for them, today’s practice is never good
enough for tomorrow” (p. 18). While replicative entrepreneurship is
critical for short-term economic growth in local economies, innovative
entrepreneurship is essential for long-term economic development and
holds the potential to establish entirely new industries and transform
national and global markets.
Theory of Planned Behavior
To examine students’ intention to innovate as an internationally
relevant outcome of interest, we used the theory of planned behavior
(TPB) (Ajzen, 1991, 2002) to explain intention and its relationship to
behaviors. This particular theory has gained support by global scholars
who examine the effectiveness of entrepreneurship education (Fayolle,
Gailly, & Lassas-Clerc, 2006; Liñán & Chen, 2009; Wu & Wu, 2008)
and has remained relevant to higher education scholars interested in
a variety of outcomes, such as persistence (Sandler, 2000) and cheat-
ing (Harding, Mayhew, Finelli, & Carpenter, 2007; Mayhew, Hubbard,
Finelli, & Harding, 2009; Whitley, 1998). In his presentation of this
theory, Ajzen (1991, 2002) argues that behavior is ultimately a function
of intentions; those intentions seen as favorable, socially desirable, and
accomplishable are most likely to become actions. Thus, students who
have innovative entrepreneurial intentions would be theoretically more
likely to exhibit innovative entrepreneurial behaviors, including but not
limited to securing patents and obtaining venture capital funding.
A growing body of research (see Lange et al., 2011; SBA Report,
2009) supports this theoretical assertion—that innovative entrepre-
neurial intentions are statistically related to innovative entrepreneurial
behaviors. Despite this relationship, we concede that intention to inno-
vate may not lead always to entrepreneurial behaviors. However, we
argue that leveraging higher education to promote innovative entrepre-
neurial intentions is important precisely because such intentions may
be difcult to actualize. Just as we would not argue that children stop
attempting to learn how to hit a curveball because they are unlikely
to become major league baseball players, we would not discourage
colleges from promoting innovation—especially because, unlike in

424 The Journal of Higher Education
baseball, there is always room for new “players” and “teams” in the
global marketplace.
Review of the Literature
We identied several key discussions in the literature that informed
our study. First, we briey turned to scholars who argued the extent to
which innovative entrepreneurship could be taught. Second, we consid-
ered what an effective entrepreneurship curriculum should include, how
to best provide instruction that encouraged the cultivation of innovative
entrepreneurial intentions, and who pursues coursework that contains
content related to innovative entrepreneurship. Finally, as our sample
includes students from the United States and Germany, we explored
international entrepreneurship education research.
The “Yes-School” and the “No-School”
Scholars exploring entrepreneurship education have been forced to
grapple with a fundamental and important underlying question: To what
extent can innovative entrepreneurship be taught? As Nilsson (2012)
noted in his study of educational impact, two schools of thought exist
with regard to this question: a “yes-school” where education can effec-
tively develop innovation and entrepreneurship skills and a “no-school”
where intentions in this area exist independently of education (p. 41).
While cultivating students’ entrepreneurial intentions produces socially
benecial economic returns (van Praag & Versloot, 2007), disagreement
still persists regarding whether higher education can play an effective
role in this cultivation.
This disagreement noted, two extensive literature reviews (Gorman,
Hanlon, & King, 1997; Pittaway & Cope, 2007), and previous research
specically on innovative entrepreneurial intentions (Mayhew et al.,
2012) lend support to the “yes-school,” nding that educational expe-
riences can increase an individual’s propensity to innovate and pursue
innovative entrepreneurship upon completing postsecondary education.
From these studies, we learned that any inquiry into the relationship
between higher education participation and entrepreneurial intentions
and behaviors should include variables that measure personality dimen-
sions. Thus, we included a series of personality model covariates and
educational experiences in our predictive models designed to explain
innovative entrepreneurial intentions.

Innovative Entrepreneurship 425
Curricula, Educational Practices, and Students
Curriculum. Two approaches have been used to understand the rela-
tionship between entrepreneurship course-taking and outcomes. The
rst approach attempts to identify competencies that can be developed
through exposure to and participation in entrepreneurship curriculum
(Morris, Webb, Fu, & Singhal, 2013). Those competencies most rel-
evant to our study due to their relationship with innovation include
creative problem solving/imaginativeness, tenacity/perseverance, resil-
ience, and value creation (Morris et al., 2013, p. 358). The competency-
based approach also encompasses the notion that entrepreneurship is
related to personality dimensions (Obschonka, Silbereisen, & Schmitt-
Rodermund, 2012).
The social-cognitive approach positions the entrepreneurship cur-
riculum as a course of study capable of helping individuals build self-
efcacy (von Graevenitz, Harhoff, & Weber, 2010) and self-esteem
(Souitaris, Zerbinati, & Al-Laham, 2007) with regard to entrepreneur-
ship tasks while also learning to recognize opportunities to introduce
new products and services into the current market environment (Morris
et al., 2013; Ronstadt, 1987). Since course-taking experiences appear to
share a relationship with a variety of college outcomes, we included the
extent to which participation in an entrepreneurship course might shape
students’ innovative entrepreneurial intentions.
Educational Practices. What educational practices inuence the cul-
tivation of student intentions to become innovative entrepreneurs?
Recent literature on this topic has discussed the importance of learn-
ing for rather than about entrepreneurship (Pache & Chowdhury, 2012;
Pittaway & Cope, 2007; Rae, 2009) through active curricular, cocur-
ricular, and preprofessional engagement during postsecondary education
(Kauffman Foundation, 2013; Raffo, Lovatt, Banks, & O’Connor, 2000;
Vanevenhoven, 2013). Examples of such engagement include: partici-
pating in internships (Kauffman Foundation, 2013); working with on-
campus business incubators (Kauffman Foundation, 2013); developing
and presenting business plans (Gartner & Vesper, 1994); pursuing mar-
ket ventures in conjunction with others on campus (Mars & Rhoades,
2012; Mars et al., 2008); and interacting with practicing entrepreneurs
(Vanevenhoven, 2013). In a recent article, Vanevenhoven (2013) chal-
lenged faculty charged with teaching innovation to become more cre-
ative and involved in experiential learning, noting: “We not only need to
kick students out of the classroom, but we ourselves need to get out of
our ofces and share these [professional] experiences directly with our
students” (p. 468).

426 The Journal of Higher Education
Yet, problems arise when educational practices focus only on help-
ing students learn for entrepreneurship without knowing much about the
mechanisms involved in bringing new ideas to life. As Baumol (2004)
has noted, teaching connected with innovation must walk something of
a tightrope between providing education necessary for entrepreneurs
to succeed without imposing rigid, standardized ways of thinking that
might diminish a student’s creative spirit (p. 50). For these reasons, we
included both traditional and innovative educational practices in our
models designed to predict innovative entrepreneurial intentions.
Entrepreneurship Students. Who takes entrepreneurship courses? Due
to the core skills discussed and the notion that innovative entrepreneurs
aim to start value-creating ventures, the traditional home for entrepre-
neurship coursework has been within business schools and for busi-
ness students (Solomon, 2007). However, in recognition of the global
economic importance of new business ventures (van Praag & Versloot,
2007) and the potential for entrepreneurs to ourish across a variety of
economic sectors (Raffo, et al., 2000), elements of the entrepreneur-
ship curriculum have spread across disciplines (Levenburg, Lane, &
Schwarz, 2006) and university divisions (Katz, 2003).
Studies specically examining the impact of entrepreneurship pro-
grams on students in elds ranging from science and engineering
(Souitaris et al., 2007) to cultural industries (Raffo et al., 2000) found
that such programs encouraged and inspired students to approach their
elds with an enhanced focus on innovation and new venture creation.
However, concerns remain regarding the reach of entrepreneurship edu-
cation to all possible audiences. For example, women may be less likely
than men to pursue academic and professional avenues leading to inno-
vative entrepreneurship (de Bruin, Brush, & Welter, 2006).
Despite recent calls to expand studies of entrepreneurship to all
students, our study restricted its sample to business students due, in
large part, to their exposure to and participation in entrepreneurship
curriculum. Since the German students examined in this study were
tracked into highly structured business-related educational sequences,
we needed to conne our sample to U.S. business students both at the
undergraduate and graduate levels. Through controlling for major in our
design rather than our analysis does present limitations, such a deci-
sion allows us to better understand relationships between setting and
outcome.
Global Educational Environments
Questions about the inuence of higher education settings on stu-
dents’ intentions to innovate are not limited to the United States.

Innovative Entrepreneurship 427
Research has examined country-specic entrepreneurship education in
German-speaking Europe (Klandt, 2004); China (Wu & Wu, 2008; Qian
& Lai, 2012); France (Fayolle et al., 2006); South Africa (Shambare,
2013); and Zimbabwe (Mushipe, 2013). Overall, the ndings of these
studies suggest that while minor yet important differences exist between
cultures (e.g., small effects based on personality traits and domestic
job markets), entrepreneurship skills can be taught in all educational
settings.
As a country rich with entrepreneurship history (Schmude, Welter, &
Heumann, 2008) and entrepreneurial engagement (Audretsch, Dohse, &
Niebuhr, 2010), Germany provides an international context supportive
to our explorative line of inquiry. Important to our study, Germany has
recently experienced signicant growth in entrepreneurship education
(Klandt, 2004), with the number of entrepreneurship professors reach-
ing over 100 across the German postsecondary sphere (FGF, 2013).
Like the United States, Germany’s growth in entrepreneurship educa-
tion over the past 20 years reects the country’s commitment to higher
education as a place for teaching innovation and entrepreneurship skills
(Domke-Damonte, Faulstich, & Woodson, 2008).
Germany was further selected because, as Domke-Damonte et al.
(2008) noted in their empirical cross-cultural comparison of entrepre-
neurial orientation in the two nations, Germany and the United States
score reasonably close to one another along several of Hofstede’s
dimensions for conducting international research (p. 20). Thus, our
data includes a sample of German students who were tested and subse-
quently tracked into a multiyear business education curriculum in hopes
that we will be able to develop an initial understanding of the factors at
work in cultivating innovative entrepreneurial intentions in a non-U.S.
educational setting.
Conceptual Framework
To frame this study of educational impact, we adopted Astin’s (1993)
Input-Environment-Outcome model. Our set of input variables included:
personality, gender, age, race, and family history with entrepreneurship.
Environmental variables were broken down into descriptive educational
characteristics (e.g., G.P.A., political orientation) and higher education
experiences (e.g., enrollment in entrepreneurship class, perceptions of
the learning environment). Our outcome of this study was a student’s
intention to innovate upon completion of his/her postsecondary course
of study.
Consistent with college impact research (see Pascarella & Terenzini,
2005), this outcome measure was derived from a body of theoretical

428 The Journal of Higher Education
work examining the predictive value of student intentions (Ajzen, 1991,
2002). To operationalize intentions in the domain of innovative entre-
preneurship, we relied on Shane’s (2003) positioning of entrepreneur-
ship as a process—opportunity recognition; strategy formation; resource
acquisition; and new venture creation—which the literature supports
can be cultivated through educational experiences (Mayhew et al.,
2012). While this outcome is related to the concept of promoting entre-
preneurial change agency through actively utilizing entrepreneurship
strategies during educational experiences (Mars & Rhoades, 2012), we
position intention to innovate as a distinct outcome in itself, the realiza-
tion of which is engaging in innovative entrepreneurship upon comple-
tion of higher education.
Finally, and unlike many studies in our literature review which either
investigated the nature of relationships between individuals and entre-
preneurship outcomes directly or through incorporating broad con-
trols for academic differences (e.g., major), our study relied on Astin’s
(1993) model to empirically examine relationships between specic cur-
ricular and cocurricular practices and this outcome after controlling for
theoretically-related covariates. This conceptual framework informed
our cross-cultural data collection and analysis, providing a mechanism
by which to study the association between higher educational experi-
ences across settings and the outcome measure across academic levels
and cultural contexts. See Figure 1 for this conceptual framework.
Method
Description of Educational Settings and Sample
To understand the relationship between educational setting and our
outcome measure, our data drew from three distinct educational set-
tings. We briey describe these settings and the sample within each.
U.S. Undergraduate Sample. The U.S. undergraduate data was drawn
from students pursuing coursework in two business schools located at
research comprehensive universities, one in the Northeast and one in
the Southeast. The undergraduate students were primarily entering their
senior year of baccalaureate study. The U.S. undergraduate sample con-
sisted of 626 undergraduates from one of the two participating institu-
tions. Surveys were distributed in the spring of 2012 and the response
rate for this sample was 60%. In terms of age, the majority of the U.S.
undergraduate sample (57%) was 22–25 years old, with the bulk of the
remaining sample skewing slightly younger (36% aged 21). In addition,
52% of participants self-identied as female, 45% as Asian American,

Figu re 1. Conceptual Framework

430 The Journal of Higher Education
and 39% as white, and just over 22% of the U.S. undergraduate sample
had enrolled in an entrepreneurship course. The total sample with com-
plete and usable responses for the U.S. undergraduates was 375.
U.S. M.B.A. Sample. The U.S. M.B.A. data were drawn from stu-
dents pursuing a two-year Master’s degree at the same two business
schools located within larger research comprehensive universities. The
M.B.A. students were primarily those who had already completed some
coursework towards obtaining this credential. The U.S. M.B.A. sample
consisted of 242 M.B.A. students from one of two participating U.S.
business schools. With a 45% response rate, the majority of the M.B.A.
sample (65%) reported being in the age range of 26–30. In the M.B.A.
sample 39% of participants self-identied as female, 65% as white and
26% as Asian American, with 72% having taken an entrepreneurship
course. The total sample with complete and usable responses for the
M.B.A. students was 109.
The German Sample. The German data were drawn from students pur-
suing a ve-year business curriculum within an institution considered as
a major Research Comprehensive University. Notably, the sample from
this institution was comprised of students who were tested and subse-
quently tracked into this educational setting and consisted of 526 busi-
ness students. The response rate for this sample reached 40%. In terms
of gender, 76% of participants self-identied as male and 89% as white.
In terms of age, the majority (52%) of the German sample was 22–25
years old, with the remainder of the sample skewing slightly older (29%
aged 26–30). Finally, a large portion of students in the German sam-
ple (81%) had taken an entrepreneurship course. Table 1 summarizes
important demographic, personality, and other characteristics pertinent
to the analysis for each of the three samples.
Measures
Two measures were administered to the three sets of students. The
Ten Item Personality Measure (TIPI; Gosling, Rentfrow, & Swann,
2003) assesses personality dimensions, including Extraversion, Agree-
ableness, Conscientiousness, Emotional Stability, and Openness to New
Experiences. The TIPI was selected for its high level of reliability and
validity (Gosling et al., 2003) and to ensure comparability across sam-
ples. The second measure was an assessment loosely based on the WNS
Student Experiences Survey (WSES), developed by Pascarella (2006)
and his colleagues (Pascarella, Pierson, Wolniak, & Terenzini, 2004;
Pascarella, Wolniak, Seifert, Cruce, & Blaich, 2005). We used selected
items from the WSES, in addition to items piloted for a similar study
(Mayhew et al., 2012), to construct scales of student experiences in

TABLE 1
Summary Statistics for Variables Used in Regression Modeling
Undergraduate Sample (n = 375) MBA Sample (n = 109) German Sample (n = 211)
Variable MSD Min Max MSD Min Max MSD Min Max
Outcome
Intention to innovatea0.00 1.00 –2.99 1.84 0.00 1.00 –3.23 1.84 0.00 1.00 –2.99 1.84
Personality
Extroversiona0.00 1.00 –2.56 1.78 0.00 1.00 –2.01 1.78 0.00 1.00 –2.56 1.78
Agreeablenessa0.00 1.00 –3.18 1.91 0.00 1.00 –3.18 1.91 0.00 1.00 –3.18 1.91
Conscientiousnessa0.00 1.00 –3.27 1.19 0.00 1.00 –2.63 1.19 0.00 1.00 –3.27 1.19
Emotional stabilitya0.00 1.00 –2.50 1.62 0.00 1.00 –2.50 1.62 0.00 1.00 –2.50 1.62
Openness to experiencea0.00 1.00 –2.83 1.46 0.00 1.00 –2.11 1.46 0.00 1.00 –2.83 1.46
Descriptive
Gender
Male 0.48 0.50 0.00 1.00 0.61 0.54 0.00 1.00 0.76 0.43 0.00 1.00
Female 0.52 0.50 0.00 1.00 0.39 0.54 0.00 1.00 0.24 0.43 0.00 1.00
Race
African-American 0.05 0.21 0.00 1.00 0.05 0.21 0.00 1.00 0.00 0.00 0.00 1.00
Asian/Asian-American 0.45 0.50 0.00 1.00 0.26 0.44 0.00 1.00 0.02 0.15 0.00 1.00
Hispanic/Latino 0.12 0.33 0.00 1.00 0.13 0.34 0.00 1.00 0.02 0.14 0.00 1.00
Native American 0.00 0.07 0.00 1.00 0.01 0.10 0.00 1.00 0.00 0.00 0.00 1.00
White 0.39 0.49 0.00 1.00 0.65 0.48 0.00 1.00 0.89 0.32 0.00 1.00
Multiracial 0.04 0.20 0.00 1.00 0.04 0.19 0.00 1.00 0.08 0.27 0.00 1.00
Other 0.02 0.14 0.00 1.00 0.01 0.10 0.00 1.00 0.03 0.18 0.00 1.00
Other
Agea0.00 1.00 –1.30 4.44 0.00 1.00 –3.07 4.44 0.00 1.00 –1.30 4.44
Family exposure to entrepreneurship 0.52 0.50 0.00 1.00 0.45 0.50 0.00 1.00 0.36 0.48 0.00 1.00
(continued)

Undergraduate Sample (n = 375) MBA Sample (n = 109) German Sample (n = 211)
Variable MSD Min Max MSD Min Max MSD Min Max
Educational/political
Grade point averagea0.00 1.00 –0.36 1.76 0.00 1.00 –3.26 1.76 n/a n/a n/a n/a
Political Views 0.00 1.00 –2.16 2.58 0.00 1.00 –2.16 2.58 n/a n/a n/a n/a
Entrepreneurial class
Enroll in entrepreneurial class 0.22 0.42 0.00 1.00 0.72 0.45 0.00 1.00 0.81 0.40 0.00 1.00
Perceptions of learning environment
Challenging learning environmentsa0.00 1.00 –2.18 2.01 0.00 1.00 –2.33 2.01 0.00 1.00 –2.90 1.16
Connecting experiencesa0.00 1.00 –4.35 1.34 0.00 1.00 –3.11 1.34 0.00 1.00 –3.27 1.34
Personal relationships with facultya0.00 1.00 –2.77 1.60 0.00 1.00 –2.77 1.60 0.00 1.00 –2.77 1.60
Assessments encouraging argument developmenta0.00 1.00 –2.39 1.67 0.00 1.00 –1.72 1.67 0.00 1.00 –2.69 1.39
Assessments encouraging innovative approaches to
problem solvinga
0.00 1.00 –2.82 1.97 0.00 1.00 –2.31 1.97 0.00 1.00 –2.56 1.26
a These variables are constructed as z-scores, with mean 0 and standard deviation 1.
TABLE 1 (continued)
Summary Statistics for Variables Used in Regression Modeling

TABLE 2
Reliability for Measured Variables
Scales and Items
Intentions to Innovate (α = 0.77)a
Developing a strategy to direct your and others’ efforts with the goal of taking advantage of a new business-related opportu-
nity (such as developing a business plan)
Developing a new entity to take advantage of new business-related opportunities (for example, a team organization devoted
to the new opportunity)
Acquiring the resources necessary to take advantage of a new business-related opportunity (such as nancial resources or
expertise)
Identifying new business-related opportunities (such as a new product or service people need that is currently not available
or a more effective way of producing or running an organization)
Challenging Learning Environments (α = 0.87)a
Faculty challenge my ideas in class
Faculty ask me to point out any fallacies in basic ideas, principles, or points of view represented in the course
Faculty ask me to argue for or against a particular point of view
Faculty encourage me to explore original ideas
Faculty challenge me to think outside the box to create solutions to problems presented in class
Faculty ask me to show how a particular course concept could be applied to an actual problem or situation
Faculty ask challenging questions in class
Connecting Experiences (α = 0.81)b
My out-of-class experiences had a positive inuence on my intellectual growth and ideas
My out-of-class experiences helped me to connect what I learned in the classroom with life events
My out-of-class experiences helped me translate knowledge and understanding from the classroom into action
(continued)

Scales and Items
Personal Relationships With Faculty (α = 0.79)b
My non-classroom interactions with faculty had a positive inuence on my personal growth, attitudes, and values
My non-classroom interactions with faculty had a positive inuence on my career goals and aspirations
Since coming to this institution, I developed a close personal relationship with at least one faculty member
Assessments Encouraging Argument Development (α = 0.82)c
Exams or assignments required me to argue for or against a particular point of view and defend an argument
Exams or assignments required me to point out the strengths and weaknesses of a particular argument or point of view
Exams or assignments required me to compare or contrast topics or ideas for a course
Exams or assignments required me to write essays and/or solve problems
Assessments Encouraging Innovative Approaches to Problem Solving (α = 0.72)
Exams or assignments required me to create innovative solutions to presented problemsa
Creating solutions to problemsa
Exams or assignments required me to use course content to address a problem not presented in the coursec
Applying theories to concepts to practical problems or in new situationsd
a Items based on the following ve-point scale: Indicate how effective you believe you are in each of the following areas: 1 = extremely ineffective,
2 = somewhat ineffective, 3 = neutral, 4 = somewhat effective, 5 = extremely effective. b Items based on the following ve-point scale: Indicate
your level of agreement/disagreement with each of the followings statements: 1 = strongly disagree, 2 = somewhat disagree, 3 = neutral, 4 = some-
what agree, 5 = strongly agree. c Items based on the following ve-point scale: Indicate how often you experienced the following: 1 = never, 2 =
rarely, 3 = occasionally, 4 = often, 5 = very often. d Items based on the following ve-point scale: Select the response that best ts the frequency
with which faculty or coursework emphasized these activities: 1 = not at all, 2 = very little, 3 = some, 4 = quite a bit, 5 = very much.
TABLE 2 (continued)
Reliability for Measured Variables

Innovative Entrepreneurship 435
college and their relationship to innovative entrepreneurial intentions.
Though testing of validity and generalizability across different educa-
tional cultures is still needed, the previous study conducted by Mayhew
et al. (2012) served as an initial basis for comparison.
Conrmatory factor analyses were conducted on these scales. The
dependent measure of intention to innovate, utilized and validated in
previous research on this topic (Mayhew et al., 2012), is a theoretically-
derived (Shane, 2003) four-item scale found to hold an overall reliabil-
ity of α = 0.77 in this study and α = 0.83 in previous work (Mayhew et
al., 2012). Turning to independent variable measures, student learning
experiences within the college environment were examined by way of
ve additional constructs: challenging learning environments (α = 0.87);
connecting experiences (α = 0.81); personal relationships with faculty
(α = 0.79); assessments encouraging argument development (α = 0.82);
and assessments encouraging innovative approaches to problem solving
(α = 0.72). The scales and items are included in Table 2.
Analysis
Multilevel categorical independent variables were effect coded in
order to make the slope coefcients interpretable as deviations from an
overall level, rather than as deviations from an arbitrarily chosen refer-
ence group. In this study, only race was effect coded as a categorical
predictor (Mayhew & Simonoff, 2015). The criterion and all continu-
ous covariates were standardized so coefcients could be interpreted as
effect sizes for all models.
For all samples, we used linear regression techniques to estimate the
net effects of inputs and postsecondary environments on intentions to
innovate. Model 1 examined the outcome as a function of personality
covariates. Model 2 accounted for other demographic covariates, such
as race, gender, socioeconomic status, age, and family history with
entrepreneurship. In Model 3, with the exception of the German sample,
we added self-reported grade point average and political orientation. For
Model 4, we included our measure of course-taking, enrollment in an
entrepreneurship course. Finally, learning environment measures were
added to Model 5.
Limitations
There are numerous limitations with this dataset. First, we surveyed
students at only one time point, making it difcult to address how col-
lege inuences the development of innovative entrepreneurial intentions
and whether these intentions remain over time.

Second, given the number of variables used in the regression models,
model estimates should be interpreted cautiously, in particular for the
small M.B.A. sample. Although likely to increase Type II error, sug-
gesting that results are nonsignicant when they might not be, the small
M.B.A. sample was important to keep separated from the undergraduate
sample in order to address the distinctive nature of the educational set-
tings examined for this study.
Third, this study emerged as a second step in an ongoing larger
research effort designed to explore ties between different educational
settings and innovative entrepreneurial intentions among postsecond-
ary students. We attempted to administer surveys consistently across all
samples but important differences arose with respect to the set of pre-
dictors included. Notably, the political orientation variable was omit-
ted from the German analysis as differences in political systems and
resultant linguistic and cultural challenges emerged when attempting to
include this variable in our analysis.
Fourth, as an exploratory study examining a newly-emerging idea,
innovative entrepreneurship, this effort was intended to broadly identify
educational practices and their relationship to innovative entrepreneur-
ial intentions across cultures. These data were collected to determine if
results differed cross-culturally. Additional empirical efforts are needed
to fully explore cross-cultural differences and describe why certain edu-
cational practices inuence innovative entrepreneurial intentions within
certain cultural contexts.
Finally, we recognize that though we attempted to capture as many
input and environmental characteristics as possible, the parameters of
this study did not permit us to account for students outside of the busi-
ness major. Furthermore, we were unable to include in our models any
potential effect that undergraduate major may have had on M.B.A. stu-
dent’s intentions. These are notable limitations, as they speak to our
rm recognition and belief that students across the curriculum—espe-
cially those pursuing STEM elds (see Kauffman Foundation, 2013;
Mars, et al., 2008)—stand to benet extensively from teaching practices
and learning environments that cultivate innovation.
Results
Model Summary Estimates
Model summary estimates are provided in Table 3 for each of the
three samples. By providing the adjusted R2 and standard error of the
estimate (where ̂σ is the standard deviation of the error term) for each
436 The Journal of Higher Education436 The Journal of Higher Education

TABLE 3
Summary of Model Fitting for Least Squares Regressions with Intention to Innovate Response Variable
Undergraduate Sample (n = 375) MBA Sample (n = 109) German Sample (n = 211)
Added covariates R2
adj ̂σ AIC F p R2
adj ̂σ AIC F p R2
adj ̂σ AIC F p
Model 1 Personality 0.06 1.11 1150.0 0.09 0.96 307.4 0.23 0.75 487.2
Model 2 Descriptive 0.12 1.07 1134.7 3.72 < 10-3 0.08 0.96 316.3 0.80 0.63 0.22 0.76 497.0 0.74 0.66
Model 3 Educational/political 0.15 1.06 1122.7 7.80 < 10-3 0.08 0.96 317.5 1.18 0.31 n/a n/a n/a n/a n/a
Model 4 Entrepreneurial course 0.16 1.05 1119.8 4.64 0.03 0.07 0.97 319.3 0.24 0.62 0.23 0.75 495.0 3.68 0.06
Model 5 Perceptions of learning
environment
0.19 1.03 1111.5 3.53 < 10-2 0.15 0.92 313.0 2.80 0.02 0.29 0.72 484.0 4.01 < 10-2
Note. F statistics refer to partial F-tests comparing t to the model immediately above.

model, more direct comparisons across samples could be inferred. For
the U.S. undergraduate sample, inserting each additional set of predic-
tors generated useful predictive ability as evidenced by the AIC val-
ues described in Table 3. For the M.B.A. sample, with the exception
of personality and learning environment covariates reecting network-
ing opportunity, AIC values showed that the vast majority of variables
added no predictive power to explaining innovative entrepreneurial
intentions. The AIC values in the German sample indicated that per-
sonality variables were the most important determinants of intention to
innovate, though adding school environmental variables, such as tak-
ing an entrepreneurship class, connectedness, and personal relationships
with faculty, produced additional predictive power. Table 4 provides
coefcients from each of the model ts across all three samples.
U.S. Undergraduate Setting
In Model 1, intention to innovate was explored as a function of
ve personality covariates: extraversion, agreeability, conscientious-
ness, emotional stability, and openness to new experiences. Personal-
ity explained 6.0% of the variance in the criterion. Extroverted students
were more likely to intend to innovate ( ̂
β = .18, p < .01) along with
those who were conscientious ( ̂
β = .11, p < .10), open to new experi-
ences ( ̂
β = .12, p < .10), and less agreeable ( ̂
β = –.15, p < .06).
Adding descriptive variables to the model (Model 2) explained an
additional and signicant 6.0% of variance in the criterion. With regard
to self-identied race, compared with all students, Asian-American stu-
dents were signicantly more likely to intend to innovate relative to all
other self-identied racial groups. Gender was also signicant, with
females signicantly less likely than males to express innovative entre-
preneurial intentions ( ̂
β = –.30, p < .05). Finally, students with a parent
who started a business were signicantly more likely to intend to inno-
vate than those with less exposure ( ̂
β = –.36, p < .01).
For Model 3, self-reported grade point averages and political ori-
entation were included and an additional and signicant 3.0% of the
criterion was explained. Although G.P.A. was only marginally related
to innovative entrepreneurial intentions, political orientation was sig-
nicantly related, with students holding more conservative views were
more likely to express intention to innovate ( ̂
β = .19, p < .001).
Next we added an indicator of whether the respondent had ever taken
a class devoted to entrepreneurship (Model 4). Taking an entrepreneur-
ship class was associated with higher intention to innovate and was sta-
tistically signicant ( ̂
β = .14, p < .05). This one variable explained an
additional 1.0% of the variance in the criterion.
438 The Journal of Higher Education

The full model, Model 5, included covariates measuring educational
practices and perceptions of the learning environment at the institution.
These covariates added a signicant 3.0% of variation explanation to
the intention to innovate criterion. Despite the additional power, only
the “assessments that encourage argument development” factor was
marginally signicant at the 10% level ( ̂
β = .14, p < .10).
M.B.A. Setting
For the M.B.A. sample, Model 1 explained 9.0% of variation in the
criterion. The only personality covariate signicantly related to inten-
tion to innovate was openness to new experiences ( ̂
β = .33, p < .01).
Adding descriptive variables to the model (Model 2), self-reported
grade point average and political orientation (Model 3), and course-tak-
ing behavior (Model 4) failed to signicantly explain respective propor-
tions of variance in the criterion.
Model 5 included the covariates measuring educational practices and
perceptions of the learning environment. Taken together, these covari-
ates explained an additional 6.0% of the variation in the criterion; only
the variable capturing connecting experiences was statistically signi-
cant ( ̂
β = .26, p < .05), which suggests that M.B.A. students were per-
haps the most interested in networking and seeking opportunities to
connect with faculty.
German Setting
For the German sample, the relationship between personality covari-
ates and innovative entrepreneurial intentions was much stronger than
with the U.S. undergraduate sample. Model 1 explained 23.0% of the
variance in the criterion, almost quadruple the amount explained in the
U.S. undergraduate sample. Extroverted German students were more
likely to intend to innovate ( ̂
β = .18, p < .01) along with those who were
less agreeable ( ̂
β = –.12, p < .05). Unlike in the U.S. undergraduate
sample, all personality covariates were statistically signicant as Ger-
man students who were more conscientious ( ̂
β = .19, p < .01), more
open to new experiences ( ̂
β = .22, p < .001), and more emotionally sta-
ble ( ̂
β = .15, p < .01) were all signicantly more likely to intend to
innovate.
Adding descriptive variables to the model (Model 2) provided no
additional explanatory power of the variance in the criterion. In contrast
with the U.S. undergraduate sample, there was no relationship between
intention to innovate and race, gender, or family history with entrepre-
neurship. As noted earlier, grade point average and political orientation
Innovative Entrepreneurship 439

TABLE 4
Parameter Estimates for Hierarchical Models
Undergraduate Sample (n = 375) MBA Sample (n = 109) German Sample (n = 211)
Model Model Model
Construct Variable
1
Beta
(SE)
2
Beta
(SE)
3
Beta
(SE)
4
Beta
(SE)
5
Beta
(SE)
1
Beta
(SE)
2
Beta
(SE)
3
Beta
(SE)
4
Beta
(SE)
5
Beta
(SE)
1
Beta
(SE)
2
Beta
(SE)
3
Beta
(SE)
4
Beta
(SE)
5
Beta
(SE)
Personality Extroversion 0.18**
(0.06)
0.21**
(0.06)
0.20**
(0.06)
0.19**
(0.06)
0.15*
(0.06)
0.07
(0.90)
0.11
(0.10)
0.05
(0.11)
0.10
(0.10)
0.03
(0.10)
0.18**
(0.06)
0.17**
(0.06)
n/a 0.16**
(0.06)
0.13*
(0.06)
Agreeability –0.15*
(0.06)
–0.10
(0.06)
–0.07
(0.06)
–0.07
(0.06)
–0.10
(0.06)
0.08
(0.09)
0.09
(0.09)
0.16
(0.11)
0.11
(0.10)
0.00
(0.11)
–0.12*
(0.06)
–0.10
(0.06)
n/a –0.10
(0.06)
–0.10
(0.06)
Conscientiousness 0.11
(0.06)
0.17**
(0.06)
0.19**
(0.07)
0.20**
(0.07)
0.18**
(0.07)
0.08
(0.10)
0.11
(0.11)
0.09
(0.13)
0.11
(0.11)
0.14
(0.11)
0.19**
(0.05)
0.21***
(0.06)
n/a 0.21***
(0.06)
0.19**
(0.06)
Emotional stability 0.06
(0.06)
0.02
(0.06)
0.01
(0.06)
0.01
(0.06)
0.04
(0.06)
0.07
(0.10)
0.03
(0.11)
–0.03
(0.14)
0.05
(0.11)
0.00
(0.11)
0.15**
(0.06)
0.12*
(0.06)
n/a 0.11.
(0.06)
0.08
(0.06)
Openness to experience 0.12
(0.06)
0.11
(0.06)
0.10
(0.06)
0.10
(0.06)
0.09
(0.06)
0.33**
(0.11)
0.29**
(0.11)
0.31*
(0.13)
0.29*
(0.12)
0.25*
(0.11)
0.22***
(0.06)
0.23***
(0.06)
n/a 0.23***
(0.06)
0.20***
(0.06)
Descriptive African-Americana0.15
(0.34)
0.01
(0.34)
0.05
(0.33)
0.16
(0.33)
5.34
(3.62)
4.39
(3.64)
5.25
(3.70)
2.25
(3.78)
–1.09
(1.65)
n/a –1.16
(1.64)
–1.12
(1.60)
Asiana0.62*
(0.27)
0.58*
(0.26)
0.55*
(0.26)
0.62*
(0.26)
5.72
(3.55)
4.92
(3.57)
5.56
(3.62)
2.59
(3.68)
0.22
(0.46)
n/a 0.37
(0.46)
0.31
(0.45)
Bi/Multiraciala–0.28
(0.48)
–0.20
(0.47)
–0.25
(0.47)
–0.03
(0.47)
6.04
(3.79)
5.13
(3.81)
6.01
(3.88)
3.14
(3.90)
0.44
(0.39)
n/a 0.42
(0.38)
0.33
(0.37)
Latina0.17
(0.28)
0.10
(0.28)
0.08
(0.27)
0.11
(0.27)
5.74
(3.56)
4.57
(3.59)
5.56
(3.63)
2.25
(3.69)
–0.18
(0.57)
n/a –0.15
(0.57)
–0.11
(0.55)
Native Americana,b 0.23
(1.38)
0.77
(1.37)
0.80
(1.36)
0.26
(1.35)
n/a n/a n/a n/a n/a n/a n/a n/a
Whitea0.08
(0.27)
0.06
(0.26)
0.05
(0.26)
0.12
(0.26)
5.91
(3.55)
4.94
(3.57)
5.78
(3.63)
2.64
(3.69)
0.27
(0.30)
n/a 0.26
(0.30)
0.26
(0.29)
Female –0.30*
(0.12)
–0.30*
(0.12)
–0.30*
(0.12)
–0.32**
(0.12)
–0.27
(0.21)
–0.43
(0.23)
–0.31
(0.22)
–0.32
(0.21)
–0.21
(0.13)
n/a –0.19
(0.13)
–0.20
(0.13)
Age 0.00
(0.12)
–0.02
(0.11)
–0.01
(0.11)
–0.02
(0.11)
0.00
(0.11)
–0.10
(0.13)
–0.01
(0.11)
0.03
(0.11)
0.03
(0.05)
n/a 0.04
(0.05)
0.03
(0.05)
No family exposure to
entrepreneurship
–0.36**
(0.12)
–0.39***
(0.11)
–0.38***
(0.11)
–0.36**
(0.11)
0.05
(0.20)
0.13
(0.23)
0.09
(0.21)
0.03
(0.20)
–0.07
(0.11)
n/a (0.06)
(0.11)
–0.04
(0.11)
Educational/ political High grade point average –0.11
(0.06)
–0.09
(0.06)
–0.10
(0.06)
–0.18
(0.12)
–0.15
(0.11)
–0.11
(0.11)
n/a n/a
Politically conservative 0.19***
(0.06)
0.19***
(0.05)
0.19***
(0.05)
0.06
(0.12)
0.05
(0.11)
–0.02
(0.11)
n/a n/a
Entrepreneurial class Enroll in entrepreneurial class 0.14*
(0.07)
0.12
(0.07)
–0.06
(0.11)
–0.03
(0.11)
0.13
(0.07)
0.13
(0.07)
Perceptions
of learning
environment
Challenging learning environments 0.12
(0.09)
0.19
(0.15)
–0.13
(0.09)
Connecting experiences 0.02
(0.07)
0.26*
(0.12)
0.20**
(0.07)
Assessments encouraging argument
development
0.14
(0.08)
–0.29
(0.17)
0.10
(0.07)
Assessments encouraging
innovative approaches to
problem–solving
–0.01
(0.08)
0.21
(0.15)
0.00
(0.08)
Personal relationships with faculty 0.04
(0.07)
0.13
(0.13)
0.13*
(0.06)
a Effect coding; omitted category irrelevant. b Variable omitted in the German and MBA models because variable was perfectly correlated with the
“other” race variable.
*p < .05. **p < .01. ***p < .001.

TABLE 4
Parameter Estimates for Hierarchical Models
Undergraduate Sample (n = 375) MBA Sample (n = 109) German Sample (n = 211)
Model Model Model
Construct Variable
1
Beta
(SE)
2
Beta
(SE)
3
Beta
(SE)
4
Beta
(SE)
5
Beta
(SE)
1
Beta
(SE)
2
Beta
(SE)
3
Beta
(SE)
4
Beta
(SE)
5
Beta
(SE)
1
Beta
(SE)
2
Beta
(SE)
3
Beta
(SE)
4
Beta
(SE)
5
Beta
(SE)
Personality Extroversion 0.18**
(0.06)
0.21**
(0.06)
0.20**
(0.06)
0.19**
(0.06)
0.15*
(0.06)
0.07
(0.90)
0.11
(0.10)
0.05
(0.11)
0.10
(0.10)
0.03
(0.10)
0.18**
(0.06)
0.17**
(0.06)
n/a 0.16**
(0.06)
0.13*
(0.06)
Agreeability –0.15*
(0.06)
–0.10
(0.06)
–0.07
(0.06)
–0.07
(0.06)
–0.10
(0.06)
0.08
(0.09)
0.09
(0.09)
0.16
(0.11)
0.11
(0.10)
0.00
(0.11)
–0.12*
(0.06)
–0.10
(0.06)
n/a –0.10
(0.06)
–0.10
(0.06)
Conscientiousness 0.11
(0.06)
0.17**
(0.06)
0.19**
(0.07)
0.20**
(0.07)
0.18**
(0.07)
0.08
(0.10)
0.11
(0.11)
0.09
(0.13)
0.11
(0.11)
0.14
(0.11)
0.19**
(0.05)
0.21***
(0.06)
n/a 0.21***
(0.06)
0.19**
(0.06)
Emotional stability 0.06
(0.06)
0.02
(0.06)
0.01
(0.06)
0.01
(0.06)
0.04
(0.06)
0.07
(0.10)
0.03
(0.11)
–0.03
(0.14)
0.05
(0.11)
0.00
(0.11)
0.15**
(0.06)
0.12*
(0.06)
n/a 0.11.
(0.06)
0.08
(0.06)
Openness to experience 0.12
(0.06)
0.11
(0.06)
0.10
(0.06)
0.10
(0.06)
0.09
(0.06)
0.33**
(0.11)
0.29**
(0.11)
0.31*
(0.13)
0.29*
(0.12)
0.25*
(0.11)
0.22***
(0.06)
0.23***
(0.06)
n/a 0.23***
(0.06)
0.20***
(0.06)
Descriptive African-Americana0.15
(0.34)
0.01
(0.34)
0.05
(0.33)
0.16
(0.33)
5.34
(3.62)
4.39
(3.64)
5.25
(3.70)
2.25
(3.78)
–1.09
(1.65)
n/a –1.16
(1.64)
–1.12
(1.60)
Asiana 0.62*
(0.27)
0.58*
(0.26)
0.55*
(0.26)
0.62*
(0.26)
5.72
(3.55)
4.92
(3.57)
5.56
(3.62)
2.59
(3.68)
0.22
(0.46)
n/a 0.37
(0.46)
0.31
(0.45)
Bi/Multiraciala–0.28
(0.48)
–0.20
(0.47)
–0.25
(0.47)
–0.03
(0.47)
6.04
(3.79)
5.13
(3.81)
6.01
(3.88)
3.14
(3.90)
0.44
(0.39)
n/a 0.42
(0.38)
0.33
(0.37)
Latina 0.17
(0.28)
0.10
(0.28)
0.08
(0.27)
0.11
(0.27)
5.74
(3.56)
4.57
(3.59)
5.56
(3.63)
2.25
(3.69)
–0.18
(0.57)
n/a –0.15
(0.57)
–0.11
(0.55)
Native Americana,b 0.23
(1.38)
0.77
(1.37)
0.80
(1.36)
0.26
(1.35)
n/a n/a n/a n/a n/a n/a n/a n/a
Whitea0.08
(0.27)
0.06
(0.26)
0.05
(0.26)
0.12
(0.26)
5.91
(3.55)
4.94
(3.57)
5.78
(3.63)
2.64
(3.69)
0.27
(0.30)
n/a 0.26
(0.30)
0.26
(0.29)
Female –0.30*
(0.12)
–0.30*
(0.12)
–0.30*
(0.12)
–0.32**
(0.12)
–0.27
(0.21)
–0.43
(0.23)
–0.31
(0.22)
–0.32
(0.21)
–0.21
(0.13)
n/a –0.19
(0.13)
–0.20
(0.13)
Age 0.00
(0.12)
–0.02
(0.11)
–0.01
(0.11)
–0.02
(0.11)
0.00
(0.11)
–0.10
(0.13)
–0.01
(0.11)
0.03
(0.11)
0.03
(0.05)
n/a 0.04
(0.05)
0.03
(0.05)
No family exposure to
entrepreneurship
–0.36**
(0.12)
–0.39***
(0.11)
–0.38***
(0.11)
–0.36**
(0.11)
0.05
(0.20)
0.13
(0.23)
0.09
(0.21)
0.03
(0.20)
–0.07
(0.11)
n/a (0.06)
(0.11)
–0.04
(0.11)
Educational/ political High grade point average –0.11
(0.06)
–0.09
(0.06)
–0.10
(0.06)
–0.18
(0.12)
–0.15
(0.11)
–0.11
(0.11)
n/a n/a
Politically conservative 0.19***
(0.06)
0.19***
(0.05)
0.19***
(0.05)
0.06
(0.12)
0.05
(0.11)
–0.02
(0.11)
n/a n/a
Entrepreneurial class Enroll in entrepreneurial class 0.14*
(0.07)
0.12
(0.07)
–0.06
(0.11)
–0.03
(0.11)
0.13
(0.07)
0.13
(0.07)
Perceptions
of learning
environment
Challenging learning environments 0.12
(0.09)
0.19
(0.15)
–0.13
(0.09)
Connecting experiences 0.02
(0.07)
0.26*
(0.12)
0.20**
(0.07)
Assessments encouraging argument
development
0.14
(0.08)
–0.29
(0.17)
0.10
(0.07)
Assessments encouraging
innovative approaches to
problem–solving
–0.01
(0.08)
0.21
(0.15)
0.00
(0.08)
Personal relationships with faculty 0.04
(0.07)
0.13
(0.13)
0.13*
(0.06)
a Effect coding; omitted category irrelevant. b Variable omitted in the German and MBA models because variable was perfectly correlated with the
“other” race variable.
*p < .05. **p < .01. ***p < .001.

442 The Journal of Higher Education
data were not collected for the German sample and thus Model 3 was
not constructed for this sample.
For Model 4, we added an indicator of whether the respondent had
ever taken a class devoted to entrepreneurship. Like the U.S. under-
graduate sample, taking an entrepreneurship class was associated with
higher intention to innovate. Interestingly, the responses were very sim-
ilar between the German sample and the U.S. sample with respect to
effect sizes and statistical signicance ( ̂
β = .13, p < .10).
For the German sample, Model 5 included the same covariates mea-
suring educational practices and perceptions of the learning environ-
ment. These covariates added 6.0% of variation explanation to the
intention to innovate criterion, and experiences connecting with faculty
( ̂
β = .20, p < .01) and the development of personal relationships with
faculty ( ̂
β = .13, p < .05) were both statistically signicant.
Discussion
This research explores the relationship between education experi-
ences and innovative entrepreneurial intentions among students in three
distinctive college settings. Resonating with previous work suggesting
that innovative entrepreneurial intentions may lie at the nexus of nature
and nurture (Nilsson, 2012), we offer that innovative entrepreneurial
intentions are indeed complex and nuanced, involving certain personal-
ity traits, social and cultural capital associated with family history of
entrepreneurship, and distinctive educational experiences.
Participation in both the German and the American settings positively
inuenced innovative entrepreneurial intentions. Within the German
system, where students are tracked to a greater extent into disciplines
based upon prior academic performance (see Schnepf, 2002), educators
can leverage structured course taking patterns and learning environ-
ments to promote these intentions. Similarly, educators in the American
undergraduate setting can provide students opportunities to explore new
subject areas and to incorporate a wide variety of ideas and perspectives
through engagement in both the curriculum (Astin, 1993) and cocur-
riculum (Kuh, 2008). The good news across results from samples in this
study is that innovative entrepreneurial intentions can be cultivated by
educators, regardless of the many differences in traits and experiences
that students across cultures bring to the college campus.
What might account for the observed differences between students in
the undergraduate and M.B.A. setting? In general, undergraduate educa-
tional settings emphasize acquiring and demonstrating mastery of estab-
lished knowledge (Pascarella & Terenzini, 2005). Thus, undergraduates

Innovative Entrepreneurship 443
are by nature perhaps more receptive to classroom learning. Graduate
students, on the other hand, frequently spend more time outside of the
classroom coming up with new ideas, participating in research, and
learning from peers (Flores-Scott & Nerad, 2012). An alternative expla-
nation of this nding may be that students in the M.B.A. setting, due to
their self-selection into a graduate business program and their previous
work experience in professional areas related to business, are engaging
in a process of enacting a predisposition toward innovation rather than
cultivating intentions through participation in curricular and cocurricu-
lar educational practices. Of course, longitudinal studies are needed to
substantiate such a claim.
Personality played an important role in predicting intentions to inno-
vate, albeit to varying degrees across educational settings. The portion
of the variance explained by personality traits reached 0.23 for students
in the German setting, 0.06 for students in the American undergradu-
ate setting and 0.09 for students in the M.B.A. setting. Unlike German
students, who enroll into a discipline-specic university experience
based on early testing and tracking, American students are typically
given more opportunities to explore different pathways after enrolling
in any given college or university. As a result, the U.S. students might
be more likely to get “pulled” into innovative entrepreneurship based on
a variety of environmental factors rather than “pushed” in based upon
preexisting input characteristics (Vanevenhoven, 2013), like personal-
ity traits. Perhaps, the American system of higher education might hold
distinctive potential to produce heterodox and unanticipated results by
way of student innovation?
Specic personality characteristics differentially inuenced the inno-
vative entrepreneurial intentions among samples in this study. Such
intentions were statistically related to a personality that is both extro-
verted and conscientious for U.S. undergraduate students; a personal-
ity that is extroverted, conscientious, and open to new experiences
for German students; and a personality that was open to new experi-
ences for U.S. M.B.A. students. For education settings where students
are exposed to higher education for the rst time (i.e., U.S. under-
graduate and German), it is perhaps unsurprising that individuals with
extroverted, conscientious personalities might both select educational
experiences that promote innovation as well as further cultivate innova-
tive entrepreneurial intentions through acting in accordance with these
personality attributes (Obschonka et al., 2012). Often, commencing
entrepreneurial activities may involve constructing partnerships with
unfamiliar others, demonstrating the value of his/her idea to potential

444 The Journal of Higher Education
investors, and actively raising capital—experiences that conscientious
extroverts might actively seek.
Interestingly, openness to new experiences was statistically related to
innovative entrepreneurial intentions for both M.B.A. and German stu-
dents. This result suggests that certain personality traits, like openness
to new experiences, might be related to choice of discipline, as both
M.B.A. and tracked German students demonstrate a more focused com-
mitment to subject-matter learning. Linking personality considerations
with choice of major has been examined, at least tangentially, by higher
education scholars who use typologies to describe and explain student
decision-making, often regarding expectations of college (Pike, 2006a,
2006b), choice of major (Larson, et al., 2010; Pike, 2006a) and career
decisions (Neumann, Olitsky, & Robbins, 2009; Pike, 2006b; Wang,
Jome, Hasse, & Bruch, 2006).
Another common nding shared by M.B.A. and German students
involved their perceptions of the learning environment, with both sam-
ples indicating that innovative entrepreneurial intentions were related to
participation in curricular and cocurricular experiences that connected
subject-matter learning to real-world applications. With problem-based
inquiry emerging as a pedagogical choice among engineering educators
(see Mantri, 2013), it is intriguing that students in this study relate inno-
vative entrepreneurial intentions to educational practices that connect
the theoretical with the practical, the hypothetical with the pragmatic,
the problem with the solution.
Additionally, in the German setting, results indicated that innovative
entrepreneurial intentions were associated with personal experiences
with faculty. Specically, developing a close personal relationship with
at least one faculty member outside-of-the classroom was related to
innovative entrepreneurial intentions among German students. Ubiqui-
tous among ndings in the higher education literature (see Pascarella &
Terenzini, 2005), the relationship between faculty and students seems to
once again emerge as important in explaining the relationship between
education experience and student outcomes. However, this study adds a
new dimension to this body of work, as out of classroom close relation-
ships with faculty might promote aspects of mentorship (see Reddick,
Grifn, & Cherwitz, 2011) or perhaps serve as a proxy for professional
networking (see Baker & Lattuca, 2010), especially among tracked Ger-
man students.
Our analysis further found signicant relationships between several
input characteristics—race, political identication, gender, and family
history with entrepreneurship—and innovative entrepreneurial inten-
tions, especially among the U.S. undergraduate sample. Conrming

Innovative Entrepreneurship 445
earlier ndings (Mayhew et al., 2012), undergraduate students identify-
ing as Asian, as well as students identifying as politically conservative,
were more likely than peers to demonstrate innovative entrepreneur-
ial intentions. This said, emerging literature on students identifying as
Asian or Asian-American suggest that this category might be too gross
an indicator to make meaning about this racial subgroup, as ethnicities
within the Asian and Asian-American categories (e.g., Vietnamese com-
pared to Chinese students) often differ in their college perceptions and
experiences (see Museus, 2009; Teranishi, 2010). Further research that
disaggregates this subgroup would lend a greater level of clarity (Stage,
2007) and contribute greatly to additional conversations concerning the
role racial and ethnic differences might play in cultivating innovative
entrepreneurial intentions.
Turning to political identication, U.S. undergraduate conservative
students are more likely to intend to innovate than more liberal stu-
dents, even after controlling for personality and major. Perhaps, this
result reects acquired cultural and social capital conservative students
receive from their caregivers. Beyond political identications, extensive
conversations about these nuanced forms of capital abound in the litera-
ture (see Yosso, 2005) and may be too complicated to be measured by
a single item indicator relating to political forms of capital. That said,
questions about the relationship between political ideology and innova-
tive entrepreneurial intentions are interesting and may serve as fruitful
lines of future inquiry.
Females in the U.S. undergraduate sample were signicantly less
likely to report innovative entrepreneurial intentions than males. One
explanation may be a reection of the sample itself: while the U.S.
undergraduate sample contained slightly more females (52%) than
males (48%), the M.B.A. and German samples had a disproportionate
representation of males (61% and 76% respectively). Such gender dis-
parity in both the sample and the ndings could potentially be related
to societal factors—including an historical legacy of excluding women
from business education until recent decades—as well as a paucity of
research on the topic of how to provide education that specically pro-
motes female entrepreneurship (see de Bruin, Brush, & Welter, 2006;
Mirjana, 2013). This study provides concerning evidence that gender
differences exist in connection with innovative entrepreneurship; imag-
ine the explosion of new processes and products that would emerge in a
world where half the population was socialized to believe that it could
and should innovate.
Finally, for U.S. undergraduate students, family history of entrepre-
neurship was related to innovative entrepreneurial intentions. While

446 The Journal of Higher Education
research has demonstrated that parental employment informs an indi-
vidual’s career development (see Bergen, 2006), this study’s ndings
specic to entrepreneurship might reect an increased level of social
and cultural capital regarding the specic tasks (e.g., opportunity iden-
tication, fundraising) required to establish protable entrepreneurial
ventures (Greve & Salaff, 2003; Kim & Aldrich, 2005). In tandem, this
result may also serve as an indicator of perceived parental support in a
student’s intention to pursue a potentially riskier path from college to
career.
Implications
As scholarship related to innovative entrepreneurial intentions as an
outcome of higher education evolves, we believe that our ndings hold
signicant implications for theory, research, and practice. We turn now
to a discussion of each.
Theoretical
Theoretically, this study begins to lay the foundation for understand-
ing the relationships among different forms of entrepreneurship and
their potential contribution to an increasingly diverse and global society.
What is the value of entrepreneurship if the new process or product only
benets the innovator? While educators and business leaders continue
to discuss the importance of social entrepreneurship (Frank, 2008),
they often fail to make the distinction between replicative and innova-
tive entrepreneurial forms as parts of these conversations (see Baumol,
2010). Perhaps the ideal form of entrepreneurship that serves a global
citizenry is innovative social entrepreneurship, dened as bringing new
processes and products to market that add direct value to all members of
society, including anonymous others.
This study informs conversations concerning the relationship between
nature and nurture, between personality and experience. Cultivating
innovative entrepreneurial intentions appears to involve both, as each
is statistically related to students’ intentions to bring new processes and
products to market. This nding disrupts Thiel’s position (Wieder, 2011)
– that participation in higher education may not be conducive to fos-
tering innovation—by suggesting that both personality and structured
higher educational experiences contribute to cultivating innovation
potential among college-aged students.
A third theoretical implication of this work is its potential to inform
understandings of student career development. To the extent that higher
education participation helps prepare students to enter the workforce

Innovative Entrepreneurship 447
by acquiring human capital that is responsive to labor market needs
(Becker, 1993; Robst, 2007; Roksa & Levey, 2010), new theory should
consider where innovative entrepreneurship ts into career trajectories
(Sinclair, 2008). Theoretical perspectives could also incorporate con-
temporary career development frameworks, such as the happenstance
learning theory (Krumboltz, 2009) and the chaos theory of careers
(Pryor & Bright, 2011); both consider career development not as pro-
gression towards a xed point but rather as a dynamic and ongoing
process beneted by embracing an openness to new experiences and
change.
Research
Research on innovative entrepreneurship is not complete. Based upon
our literature review and results, we believe several avenues for future
exploration emerge from our ndings. First, as this study examined col-
lege-going and its inuence on innovative entrepreneurial intentions, a
logical next step would be to understand how intentions predict entre-
preneurial behaviors after graduation. We believe that a multi-institu-
tional, longitudinal study designed to assess students at multiple time
points during college (e.g., beginning of rst year, end of rst year,
senior year) and again after graduation (e.g., ve years postcollege, ten
years postcollege) could provide deeper insight into which aspects of
learning environments may encourage individuals to develop and act
upon innovative entrepreneurial intentions.
Second, as more research continues to be conducted in the area of
entrepreneurship, more nuanced approaches to creating and rening an
entrepreneurial taxonomy are needed (Shockley et al., 2008). How does
innovative entrepreneurship differ from replicative entrepreneurship?
From novel forms of social entrepreneurship? How do entrepreneurs
envision differences in bringing value-added and new processes and
products to a global market? Is the value in the innovation? Or in the
individuals the innovation serves?
Third, higher education scholars need to continue challenging con-
versations about the value, understanding, measurement, and operation
of college major—especially at the graduate level. As this study sug-
gests, especially among students in the German sample and M.B.A. stu-
dents, outcomes related to participation in graduate or tracked higher
education experiences may be more a function of engagement in social
networking opportunities than of course sequencing per se. With more
students attending graduate school in the U.S. now than during any
other era (National Center for Education Statistics, 2013), higher edu-
cation scholars need to continue to disrupt notions of major and school

448 The Journal of Higher Education
choice in order to have a more accurate understanding of student gains
as a result of identication with and participation in a specic set of
educational experiences.
Fourth, additional work that appropriately “cut[s] across national
boundaries” (Shahjahan & Kezar, 2013, p. 24) remains as scholars
consider the relationship between education experiences and cross-
cultural dimensions of innovative entrepreneurship. Though Moriano
and colleagues (2012) have signicantly contributed to this conversa-
tion through nding that the application of TPB to entrepreneurial inten-
tions held across cultures, future research should account for the ways
in which differences in educational systems might promote or hinder
innovation. As such research continues, we believe this scholarship
not only holds additional opportunities to further test the validity of
empirical survey instruments (e.g., TIPI) in international educational
environments, but will continue to expand the reach of research on
entrepreneurship into other education systems.
Fifth, additional insight could be gained by conducting research
using practicing entrepreneurs as the unit of analysis. Such work would
endeavor to determine, albeit retrospectively, how either participating
or not participating in postsecondary education informed entrepreneurs’
career trajectories, types of products or services launched, fundraising
networks, and business development strategies.
Sixth, this research drew its conclusions in part by including per-
sonality covariates into its statistical modeling. Based on our success
with this approach, and its ability to contribute to explaining variance
on other measures involving college students (e.g., Logue, Lounsbury,
Gupta, & Leong, 2007), we surmise that including personality covari-
ates in future research on the relationships between college-going and
targeted student outcomes may prove benecial to scholarship on col-
lege student learning and development.
Practice
Though our analysis was limited to business students, we fully sup-
port the notion that entrepreneurship education stands to benet from
increased interdepartmental learning (Kauffman Foundation, 2013). For
instance, science students might benet from learning how to raise cap-
ital while business students stand to gain by learning enough science
to be able to rigorously vet start-up technologies (W. J. Baumol, per-
sonal communication, July 3, 2014). We argue that providing students
exposure to these nonmajor content areas may spur the development of
innovative entrepreneurial intentions and further bring entrepreneurial
lines of inquiry out of the business silo and into the curriculum for more

Innovative Entrepreneurship 449
students (Kauffman Foundation, 2013). On the cocurricular side, we
believe that institutions wishing to promote the development of inno-
vative entrepreneurial intentions should strive to structure out-of-class
experiences that leverage high-impact practices (Kuh, 2008) in the ser-
vice of promoting learning environments that connect students to others
in the academic community and challenge them to think in different and
creative ways (James & Brookeld, 2014).
In addition, care and attention must be paid to individual differences
when constructing curricular and cocurricular interventions aimed at
promoting innovation. With regard to race/ethnicity, political identica-
tion, and gender, it is important that all students be provided with oppor-
tunities to involve themselves in educational activities that promote the
cultivation of innovative entrepreneurial intentions. Institutions speci-
cally seeking to close the gender gap could provide resources such as
faculty mentorship and peer learning specically geared towards pro-
moting women’s involvement, as an example, in entrepreneurship edu-
cation and exploration of entrepreneurial career pathways.
Conclusion
Though we continue to offer the observation that innovative entrepre-
neurship contributes to the general welfare and to reduction of poverty
and inequality, we have no intention of implying that it is always ben-
ecial to humanity as a whole and that it is never misused. Innovative
entrepreneurship—across many spheres, including but not limited to the
technological—has been and will continue to be employed to benet
a limited section of the population. Nevertheless, throughout much of
the industrialized portions of the world, innovative entrepreneurship has
improved living standards, levels of education, and health care for the
general population (Baumol, 2010). Indeed, this improvement has gone
far beyond anything that could have been imagined earlier.
Perhaps the primary source for unlocking this innovation potential is
through student participation in higher education. While this research is
sensitive to concerns pertaining to academic capitalism and the emer-
gence of academic entrepreneurial cultures (see Slaughter & Rhoades,
2004), we nonetheless believe that positioning innovative entrepreneur-
ship intentions as central to the broader higher education agenda holds
numerous benets not only for students themselves, but also for the
increasingly complex societies that stand to benet from graduates able
to recognize opportunities, address common problems, and take action
in the direction of new solutions.

450 The Journal of Higher Education
Note
The authors gratefully acknowledge the Ewing Marion Kauffman Foundation for its
generous support in the funding of this research project.
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