ELSEVIER
USING COGNITIVE THEORY
TO EXPLAIN
ENTREPRENEURIAL
RISK-TAKING: CHALLENGING
CONVENTIONAL WISDOM
LESLIE E. PALICH
Baylor University
D. RAY BAGBY
Baylor University
Though it occupies the center of most definitions of entrepreneurship, the
concept of risk-taking and its linkages with other constructs (most notably
personal traits) have been difficult to capture. As a result, it has been difficult
to explain why entrepreneurs rush in to take advantage o f opportunities that
others fail to see or act upon. However, research on social cognition may
shed new light on these challenging issues (Shaver and Scott 1991), providing useful frameworks that differentiate entrepreneurs from others while predicting differences in risktaking behavior.
Within the strategic management literature, Dutton and Jackson (1987) adopted categorization
theory as a conceptual framework to explain how decision-makers evoke alternate strategic decision
frames. They argue that the attributes of a particular issue cause the decision-maker to categorize that
strategic issue in different ways, and this heuristic guides the meaning of a stimulus by directing attention
toward some of its elements and away from others. Building upon this work and the knowledge structure
literature, Gooding (1989) developed decision frames concerning perceptions of strengths~weaknesses
and opportunities/threats. Using distinctive and equivocal data in scenarios, he found that distinctive
data tended to evoke the same decision frame in all subjects, whereas equivocal data led to different
decision frames among subjects. In other words, in the absence of a particular stimulus (i. e., a scenario
is equivocal in nature), individuals tend to resort to a chronic frame of reference when interpreting
those data.
This research produced some revealing results, but these studies were not constructed to investigate
the unique responses of entrepreneurs when faced with common circumstances. To extend this area
EXECUTIVE
SUMMARY
Address correspondence to Leslie E. Palich, Department of Management, Hankamer School of Business,
Baylor University, Waco, TX 76798-8006.
We gratefully acknowledge the assistance of Harry A. Domicone in the collection of data as well as two of
this journal's anonymous reviewers for their helpful comments on an earlier draft of this article.
Journal of Business Venturing 10, 425-438
© 1995 Elsevier Science Inc.
655 Avenue of the Americas, New York, NY 10010
0883-9026/95/$9.50
SSDI 0883-9026 (95) 00082-J
426
L.E. PALICH AND D.R. BAGBY
of inquiry, we designed our study using a scenario approach to determine if entrepreneurs exhibit
evidence of unique cognitive categorization processes when they are presented with equivocal data.
Ourfindings proved interesting. As predicted, entrepreneurs did not vary significantly in their responses
to a risk propensity scale, meaning that they did not perceive themselves as being any more predisposed
to taking risks than nonentrepreneurs. This is consistent with previous findings. However, multivariate
tests revealed that entrepreneurs categorized equivocal business scenarios significantly more positively
than did other subjects, and univariate tests demonstrated that these perceptual differences were consistent and significant (i.e., entrepreneurs perceived more strengths versus weaknesses, opportunities
versus threats, and potential for performance improvement versus deterioration). These results have
implications for self-report risk propensity scales. Entrepreneurs may not think of themselves as being
any more likely to take risks than nonentrepreneurs, but they are nonetheless predisposed to cognitively
categorize business situations more positively. This interpretation leads entrepreneurs to view some
situations as "opportunities," even though others perceive them to have little potential (i. e., the latter
view these situations as risky ventures that offer disproportionately low returns relative to their associated
risks).
These results offer hope to those who aspire to identify and exploit business opportunities, even
when they are distracted by the perceived high risk of these ventures. Unlike personal traits, cognitive
processes can be changed. That is, if certain aspects of cognition are different for entrepreneurs, or
more successful entrepreneurs, these processes can be learned or mastered through programs such as
~rame of reference" training. This approach has successfully increased the assessment accuracy of
individuals charged with various assignments, including performance rating (cf Sulsky and Day 1992).
These efforts may be adapted for training in opportunity evaluation, allowing those predisposed to
negative framing to increase the frequency of correct categorizations.
Our results also offer the potential to develop a taxonomy that may help to identify entrepreneurs, a
tool that would be useful tofirms interested in assessing individuals'natural potentialfor entrepreneurial
behavior. At the same time, systematic differences in cognitive processes may permit the differentiation
of entrepreneurs from small business owners, which would be useful since these groups ofien cannot
be determined from the size of an enterprise (i.e., both tend to be associated with smaller ventures).
Finally, such a taxonomy would provide the impetus for future research that mayfurther define characteristics of risk-taking and, indeed, the nature of entrepreneurship itself
INTRODUCTION
What each man wishes, that he also believes to be true.
- Demosthenes
Entrepreneurship is a multidimensional phenomenon. When tracing the development of this
concept in the literature, it becomes clear that no one definition of an entrepreneur prevails.
This diversity is reflected in works such as those that have conceived of entrepreneurs as
confident individuals who act upon their own judgment in the face of uncertainty (Knight
1921), innovators who "carry out new combination s" by introducing new products or processes
(Schumpeter 1934), or those who quickly recognize opportunity but have little interest in
building organizations (Kirzner 1973). Despite this variance, one common theme running
through the entrepreneurship literature revolves around differences in predisposition toward
risk-taking. This was clearly at the center of the first formal theory ofentrepreneurship wherein
Cantillion (1755) described entrepreneurs as the self-employed who "adjust themselves to
risk" where the return is uncertain. Although theorists disagree over exact definitions, entrepreneurs are widely considered to be attracted to risky ventures that promise above-average
profit and growth (d'Amboise and Muldowney 1988).
COGNITIVE THEORY AND RISK-TAKING
427
Notwithstanding this core concept, it remains difficult to identify entrepreneurs. Vesper
(1980) investigated entrepreneurship and concluded that its nature may be a matter of individual perceptions. For example, economists tend to adopt Schumpeter's view that entrepreneurs
are those that integrate resources in unique combinations to generate profits. Corporate
executives often equate entrepreneurs with small business managers incapable of directing
larger enterprises. Governments see entrepreneurs as the drivers of new job creation. Still
others suggest that entrepreneurs can be recognized by traits such as their need for achievement
(McClelland 1961) or a strong internal locus of control (Van de Ven, Hudson, and Schroeder
1984). Nonetheless, empirical support for these conceptualizations has been disappointing
at best (Low and MacMillan 1988).
Recently several scholars (e.g., Gartner 1985; Wortman 1987) have suggested that
entrepreneurs may be as different from each other as they are from the rest of the population.
This realization, and the lack of results from trait research in particular, have created interest
in cognitive dimensions of entrepreneurship. As Shaver and Scott (1991, p. 26) conclude,
"a psychological approach to new venture creation must involve cognitive processes that
occur within the individual." Although risk-taking seems to be the common denominator to
most definitions of entrepreneurship, we postulate that entrepreneurs may have no greater
propensity to bear risk than nonentrepreneurs (cf. Brockhaus 1980; Brockhaus and Horwitz
1986). Rather, based upon the tenets of cognitive theory, entrepreneurs may simply categorize
and subsequently frame the same stimuli differently from nonentrepreneurs. That is, what
has been widely recognized as a propensity for risk on the part of the entrepreneur may
instead be an artifact of this alternate framing. Entrepreneurs may not necessarily prefer to
engage in more risky behavior; instead, their behavior may be the result of framing a given
situation more positively than negatively, thereby focusing on the high probability for favorable outcomes and responding according to these perceptions. In contrast, nonentrepreneurs
may not share this "rose garden" view, leading them to react more cautiously.
Within the strategic management literature, Dutton and Jackson (1987) adopted categorization theory as a conceptual framework to explain how decision-makers evoke alternate
strategic decision frames. They argue that the attributes of a particular issue cause the decisionmaker to categorize that strategic issue in different ways, and this heuristic guides the meaning
of a stimulus by directing attention toward some of its elements and away from others.
Building upon this work and the knowledge structure literature, Gooding (1989) developed
decision frames concerning perceptions of strengths/weaknesses and opportunities/threats.
Using distinctive and equivocal data in scenarios, he found that distinctive data tended to
evoke the same decision frame in all subjects, whereas equivocal data led to different decision
frames among subjects. In other words, in the absence of a particular stimulus (i.e., a scenario
is equivocal in nature), individuals tend to resort to a chronic frame of reference when
interpreting those data.
This research produced some revealing results, but these studies were not constructed
to investigate the unique responses of entrepreneurs when faced with common circumstances.
To extend this area of inquiry, we designed our study using a scenario approach to determine
if entrepreneurs exhibit evidence of unique cognitive categorization processes when they are
presented with equivocal data.
CATEGORIZATION
THEORY
Categorization is one of several theories of social cognition. Pioneered by Rosch and colleagues (e.g., Mervis and Rosch 1981 ; Rosch 1975, 1978; Rosch et al. 1976), categorization
428
L.E. PALICH AND D.R. BAGBY
theory acknowledges the power of cognitive heuristics to explain human behavior and decision-making. Human beings simply do not have the cognitive capacity to process and remember all information stimuli that arise from complex situations (Komatsu 1992). Therefore,
for the sake of mental economy, they use cognitive devices to manage these complicated
cues. One common heuristic involves matching observed stimuli with a mental "prototype"
(the most representative member of a cognitive category) or, more generally, with the schema
represented by the prototype (Anderson 1991; Mount and Thompson 1987). This cognitive
organization allows the perceiver to make inferences about the attributes of the situation as
well as the relationships among those attributes (Fiske and Linville 1980). That is, based
upon observations of the salient attributes of an object or concept, decision-makers formulate
mental categories to optimize the management of that information (Dutton and Jackson 1987).
As one of the most basic cognitive functions, categorization proves useful by allowing
for efficient storage of information (Mount and Thompson 1987). Implicitly, these categories
improve the accuracy of predictions regarding categorized situations while at the same time
permitting efficient communication about the features of category members (Anderson 1991;
Corter and Gluck 1992). Because of these functional advantages, managers are quick to
apply this heuristic as they form opinions about complex business situations that reveal less
than complete information. This leaves room for alternate interpretations (assessments) of
the very same scenario, depending upon the "mental short-cut" each perceiver is predisposed
to take (i.e., the category they are most likely to associate with that situation). If these
categorizations vary systematically between perceivers or groups of perceivers, then assessments are likely to be similarly skewed or distorted (Kahneman 1992; Krueger, Rothbart,
and Sriram 1989; Tversky and Kahneman 1992).
ENTREPRENEURS
AND COGNITIVE PROCESSES
Historically, much of the literature has characterized entrepreneurs as risk-takers. However,
we posit that this view may be inaccurate. Rather than risk-taking, perhaps the characteristics
observed and reported in the entrepreneurship literature are actually the result of systematic
differences in cognitive processes. Research has demonstrated that entrepreneurs are notably
more optimistic in their assessments of business situations (e.g., Cooper, Woo, and Dunkelberg 1988). Applying the previous theory, entrepreneurs will generally categorize more situations as holding strengths and opportunities because the positive attributes (and potential
outcomes) of a situation are naturally more salient to them. Therefore, concomitant decisionmaking behavior could be consistent with that of others who are less risk-taking, had the
latter categorized the situation similarly as dominated by strengths and opportunities. In
reality, nonentrepreneurs may be less likely to characterize the situation in optimistic terms
(i.e., as holding greater weaknesses and threats) and thus make decisions reflecting that
negative perspective.
In short, these responses illustrate the aforementioned principle articulated by Demosthenes. Perhaps Weick (1979) said it better when he concluded from observing human behavior
that "believing is seeing." That is, when receiving equivocal information, individuals are
likely to perceive that which they are predisposed to see. The literature sometimes refers to
this as "schema accessibility" (Fiske and Taylor 1984) or the "available heuristic" (Wofford
1994). Higgins and King (1981) describe this phenomenon as the readiness with which a
particular schema is used in information processing. Others simply define it as the availability
of a specific schema or cognitive structure in a person's memory (Bruner 1957; Tulving and
Pearlstone 1966), which increases the likelihood of its use (Kahneman and Tversky 1987).
COGNITIVE THEORY AND RISK-TAKING
429
The essence of these definitions is the same-that is, at any given time one cognitive structure
may be more available to an individual than others. This undergirds our conclusion that
entrepreneurs do not perceive and accept risk more than their nonentrepreneurial counterparts;
they are simply predisposed to access categories that suggest more potential, on balance,
when they assess business scenarios. Assuming rational behavior, this should naturally lead
entrepreneurs to pursue potential enterprises that others would reject.
Decision Dimensions
Perhaps the most well-recognized framework for an overview of the strategic situation of
an enterprise is what has come to be called "SWOT Analysis" (Thompson and Stricldand
1992). This approach considers four dimensions that underlie that assessment: internal
strengths and weaknesses and external opportunities and threats. We incorporated these
dimensions into the present study as they have already been established and justified in the
literature and in similar research (cf. Dutton and Jackson 1987; Gooding 1989) and because
they provide a concise summary of business situations. Strengths and opportunities are positive
attributes, whereas weaknesses and threats represent negative dimensions. Strengths and
weaknesses are internal characteristics of a frame, whereas opportunities and threats are
external orientations. Each of the above pairs represents an opposing frame which is similar
but not overlapping in terms of cognitive framing. Nonetheless, both pairs are complementary.
Given the general optimism with which entrepreneurs regard business situations (Cooper et
al. 1988), we also included a measure for optimism/pessimism in the study. This measure
required respondents to record their projections of potential venture performance in terms
of improvement versus deterioration (cf. Gooding 1989).
SPECIFIC HYPOTHESES
To restate our central thesis, although entrepreneurs are widely considered to be risk-takers,
their business-related behaviors may be the result of their unique perceptions from systematic
differences in cognitive processes, not a desire to pursue ventures because they are risky
per se. Therefore, their propensity for risk should be no different from that of nonentrepreneurs, even though their perceptions of the differences in internal strengths and weaknesses,
external opportunities and threats, and performance improvement versus deterioration will be
skewed toward optimism (Cooper et al. 1988). To test this cognitive theory of entrepreneurial
perceptions, we developed the following four hypotheses:
H I : There will be no difference in risk propensity between entrepreneurs and
nonentrepreneurs. 1
H2: When presented with identical situations, entrepreneurs will categorize them
as having more strengths (versus weaknesses) than nonentrepreneurs.
1-13: When presented with identical situations, entrepreneurs will categorize them
as having more opportunities (versus threats) than nonentrepreneurs.
~Our theory suggests that entrepreneurs do not see themselves as having any greater risk propensity than
nonentrepreneurs-they simply frame business situations as more positive and opportunity-laden. That is, our
position would only be consistent with nonsignificant findings on this hypothesis; therefore, we have stated it in
its null form.
430
L.E. PALICH AND D.R. BAGBY
H4: When presented with identical situations, entrepreneurs will categorize them
as having more potential for gain (versus loss) than nonentrepreneurs.
METHODS
Subjects
Samples for the study were derived from a 2,500 member business organization. The purpose
of the association was to provide a context for networking between entrepreneurs and potential
sources of support resources (i.e., nonentrepreneurs such as bankers, managers, and venture
capitalists). The study used a random sample of 548 members of the organization. Initially
we mailed subjects a four-page questionnaire along with a cover letter that revealed only
that we were studying decision-making processes of members of the business community.
In cases of nonresponse, we sent as many as two follow-up letters (with questionnaires
enclosed) to maximize returns (cf. Dillman 1977). In all, 148 members responded to the
survey for a favorable 27 % response rate. Of the returned surveys, 92 contained responses
to all parts of the instrument and were therefore included in the analysis.
Scenario Development
In order to measure cognitive categorization characteristics, we presented each respondent
with the same stimuli and recorded variations in their responses. The stimuli consisted of a
series of three scenarios with embedded ambiguous data regarding three issues-technological
developments, changes in the competitive environment, and the trend toward internationalization (see the Appendix for a sample of these scenarios). These were adapted from Dutton
and Jackson's (1987) equivocal scenarios describing a fictitious bank, which we changed to
a clothing retailer, J. J. Long and Co. The information paralleled that of the original scenarios.
MEASURES
Entrepreneur versus Nonentrepreneur
In order to make comparisons between entrepreneurs and nonentrepreneurs, it was necessary
to divide respondents into these two groups. We achieved this via a sorting exercise conducted
by a panel of three entrepreneurship experts, two of whom serve on the faculty of a graduate
business school while the third was a practitioner highly familiar with entrepreneurs and
their firms. Based upon a common entrepreneur profile emphasizing the founding of new
ventures, the creation of new innovations, and aspirations for rapid enterprise growth and
high profitability (cf. d'Amboise and Muldowney 1988), panel members assigned subjects
to the two groups according to their responses to eight survey questions that captured this
information (e.g., items to measure new venture involvement, priority of goals for rapid
growth and high profitability for the respondent's enterprise, and revenue growth projections).
Agreement among these experts was high (exact agreement more than 87% of the time); all
split assessments were decided by assignment majority.
Risk Propensity
We used a scale developed and validated by Gomez-Mejia and Balkin (1989) to measure
each respondent's level of risk propensity. We asked subjects to respond to each of four
COGNITIVETHEORYAND RISK-TAKING 431
TABLE 1 Descriptive Statistics and Correlationsa
Variables
Mean
SD
1
2
3
4
1.
2.
3.
4.
5.
1.62
5.84
1.09
1.45
1.07
0.49
0.92
1.26
1.71
1.36
- 0.04
-0.25 b
-0.20
-0.38 d
0.14
0.11
0.10
0.23 b
0.68 d
.46 d
Group
Risk propensity
Strengths/Weaknesses
Opportunities/Threats
Improve/Deteriorate
a N = 92.
b p < .05.
c p < .01.
d p < .001.
items using a seven-point Likert-type scale ranging from strongly agree to strongly disagree.
With a Cronbach's alpha of 0.67, this scale exhibited acceptable reliabilities (cf. Nunnally
1978). Results of our factor analysis of the scale yielded support for its unidimensionality.
For example, analysis of the scree-plot (the most reliable indicator of factor structure: Cattell
1966; Kim and Mueller 1978) demonstrated that a one-factor solution was appropriate.
Perceptual Measures
Subjects responded to three items after reading each of the scenarios. These items measured
their perceptions of the relative levels of the scenario firm's (1) internal strengths versus
weaknesses, (2) external opportunities versus threats, and (3) the potential for increases
versus decreases in future performance (cf. Gooding 1989). These were nine-point Likert-type
scales running from strengths (4) to weaknesses (-4), opportunities (4) to threats (-4), and
improve (4) to deteriorate (-4), respectively.
Analyses
A MANOVA design was used to assess whether entrepreneurs and nonentrepreneurs differed
significantly in their perceptions of strengths, weaknesses, opportunities, threats, and prospects for performance improvement or deterioration2-all of these taken jointly. We then
used univariate tests (separate ANOVAs) to look at each of these attributes in isolation. The
results of these analyses reveal whether entrepreneurs differ from others overall in their
cognitive responses to identical business information (scenarios). Then the univariate tests
detect specific dimensions across which these two groups may differ.
RESULTS
As a further check of interrater reliability, we ran all analyses using the entire sample and
then using only those cases which the panel sorted with 100% agreement. In all analyses,
these follow-up tests replicated the results found using the entire sample. To augment our
analyses, Table 1 reveals the means, standard deviations, and correlations for all of the
variables used in the study. The strongest correlation among the variables was 0.68 (that
between perceived strengths/weaknesses and performance deterioration/improvement).
Overall, the strongest correlations involved the improve/deteriorate variable.
2 The analysis entered each o f these variables using the respondent's m e a n assessment across all three scenarios.
432
L.E. PALICH AND D.R. BAGBY
TABLE 2
Results of A N O V A C o m p a r i n g Risk Propensity for Entrepreneurs and Nonentrepreneurs
Group
N
Mean Risk Propensity
Entrepreneurs
Nonentrepreneurs
F
35
57
5.89
5.81
0.16 NS
Risk Propensity
According to cognitive theory as applied to perceptions of business situations, entrepreneurs
tend to frame these scenarios more favorably than others. However, we theorize that they
will not be any more predisposed to accept risk than nonentrepreneurs (i.e., they will have
the same risk propensity). To test this notion we compared differences in responses to GomezMejia and Balkin's (1989) risk propensity scale across groups using a one-way ANOVA.
This test demonstrated that the difference between mean responses (see Table 2) for entrepreneurs and nonentrepreneurs was far from significant: F(1, 90) : 0.16, NS. Thus, we cannot
reject H1, a finding that is consistent with our revised view of entrepreneurs. 3
Responses to S c e n a r i o s
To test the main hypotheses of the study, a one-way MANOVA assessed differences between
entrepreneurs and nonentrepreneurs. A significant multivariate effect indicates that the vectors
of mean scores (across all dependent variables) for the two groups are statistically different.
Further, this effect is a necessary precondition before conducting univariate comparisons
(Dillon and Goldstein 1984; Hair, Anderson, and Tatham 1987; Stevens 1986). As reported
in Table 3, the results of our MANOVA test (Multivariate F[3,86] = 4.79, p < .01) indicated
that entrepreneurs significantly differed from nonentrepreneurs across all perceptual measures
TABLE 3
Results o f Multivariate and Univariate Analyses
Variables
N
Mean Scores
Multivariate Model
Strengths/Weaknesses
Entrepreneurs
Nonentrepreneurs
Opportunities/Threats
Entrepreneurs
Nonentrepreneurs
Improve/Deteriorate
Entrepreneurs
Nonentrepreneurs
Wilkes
Lambda
0.86
35
55
1.48
0.84
35
55
1.89
1.18
35
55
1.71
0.67
F
Rz
4.79 b
5.75"
0.06
3.80 ~
0.04
14.58 c
0.14
° p < .05.
~'p < .0l.
' p < .001.
3We measured the statistical power of our test to determine whether the probability of Type II error was
within acceptable limits. Following the prescription of Cohen and Cohen (1983), we assumed a medium effect size
of r = 0.30. We then used their tables to determine the power of our test, using an alpha of 0.05 and our sample
size (n = 92). Power was calculated to be .83, which exceeds the .80 threshold established by Cohen (1988).
Therefore, it appears that our test had sufficient power to minimize the probability of Type II error.
COGNITIVE THEORY AND RISK-TAKING
433
taken together-strengths versus weaknesses, opportunities versus threats, and improvement
versus deterioration in future performance. 4
Table 3 also presents group differences from univariate tests. First, the mean response
for entrepreneurs on strengths versus weaknesses was higher than for nonentrepreneurs (i.e.,
entrepreneurs perceived greater strengths relative to weaknesses), and this difference is significant: F = 5.75 (1, 88), p < .05. In other words, compared to others, entrepreneurs
perceive that the firm has greater internal capabilities and fewer weaknesses, even when
responding to the same business scenario (supporting H2). Cognitive theory suggests that
the accessed schema may be characterized by more favorable internal assessments.
Differences between perceptions of opportunities versus threats were also significant:
F (1,88) = 3.80, p < .05. These results indicate that in contrast to other business people,
entrepreneurs tend to perceive the firm's environment as holding more opportunities or external potentials to be exploited and fewer threats against which to guard. This, too, is consistent
with cognitive theory. That is, responding to the same business situation, entrepreneurs will
associate the firm with a schema suggesting positive environmental attributes. This provides
support for H3.
Extending beyond the SWOT framework, we also measured subjects' perceptions of
the firm's potential for future performance. Again, after reviewing the same business scenario,
entrepreneurs were more optimistic about the future of the hypothetical firm than were
nonentrepreneurs, and the difference was significant: F (1,88) = 14.57, p < .001. This is
consistent with categorization theory (as posited in H4) and with previous empirical findings
(e.g., Cooper et al. 1988).
DISCUSSION
Most definitions of an "entrepreneur" emphasize the risk propensity of these unique individuals. That is, they are usually described as risk-takers who attempt to achieve fast enterprise
growth and above-average profits (d'Amboise and Muldowney 1988). In accord with cognitive
theory, we averred that entrepreneurs may not actually prefer to take risks; rather, due to
schema accessibility, they simply tend to associate business situations with cognitive categories that suggest more favorable attributes (greater strengths versus weaknesses, opportunities
versus threats, and potential for future performance improvement versus deterioration). In
other words, entrepreneurs are more likely to see the business world through "rose-colored
glasses." This optimistic outlook has been documented in previous research (e.g., Cooper
et al. 1988).
Two conditions are necessary to support the theory of entrepreneurial perceptions outlined previously: first, entrepreneurs must not report any greater risk propensity than their
nonentrepreneurial counterparts, and second, they must generally associate business situations
with more positive cognitive structures. Our comparison of entrepreneur and nonentrepreneur
samples satisfied both of these conditions. That is, these two groups did not differ significantly
in their responses to Gomez-Mejia and Balkin's (1989) risk propensity scale. At the same time
our findings suggest that entrepreneurs tend to derive more positive/optimistic perceptions,
compared to others, when presented with identical business scenarios. Both MANOVA and
univariate tests confirmed that the former perceived greater internal strengths (versus weak4Follow-up analyses indicated that these results were robust across all scenarios (representing three different
issues). That is, we ran MANOVAs using data from each scenario taken separately, and these also demonstrated
significant multivariate differences between entrepreneurs and nonentrepreneurs (p < .05).
434
L.E. PALICH AND D.R. BAGBY
nesses), external opportunities (versus threats), and potential for improvement in future
performance (versus deterioration). These are all consistent with cognitive theory and previous findings (e.g., Cooper et al. 1988). When an entrepreneur pursues an activity that would
be ignored or neglected by a nonentrepreneur, it may be due to the entrepreneur's perception
of a positive outcome rather than to differences in predisposition toward risk.
Implications
Because cognitive theory provides a cogent explanation for entrepreneurial and nonentrepreneurial behavior, several implications follow for academics and practitioners. In line with
previous research in cognitive processes, our findings suggest that people do indeed use
simplified cognitive processes when they form perceptions (Lord and Maher 1990). Unfortunately, categorizations often lead to serious distortions in the processing of information (Lord
and Maher 1991; Mount and Thompson 1987; Slusher and Anderson 1987; Sulsky and
Day 1992). As applied to entrepreneurship, this can lead to two potential biases-excessive
optimism (by entrepreneurs) or pessimism (by nonentrepreneurs). In effect, the former may
underestimate the riskiness of their enterprises while the latter may overlook promising
ventures by inflating estimated venture risk through inaccurate impressions. Either extreme
yields less than optimal business decisions.
When observations are consistent with expectations or the mental prototype of the perceiver, the categorization process tends to operate automatically (Mount and Thompson
1987) and often increases the inaccuracy of subsequent recall (Lord and Maher 1991). Thus
entrepreneurs and nonentrepreneurs alike may benefit from training that provides a framework
to identify the critical dimensions of assessment and to understand how to accurately appraise
business situations according to those important attributes (Mount and Thompson 1987).
Sulsky and Day (1992) used such an approach (i.e., "frame of reference" training) to improve
the accuracy of the ratings of performance raters. The objective of this training is to increase
the frequency of correct categorizations. Though the success of Sulsky and Day's (1992)
intervention may be duplicated for those assessing potential business opportunities, this effort
must overcome resistance from assessors who lack the motivation to adopt a new framework
or have difficulty mastering new prototypes (Fiske and Dyer 1985).
A more positive view of our findings may recommend a different approach. That is,
entrepreneurs may be best distinguished from others according to their cognitive tendencies
(Shaver and Scott 1991). This may be particularly useful given the shortcomings of other
streams of research (especially trait studies) that have endeavored to identify the differentiating
qualities of entrepreneurs. Further, understanding the phenomenon of entrepreneurship on
a cognitive level may pave the way for more efficacious pedagogy for use in entrepreneurship
programs in educational and governmental environments, enhancing the business assessment
skills of these individuals. Finally, systematic differences in cognitive processes may help
to distinguish high growth entrepreneurs from those interested in lifestyle enterprises, which
would be useful because these groups often cannot be divided based upon firm size (i.e.,
both tend to be associated with smaller enterprises). This may also help to identify small
business owners who have greater potential to identify opportunities and expand their operations rapidly in a way that typifies entrepreneurial concerns.
L I M I T A T I O N S AND F U T U R E R E S E A R C H
As with all research, this study is subject to certain limitations. For example, we examined
evidence for categorization processes that follow immediately after reviewing business scenar-
COGNITIVETHEORY AND RISK-TAKING 435
ios. This approach fails to consider distortions that may occur only after a certain interval
of time has lapsed. Detection of these delayed effects must await future research that adopts
alternate study designs. Heuristics such as those related to availability, representativeness,
or anchoring were not considered in the current design either. Also, what we actually assessed
in this study were outcomes of cognitive processes, not the processes themselves. Future
research should incorporate direct observation of subjects while they make decisions in order
to gather more revealing information regarding cognitive processes.
Like most survey research, our achieved response rate was less than ideal. Although
it was consistent with that of most reported research in the field, we must acknowledge the
potential for response bias and resist making strong conclusions from the data. The sample
also was drawn from a limited geographical area, calling for caution when generalizing the
results to other populations. Clearly, more research would be helpful in order to expand our
sample.
Further, we examined only equivocal business scenarios. It is possible that responses
from both entrepreneurs and others will vary when exposed to situations that are skewed
toward either positive or negative frames. As a first step, our exploratory study used only
equivocal scenarios to assess intergroup differences in responses. Given our significant findings, a next step may require more varied stimuli. This would demonstrate whether entrepreneurs are more sensitive to different types of information.
Finally, we recognize that human perceptions are prone to distortion due to the cognitive
limitations of observers (Mount and Thompson 1987). However, elimination of the biases
we examined in this study nonetheless would not guarantee accurate assessments. Further
complicating this problem, it is impossible to get true (i.e., unquestionably valid) measures
of a firm's strengths, weaknesses, opportunities, threats, and potential for future performance.
Therefore, researchers cannot know with certainty the quality of an individual's assessment
of these dimensions.
In addition to the research directions implied previously, we have others to recommend.
For example, some researchers (cf. Gartner 1985; Wortman 1987) have suggested that entrepreneurs may be as different from one another as they are from the rest of the population.
Therefore, assessing cognitions may provide a method to differentiate between high growth
and life style entrepreneurs, among others. A taxonomy of entrepreneurs could enhance
research efforts in the field. At present, the most popular operational definition of an entrepreneur appears to be the founding of new ventures, but individuals start firms for different
reasons. Cognitive styles may present a means by which these groups can be differentiated.
As suggested by our findings, we are convinced that cognition affects entrepreneurship.
However, the role that experience and other such factors play in shaping the selection of
various decision frames begs exploration. For example, do successful entrepreneurs adjust
their frames as the venture grows? Do unsuccessful entrepreneurs maintain a chronic frame
in spite of changing conditions? Do success and failure impact cognitive processes? These
and other questions will simply remain unanswered for now, awaiting the illumination of
future research.
Nonetheless, our findings suggest that entrepreneurs do indeed operate by a unique set
of cognitive processes, thereby supporting their documented optimism. Gordon Allport (1954,
p. 172) contended that a"principle of least effort inclines us to hold coarse and early generalizations as long as they can possibly be made to serve our purposes." By this logic, entrepreneurs
may be inclined to offer positive/optimistic assessments of business scenarios since they are
constantly searching for new ventures (Kirzner 1973). It stands to reason that those who
seek opportunity are most likely to find it.
436
L.E. PALICH AND D.R. BAGBY
APPENDIX
Sample Scenario (Technological Developments)
Interviews with top- and middle-level managers have revealed the following industry trends. There
are many new technological developments that will affect the future of J.J. Long and Co. These
developments have potential for a wide range of retailing activities. For example, cash and personal
checks will no longer be the dominant means of payments used by customers in the future. Technological
breakthroughs have increased the convenience and therefore the use of credit cards, debit cards, and
other electronic transfers. J.J. Long and Co. may be able to make some gains here, but in any case,
they are unlikely to lose much.
REFERENCES
Allport, G.W. 1954. On the Nature of Prejudice. Reading, MA: Addison-Wesley.
Anderson, J.R. 1991. The adaptive nature of human categorization. Psychological Review 98(3):409429.
Brockhaus, R.H. 1980. Risk taking propensity of entrepreneurs. Academy of Management Journal
23(3):509-520.
Brockhaus, R.H., and Horwitz, P.S. 1986. The psychology of the entrepreneur. In D.L. Sexton and
R.W. Smilor, eds., The Art and Science of Entrepreneurship. Cambridge, MA: Ballinger.
Bruner, J.S. 1957. On perceptual readiness. Psychological Review 64(1):123-152.
Cantillion, R. [1755] 1964. Essai Sur la Nature du Commerce en General. New York: Augustus M.
Kelley.
Cattell, R.B. 1966. Handbook of Multivariate Experimental Psychology. Chicago: Rand McNally.
Cohen, J. 1988. Statistical Power Analysis for the Behavioral Sciences. Hillsdale, NJ: Lawrence
Erlbaum Associates.
Cohen, J., and Cohen, P. 1983. Applied Multiple Regression~Correlation Analysis for the Behavioral
Sciences. Hillsdale, NJ: Lawrence Erlbaum Associates.
Corter, J.E., and Gluck, M.A. 1992. Explaining basic categories:feature predictability and information.
Psychological Bulletin 111(2):291-303.
Cooper, A.C., Woo, C.Y., and Dunkelberg, W.C. 1988. Entrepreneurs' perceived chances for success.
Journal of Business Venturing 3(1):97-108.
d'Amboise, G., and Muldowney, M. 1988. Management theory for small business: attempts and requirements. Academy of Management Review 13(2):226-240.
Dillman, D.A. 1977. Mail and Telephone Surveys. New York: Wiley.
Dillon, W.R., and Goldstein, M. 1984. Multivariate Analysis: Methods and Applications. New York:
Wiley.
Dutton, J.E., and Jackson, S.E. 1987. Categorizing strategic issues: links to organizational action.
Academy of Management Review 12(1 ): 76-90.
Fiske, S.T., and Dyer, L.M. 1985. Structure and development of social schemata: evidence from
positive and negative transfer effects. Journal of Personality and Social Psychology 48(6): 839852.
Fiske, S.T., and Linville, P.W. 1980. What does the schema concept buy us? Personality and Social
Psychology Bulletin 6(4):543-557.
Fiske, S.T., and Taylor, S.E. 1984. Social Cognition. Reading, MA: Addison-Wesley.
Gartner, W.B. 1985. A conceptual framework for describing the phenomenon of new venture creation.
Academy of Management Review 10(4):596-606.
Gomez-Mejia, L.R., and Balkin, D.B. 1989. Effectiveness of individual and aggregate compensation
strategies. Industrial Relations 28(3):431-445.
COGNITIVE THEORY AND RISK-TAKING 437
Gooding, R.Z. 1989. Decision framing and the structuring of strategic problems. Paper presented at
the Working Conference on Managerial Cognition, Washington, D.C.
Hair, J.F., Anderson, R.E., and Tatham, R.L. 1987. Multivariate Data Analysis. New York: Macmillan.
Higgins, E.T., and King, G.A. 1981. Accessibility of social constructs: information-processing consequences of individual and contextual variability. In N. Cantor and J.F. Kihlstrom, eds., Personality, Cognition, and Social Interaction. Hillsdale, NJ: Erlbaum.
Kahneman, D. 1992. Reference points, anchors, norms, and mixed feelings. Organizational Behavior
and Human Decision Processes 51 (2):296-312.
Kahneman, D., and Tversky, A. 1987. Judgment under Uncertainty: Heuristics and Biases. New York:
Cambridge University Press.
Kim, J., and Mueller, C.W. 1978. Factor Analysis: Statistical Methods and Practical Issues. Beverly
Hills: Sage.
Kirzner, I.M. 1973. Competition and Entrepreneurship. Chicago: University of Chicago Press.
Knight, F.H. 1921. Risk, Uncertainty, and Profit. New York: Kelly and Millman, Inc.
Komatsu, L.K. 1992. Recent views of conceptual structure. Psychological Bulletin 112(4):500-526.
Krueger, J., Rothbart, M., and Sriram., N. 1989. Category learning and change: differences in sensitivity to information that enhances or reduces intercategory distinctions. Journal of Personality
and Social Psychology 56(6):866-875.
Lord, R.G., and Maher, K.J. 1990. Alternative information-processing models and their implications
for theory, research, and practice. Academy of Management Review 15(1):9-28.
Lord, R.G., and Maher, K.J. 1991. Cognitive theory in industrial and organizational psychology. In
M.D. Dunnette and L.M. Hough, eds., Handbook oflndustrial and Organizational Psychology.
Palo Alto, CA: Consulting Psychologists Press.
Low, M.B., and MacMillan, I.C. 1988. Entrepreneurship: past research and future challenges. Journal
of Management 14(2): 139-161.
McClelland, D.C. 1961. The Achieving Society. Princeton, NJ: Van Nostrand.
Mervis, C.B., and Rosch, E. 1981. Categorization of natural objects. Annual Review of Psychology
32(1):89-115.
Mount, M.K., and Thompson, D.E. 1987. Cognitive categorization and quality of performance ratings.
Journal of Applied Psychology 72(2):240-246.
Nunnally, J.C. 1978. Psychometric Theory. New York: McGraw-Hill.
Rosch, E. 1975. Cognitive reference points. Cognitive Psychology 7(4):532-547.
Rosch, E. 1978. Principles of categorization. In E. Rosch and B. Lloyd, eds., Cognition and Categorization. Hillsdale, NJ: Erlbaum.
Rosch, E., Mervis, C., Gray, W., Johnson, D., and Boyes-Graem, P. 1976. Basic objects in natural
categories. Cognitive Psychology 8(3):382-489.
Schumpeter, J. 1934. The Theory of Economic Development. Boston: Harvard University Press.
Shaver, K.G., and Scott, L.R. 1991. Person, process, choice: the psychology of new venture creation.
Entrepreneurship, Theory, and Practice 16(2):23-45.
Slusher, M.P., and Anderson, C.A. 1987. When reality monitoring fails: the role of imagination in
stereotype maintenance. Journal of Personality and Social Psychology 52(5):653-662.
Stevens, J. 1986. Applied Multivariate Statistics. Hillsdale, NJ: Lawrence Earlbaum Associates.
Sulsky, L.M., and Day, D.V. 1992. Frame-of-reference training and cognitive categorization: an
empirical investigation of rater memory issues. Journal of Applied Psychology 77(4):501-510.
Thompson, A.A., and Strickland, A.J. 1992. Strategic Management. Homewood, IL: Irwin.
Tulving, A., and Pearlstone, Z. 1966. Availability versus accessibility of information in memory for
words. Journal of Verbal Learning and Verbal Behavior 5(3):381-391.
Tversky, A., and Kahneman, D. 1992. Advances in prospect theory: cumulative representation of
uncertainty. Journal of Risk and Uncertainty 5(2):297-323.
Van de Ven, A.H., Hudson, R., and Schroeder, D.M. 1984. Designing new business start-ups: entrepreneurial, organizational, and ecological considerations. Journal of Management 10(1): 87-107.
438
L.E. PALICH AND D.R. BAGBY
Vesper, K.H. 1980. New Venture Strategies. Englewood Cliffs, NJ: Prentice-Hall.
Weick, K.E. 1979. The Social Psychology of Organizing. New York: Random House.
Wofford, J.C. 1994. An examination of the cognitive processes used to handle employee job problems.
Academy of Management Journal 37(1): 180-192.
Wortman, M.S. 1987. Entrepreneurship: an integrating typology and evaluation of empirical research
in the field. Journal of Management 13(2):259-279.
本文献由“学霸图书馆-文献云下载”收集自网络，仅供学习交流使用。
学霸图书馆（www.xuebalib.com）是一个“整合众多图书馆数据库资源，
提供一站式文献检索和下载服务”的24 小时在线不限IP 图书馆。
图书馆致力于便利、促进学习与科研，提供最强文献下载服务。
图书馆导航：
图书馆首页
文献云下载
图书馆入口
外文数据库大全
疑难文献辅助工具