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Venturing into the Unknown: A Meta-Analytic Assessment of Uncertainty in Entrepreneurship Research

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Uncertainty exists within a small constellation of core constructs that are central to the study of entrepreneurship. And yet, despite the common agreement and consensus that uncertainty plays a central role in entrepreneurship theory and research, there are important unresolved debates around several key questions including conflicting views on the nature of uncertainty (i.e., objective versus subjective uncertainty), the relationship between uncertainty and different types of entrepreneurial action (i.e., innovation, adaptation, and uncertainty bearing), and the complex relationships among uncertainty, entrepreneurial action, and organizational performance. The purpose of this study is to examine the body of empirical evidence in the field of entrepreneurship through the use of meta-analysis and meta-structural equation modeling in order to take steps towards disentangling the multilevel and multidimensional relationship among uncertainty, entrepreneurial action, and the fate of entrepreneurial ventures, thereby contributing to future theory development in the field of entrepreneurship.
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VENTURING INTO THE UNKNOWN: A META-ANALYTIC ASSESSMENT OF
UNCERTAINTY IN ENTREPRENEURSHIP RESEARCH
David M. Townsend
Entrepreneurship
Virginia Polytechnic Institute
Blacksburg, VA, USA 24061
Tel: (540) 231-4553
E-mail: dtown@vt.edu
Richard A. Hunt
Strategy and Entrepreneurship
Virginia Polytechnic Institute
Blacksburg, VA, USA 24061
E-mail: rickhunt@vt.edu
Daniel J. Beal
Management
Virginia Polytechnic Institute
Blacksburg, VA, USA 24061
E-mail: dbeal@vt.edu
Ju hyeong Jin
Management
Virginia Polytechnic Institute
Blacksburg, VA, USA 24061
E-mail: jinjh@vt.edu
Note: PRIVATE COPY. Paper presented at the Virtual Academy of Management Annual
Conference, August, 2020. A significantly revised version of this work is currently under
review. We will send a copy of that version when the review process allows us to do so. Please
do not copy or circulate this draft. Thank you for your interest in this research. Keep us
abreast of your own good work in this vein. We would certainly benefit!
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VENTURING INTO THE UNKNOWN: A META-ANALYTIC ASSESSMENT OF
UNCERTAINTY IN ENTREPRENEURSHIP RESEARCH
ABSTRACT
Uncertainty exists within a small constellation of core constructs that are central to the study of
entrepreneurship. And yet, despite the common agreement and consensus that uncertainty plays a
central role in entrepreneurship theory and research, there are important unresolved debates around
several key questions including conflicting views on the nature of uncertainty (i.e., objective
versus subjective uncertainty), the relationship between uncertainty and different types of
entrepreneurial action (i.e., innovation, adaptation, and uncertainty bearing), and the complex
relationships among uncertainty, entrepreneurial action, and organizational performance. The
purpose of this study is to examine the body of empirical evidence in the field of entrepreneurship
through the use of meta-analysis and meta-structural equation modeling in order to take steps
towards disentangling the multilevel and multidimensional relationship among uncertainty,
entrepreneurial action, and the fate of entrepreneurial ventures, thereby contributing to future
theory development in the field of entrepreneurship.
“Uncertainty is one of the fundamental facts of life.” (Knight, 1921)
INTRODUCTION
For more than a century, across diverse areas of research spanning the work of early
administrative theorists to contemporary scholarship in the fields of economics, management, and
entrepreneurship research, scholars have grappled with the pervasive but often pernicious effects
of uncertainty in organizational phenomena (Knight, 1921; Keynes, 1937; Simon 1955, 1959;
Shackle, 1961; Cyert & March 1963; Alchian & Demsetz 1972; Kahneman & Tversky, 1979;
Williamson, 1979; Akerlof 1995). Uncertainty ubiquitously and pervasively pervades
organizational phenomena because “…there is a real world that is imperfectly understand” due to
our collective “…limitation(s) on understanding and intelligence” (March, 1994: 178; Simon,
1972). In response, organizational scholars have explored how a wide range of factors including
organizational structures (Dutt & Joseph, Forthcoming), routines (Becker & Knudsen, 2005),
interorganizational ties (Beckman, Haunschild, & Phillips, 2004), decision-making processes
(Gavetti, Levinthal, & Ocasio, 2007), real option strategies (McGrath, 1999), enable firms to
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mitigate the pernicious effects of uncertainty through organizational action (Thompson, 1967) and
the rational design and control of organizations (Wren & Bedeian, 2009).
For the field of entrepreneurship, the importance of uncertainty is virtually unquestioned,
yet its precise role in entrepreneurial phenomena is thinly understood and hotly debated (Packard
& Clark, forthcoming; Townsend et al., 2018). While entrepreneurship scholars continue to draw
heavily upon the logic and substance of foundational perspectives on uncertainty in organizational
research, the field is characterized by sharply contrasting views of uncertainty’s role in
entrepreneurship theory (Knight, 1921; Venkataraman, 1997; Sarasvathy, 2001; McMullen &
Shepherd, 2006; McKelvie, Haynie, & Gustavsson, 2011; Packard et al., 2017; Townsend et al.,
2018; Alvarez et al., 2018). In many studies, and in particular those studies which build upon
mainstream organizational research, entrepreneurship scholars perpetuate the near consensus view
that, as an analytical construct, uncertainty is an aversive force in entrepreneurial action and
outcomes, an epistemological obstacle to be overcome, mitigated, reduced, diminished, or
passively accepted by the entrepreneurial actor (Artinger & Powell, 2016; Tang & Wezel, 2015;
Townsend & Busenitz, 2015; Audretsch et al., 2014; Bianco et al., 2013). For other scholars,
however, “uncertainty constitutes a conceptual cornerstone for most theories of the entrepreneur”
(McMullen & Shepherd (2006: 132), functioning as the wellspring of entrepreneurial opportunities
(Alvarez & Barney, 2007) and the source of an entrepreneur’s profits (Knight, 1921;
Venkataraman, 1997). Where, despite the murky asperity of the path forward, entrepreneurs
operate as a unique class of actors, willing and able to advance into the unknown and unknowable
future (Sarasvathy, 2001; 2008; McGrath, 1999). In this latter case, uncertainty is not seen as an
inhibiting force per se, but instead functions as a generative source of possibilities or propensities
(Ramoglou & Tsang, 2016) through which the creative entrepreneurial act (Alvarez, Barney,
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McBride, & Wuebker, 2014) turns imagined artifacts (Klein, 2008) into real opportunities
(Alvarez, Barney, & Anderson, 2013).
To bridge these contrasting perspectives, there is a growing recognition that greater
precision and clarity is needed to disentangle the complex relationship between uncertainty, as an
analytical construct, and entrepreneurial action (Townsend et al., 2018). In response, important
new conceptual work is emerging in the field of entrepreneurship, refining definitions of
uncertainty, clarifying boundary conditions, and deepening the field’s understanding of the causal
role of uncertainty in entrepreneurial action (Packard & Clark, forthcoming; Townsend et al.,
2018; Alvarez et al., 2018; Packard et al., 2017; Ramoglou & Tsang, 2016; McKelvie et al., 2011).
And yet, despite these important efforts to refine the logic, coherence, and clarity of the uncertainty
construct in organizational research, something fundamental is missing from this discussion, as no
study to date has systematically investigated the empirical relationship between uncertainty and
entrepreneurial action. This is a problematic state of affairs in the field’s collective efforts to refine
and solidify the uncertainty construct given the prominence with which uncertainty is afforded
within entrepreneurship theory (Folta, 2007).
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For the field of entrepreneurship, the lack of
systematic analysis to investigate the relationship between uncertainty and entrepreneurial action
is problematic as it points to growing disconnect between the field’s foundational theories and the
body of evidence that is being accumulated through empirical research.
The purpose of this study is to address the growing chasm between the robust and fresh
conceptual work in the field of entrepreneurship regarding the role of uncertainty in theories of
entrepreneurship (Packard & Clark, forthcoming; Townsend et al., 2018; Alvarez et al., 2018;
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The meta-analytic work of Brinckmann and colleagues is a notable exception but as we will
discuss below, the analysis of the relationship between uncertainty and entrepreneurial action is a
secondary focus of their study, with only a limited analysis of the uncertainty construct. We will
discuss the important contributions of this study in our literature review.
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Packard et al., 2017; Ramoglou & Tsang, 2016; McKelvie et al., 2011), with complementary and
systematic analyses on the empirical evidence linking uncertainty to entrepreneurial action. We
take up this challenge building on meta-analytic techniques developed in previous research (e.g.,
Hunter & Schmidt, 2004) to evaluate the status of uncertainty as an analytical construct in the field
of entrepreneurship. Specifically, we utilize Cheung’s (2014; 2015) meta-analytic approach to
multilevel structural equation modeling (SEM). Based on analyses, we make fundamental
contributions to the burgeoning literature on uncertainty in entrepreneurship research, and take
decisive steps towards disentangling the multilevel and multidimensional relationship among
different types of uncertainty, different modes of entrepreneurial action, and organizational
performance among entrepreneurial ventures, thereby contributing to future theory development
in the field of entrepreneurship.
THEORY & HYPOTHESES
As a multidisciplinary field, entrepreneurship research draws upon a wide variety of
perspectives to account to explore entrepreneurship phenomena across the macro environment,
organizations, and individual actors (e.g., Burns & Stalker, 1961; Downey & Slocum, 1975;
Duncan, 1972; Keynes, 1937; Lawrence & Lorsch, 1967; Milliken, 1987; Neumann, 1944;
Shackle, 1949; Teece, Peteraf, & Leih, 2016). Although the nature and intent of these studies vary
in important ways, the recognition of the role of uncertainty in shaping entrepreneurial phenomena
provides “the conceptual cornerstone” across many of these studies (McMullen & Shepherd, 2006:
page), providing at times, even the logic for the boundary conditions between the field of
entrepreneurship and other closely related scholarly domains (Folta, 2007). The problem of
uncertainty, thus, provides common cause for entrepreneurship scholars to address questions that
are centrally important to the domain namely exploring the causes and consequences of
entrepreneurial action to create “future goods and services” (Venkataraman, 1997: Page).
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The field of entrepreneurship has benefitted greatly from this common research goal as
scholars grounded in economics (Kirzner, 1973; Schumpeter & Backhaus, 1934), psychology
(Busenitz & Barney, 1997), sociology (Thornton 1999), as well as many other fields (e.g. Emmett,
1999; Fraser & Greene, 2006; Knight, 2015) have addressed the role of uncertainty to explore the
questions of who takes action, why action occurs, and how actions unfold to influence
entrepreneurial environments (Begley & Boyd, 1987; McMullen & Shepherd, 2006; Sarasvathy,
2001; Shane & Venkataraman, 2000; Shaver & Scott, 1992). These perspectives have converged
in remarkable fashion to a near-universal assumption that uncertainty is fundamentally intertwined
and inextricably linked to entrepreneurial phenomena (Sarasvathy, 2001; 2008; McMullen &
Shepherd, 2006; Alvarez & Barney, 2007; Foss & Klein, 2012). Under these conditions, the
precursors of entrepreneurial action instantiated in entrepreneurial judgment and decision-making
processes largely involve a process of choosing a course of action when the consequences of one’s
choices cannot be known or predicted a priori (McMullen & Shepherd, 2006; Foss & Klein, 2012;
Knight, 1921). These arguments are based in the familiar contours of Knight’s (1921) foundational
work on uncertainty and entrepreneurial action where uncertainty is defined as:
“Uncertainty must be taken in a sense radically distinct from the familiar notion of
risk, from which it has never been properly separated.... The essential fact is that
'risk' means in some cases a quantity susceptible of measurement, while at other
times it is something distinctly not of this character; and there are far-reaching and
crucial differences in the bearings of the phenomena depending on which of the
two is really present and operating.... It will appear that a measurable uncertainty,
or 'risk' proper, as we shall use the term, is so far different from an unmeasurable
one that it is not in effect an uncertainty at all” (1921:19).
In this fashion, entrepreneurship under conditions of Knightian uncertainty is
distinguishable from other modalities of reasoned behavior by the fact that it necessarily
entails taking action in the context of an unknowable future (Hébert & Link, 1988;
McMullen & Shepherd, 2006), which cannot be mitigated or reduced a priori (McGrath,
1999), and the consequences of one’s actions cannot be foreknown.
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Emerging Debates Regarding the Uncertainty Construct in Entrepreneurship Research
At the same time, despite its importance as a defining characteristic of entrepreneurship,
scholars are raising new questions about the status of uncertainty as an analytical construct
(Ramoglou & Tsang, 2016; Packard et al., 2018; Townsend et al., 2018; Alvarez et al., 2018;
Townsend, Hunt, & Dimov, 2019; Packard & Clark, forthcoming). Currently, these debates
regarding the uncertainty construct focus on several fundamental issues. The first debate centers
on the nature (ontology) of uncertainty within foundational entrepreneurship and innovation
theories (Packard & Clark, forthcoming; Townsend et al., 2018). To date, the fundamental split in
the field is between objective versus subjective theories of uncertainty (e.g., aleatory versus
epistemic uncertainty Packard & Clark, forthcoming) that is, between uncertainty as an
objective property of the decision environment (Townsend et al., 2018) versus uncertainty as the
subjective state of the entrepreneurial actor(s) (McMullen & Shepherd, 2006; Alvarez & Barney,
2007; Foss & Klein, 2012; Packard et al., 2017). The distinction between objective and subjective
uncertainty is important here because it drives to the heart of the reasons why entrepreneurial
decision environments are fundamentally unknowable a priori based on whether the decision
environment is objectively uncertain or whether uncertainty simply reflects the ignorance of
entrepreneurial actors.
A second debate focuses on the role of entrepreneurial action enacted in response to
uncertainty (Townsend et al., 2018). Encompassed within this debate are several spirited
conversations regarding the effectiveness of business planning, rational choice and prediction,
judgment, and design within uncertain environments (Gruber, 2005; Felin et al., 2019). These
debates are generally split between two contradistinctive perspectives on the role of uncertainty in
shaping entrepreneurial action: one depicting uncertainty as an aversive state that inhibits
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entrepreneurial action, and the second propounding the view that uncertainty is a generative force
in stimulating entrepreneurial action (e.g., Alvarez & Barney, 2007; Sarasvathy, 2001; 2008). The
former perspective is typified by the literature that draws on foundational research in
organizational economics, including transaction cost economics (TCE), which argues that
uncertainty is inversely related to risk taking and, therefore reduces the supply of entrepreneurial
action (Coase, 1937; Parkhe, 1993; Williamson, 1979, 1981) while the latter perspective is typified
by theoretical perspectives which focus on the benefits to be accrued through the willingness to
bear uncertainty (Busenitz & Barney, 1997; Knight, 1921; McMullen & Shepherd, 2006;
Schumpeter & Backhaus, 1934; Shepherd, McMullen, & Jennings, 2007).
The third debate centers on the consequences of entrepreneurial actions enacted in response
to uncertain environments. Similar to the debates highlighted above, the issues of enactment
harken back to early administrative theorists like Fayol who noted that the central task of both
managers and entrepreneurs in contending with the problem of uncertainty in organizational
environments is to maintain, as much as possible, “harmonious relations with the environment”
(Wren & Bedeian, 2009: 220). Yet, because so much of the current entrepreneurship literature has
focused so directly on subjective uncertainty, the relationship between objective and subjective
uncertainty remains an open question. In these situations, the danger of misinterpreting the “true”
nature of the surrounding environment amplifies the likelihood entrepreneurs will make fatal
mistakes during the entrepreneurial process. The danger of course is most apparent when
entrepreneurs are confronted with true, a priori objective sources uncertainty that they cannot
explain or wish away. Under these conditions, the negative effects of objective uncertainty will
impact the firm even when entrepreneurs remain ignorant of these external influences.
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In summary, these emerging debates about the nature, role, and status of uncertainty as an
analytical construct in entrepreneurship and organizational research (Ramoglou & Tsang, 2016;
Packard et al., 2018; Townsend et al., 2018; Alvarez et al., 2018; Townsend, Hunt, & Dimov,
2019; Packard & Clark, forthcoming) focus on three main questions: What is the nature of
uncertainty? Which mode of action is most effective for addressing different forms of uncertainty?
And what are consequences of different forms of uncertainty on entrepreneurial ventures? In the
following section, we now turn towards elaborating the logic of a research model which situates
these questions onto a comprehensive model of entrepreneurial action.
Objective versus Subjective Uncertainty
The first question we address centers on the nature of uncertainty, and whether it is best
characterized as a subjective perception of the actor or an objective characteristic of the
environment. This question has perplexed organizational scholars for more than a century
(Shenhav & Weitz, 2000; Wagner-Tsukamato, 2007). From the turn of century into the mid-1920s,
the emphasis among practitioners of scientific management was on uncertainty reduction “through
imposing standard work procedures on the workers” (Shenhav & Weitz, 2000: 375). Around the
same time, administrative theorists such as Fayol emphasized how uncertainty complicated the
task of future-oriented contingency planning by managers: “One cannot anticipate with precision
everything which will happen over a longer period but one can minimize uncertainty and carry out
one’s program as a result…the program must without ceasing be kept, as far as possible, in
harmony with the environment” (Fayol quoted in Wren and Bedeian, 2009: 222). In economic
theory, Knight (1921: 233) published his now classic treatise on the nature of uncertainty, noting
that “we can also employ the terms ‘objective’ and ‘subjective’ probability to designate the risk
and uncertainty respectively,” and defines “true uncertainty” as future events where the
probabilities of the outcomes cannot be measured a priori. The collective force of this work
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inspired in part efforts in organization theory to explore how uncertainty impacts organizational
performance (Blau & Scott, 1962; Thompson, 1967) and the Carnegie School’s emphasis on the
importance of decision heuristics, organizational routines, and flexible decision-making processes
in order to minimize the negative and unavoidable effects of environmental uncertainty on
organizational outcomes (March & Simon, 1958; Cyert & March, 1963).
Yet, despite robust efforts spanning multiple decades to disentangle the “inconsistent and
often-difficult to interpret” relationship between environmental uncertainty and the actions of
organizational actors (Thompson, 1967; Downey & Slocum, 1975), “one source of confusion in
the environmental uncertainty literature is that the term ‘environmental uncertainty’ has been used
both as a descriptor of the state of organizational environments and as a descriptor of the state of
the person who perceives himself/herself to be lacking critical information about the environment
(Milliken, 1987: 133, 134). The problem hinges on whether uncertainty is defined as an objective
characteristic of the environment (e.g., “real indeterminism” Popper, 1982) or whether
uncertainty simply reflects the ignorance of the entrepreneur or manager (Milliken, 1987). This
distinction between objective versus subjective types of uncertainty is important for several key
reasons. On one hand, if uncertainty is defined as an objective feature of the external environment
then regardless of what each individual might perceive or believe to be true, the information needed
to make a decision simply does not exist in any meaningful sense, but actors could still act as if
the decision environment was certain (Townsend et al., 2018). On the other hand, if uncertainty is
defined as a description of the subjective perceptions and beliefs of individual actors then these
perceived forms of uncertainty would ostensibly anchor the idiosyncratic judgments of individual
actors (Keynes, 1937; McKelvie et al., 2011; Forbes, 2007). Under these conditions, the initiation
of entrepreneurial action is thus precipitated through and shaped by an amalgamation of individual
perceptions, consisting of perceived opportunities in the context of perceived uncertainties, created
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by the “pre-commitment of our lives around a particular future scenario, to which we aspire”
(Dimov, 2017; Choi & Shepherd, 2004).
In action theoretic research in the field of entrepreneurship, a consensus appears to be
emerging in recent conceptual work around defining uncertainty through a subjective lens (e.g.,
Packard et al., 2017; Sarasvathy & Dew, 2013; Foss & Klein, 2012; McMullen & Shepherd, 2006;
Sarasvathy, 2001) where the emphasis is placed upon reducing ignorance (i.e., uncertainty
reduction) through entrepreneurial action (Alvarez & Barney, 2007; Shepherd, McMullen, &
Jennings, 2007; McMullen & Shepherd, 2006). And yet, in existing empirical research, uncertainty
is often modeled, as an objective, persistent, broadly applicable, systematic force in entrepreneurial
environments (e.g., Bakker & Shepherd, 2017; Townsend & Busenitz, 2015; Hmieleski & Baron,
2008). Unfortunately, it is quite common for empirical studies to draw on the logic of conceptual
arguments based on a subjective view of uncertainty but still operationalize uncertainty as an
objective characteristic of the external environment. Our point here is not to critique either the
empirical studies or the conceptual work that is emerging in the field of entrepreneurship, but
simply to point to the gap between theory and methods – a gap, we believe, that is bridged by two
stage models of entrepreneurial action which anchor the subjective assessments of uncertainty in
the realities of external environments (McMullen et al., 2007; McMullen & Shepherd, 2006).
Based on this two-stage model, uncertainty cannot be wholly understood by the idiosyncratic
perspectives or beliefs of individual actors, but instead, these perceptions of uncertainty are
anchored in systemic or environmental sources of objective uncertainty.
H1: There is a positive relationship between objective and subjective uncertainty among
organizational actors.
Types of Entrepreneurial Action under Conditions of Uncertainty
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The lack of consensus on the important distinction between objective versus subjective
types of uncertainty stems largely from the observation that regardless of the modality of action,
“entrepreneurs act, even in cases where the underlying research operationalizes objective
uncertainty through archival data (Dimov, 2017). This notion that entrepreneurial action emerges
in the face of uncertainty is grounded in the work of Knight (1921) and others where the
willingness and ability to bear uncertainty is the underlying engine that ultimately generates
entrepreneurial action and the possibility of profit generation. “…[the role of the entrepreneur] is
to improve knowledge, especially foresight, and bear the incidence of its limitations” (Knight,
(1921). McMullen and Shepherd (2006) extended and enriched Knight’s model of uncertainty-
bearing by being the first to consider both the amount of perceived uncertainty and the willingness
to bear uncertainty, allowing analysis at both the individual-level and the system-level, while
incorporating both knowledge (i.e., perceived uncertainty) and motivation (i.e., uncertainty-
bearing) to explain entrepreneurial action. And since other organizational actors, such corporate
managers, are not willing to act in the face of uncertainty (Busenitz & Barney, 1997; Alvarez &
Busenitz, 2001), these perspectives have coalesced to a “…loosely enforced orthodoxy”
(Townsend et al., 2018) in entrepreneurship research is that the presence of uncertainty promotes
entrepreneurial action.
Much of the contemporary research in entrepreneurship anchors this willingness of
entrepreneurs to bear uncertainty based on the assumption that entrepreneurs are uniquely
endowed with (Raffiee & Jie, 2014; Busenitz & Barney, 1997; Baron, 1998) or develop (Autio et
al., 2011; Engel et al., 2014; ) special abilities or decision-making processes that enable them to
navigate fundamentally uncertain environments (Dew et al., 2015). This contemporary view is also
grounded in the earlier work of Knight (1921: 260) who argues “[…] it is fundamental to the
entrepreneur system that it tends to promote better management in addition to consolidating risks
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and throwing them into the hands of those most disposed to assume them.” Because these
uncertainty-bearing “endowments” are not uniformly distributed across different cultural contexts,
a broad literature has emerged which contends that high levels of uncertainty avoidance negatively
impact the willingness of entrepreneurs to take proactive risks (Kreiser et al., 2010). These effects
are also present at the individual level where uncertainty avoidance decreases the willingness of
individuals to engage in self-employment (Minola et al., 212) And where high levels of perceived
uncertainty do not completely discourage individuals from engaging in entrepreneurial action, both
the unique skills and abilities of these individuals combined with the perception of uncertainty
directly shape the types and modes of action these individuals are willing to take (Raffiee & Jie,
2014; McMullen & Shepherd, 2006).
Uncertainty & Innovation. Yet, not all individuals who engage in entrepreneurship are
willing to “bear uncertainty;” Nor is uncertainty-bearing the only mode of action entrepreneurs
pursue. In a complementary article to his now-classic treatise on the role of uncertainty in
entrepreneurship (Knight, 1921), Knight (1942) identifies three types of entrepreneurial action:
innovation, adaptive leadership, and uncertainty-bearing. Regarding innovation, Knight (1942:
128) argues that this mode of action is the primary function of the entrepreneur, and that “the
innovation itself may have various forms, and usually involves some change in the character of
products, combined with some improvement in methods of production.” Contemporary work in
the field of entrepreneurship generally acknowledges the importance of innovation as a mode of
entrepreneurial action under conditions of uncertainty. Scholars exploring the implications of
uncertainty for the creation and emergence of innovation through entrepreneurial action (Alvarez
& Barney, 2007; McMullen & Shepherd, 2006) argue that “one cannot have opportunity without
uncertainty” (McMullen, Plummer, & Acs, 2007: 279). Consistent with this view, prior empirical
works reports various forms of uncertainty are positively linked with new innovations (Baron &
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Tang, 2011; Perez-Luno et al., 2011; Tan, 2001; Zahra, 1991) and the emergence of creative new
products and services (Kyriakopolos & Ruyter, 2004). Although in some cases, the effects appear
to be negligible, there does appear to be a clear relationships between uncertainty and innovation
under conditions of uncertainty (Nakami & Chen, 2014).
H2a: There is a positive relationship between epistemic uncertainty and innovative types
of entrepreneurial action.
Uncertainty & Adaptation. Juxtaposed against innovation, Knight (1942) identifies two
additional, related functions of entrepreneurs: 1) managing new ventures through “constantly
adapting…and attempting to ‘forecast’ such changes” (Knight, 1942: 129); 2) Knight (1942: 129)
pairs his arguments on adaptation with an even more passive view of entrepreneurial action by
noting that the least important function of entrepreneurship involves bearing the “various
contingencies (i.e., uncertainties) which are inherently unpredictable…simply (taking) their
consequences, for good or ill.” In contemporary entrepreneurship research, the role of planning,
forecasting, adaptive behavior, or passive uncertainty-bearing in the face of uncertainty is highly
contested (Gruber, 2005; Wiltbank et al., 2006; Sarasvathy, 2001). On one hand, numerous
scholars have criticized the role of planning or adaptive behaviors in the context on Knightian
uncertainty (Wiltbank et al., 2006; Sarasvathy, 2001; 2008), arguing instead that the irreducible
nature of uncertainty requires alternative approaches to entrepreneurial action (Chandler et al.,
2011). In contrast, other scholars have emphasized the importance of adaptive or iterative
approaches to addressing the impact of uncertainty on new ventures (Bakker & Shepherd, 201).
Examples of these approaches include real option strategies (McGrath, 1999; 1997, improvisation
(Hmieleski et al., 2013) and other iterative approaches to reducing uncertainty (Artinger & Powell,
2016; Tang & Wezel, 2015; Anderson et al., 2009). In these cases, adaptive strategies, whether
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pro-active or passive, are likely enacted in response to the perception of uncontrollable facets of
the external environment,
H2b: There is a positive relationship between epistemic uncertainty and adaptive types of
entrepreneurial action.
H2c: There is a positive relationship between epistemic uncertainty and uncertainty-
bearing (passive avoidance) types of entrepreneurial action.
The Consequences of Entrepreneurial Action on Organizational Performance
Ultimately, the purpose of entrepreneurship is not to simply act under conditions of
uncertainty; Rather through the creation of new goods and services, entrepreneurs coordinate
resources, suppliers, customers, and employees to deliver “future goods and services” thereby
driving social and economic progress (Venkataraman, 1997). Towards this end, it is important to
make a careful distinction between the initial willingness to engage in entrepreneurial acts and the
ultimate outcomes of these actions (Alvarez & Barney, 2007). Since by its very nature, structural
forms of true, underlying, a priori irreducible uncertainty (McGrath, 1999) are a function of
external factors that are ultimately unknowable and, outside the control of the entrepreneur, the
force of impact on the firm is impossible to anticipate. For Knight (1921), this distinction was
crucial to his theorizing as the presence of uncertainty merely provides the opportunity but not the
guarantee to generate a profitable result for the entrepreneur. “We must see at once that it is
perfectly possible for entrepreneurs as a class to sustain a net loss…this would be the natural results
in a population combining low ability with high ‘courage’” (Knight, 1921: 284).
Innovation & Organizational Performance. Consistent with this argument, contemporary
research suggests that, under conditions of uncertainty, entrepreneurs are more willing than other
actors to commercialize new innovations (Townsend & Busenitz, 2015). The willingness to act in
the face of high levels of uncertainty stems in part from the role of biases, judgements, and
heuristics in entrepreneurial action and decision-making, involving processes and cognitive
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processing that have given rise to behavioral economics (e.g. Tversky & Kahneman, 1974),
behavioral strategy (Powell, Lovallo & Fox, 2011), and behavioral foci within entrepreneurship
(Baron, 2007). Recent studies based in behavioral economics (Camerer & Lovallo, 1999) and
entrepreneur cognition research (Busenitz & Barney, 1997) indicates that entrepreneurs are highly
susceptible to the overconfidence bias and appear to be especially prone to the negative effects of
hubris (Hayward et al., 2006). Moreover, these effects appear to be exacerbated in dynamic and
turbulent environments (Ensley, Pearce & Hmieleski, 2006) thereby leading to problems of excess
entry by overconfident entrepreneurs attempting to commercialize new innovations in emerging
markets (Wu & Knott, 2006).
H3a: There is a negative relationship between innovative action and firm performance
under conditions of uncertainty
Adaptation, Uncertainty-bearing, & Organizational Performance. The aggregate problems
of excess entry tend to amplify the problems of volatility in uncertain environments as the rush of
new firms into emerging opportunity spaces drives up both factor prices for the key inputs utilized
in production or operations (Barney, 1986) and leading to a crowding out effect on the demand
side for the full range of goods and services (Camerer & Lovallo, 1999; Wu & Knott, 2006). Under
these conditions, as the rate of entry exceeds the growth of demand for products and services, firm
survival rates will decrease significantly (Hunt, 2013, 2015). Entrepreneurs appear susceptible to
these problems since, as some evidence suggests, their entry decision is largely driven not by an
estimation of outcome probabilities by rather based on the degree of confidence in their own
abilities (Camerer & Lovallo, 1999; Townsend et al., 2010). That is, if entrepreneurs believe in
their abilities a priori their rate of entry is much higher than other entrepreneurs with a less robust
belief in their abilities. By implication, the extent to which the judgment and decisions of
entrepreneurs are tied to inflated appraisals of their prospects of success, anchored, in part, by an
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unrealistic assessment of their own abilities, the inaccuracy demand forecasts (Efendigil, et al.,
2009), limit the extent to which adaptive decision (e.g., Bayesian updating Alvarez & Parker,
2009) might be enacted.
H3b: There is a negative relationship between adaptive action and firm performance under
conditions of uncertainty
H3c: There is a negative relationship between uncertainty bearing and firm performance
under conditions of uncertainty
The Consequences of Uncertainty on Organizational Performance
The role of entrepreneurial action in determining the success of new ventures is also very
likely to be offset by the direct impact of uncertainty on organizational performance
(Venkataraman, 1997). Uncertainty challenges entrepreneurial actors since there are virtually
unlimited possible future states of the world (McGrath & MacMillan, 2000). Since actors engage
these possible future worlds with only partial knowledge, the willingness to bear such uncertainties
is at the center of entrepreneurial action (McMullen & Shepherd, 2006). Furthermore, since
entrepreneurs cannot simultaneously pursue opportunities in multiple possible worlds, the
opportunity costs of action are high under conditions of uncertainty (Shackle, 1955). The “non-
divisible, non-seriable experiments” Shackle, 1955: 8) that characterize entrepreneurial action
belie attempts for pooling or aggregating these uncertainties in a manner in which they can be
insured against (Sarasvathy, et al., 2013). Much of this uncertainty stems from the inherent
complexities that characterize dynamic circumstances (Davis, Eisenhardt, and Bingham, 2009) in
which markets, technologies, and business models face continual change. Under these conditions,
entrepreneurs face the challenging task of organizing resources and personnel to create and capture
value (Klein, 2008).
Objective Uncertainty & Organizational Performance. Objective approaches to
uncertainty focus on the nature and impact of unanticipated events given the configuration and
18
defining characteristics of an economy, market, or organization (Knight, 1921). Objective
uncertainty constitutes an important facet of the complex interactions between actors, structures,
and events including occurrences that are rare or even unprecedented. According to Knight
(1921: 33), “five generic changes” are constant features of the cyclical nature of economic systems:
population increases, capital increases, production method improvements, changes in
organizational forms, and changes in customer preferences. Provided these changes are predictable
and “the law of change is known” there is no potential for firms to generate economic profits since
these measureable “risks” can be hedged or insured against. When these changes are unpredictable
and defy categorization, the resulting uncertainty creates the potential for generating economic
profits (Knight, 1921) and thus entrepreneurs play the central role of bearing such uncertainties.
To the extent that objective uncertainties exist in entrepreneurial environments, their presence
limits the generation of entrepreneurial rents through a structural reconfiguration of opportunities
that would otherwise be discovered (Kirzner 1979), created (Alvarez, et al. 2012), effectuated
(Sarasvathy 2001), or imagined (Klein 2008) by entrepreneurial actors. Absent the opportunity to
bear uncertainty there is no meaningful basis for the emergence of entrepreneurial action.
Given the continually shifting nature of consumer markets and competitive industries, all
firms face a moving target in seeking to develop and channel their respective competencies and
resources to productive use; but, the challenge is particularly acute for new ventures, seeking to
provide novel goods and services with limited resources while functioning within the perilous
frame of dynamic complexity. Before products are built, customer preferences are validated, and
the firm’s strategy is set, entrepreneurs must begin the process of acquiring and organizing
heterogeneous bundles of resources with clear capital constraints and ambiguous resource values
(Foss & Klein, 2012). To the extent that entrepreneurs can identify undervalued resources and
generate opportunities to maximize complementarities through bundling these resources, wealth
19
can be created through the organizing process (Townsend & Busenitz, 2008). This is a difficult
task, however, because if factor markets are functioning efficiently, the marginal productivity of
key resources will be reflected in the prices these resources command in the market (Barney,
1986). Under these conditions, effective factor market strategies require “strategic factor market
intelligence” through which entrepreneurs can identify and acquire undervalued resources
(Barney, 1986), largely by perceiving valuable uses for resources that others do not simultaneously
perceive Alvarez & Busenitz, 2001).
H4: There is a negative relationship between objective uncertainty and organizational
performance.
Subjective Uncertainty & Organizational Performance. These conditions place a
significant premium on judgment of entrepreneurs to identify valuable resources under conditions
of high uncertainty (Foss & Klein, 2005; Klein, 2008). Yet, apart from the exchange value of
resources set by factor markets, entrepreneurs play an important role in valuing resources based
on their functional and symbolic uses (Townsend & Busenitz, 2015), thereby yielding numerous
pathways for creating unique bundles of valuable resources. Clearly, while there are numerous
ways to recombine resources to create value combinations, as markets for novel resource
combinations will always be incomplete due to changes in consumer preferences (Foss, Foss,
Klein, & Klein, 2007). These changes, in turn, will continue to generate new opportunities for
organizing resources into more valuable bundles (Foss, Foss, Klein, & Klein, 2007). These
challenges of identifying and orchestrating (Sirmon et al., 2011) valuable resources are
compounded by the fact that many strategically valuable resources are not openly traded or
exchanged on strategic factor markets (Dierickx & Cool, 1989). Instead, these vital resources are
created by entrepreneurs (Alvarez & Barney, 2007), often through the organizing process
(Ardichvili et al. 2003), which places a premium on experienced actors resiliently executing in the
20
context of perceived uncertainty. Entrepreneurial firms face substantial disadvantages in this
regard as they lack an operating history and have not had sufficient time to develop complementary
ties among these resources (Townsend & Busenitz, 2015). For these reasons, entrepreneurial
judgment in the face of ignorance and subjective uncertainty is essential to the organizing process
(Klein, 2008), and is inextricably linked with organizational performance.
While subjective uncertainties are bounded up within entrepreneur imaginativeness and
judgment (Kier & McMullen, 2018), entrepreneurial action under conditions of uncertainty also
amplify the frequency with which cognitive biases influence entrepreneur decision-making
(Busenitz & Barney, 1997). Entrepreneurs are particularly susceptible to the overconfidence bias
where they tend to overestimate both their abilities (Townsend, Busenitz, & Arthurs, 2010) and
probability of success (Koellinger, Minniti, and Schade, 2007). Overconfidence also exacerbates
problems with entrepreneur hubris (Hayward et al., 2006), creating problems of excess entry in
new and emerging markets (Koellinger et al., 2007). Excess entry creates numerous supply-side
challenges in the aggregate for markets as the mismatch between available supply and market
demand amplify survival pressures on both incumbents and new entrants (Santarelli & Vivarelli,
2007). Oversupply also can lead to price deflation in emerging markets as an abundance of firms
strive to cover both entry costs and fixed asset costs through increased sales (Camerer and Lovallo,
1999).
In addition to rushing into new markets, hubris also tempts entrepreneurs to overcommit
resources to opportunities with highly speculative pay-offs and low probabilities of success
(Hayward et al., 2006). The framing of such opportunities is crucial as both structural uncertainty
and high levels of ambiguity produce inconsistent risk preferences among entrepreneurs and other
market actors (cf. Kahneman & Tversky, 1979; Ellsberg, 1961). These inconsistent preferences
can generate numerous coordination problems for entrepreneurs and their stakeholders as the
21
misalignment of objectives and the interpretation of the surrounding environment challenge the
organizing efforts of entrepreneurs (Harper, 2008). Overall, the prevalence of biases and heuristics
in entrepreneur decision-making, exacerbated by the uncertainty of entrepreneurial environments,
raises key challenges for the long-term performance and success of entrepreneurial endeavors.
H5: There is a negative relationship between subjective uncertainty and organizational
performance.
The Mediating Effects of Entrepreneurial Action on Organizational Performance. As we
noted earlier in the paper, one of the central debates in the field of entrepreneurship is split between
competing views of whether uncertainty exerts a positive or negative global effect on
organizational performance (Sarasvathy, 2001; McMullen & Shepherd, 2006; Alvarez & Barney,
2007; Alvarez & Barney, 2010). In one stream of research, scholars uphold the standard view in
organizational research of uncertainty as an aversive state which inhibits entrepreneurial action
and organizational performance. In the second stream, scholars propound the view that
entrepreneurs represent a special class of actors who are willing and able to bear the uncertainty
in the external environment. This second perspective has emerged in recent years as the
mainstream view in the field of entrepreneurship (McMullen & Shepherd, 2006) and remains
central to theory development in several important research domains in the field of
entrepreneurship (e.g., Busenitz & Barney, 1997; Sarasvathy, 2001; McMullen & Shepherd, 2006;
Alvarez & Barney, 2007; York & Venkataraman, 2010). The crux of these arguments hinges on
the notion that rather than generating an aversive state, the presence of uncertainty is the source of
entrepreneurial opportunities (Alvarez & Barney, 2010).
This notion that opportunities emerge out of uncertainty is grounded in the work of Knight
(1921) and others where the willingness and ability to bear uncertainty is the underlying engine
that ultimately generates entrepreneurial action and the possibility of profit generation. “…[the
role of the entrepreneur] is to improve knowledge, especially foresight, and bear the incidence of
22
its limitations” (Knight, 1921). Importantly, this perspective has been extended and refined by the
work of McMullen and Shepherd (2006) and others to consider both the amount of perceived
uncertainty and the willingness to bear uncertainty, allowing analysis at both the individual-level
and the system-level, while incorporating both knowledge (i.e., perceived uncertainty) and
motivation (i.e., uncertainty-bearing) to explain entrepreneurial action. Towards this end, the
complex linkages among uncertainty and entrepreneurial action with regard to entrepreneurial
performance, outcomes, and survival are a function of forces factually exerted by external realities,
consisting of socially embedded, market-based consequences which are filtered through an actor-
entrepreneur’s perceptions. Organizational performance is thus directly impacted by substance,
context, speed, and consequences of entrepreneurial action. Since new and small firms are
typically attempting to existing markets by offering goods and services that are in form or fashion
novel, there is an inherent element of social disruption that tends to increase the challenges of
navigating uncertainty environments. To contend with high levels of uncertainty, individual level
approaches to judgment and decision-making in entrepreneurship draw from research in behavioral
economics to explore the role of biases and heuristics in entrepreneur decision-making (Busenitz
and Barney, 1997). Since new markets are by nature incomplete and the relevant information is
only partially known by actors attempting to enter into these markets, pattern-matching capabilities
are at a premium in entrepreneurial contexts (Baron, 1998). In these cases, entrepreneurs must
attend to weak and incomplete signals from the environment, using imagination and creativity to
identify future opportunities for action (Kier & McMullen, 2018; McMullen, 2015; Klein, 2008).
In doing so, entrepreneurial action provides the critical link mediating link between uncertainty
and organizational performance.
H6: Entrepreneurial action mediates the relationship between subjective uncertainty and
organizational performance.
23
METHODS & DATA
In response to a growing number of callsThe purpose of this study is to address important
emerging debates in entrepreneurship and organizational research about the nature, role, and status
of uncertainty as analytical construct in existing empirical research (Ramoglou & Tsang, 2016;
Packard et al., 2018; Townsend et al., 2018; Alvarez et al., 2018; Townsend, Hunt, & Dimov,
2019; Packard & Clark, forthcoming) (Packard & Clark, forthcoming; Townsend et al., 2018;
Alvarez et al., 2018; Packard et al., 2017; Ramoglou & Tsang, 2016; McKelvie et al., 2011). We
take up this challenge building on meta-analytic techniques developed in previous research (e.g.,
Hunter & Schmidt, 2004) to evaluate the status of uncertainty as an analytical construct in the field
of entrepreneurship. Specifically, we utilize Cheung’s (2014; 2015) approach to multilevel
structural equation modeling (SEM). Based on analyses, we make fundamental contributions to
the burgeoning literature on uncertainty in entrepreneurship research, and take decisive steps
towards disentangling the multilevel and multidimensional relationship among different types of
uncertainty, different modes of entrepreneurial action, and organizational performance among
entrepreneurial ventures, thereby contributing to future theory development in the field of
entrepreneurship.
In order to address these emerging debates about the nature, role, and status of uncertainty
in entrepreneurship and organizational research (Ramoglou & Tsang, 2016; Packard et al., 2018;
Townsend et al., 2018; Alvarez et al., 2018; Townsend, Hunt, & Dimov, 2019; Packard & Clark,
forthcoming) we use the tools of meta-analysis and meta-structural equation modeling to examine
the state of empirical evidence in a systematic fashion to address our three main research questions:
What is the nature of uncertainty? Which mode of action is most effective for addressing different
forms of uncertainty? And what are consequences of different forms of uncertainty on
entrepreneurial ventures? As we noted earlier in the paper, despite the fact that as an analytical
24
construct, uncertainty remains “a loosely enforced orthodoxy among entrepreneurship scholars”
(Townsend et al., 2018), no previous studies-to-date have systematically examined the relationship
among different types of uncertainty, different modes of entrepreneurial action, and the
performance of entrepreneurial ventures. Therefore, in direct response to the call from a growing
chorus of scholars asking for more nuanced and precise approaches to exploring the role of
uncertainty in theories of entrepreneurship action (Packard et al., 2017; Ramoglou & Tsang, 2016),
we conducted this study to test the canonical conceptions regarding the relationship among
uncertainty, entrepreneurial action, and organizational performance.
Database and Inclusion criteria
Similar to search techniques used previously in the study of entrepreneurial phenomena
(e.g. Brinckmann et al., 2010; Rauch & Frese, 2007), we searched all empirical articles for the
period 1980 to 2017 that reported correlations between some facet of uncertainty, entrepreneurial
action, and organizational performance. We conducted our literature search using several different
methods. First, we used Web of Science to conduct a systematic search for articles that might
broadly fit within our domain of interest, using the following search strings for each individual
journal: Topic -- entre* OR innov*; Topic – uncert* OR dyna* OR vola* OR turb*; years – 1980
to 2017. Table One reports on the results of this electronic search.
*******************************************
Please Insert Table One about Here
*******************************************
Our initial search yielded 1615 articles. Next, two members of authorship team reviewed each
article and removed articles from the study set based on three criteria: 1) study deemed to not be
relevant to the central research questions (e.g., articles were removed where search string
uncert* appears solely based on a discussion of the article’s statistical models); 2) Non-
quantitative articles (e.g., qualitative and conceptual articles were removed from the study set); 3)
25
No reported correlations between any of the variables of interest in the study. Consistent with these
criteria, any articles which could be removed based on one of these factors was removed after both
coders agreed the article should be excluded. Based on these inclusion criteria, the total set of
articles was reduced down to 86. In addition to the electronic search, due to changing electronic
subscriptions through Web of Science to individual journals for all years included within the study,
we then used the ABI-Inform database to search each journal issue-by-issue for the entire available
set of articles encompassed within the scope of the study. We also posted emails on several
different listservs managed by the Academy of Management on several different occasions asking
for additional unpublished studies. Through both the manual search and the email request, we
identified 115 additional studies which were included in the final set, resulting in a total sample of
201 studies.
Meta-Analytic Modeling
We followed the general procedures of psychometric meta-analysis outlined in classic texts
by Hunter and Schmidt (2004; Schmidt & Hunter, 2015), but updated several aspects of these
techniques to address issues of dependencies in effect size estimates (Cheung, 2015). Specifically,
we relied on reported information concerning predictor and criterion reliability to correct for
attenuation, and used sample-size weighted estimates of reliabilities to correct correlations that did
not report this information. As is often the case in meta-analysis, many of the samples we identified
for inclusion produced multiple correlations that might be used (e.g., a single study might employ
two measures of organizational performance, yielding at least two dependent effect size estimates).
Cheung (2014; 2015) recently introduced a multilevel structural equation modeling (SEM)
approach that allows for the inclusion of all viable effects while modeling any dependencies that
might exist within a particular study. This approach allows all identified correlations to contribute
to both the average effect size as well as providing a more accurate assessment of the variability
26
of effect sizes. Specifically, it produces separate estimates of variability within studies (for studies
with multiple effect size estimates) and variability between studies. The model developed by
Cheung (2015) is as follows:
Level 1: yij =
l
ij + eij
Level 2:
l
ij = fj + u(2)ij
Level 3: fj =
b
0 + u(3)ij
Where
l
ij is the coded correlation; eij is the sampling variance for the ith effect in the jth cluster
(when a sample produces 1 effect, then i=1, and “cluster” j has just 1 effect; when a sample
produces m dependent effects, then i = 1 to m within cluster j); fj refers to the estimated effect size
for cluster j;
b
0 refers to the estimated effect size for the population of effects, and u(2)ij and u(3)ij
refer to the random effects (heterogeneity) within each of the clusters and the population,
respectively. In the current meta-analysis, some studies reported only the predictor reliability,
others just the criterion reliability, and still others reported both or neither. As a result, we relied
on estimates for eij that take these different scenarios into account (Raju, Burke, Normand, &
Langlois, 1994).
Applying this procedure allowed us to code 617 total effect sizes across 201 independent
samples. We then examined this distribution of effects for statistical outliers (Beal, Corey, &
Dunlap, 2002; Huffcutt & Arthur, 1995). Based on a combination of effect size and sample size,
our analysis identified a total of 13 effects that departed markedly from the rest of the distribution
(3 on the negative side; 10 on the positive side). We then examined the studies that produced these
effects and through discussion decided to drop eight of the effects.
2
Furthermore, two additional
studies had sample sizes one or more orders of magnitude larger than the rest of the studies (i.e.,
N = 22,388 and N = 1,269,420). Although these effects were not identified as statistical outliers
2
Specific reasons for the inclusion or exclusion of each identified outlier are available
from the first author.
27
(i.e., their effect sizes fell toward the middle of the distribution), we removed them from our
analyses so that our estimates would not be dominated by any single study. Finally, we conducted
sensitivity analyses that compared results including all potential outliers to results with the
exclusions just noted. As the results did not differ greatly in any case, we decided to move forward
without the outlier effects.
Analytic Strategy
Our approach to examining the hypotheses involved populating a meta-analytic correlation
matrix (see Table 2). We then used this matrix to test the model depicted in Figure 1. As can be
seen, there were four cells of the matrix for which estimates could not be derived. First, and most
importantly, not a single study identified in our search examined both objective and subjective
uncertainty in the same sample but instead operationalized uncertainty either as an objective or a
subjective state. The surprising lack of studies which attempted to calibrate subjective assessments
of uncertainty with objective types of uncertainty raises several important questions about the
growing disconnect between the empirical literature and the conceptual treatment of uncertainty
in entrepreneurship research. We will return to these problems momentarily.
In addition, no study examined the extent to which the different modes of entrepreneurial
actions are inter-related. In keeping with Knight's (1942) original descriptions of these actions,
most studies focused on one action only, and given the fact that Knight described these actions as
independent approaches to handling uncertainty, we made the tentative assumption that they held
inter-correlations of zero. Indeed, Knight defined uncertainty bearing essentially as that which is
enacted in the absence of innovation or adaptation, rendering its correlation with these two actions
necessarily as zero.
As we could identify no estimates of the relation between objective and subjective
uncertainty, we adopted a different approach. Specifically, we examined our hypothesized model
28
under a set of varying assumptions about the potential true nature of the connection between
objective and subjective uncertainty. A favorable view might suggest that actors are at least
moderately capable of divining the extent of uncertainty in their environment. A less favorable
view would in turn suggest that only a modest degree of accuracy can be perceived concerning
uncertainty. A harsh view of the abilities of actors to discern objective levels of uncertainty would
suggest no relationship whatsoever. Finally, as some evidence prior literature reports that in certain
cases there are negative correlations between objective and subjective types of uncertainty (e.g.,
Tosi, Aldag, & Storey, 1973). In other words, actors might perceive decision environments to be
uncertain/certain when the objective measures report the opposite conditions to be true. To
examine these scenarios, we estimated out model four times, substituting correlations of .3, .1, 0,
and -.1 between subjective and objective forms of uncertainty to match the respective cases above.
We then compared indices of model fit to evaluate which effect size would be most likely given
the validity of the remaining aspects of our model. Through these comparisons, we are also to
estimate the effects of varying levels of objective uncertainty on subjective uncertainty. We will
discuss the implications of these models in our Discussion Section below.
RESULTS
We now turn towards a discussion of the results of our analysis of the existing empirical
literature on the relationships among different types of uncertainty, different modes of
entrepreneurial action, and organizational performance. Table 2 reported here summarizes the
results of our meta-analytic assessment of the hypothesized relationships we discuss above.
*******************************************
Please Insert Table Two about Here
*******************************************
In H1, we hypothesized that there would be a positive relationship between objective and
subjective types of uncertainty. As we noted above, however, no study in the set we examined in
the paper actually tested this relationship. This is an important gap in existing empirical research.
29
Therefore, H1 is not supported based on a lack of available data. In light of this notable gap in
existing research, we will discuss the results of our post hoc sensitivity analyses in the Discussion
Section to provide a detailed set of guidelines for future research to examine this question.
In H2a through H2c, we argued that, consistent with contemporary entrepreneurship
theory, Subjective Uncertainty would be positively related to the different forms of entrepreneurial
action. As part of this analysis, we also tested the relationship between Objective Uncertainty on
the three modes of entrepreneurial action to see if perhaps Objective Uncertainty was exerted an
independent set of effects on entrepreneurial action which were not being mediated through
Subjective Uncertainty. As the results in Table 2 indicate, our analyses of estimated population
correlation (corrected for unreliability in the predictor and criterion) between Subjective
Uncertainty and Innovation and Adaptation, respectively, provide strong support for H2a and H2b
(i.e., Subj Unc Innov: =.134***; Subj Unc Adapt: =.085**). However, for H2c, the
hypothesized relationship between Subjective Uncertainty and Uncertainty-bearing is not
significant (i.e., Subj Unc – Bear: =.005 NS). In addition, our analysis also indicates that there are
no significant relationships between Objective Uncertainty and any mode of entrepreneurial
action. In H3a through H3c, we hypothesized that each of the modes of entrepreneurial action
would be positively related to firm performance. As the results in Table 2 indicate, our analyses of
estimated population correlation (corrected for unreliability in the predictor and criterion) between
Innovation, Adaptation, and Uncertainty-bearing respectively, provide strong support for H3a and
H3b (i.e., Innov -- Perf: =.140***; Adapt -- Perf: =.068**). However, for H3c, the hypothesized
relationship between Uncertainty-bearing and Organizational Performance is not significant (i.e.,
Bear -- .Perf: =.040 NS).
In H4 – H6, we turn our attention to examining the extent to which the effects of Objective
and Subjective Uncertainty on Organizational Performance are mediated through the modes of
30
entrepreneurial action that are operationalized within our sample of studies. To test these
relationships, we use the population correlations we calculated in our meta-analysis to estimate a
multilevel structural equation model (SEM), including of all viable effects while modeling any
dependencies that might exist within a particular study. As we noted above, this approach allows
all identified correlations to contribute to both the average effect size as well as providing a more
accurate assessment of the variability of effect sizes across each estimated path in the research
model. Figure 1 reports the results of this analysis.
*******************************************
Please Insert Figure One about Here
*******************************************
In H4, we hypothesized that Objective Uncertainty would be negatively related to Organizational
Performance. However, as Figure 1 reports, the estimated path coefficient between Objective
Uncertainty and Organizational Performance is positive (.02) and the coefficient is non-significant
suggesting a lack of support for this hypothesis. In H5, we argued that the relationship between
Subjective Uncertainty and Organizational Performance is negative. Based on the results of our
analysis, the estimated path coefficient is negative (-.03) and significant suggesting support for
this hypothesis. Lastly, in H6, we argued that the effects of Subjective Uncertainty on
Organizational Performance would be mediated through the various modes of entrepreneurial
action we discuss in this study. As Figure 1 illustrates, the estimated path coefficients in the full
SEM are positive from Subjective Uncertainty to Innovation and Adaption, and non-significant
from Subjective Uncertainty to Uncertainty-bearing. Furthermore, the path coefficients from
Innovation, Adaption, and Uncertainty-bearing to Organizational Performance are significant and
positive, indicating that the effects of Subjective Uncertainty are partially mediated by the modes
of entrepreneurial action tested within the model. These results suggest qualified support for H6.
Overall, based on the results of our analyses, we find strong support for several key questions
regarding the nature, role and impact of subjective uncertainty on different modes of
31
entrepreneurial action and organizational performance. Furthermore, we find that objective
uncertainty does not appear to play a role in our models. Taken together, these results indicate
strong support for theories of entrepreneurial action based on subjectivist notions of uncertainty
(Packard et al., 2017; Sarasvathy & Dew, 2013; Foss & Klein, 2012; McMullen & Shepherd, 2006;
Sarasvathy, 2001). We will discuss the implications of these findings for existing debates in
entrepreneurship and organizational research in the next section.
DISCUSSION & DIRECTIONS FOR FUTURE RESEARCH
In response to a growing number of scholars calling for greater precision and clarity in how
the field of entrepreneurship theorizes and operationalizes the uncertainty construct, the central
purpose of this paper is to examine the state of the empirical literature on the nature, role, and
status of uncertainty as an analytical construct in entrepreneurship and organizational research
(Ramoglou & Tsang, 2016; Packard et al., 2018; Townsend et al., 2018; Alvarez et al., 2018;
Townsend, Hunt, & Dimov, 2019; Packard & Clark, forthcoming). Using the tools of multilevel
structural equation modeling (SEM Cheung, 2014; 2015), we systematically analyze 201
previously published empirical studies in the fields of entrepreneurship and organizational research
to answer three main research questions: What is the nature of uncertainty? Which mode of action
is most effective for addressing different forms of uncertainty? And what are consequences of
different forms of uncertainty on entrepreneurial ventures? In this section, we now turn towards
discussing the implications of our analyses for several core debates in the field of entrepreneurship,
followed by a discussion of future research opportunities.
Debate #1: Objective versus Subjective Uncertainty
The first debate we discussed in the paper raises questions about the nature (ontology) of
uncertainty within entrepreneurship and organizational research (Packard & Clark, forthcoming;
32
Townsend et al., 2018). In recent research, scholars have been pointing to the need to clarify how
the field defines and theorizes objective and subjective types of uncertainty (e.g., aleatory versus
epistemic uncertainty – Packard & Clark, forthcoming). Addressing this question is fundamentally
important for entrepreneurship scholars given the central role uncertainty plays in entrepreneurship
theory, and because the distinction between objective and subjective uncertainty is foundational to
why entrepreneurial decision environments are fundamentally unknowable a priori.
Towards this end, the results of our analyses provide a clear verdict regarding the
competing views on the role of objective versus subjective uncertainty. Consistent with the results
of our use of Cheung’s (2014; 2015) meta-analytic approach to multilevel structural equation
modeling (SEM), we do not find evidence to support the contention that objective uncertainty is
causally related to either entrepreneurial action or organizational performance. Instead, we find
clear support for the contemporary approaches to subjective uncertainty which are fundamental to
emerging conceptual work in the field. By implication, these results suggest that the causal role of
uncertainty in entrepreneurship is inextricably bound to the idiosyncratic judgments of individual
actors (Keynes, 1937; McKelvie et al., 2011; Forbes, 2007). Therefore, the initiation of
entrepreneurial action that is shaped by an entrepreneur’s subjective judgments is fundamental to
the ultimate success of entrepreneurial action (Foss & Klein, 2012; McMullen & Shepherd, 2006).
Debate #2: Uncertainty & the Modes of Entrepreneurial Action
The second debate we address in this study examines how various modes of entrepreneurial
action are enacted in response to uncertainty (Townsend et al., 2018; Packard et al., 2017;
McMullen & Shepherd, 2006). Building on foundational work (Knight, 1942), we examined how
different types of uncertainty were causally linked with three different modes of entrepreneurial
action: innovation, adaption, and passive, uncertainty-bearing (Busenitz & Barney, 1997; Knight,
1921; McMullen & Shepherd, 2006; Schumpeter & Backhaus, 1934; Shepherd, McMullen, &
33
Jennings, 2007). Again, here, our models provide clear evidence of the important role that
subjective uncertainty plays in shaping the modes of action that are enacted by entrepreneurs.
Consistent with work which argues that “one cannot have opportunity without uncertainty”
(McMullen, Plummer, & Acs, 2007: 279), we find strong support for the link between subjective
uncertainty and innovation (e.g., Baron & Tang, 2011; Perez-Luno et al., 2011; Tan, 2001; Zahra,
1991). At the same time, we find significant but slightly weaker support for the relationship
between subjective uncertainty and adaptive modes of entrepreneurial action. At the same time,
we find no evidence that subjective uncertainty is directly linked to more passive forms of
uncertainty-bearing. Furthermore, we find no evidence to support the notion that objective
uncertainty is directly linked to entrepreneurial action. Collectively, these results indicate strong
support for the premise that in response to subjective uncertainty, entrepreneurs generate new
opportunities for action (McMullen & Shepherd, 2006; Foss & Klein, 2012; Alvarez & Barney,
2007).
Debate #3: Consequences of Entrepreneurial Action on Organizational Performance
The third debate we address in this study centers on the consequences of entrepreneurial
actions enacted in response to uncertain environments on organizational performance. One of the
central questions in this debate centers on whether entrepreneurs increase the danger of failure if
they misinterpret the “true” nature of the surrounding environment? As we noted, the true danger
emerges when entrepreneurs are faced with objective sources uncertainty that they cannot explain
or wish away. Again, here, the results of our analyses indicate strong support for the notion that
two of modes of entrepreneurial action that are enacted in response to subjective uncertainty
strongly enhance organizational performance. Specifically, our models indicate that innovation
and adaption when enacted by entrepreneurs, positively enhance organizational performance
34
consistent with the both emerging theoretical perspectives on the role entrepreneurial action
enacted in response to subjective uncertainty, and also with Knight’s (1942) original work on the
functions of the entrepreneur. Furthermore, we find that more passive modes of entrepreneurial
action do not appear to positively impact organizational performance in the same way. Overall,
these results confirm a foundational view in the field of entrepreneurship regarding entrepreneurial
action as a critical form of social agency which, when enacted in the face of uncertainty, enables
entrepreneurs to turn uncertainty in viable opportunities for generating new products and services
(Venkataraman, 1997).
Future Research Opportunities
3
As we noted above, we were unable to test one of the central hypothesized relationships in
the study between objective and subjective types of uncertainty in the context of entrepreneurial
action since no previous study in our sample had attempted to model this relationship. For future
research, this is an important question to address since it drives into the heart of the relative
importance placed on entrepreneurs calibrating their judgments of objective environmental
uncertainty with their perceptions of subjective uncertainty. To help guide this future line of
research, we conducted a supplementary analysis using the results of our multi-level SEM to
estimate the relative impact of various correlations between objective and subjective uncertainty.
Table 3 reports on the results of these analyses based on different modeled correlations based on
different assumptions of how correlated the objective and subjective measures of uncertainty might
be under different conditoins. The purpose behind this test is to see whether higher correlations
3
Although space limitations prevent a full discussion of the implications of our models for future
research, we will now briefly discuss one important implication of our study for future research.
35
between objective and subjective uncertainty – implying that the entrepreneurs is interpreting the
environment accurately – are important for enhancing the overall success of venture.
*******************************************
Please Insert Table Three about Here
*******************************************
Towards this end, we modeled several different correlation levels to help us determine the relative
sensitivity of our overall model on the accuracy of the entrepreneur’s assessment of the
environment. As Table 3 indicates, higher correlations between objective and subjective
uncertainty do not enhance the overall fit of the models. Instead, our analyses indicate that as long
as the entrepreneur appears to be at least moderately aware of the external, objective uncertainty
(i.e., the models with the “best fit” are based on correlations of .3), the enactment of innovative
and adaptive modes of entrepreneurial action will be most strongly associated with enhanced
organizational performance. By implication, these results preserve the importance of
entrepreneurial judgment (Foss & Klein, 2012) in the face subjective uncertainty, where the
entrepreneur is moderately aware of the “reality” of the surrounding uncertainty but choose to act
decisively in the face of such uncertainty.
SELECTED REFERENCES
4
Alvarez, S. A., & Barney, J. B. (2007). Discovery and creation: Alternative theories of
entrepreneurial action. Strategic Entrepreneurship Journal, 1(1-2), 11-26.
Alvarez, S., Afuah, A., & Gibson, C. (2018). Editors’ comments: should management theories take
uncertainty seriously? Academy of Management Review, In Press.
Dimov, D. (2007). From opportunity insight to opportunity intention: The importance of person–
situation learning match. Entrepreneurship Theory and Practice, 31(4), 561-583.
Dimov, D. (2011). Grappling with the unbearable elusiveness of entrepreneurial opportunities.
Entrepreneurship Theory and Practice, 35(1), 57-81.
Foss, N. J., & Klein, P. G. (2012). Organizing entrepreneurial judgment: A new approach to the
firm. Cambridge University Press.
4
Unfortunately, space limitations prevent us from including all 200+ citations and so we will
report select references from the text of the study. A comprehensive and complete list is
available from the lead author of the study.
36
Kier, A. S., & McMullen, J. S. (2018). Entrepreneurial imaginativeness in new venture ideation.
Academy of Management Journal, 61(6), 2265-2295.
Klein, P. G. (2008). Opportunity discovery, entrepreneurial action, and economic
organization. Strategic Entrepreneurship Journal, 2(3), 175-190.
Knight, F. H. (1921). Risk, Uncertainty and Profit. New York: Hart, Schaffner and Marx.
McGrath, R. G. (1999). Falling forward: Real options reasoning and entrepreneurial
failure. Academy of Management review, 24(1), 13-30.
McKelvie, A., Haynie, J. M., & Gustavsson, V. (2011). Unpacking the uncertainty construct:
Implications for entrepreneurial action. Journal of Business Venturing, 26(3), 273-292.
McMullen, J. S. (2015). Entrepreneurial judgment as empathic accuracy: A sequential decision-
making approach to entrepreneurial action. Journal of Institutional Economics, 11(3), 651-
681.
McMullen, J. S., & Dimov, D. (2013). Time and the entrepreneurial journey: The problems and
promise of studying entrepreneurship as a process. Journal of Management Studies, 50(8),
1481-1512.
McMullen, J. S., & Shepherd, D. A. (2006). Entrepreneurial action and the role of uncertainty in
the theory of the entrepreneur. Academy of Management Review, 31(1), 132-152.
Packard, M.D., Clark, B.B., & Klein, P.G. (2017). Uncertainty types and transitions in the
entrepreneurial process. Organization Science, 28(5): 840-856.
Packard, M.D. & Clark, B.B. (Forthcoming). On the mitigability of uncertainty and the choice
between predictive and non-predictive strategy. Academy of Management Review,
forthcoming.
Sarasvathy, S. D. (2001). Causation and effectuation: Toward a theoretical shift from economic
inevitability to entrepreneurial contingency. Academy of Management Review,26(2):243-263.
Sarasvathy SD. 2008. Effectuation: Elements of entrepreneurial expertise. Cheltenham, UK:
Edward Elgar.
Shepherd, D. A., McMullen, J. S., & Jennings, P. D. (2007). The formation of opportunity
beliefs: Overcoming ignorance and reducing doubt. Strategic Entrepreneurship
Journal, 1(1-2), 75-95.
Townsend, D. M., Hunt, R. A., McMullen, J. S., & Sarasvathy, S. D. (2018). Uncertainty,
knowledge problems, and entrepreneurial action. Academy of Management Annals, 12(2),
659-687.
Townsend, D.M., Hunt, R.A., & Dimov, D. (2019). Addressing entrepreneurship's false
dichotomization of risk and uncertainty through modal logics. Working paper.
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Entrepreneurship, Firm Emerges and Growth, 119-138.
37
Appendix 1: Tables & Figures
Table 1: Results of Article Search from Web of Science
38
Table 2: Summary of meta-analytic samples, estimated effect sizes, and heterogeneity
Note: Obj = Objective; Unc = Uncertainty; Innov = Innovation; Adapt = Adaptation; Bear = Bearing; Perf = Performance; ki =
number of independent samples; kt = total number of samples (independent and dependent); Ni = total sample size for the independent
samples;
!
" = estimated population correlation (corrected for unreliability in the predictor and criterion); SE = Standard Error; CI =
Confidence Interval.
Table 3: Summary of fit for models with different assumed correlations between subjective and objective uncertainty
Meta-Analytic
Effect
ki
Ni
r
!
"
SE
Lower
95%
CI
Upper
95%
CI
Z
p
Q
df
p
Obj Unc - Innov
31
11,106
.028
.036
.0442
-.051
.122
.809
.4184
383.50
49
.0000
Obj Unc - Adapt
22
8,812
.034
.045
.0472
-.048
.137
.946
.3440
183.79
30
.0000
Obj Unc - Bear
6
6,107
-.010
-.013
.0407
-.093
.066
-.328
.7432
16.06
8
.0415
Obj Unc - Perf
42
16,158
.012
.015
.0291
-.042
.073
.531
.5957
364.20
60
.0000
Subj Unc - Innov
43
8,689
.134
.172
.0325
.108
.235
5.283
.0000
457.07
59
.0000
Subj Unc - Adapt
52
8,830
.085
.111
.0288
.054
.167
3.847
.0001
557.55
103
.0000
Subj Unc - Bear
7
1,058
.003
.005
.0711
-.135
.144
.064
.9493
48.17
12
.0000
Subj Unc - Perf
67
13,055
.006
.008
.0257
-.042
.059
.325
.7455
870.72
126
.0000
Innov - Perf
83
23,354
.110
.140
.0239
.093
.187
5.835
.0000
1688.85
182
.0000
Adapt - Perf
81
18,430
.068
.088
.0223
.044
.131
3.935
.0001
1592.88
238
.0000
Bear - Perf
16
7,690
.030
.040
.0388
-.036
.116
1.028
.3038
156.92
37
.0000
39
Model
c2
df
p
RMSEA
CFI
TLI
SRMR
Large Pos Obj-Subj Unc
25.00
6
.0003
.023
.991
.977
.013
Moderate Pos Obj-Subj Unc
5.96
6
.4276
.000
1.000
1.000
.007
Small Pos Obj-Subj Unc
12.18
6
.0581
.013
.987
.967
.010
Zero Obj-Subj Unc
22.87
6
.0008
.022
.960
.901
.014
Small Neg Obj-Subj Unc
39.10
6
.0000
.031
.934
.834
.018
Moderate Neg Obj-Subj Unc
94.20
6
.0000
.050
.915
.788
.027
Large Neg Obj-Subj Unc
205.45
6
.0000
.076
.912
.780
.036
Note: Obj-Subj Unc = fixed correlation between objective and subjective uncertainty; Pos = Positive; Neg = Negative; Small,
Moderate, and Large correspond to correlations of .1, .3, and .5, respectively.
Figure 1: Hypothesized model with standardized meta-analytic path coefficients.
40
Note: Innov = Innovation; Adapt = Adaptation; the paths displayed are from the model in which the correlation between objective and
subjective uncertainty was fixed at .3 (i.e., the best fitting model, see Table 2). Other path coefficients varied by less than .02 across
different assumed objective-subjective uncertainty correlations. Sample size for the model was set to 5,770, which is the harmonic
mean of the total independent sample sizes for each meta-analyzed effect (see Viswesvaran & Ones, 1995 for details on this
approach).
Objective
Uncertainty
Subjective
Uncertainty
Innov
Adapt
Bearing
Performance
.02
-.03*
.15*
.17*
.09*
.04*
.11*
.01
.3
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