Uncertainty, Knowledge Problems, and Entrepreneurial Action

Abstract

Whether business venturing emerges in the context of nascent-stage start-ups or corporate giants, one of the enduring and fundamental assumptions underlying theories of entrepreneurial action is that entrepreneurs operate in uncertain environments. And yet, nearly a century since the unveiling of Knightian uncertainty as a precursor to profit-making, the identification, description and operationalization of uncertainty as a construct continues to exhibit conflicting definitions, tautological measures, and unwitting conflation with more apt, more precise constructs in entrepreneurship and organization theory. The purpose of this study is to review the multiple research streams that together constitute the literature on knowledge problems to identify critical boundary conditions of uncertainty as an analytical construct. Based on this review, we then set forth a multi-level research agenda for exploring entrepreneurial action under conditions of ambiguity, complexity, equivocality, and uncertainty.

Full text

rAcademy of Management Annals
2018, Vol. 12, No. 2, 659–687.
https://doi.org/10.5465/annals.2016.0109
UNCERTAINTY, KNOWLEDGE PROBLEMS, AND
ENTREPRENEURIAL ACTION
DAVID M. TOWNSEND
1
RICHARD A. HUNT
Virginia Polytechnic Institute and State University
JEFFERY S. MCMULLEN
Indiana University
SARAS D. SARASVATHY
University of Virginia and Indian Institute of Management Bangalore
Whether new business ventures emerge in the context of start-ups or corporate giants,
one of the enduring and fundamental assumptions underlying theories of entrepre-
neurial action is that entrepreneurs operate in uncertain environments. And yet, nearly
a century since the unveiling of Knightian uncertainty as a precursor to profit-making,
the identification, description, and operationalization of uncertainty as a construct
continue to exhibit conflicting definitions, tautological measures, and unwitting con-
flation with more precise constructs along the spectrum of ignorance and unknowing-
ness. The purpose of this study is to review the multiple research streams that together
constitute the literature on knowledge problems to identify critical boundary conditions
of uncertainty as an analytical construct. Based on this review, we then set forth a multi-
level research agenda for exploring entrepreneurial action under conditions of ambi-
guity, complexity, equivocality, and uncertainty.
INTRODUCTION
For almost a century, the connection between
uncertainty and entrepreneurial action has ener-
gized research across a wide variety of resear ch fields
in social and human sciences (Knight, 1921). And
although uncertainty remains fundamental to theo-
ries of entrepreneurial action (Packard, Clark, &
Klein, 2017), existing conceptions of uncertainty in
entrepreneurship research are complex and prob-
lematic. On one hand, it is widely recognized that
uncertainty creates innumerable challenges for even
the most skilled organizational actors (Busenitz
& Barney, 1997; Eisenhardt & Zbaracki, 1992;
Schwenk, 1995; Wiltbank, Dew, Read, & Sarasvathy,
2006). Because an “unknowable”future stymies
attempts by actors to comprehend and predict the
consequences of their actions (Huang & Pearce,
2015), uncertainty often thwarts the well-conceived
plans of managers and entrepreneurs (Sarasvathy,
2001). Similarly, because decision theories in
neoclassical economic models were never designed
to address decision-making under uncertainty
(Simon, 1979), the inability to predict the conse-
quences of one’s actions presents theoretical chal-
lenges as well. Thus, the probabilistic reasoning
that undergirds decision theory breaks down in the
presence of uncertainty (Shackle, 1955).
Yet, despite these practical and theoretical chal-
lenges, uncertainty cannot be ignored. It is the life-
blood of the entrepreneurial opportunities that are
necessary for the rejuvenation of organizations and
economies (Venkataraman, 1997). Without human
agency and action in the context of a priori irreducible
uncertainty, there are no mechanisms through which
the entrepreneur-opportunity nexus creates value
(McMullen & Shepherd, 2006; Sarasvathy, 2001).
McGrath, Ferrier and Mendelow (2004) likened this
interplay to a ship captain journeying through un-
charted waters in search of treasures. Even while the
adventuring entrepreneur is unable at any point in
time to comprehend fully what lies ahead, he or she is
compelled to make a series of “stepping stone”de-
cisions along the twisting river bends of irreducible
uncertainty (McGrath & MacMillan, 2000; McMullen,
2015; McMullen & Kier, 2016) that will prove to be
We thank associate editor Madan Pillutla and the editorial
staff for their helpful comments and feedback on this article.
1Corresponding author.
659
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decisive in determining what, if any, social or eco-
nomic value the entrepreneur ultimately creates.
Given the problematic yet productive role of un-
certainty in human affairs, a wide range of organiza-
tional theories have emerged to incorporate various
types of uncertainty as analytical constructs (Akerlof,
1995; Alchian & Demsetz,1972; Cyert & March, 1963;
Kahneman & Tversky, 1979; Simon, 1955, 1959;
Williamson, 1979). The goal of these theoretical per-
spectives has been to develop models of decision-
making and action that equip organizational actors
with the tools to navigate uncertain environments
effectively. The problem with these approaches, and
with the use of uncertainty more generally, is that both
scholars and practitioners use the construct as a syn-
onym for all manner of “unknowingness.”Although
unknowingness—which spans the entire landscape
of human consciousness lying between ignorance and
certainty—truly is ubiquitous, uncertainty is merely
a subset of unknowingness. Yet, the implicit famil-
iarity of the term uncertainty (i.e., the perception that
we all know what it means!), shaped by over a century
of use and misuse to describe the epistemological
limits of human knowledge, encourages even the
most analytically inclined to overlook it or take its
meaning for granted when developing what are oth-
erwise rigorous theoretical models.
Being constituted of many states of unknowing-
ness, and as a condition that may be perceivedto exist
even when it does not, the uncertainty construct is far
more problematic than its widespread use might
suggest, and its central role in management and or-
ganizational research belies rampant imprecision,
overuse, and misuse (Packard et al., 2017). With
countless scholarly titles and journal abstracts refer-
encing “uncertainty,”it is incumbent upon scholars
to ensure that the construct is accurate, intelligible,
utilizable, and meaningful. These problems are par-
ticularly acute in the study of entrepreneurship
(McMullen & Shepherd, 2006; Ramoglou & Tsang,
2016), where the raison d’etre of entrepreneurial ac-
tion is inseparable from the state of uncertainty
(Knight, 1921; McGrath, 1999; Rumelt, 1987). Among
eminent commentators in the history of scholarship
in entrepreneurship—Cantillon, Say, Sombart, We-
ber, Knight, and Schumpeter—the common de-
nominator has always been that the creation, and
capture of value is contingent upon the premise that
action is taken in the context of some level of
unknowingness. Without this premise, an action is
simply a perfunctory enactment of known desires
with probabilistic outcomes. Yet, the overuse of the
term “uncertainty,”the lack of definitional clarity,
and the tendency to operationalize the concept im-
precisely have stretched the construct’s boundaries so
severely that its theoretical usefulness is at risk. Al-
though recent calls for “a more nuanced view of un-
certainty”(Ramoglou & Tsang, 2016) or “[a] better
notion of uncertainty”in entrepreneurship theory
(Packard et al., 2017) are steps in the right direction,
scholarly attempts to continue stretching the bound-
aries of uncertainty to cover an ever-increasing range
of actions under conditions of ignorance, and
“unknowingness”threatens the very utility of this
valuable construct (McKelvie, Haynie, & Gustavsson,
2011). Thus, there is an urgent need for more research
that (i) builds on the seminal work of Knight (1921)
and others to disaggregate extant conceptions of un-
certainty, (ii) identifies and explicates the nature of
knowledge problems that have been subsumed er-
rantly by uncertainty, and (iii) explores alternative
models of action that entrepreneurs use to mitigate
this array of knowledge problems.
To accomplish these three objectives in this re-
view, we conduct a multi-disciplinary investigation
of existing research on the role of uncertainty in
theories of entrepreneurial action (McGrath &
McMillen, 2000; McMullen & Shepherd, 2006). As
a crucial next step toward building more robust
theories of entrepreneurial action, our goal is to
provide more nuance and depth regarding the role
and nature of unknowingness faced by entrepre-
neurs as well as the causes and consequences of
entrepreneurial action undertaken to resolve un-
certainty. Making progress in this regard necessitates
the development of a more complete, more precise
conceptualization of unknowingness, one that ex-
tends beyond uncertainty into other closely related
knowledge problems: ambiguity, complexity, and
equivocality. Ambiguity refers to the collapse of
sensemaking (Weick, 1995), when it is impossible to
discern what is important or even what is going to
happen. Complexity emanates from a combination
of detail complexity, which is the quantity of vari-
ables involved in a problem, and from dynamic
complexity, which is the quantity of the interactions
between the variables over time (Clarysse, Tartari, &
Salter, 2011). Equivocality refers to the existence of
multiple meanings or interpretations that are in-
dividually unambiguous but collectively lie in direct
conflict with one another (Zack, 2001). To move
forward with stronger theory in the entrepreneur-
ship domain, a successful exposition of action re-
quires a richer, more thorough examination of all
four knowledge problems and the impediments they
generate.
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By “knowledge problem,”we refer to an episte-
mological obstacle to strategic action that manifests in
terms of the novelty being confronted along one or
more dimensions of action, including what is being
done, who is doing it, why theyare doing it, and when,
where, or how they are doing it. These dimensions
may be structural (e.g., where and when) or agentic
(e.g., how and why). Simply put, actors may not know
what the consequences of their actions will be or even
what those actions should be owing to the novelty
confronted along one or more of these dimensions
of entrepreneurial action (Companys & McMullen,
2007). This knowledge problem leaves them ponder-
ing whether to take action, and if so, how? Building on
this approach, we conclude the article by introducing
a robust agenda for researching a rich and broader set
of knowledge problems within the context of entre-
preneurial action research.
UNCERTAINTY AND
ENTREPRENEURIAL ACTION
To explore the current state of research into the
role of uncertainty in theories of entrepreneurial
action, we conduct a review of the literature on un-
certainty across a core set of entrepreneurship and
management scholarly journals. In the first stage of
the review, we discuss foundational research expli-
cating the link between uncertainty and entrepre-
neurial action to highlight key assumptions and
perspectives that have shaped this area of research.
In the second stage of the review, we conduct a sys-
tematic analysis of contemporary research pub-
lished between 2006–2016. We chose this time
period, beginning with the work of McMullen and
Shepherd (2006) who linked a theory of entrepre-
neurial action with the literature on uncertainty, to
spotlight the most relevant contemporary themes,
perspectives, debates, and omissions in subsequent
research. We will elaborate on these sections of the
review in the following paragraphs.
Foundational Perspectives on Uncertainty in
Theories of Entrepreneurial Action
The concept of uncertainty looms large within the
domain of entrepreneurship research, coloring vir-
tually every condition, context, and level of analysis.
Uncertainty has been used to characterize entrepre-
neurial environments (Busenitz, 1996; Gaglio & Katz,
2001; Hannan & Freeman, 1984; Russell & Russell,
1992), new industry sector indeterminacy (York &
Venkataraman, 2010), firm-level strategic unknowns
(Barnett and Hansen, 1996; Hage, 1999), and
individual-founder expertise (Freel, 2005; Kirzner,
1979; Sarasvathy, 2001; Sarasvathy, 2008) or igno-
rance (Baron & Ensley, 2006; Hoffman & Hammonds,
1994; Hunt & Kiefer, 2017; Simon, 1979; Tversky &
Kahneman, 1974). Modern usage of the term extends
back to Cantillon (1755), who was the first to recog-
nize that decentralized, real-world markets were
driven by essential links between entrepreneurship,
opportunity pursuit, and decision-making in the face
of uncertain outcomes (Herbert & Link, 1989).
Knightian risk and uncertainty. Left dormant for
nearly two centuries, Frank Knight (1921) resurrected
the importance of uncertainty bearing as a key tenet for
the existence of profit as a reward for entrepreneurial
activity. Knight’s view eschewed the dominant theo-
retical perspective of the time, which held that in the
long run, uncertainty and individual decision-making
are of little importance—aviewthatrendersindivid-
ual entrepreneurial action virtually meaningless in the
broad context general market equilibrium. Yet, for
Knight (1921), the ubiquity of uncertainty undermines
the functioning of the pricing system, thereby neces-
sitating a special class of entrepreneurs capable of
bearing that uncertainty on behalf of the economy,
thereby earning the right to “profit.”Extending
Knight’slineofthinking,bothCoase(1937)and
Keynes (1937) assertedthat uncertainty constitutes the
central problem confronted by entrepreneurs, and
thus a consensus emerged that uncertainty and en-
trepreneurial action are inextricably linked in foun-
dational theories of entrepreneurship (Boudreaux &
Holcomb, 1989).
Although awareness and acceptance of uncertainty-
bearing individuals generates momentum toward the
study of entrepreneurship, it does not settle the need
for better definitions of uncertainty. Ironically, the
ubiquity of uncertainty as a market-based reality, and
its influence as a scholarly concept of escalating
prominence in theories of entrepreneurship, has fa-
cilitated neither the adoption of common definitions
nor an evolution toward consistent usage. Within the
broader domain of management, organizational theo-
rists have sought to contend with uncertainty in a va-
riety of ways. Lipshitz and Strauss (1997), for example,
cataloged an assortment of conceptualizations, in-
cluding perspectives that equate uncertainty to risk
(Anderson, Deane, Hammond, & McClelland, 1981;
Arrow, 1965; MacCrimmon & Wehrung, 1986), ambi-
guity (Hogarth, 1987; March and Olson, 1976), the in-
ability to act deterministically (Thompson, 1967), a
paucity of information (Galbraith et al., 1975), turbu-
lence (Terreberry, 1968), equivocality (Weick, 1979),
2018 661Townsend, Hunt, McMullen, and Sarasvathy

conflict (March & Simon, 1958), and ignorance
(Anderson et al., 1981).
Research in behavioral economics arising from
vigorous conversations within the “Carnegie School”
of thought posed challenges to existing conceptions
of decision-making under uncertainty. These con-
versations questioned the efficacy of three assump-
tions: (a) the human brain’s capacity to comprehend
and process probabilities with any degree of formal
precision, even among professional probability the-
orists (Gigerenzer, 2003; Gigerenzer & Goldstein,
1996), (b) the presence of known, well-formulated
preferences that drive action (March, 1978), and (c)
the need for and usefulness of large quantities of in-
formation as facilitators of better decisions (Simon,
1996). Sarasvathy (2008) termed these the problems
of uncertainty, goal ambiguity, and isotropy, re-
spectively, and showed how expert entrepreneurs
learn through the experience of action and in-
teraction to overcome these within the effectual
process.
Among these various conceptualizations of un-
certainty, none has been more central to the discus-
sion of entrepreneurship than the differentiation
between uncertainty and risk. The tendency to con-
flate the concepts of risk and uncertainty, especially
as they pertain to entrepreneurial action, has hin-
dered efforts to identify, distinguish, and model the
value-enhancing facets of action under uncertain
conditions from other types of ignorance and
unknowingness (Dew, 2009). Knight (1921) framed
the concern in the following fashion:
“Uncertainty must be taken in a sense radically dis-
tinct 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 mea-
surable 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).
Risk, then, is characterized as the ability to assign
a probability distribution to the potential outcomes.
In other domains, this is sometimes referred to
as Type B uncertainty, in which the assessment
end point is fixed but unknown (Hoffmann &
Hammonds, 1994). With risk, we do not know for
certain what is going to happen next, but we do know
what the distribution of all possible outcomes looks
like. For example, ex ante, we do not know the out-
come of rolling two dice, but we do know the exact
probabilities of any two fair dice yielding each value
from 2 to 12. The outcome of each roll or each series
of rolls is unknown, but a complete set of all the
possible outcomes for each roll are known, as is the
probability of each outcome occurring. Actors know
these probabilities because while the exact outcome
is unknown, the range of possible solutions is fixed
because there is a limited set of combinatorial solu-
tions based on the number of dice. Thus, risky
problems are “insurable”(Knight, 1921)—meaning
that risks can be hedged, pooled, or otherwise neu-
tralized by paying insurance to cover the potential
occurrence of unfavorable outcomes—whereas cer-
tain other types of uncertainty are a priori irreducible
(McGrath, 1999) and, therefore, “uninsurable”be-
cause there are no immediate market pricing mech-
anisms to cover unforeseen eventualities.
Knight’s careful distinction between risk and un-
certainty is particularly critical to theory building in
entrepreneurship (Folta, 2007). This is because the
facets of the entrepreneurship domain that are not
otherwise subsumed by theories drawn from eco-
nomics, strategic management, sociology, and psy-
chology tend to involve nascent-stage venturing,
settings in which the sifting and sorting and pro-
cessing of an opportunity’s potential plays out on
a patently micro-level scale where a priori un-
certainties cannot be hedged in advance of the en-
trepreneur taking action. “Though uncertainty is
prevalent in business and other social situations, it
is pervasive in entrepreneurial settings,”noted
Sorenson and Stuart (2008: 530). Folta (2007), in an
essay published in the inaugural issue of Strategic
Entrepreneurship Journal hearkens back to Knight,
Coase, and Keynes in declaring that in entrepre-
neurship, “uncertainty rules the day.”
Contrary to the negative connotations that accom-
pany the view of uncertainty in common parlance, the
foundational perspective in entrepreneurship re-
search is based on the logic that uncertainty does not
constitute a patently aversive state. This distinctive
relationship with uncertainty makes the field unique
within the social sciences. In fact, the presence of
a priori uncertainty regarding the viability of an en-
trepreneurial opportunity is in some sense an essen-
tial pre-condition for the very existence of the
opportunity (McMullen, Plummer, & Acs, 2007). An
entrepreneur’s willingness and ability to bear un-
certainty isa decisive determinant of both the path he
or she selects and the outcomes that ultimately tran-
spire (Gnyawali & Fogel, 1994; Shepherd, McMullen,
662 JuneAcademy of Management Annals

& Jennings, 2007). Rumelt (1987) maintains that an
entrepreneur’s ability to position himself or herself
to capitalize on environmental uncertainty is the key
driver in generating and harvesting entrepreneurial
rents. Building on Venkataraman (1997), McGrath
(1999:31) too refers to the role of uncertainty in real
options as follows: “Embracing entrepreneurship,
implies accepting all that goes with it, particularly the
recognition of a priori irreducible uncertainty.”
Knight prefaced his update to Risk, Uncertainty
and Profit in 1957 by noting that, “Universal fore-
knowledge would leave no place for an entrepre-
neur”(1957: lxii). Even more pointedly, McMullen,
Plummer, and Acs (2007: 279) observed, “...one
cannot have opportunity without uncertainty, but
because the human condition is characterized by the
passage of time, there will always be uncertainty, and
therefore, some form of opportunity.”Likewise,
York and Venkataraman (2010: 454) concluded that,
“Entrepreneurs can be viewed as individuals who
have a way of producing value out of uncertainty”
(italicized emphasis in the original).
Critiques of knightian risk and uncertainty. Not
all scholars share the Knightian distinctions between
uncertainty and risk nor do they embrace what some
see as a misplaced romanticization of uncertainty in
the study of innovation and entrepreneurship
(Adner & Levinthal, 2004). Despite the centrality of
uncertainty in theories of entrepreneurial action,
and in some sense, the essentiality of uncertainty in
the pursuit of entrepreneurial opportunities (Hunt
& Song, 2015; McMullen & Shepherd, 2006;
Venkataraman, 1997), there remains a persistent
question as to whether entrepreneurs actually capi-
talize on irreducible a priori uncertainty in practice
(Driouchi & Bennett, 2012; Klingebiel & Adner, 2015;
Posen, Leiblein, & Chen, 2015). In other words, does
the presence of uncertainty positively facilitate
micro-level entrepreneurial action directly? Al-
though Knight’s distinction constitutes a loosely
enforced orthodoxy among entrepreneurship
scholars, there are several noteworthy concerns that
have been raised and debates that have emerged, the
most prominent of which have been captured in the
following three critiques.
First, one of the central critiques in the founda-
tional literature on Knight’s distinction between risk
and uncertainty centered on the arguments that
functionally, individuals are unable or unwilling to
differentiate between risk and uncertainty at the
microlevel (Savage, 1972; Taleb, 2007). The notion
that market actors can or should develop probability
distributions to assist in decision-making when
confronted by risks seems preposterous to other
scholars (e.g. Gigerenzer & Goldstein, 1996). To these
scholars, the distinctions drawn between Knightian
uncertainty and Knightian risks lack veridicality
(Taleb, Goldstein, & Spitznagel, 2009). “Behaviorally,
individuals confront uncertainty and risk as though
they are one and the same,”argued Taleb (2007:128).
Arrow’s(1951:417)critiqueofKnightisparticularly
poignant when he argued that at macrolevel,
“...Knight’s uncertainties seem to have surpris-
ingly many ofthe propertiesof ordinary probabilities”
and that the “...degree of uncertainty (is) reducible by
consolidation of many cases, analogously to the law of
large numbers”(Arrow, 1951: 417). This distinction is
crucial as it suggests that to the extent Knightian un-
certainties can be aggregated, they can potentially be
mitigated through risk pooling.
Second, others, however, have argued pointedly
that the benefits of macro-level “risk pooling”are
usually limited in the context of entrepreneurship
because micro-level entrepreneurial action is often
characterized by “non-divisible, non-seriable ex-
periments”(i.e., entrepreneurs have “one shot”to get
it right—Shackle, 1955: 8). So, whereas some actors
could obviously insure against catastrophe by ag-
gregating micro-level, situational uncertainties to
where an unforeseen catastrophic outcome with any
one product or market failure would not create sys-
temic damage in the aggregate, micro-level entre-
preneurial action is more susceptible to these
failures because they are less able to hedge their risks
through pooling together many products or markets.
As Sarasvathy, Menon, & Kuechle (2013: 426) note:
“The use of heterogeneity (diversity) to average out
losses from firm failure is not an option for the serial
entrepreneur; he/she cannot start nfirms concur-
rently with the idea of exploiting negatively corre-
lated dependencies between the firms. To paraphrase
a well-known example, it may make sense to buy
‘shares in a coal and in an ice company’(Samuelson,
1967), but it may not be feasible to start coal and ice
companies at the same time.”
The crux of this problem, therefore, hinges on key
differences between micro-level sources of un-
certainty, where the accuracy of individual judg-
ment is thwarted by situational factors and structural
sources of uncertainty, which can be transformed
into risk by pooling these uncertainties together and
insuring against any ill effects they might present.
Third, this situation is distinct from still another
form of uncertainty identified in foundational re-
search, involving conditions under which the true
2018 663Townsend, Hunt, McMullen, and Sarasvathy

aggregate distributions for a set of parameters are un-
known, and the inclusion of new information does not
necessarily enable the actor to reduce uncertainty
ex post. In such cases, not only do we not know
what is going to happen next (aprioriuncertainty)
or what the distribution of all potential outcomes
look like, new information can actually make the
knowledge problem worse for the individual actor.
Keynes elaborates on this important point:
“By ‘uncertain’knowledge...I do not mean merely to
distinguish what is known for certain from what is
only probable. The game of roulette is not subject, in
this sense, to uncertainty...The sense in which I am
using the term is that in which the prospect of a Eu-
ropean war is uncertain, or the price of copper and
the rate of interest twenty years hence, or the obso-
lescence of a new invention...About these matters
there is no scientific basis on which to form any
calculable probability whatever. We simply do not
know!”(1937: 213–214).
Keynes differentiates situational uncertainties
(i.e., a game of roulette) from macro sources of
uncertainty where the aggregation of a variety of
factors creates an uncertain environment (e.g.,
prospect of European war) that is at least partially
influenced by the micro-level actions of various
actors (e.g., political choices of leaders in key Eu-
ropean countries influenced the outbreak of war
2 years after he made his statement). In these de-
cision environments, entrepreneurial decisions
are characterized by “...a non-exhaustive list of
possible states of the world known to the entre-
preneur”(Basili & Zappia, 2010: 450). To this
point, as we noted earlier, Taleb (2007: 128) ar-
gued that under such conditions of complexity,
“Behaviorally, individuals confront uncertainty
and risk as though they are one and the same...”
These decision environments are particularly
challenging for entrepreneurial actors because
the addition of more variables to a decision model
often exacerbates the challenges of solving
complex knowledge problems. The inclusion of
each individual new model parameter can gener-
ate an almost infinite range of potential out-
comes through interactions among all of the
variables. Such complex interactions are not only
aprioriirreducible, but uncertainty is often in-
creased ex post based on the unforeseen conse-
quences of operating in complex environments.
Taleb (2007: 128) summarized his critiques of
Knight’s distinction between risk and uncertainty
by arguing that in such complex environments,
“...(c)omputable risks are absent from real life”or
perhaps even impossible, thereby rendering the
risk-uncertainty distinction largely moot because
more information does not solve the uncertainty
puzzle ex post.
Overall, Knight’s distinction between risk and
uncertainty has played a crucial role in shaping
theories of entrepreneurial action over the past
century. Yet, as we will discuss in the following
paragraphs, much of the contemporary research
in entrepreneurship continues to use uncertainty in
an omnibus fashion, stretching the concept of un-
certainty to cover many types of ignorance or
unknowingness. For example, if uncertainty is de-
fined as a structural feature of the objective world,
few remedies exist to resolve it because the in-
formation simply does not exist. If uncertainty de-
scribes the ignorance of the individual actor, they
can resolve it by exploring the external world until
the “correct”information is discovered. However, if
uncertainty is defined as a fuzzy, unclear set of sub-
jective perspectives or preferences, entrepreneurial
actions intended to influence these environments
can reduce the overall level of “uncertainty”by
creating intersubjective agreement. In each case, the
end result is the same (i.e., uncertainty is reduced),
but the underlying mechanisms for resolving such
states of initial unknowingness are entirely different.
Taken together, the status quo in entrepreneurship
theory is problematic because inconsistent defini-
tions of uncertainty create confusion regarding both
the impact of uncertainty on entrepreneurial action
and on the effectiveness of the processes and strate-
gies used to resolve it.
Reviewing the Contemporary Literature
The literature on uncertainty contains hundreds
of thousands of textual “mentions.”So, for our sys-
tematic review of contemporary literature, we began
with a winnowing process. We conducted a system-
atic search of prominent journals to include only
those articles with uncertainty in the title, abstract,
or keywords. Table 1 identifies the journals we in-
cluded in the review process and Table 2 lists the
citations of the individual articles.
To ensure that each of the articles explored
uncertainty as a subject of interest, we identified
and excluded articles that simply used the term as
an adjective or description of previous research
(e.g., “the findings of previous research are ‘un-
certain’”). In addition, because the main purpose
of this review was to analyze the literature on
664 JuneAcademy of Management Annals

uncertainty as it relates to theories of entrepreneurial
action, we then examined each of these articles to
ensure that the phenomenon of interest was either
independent or corporate entrepreneurship (in-
cluding family business). This step further refined
our final article set to 146 articles. In the following
sections, we highlight the key findings from our
review.
Boundaries and Construct Clarity in Uncertainty
Research Afirstkeyfindingfromourreviewisthat
despite the long history and central importance of
Knightian uncertainty to theories of entrepreneurial
action, there remains a surprising lack of agreement on
core definitions of uncertainty in contemporary re-
search. Although there have been several recent at-
tempts to provide a more nuanced view of uncertainty
in theories of entrepreneurial action (Packard et al.,
2017; Ramaglou & Tsang, 2016), contemporary re-
search continues to stretch the boundaries of the
uncertainty-risk continuum to cover numerous states
of ignorance and unknowingness (Packard et al., 2017).
For example, York and Venkataraman (2010) use
Knight’s(1921)distinctionbetweenriskandun-
certainty as a foundational argument for their appli-
cation of entrepreneurial action to the context of
sustainable or environmental entrepreneurship. In
their study, they define uncertainty as “risks we cannot
assign probability to or predict in an accurate manner”
(York & Venktaraman, 2010: 452). They elaborate on
this further by noting that, to alleviate environmental
degradation, entrepreneurial action “...must address
uncertainty and create action in the face of ambiguity”
and later argue that “environmental issues are, by their
nature uncertain; the future is unknowable, and the
framing of environmental issues occurs in a future
context”(York & Venkataraman, 2010: 452–3). In this
definition, uncertainty and ambiguity are used in-
terchangeably, referring to both the interpretive (i.e.,
which factors matter and how they should be inter-
preted?) and prediction problems (i.e., what are the
likely consequences of taking or not taking action?)
inherent in making decisions about the future.
Kuechle, Boulu-Reshef, and Carr (2016) take a
similar approach and define Knightian uncertainty
as “...a situation in which the missing information
is yet to be created,”and contend that “...there is
no procedure that can reduce the doubts about the
possible courses of action, the possible states of the
world and the nature of their outcomes”(Kuechle
et al., 2016: 46). They also note that they “...use the
terms ambiguity and uncertainty interchangeably”
(Kuechle et al., 2016: 46). The interchangeable use of
uncertainty and ambiguity also influences how
Kuechle et al. (2016: 46) interpret other related re-
search: “The individuals studied by McKelvie et al.
(2009)2showed overall aversion to uncertainty and
expressed particular concern about the ambiguity
surrounding the impact of their own actions...”
Overall, Kuechle et al. argue that different types of
information will enable entrepreneurial actors to
solve uncertainty/ambiguity.
Much of this confusion stemming from a lack of
construct clarity in contemporary research occurs
in research that attempts to build on normative
decision theories in the economic literature. Recent
contemporary research has resurrected Ellsberg’s
(1961) argument that Knightian uncertainty is a
type of ambiguity, which he defines as “...a quality
of depending on the amount, type, reliability,
and ‘unanimity’of information, and giving rise to
one’s degree of ‘confidence’in an estimate of rela-
tive likelihoods”(Ellsberg, 1961: 657). Yet, later in
the article, Ellsberg (1961: 659) also argues that “(a)
mbiguity may be high even where there is ample
quantity of information, when there are questions of
reliability and relevance of information, and par-
ticularly where there is conflicting opinion and
evidence.”This is a crucial point here in that am-
biguity is not a function of incomplete information
in an environment, but that individuals just might
TABLE 1
Journals Used in Conducting Our Review
Management:
Academy of Management Review (AMR), Academy of Management Journal (AMJ), Administrative Science Quarterly (ASQ), Journal of
International Business Studies (JIBS), Journal of Management Studies (JMS), Management Science (MS), Organization Science (OS), and
Strategic Management Journal (SMJ).
Entrepreneurship:
Entrepreneurship Theory and Practice (ETP), Journal of Business Venturing (JBV), Strategic Entrepreneurship Journal, Small Business
Economics (SBE), and Journal of Small Business Management (JSBM)
2The article references and the publication date of
McKelvie et al. in 2009 when the article was first available
online versus the final publication date of 2011.
2018 665Townsend, Hunt, McMullen, and Sarasvathy

TABLE 2
Uncertainty Articles Included in Review (2006-2016)
AHaynie et al., 2009 R
Ahlers et al., 2015 Haynie et al., 2010 Raffiee & Jie, 2014
Alvarez, 2007 Haynie et al., 2012 Ramoglou & Tsang, 2016
Alvarez & Barney, 2007 Heavey et al., 2009 Rauch & Hatak, 2016
Alvarez & Parker, 2009 Henfridsson & Youngjin, 2014 Raymond et al., 2015
Andries et al., 2013 Hmieleski & Baron, 2007 Read et al., 2009
Artinger & Powell, 2016 Hmieleski & Baron, 2008 Reuer et al., 2012
Audretsch et al., 2014 Hmieleski & Baron; 2009 Reymen et al., 2015
Autio et al., 2013 Hmieleski et al., 2015 Rosenbusch et al., 2013
Autio et al., 2011 Holm et al., 2013
Autio et al., 2013 Huang & Pearce, 2015 S
Sarooghi et al., 2015
BJ Saxton et al., 2016
Baron, 2006 Jones & Casulli, 2014 Scarbrough et al., 2013
Belleflamme et al., 2014 Simsek et al., 2007
Bhawe et al., 2016 KSmith & Cao, 2007
Bianco et al., 2013 Kacperczyk, 2013 Sohn & Kim, 2013
Bjørnskov & Foss, 2013 Kaplan, 2008 Stephan & Pathak, 2016
Block, 2012 Kaul, 2013 Stewart et al., 2008
Boeker & Fleming, 2010 Keil et al., 2008 Sommer et al., 2009
Bowen & De Clercq, 2008 Kirsch et al., 2009
Burns et al., 2016 Klingebiel, 2012 T
Kor et al., 2007 Tang & Wezel, 2015
CKorsgaard et al., 2016 Tong & Li, 2011
Cacciotti et al., 2016 Kreiser et al., 2010 Townsend & Busenitz, 2015
Çakar & Ert ¨
urk, 2010 Kuechle et al., 2016 Thornhill, 2006
Cassar, 2014
Chandler et al., 2011 LU
Chwolka & Raith, 2012 Lanivich et al., 2015 Ucbasaran, 2008
Cobb et al., 2016 Langlois, 2007 Uygur & Kim, 2016
Compagni et al., 2015 Le Breton-Miller & Miller, 2015
Lee et al., 2011 V
DLee, S-H & Makhija, 2008 Van de Vrande &
Dawson, 2016 Levitas & Chi, 2010 Vanhaverbeke, 2013
Dean & McMullen, 2007 Leyden, 2016 Verreynne et al., 2016
Dew et al., 2015 Li, 2008 Vrande et al., 2009
Dimov & Milanov, 2010 Li, 2013
Du & Mickiewicz, 2016 Li & Chi, 2013 W
Li & Mahoney, 2011 Wallace et al., 2010
ELi & Zahra, 2012 Welter & Smallbone, 2011
Engel et al., 2014 Lowe & Ziedonis, 2006 Wennberg et al., 2011
Ensley et al., 2006 Wiklund et al., 2010
MWiklund et al., 2016
FMahnke et al., 2007 Wiltbank et al. 2006
Ferrary, 2010 Martiarena, 2013 Wiltbank et al., 2009
Fiet, 2007 Matusik & Fitza, 2012 Wuebker et al., 2015
Fischer & Reuber, 2014 Matusik et al., 2008 Wyrwich et al., 2016
Flatten et al., 2015 McKelvie et al., 2011 Wu & Knott, 2006
Folta, 2007 McMullen & Shepherd, 2006
Forbes, 2007 McVea, 2009 Y
Foss et al., 2007 Miller & Sardais, 2015 Yenkey, 2015
Foo, 2011 Miller, 2012 York & Venkataraman, 2010
Minola et al., 2016 Yu & Lindsay, 2016
GMoreno-Moya &
Gaba & Terlaak, 2013 Munuera-Aleman, 2016 Z
Garrett & Holland, 2015 Zacharakis et al., 2007
Gartner & Liao, 2012 PZahra et al., 2006
Garud et al., 2014 Packalen, 2007 Zander, 2007
Gaur et al., 2011 Parker, 2006 Zheng & Mai, 2013
Ghosal & Ye, 2015 Park & Steensma, 2012 Zott & Amit, 2007
Gruber, 2008 Parnell, 2013 Zott & Huy, 2007
Guerra & Patuelli, 2016 Patel & Fiet, 2009
Podoynitsyna et al., 2013
HPollock et al., 2007
Halme et al., 2012 Puffer et al., 2010
Haynie & Shepherd, 2009
666 JuneAcademy of Management Annals

have conflicting perspectives on how to interpret
such information.
Another stream in contemporary entrepreneur-
ship research builds on Garud and Van de Ven’s
(1992) distinction between ambiguity and un-
certainty as the difference between the utility of
pursuing certain end goals versus the probability of
end goals occurring. Santos and Eisenhardt (2009)
define ambiguity as “unknown cause–effect re-
lations and a lack of recurrent, institutionalized
patterns of relations and action,”and uncertainty
as the “inability to predict the probability of spe-
cific outcomes.”Davis, Eisenhardt, and Bingham
(2009) extend this definition of ambiguity as the
“lack of clarity such that it is difficult to interpret or
distinguish opportunities.”They further differen-
tiate environmental ambiguity from related envi-
ronmental forces such as velocity, complexity, and
unpredictability. Rindova, Ferrier, and Wiltbank
(2010: 1477) define high ambiguity as creating “...a
problem of interpretation because it results from
a lack of understanding and/or consensus re-
garding the applicability of available knowledge.”
Last, Petkova, Wadhwa, Yao, and Jain (2014: 424)
quote Santos and Eisenhardt (2009) directly in their
definitions of ambiguity versus uncertainty but
emphasize the confusion caused by “multiple in-
terpretations of the meaning, value, and usefulness
of new activities, products, and business models.”
The crucial difference this stream draws between
ambiguity and uncertainty centers on the relative
effectiveness of organizing strategies to solve dif-
ferent knowledge problems (i.e., searching for in-
formation versus creating common interpretive
frames and intersubjective agreement).
Much of this second stream of research builds
on the work of March (1994: 178), who argues that
“ambiguity is related to, but distinguishable from,
uncertainty”and that “uncertainty is a limitation
on understanding and intelligence. It is reduced
through the realizations of history, search, and
negotiation.”March (1994: 178) also argues that
the main idea behind most theories of uncer-
tainty in decision-making is that “...there is a real
world that is imperfectly understood.”In this
sense, March’s (1994) perspective resonates with
core distinctions between risk and uncertainty in
previous entrepreneurship research in that the
diffusion of more information over time turns
uncertainty into risk. By contrast, though, March
(1994: 179) posits that “ambiguity refers to a fea-
ture of decision-making in which alternative
states are hazily defined or in which they have
multiple meanings, simultaneously opposing
interpretations”and that “...(more) information
may not resolve misunderstandings of the
world...(since) the ‘real’world may itself be
a product of social construction.”Thus, in direct
contrast to research that builds on Ellsberg (1961)
where uncertainty and ambiguity are conceptu-
alized as the same construct, March (1994) argues
that uncertainty is resolved through systematic
search, whereas ambiguity can only be resolved
through intersubjective agreement.
The locus of uncertainty: Actor or environment?
Construct clarity in uncertainty research is also
hampered by a lack of specification of the locus of
uncertainty where actors, actions, and environments
are all frequently described as “uncertain.”At the
heart of much of this debate are questions about the
“objectivity”and “knowability”of the external en-
vironment. Miller (2012):
“Knightian uncertainty goes to objective unknow-
ability, existing in the environment, about potential
outcomes and the probability distributions on possi-
ble outcomes from actions: these are not knowable ex
ante. This is distinct from other forms of uncertainty
discussed in the management literature, such as
‘perceived uncertainty’(Milliken, 1987) or ‘adopter-
specific uncertainty’(Rogers, 2010), which are both
a quality of the individual undertaking an action.
These alternative conceptualizations of uncertainty
do not address the potential, ex ante, understand-
ability of outcomes and probability distributions”
(Miller, 2012: 60).
Here, where uncertainty is defined as the “objec-
tive unknowability”of the external environment
(Miller, 2012), the thrust of much of this re-
search vitiates attempts to predict key outcomes
by rendering the environment incomprehensi-
ble. Yet, adaptive decision-making processes
such as real options reasoning do not always en-
hance the performance of new ventures in the
face of high levels of environmental uncertainty
(Podoynitsyna et al., 2013). Others report that
various forms of environmental uncertainty (i.e.,
demand uncertainty) negatively impact key firm-
level outcomes such as early-stage capitalization
processes (Townsend & Busenitz, 2015). So, al-
though Knightian uncertainty might enable the
existence of opportunities, at the same time, it
also appears to diminish entrepreneurs’ability to
exploit those opportunities successfully (Miller,
2012). In general, much of this research indi-
cates that the locus of uncertainty resides in the
2018 667Townsend, Hunt, McMullen, and Sarasvathy

“objective constraints”of environmental uncer-
tainty and exerts a measureable, but largely negative
effect on various outcomes associated with entrepre-
neurial action. Furthermore, this research stream
suggests that entrepreneurs who are in a position to
receive new information from the environment are
able to resolve or mitigate some of the negative ef-
fects of environmental uncertainty (Hunt & Song,
2015).
Whereas many articles focus on the objective
unknowability of these environments, other re-
search has adopted a subjectivist approach for
exploring how entrepreneurs interpret and navi-
gate three different types of uncertainty (Forbes,
2007; McKelvie et al., 2011). This distinction is
important as several key articles demonstrate that
entrepreneurs display different attitudes toward
exogenous (outside the influence of entrepre-
neurs) versus endogenous (entrepreneurs can in-
fluence) sources of uncertainty (Forbes, 2007; Wu
& Knott, 2006). When uncertainty is objective and
exogenous, uncertainty avoidance reduces the
aggregate rate of startup activity and funding pat-
terns across different institutional environments
(Li & Zahra, 2012). Subjectivist approaches gen-
erally identify three different types of perceived
environmental uncertainty—state, effect, and re-
sponse (Forbes, 2007; McKelvie et al., 2011;
Milliken, 1987). In the original framework,
Milliken (1987) defines state uncertainty as the
difficulty of predicting how an environment is
changing. Effect uncertainty addresses the diffi-
culty of understanding how these changes will
impact the individual or firm. Response un-
certainty refers to the difficulty in understanding
the consequences of one’s action. Each of these
different types of perceived uncertainty impact
entrepreneurs differently and require different
types of information to resolve (McKelvie et al.,
2011).
Although this line of inquiry is still early stage
within the entrepreneurship literature, these dis-
tinctions are important because recent research
indicates that state uncertainty (perceived envi-
ronmental uncertainty) does not influence the
willingness of entrepreneurs to engage directly in
entrepreneurial action (McKelvie et al., 2011).
These results are generally consistent with previous
research on biases and heuristics in entrepreneur-
ship decision-making, namely, entrepreneurs do
not always perceive or acknowledge the “objective
uncertainties”in the external environment before
taking action (Busenitz, 1996; Busenitz & Barney,
1997; McMullen & Kier, 2016). Present research
also supports such a conjecture as both heuristics
and analogical reasoning equip entrepreneurs to
contend with uncertainties faced by entrepre-
neurs attempting to internationalize their ventures
(Jones & Casuli, 2014). In summary, individual-
level theories of uncertainty generally suggest that
perceived effect uncertainty (i.e., perceived un-
certainties about the effects of uncertainty on the
entrepreneur/firm) exerts a negative effect on the
willingness of entrepreneurs to engage in entre-
preneurial action (McKelvie et al., 2011).
The role of entrepreneurial action in resolving
uncertainty. Contemporary entrepreneurial action
research also has developed a rich body of literature
on the role of cognitive and action-formation mech-
anisms under various environmental conditions.
Effectuation theory (Sarasvathy, 2001), bricolage
theory (Baker & Nelson, 2005), and social capital and
network theories (Dushnitsky & Lavie, 2010; Hughes
et al., 2014) all represent vibrant streams of research
focused on exploring how entrepreneurs take
action within various environments. Much of this
research on the role of action-formation mechanisms is
anchored in either general conceptualizations of the
environment (i.e., constructing resources in resource-
constrained environments in bricolage research—
Baker & Nelson, 2005) or co-creating artifacts and
taking action in environments involving multiple un-
certainties (Sarasvathy, 2008). In each of these cases,
entrepreneurs are assumed to hold a high degree of
agency both in responding to the constraints of the
environment and in enacting various organizing
mechanisms.
Effectuation theory (Dew et al., 2015; Sarasvathy,
2001) emphasizes the use of control strategies and
the co-creation of social artifacts by expert entre-
preneurs in the face of Knightian uncertainty while
eschewing the use of predictive strategies due to the
unknowability of the future environment. A wide
variety of studies have demonstrated the usefulness
of such strategies and organizing mechanisms (Davis
et al., 2009). Yet, contemporary research on entre-
preneurial action under conditions of uncertainty
generally suggests that perceived effect uncertainty
(i.e., perceived uncertainties about the effects of
uncertainty on the entrepreneur/firm) exerts a nega-
tive effect on entrepreneurial action (McKelvie
et al., 2011). On this point, this research notes that
these results appear to conflict with the core tenets
of effectuation theory in regard to how outcome
uncertainties impact entrepreneurial action. In
response, several articles based in effectuation
668 JuneAcademy of Management Annals

theory suggest that the superior pattern matching
skills of expert entrepreneurs enable them to not just
contend with but to capitalize on opportunities in
uncertain environments (Dew et al., 2015). Kuechle
et al. (2016) suggest that this is because expert en-
trepreneurs endeavor to seek control of elements
within uncertain environments versus attempting to
try to predict outcomes. For a fuller and more up-to-
date review of this literature stream, see Dew et al.
(2015).
Although important, this debate leaves several
important questions unanswered. First, despite
the willingness of expert entrepreneurs to use
control strategies to engage in entrepreneurial
action, how might such control strategies be
enacted in the face of uncertainties regarding the
external consequences of such actions? Garud,
Gehman, and Giuliani (2014) contend that “pro-
jective stories”designed to set audience expecta-
tions often set the firm up to disappoint audiences,
given that “inherent objective environmental un-
certainties”will force entrepreneurs to adapt
miscalibrated plans (Hunt, 2015; Hunt & Lerner,
2012). In other words, despite attempts to socially
construct appealing narratives designed to solicit
stakeholder approval and engagement (i.e., a
control strategy—Garud, Hardy, & Maguire, 2007),
the objective environment will still influence the
outcomes of entrepreneurial action. For these
reasons, perhaps entrepreneurs use multiple
logics over time while engaging in entrepreneurial
action?
A related stream of research, concerning the pro-
cesses of social negotiation, explores the ways in
which entrepreneurs rely on key levers of social in-
fluence, such as empathic accuracy (McMullen,
2015), political skill (Companys & McMullen,
2007), and/or social skill (Fligstein, 1997) to en-
courage cooperative behaviors (Dorado, 2005;
McMullen, 2010) when mobilizing the collective
action needed for institutional innovation and
change (Battilana, Leca, & Boxenbaum, 2009; Garud
et al., 2007; Hargrave & Van de Ven, 2006). This
process of social negotiation—the essence of which
Davidson (2001) referred to as “intersubjective
agreement”—results in new goals and actions, each
of which is made possible by an enlarged pool of
resources resulting from the discovery of mutually
desirable ends. So, although research in this line
of inquiry is still emerging, such articles do
provide unique insights into the role of entrepren-
eurial action in shaping environmental or institu-
tional change through actor-provocated attempts to
resolve uncertainty (Henfridsson & Youngjin, 2014;
Sarasvathy, 2008).
Aggregation problems in the emergence of
uncertainty. Contemporary research on the nexus of
uncertainty and entrepreneurial action is also
complicated by the fact that some of the “entre-
preneur’s decisions effectively shape the future
environment”(Basili & Zappia, 2010: 450). Not
only are socially constructed decision environ-
ments not solvable aprioribut also the evolution
of these environments is influenced by entrepre-
neurial action—whether individual or collective
(McGrath, 1999). The emphasis in these environ-
ments is not just to diagnose the structural features
accurately but also to extend understanding re-
garding how one’sactionsmightbeaggregated
into a set of collective choices made by a variety of
actors that ultimately influence how these envi-
ronments evolve and change (Cope, 2011). In these
cases, the critical information that is needed to
solve the underlying knowledge problem will
not exist before action being taken (McGrath
et al., 2004). Nor can individual actors always
predict or comprehend how their micro-level ac-
tions will aggregate across the environment
(Acs, Braunerhjelm, Audretsch, & Carlsson, 2009;
Agarwal, Audretsch, & Sarkar, 2010). In certain
situations, entrepreneurs might narrow the de-
cision space by trying to create partial solutions
through intersubjective agreement, which can
yield partial solutions, but because these decision
environments are a product of social construction,
they are not, by nature, predictable in advance of
the entrepreneur taking action. They are, however,
susceptible to the influences of individual and collec-
tive action (Sarasvathy, 2001; Dew & Sarasvathy,
2007).
At the same time, the transformative impact of
entrepreneurial action in uncertain environments
is primarily a tail-driven phenomenon where
power-law distributions of market returns aggre-
gate to just a few winners (Crawford, Aguinis,
Lichtenstein, & Davidsson, 2015). Under these
circumstances, there is a temptation to attribute
these extreme outcomes in theories of entrepre-
neurial action to the prescient, heroic actions of
individual entrepreneurs or teams (Williams &
Nadin, 2013). Socioeconomic transformation, it
seems, is the inevitable outcome of the actions of
highly skilled, expert entrepreneurs who possess
an almost omniscient view of markets and in-
dustries (Brouwer, 2002). Entrepreneurs fill an
economic role that is highly similar to that of the
2018 669Townsend, Hunt, McMullen, and Sarasvathy

mythical hero (McMullen, 2017), but this obser-
vation highlights just how little we know about the
role of entrepreneurial action in uncertain envi-
ronments, especially when one considers that
only about 6 percent of the articles we reviewed
explored the cross-level, transformative impact of
entrepreneurial action on external environments.
Thus, much more research is needed to build
a robust micro-to-macro theory in entrepreneur-
ship research.
DISCUSSION AND OPPORTUNITIES FOR
FUTURE RESEARCH
As the foregoing review reveals, uncertainty
continues to be a problematic construct in con-
temporary research. Although scholars have
addressed some sources of conflation and confu-
sion since Knight’s articulation of the risk-
uncertainty bifurcation (Camerer & Weber, 1992;
Hey et al., 2010), our review of contemporary en-
trepreneurship literature indicates that the un-
certainty construct remains subject to overuse
and misuse, especially when used to refer to all
manner of unknowingness (Downey, Hellriegel, &
Slocum, 1975). Certainly, in some contemporary
research, many instances of unknowingness are
aptly characterized as uncertainty, in precisely
the fashion that Knight originally conceived;
other instances involve risk rather than un-
certainty because some measure of probability
can be assigned to the potential outcomes. Still
others, however, defy simple categorization as
either uncertainty or risk.
As noted from the outset, a knowledge problem
is any decision-making state in which the
decision-maker has moved past ignorance—that
is, he or she possesses at least some minimal
awareness that a decision, judgment, prediction,
observation, or assessment must be made—but
the individual does not possess certitude re-
garding either the relevant factors or likely con-
sequences of action. When this occurs, there
exists a state of unknowingness. Such condi-
tions reign supreme within the entrepreneurial
context and, in some sense, are necessary for
the existence of entrepreneurial opportunities
(McMullen & Shepherd, 2006). Yet, although
uncertainty is essential to an understanding
of management and organizational decision-
making, it loses its meaning and value when it
is used to refer to the entire landscape of in-
formational contexts lying between ignorance
and incontrovertible fact. Therefore, given the
central role and extraordinarily nuanced role of
unknowingness to entrepreneurial action, the
need for better definitions and greater precision
are clearly indicated.
Recent work by Packard et al. (2017) takes steps
to address these issues by attempting to expand
the multi-dimensionality of Knightian uncertainty
to cover multiple states of unknowingness while
underscoring the continuous and dynamic nature
of decision-making under uncertainty: “Over time,
entrepreneurs face different uncertainties as de-
cisions are made, new information is obtained, and
the entrepreneur or environment changes. As a re-
sult, entrepreneurial judgments are regularly revis-
ited, renewed, and revised”(2017: 1). These are
important considerations and further disaggrega-
tion of the uncertainty construct into more nu-
anced categories is a welcome development. Yet,
such a textured typology of uncertainty runs the
risk of conflating the decision rules, logics, and
inherent problems posed by different states of
unknowingness. This is because there is not
a“spectrum of uncertainty”but rather a “spectrum
of unknowingness”—ranging from ignorance to
certitude—some portion of which involves the
problem of uncertainty. The remainder is com-
prised of other knowledge problems, each of
which uses a distinct decision rule and logic, and
poses a distinct decision problem for entrepre-
neurial actors. In particular, in our review, we have
identified three sources of unknowingness that
have been consistently and errantly subsumed by
conceptions of uncertainty in contemporary entre-
preneurial action research: complexity, ambiguity,
and equivocality. In the following sections, we will
describe these three additional knowledge prob-
lems and discuss key boundary conditions sur-
rounding each knowledge problem and how this
more nuanced approach to knowledge prob-
lems enriches and extends entrepreneurial action
theory.
Uncertainty as One among Many
Knowledge Problems
Regardless of whether unknowingness manifests
as ambiguity, complexity, equivocality, or uncertainty,
or even various combinations of these four knowledge
problems, the multi-dimensional nature of unknow-
ingness will remain a persistent confound until defi-
nitions and empirical operationalizations are more
precisely articulated in contemporary entrepreneurial
670 JuneAcademy of Management Annals

action research. The commonplace practice of defining
one knowledge problem in terms of the others fails
to meet the minimum standard of disambiguation
(Stevenson & Wilks, 2003). The price tag for this im-
precision and conflation is stymied progress in un-
derstanding the nexus between actors and their
respective environments. Most of human judgment
and decision-making is influenced by informa-
tional assumptions that fall somewhere between
ignorance and certainty, consisting of neither
pure ignorance, nor pure certainty. Yet, approaches
to unknowingness that label this entire region
“uncertainty”or that categorize all knowledge
problems as a subset of uncertainty fail to provide
a substantive basis for the consideration of human
action. As the foregoing discussion reveals,
unknowingness takes various forms, each of which
involves different decision-making processes and
entrepreneurial actions. Because entrepreneurial
action depends on the presence of unknowingness
for opportunities to be discovered (Kirzner, 1997;
Shane & Venkataraman, 2000), created (Alvarez &
Barney, 2007), effectuated (Sarasvathy, 2001), or
imagined (Klein, 2008), well-intended uses of
knowledge problems that suffer from conflation
tend to obfuscate the nature and importance of the
impediments to entrepreneurial action. So, al-
though the risk-uncertainty bifurcation is sound,
the unintended consequence is that entrepreneurial
action research since 1921 has viewed uncertainty
as a synonym for unknowingness and as a catchall
for any set of conditions in which no probability
distribution can be generated for the set of possible
outcomes.
Furthermore, despite thesharedsearchforso-
cially and semantically appropriate decision
logics, knowledge taxonomies that situate knowl-
edge problems as subgroups underneath un-
certainty (e.g., Kahneman & Tversky, 1982; Lytras
& Pouloudi, 2006; Smithson, 2008) miss important
facets of the causes and cures of unknowingness
that are unique to each of the knowledge problems.
For example, Daft, Lengel, and Trevino (1987: 359)
argued that equivocality differs quite markedly
from uncertainty in that “no certain answers exist
and perhaps the right questions have yet to be
formulated.”Ambiguity and equivocality, unlike
uncertainty, involve the absence of factual answers
(Murphy & Pinelli, 1994), whereas complexity in-
volves a state of unknowingness that is constrained
by the need to discover effective tools to address
massive volumes and vexing convolutions (Zack,
1999). In these cases, the appropriate decision rules
and logics as well as the likely impact of entrepre-
neurial action on resolving these problems differ
considerably based on the epistemic differences in
each type of knowledge problem. Taxonomic clas-
sifications that attempt to subordinate complexity,
ambiguity, and equivocality under uncertainty
(Lytras & Pouloudi, 2006; Smithson, 2008), rather
than situating uncertainty as one of myriad knowl-
edge problems, result in addlepated conceptions of
knowledge problems, methods, and solutions.
Ambiguity. Ambiguity refers to what Weick calls
the collapse of sensemaking, the conditions that
emerge when people suddenly feel that the world is
no longer constituted as a rational, orderly system
(Weick, 1995). “Ambiguity refers to features of de-
cision environments in which alternative states are
hazily defined or in which they have multiple mean-
ings”and that “...the ‘real’world may itself be
a product of social construction”(March, 1994: 179).
In both cases, uncertainty and ambiguity might be
solved by including more information (March, 1994;
Weick, 2015) but differ based on whether the decision
environment is objective versus socially constructed
(March, 1994). To this point, uncertainty can be re-
solved by searching for additional information in
the world, whereas ambiguity is solved through the
construction of intersubjective agreement.
Ambiguity is a central topic of inquiry in the
decision theories of both economics and organi-
zation theory. In the economics literature, re-
search on ambiguity emerged from the criticisms
concerning the application of probabilistic rea-
soning in decision theory (i.e., Savage, 1951) and
criticisms of Knight’s distinction between risk
and uncertainty (1921). Although entrepreneur-
ship researchers largely assume that mentions of
Knightian uncertainty refer to something closely
akin to Venkataraman’s(1997:124)“afunda-
mental uncertainty that cannot be insured against
or diversified away,”decision theorists in eco-
nomics equate Knightian uncertainty with ambi-
guity (Fox & Tversky, 1995). For example, Holm,
Opper, and Nee (2013: 1672) define risk and am-
biguity as a nonstrategic form of uncertainty
where outcomes are not contingent upon the ac-
tions of entrepreneurs. Essentially, ambiguity is
defined as decision environments where actors
possess information about potential conse-
quences of their decision, but lack information to
specify the probabilities of these various out-
comes (Holm et al., 2013). Such ambiguities may
remain high even when there is an abundance of in-
formation if questions remain about the reliability of
2018 671Townsend, Hunt, McMullen, and Sarasvathy

key information or if there are conflicting interpre-
tations of such data (Ellsberg, 1961).
In organization theory, despite the tendency to
conflate ambiguity with various other knowledge
problems, scholars’emphasis on the subjectivist
nature of ambiguity is a cornerstone of behavioral
approaches to decision theory. For example, March
and Olsen (1976) argue that ambiguity arises from
“...goals that are unclear, technologies that are
imperfectly understood, histories that are difficult
to interpret, and (because of) participants who
wander in and out”(Cohen, March, & Olsen, 1972:
8). Ambiguity is also a central facet of Weick’sthe-
ory of sensemaking and organization (1979; 2001).
Following McCasky (1982) and March and Olsen
(1976), Weick (2001) identifies a broad set of fac-
tors that create ambiguity. Generally, these factors
are derived from unclear problems, conflicting
values and goals, or limited understanding of
cause–effect relationships. Garud and Van de Ven
(1992: 95) adopt a slightly different perspec-
tive than Weick and argue that in the context of
corporate entrepreneurship, uncertainty “implies
imperfect knowledge about causal relationships
between means and ends,”whereas ambiguity exists
when entrepreneurs are unclear about which ends are
worth pursuing.
Out of all of the other knowledge problems
discussed in entrepreneurial action research,
uncertainty is most often confused with ambigu-
ity in the articles reviewed in this study. This
conflation, in turn, perpetuates a variety of mal-
adies, including a lack of definitional clarity and
construct boundaries, and questions about the
microfoundations of entrepreneurial actions to
contend with and resolve ambiguity. In re-
cent years, interest has grown among scholars
to differentiate ambiguity from other related
knowledge problems (Alvarez & Barney, 2010;
Davis et al., 2009; Maitlis & Christianson, 2014),
and to explore the role and resolution of ambi-
guity through entrepreneurial action (Rindova
et al., 2010; Santos & Eisenhardt, 2009). Ironi-
cally, this attempt to draw a distinction be-
tween uncertainty and ambiguity collides with
still another oft-conflated knowledge problem,
equivocality.
Equivocality
Equivocality refers to knowledge problems stem-
ming from the existence of multiple meanings or
interpretations (Daft & Macintosh, 1981). Although
often conflated with ambiguity, equivocality is a
distinct condition because each interpretation is
individually unambiguous, but collectively, the
interpretations differ. In fact, the competing con-
ceptions of reality that characterize equivocality
are often either mutually exclusive or in conflict
(Daft & Weick, 1984; Weick, 1995). Equivocality
is a condition for which individuals and firms
do not suffer for want of more information. No
amount of new information has the capacity to
resolve equivocality, thereby radically differentiating
it from uncertainty, for which there is an unquench-
able pursuit for clarifying information in the greatest
achievable quantity. In fact, additional information
only serves to exacerbate equivocality into isotropy,
making it virtually impossible to decipher which data
are relevant and which not in any given decision or
action situation (Sarasvathy and Dew, 2005).
High equivocality implies confusion. “The key
problem in an equivocal situation,”wrote Frishammar,
Flor´
en, and Wincent (2011:553), “is not that the real
world is imperfectly understood and that addi-
tional information will render it understandable;
instead, the problem is that additional information
may not actually resolve misunderstandings.”The
prototypical decision-maker confronting equivocal
circumstances—the Weickian sensemaker (1995)—
faces too many meanings, not too few, so that the
problem is not ignorance but rather confusion.
By definition, equivocal situations have no ob-
jective answers (Weick, 1979). Instead, equivo-
cality is characterized by multi-sided contests
to define reality (Daft & Weick, 1984). Impor-
tant historical examples of equivocality are numer-
ous, including vigorous debates over social
Darwinism and eugenics (Hofstadter, 1944), and dis-
putes over the scientific foundations of second-hand
smoke carcinogenicity (Ong & Glantz, 2000), lead in
drinking water (Reiman & Banks, 2004), and
the global warming effects of greenhouse gases
(Bastianoni, Pulselli, & Tiezzi, 2004). Recent
industrial examples of equivocal circumstances in-
clude the ongoing battle to define commercializable
parameters of cloud computing (Armbrust et al.,
2010), education (Ball, 2013), cyber-security (Byres
& Lowe, 2004; Choo, 2011) and nano-scale technol-
ogies (Baird, Nordmann, & Schummer, 2004).
Entrepreneurship has largely ignored the chal-
lenges posed by equivocality to theories of entre-
preneurial action. Apart from a few textual citations,
equivocality remains an underexplored decision en-
vironment and ill-defined impediment to entre-
preneurial action. The one notable exception comes
672 JuneAcademy of Management Annals

from Gartner, Bird, and Starr (1992), who explore the
behaviors and actions of entrepreneurs. Specifically,
they argue as follows:
“Emerging organizations are thoroughly equivocal re-
alities(Weick, 1979) thattend toward non-equivocality
through entrepreneurial action. In emerging organiza-
tions, entrepreneurs offer plausible explanations of
current and future equivocal events as non-equivocal
interpretations. Entrepreneurs talk and act ‘as if’
equivocal events were non-equivocal. Emerging orga-
nizations are elaborate fictions of proposed possible
future states of existence. Inthe context of the emerging
organization, action is taken in expectation of a non-
equivocal event occurring in the future...An emerging
businessis embedded in an equivocal reality wherethe
possible results of specific actions taken in the present
can only have assumed future consequences”(Gartner
et al., 1992: 17–18).
Gartner et al. (1992) further argue that the almost
infinite range of behaviors available to entrepreneurs
reflect a significant degree of equivocality in many
decision environments. Over time, the emergence of
specific decision environments might calcify around
certain normative assumptions, but the exact role of
emergent organizing processes in resolving equivo-
cality remains an open question, as does its discrete
differentiation from the uncertainty construct. Thus,
Gartner et al. (1992: 19) contention that “(g)iven the
equivocal nature of the process of emergence...the
phenomenon of organization emergence has yet to be
specified in a comprehensive manner”remains both
apt and prescient regarding entrepreneurial action
research in equivocal decision environments.
However, since 1992, only a 2011 AMR article by
Navis and Glynn has journeyed significantly into the
relationship between equivocality and entrepreneur-
ship. In their study of entrepreneurial identities pro-
pounded by new ventures and the sensemaking
undertaken by potential investors, Navis and Glynn
develop a framework that positions institutional
primes and equivocal cues as the building blocks on
which investors interpret entrepreneurial identities
(2011). Their insight is that the combined force of in-
stitutional primes and equivocal cues create the
means through which the legitimate distinctiveness of
market opportunities is confirmed or denied. The cues
are considered “equivocal”precisely because “the
existence of ‘numerous or disputed interpretations’
(Powell & Colyvas, 2008: 283) precipitates the search
for meaning and certainty (Weick, Sutcliffe, &
Obstfeld, 2005: 414)”(Navis & Glynn, 2011: 488).
More recently, Maitlis and Christianson (2014)
undertook a panoramic treatment of sensemaking.
Although their treatment was not framed by an ex-
amination of the entrepreneurship context, like
Navis and Glynn (2011), they recognize the impor-
tance of equivocal cues in eliciting senseseeking and
sensemaking actions. The subtext to these more re-
cent treatments is that equivocality constitutes a rel-
atively untapped source of fresh insights about when
and how innovators and society interact to adjudi-
cate the fate of novel goods and services. Effectuation
theory (Sarasvathy, 2001) functionally aims to con-
vey the same point, although it does so without ex-
plicitly invoking the equivocality construct. Instead,
Sarasvathy and Dew (2005: 539) explore the problem
of isotropy defined as “...the fact that in decisions
and actions involving uncertain future conse-
quences it is not always clear ex ante which pieces of
information are worth paying attention to and which
not”(Fodor, 1987). The resolution to isotropy in ef-
fectuation is provided by commitments from self-
selected stakeholders to particular courses of action,
each of which aims to shape, influence, and co-create
the environment rather than derive justification from
it. This could arguably be seen as consistent with
Weick’s premise that the only viable response to
equivocality is itself equivocality (Weick, 1979).
Complexity
Complexity knowledge problems emanate from
a combination of detail complexity, which is the
multiplicity of variables involved in a problem, and
from dynamic complexity, which is the multiplic-
ity of the interactions that occur between these
variables over time (Simon, 1959; Zack, 1999).
Complexity research is a vibrant area of inquiry
within several fields in organizational research.
Of these fields, research on institutional complex-
ity (Greenwood, Raynard, Kodeih, Micelotta, &
Lounsbury, 2011), managing complex knowledge
within organizations (Kogut & Zander, 1992;
Tsoukas, 2005) or across interorganizational net-
works (Reagans & McEvily, 2003), or even research
on managing complex strategic actions and re-
sponses to establish or maintain competitive ad-
vantages (Barney, 1991; Rivkin, 2000) remain
important areas of organizational research. The
rapid rise of research exploring systems dynamics
and complexity science is a testament to the central
importance of these perspectives across a variety of
scientific fields (Benbya & McKelvey, 2006; Macy &
Willer, 2002; Page, 2015; Wolfram, 2002).
2018 673Townsend, Hunt, McMullen, and Sarasvathy

Complexity research in the field of entrepreneur-
ship has been led for decades by a cadre of scholars
who have explored the role of complexity and sys-
tems dynamics in shaping organizational emergence
(Gartner et al., 1992; Katz & Gartner, 1988; Lichtenstein,
Carter, Dooley, & Gartner, 2007; Tornikoski & Newbert,
2007). The inherent nonlinearity of complex systems
has made this line of inquiry attractive to many en-
trepreneurship scholars to provide models of organi-
zational emergence and environmental change
(Schindehutte & Morris, 2009; Uhl-Bien, Marion, &
McKelvey, 2007). Despite the depth and intellectual
importance of this research, recent evidence sug-
gests that important outcomes in entrepreneurship
are best characterized as power-law distributions
where “average”returns are heavily influenced by
relatively rare, alpha-tail events (Crawford et al.,
2015). Such patterns suggest the need to develop
new theories of entrepreneurial action and entre-
preneurship (Crawford et al., 2015) across a variety
of subfields within entrepreneurship such as social
entrepreneurship (Dorado & Ventresca, 2013), en-
trepreneurial finance (Drover et al., 2017), new
venture creation, and processes of organizational
emergence (Lichtenstein, Dooley, & Lumpkin,
2006), among many other areas.
Yet, present research on the inherent knowledge
problems associated with entrepreneurial action in
complex environments remains sparse as un-
certainty has been stretched to try to address aspects
of unknowingness that are better conceptualized as
complexity. In present entrepreneurship research,
complexity is defined as the “heterogeneity and
range of factors that have to be taken into account”
(Clarysse et al., 2011: 140). In this sense, complex
environments are thought to be difficult for entre-
preneurs to compete within because they invoke an
inability to identify all of the relevant factors that
might influence the actions of the entrepreneurs and
because they pose inherent difficulties for de-
termining how these factors will interact (Clarysse
et al., 2011). Davis et al. (2009: 420) define environ-
mental complexity as “the number of opportunity
contingencies that must (be) addressed successfully.”
Murky distinctions between uncertainty and
complexity complicate research into the emergent,
interrelated subsystems of entrepreneurial action—
for example, sensemaking interactions among en-
trepreneurs, stakeholders, firms, and markets
(Selden and Fletcher, 2015)—and the micro-
foundational impacts of complexity on entrepreneurial
action (Clarysse et al., 2011; Jones & Casulli, 2014;
Palmi´
eetal.,2016;Shepherd,2011).Forexample,atthe
individual level of analysis, one of the key lines of
inquiry in present research explores how cognitive
complexity (Malmstr¨
om et al., 2015), belief struc-
tures (Kiss & Barr, 2015), and other cognitive factors
impact entrepreneurial decision-making (Garrett &
Holland, 2015).
In certain cases, “practicing analogical reasoning
over many novel and complex problems increases
reasoning capability”(Jones and Casulli, 2014:55)
and simplifying heuristics ostensibly create the
simple rules used to guide entrepreneurial action in
complex environments (Davis et al., 2009;
Eisenhardt, 2013; Sull & Eisenhardt, 2015). The dif-
ficulty is that scholarly recommendations for
decision-making in the context of high-velocity,
nascent-stage venturing similarly prescribe analogi-
cal reasoning and pattern matching for ambiguous,
equivocal, and uncertain conditions, as well. When
small initial differences between decision environ-
ments can generate massive differences in perfor-
mance and survival outcomes (Crawford et al., 2015),
definitional distinctions between knowledge prob-
lems take on added significance.
Establishing Boundary Conditions among
Entrepreneurial Knowledge Problems
If construct conflation with uncertainty and other
knowledge problems across the landscape of unknow-
ingness is the problem, then careful boundary setting is
the solution. Although colloquial and scholarly usage
of the four knowledge problems has often exacerbated
the fuzzy boundaries and rampant misuse, there are key
points of differentiation. Table 3 builds on the findings
of our review of foundationalandcontemporaryliter-
ature by incorporating the new insights and highlight-
ing a more complete set of factors that differentiate the
four knowledge problems from one another—namely,
the decision rule, the decision logic, and the nature
of the knowledge problem. We will outline these
boundary conditions in more detail in the follow-
ing paragraphs.
Structure of decision rules. First, knowledge
problems can be differentiated based on the typical
structure of the decision rules that reflect the role of
information or the steps taken to resolve the knowl-
edge problem.3For example, March (1994: 178)
3Our intent with discussing the structure of the decision
rules is not to imply that these decisions are rational
choices but rather we simply wish to identify the key
epistemological problems each type of knowledge problem
addresses.
674 JuneAcademy of Management Annals

TABLE 3
Boundary Conditions among Entrepreneur Knowledge Problems
Uncertainty Complexity Ambiguity Equivocality
Structure of typical
decision rule
Can action X cause outcome Y? (Is
there a rule that X →Y?)
Do actions X1 or X2 cause outcome
Y? (Does X1 * X2 change the first-
order rules that X1 →Y or
X2→Y)?
Does action X cause outcome Y in
situation Z? (Does the rule X →Y
apply in situation Z?)
Which action, X1 or X2, should I
take to produce outcome Y given
what I know about situation Z?
(Which rule, X1 →Y or X2 →Y,
applies in situation Z?)
Decision logic Decision environment:
probabilistic
Decision environment:
probabilistic
Decision environment: vague Decision environment: vague
Logic of consequence Logic of consequence Logic of appropriateness Logic of appropriateness
Question about whether
cause–effect or if–then rule
exists
Question about whether
cause–effect or if–then rule
exists
Question about when application
of cause–effect or if–then rule is
justified
Question about when application
of cause–effect or if–then rule is
justified
Is the technical relationship
between action and outcome
understood?
Is the technical relationship
between action and outcome
understood?
Is the situational appropriateness of
the relationship between action
and outcome understood?
Is the situational appropriateness of
the relationship between action
and outcome understood?
Role of
entrepreneurial
action in resolving
decision problem
Decisions concerning actions in
isolation
Decisions concerning actions in
comparison
Decisions concerning actions in
isolation
Decisions concerning actions in
comparison
The actor knows the question being
asked, the rule being considered,
and thus how to interpret the data
such that data constitute
information.
The actor is confronted by multiple
questions and decision rules. As
a result, how to interpret the data
is not clear such that data do not
equal information.
The actor knows the question being
asked, the rule being considered,
and thus how to interpret the data
such that data constitute
information.
The actor is confronted by multiple
questions and decision rules. As
a result, how to interpret the data
is not clear such that data do not
equal information.
Thus, the discovery of critical data
through entrepreneurial action
will resolve the knowledge
problem.
Thus, the discovery of more data
through entrepreneurial action
complicates the scope of relevant
information and degrades
decision-making accuracy.
Thus, the creation or generation of
critical data through
entrepreneurial action will
resolve the knowledge problem.
Thus, the creation or generation of
more data through
entrepreneurial action
complicates the scope of relevant
information and degrades
decision-making accuracy.
2018 675Townsend, Hunt, McMullen, and Sarasvathy

asserts that the main idea behind uncertainty is that
“...there is a real world that is imperfectly un-
derstood,”whereas “ambiguity refers to feature of
decision-making in which alternative states are
hazily defined or in which they have multiple
meanings ...(since) the ‘real’world may itself be
a product of social construction.”For a decision rule,
actors resolve uncertainty by collecting information
to confirm whether action X causes outcome Y. For
ambiguity, however, the socially constructed nature of
the world implies that action X only causes outcome Y
under a specific set of Z (social/intersubjective) con-
ditions. By contrast, the decision rule under conditions
of complexity addresses the potential for nonlinear
interactions among the decision criteria to explore
the extent to which “...interactions produce higher
order structures (self-organization) and functionalities
(emergence)”(Page, 2015: 22). These higher order
outcomes derived from the interactions among key
decision criteria produce the nonlinearities that thwart
attempts by entrepreneurs to estimate key outcomes.
Furthermore, as we noted earlier, complexity knowl-
edge problems are often exacerbated by inclusion of
new information. Hayek (1945), Taleb (2007), among
others, discuss the inherent futility of attempting to
compute the probabilistic outcomes of complex envi-
ronments. No new information will resolve such
complex computations. As such, much of the present
research on operating in complex environments em-
phasizes the importance of fast and simple rules. On
the other hand, both ambiguity and uncertainty can be
resolved by gathering more information but differ
based on whether this additional information im-
proves the predictability of outcome probabilities
(uncertainty) or improves the predictability of out-
come preferences (ambiguities). Importantly, so when
March (1994) argues that ambiguity cannot be solved
by gathering more information, he is arguing that the
predictability of ambiguous preferences is not resolved
through search, but can be solved through imagination
and through the development of intersubjective
agreement.
Decision logic. Knowledge problems can also be
differentiated based on the types of decision logic
used to resolve the underlying problems. Specifi-
cally, uncertainty and complexity use a logic of
consequences, whereas ambiguity and equivocality
use a logic of appropriateness. According to March
(1994: 2), the logic of consequences refers to de-
cisions that are “...consequential in the sense that
action depends on anticipations of the future effects
of future actions.”In the case of action under con-
ditions of uncertainty, concern with the future
consequences of action often stimulates search or in-
crementalprocesses of action (McKelvie et al., 2011).
Under conditions of complexity, entrepreneurial
action involves simplifying the decision environ-
ment to minimize the challenges of comprehending
the dynamic interactions of factors in the decision
environment. Conversely, ambiguity often invokes
a logic of appropriateness in that the “reasoning
process is one of establishing identifies and matching
rules to recognized situations.”In ambiguous and
equivocal situations, unclear preferences invoke
identity claims and other interpretive frames to es-
tablish a basis for the outcome preferences.
Role of entrepreneurial action. Last, these know-
ledge problems invoke different conceptualizations of
the role of entrepreneurial agency and action in resolving
each knowledge problem. In the case of uncertainty, al-
though the outcome probabilities based in the func-
tioning of the real world are likely not influenced
directly by the actions of the entrepreneur, un-
dertaking more systematic search processes to dis-
cover additional relevant information will enable
entrepreneurs to resolve uncertainty. Emergent pro-
cesses in complex environments limit the extent to
which entrepreneurial actions shape the external en-
vironment once the interactive complexity of the en-
vironment begins to control the processes of change.
Under these conditions, more data do not always
equate to more information—especially when these
data produce nonlinear outcomes. For ambiguity, the
factors suggest that actions taken by entrepreneurs to
bracket or frame the external environment can enable
the development of intersubjective consensus. Be-
cause these environments are the product of social
construction, entrepreneurial actions that generate
these intersubjective agreements can shape these en-
vironments. Finally, although the knowledge prob-
lems in equivocal environments are exacerbated by
the inclusion of the new information, these environ-
ments are also the product of social construction and
thus are influenced by the actions taken by entrepre-
neurs to produce intersubjective agreement (Dew,
Velamuri, & Venkataraman, 2004). In these cases,
proactive framing strategies or political maneuvering
can help ensure that desired outcomes are achieved
through entrepreneurial action (Santos & Eisenhardt,
2009).
Opportunities for Future Research
It is clear from our review that despite the breadth
of present research on knowledge problems and en-
trepreneurial action, numerous gaps remain in our
676 JuneAcademy of Management Annals

understanding of the role entrepreneurial action
plays in resolving each of the knowledge problems.
In this section, we outline several of the opportuni-
ties for future research. Although a complete list of
these opportunities is beyond the scope of this arti-
cle, our intention here is to highlight a few intriguing
avenues for further inquiry.
Misdiagnosis of knowledge problems. One of the
major implications of this review is that entrepreneurs
face a more pluralistic set of environments than is
typically imagined in the Knightian universe of risk
and uncertainty. Because these environments operate
under different decision logics (i.e., logic of conse-
quences versus logic of appropriateness) and are
impacted differentially by information (i.e., more in-
formation helps resolve uncertainty/ambiguity while
more information exacerbates complexity and equiv-
ocality), the misdiagnosis of a knowledge problem and
the resulting actions taken by entrepreneurs to re-
solve these problems hold major significance con-
cerning the relative effectiveness of organizing
mechanisms used by entrepreneurs. For example,
one of the important contributions of effectuation
research to theories of entrepreneurial action is the
comparative emphasis on using social artifacts to
provide interpretive frames for environments char-
acterized by Knightian uncertainty (Sarasvathy &
Kotha, 2001). Under ambiguity, these artifacts at
least partially enable entrepreneurs to socially con-
struct elements of their operating environment and
to operate “as-if”the venture possesses legitimacy
(Gartner et al., 1992; Wiltbank et al., 2006). What is
less known is whether such strategies enable or
constrain entrepreneurial action in complex
environments.
In a sense, complex environments present some of
the same challenges effectuation is designed to ad-
dress as the problem of emergence in complex en-
vironments often prevents effective forecasting or
prediction (Fisher, 2012; Read, Dew, Sarasvathy,
Song, & Wiltbank, 2009). At the same time, it remains
to be seen whether organizing around the resources/
means currently controlled by the entrepreneurs
would facilitate effective action in complex envi-
ronments. The evolution of complex environments
is strongly influenced by initial, local conditions
(Aldrich & Martinez, 2001; Mainela & Puhakka,
2009; Miller, 1983), but ultimately these tend to
change, often in unexpected ways. Although strate-
gies exist for “making do with the resources at hand,”
(Baker, Miner, & Eesley, 2003) there is no guarantee
that such actions will enhance the firm’s long-term
effectiveness, particularly if precious resources are
channeled toward combatting the wrong knowledge
problem.
Consistent with this point, Davis et al. (2009) use
the tools of analytical theory to demonstrate the
varying influences of situational mechanisms on the
organizing strategies of firms as they are embedded
in different environments. The authors demonstrate
that ambiguous and complex environments exert
distinct influences on the organizing strategies of
firms and that in the case of ambiguity, these orga-
nizing strategies often yield mediocre long-term
performance. These studies effectively demonstrate
the influence of situational mechanisms on firm or-
ganizing decisions, but extant research has yet to
take the additional step of addressing whether and
how a mismatch between the perceived knowledge
problem and the actual knowledge problem in-
fluences the entrepreneur’s long-term prospects. An
entrepreneur who applies the logic of consequences,
when perceiving uncertainty, would be at odds with
the prevailing knowledge problem impediment if the
actual environmental conditions were ambiguous,
a condition that functions in accordance with the
logic of appropriateness. Such a mismatch could
foster a dogmatic approach to market entry prospects
for a novel business model, rather than a facilitative
approach that embraces a social constructive per-
spective of shared discovery, an approach that may
be more conducive to resolving the ambiguous en-
vironmental conditions, as opposed to the uncertain
conditions perceived by the entrepreneur.
Among the knowledge problems elaborated in this
review, there are 16 possible pairings between the
knowledge problem that an entrepreneur perceives
and the knowledge problem that actually exists.
Only four of these pairings will produce alignment
between the perceived and actual knowledge prob-
lems. For example, an entrepreneur pursuing an op-
portunity may perceive environmental conditions to
be ambiguous when in fact they are ambiguous. Under
these circumstances, the entrepreneur’s organizing
efforts to apply the logic of appropriateness and the
pursuit of more information are aligned with the en-
vironmental realities. Similarly, perceived versus
actual pairings of complex–complex, equivocal–
equivocal, and uncertain–uncertain exhibit alignment
between the knowledge problem impediments and
the entrepreneur’s organizing action. However, the
other 12 pairings involve misalignment; for exam-
ple, perceived ambiguity versus actual uncertainty.
In these 12 instances, the perceptions and organiz-
ing activities of entrepreneurs are not congruent
with the knowledge problem impediments posed by
2018 677Townsend, Hunt, McMullen, and Sarasvathy

the operating environment. For scholars, unchain-
ing extant theories of opportunity pursuit from both
the overly broad application of Knightian un-
certainty and the overly narrow conception of
knowledge problems opens the door to new theory
and new empirical pathways regarding the ques-
tions of when, why, and how ventures succeed or
fail in their efforts to achieve market acceptance.
The price tag for misdiagnosing the environment
can be high. For example, from 2008 to 2015,
Hewlett-Packard acquired 20 businesses, costing
more than $45 billion, in its effort to establish market
relevance in information management, networking,
and cloud computing software. The acquisitions
were driven by Hewlett-Packard’s perception that
the emerging opportunities in hybrid cloud services
constituted a complex knowledge problem, just as its
corporate culture had influenced and directed the
firm for 70 years (Kotter, 2008). In fact, however, the
operating environment for cloud services through-
out this era was more reflective of equivocality,
conditions in which competing conceptions of cloud
computing’s future were still playing out. The logic
of appropriateness was far more relevant to the
conditions than were the tool-building and brute
force problem-solving approaches that characterize
the logic of consequences, wherein the end point is
well understood, but the pathway requires develop-
ment. The misalignment between perceived complexity
and actual equivocality proved costly to Hewlett-
Packard. In time, some $20 billion was eventually
written off as a permanent loss due to asset impairment
(Darrow, 2016).
Additional research to explore how knowledge
problem “misdiagnoses”occur and to what end
could provide important insights for scholars seek-
ing to establish a firmer foundation for the articula-
tion of transformative mechanisms that are more
conducive to multi-level analysis. It would also be
interesting to see if the effects of some knowledge
problem mismatches wield a more potent influence
than others. Some misdiagnoses may be “merely”
costly, whereas others may prove to be fatal.
The multi-level, multi-dimensional, multi-temporal
nature of knowledge problems. Further compounding
the challenges of knowledge problem “diagnosis”is the
reality that knowledge problems are not “well-behaved”
confounds insofar as they are constantly evolving as the
market participants and environmental conditions
change. Moreover, knowledge problems are not demo-
cratic. As Weick famously demonstrated in his knowl-
edge problem deconstruction of the Mann Gulch
disaster (1993), not all of the firefighters were equally
well equipped to assess the circumstances and respond
accordingly. The same inequity holds true when
knowledge problems impact market participants at the
firm level, industry level, and national level of analysis.
Some forms of unknowingness may impact all humans,
everywhere, whereas other forms’unknowingness
may cause perceived uncertainty among some in-
dividuals but not others. Similarly, the perception
of complexity across an entire industry does not
mean that all individuals will also perceive com-
plexity. The vantage points of individual actors
matter. By any measure then, knowledge problems
constitute a multi-level set of challenges that exist
simultaneously in multiple states. Scholars wishing
to assess the role of knowledge problems will nec-
essarily engage research designs that are capable of
multi-level analysis. In no small way, the dynamic
capabilities literature (Teece, Pisano, & Shuen,
1997; Winter, 2003)—including specific foci in the
realm of entrepreneurship (Zahra, Sapienza, &
Davidsson, 2006)—constitutes an attempt to dif-
ferentiate firm-level effectiveness in managing the
vagaries continually shifting operational requirements.
Multi-level analysis is crucial as it encompasses both
situational and transformative mechanisms that con-
stitute the essence of Coleman’smacro-to-micro-to-
macro approach to action theory (Kim et al., 2016).
Knowledge problems are also multi-dimensional.
As the foregoing discussion of knowledge problem
diagnosis demonstrated, mismatched pairings are an
expensive source of complication for individuals
and firms that misread the nature of unknowingness
being confronted. In fact, however, these one-to-one
pairings may over-simplify circumstances in which mul-
tiple forms of unknowingness are faced simultaneously,
at various levels of analysis and potentially in
combination with one another. For example,
a“born global”energy company may simulta-
neously face threats to its ability to create and cap-
ture value by all four knowledge problems:
uncertainties in forecasting foreign market growth
rates; ambiguities in responding to diverse local,
state, and federal regulations; complexities in de-
veloping high-performance distillates; and equivo-
cality in addressing the trade-offs between renewable
and nonrenewable energy. Each of these knowledge
problems constitutes a distinctive form of unknowability
that requires a different resolution, even while all four
exist simultaneously.
The challenges of addressing such multi-
dimensionalities are compounded by the multi-
temporal nature of unknowingness. Multi-temporality
occurs in two forms, both of which have a significant
678 JuneAcademy of Management Annals

impact on how knowledge problems are identified and
processed. The first involves the simultaneous occur-
rence of more than one tempo. Different individuals
and firms will have differing levels of resources, capa-
bilities, insights, and commitment, each of which im-
pacts the willingness and ability (Gnyawali & Fogel,
1994) to move fast or slow in identifying and pursuing
an opportunity. Even within firms, differing tempos
exist. Some of these are done on purpose, depending on
the knowledge problem being encountered. For
example, marketing and sales personnel are highly
motivated to resolve demand uncertainties through
aggressive expenditures on test markets and pro-
motion. Conversely, research and development may
require decades to develop technologies and algo-
rithms capable of targeting novel therapies based on
insights from gene sequencing. Among entrepreneurs,
some market actors may interpret the presence of un-
certainty as a signal that speed-to-market strategies are
favored. Another entrepreneur, confronting the iden-
tical set of circumstances, may opt for a slower ap-
proach in deference to concerns about coexistent
equivocality over which solution set is likely to best
interface with existing technologies. Each entrepreneur
functions at a different tempo based on idiosyncratic
assumptions regarding the knowledge problems being
faced.
The second form of multi-temporality involves
capturing the same individual or organization across
multiple timeframes. It is essentially a time-lapsed
sequence of snapshots, showing the changes that
occur over time, like a flower bud evolving into
a blossom. Similarly, unknowingness changes over
time as resolving events occur, new tools are de-
veloped, or sociocultural battles are won or lost.
Scholars have convincingly applied real options
reasoning to the role this continual state of change is
marked value-creating and value-destroying in-
teractions of time, entrepreneurs, and opportunities
(McGrath, 1999). Such efforts have tended to focus
exclusively on the relationship between entrepre-
neurs and uncertainty; however, a continual state of
change affects the nature and substance of all forms
of unknowingness, not just uncertainty. For scholars,
this means that the methods and techniques used to
observe the antecedents and outcomes of decision-
making under conditions of unknowingness must
function in pulse-like fashion to capture the changes
as they occur over time. Reliance on self-report sur-
veys, cross-sectional data sets, and retrospective ar-
chives is likely to result in biases and confounds
when investigating the ways in which individuals
and firms address unknowingness over time.
Organizations as portfolios of knowledge problems.
Given the potent challenges of multi-level, multi-
dimensional, and multi-temporal effects of unknowing-
ness facing entrepreneurs, scholars may be well
served by approaching scholarly inquiry as a pro-
cess of identifying and resolving problems. With
a multitude of interactions continually occurring
over time, across and within various levels that in-
volve all four knowledge problems, it is virtually
impossible to parse the forms of unknowingness
encountered by any one individual or firm, much
less a population of market actors. Accordingly,
scholars attempting to better understand and in-
corporate unknowingness may be well served by
thinking about organizations as portfolios of knowl-
edge problems. In the same way that financial, R&D,
product, capital project, and business line portfolios
are comprised of highly interrelated, statistically,
strategically, and operationally nonindependent ele-
ments (Blichfeldt & Eskerod, 2008), so too are the
evolving knowledge problems confronted by an or-
ganization over time. Organizational structures and
activities are only useful to the extent that they enable
mitigation of or coexistence with the knowledge
problems that substantively frame an organization’s
situation. This is particularly evident among entre-
preneurs where the arc of opportunity development
involves identifying and confronting various forms of
unknowingness in evolving fashion throughout the
life cycle of a nascent-stage venture.
Because entrepreneurship entails the willingness
and ability to monetize unknowingness (McGrath,
1999; McGrath and MacMillan, 2000), entrepre-
neurship scholars are likely to benefit from a recon-
ceptualization of organizations as a portfolio of
perceptions and behaviors stemming from the vari-
ous forms of unknowingness over the course of en-
trepreneurial opportunity development (Ardichvili,
Cardozo, & Ray, 2003). Through the efforts to cope
with the four knowledge problems, early-stage firms
will recruit new employees and implement business
approaches that structure the organization the ability
to monetize unknowingness. Over time, the organi-
zation literally forms as an outgrowth of this evolving
portfolio of people and processes intended to
broaden and deepen the organization’s capacity to
survive and thrive in the midst of unknowingness.
Strategic uses of knowledge problems. By think-
ing of organizations as portfolios of knowledge problems,
it follows that because each specific portfolio will
differ from all others, heterogeneous firm strategies
and firm performance will emerge over time. Al-
though it is important to diagnose and identify the
2018 679Townsend, Hunt, McMullen, and Sarasvathy

knowledge problems inherent in local decision
environments accurately to deploy organizing
mechanisms effectively, prior research also in-
dicates that entrepreneurs might be able to use these
knowledge problems strategically. Notable theories
such as the resource-based view of the firm ac-
knowledge the importance of “causal ambiguity”in
preventing mimicry by competitors (Barney, 1991).
The benefits of strategic uses of ambiguity might
extend well beyond mitigating problems with mi-
mesis by competitors. Eisenberg (1984) suggests
that strategic uses of ambiguity enable organiza-
tions to create “unified diversity.”In other words,
among entrepreneurs, the lack of clarity about the
primary functional uses of a particular technologi-
cal product or service might enable the entrepre-
neur to use a common product platform to appeal to
a diverse set of customer groups (Muegge, 2013;
Reed & DeFillippi, 1990; Santos & Eisenhardt,
2009). Or perhaps, an entrepreneur might use an
ambiguous strategic orientation to appeal to a di-
verse set of investors. It is not entirely clear where
the boundaries between the benefits of clarity and
ambiguity exist in many strategic scenarios faced by
entrepreneurs. Rather than assuming that clarity is
always beneficial, it remains an open question for
future research to explore how strategic ambiguity
might facilitate entrepreneurial action.
Other research in management is studying how
issue equivocality shapes stakeholder relations
among and within firms (Daft & Macintosh, 1981;
Daft & Weick, 1984; Lewis, 2004). Given the diversity
of stakeholder ties, issue equivocality creates nu-
merous challenges for managers and social change
agents (Sonenshein, 2016) and also opens up room
for strategic action to enhance the flexibility of stra-
tegic options enjoyed by the firm. Because equivocal
issues can be interpreted in multiple ways, the use
of framing strategies might potentially enable entre-
preneurs to draw the attention of stakeholders to
interpretations that better accommodate their de-
sired strategic aims (Santos & Eisenhardt, 2009).
CONCLUSION
After almost a century of research framed around the
question of risk and uncertainty, the overuse of the term
“uncertainty,”alackofdefinitionalclarity,andaten-
dency to operationalize the concept imprecisely have
led to increasing calls for more nuance and a better
conceptualization of uncertainty in entrepreneurship
theory (Packard et al., 2017; Ramoglou & Tsang, 2016).
To address these problems, we conduct a multi-
disciplinary review of existing research to consider
how uncertainty impacts and is influenced through
entrepreneurial action. Based on this review, although
we agree that more construct clarity is needed regarding
the role and resolution of uncertainty as a knowledge
problem impeding entrepreneurial action, a central
contribution of this review is to extend the range of
knowledge problems beyond uncertainty to consider
also how ambiguity, complexity, and equivocality im-
pact entrepreneurial action. Through these efforts, we
identify a wide range of potential research questions to
explore how entrepreneurial action overcomes the in-
herent epistemological obstacles to strategic action that
manifests in terms of the novelty being confronted
along one or more dimensions of action.
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