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Unicorns, Gazelles, and Other Distractions on the Way to Understanding Real Entrepreneurship in America

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Dazed and confused by the wild hype surrounding gazelles and unicorns, entrepreneurship researchers have focused on the black swans of the entrepreneurial world, even though IPOs and venture capital financing of firms are extremely rare events. Despite their rarity, entrepreneurship conferences and journals have been filled with papers on various aspects of the process of “going public” and “VC networks.” Fortunately, in the middle of the Silicon Valley mania, other scholars have been paying attention to the mundane aspects of business startups – – the ordinary business starts, numbering in the hundreds of thousands each year in the United States for businesses with employees. We point out what we believe to be scholars’ misplaced attention to the extreme and their corresponding neglect of the mundane. Correcting the misperception that has been introduced into the literature by selection biases favoring growing and profitable firms will give scholars and policymakers a more accurate and policy-relevant picture of entrepreneurship in the 21st century.
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Unicorns, Gazelles, and Other Distractions on the Way to
Understanding Real Entrepreneurship in America
Howard E. Aldrich
University of North Carolina at Chapel Hill
Email: howard_aldrich@unc.edu
Martin Ruef
Duke University
Email: martin.ruef@duke.edu
Citation: Aldrich, H.E. and M. Ruef. (2018). Unicorns, Gazelles, and Other Distractions on the
Way to Understanding Real Entrepreneurship in America,” Academy of Management
Perspectives, 32(4): 458-472.
DOI: https://doi.org/10.5465/amp.2017.0123
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ABSTRACT
Dazed and confused by the wild hype surrounding gazelles and unicorns, entrepreneurship
researchers have focused on the black swans of the entrepreneurial world, even though IPOs and
venture capital financing of firms are extremely rare events. Despite their rarity, entrepreneurship
conferences and journals have been filled with papers on various aspects of the process of “going
public” and “VC networks.” Fortunately, in the middle of the Silicon Valley mania, other scholars
have been paying attention to the mundane aspects of business startups the ordinary business
starts, numbering in the hundreds of thousands for businesses with employees. The purpose of this
article is to address what we believe to be scholars’ misplaced attention to the extreme and their
corresponding neglect of the mundane. Correcting the misperception that has been introduced into
the literature by selection biases favoring growing and profitable firms will give scholars and
policymakers a more accurate and policy-relevant picture of entrepreneurship in the 21st century.
KEYWORDS: entrepreneur, entrepreneurship, startup, new venture, venture capital, initial
public offering, Silicon Valley, organizational growth
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In December 1996, the number of publicly traded domestic companies in the United States
reached a peak of 8,025. In the ensuing two decades, that number dropped to 4,333, down 46%
from its peak (Davis, 2016). Entrepreneurship scholars, especially those studying initial public
offerings (IPOs), took little notice. Bedazzled by the wild hype surrounding gazelles and
unicorns, entrepreneurship researchers continued to focus on the black swans, even though the
total IPOs in any given year would fit comfortably into a large lecture hall.
1
On average just over
100 U.S. firms went public annually between 2001 and 2016. Even at the peak, there were fewer
than 700 U.S. IPOs in 1996.
2
Venture capital (VC) financing of firms was only slightly more
common, peaking at just over 6,400 deals in 2000. Nonetheless, entrepreneurship conferences and
journals were filled with papers on various aspects of the process of “going public” and “VC
networks.” Fortunately, in the middle of the Silicon Valley mania, other scholars were paying
attention to the more mundane aspects of business startups the ordinary business starts,
numbering in the hundreds of thousands for businesses with employees, through the same era. The
purpose of this article is to address what we believe to be scholars’ misplaced attention to the
extreme and their neglect of the mundane.
[ Insert Figure 1 About Here ]
The trend toward rare events in entrepreneurship and management scholarship can be seen
in Figure 1. We identified articles that included mentions of “initial public offering” or “venture
1
Unicorns are startup businesses with a stock market value (or estimated value) of at least $1 billion. Gazelles are
high-growth companies, particularly those that have increased their revenues by 20% or more annually over a period
of four or more years. Black swans are rare events, especially those that are random and unexpected.
2
Global IPO’s have been equally subdued in recent years, consistently falling below a total of 500 since 2007 when
attention is restricted to larger deals ($100 million+) (Renaissance Capital, 2016a).
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capital” (or their respective abbreviations) in the full text of six journals, including the Journal of
Business Venturing (JBV), Entrepreneurship Theory and Practice (ETP), the Strategic
Entrepreneurship Journal (SEJ), and the Strategic Management Journal (SMJ) (see Appendix).
We also examined two Academy of Management journals, the Academy of Management Review
(AMR) and the Academy of Management Journal (AMJ), even though they published relatively
few articles with “entrepreneurship” as their subject over this time span, because we wanted to see
whether the same trends were evident in more general-interest journals.
For the journals with an entrepreneurship emphasis, Figure 1 plots articles that mentioned
IPO or VC topics as a proportion of all articles published in those journals between 1990 and early
2017. The oldest entrepreneurship publication in the set, the Journal of Business Venturing, has
shown a consistent bias toward high-capitalization businesses since its inception, with roughly
40%-50% of articles including some mention of these topics. The far younger Strategic
Entrepreneurship Journal, started in 2007, has also been unwavering in its attention to these rare
outcomes among startups. In contrast, the journal devoted to a less specialized audience the
Strategic Management Journal published a relatively limited number of articles that discussed
IPOs and VCs during the 1990s, before picking up steam and doubling that proportion in the 2000s
and then quadrupling it in the early 2010s (to nearly a third of all articles). The variance for ETP
has been the highest over time, but that trend line also concludes with very frequent mentions of
high capitalization events. Indeed, between 2006 and 2016, we counted an average of six ETP
titles or abstracts per year that referred to venture capital or initial public offerings.
Few papers published in AMR and AMJ between 1990 and 2017 concerned
entrepreneurship. Including all articles, dialogues, comments, and papers in special issues, only
7% of the AMR papers and 3% of the AMJ papers were classified as having “entrepreneurship
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as a subject. However, interest in entrepreneurship in those two journals picked up substantially in
the past decade; more than half of the entrepreneurship papers were published between 2008 and
2017. Of the 59 entrepreneurship articles published in AMJ over the entire time span, 58%
discussed IPOs and VCs, an even higher proportion than in the more specialized journals focusing
on entrepreneurship. Of the 69 entrepreneurship articles published in AMR, 28% discussed IPOs
and VCs, putting it slightly below three of the four specialized journals. We conclude that the
obsession with IPOs and VCs manifested in specialized entrepreneurship journals was making its
presence felt in more general-interest journals published by the Academy of Management.
These trends in scholarship might appear sensible if they were positively correlated with
the occurrence of high-capitalization events for new businesses. They are not. IPOs have suffered
several waves of setbacks, including ones that coincided with the bursting of the dot-com bubble
after 2000, the Great Recession after 2007, and the global uncertainty of recent years (Renaissance
Capital, 2016b; Ritholtz, 2015). Since 2001, venture capital deals have been flat, averaging
roughly half their 2000 level (Dow Jones, 2016). Despite this, many entrepreneurship scholars
have not wavered in their focus on large and successful firms. The infatuation with high-
capitalization startups persists, despite their uncertain fate at the hands of the people doing the
actual investing. In academia, where research time and funds are limited resources, far too much
effort is devoted to understanding the handful of business startups that experience high growth or
public offerings, and far too little effort is devoted to understanding the millions of startups that
struggle alongside them. These business startups are organizations and, as such, are worthy of
attention as units whose origins, growth, and survival constitute a fundamental part of the fabric
of U.S. society.
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Our plan is as follows. We have begun by establishing that IPOs and VC funding events
are very rare, and yet entrepreneurship scholars have been paying a disproportionate share of
attention those these unusual startups. In the next section, we identify the historical conditions and
theoretical perspectives that have contributed to this myopia. Finally, we show the reader what
entrepreneurship scholars tend to miss in the landscape of founders and startups and the kinds of
perspectives and data sources that can help address those gaps. We offer several tables and figures
to graphically portray our contention that entrepreneurship research needs to devote more attention
to the rest of the iceberg and not just the tip.
Historical Roots of the Problem
Since the late 1970s, the academic field of entrepreneurship research has grown from
groups of isolated scholars doing research on small businesses to an international community of
departments, institutes, and foundations promoting research on new and high-growth firms
(Aldrich, 2012). Growing numbers of knowledge producers and knowledge users now share core
concepts, principles, and research methods, and a handful of highly cited scholars have emerged
as thought leaders within research subfields (Reader & Watkins, 2006; Teixeira, 2011). Landström
and colleagues (2012) characterized the field as increasingly formalized and anchored in a small
set of intellectual bases, although there are some signs of differentiation and fragmentation. Thus,
we view the evolving system described by Landström et al. (2012) as an institution that has
evolved within a context of institutional entrepreneurship, involving collective action by countless
numbers of scholars, groups, associations, organizations, and agencies. Sometimes such collective
action takes a scholarly community down the wrong path, and their view of the world becomes
6
distorted by a few highly visible phenomena. We think that is what happened with respect to the
Silicon Valley model and the entrepreneurship research community.
The development of the entrepreneurship field has much in common with the process
underlying the growth of scientific/intellectual movements (SIM), as described by Frickel and
Gross (2005). A SIM is a collective effort to pursue research programs and projects while
overcoming resistance from others in the scientific/intellectual community. SIMs try to produce
and distribute knowledge, go beyond existing ways of approaching problems, and defeat
opposition from others by taking organized collective action. The debate over what counts as “real
entrepreneurship” represents one such contest. SIMs are embedded in specific historical
circumstances and may attempt to alter the boundaries of existing scientific/intellectual fields, as
reflected in the struggle between the traditional fields of small and family business and the
emerging field of entrepreneurship over how to define their domains. In this struggle, a central
paradox confronts scholars of entrepreneurship: Over the last three decades, rates of self-
employment and business starts in developed nations have remained fairly flat, and were, on
average, far lower than the rates observed between the 19th century and the post-World War II
period (ILO, 2017; Steinmetz & Wright, 1989). Nonetheless, the golden age of entrepreneurship
research emerged even as actual entrepreneurship entered a comparatively stagnant phase.
Three theoretical presuppositions for the analysis of SIMs are particularly relevant to the
emergence of entrepreneurship as a field. First, the popularity of an idea rests not only on the extent
to which it is scientifically valid, but also on social processes that institutionalize specific routes
for pursuing that idea. For example, what journal reviewers and editors accept for publication
validates the chosen topics and themes as worth pursuing by others. Second, the ultimate shape of
a SIM is contingent upon the historical circumstances within which it emerges. We believe the
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decade of the 1990s had a major effect on the field and slanted it toward a narrower definition of
entrepreneurship than was previously held. The decade not only affected the intellectual compass
of entrepreneurship research directly but also had an indirect impact via the dissemination of new
data sources (e.g., the Venture Xpert database) and the creation of new university positions (e.g.,
postdoctoral fellowships and faculty appointments oriented toward high-growth enterprise). Third,
the wider cultural and political environment critically affects the emergence of a SIM. Concern in
the United States over economic growth, particularly employment growth, has strongly affected
the field and its priorities.
In retrospect, the historical circumstances of the 1990s marked a turning point in the
struggle of entrepreneurship scholars as they battled for academic legitimacy in colleges and
universities (Aldrich, 2012). Debates over the meaning of the terms “entrepreneur” and
“entrepreneurship” were a regular feature of conference presentations and journal articles 40 years
ago, and that conflict intensified during the 1990s. The divestiture movement in the 1980s broke
up many large corporations and investment money began flowing into, and creating, a market for
highly capitalized new ventures. When large corporations, especially conglomerates, ruled the
roost, small businesses were on the back burner. However, when the market for initial public
offerings began to grow rapidly, new small firms were no longer consigned to the backwaters in
business schools. Entrepreneurship and strategy programs began to grow.
Many of the debates in the 1990s reflected the fields attempt to distinguish itself from the
field of small business studies, which had been the traditional home of people studying business
startups. The debate also reflected disciplinary disputes over units and levels of analysis, methods,
and theoretical perspectives. Articles offering conceptual schemes, taxonomies, and typologies
defining “entrepreneur” appeared regularly after the Babson College Entrepreneurship
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conferences began in the 1980s. In a sign that many of the contentious debates about fundamental
assumptions in the field had largely been solved, the “state-of-the-art” handbooks that had
appeared every 5 years or so since the early 1980s stopped in 2000 (Sexton & Landström, 2000).
However, the IPO and VC mania of the 1990s sparked a line of work whose flames consumed
many junior authors and journal editors! Even though the IPO market is a shade of its former self
and venture capital financing has never been available to more than the tiniest sliver of business
startups, effects of the 1990’s conflagration are still being felt, as we argue in the remainder of this
essay.
What Should Entrepreneurship Scholars Study?
The “Silicon Valley model of entrepreneurship,” as described by Audretsch and Calazza
(this issue), consists of three interrelated threads that can be implicitly contrasted with a more
evolutionary or emergent view. The three threads include a focus on high growth and highly
capitalized firms, a focus on innovation and creativity, and in some variants, a focus on the
recognition of promising opportunities. The emergence model of entrepreneurial and
organizational learning that we favor certainly makes room for these three threads, but it begins
with no assumptions about a new venture, beyond the fact that nascent entrepreneurs must “do
something” to organize it (Aldrich & Ruef, 2006; Katz & Gartner, 1988). Unpacking the three
components of the Silicon Valley model reveals the extent to which it has distorted our view of
entrepreneurship.
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Focus on High-Growth Firms
Some scholars argue that high capitalization and high growth businesses are the proper
focus of entrepreneurship studies. They distinguish such businesses from so called “lifestyle” or
traditional businesses, which are purportedly founded by people content with low growth and low
returns to their enterprises (Carland, Hoy, Boulton, & Carland, 1984). Some scholars implicitly
equate raising large amounts of capital and taking firms public with “entrepreneurship” (Lerner,
2012; Stuart & Sorenson, 2003). In a study of 172 Silicon Valley firms often cited as a landmark
in the sociological study of new ventures -- the Stanford Project on Emerging Companies (SPEC)
-- the average firm obtained about $2.5 million in startup funds (Baron, Hannan, & Burton, 1999).
Most received venture capital funding and more than half took their firms public. Many of the
concepts and generalizations based on this study made their way into the organizations literature,
such as the concept of employment models, despite the highly unrepresentative nature of such a
sample. Such studies reinforce the idea that “entrepreneurship” means starting a business with lots
of funding from outside investors, scaling up rapidly, and then taking the venture public. But the
odds of any startup following this path are infinitesimally small, even for firms in Silicon Valley.
High-growth and highly capitalized firms are certainly attractive entities to study, but
confining studies of entrepreneurship and entrepreneurial ventures to high growth companies
introduces a strong selection bias into research (McKelvie & Wicklund, 2010). Growth is an
outcome of an uncertain process, and research has shown that it is difficult to predict which firms
will grow (Guzman & Stern, 2015). For example, PC Connection began with $8,000 in a small
town in rural New Hampshire in 1982, and despite its humble beginnings, grew to sales of about
$300 million by 1995 (Chura, 1995). Many eventual Silicon Valley unicorns began in garages,
basements, or college dormitory rooms. Moreover, regardless of their intentions, most
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entrepreneurs create short-lived ventures. Even highly capitalized firms run into problems they
cannot overcome, as the Internet dot-com bust in 2000 demonstrated. Understanding which
activities lead to successful startup and growth, in varying environments, requires that researchers
cast as wide a net as possible, beginning with even very modest and unlikely startup efforts.
For example, the Panel Study on Entrepreneurial Dynamics (PSED I and PSED II) was
explicitly designed to study a nationally representative sample of new businesses and
entrepreneurial teams. Prior to the PSED, research on entrepreneurship was constrained by the
difficulties of obtaining representative samples. Beginning in the early 1990s, Reynolds and his
collaborators demonstrated that it was possible to rigorously identify nascent entrepreneurs who
were attempting to start new businesses (Reynolds & Curtin, 2009). The resulting panel research
design was eventually called the Panel Study of Entrepreneurial Dynamics I (PSED I). Based on
what investigators learned from that study, an improved research design was created for PSED II,
with more effective screening questions for identifying entrepreneurs and their co-owners.
The research design for the PSED II consisted of two phases. In the first phase, a
representative sample of 31,845 individuals living in the contiguous 48 states and the District of
Columbia was screened in 2005 to identify nascent entrepreneurs. Opinion Research Corporation
(ORC) phoned households as part of a national survey that involved contacting 1,000 adults (500
females and 500 males 18 years of age or older) each week. When an adult 18 years of age or older
was identified and agreed to respond to the survey, a screening interview was conducted to identify
nascent entrepreneurs, using a set of three general qualification questions. If respondents said yes
to at least one of the three questions, three additional questions were used to ascertain whether
respondents had taken any action in creating a new business, whether they would share ownership
of the new businesses, and whether the new businesses had become fledging firms. About 87%
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(1,214) of those identified as entrepreneurs agreed to participate in the study (Reynolds & Curtin,
2009). In the second phase, the University of Michigan Institute for Social Research conducted
full interviews to collect information on all the entrepreneurs. The data set has subsequently been
used to study the gendered nature of control in new businesses (Yang & Aldrich, 2014), the role
of wealth in sustaining the startup process (Frid, Wyman, & Coffey, 2016), and the importance of
constructing effective organizational boundaries in startup survival (Yang & Aldrich,
Forthcoming), among other things. Because it is a representative sample of all business startup
attempts in the United States, we can have great confidence that its results generalize. Given the
mania around venture capital and other forms of outside financing, the PSED estimates regarding
the involvement of businesses and financial intermediaries as owners in average startups are
particularly instructive. In both the late 1990s and in 2005-06, the overwhelming majority of
owners (97-98%) in these new businesses were individuals acting on their own behalf. In the
PSED II, venture capital firms only accounted for a meager 0.3 percent of owners in U.S. business
startups (Ruef, 2010: 63).
[ Insert Table 1 About Here ]
The issue of representativeness in research extends not only to investment and financial
returns but also to the effects of entrepreneurship on employment. The SPEC study and mass
media accounts have highlighted the number of workers employed in high-growth business
startups and their career opportunities. But a relatively small percentage of average startups hire
employees and those that do tend to contribute to high levels of employment “churn” as a function
of the short life of new business establishments. Table 1 summarizes the employment created and
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destroyed by establishment births and deaths in the U.S. for two annual cycles, one well before the
Great Recession (2005-06) and one several years afterward (2013-14). During each annual cycle,
almost a million new establishments with employees were created and each employed around four
workers, all contributing to seemingly large numbers in the aggregate. But about half of the new
establishments were created by existing firms and the other half million only represented a small
fraction of the 7 million business startups attempted each year (Reynolds and Curtin, 2009).
Moreover, there has been a notable decline in employees per employer establishment, with a
roughly 13% decrease over this short eight-year interval. With less than half an employee on
average (combining employer and non-employer businesses), the typical startup attempt is now
dwarfed by the employees in iconic cases of entrepreneurship studied in business schools, such as
Google (72,000 employees), Apple (66,000 in the U.S.), or Facebook (17,000).
The consequences of a disproportionate focus on high-growth firms include a set of myths
that are perpetuated by business case studies and some entrepreneurship scholars. One is that
“liquidity constraints” constitute a major barrier-to-entry for startups, even though financial assets
are generally not associated with significant differences in rates of entrepreneurial entry (Kim,
Aldrich, & Keister, 2006), the majority of startup efforts begin with $5,000 or less in capitalization
(Ruef, 2010), and external funding from fickle investors tends to increase the risk of disbanding
(Ruef, 2002). Another is that employment models and startup “culture” are a major source of
consideration among startup founders. Instead, it is far more likely that participants will be cobbled
together from a founder’s family members, friends, and existing business associates. Finally, the
emphasis on high-growth enterprises contributes to a view of entrepreneurs as unusual, even
heroic, personalities. Yet roughly 40% of U.S. men experience a spell of self-employment or
entrepreneurial activity before retirement age (Arum & Mueller, 2004).
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Focus on Innovative Activity
Based on their reading of Schumpeter, other scholars have argued that entrepreneurship
should focus on innovative activity and the process by which innovations lead to new products and
new markets. For example, business strategy authors often use the term “entrepreneurial” in
referring to managers and executives who take innovative action in established firms, associating
it with “corporate venturing,” “intrapreneurship,” and similar neologisms (Kanter, 1989). Note
that “creative” does not necessarily mean “innovative” (Aldrich & Martinez, 2015). In contrast to
“creativity,” which is defined as the capacity to generate novel ideas, innovation is about the
translation of those ideas into viable and successful products, processes, systems, and institutions.
Innovation thus represents the realization of the potential latent in creative ideas. Innovation does
not necessarily mean the creation of something that is new to the world, but rather only something
new for the individuals or organizations attempting to bring it to life.
Entrepreneurs would seem to have more opportunities for creativity and innovation than
people working within established organizations (Aldrich & Martinez, 2015). First, they are free
from the bureaucratic strictures of firms that suppress creativity and innovation. By enacting their
efforts outside established structures, they are not subject to path dependency through bureaucratic
mechanisms (McMullen & Shepherd, 2006). Second, some researchers argue that entrepreneurs
of necessity have to make do with whatever resources they have, following the principles of
bricolage, and thus are driven to find creative ways to satisfy their needs with whatever they can
cobble together (Baker, Miner, & Easley, 2003; Baker & Nelson, 2005; Desa, 2012). Based on
these principles, it would seem reasonable to expect that we could use the presence of innovation
as a marker for entrepreneurship and entrepreneurial firms.
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However, using the degree of “innovativeness” to define entrepreneurship poses several
problems for the field, one methodological and the other substantive. First, from a research design
perspective, using degree of innovativeness as a criterion for picking entrepreneurs and
entrepreneurial ventures to study once again introduces selection bias into research in much the
same way as if we were to focus only on high-growth firms. Innovation is typically a classification
of activities as new to a particular set of users and a particular environment, and is thus relative to
existing conditions (Rogers, 1995). A priori, it is difficult to classify which acts are innovative and
which are not, until they have been introduced and others’ reactions gauged. Over his intellectual
career, Schumpeter himself displayed a considerable change in perspective for what he viewed as
the typical character of organizational innovation. In his Theory of Economic Development
(Schumpeter, 2011: 66), he posited that “new combinations are, as a rule, embodied in new
firms which generally do not arise out of the old ones but start producing beside them”. But thirty
years later, when he completed Capitalism, Socialism, and Democracy (Schumpeter, 1942), he
suggested that the innovative “entrepreneurial function was increasingly being conducted within
large established firms. An a priori approach that only samples innovative firms would be ill-
equipped to say which of Schumpeter’s views is empirically correct; i.e., whether firm size and
age are positively or negatively associated with innovative capacity.
If we want to understand the contingencies affecting a firm’s degree of innovativeness,
then our sample must first include all firms at risk of being innovative, which requires a
representative sample. From an evolutionary point of view, most variations, even most intentional
variations, are likely to be inferior to variations that have previously been selected and retained
(Aldrich & Ruef, 2006). In cases of radical changes in environments, it is quite likely that a high
proportion of creative variations will be selected against. From a public policy point of view,
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perhaps the most important question to address is what differentiates the firms that survived from
those that exited. To answer that question, we need a representative sample of all startups, not just
the most innovative ones.
Second, limiting the field to defining entrepreneurship as innovation deflects attention
away from models of institutional structures and entrepreneurial ecosystems that link the study of
entrepreneurship to organization and management studies. One of the most widely used
perspectives on organizations, new institutional theory (NIT), offers not only an explanation for
conditions constraining entrepreneurial innovation but also for those conditions facilitating
innovation. Using NIT helps us appreciate how infrequent truly radical entrepreneurial innovation
is, while at the same time helping us understand the difficulties facing entrepreneurs with
innovative intentions.
When entrepreneurs begin the process of organizing their new ventures, they encounter
contexts in which other people -- vendors, investors, employees, customers, regulators, and so
forth -- already have their own expectations concerning "entrepreneurship" and the practices,
processes, and products they will be offered (Aldrich & Martinez, 2015). Such expectations will
constrain, to some extent, entrepreneurial creativity and innovation. Of course, those expectations
might also educate entrepreneurs by showing them what they are supposed to do, depending upon
the context. Many of these expectations come from institutions, which are collections of stable
rules and roles with corresponding set of meanings that constrain actions (Czarniawska, 2008),
leading humans to select activities based on their appropriateness, rather than on more technical
but potentially less appropriate criteria (Biggart & Beamish, 2003).
Institutional environments have powerful effects on individuals and it would be
theoretically implausible to posit that innovative activity occurs frequently, even in favorable
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environments, such as Silicon Valley. Institutional theory’s view is a set of assumptions about the
extent to which habits and heuristics make humans highly susceptible to their surroundings.
Accumulated evidence documents that much of human behavior is driven by habits and reactions
to context-specific cues, rather than by contemplative forethought (Dalton, 2004; Dequech, 2013;
Hodgson, 2004; Wood, Quinn, & Kashy, 2002). Habits are dispositions to act in specific ways
under certain conditions, and play an important role in how people respond to new situations.
Thus, building a more realistic understanding of entrepreneurs and entrepreneurship requires
understanding why institutional forces have such strong effects on the process of starting new
ventures (Aldrich & Martinez, 2015). Continuing to favor an innovation view” of
entrepreneurship thwarts the development of more plausible and realistic models in which most of
the people, most of the time, are stuck in familiar grooves, cutting them deeper.
Focus on Opportunity Recognition/Formation
Following Kirzner (1997), some scholars have argued that “opportunity recognition” or
“opportunity formation” constitutes the heart of entrepreneurship and entrepreneurial activities
(Shane & Venkataraman, 2000). From this perspective, the critical issue is not initial capitalization
but rather the ability of some individuals to detect potentially valuable opportunities overlooked
by others. Stevenson and Gumpert (1985), for example, defined entrepreneurship as the pursuit of
opportunities without regard to resources currently controlled. This view accords with the outlook
of investors and business strategy theorists, who often talk of the importance of future
considerations, such as prospective market size, in funding ventures.
Two distinct positions on entrepreneurial opportunities have emerged in the past several
decades. First, the “discovery” view, or the “individual/opportunity nexus” view, argues that
opportunities for entrepreneurial profits have an objective existence, independently of human
17
activity, and can be discovered and exploited by skillful entrepreneurs (Shane & Venkataraman,
2000). Although Kirzner (1997) is often cited as the source of this position, Foss and Klein (2017:
3) pointed out that Kirzner had always made it clear that “entrepreneurial discovery is a metaphor
or analytic device, not an ontological claim.” Nevertheless, scholars pursuing the discovery view
treat the opportunity recognition process as unfolding in much the same way as natural resource
prospectors search for coal or oil. If they refine their search process and possess enough
“entrepreneurial alertness” (Kirzner, 1973) to obtain the valuable information they need,
eventually the prospectors will be rewarded.
Second, the “creation” view drops the idea that opportunities exist independently, waiting
to be discovered, and instead takes a social constructionist or “evolutionary realist” view (Aldrich
& Kenworthy, 1999; Aldrich & Ruef, 2006; Alvarez, Barney, & Anderson, 2013). Focus shifts
from “discovering” something to conceptualizing and executing a plan to bring a profit opportunity
into existence. Opportunities are thus formed endogenously by entrepreneurs who create them,
rather than exogenously by economic forces that drive markets and industries. However, in their
recent statement, Alvarez et al. (2013: 302) -- several theorists associated with the “creation” view
-- seemed to accept a fundamental assumption of the discovery view in their description of
opportunities as being a result of competitive imperfections in a market. They differed from those
using a discovery view, however, because they argued that entrepreneurs must use their skills to
disturb market equilibrium, thus creating opportunities, and then turn those opportunities into
fruitful ventures.
From its inception, critics have pointed to weaknesses with the opportunity recognition
perspectives. Opportunity discovery scholars work with the implicit assumption that the domain
of potential opportunities studied includes those that could lead to business startups (Fiet, 2002).
18
The perspective seems to endow some entrepreneurs with extraordinary cognitive powers. For
example, Shane and Venkataraman (2000: 220) argued that, “although recognition of
entrepreneurial opportunities is a subjective process, the opportunities themselves are objective
phenomena that are not known to all parties at all times.” Researchers must then discover what
distinguishes those who recognize opportunities from those who do not. More generally, a major
problem for organization theorists has been the pervasive belief that “discovery” explanations for
entrepreneurial achievements must be sought in cognitive traits, such as “achievement motivation”
and “self-confidence.” Unfortunately, for theorists pursuing this avenue of investigation, such
traits are widely shared and do not differentiate between entrepreneurs and other people. Moreover,
some traits traditionally associated with entrepreneurial activity such as financial risk-tolerance
are more common in the general population than among nascent entrepreneurs (Xu & Ruef,
2004).
The “creation view” of opportunities has fared better at the hands of critics, as research on
it has continued to evolve in the direction of a more evolutionary and sociological perspective on
entrepreneurship. In their comprehensive review of the differences between the two “opportunity”
views, Alvarez et al. (2013) argued that “creation” should be seen as an evolutionary process in
which enacted opportunities are formed endogenously by entrepreneurs seeking to exploit them.
Drawing upon the work of Weick (1969), Campbell (1969), and Aldrich and Ruef (2006), they
emphasized that entrepreneurs are working in uncertain contexts in which neither outcomes nor
probabilities of success are well defined. Their model embeds the opportunity creation process in
a realistic social psychology of humans as entrepreneurs, as well as taking account of the
institutional context in which entrepreneurs operate (Aldrich, 2010). If widely adopted as an
19
alternative to the “discovery” view, it would be a substantial corrective to the biases we have
described above.
Focus on What Entrepreneurs Do
In contrast to the three views presented above, concerning what entrepreneurship scholars
should focus on, some researchers counsel focusing on what it is that entrepreneurs are trying to
do, which is to found a new organization. From this perspective, entrepreneurs are people who
create new social entities. This view fits the conventional use of the term “entrepreneur,” referring
to those who found an organization, regardless of its size. For example, in his review of the
literature on the alleged traits of entrepreneurs, Gartner (1988) argued that entrepreneurship should
be studied by focusing on the behaviors and activities of people trying to create businesses, rather
than on their psychological states and personality characteristics. These startup activities often do
not culminate in success. Looking at the PSED II, most individuals (95%) who say they are “trying
to start a business” have involved others in the process or hope to do so over a five-year time
horizon (Ruef, 2010: 10-11). This seems to be one important criterion that distinguishes the effort
among these business founders to create a new social entity rather than engage in mere self-
employment. Of course, many of the activities that seek to bring others into the organizing process
end in frustration for average entrepreneurs.
Similarly, in a rebuttal to Ramoglou and Tsang’s (2017) proposal for a middle ground
between the discovery and creationist views, Foss and Klein (2017) argued that the real middle
ground would be a perspective based on the literatures in judgment (Kahneman, 2003) and
effectuation (Sarasvathy, Menon, & Kuechle, 2013). Those literatures emphasize humans as
struggling to do the best they can under conditions of uncertainty, making experimental forays and
20
occasionally learning from their mistakes. Foss and Klein (2017) argued that invoking notions of
opportunity creation and formation introduces unnecessary redundancy into the study of
entrepreneurship, because opportunities do not exist independently of entrepreneurial actions and
it is not “opportunities” that are formed but rather new ventures that are struggling to make sense
of their environments as they compete for customers, revenue, supporters, and participants.
What to do Next?
In nearly all modern capitalist economies, people see business ownership as a desirable and
feasible status. Positive conceptions of “entrepreneurs” and “entrepreneurship” have been
pervasively diffused because multiple institutions -- the media, education systems, governments,
and public opinion -- have bolstered the cultural appeal and social legitimacy of creating new
businesses. Cross-national studies have found that millions of people participate in new venture
creation every year, although there is large variation in startup rates among countries
(Blanchflower, Oswald, & Stuzer, 2001; Kelley, Bosma, & Amoros, 2011). Tellingly, some of
the highest rates of adult participation in total early-stage entrepreneurial activity (TEA) are found
in those countries that are least studied by entrepreneurship scholars. Thus, researchers tend to
focus on the United States, where about 13% of adults are involved in entrepreneurial activity, or
Western European countries such as France, Germany, and Italy, where the number is closer to
5% (Global_Entrepreneurship_Monitor, 2017), far fewer entrepreneurship scholars have devoted
much attention to the Global South, where countries such as Ecuador (32% TEA) and Burkina
Faso (34%) exhibit extraordinarily high rates of entrepreneurial activity.
Concomitantly, the large numbers of startup attempts are matched by equally large numbers
of failed efforts (Levie, Gavin;, & Leleux, 2011; Sadeghi, 2008). Despite the positive valuation
21
people place upon creating a successful venture, most attempts are abandoned after a few years
and only a minority survive and succeed in becoming profitable entities. As Loasby (2007: 1104)
noted, “Though entrepreneurship is purposeful, it is an evolutionary process of trial and error; and
error is more likely than success.” We think that the field of entrepreneurship research should
reflect such turbulence, rather than being skewed by focusing on unicorns, gazelles, and other rare
creatures, which also inhabit the most unusual ecosystems (i.e., high-tech agglomerations within
advanced industrial countries).
Given the problems posed by the first three perspectives’ focus on the rare and unusual, we
suggest reframing the issue of emergence by focusing on questions suggested by the fourth
perspective, involving entrepreneurial and organizational learning under uncertainty. First,
through what process do founders construct new organizations? Organizations, as we have defined
them (Aldrich & Ruef, 2006), are goal-directed boundary-maintaining activity systems, and
organizational founders must attend to all three components of this definition in constructing an
organization. A scheme for analyzing organizational emergence builds on the pioneering work of
Katz and Gartner (1988), whose achievement was to drive home the point that organizational
emergence is not a linear, step-by-step process. Katz and Gartner (1988) noted that the boundary
between pre-organization and organization is ambiguous, and suggested four criteria for
identifying when an organization comes into existence: (1) intentionality, perhaps as reflected in
stated goals; (2) mobilization of necessary resources; (3) coalescence of boundaries, such as
through formal registration and naming of the entity; and (4) the exchange of resources with
outsiders. Emergence involves uneven development along several lines, any one of which might
be stopped well short of an organization’s successful founding. Treating entrepreneurship as the
22
creation of new organizations changes the focus of entrepreneurship research from studying
outcomes to studying the initiation of organizing processes that could result in new social entities.
Using an evolutionary perspective, we can investigate what makes the situation of
entrepreneurs starting new ventures different from that of managers in established firms in their
learning and knowledge (Aldrich & Yang, 2013). Unlike managers in established organizations
who generally follow or modify pre-existing routines already selected by others, entrepreneurs
begin with mostly a blank slate. They must initiate rules or principles and experiment with them
until they find the most effective or appropriate ones for their new businesses. Entrepreneurs who
begin with inadequate knowledge or experience will feel strong pressures toward learning by
doing. Entrepreneurs who have acquired routines or organizing procedures from existing
workplaces may find it easier to muddle through the initial stages, but nonetheless they must learn
to anticipate and cope with environmental changes.
Entrepreneurial learning must therefore be understood in dynamic terms, through a life
course perspective (Elder, Johnson, & Crosnoe, 2006). From the viewpoint of the people involved,
the issue is one of entrepreneurial learning, and from the viewpoint of the organizations they
attempt to create, the issue is one of organizational learning. Recent developments in the study of
organizational routines and organizational learning have gone a long way toward adding a dynamic
dimension to our theories (Becker & Lazaric, 2009; Rerup & Feldman, 2011). We suggest focusing
on the emergence of new organizations and the way in which entrepreneurs draw upon their
previous experience as well as the conditions they encounter during the startup process.
Second, what selection processes affect whether new organizations reproduce or depart
from existing organizational forms, routines, and competencies? This question raises a perplexing
methodological issue for anyone using current research findings. Organizations need founders. But
23
organizations cannot recruit them, because organizations don’t exist until founders construct them.
Thus, we typically identify founders only after we have already identified their organizations. If
we only study entrepreneurs after their organizations have attracted enough public notice to be
included in standard sampling frames, we overlook a critical phase in the founding process
(Aldrich, Kalleberg, Marsden, & Cassell, 1989). At that point, selection processes have winnowed
out many interesting variations. We also miss the process by which new organizations with
innovative routines and competencies set in motion the genesis of new populations.
[ Insert Figure 2 About Here ]
For entrepreneurship in the United States, the winnowing process can be illustrated by a
pyramid showing a progressive falloff in numbers from bottom to top, which begins with startups
as an everyday occurrence and ends with the kinds of rare high-capitalization businesses that
dominate the pages of entrepreneurship journals and the business media (see Figure 2). Before the
Great Recession, roughly 12 million entrepreneurs were involved as equity participants in seven
million startup attempts (Reynolds & Curtin, 2009). Only a fraction of those startups eventually
became profitable or hired employees (Reynolds, 2016). The firms receiving angel funds are
roughly 1 in a 100 among the startup attempts (Center for Venture Research, 2015), and VC deals
are even less common by an order of magnitude (moreover, many of those VC deals entail follow-
up funding to the unusual firms that have already been financed). Once we get to IPOs in general
and information technology IPOs in particular -- that is, the land of unicorns and gazelles -- we
have winnowed the initial range of startup attempts to approximately 1 in 50,000.
24
Discussion
Our contributions have been threefold. First, analyzing historical data since the 1990s, we
have demonstrated that even though scholars publishing in the major journals on entrepreneurship
pay a disproportionate amount of attention to these unusual startups, IPOs and VC funding events
are very rare. Second, we have identified the historical conditions and theoretical perspectives that
have contributed to this myopia, with the resulting focus on growth, innovation, and opportunity
recognition being especially problematic. Finally, we have shown what entrepreneurship scholars
tend to miss in the landscape of founders and startups and the kinds of perspectives and data
sources that can help address those gaps.
We have not attempted to add new theory to the field, as we think the problem is not an
absence of theory but rather a misallocation of theoretical resources toward explaining rare events.
Consequently, our purpose has been to shift the empirical emphasis in entrepreneurship
scholarship. We urge entrepreneurship researchers to pay more attention to the mundane and the
ordinary, and to avoid emphasizing the rarefied stratum of new ventures that has caused so much
misunderstanding. Just as research in the biological sciences has been greatly advanced by
studying simple organisms, such as the common fruit fly, entrepreneurship research would benefit
from an emphasis on average startups rather than creatures that are more exotic (e.g., high-growth
gazelles) or even mythical (billion-dollar unicorns). An increasing array of methodological tools
and data sets are available that permit an investigation of the entrepreneurial dynamics at the
bottom of the pyramid.
We have already described the research design used to create the Panel Study of
Entrepreneurial Dynamics, a model that has been replicated in numerous countries. Other
researchers have increasingly turned to longitudinal databases that cover all labor market activity
25
in a country, such as the Longitudinal Integration Database for Health Insurance and Labor Market
Statistics in Sweden (LISA) or the Integrated Database for Labor Market Research in Denmark
(IDA). As entrepreneurship scholars make use of such nationally representative samples or
censuses of business startups in their research, we would expect to see greater balance in the
literature on start-ups and growth. Not only do most new businesses not grow, but more than half
do not even survive for more than a few years (Frid et al., 2016; Yang & Aldrich, 2017). Correcting
the misperception that has been introduced into the literature by selection biases favoring growing
and profitable firms will give scholars and policymakers a more accurate and policy-relevant
picture of entrepreneurship in the 21st century.
26
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34
APPENDIX
We employed the following research design to study terms and concepts used in four leading
journals that publish entrepreneurship research: the Journal of Business Venturing (JBV),
Entrepreneurship Theory and Practice (ETP), Strategic Entrepreneurship Journal (SEJ), and
Strategic Management Journal (SMJ).
First, we searched for two terms concerning venture capitalists and initial public offerings: “initial
public offering/IPO,” and “venture capital/VC.” Some articles used only the initials of the terms
and others wrote the terms out.
Then we counted the number of articles published since 1990 that included these terms, by journal
and by year. We also counted the total number of articles published each year and used it as the
denominator, with the numerator being the number of articles with mentions of the term. Each
article is counted only once, no matter how many times the terms are used within the article.
The resulting general format is shown below, with cell entries being the number of mentions of
the terms and the number of articles published in that year (# articles with mentions/total # articles
that year):
YEAR
JBV
JBV
JBV
ETP
ETP
SEJ
SEJ
SEJ
SMJ
SMJ
SMJ
IPO
VC
IPO
or VC
IPO
VC
IPO
VC
IPO
or VC
IPO
VC
IPO
or VC
1990
Xx/yy
Xx/yy
Xx/yy
1991
1992
1993
1994
1995
1996
etc.
35
Table 1. Volatility in the U.S. Business Employer Population
(Private-Sector Establishments)
Source: Business Employment Dynamics (BED) Data Series, 2016, Entrepreneurship and the U.S.
Economy. Washington, DC: Bureau of Labor Statistics.
Births
Deaths
# Employees for
Births
# Employees for
Deaths
2nd Qtr, 2005
232,000
192,000
964,000
845,000
3rd Qtr, 2005
236,000
195,000
1,005,000
885,000
4th Qtr, 2005
236,000
200,000
988,000
850,000
1st, Qtr 2006
236,000
195,000
949,000
767,000
2nd Qtr, 2013
222,000
215,000
791,000
695,000
3rd Qtr, 2013
219,000
195,000
824,000
681,000
4th Qtr, 2013
215,000
186,000
805,000
672,000
1st Qtr, 2014
220,000
189,000
779,000
630,000
36
Figure 1. Articles with Mentions of IPO/Initial Public Offering” or “VC/Venture Capital” in
Full Text Published in JBV, ETP, SEJ, and SMJ *
Notes (*): Proportion is computed by dividing articles that include any mention of IPOs or VCs
by total number of articles. All calculations occur over five-year intervals, except 2015-17.
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
1990-94 1995-99 2000-04 2005-09 2010-14 2015-17*
Proportion of Articles
JBV
ETP
SEJ
SMJ
37
Figure 2. Many Businesses Are Created, but
Few Become Unicorns and Black Swans
Sources: Reynolds and Curtin (2009); Reynolds (2016); Center for Venture Research (2015);
(Ritholtz, 2015); (Dow Jones, 2016); (Renaissance Capital, 2016b)
24 IT IPOs
170 IPOs (2015)
~5,700 public firms (2016)
~4,200 venture capital deals (2015)
~71,000 firms receiving angel funds (2015)
~500,000+ startups (2005) hiring within 1 year
~1,800,000 startups (2005) profitable within 6 years
~7,400,000 business startup attempts (2005)
~12,100,000 people involved as owners in new startups (2005)
38
Biographies of the authors:
Howard E. Aldrich (howard_aldrich@unc.edu) is Kenan Professor of Sociology; Adjunct
Professor of Business at the University of North Carolina, Chapel Hill; Faculty
Research Associate at the Department of Strategy & Entrepreneurship, Fuqua
School of Business, Duke University; and Fellow, Sidney Sussex College,
Cambridge University. His main research interests are entrepreneurship,
entrepreneurial team formation, gender and entrepreneurship, and evolutionary
theory.
Martin Ruef (martin.ruef@duke.edu) is Jack and Pamela Egan Professor of
Entrepreneurship in the Department of Sociology at Duke University. His
research considers the social context of entrepreneurship from both a
contemporary and historical perspective. He draws on large-scale surveys and
census data on entrepreneurs to explore processes of team formation, innovation,
and entry into self-employment.
... High-growth startups, while important drivers of job creation (Acs & Mueller, 2007;Henrekson & Johansson, 2010), represent only a small fraction of entrepreneurial activity, and limiting the scope to only the "handful of business start-ups that experience high growth" (Aldrich & Ruef, 2018, p. 460) is problematic for several reasons. First, it overlooks the broader spectrum of entrepreneurship, neglecting the overwhelming majority of "mundane," everyday types of entrepreneurship that employ a significant portion of the population and contribute positively to the well-being of regions and nations (Aldrich & Ruef, 2018;Kuratko & Audretsch, 2022;Sarasvathy, 2021). At the same time, this narrower approach is at odds with Baumol's (1990) original conceptualization of productive entrepreneurship, which views it as a widespread social phenomenon. ...
... A key feature of Baumol's framework is to encompass a wide range of entrepreneurial activities that enhance economic and social welfare (Minniti, 2016;Sobel, 2008). This includes the vast majority of entrepreneurs-those behind the more "mundane" startups and businesses, who, in fact, employ most of the workforce (Aldrich & Ruef, 2018;Welter et al., 2017). ...
... Despite this diversity within entrepreneurship, scholars and analysts have increasingly embraced a Silicon Valley model of entrepreneurship (Audretsch, 2021;Kyprianou et al., 2025;Pahnke & Welter, 2019), which emphasizes "high-growth, technologyenabled, venture-capital backed businesses that… create thousands of jobs" (Welter et al., 2017, p. 312). This is evidenced by the disproportionate share of studies in top journals focused on end-of-the-tail events, such as initial public offerings (IPOs) and venture capital (VC) deals (Aldrich & Ruef, 2018), as well as recommendations that public policy focus on high-growth, innovative startups (Mason & Brown, 2013;Shane, 2009). ...
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Plain English Summary “If you build it, entrepreneurs may not come. Tailored strategies, not replicating the ‘Silicon Valley’ model, should drive entrepreneurial ecosystems. Our study reveals 5 unique ecosystem types that fuel diverse entrepreneurship growth in the USA”. This study explores how different regional entrepreneurial ecosystems (EEs) in the USA foster various types of entrepreneurship. By examining the interplay between institutional arrangements (like public policies and culture) and resource endowments (like talent and finance), we find that these factors impact entrepreneurial outcomes differently. Institutional arrangements are consistently foundational for entrepreneurship that is not necessarily high growth, such as self-employment and the rate of new business creation. In contrast, resource endowments are more critical for high-growth entrepreneurship. We also identify five types of entrepreneurial ecosystems—Bottom-Up Ecosystem, Top-Down Ecosystem, Free Enterprise Foundation, Collectivistic VC-backed Ecosystem, and Individualistic VC-backed Ecosystem—each representing different ways that regions can nurture entrepreneurship. Given the diversity of configurations found, our study suggests that regions should adopt tailored strategies that consider their unique institutional and resource contexts to support a more diverse range of entrepreneurial activities, rather than focusing excessively on “gazelles,” or high-growth firms. Similarly, policymakers and ecosystem builders should avoid a “one-size-fits-all” approach that seeks to replicate the “Silicon Valley” model of success in their regions. Instead, developing strategies that align with their region’s specific institutional and resource strengths should be a more effective way of adopting the entrepreneurial ecosystems approach to enhance economic and social development and avoid wasting scarce resources on an entrepreneurial field of dreams.
... It is very important that ambition is not categorized as either good or bad in this context. Aldrich and Ruef [44], Morris & Kuratko [45], Kuratko and Audretsch [46], and Kuckertz et al. [36] emphasize that research should not only focus on extreme outliers of entrepreneurship (maximum ambitions in our context) but should consider the multiple aspects (different ambitions in our context). Kuratko and Audretsch [46], p. 269 raise the question "The future of entrepreneurship: the few or the many?". ...
... Hence, this response format reduces acquiescence bias [130]. Furthermore, to ensure that the position of the answers did not matter, the two items 1) long-term linear vs. short-term exponential increase in value and 2) ownership vs. exit were 44 asked inverted in the post-hoc analyses in 2021 and 2022. Our semantic differential-based scoring has two poles, each of which has the value of "strongly agree" (values -3 and 3) to "agree" (values -2 and 2) to "rather agree" (values -1 and 1) asking the entrepreneurs how much certain statements apply to their startup. ...
... There are mentions of startup types e.g. [44,49,36,46] but no theory that determines how many types exist and what they are. Therefore, this study is an exploratory approach. ...
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The development of a startup is determined by the entrepreneurial actions of its founders, and the associated entrepreneurial action theory accordingly describes the different goals, strategies, and measures of the founders for this development. The founders’ ambitions, which are a driving force behind entrepreneurial action, play a significant role in this context. Research shows that these ambitions determine the goals, strategies, and measures of the young company and, thus, the desired development from the founders’ perspective with the associated success. However, not every founder pursues the same ambitions in terms of content and form or always strives for the maximum. Based on three consecutive surveys (n = 1,985 startups), we use K-means cluster analysis to analyze three different dimensions of entrepreneurial ambition (growth, ownership, and cooperation) to examine their combined configuration. Based on this, we identified and double-checked four ambition groups with K-means cluster analysis and laid a foundation for a typology of startups based on the goals of their founders. Two types were identified that were already known in the literature and in practice: Unicorns and Zebras! But we were also able to discover two other types that have only been described rudimentarily in the literature and have not yet been proven empirically: Horses and Cows! The results have theoretical and practical implications for the founding and development of startups and a related focus on the founders’ ambitions, but also an associated broader consideration by potential investors.
... On the one hand, a moderate surge in prospective entrepreneurs trying to start ventures may signal to investors the promise of the market (especially if the market is new) and persuade them to invest, leading to the higher rate of successful transitions from organizing attempts to actual foundings, and to the lower mortality rate of newly founded ventures (Khessina & Jaffee, 2019;McKendrick et al., 2003). On the other hand, too many entrepreneurs attempting to start a new business may intensify competition for limited resources and deplete the population's carrying capacity, resulting in both fewer successful foundings and higher mortality rates of ventures that did get founded (Aldrich & Ruef, 2018;Ingram & Torfason, 2010;Pontikes & Barnett, 2017). ...
Chapter
Among a variety of approaches to studying entrepreneurship, the ecological perspective stands out by its focus on the vital rates of all entrepreneurial firms at the population level: the rates of organizing attempts, actual foundings, and early survival. Entrepreneurs are seen as boundedly rational actors that often make mistakes in identifying and acting on market opportunities, not only creating delays and unsuccessful transitions between organizing attempts and actual foundings, but also leading to early mortality even when actual foundings happen. This chapter reviews several high-level forces identified by ecologists that drive these processes at the population level: the interaction between material and non-material resource environments, the tension between convergence pressures and divergence pulls, and the balance between within-population and cross-population focus. It also discusses how, by shifting attention from an individual entrepreneur to population-level entrepreneurship rates, the ecological perspective makes it possible to explain and predict which types of entrepreneurial ventures are more likely to be started and succeed in different industries and spatio-temporal contexts.
... While resources undoubtedly seem important, the mere presence of certain types of resources alone cannot be sufficient to reliably explain the occurrence of extreme growth outliers. After all, except for a select few dominant platform businesses, most organizations that have well-developed digital or human resources or are located in well-resourced ecosystems never grow substantially (Gawer, 2021), nor do they become unicorns or have an IPO (Aldrich & Ruef, 2018). Moreover, resource-based explanations of growth typically assume relatively stable and predictable contexts in which organizations can strategically develop required resources over time (Furr & Eisenhardt, 2021). ...
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In this paper, we discuss the role of culture and creativity as a so far neglected growth factor, filling an important gap in the existing literature. We analyse both the relevant theoretical and empirical studies, and we find that there is a solid basis to integrate culture and creativity into a more comprehensive growth paradigm. Working on the Programme for the International Assessment of Adult Competencies (PIAAC) database, we adopt a cross-sectional design. We find that cultural and creative sectors are characterised by higher levels of problem solving, numeracy, and literacy skills with respect to other productive sectors, and that the same positive gap holds for cultural and creative jobs with respect to other kinds of jobs. Taking into account the well-documented effects of cultural participation on pro-social attitudes and behavioural changes, we conclude that culture and creativity deserve more attention as a socially sustainable growth factor, simultaneously acting on both the supply and demand sides. Harnessing the skills-building potential of culture and creativity may, therefore, provide the basis for a new cycle of research and policy developments on the soft determinants of growth performance.
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