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DOES ENTREPRENEURIALSELF-EFFICACY

DISTINGUISH

ENTREPRENEURS FROM

MANAGERS?CHAO C. CHEN

Rutgers University

PATRICIA GENE GREENERutgers University

ANN CRICKRutgers University

EXECUTIVESUMMARY

Previous research on the psychology of entrepreneurs found that personality

traits such as locus of control failed to distinguish entrepreneurs from man-

agers. In search of an individual characteristic that is distinctively entrepre-

neurial, we proposed an entrepreneurial self-efficacy construct (ESE) to pre-

dict the likelihood of an individual being an entrepreneur. ESE refers to the

strength of a persons belief that he or she is capable of successfully per-

forming the various roles and tasks of entrepreneurship. It consists of five factors: marketing, innovation,

management, risk-taking, and financial control.

We conducted two studies, one on students and the other on small business executives. Study 1 found

that the total ESE score differentiated entrepreneurship students from students of both management and

organizational psychology, and that across the three types of students, ESE was positively related to the

intention to set up ones own business. We also found the entrepreneurship students to have higher self-

efficacy in marketing, management, and financial control than the management and psychology students.

In study 2, we simultaneously tested effects of ESE and locus of control on the criteria of founders vs.

nonfounders of current businesses. After controlling for individual and company background variables,

Address correspondence to Dr. C.C. Chen, Rutgers University, Faculty of Management, 81 New Street, New-

ark, NJ 07102.The authors thank Fred Dansereau and John Miner for comments on earlier versions of this article. Thanks

also to Hui-yuan Liao and Terrence Brown for assistance in the project. This research was supported in part by aresearch grant from the Research Resources Committee of the Faculty of Management at Rutgers University.

Journal of Business Venturing 13, 2953161998 Elsevier Science Inc. All rights reserved. 0883-9026/98/$19.00655 Avenue of the Americas, New York, NY 10010 PII S0883-9026(97)00029-3

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296 C.C. CHEN ET AL.

the effect of ESE scores was significant, but the effect of locus of control was not. More specifically, it was

found that business founders had higher self-efficacy in innovation and risk-taking than did nonfounders.

The results of this study demonstrate the potential of entrepreneurial self-efficacy as a distinct char-

acteristic of the entrepreneur. From these results, some important implications can be drawn on entrepre-

neurial assessment, education, counseling, andcommunity intervention. First, ESEcan be used to identify

reasons for entrepreneurial avoidance. There may be many individuals who shun entrepreneurial activi-

ties not because they actually lack necessary skills but because they believe they do. This is especially

true for sectors of the population such as women or those minority groups who are perceived as lacking

entrepreneurial traditions. Communities and individuals could benefit from identifying sources of entre-

preneurial avoidance by targeting their efforts toward enhancing ESE of particular groups or individuals

for specific aspects of entrepreneurship.

An additional use of ESE is to identify areas of strength and weakness to assess the entrepreneurial

potential of both an individual and a community. Once entrepreneurial potential is identified, resources

can be channeled and more effectivelyused to promote entrepreneurship. Finally, diagnosis and treatment

of ESE can be performed on real entrepreneurs. The entrepreneur may be completely avoiding, or per-

forming less frequently, certain critical entrepreneurial activities because s/he lacks self-efficacy. For ex-

ample, the entrepreneur may be avoiding company growth for fear of losing control. Identification and

removal of self-doubt will enable the entrepreneur to be actively engaged in entrepreneurial tasks, more

persistent in the face of difficulty and setbacks, and more confident in meeting challenges.

Overall, ESE is a moderately stable belief and requires systematic and continuous efforts to be

changed. Two broad approaches can be taken toward desired change. One is the micro-approach that

directly focuses on peoples beliefs. In designing and conducting entrepreneurship courses, training insti-

tutions should not just train students in critical entrepreneurial skills and capabilities but also strengthen

their entrepreneurial self-efficacy. The current state of entrepreneurship courses in most management

schools may fall short in both respects. Courses focus on commonly identified management skills, but

often ignore entrepreneurial skills such as innovation and risk-taking. Furthermore, the teaching of entre-

preneurial skills tends to be technical, with insufficient attention paid to the cognition and belief systems

of the entrepreneur. Educators should take into account entrepreneurial attitudes and perceptions when

designingor assessing their course objectives. Conscious efforts could be made to enhance ESE by involv-

ing the students in real-life business design or community small business assistance, by inviting success-

ful entrepreneurs to lecture, and by verbal persuasion from the instructor and renowned entrepreneurs.

The second approach to enhancing ESE is to work on the environment of potential and actual

entrepreneurs. According to the reciprocal causation model, the environment may affect self-efficacy not

only directly but also indirectly through performance. An environment perceived to be more supportive

will increase entrepreneurial self-efficacy because individuals assess their entrepreneurial capacities in

reference to perceived resources, opportunities, and obstacles existing in the environment. Personal effi-

cacy is more likely to be developed and sustained in a supportive environment than in an adverse one.

A supportive environment is also more likely to breed entrepreneurial success, which in turn further en-

hances entrepreneurial self-efficacy. Communities can work toward creating an efficacy enhancing envi-

ronment by making resourcesboth available and visible, publicizing entrepreneurial successes, increasing

the diversity of opportunities, and avoiding policies that create real or perceived obstacles. 1998 Else-

vier Science Inc.

INTRODUCTION

There is an increasing emphasis on the role of self-efficacy in the study of entrepreneur-ship, including areas such as entrepreneurial career preferences, intentionality, and per-formance (Boyd and Vozikis 1994; Chandler and Jansen 1992; Gartner 1989; Krueger

and Brazeal 1994; Scherer et al. 1989). Self-efficacy is an individuals cognitive estimateof his or her capabilities to mobilize the motivation, cognitive resources, and coursesof action needed to exercise control over events in their lives (Wood and Bandura

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SELF-EFFICACY AND ENTREPRENEURS VS. MANAGERS 297

1989). One important effect of self-efficacy is on the choice of behavior settings. Individ-uals tend to choose situations in which they anticipate high personal control but avoidsituations in which they anticipate low control (Bandura 1977b, 1982; Bandura andSchunk 1981; Wood and Bandura l989). Accordingly, to the extent that people plan

and choose their career paths, they assess their personal capabilities against the require-ments of different occupations. This assessment of their personal capabilities thereforedirects people to prepare for and enter occupations in which they feel efficacious butavoid occupations in which they feel a lack of competence (Betz and Hackett 1981, 1986;Miura 1987; Scherer et al. 1989).

Starting ones own business or initiating a new venture is often described as a pur-posive and intentional career choice (e.g., Bird 1988; Katz and Gartner 1988). Althoughthere can be a wide variety of contextual as well as individual factors that influence theentrepreneurial choice, the role of entrepreneurial self-efficacy has been emphasizedas a key antecedent (Boyd and Vozikis 1994; Krueger and Brazeal 1994). Boyd and

Vozikis (1994) explicitly proposed that entrepreneurial self-efficacy affects entrepre-neurial career choice and development. However, so far no empirical research has beenreported that tests this hypothesis. In the current research, we explored whether entre-preneurial self-efficacy distinguishes those who pursue, or intend to pursue, a careerof owning and running their own businesses from those who do not. Specifically, weconducted two surveys: one on students to examine whether entrepreneurial self-effi-cacy affected entrepreneurial intentionality and the other on small business executivesto examine whether it distinguished entrepreneurs from managers.

Because the theoretical foundation of our research question lies in the self-efficacyliterature, we first review some of the pertinent conceptual and measurement issues

regarding self-efficacy. We then further develop the concept of entrepreneurial self-efficacy and its relationship to the entrepreneurial decision based on authors from thefield of entrepreneurship.Finally, we report our study and discuss theoretical and practi-cal implications.

SOME CONCEPTUAL AND MEASUREMENT

ISSUES OF SELF-EFFICACY

Self-efficacy is a central construct in Banduras social learning theory (1977a, 1982;

Wood and Bandura 1989). There have been extensive discussions of self-efficacy andits implications for management and entrepreneurship (e.g., Gist 1987; Boyd and Voz-ikis 1994; Wood and Bandura 1989). Although it is beyond the scope of this paper tosystematically delineate the construct, we address some of the salient issues pertinentto our current research.

Reciprocal Causation of Self-efficacy and Performance

Bandura (1977b, 1986) distinguishes his social learning theory from many traditionalpsychological theories by emphasizing reciprocal causation among cognition, behavior,

and environment. Whereastraditional unidirectional theories depict human behavior ascaused either by environmental events or internal dispositions, social learning theoriesexplain human behavior in terms of triadic reciprocal causation among behavior (B),

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FIGURE 1 Relations among behavior (B), cognition (C), and environment (E).

cognitive and other personal factors (C), and environment events (E) (Figure 1). Eachof the three factors affects and is affected by the other two. For example, on the one

hand, a persons action can change his or her environment as well as the way he or sheviews self and environment; on the other hand, the environment and his or her percep-tions of self and the environment can also change his or her behavior. At a particulartime, however, different sources of influences may have more or less of an effect, andreciprocal influences do not occur simultaneously (Wood and Bandura 1989).

The notion of reciprocal causation is important in understanding self-efficacy andits determinants and effects. For instance, research on the effects of self-efficacy (e.g.,Bandura 1977b, 1982, 1986; Bandura and Schunk 1981; Wood and Bandura 1989) foundthat self-efficacy is the most effective predictor of performance. People with high self-efficacy have more intrinsic interest in the tasks, are more willing to expend their effort,

and show more persistence in the face of obstacles and setbacks. As a result, they per-form more effectively. Performance and performance accomplishments are not just theoutcome of self-efficacy, they are also the determinants of self-efficacy. Performanceaccomplishments are found to be the most influential in shaping and estimating onesself-efficacy.1 Individuals monitor and assess their own performance to formulate andadjust their own sense of self-efficacy. Performance and self-efficacy therefore form acycle of mutual reinforcement. Self-efficacy affects performance through interest, moti-vation, and perseverance, whereas performance provides feedback information, on thebasis of which self-efficacy is further evaluated and modified.

It should be noted that research has consistently shown that even though thereis a positive correlation between self-efficacy and performance accomplishment, self-efficacy is a better predictor than past performance/experience for future performance(Bandura 1982, 1986). This is because, first, there are sources other than past perfor-mance that affect the persons self-efficacy. Second, it is the attribution of performancerather than the objective performance per se that affects peoples self-efficacy. Low self-efficacy may persist at times of success if external attributions (e.g., chance) are made,the same for high self-efficacy at times of failure. It is possible that even with objectivelysimilar abilities and experiences, people may still develop different levels of self-efficacy.

1The other three major sources of self-efficacy in the order of influence next to performance are vicari-ous experience (learning through role models), verbal persuasions (e.g., being told one is good), and physio-logical arousal (such as feeling fatigue).

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Level of Specificity

Students of self-efficacy frequently view the specificity of the construct as an advantageboth conceptually and for predicting and influencing behavior (Bandura l982; Gist 1987;Wood and Bandura 1989). However, we argue that it is the relative rather than the abso-

lute level of specificity that distinguishes self-efficacy from other constructs, and self-efficacy of different types of tasks can vary in the levels of specificity. In the following,we first compare specificity of self-efficacy with that of other similar constructs and thendiscuss how specificity is relevant to the target of behavior domains.

Expectancy Theory and Self-Efficacy

Self-efficacy is often compared with expectancy theory. Expectancy theory is also cogni-tive and is based on two estimates (expectations). One is of the probability that effortwill lead to a performance level (E1); the other is the probability that performance will

lead to an outcome (E2). Clearly, self-efficacy is concerned with the execution of anaction, not its outcome (E2). However, there are apparent similarities between El andself-efficacy. Both are self-assessments of peoples own abilities and are concerned withperformance. Yet, whereas E1 is exclusively about effort, self-efficacy is about all theinternal factors that bear influence on the execution of actions. Self-reflection and as-sessment of personal efficacymay be greater in scope anddepth. For instance, as pointedout by Bandura (1984), self-efficacy may involve assessing coping abilities under stressor even the very motivational state that El takes as given. A low E1 means a belief oflow probability that effort will lead to successful performance. A low self-efficacy maymean a belief that one can not execute the behavior because one does not have the

required cognitive and emotional abilities to mobilize effort.

Self-Efficacy and Locus of Control

Whereas self-efficacy is a broaderconcept than effort-performance expectancy, it is con-sidered more specific than locus of control, a belief-based personality variable. Thereare obvious similarities. Both self-efficacy and locus of control are cognitive and areabout control (Rotter 1966). Furthermore, just as self-efficacy can be affected by perfor-mance, locus of control can be affected by life experiences (Dyal 1984). However, thereare two important distinctions. First, locus of control measures not only behavioral but

also outcome control (Rotter 1966), whereas self-efficacy concerns only behavioral con-trol. Secondly, internal versus external locus of control is a generalized construct cov-ering a variety of situations, whereas self-efficacy is task specific, examining the individu-als conviction that he or she can perform a specific task at a specific level of expertise(Gist 1987, p. 478). A person may therefore have a strong internal locus of control ingeneral but have a low self-efficacy in performing specific tasks of an area.

Specificity-Generativeness of Self-Efficacy

Although self-efficacy is known to be task specific, the level of specificity can still vary

with the task domain. The most frequent definition of self-efficacy refers to perceivedcapabilities to perform a specific task (e.g., Bandura 1982; Gist 1987). However,Wood and Bandura (1989) also used the term event, which covers a range of specific-

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ity levels from execution of specific tasks to the choice of a career. Obviously the controlover the event of a singular task is much more specific than the control over the eventof a career. One can imagine even more general events that cut across different voca-tions. Thequestion is how general can self-efficacy be withoutlosing itsspecificity, which

is lauded as such an advantage over other related constructs.Bandura (1982) maintained that although self-efficacy is task specific, it can also

be generative, that is, self-efficacy with respect to onetask may be generalized to anothertask. The notion of generativeness therefore allows a broader application of self-effi-cacy, while at the same time it imposes a condition for such application. That is, thetasks should be more or less interrelated (Gist 1987). The reason that self-efficacy canbe applied to career choice is presumably because an occupation contains a set of inter-related tasks. To use self-efficacy beyond a well-defined task domain across unrelatedtasks and situations may offset the very task-specificity advantage of the construct. Itmay even render self-efficacy indistinguishable from universal dispositional constructs

such as self-esteem or locus of control.

Measurement of Self-Efficacy

Self-efficacy can be applied to a variety of domains as long as the efficacy measure istailored to the specific tasks being assessed (Bandura l982). The predictive power willbe sacrificed as the measurebecomes more general (Gist 1987). This is to say that regard-less of the specificity of the task domain, assessment of efficacy has to be at the specifictask level to maintain its predictive power. This poses a dilemma for measuring self-efficacy for a general domain. For instance, one can measure self-efficacy of runningones own business by referring to self-employment in general or alternatively, one canmeasure entrepreneurial self-efficacy by referring to specific tasks involved in runningones own business. As much as one would like to increase the predictive power, it isimpractical to enumerate all possible tasks of entrepreneurship. A balance has to bemade between specificity and generality so as to adequately but parsimoniously definea career domain.

Gist (1987 p. 481) offers the following advice: It would be more promising to gen-eralize self-efficacy perceptions by aggregating across a number of related but domain-specific measures (e.g., a cluster of specific competencies within verbal skills) than byattempting to devise a broad omnibus test. An omnibus measure is likely to offer conve-nience, but this probably will be at greater expense to predictive power. One way ofmeasuring self-efficacy of a broader domain, as we did in this study, is to develop aconceptual framework of task requirements, on the basis of which self-efficacy of a do-main is aggregated from self-efficacy of various constituent subdomains.

Self-Efficacy and the Study of Entrepreneurship

The concept of self-efficacy has been extensively researched in clinical and health-related areas. Only recently has it been extended to organization and management ingeneral (Gist 1987; Wood and Bandura 1989) and entrepreneurship in particular (Boydand Vozikis 1994, Englehart 1995; Krueger and Brazeal 1994; Scherer et al. 1989). The

self-efficacy perspective is highly appropriate for the study of the entrepreneur. First,as a task specific construct rather than a global disposition, self-efficacy theory helpsaddress the problem of lack of specificity in previous entrepreneurial personality

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research (Brockhaus and Horwitz l986; Gartner 1989). Second, as a belief of ones voca-tional capabilities, entrepreneurial self-efficacy is relatively more general than task self-efficacy. It therefore should be fairly stable yet not immutable. This allows entrepre-neurs to derive, modify, and enhance their self-efficacy in their continuous interaction

with their environment. Third, as self-efficacy is closest to action and action intentional-ity (Bird 1988; Boyd and Vozikis 1994), it can be used to predict and study entrepre-neurs behavior choice, persistence, and effectiveness. Finally, the relationship betweenself-efficacy and behavior is best demonstrated in challenging situations of risk and un-certainty, which are believed to typify entrepreneurship.

Entrepreneurial Self-Efficacy and Entrepreneurial Decision

Entrepreneurial decision refers to the decision to create and manage ones own busi-ness. It is a complex process that is subject to the influence of multiple factors. These

determinant factors have been broadly classified into contextual and individual factors.Previous studies have focused either on contextual factors such as job displacement(e.g., Shapero and Sokol 1982) and prior work experience (e.g., Mokry 1988) or individ-ual dispositional factors such as the need for achievement and locus of control (Brock-haus 1980). More recent models of entrepreneurial decision adopt a perspective inwhich the individual is an intentional decision-maker and actor, engaging in the rationalappraisal of situational as well as personal factors (e.g., Krueger and Brazeal 1994). Akey component of these intentional models is the concept of entrepreneurial self-effi-cacy (ESE).

ESE refers to the strength of an individuals belief that he or she is capable of suc-cessfully performing the roles and tasks of an entrepreneur (Boyd and Vozikis 1994;Scherer et al. 1989). Consistent with previous research on career related self-efficacy,Boyd and Vozikis (1994, p. 66) proposed ESE as an important explanatory variablein determining both the strength of entrepreneurial intentions and the likelihood thatthose intentions will result in entrepreneurial actions. Krueger and Brazeal (1994) an-chored self-efficacy in their model of entrepreneurial potential and proposed that ESEconstitutes one of the key prerequisites of the potential entrepreneur. Scherer et al.(1989) empirically examined how parental role models affect students ESE, which wastreated as an index of entrepreneurial career preferences.

According to the above authors, the entrepreneurial decision may be influencedby ESE for a number of reasons. First, the same entrepreneurial environment couldbe assessed as replete with opportunities by people with high ESE but fraught with costsand risks by people with low ESE. Secondly, even if people perceive an identical realityconsisting of uncertainties, risks, and hardships, those with high ESE would feel morecompetent to deal with that reality than those with low ESE. Lastly, people with a highESE anticipate different outcomes than people with low ESE. Brockhaus (1980) con-tended that because entrepreneurs have a very high belief in their ability to influencethe achievement of business goals, they perceive a very low possibility of failure. HighESE people are likely to associate challenging situations with rewards such as profit,community recognition, and psychological fulfillment (Hisrich and Brush 1986),whereas low ESE people are likely to harbor images of failures, such as bankruptcy,

disgrace, and psychological stress. For these reasons, individuals who consider them-selves efficacious in performing entrepreneurial roles and tasks are more likely to enterthe entrepreneurial environment than those who do not. This line of reasoning leads

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us to the following hypothesis,

H1: Individuals with high ESE are more likely to be entrepreneurs than those withlow ESE.

For its effect on behavior choice and performance, self-efficacy is widely claimed tohave greater predictive power than constructs that lack task-specificity (see our earlierdiscussion). This implies that ESE should distinguish entrepreneurs better than doglobal personality traits. Of the global constructs, locus of control has been widely re-searched in the field of entrepreneurship (Brockhaus 1980; Brockhaus and Horwitz1986). Yet, although Bandura (1977a) and others (e.g., Gist 1987; Scherer et al., 1982)have explicated similarities and distinctions between self-efficacy and locus of control,no empirical research has been conducted to test their arguments. We included locusof control in one of the surveys to, on the one hand, examine the convergent and discrim-inant validity of ESE and, on the other, to compare their relative effect on the criterion

variable, the entrepreneurial decision. Given the similarities and differences of the twoconstructs, we expect that

H2: ESE will be positively related to internal locus of control but negatively relatedto external locus of control.

H3: ESE will distinguish entrepreneurs from managers better than will locus ofcontrol.

METHOD

Specifying the Domain of Entrepreneurship for Measuring ESEAs discussed earlier, the construct of self-efficacy is intricately related to its measure-ment. The construct development of ESE dictates a specification of the domain of entre-preneurship as well as its key constituent tasks. Inappropriate specification of the taskdomain directly affects its conceptual distinctiveness and its predictive power on depen-dent variables. The challenge to us was to identify specific entrepreneurial tasks thattogether represent the entrepreneurial domain.2 For this purpose we turn to literaturethat defines entrepreneurship in terms of the roles and tasks that the entrepreneurperforms.

Roles and Tasks of the Entrepreneur

We found three sources of literature that take the role-task approach to entrepreneur-ship. The first is Longs (1983) The Meaning of Entrepreneurship, a comprehensive re-view of the definitions of entrepreneurship by theoretical economists since RichardCantillon (circa 1730). Long defines entrepreneurship primarily as a process. He definesthe entrepreneur in terms of competencies, capacities, and skills. Longs review reveals

2So far there has been no scale that measures ESE at the level of specific entrepreneurial tasks. Shereret al.s (1982) general self-efficacy measurement is not career related. Betz and Hacketts (1981) self-efficacy

scale is career related but not tailored to entrepreneurship. Sherer et al.s (1989) entrepreneurial task self-efficacy is closest to our need but is an omnibus scale that stops at major management functions of accounting,production, marketing, human resources, and general organization without spelling out specific tasks withineach function.

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three major themes of entrepreneurship and entrepreneurial capabilities: uncertaintyand risk, complementary managerial competence, and creative opportunism.

The second task-oriented author is Miner (1990, 1993), who uses the role frame-work to conceptualize and study motivation patterns of the entrepreneur in relation

to the role requirements inherent in the task system of entrepreneurship. Miner identi-fies five role prescriptions that characterize the task system of the entrepreneur: self-achievement, avoiding risks, feedback of results, personal innovation, and planning forthe future. Miners role requirement of avoiding risks is a departure from the earliertraditional view of entrepreneurs being calculated risk takers (McClelland 1961). Fol-lowing Raynor (1974), Miner argues that entrepreneurs do everything possible to avoidand reduce risks because any immediate failure has the potential consequence of failureto achieve desired career goals due to the loss of the opportunity to continue the pursuitof those goals.

Thirdly, Kazanjian(1988) had CEOs of technology-based new ventures identify

dominant problems at different stages of growth. Kazanjian identifies six clusters oftasks across the stages: organizational systems (e.g., the development of financial sys-tems and internal controls), sales/marketing (e.g, penetrating new geographic territor-ies), people ( e.g., attracting capable personnel), production (e.g., producing in volumesadequate to meet demand),strategic positioning (e.g., developing a new product or tech-nology application), and external relations (e.g., acquiring key outside advisors orboard members).

Drawing upon these sources and based upon interviews with five local entrepre-neurs, six entrepreneurial roles were identified. They were innovator, risk taker andbearer, executive manager, relation builder, risk reducer, and goal achiever. These en-trepreneurial roles served as a framework, from which 30 tasks were identified. The 36items were then rated by 30 graduate business students for their essentialness in entre-preneurship, using a 5-point scale ranging from 5 absolutelyessential to 1absolutelynonessential. Twenty-six items scored 4 points and higher and were therefore retainedto represent the domain of entrepreneurship for the purpose of assessing ESE.

Samples

Study 1

Approximately 140 students from a large northeastern university participated in study

1 on a voluntary basis. The classes included two MBA entrepreneurship electives (n 34), two MBA required organizational behavior classes (n78), and one organizationalpsychology elective for undergraduate seniors (n 29). Female students were closeto being equally represented in the psychology (47%) and the organizational behavior(52%) classes but were much fewer (23%) in the entrepreneurship classes. Each partici-pant attended only one of the three classes at the time of this study. Participants filledout the questionnaires at the beginning of the semester.

Study 2

Participating in the second study were small business owners and executives from a

county chamber of commerce in a northeastern state. We applied a rather restricteddefinition of entrepreneur (Robinson et al. 1991; Wortman 1986) to distinguish themfrom managers. Executives who founded their current companies were considered en-

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trepreneurs, whereas those who did not found their current companies were managers.By using this criterion, we attempted a more rigorous test than the class criterion as usedin the student sample. The Chamber of Commerce membership sample was restricted toeliminate executives involved with non-profit organizations and those who are currently

retired. In addition to measuring ESE, we also included a measure of locus of controlas developed by Levenson (1973).

Our original sample included 1533 potential respondents. Of these, 281 were elimi-nated because the business address or the individual in the targeted position hadchanged. Of the 1,252 remaining, we received 175 usable instruments for a response rateof 14%. The average age of respondents was 45.4 years, the average level of educationachieved was a college degree, and 18% of the respondents were female. Fifty-nine per-cent of the respondents reported being founders of their businesses.

The age of the businesses averaged 28 years and ranged from 1 year to 160 years,with 20% less than 5 years old, 50% being less than 15 years old, 80% less than 50 years

old. The businesses represented all industrial sectors; however, 42.5% were services,and an additional 13.8% were specifically financial in nature, whereas 12.7% were man-ufacturing. As for the size of the businesses, the average number of employees was 135,with 60% reporting less than 20 employees and 88% with 100 or fewer employees.

The response rate prompted a nonresponse bias test, conducted by calling 75 ran-domly selected business owners who had not previously responded to the survey. Datawas gathered from 30 of the owners on a limited number of key variables, includingowner characteristics of age (mean 47.3), gender (13% female), education (a collegedegree) and founder status (50% founders) and business characteristics of business age(mean 30) and size as measured by number of employees (mean 160).T-tests of

the means were performed, and no significant differences were found between respon-dents and nonrespondents on any of the key variables.

Measures

Entrepreneurial Self-Efficacy(ESE).

ESE was measured in reference to the 26 roles and tasks identified earlier. We askedrespondents to indicate their degree of certainty in performing each of the roles/taskson a 5-point scale ranging from 1 completely unsure to 5 completely sure. To reduce

social desirability in reporting ESE, the survey instructions emphasized the importanceof honesty for self-assessment and promised confidential and individual feedback of theparticipants own score in comparison with the aggregate score of the total sample.

Principal component factor analysis with varimax rotation was performed on thetasks based on the combined data of the two studies. A scree plot of the eigenvaluesshowed clearly five factors all above the eigenvalue of 1.00, accounting for 56.6% ofthe variance (Table 1). Twenty-two out of 26 items loaded on the five factors, all at orabove the level of 0.40. The five factors were marketing, innovation, management, risk-taking, and financial control. We calculated the total score of ESE by averaging the 22items; the five component ESE scores were calculated by averaging items within each

of the five factors. The Cronbach alpha reliability coefficients of the total and subscalesare in the diagonal positions of Table 2.

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TABLE 1 Factor Loadings of Entrepreneurial Roles and Tasks

Factors

2 3 4 5Items 1

MarketingSet and meet market share goals 0.86 0.10 0.14 0.03 0.10Set and meet sales goals 0.85 0.08 0.06 0.10 0.03Set and attain profit goals 0.76 0.08 0.06 0.10 0.03Establish position in product market 0.65 0.35 0.09 0.06 0.05Conduct market analysis 0.56 0.36 0.18 0.12 0.10Expand business 0.46 0.32 0.02 0.35 0.08

InnovationNew venturing and new ideas 0.09 0.71 0.10 0.39 0.02New products and services 0.17 0.71 0.01 0.28 0.03

New markets and geographic territories 0.36 0.61 0.04 0.06 0.00New methods of production, marketing and 0.17 0.58 0.26 0.05 0.22

managementManagement

Reduce risk and uncertainty 0.04 0.04 0.82 0.01 0.17Strategic planning and develop information 0.15 0.07 0.70 0.06 0.32

systemManage time by setting goals 0.33 0.07 0.50 0.02 0.14Establish and achieve goals and objectives 0.44 0.16 0.50 0.13 0.07Define organizational roles, responsibilities, 0.09 0.05 0.50 0.46 0.11

and policies

Risk-takingTake calculated risks 0.05 0.25 0.09 0.75 0.03Make decisions under uncertainty and risk 0.03 0.23 0.07 0.72 0.13Take responsibility for ideas and decisions 0.15 0.01 0.10 0.46 0.32Work under pressure and conflict 0.35 0.00 0.10 0.40 0.07

Financial controlPerform financial analysis 0.11 0.03 0.10 0.07 0.88Develop financial system and internal 0.08 0.09 0.23 0.05 0.86

controlsControl cost 0.26 0.18 0.20 0.23 0.47

Eigenvalue 7.42 2.36 1.88 1.71 1.28

% of variance 27.6 9.1 7.2 6.6 5.0

Locus of Control

Levenson (1973) developed a triple-dimensional measurement of locus of control: inter-nal control, control by powerful others, control by chance. For our study we focusedon the internal control and the chance control. Using principal component factor analy-sis with varimax rotation, we found two factors that confirmed Levensons original con-ception. As can be seen in Table 3, five internal control items loaded on one factor(Cronbach alpha 0.77) and five chance control items loaded on the other (Cronbachalpha 0.73).

Entrepreneurial DecisionWe measured the entrepreneurial decision of the students on a 5-point scale, in terms

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TABLE 2 Correlation Matrix of Study 2

# ofMeans SD Items 1 2 3 4 5 6 7 8 9 10

1. Marketing 3.57 0.79 6 (0.86)

2. Innovation 3.87 0.74 4 0.55a

(0.74)3. Management 3.83 0.75 5 0.56a 0.38a (0.75)4. Risk-Taking 4.25 0.56 4 0.38a 0.52a 0.45a (0.65)5. Finance 3.69 0.73 3 0.30b 0.22a 0.42a 0.27a (0.77)6. Total ESE 3.89 0.49 22 0.78a 0.73a 0.77a 0.68a 0.64a (0.89)7. I control 5.06 0.71 5 0.23a 0.27a 0.19a 0.30a 0.13a 0.30a (0.77)8. C control 2.02 0.77 5 0.18b0.18b0.10 0.19a0.21a0.24a 0.30a (0.73)9. Founder 0.59 0.49 1 0.02 0.22a 0.06 0.32a 0.07 0.18b 0.11 0.15b

10. Start-Up 0.73 0.45 1 0.07 0.21a 0.05 0.10 0.11 0.15b 0.05 0.13 0.05

Note: Numbers in the diagonal are Cronbach alphas.ap.01, b p.05.

of their intention to start up a business. In five items, we asked the respondents howinterested they were in setting up their own business; to what extent they had consideredsetting up their own business, to what extent they had been preparing to set up theirown business, how likely it was that they were going to try hard to set up their ownbusiness, and how soon they were likely to set up their own business. The Cronbachalpha for the scale is 0.92. For the sample of business executives, founder versus non-founder, coded as one and zero respectively, was the criterion of entrepreneurial de-cision.

Background Variables

The student respondents provided background information on their gender, the numberof management courses they had taken, and whether they had friends or relatives whowere or had been entrepreneurs. The business executive respondents were asked abouttheir gender, age, educational level, whetheror not they had been involved in starting upa company, whether or not parents or siblings had been entrepreneurs, and information

TABLE 3 Factor Loadings of Internal versus Chance Control

Items Factor 1 Factor 2

I am usually able to protect my personal interests. 0.69 0.14My life is determined by my own actions. 0.81 0.12I can pretty much determine what will happen in my life. 0.74 0.13When I make plans, I am almost certain to make them work. 0.63 0.25When I get what I want, its usually becuase I worked hard for it. 0.71 0.04To a great extent my life is controlled by accidental happenings. 0.10 0.62Often there is no change of protecting my personal interests 0.07 0.67

from bad happenings.When I get what I want, its usually because Im lucky. 0.10 0.62Its not always wise for me to plan too far ahead because many things turn 0.15 0.77

out to be a matter of good or bad fortune.Whether or not I get to be leader depends on whether Im lucky enough to 0.08 0.72

be in the right place at the right time.Eigenvalue 3.32 1.76% of variance 33.3 17.7

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TABLE 4 Correlation Matrix of Study 1

Means SD 1 2 3 4 5

1. Entrepreneurial decision 3.13 0.93 0.50a 0.25a 0.22a 0.23a

2. ESE total 3.81 0.48 0.12 0.30a 0.18b

3. Friends and relatives 1.32 0.82 0.04 0.014. Managment courses 3.10 1.36 0.20a

5. Gender 0.57 0.50

a p .01, bp .05.Managment courses, none 0, 1 to 4 1, 5 to 8 2, 9 to 13 3, 14 and more 4.Gender: female 0, male 1.

about the company, such as years of operation, number of employees, sales volume,and the number of management levels of the company.

ANALYSIS AND RESULTSStudy 1

Simple correlations (Table 4) showed that the total ESE score, the number of entrepre-neurial friends and relatives, and the number of management courses were all positivelyrelated to entrepreneurial decision. Furthermore, male students expressed stronger in-tention toward becoming an entrepreneur than did female students. Among the inde-pendent variables, the number of management courses was positively related to ESEbut having entrepreneur friends and relatives was not. In addition, male students hadhigher ESE than their female peers.

When entrepreneurial decision was regressed on all the independent variables, thepositive effect of ESE and of having entrepreneurial friends and relatives remained sig-nificant, but the effect of gender became marginal, and management courses had noeffect (Table 5).

Whereas the above results were consistent with H1, we further examined whetherESE also differentiated the three academic classes, which may be a proxy criterion ofthe entrepreneurial decision. As an elective, the entrepreneurship course might haveattracted students who felt more strongly efficacious in entrepreneurship than studentsin both the organizational behavior and the psychology classes. As an MBA course,the organizational behavior class was more related to entrepreneurial business than wasthe psychology class; the management students should therefore score higher in ESEthan the psychology students. In summary, we expected that the entrepreneurship classwould score the highest on ESE, whereas the psychology class would score the lowest.

The results of ANOVA on the total ESE showed a significant effect of class

TABLE 5 Results of Regression on Entrepreneurial Decision

Independent Variables

ESE total 0.44a

Friends and relatives 0.19b

Management courses 0.05Gender 0.14c

R2 0.31F 14.87a

a p .001, b p .01, c p .10.

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TABLE 6 ESE by Founding Status

Entrepreneurial Self-Efficacy

Total Marketing Innovation Management Risk-Taking Financial Control

Founder 3.94 (.52) 3.66 (.78) 4.02 (.68) 3.85 (.70) 4.47 (.47) 3.71 (.81)(n 100)

Nonfounder 3.74 (.47) 3.56 (.76) 3.70 (.72) 3.78 (.63) 4.15 (.56) 3.51 (.86)(n 58)

Pa 0.01 NS 0.001 NS 0.000 NS

a Significance values were those after controlling for individuals gender, age, and education, and the companies currentage and size.

(F2,138 7.68; p .001). Specifically, the entrepreneurship class (mean 4.00, SD 0.44) scored significantly higher than both the organizational behavior class (mean 3.80, SD 0.48) (t 2.00,p .05) and the psychology class (mean 3.47; SD 0.46)

(t 3.91;p .001). The organizational behavior class scored significantly higher thanthe psychology class(t2.83,p .01). MANOVA procedures using the five componentESE scores as the dependent variables and academic class as the factor also showedsignificance class differences (Wilks Lambda 0.84, F10,268 2.43, Sig. F .01). Theunivariate results showed that major class differences were in self-efficacy of marketing,management, and financial control.

Study 2

To test H1 with the sample of real-world entrepreneurs, the total and the componentESE scores were compared between founders and nonfounders (see Table 6). Table2 presents a correlation matrix of major variables in the second study.

Founders and Nonfounders

An ANCOVA procedure on the ESE total score, controlling for individuals gender,age, and education, and the companies current age and size, found a significant maineffect of the founding status (Mean Square 1.80;F1,154 7.07, Sig.F .008). A MA-NOVA was conducted with the component ESE scores as the dependent variables, the

founding status as the between subject factor, controlling for individuals gender, age,and education, and the companies current age and size. Results showed significant dif-ferences between the two groups of executives (Wilks Lambda 0.94;F5,147 4.57, Sig.F .001). The individual univariate statistics showed that founders had stronger self-efficacy in innovation (t 3.53, p .001), and risk-taking (t 3.96; p .000). Theseresults provided additional support for H1, which predicts that people with high ESEwill be more likely to be entrepreneurs than those with low ESE.

Relationship between ESE and Locus of Control

As can be seen from the correlation matrix (Table 2), the total and the component self-efficacy scores were generally positively related to internal control but negatively tochance control. This pattern of relations supported H2.

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TABLE 7 Results of Logistic Regression Analysis

Model 1 Model 2 Model 3 Model 4

S.E. S.E. S.E. S.E.Variables B B B B

Constant 0.70 0.81 0.08 1.35 5.19a 1.54 4.78c 2.15Gender 0.21 0.40 0.49 0.44Age 0.02 0.02 0.01 0.02Degree 0.04 0.15 0.02 0.15I Control 0.20 0.23 0.04 0.28C Control 0.37d 0.21 0.31 0.24Marketing 0.51 0.31 0.34 0.32Innovation 0.61c 0.31 0.53d 0.33Management 0.26 0.33 0.55 0.37Risk-taking 1.33a 0.40 1.32b 0.43Financial control 0.09 0.22 0.10 0.24n 169 176 176 1662 log likelihood 225.18 232.93 213.76 195.88

Model chi-square 2.61 5.21d 24.37a 27.22b

a p .001, b p .01, c p .05, dp .10.

Comparing Effects of ESE and Locus of Control

Based on the simple correlation coefficients, internal locus of control had no effect onfounding status but chance control had (r0.15,p .05), suggesting that nonfoundersbelieved more strongly than founders that life was controlled by chance. To comparethe relative effect of ESE, locus of control, and other individual demographics we rana series of logistic regression analyses of the founder versus nonfounder. We first ranseparate logistic regressions on individual backgrounds of gender, age, and education(model 1), internal and chance locus of control (model 2), and the ESE scores (model3). We then ran a full model with all three groups of variables in the equation (model4). As is indicated by the chi-square statistics in Table 7, model 1, which contained indi-vidual backgrounds was not significant; model 2 of the locus of control was only margin-ally significant; but model 3 of ESE was highly significant. Within model 3, it was ESEof innovation and risk-taking that were significant predictors. When all independentvariables were entered (model 4), risk-taking self-efficacy remained highly significant,whereas innovation self-efficacy was only marginally significant. These findings provideevidence in support of H3, which predicts that ESE will distinguish entrepreneurs frommanagers better than will locus of control.

Relations between ESE and Other Variables

Simple correlation coefficients showed that gender, age, and education of the businessexecutives did not have significant relations with ESE scores, except that age was posi-tively related to self-efficacy of financial control (r 0.17, p .05). Having a parentor sibling who was an entrepreneur did not seem to affect ESE. Having start-up experi-ence was positively correlated with the total ESE (r 0.15,p .05) and self-efficacy

of innovation (r 0.21,p .01). In general, company level variables were not correlatedto ESE. However, the start-up sales volume was positively correlated to self-efficacyof marketing, and the management level of the company was positively correlated with

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the total ESE (r 0.19, p .05), self efficacy of marketing (r 0.22, p .01) andmanagement (r 0.16, p .05).

CONCLUSIONS AND DISCUSSIONSummary of Important Findings

There are a few important findings from this research. First, the results from both stu-dents and business executives indicated a significant and consistent positive effect ofentrepreneurial self-efficacy on the likelihood of being an entrepreneur. Those studentswho reported stronger entrepreneurial self-efficacy also expressed a stronger intentionto start a business of their own; business founding executives held stronger entrepre-neurial self-efficacy than nonfounding executives. Previous research has found the ef-fects of self-efficacy on broadly defined career options, such as traditional versus nontra-ditional careers (e.g., Betz and Hackett, 1981). Our research, however, confirmed therelationships proposed by Boyd and Vozikis (1994) between self-efficacy and careerintention specific to entrepreneurship.

Second, we found preliminary evidence showing convergent and discriminant va-lidity of ESE with a related but more general construct, locus of control. As evidenceof the convergent validity, ESE was related positively to internal control but negativelyto chance control. Scherer et al. (1982) also found convergence between self-efficacyand internal-external locus of control, but their conception of self-efficacy transcendstasks and situations. That our study found a pattern of expected relationships betweenthe specific component ESE measures and the general locus of control measures indi-cated that despite its specificity, ESE is a belief-based construct and is about personalcontrol. Regarding the discriminant (criterion) validity, ESE predicts entrepreneurialcareer decision better than locus of control either when they were independent pre-dictors or when controlling for the other.

The third important finding was that the component ESE scores were related tovarious criterion variables differently.3 Although the summary ESE itself may be suffi-cient for predicting entrepreneurial choice, the component ESE measures allowed usto examine the relative potency of specific subdomains with regard to a particular choicecriterion. It was the self-efficacy of innovation and risk-taking that differentiated entre-preneurs from managers as in the case of founders versus nonfounders. This findingis consistent with Long and many others who consider innovation and/or risk-taking

as key primary entrepreneurial capabilities, and managerial competence as the comple-mentary.

However, what differentiated the entrepreneurship students from their manage-ment and psychology peers was not self-efficacy of innovation or risk-taking but self-efficacy in various managerial functions of marketing, management, and financial con-trol. There may be several reasons for the inconsistency between the students and theentrepreneurs. First, it may be the case that the MBA curriculum in general was heavilyoriented toward technical management skills associated with bureaucratic rather thanentrepreneurial firms. Students who felt they had a good mastery of these tools mightalso have felt that they were well equipped for starting their own businesses. Secondly,

3It is worth noting that this occurred even though the subscores of ESE correlated with each otherfairly highly.

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because the surveys were administered at the beginning of the entrepreneurship course,the potential of gaining self-efficacy in innovation and risk-taking may have not cometo fruition. Lastly, it may be the case that self-efficacy in innovation and risk-taking aremore likely to be developed through real-world experience, which the entrepreneurship

students were still lacking. In any case, these differences would not have been foundhad we surveyed only students or had we only had an omnibus measurement of ESE.

Limitations

As an exploratory study, this research is not without limitations. First, it is very impor-tant to extend studies of career choice beyond the more convenient sample of students.Unfortunately, the solicitation of real-world entrepreneurs proved to be a challenge tous. Our business executives were limited to the members of the chamber of commerce.Furthermore, although our nonresponse bias test did not show significant differences

between the respondents and nonrespondents in a number of key background variables,future studies should increase resources and adopt more creative methods to improvethe response rate so as to allow for increased validity and generalization of the results.

A second problem is the potential social desirability in reporting self-efficacy de-spite the precautions taken. The high interfactor correlation of our ESE scores may bein part due to social desirability, although positive correlations among the subscoreswere expected because of the inherent interrelatedness among the entrepreneurialtasks. Future research should think of ways to reduce possible social desirability. Forexample, efficacy beliefs in terms of competencies can be supplemented with those ofpotential obstacles (MacMillan, Block, and Narasimha 1986; Krueger and Brazeal1994).

Finally, the cross-sectional design of the research does not allow us to test causalrelations between ESE and entrepreneurial choice. According to the reciprocal causal-ity argument, the relationships we found between ESE and entrepreneurial decisioncan be used to attribute causality to either of the two variables. For instance, one couldtake ESE as the cause, reasoning that people with higher ESE are more likely to setup their own businesses, or one can take founding experience as the cause, reasoningthat people who get involved in setting up a business will develop higher self-efficacy.The same ambiguity can be applied to the students regarding choosing academic classes.

This study relied on the first rationale, assuming that business setup is a purposiveand intentional activity and that nonintentional entrepreneurial experience does notnecessarily lead to enhanced self-efficacy. We nevertheless emphasize that to truly de-termine causality, longitudinal research design is necessary. For example, a study couldbe designed in which MBA students ESE and entrepreneurial intentions are measuredprior to theselection of therelevant courses, and again after taking the courses, and theirreal career choice after graduation can be documented to validate the entrepreneurialintention. Wood and Bandura (1989) also suggested using business simulations to deter-mine causal effects by manipulating and controlling for ESE.

Longitudinal studies can also be conducted with the cooperation of institutionssuch as a small business development center. Potential clients can be tested on theirESE at time one, and their actual venture creation and entrepreneurial persistence can

be documented at subsequent time periods so as to explore the relationships betweenESE and entrepreneurial entry and performance. Longitudinal studies of real-worldentrepreneurial decisions also have the advantage to consistently define and measure

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the construct of entrepreneur. For, although we applied a rather restricted criterion(founder versus nonfounder) in our second study, half of the businesses were founded15 years ago; findings about these past entrepreneurs may or may not generalize topotential or future entrepreneurs.

Despite the limitations, this research has important research and practice implica-tions. It raises conceptual issues regarding doing research on the psychology of the entre-preneur and it encourages the use of ESE as an assessment and intervention tool forpromoting entrepreneurial choice.

Conceptual Implications

For a long time, entrepreneurship scholars havebeensearching for constructs of individ-ual characteristics that are unique to entrepreneurs. This study provides encouragingthough preliminary evidence that entrepreneurial self-efficacy has the potential to be

such an individual construct. The traditional personality approach to the psychologyof the entrepreneur experiences a dilemma in that an individual characteristic has to,on the one hand, transcend specific situations in order to be a stable trait and, on theother hand, be unique to the domain of entrepreneurship. Against these dual standards,general personality traits such as the need for achievement and the locus of control haveachieved only limited success in differentiating entrepreneurs from higher achievers andinternalizers in other spheres of life (Brockhaus and Horwitz 1986; Gasse 1986; Lowand MacMillan 1988). Entrepreneurship scholars have been attracted to self-efficacyprimarily for its promise of domain specificity. Because it refers to cognitive evaluationsof personal capabilities in reference to the specific tasks of entrepreneurship, ESEachieves the entrepreneurial distinctiveness that is both individual and contextual.

Although the advantage of domain specificity seems to be obvious, is ESE a stableenough construct to qualify as an individual difference variable? This is both a concep-tual and an empirical question. Conceptually, as we have discussed in the literature re-view section, self-efficacy can vary from very specific (e.g., individual tasks) to moder-ately specific (e.g., an occupation with a well defined cluster of tasks). Although themalleability of self-efficacy depends very much on the nature of the task and the charac-teristic of the person, one can say that other things being equal, malleability goes up(or stability goes down) as a task is more specific. Because vocational self-efficacy ismoderately specific, we argue it is moderately stable/malleable. In a broader spectrum,vocational self-efficacy, including ESE, is more specific/malleable than general disposi-tional constructs but more general/stable than self-efficacy of individual tasks. It is there-fore neither completely fixed nor easily changeable. Although career choice scholarssuggested that career related self-efficacy can be used for selection purposes (e.g., Gist1987), implying that it is an individual difference variable, we submit that it remainsto be validated with further empirical research. Studies and experiments can be con-ducted to explicitly explore the malleability of ESE through purposeful interventions.

How do we interpret the lack of a relationship between ESE and the company per-formance in terms of size (number of employees) and sales? To start with, self-efficacyis used to predict performance at the individual level. But even if the entrepreneur ispersonally responsible for his or her companys performance, the relationship between

ESE and entrepreneurial performance is still more complex than we initially expected.Past research has shown that task-specific self-efficacy best predicts immediately subse-quent performance; the more distal, the less the predictability (Gist 1987). Because vo-

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cational self-efficacy is multidimensional and takes a longer time to exercise its influ-ence, its predictability of career performance may be reduced. Furthermore, manythings other than ESE could intervene to affect the companys bottom line. Thirdly,although higher self-efficacy definitely motivates entrepreneurial entry, it may not al-

ways positively affect performance. Overconfidence may be too detached from realityjust as self-doubt can be debilitating. Finally, even if we found a significant correlationbetween ESE and the current sales volume we would still have difficulty interpretingit. It could be either that good sales temporarily boost ones self-efficacy or that theparticipants were merely being consistent in reporting the companys sales and theirown efficacy beliefs. The lack of a relationship at least ruled out that possibility. Tosummarize, the effects of ESE on entrepreneurial performance may be less straightfor-ward than on entrepreneurial entry. Further efforts should be made to build and testresearch efficacy models for entrepreneurial performance.

Practical Implications

The findings of this study also have practical implications. First, ESE can be used toidentify reasons for entrepreneurial avoidance. Although a low ESE may reflect an ac-curate assessment of ones actual capabilities, there are many who otherwise would be-come entrepreneurs but for doubts of their entrepreneurial self-efficacy. This is espe-cially true for sectors of the population such as women or certain minority memberswho may possess necessary entrepreneurial competencies but were deterred by lowESE from entering a particular type of business or an entrepreneurial career altogether.Communities and individuals could benefit from identifying sources of entrepreneurialavoidance by targeting their efforts of enhancing ESE at particular groups or individualsfor particular aspects of entrepreneurship.

An additional use of ESE is to assess the entrepreneurial potential of both an indi-vidual and a community. Krueger and Brazeal (1994) argued that the prerequisite ofentrepreneurship is the existence of entrepreneurial potential, of which self-efficacy isa key component. Once entrepreneurial potential is identified, resources can be chan-neled and more effectively used to stimulate entrepreneurial entry.

Diagnosis and treatment of ESE can also be performed on current entrepreneurs.Lack of ESE may lie behind the fear of growth, diversification, or performing criticalaspects of the business. Recognizing and pinpointing areas in which the entrepreneurfeels inefficacious is the first step toward addressing the problem. Strengthened self-efficacy will enable the entrepreneur to be more active in expanding and performingcritical activities and more persistent in the face of difficulty and setbacks.

Because ESE is moderately stable, systematic and continuous efforts have to bemade to enhance and sustain ESE. Two broad approaches can be taken. One is themicro-approach that directly focuses on peoples beliefs. In designing and conductingentrepreneurship courses, training institutions should not just pay attention to trainingstudents in critical entrepreneurial skills and capabilities but also to strengthening theirentrepreneurial self-efficacy. The current state of entrepreneurship courses in mostmanagement schools may fall short in both respects. Courses primarily focus on comple-mentary skills of management but not as much on entrepreneurial skills such as innova-

tion and risk-taking. Furthermore, teaching of entrepreneurial skills tends to be techni-cal with insufficient attention paid to the cognition and the belief systems of theentrepreneur. Entrepreneurship educators should take into account entrepreneurial at-

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titudes and perceptions in both designing and assessing their course objectives. Con-scious efforts can be made to enhance ESE by involving the students in business designor community small business assistance, by inviting successful entrepreneurs to lecture,and by verbal persuasion from the instructor and renowned entrepreneurs.

The second approach toward an enhancement of ESE is to work on the environ-ment of potential and actual entrepreneurs. According to the triadic reciprocal causa-tion model, the environment may affect self-efficacy not only directly but also indirectlythrough performance. An environment perceived to be more supportive will increaseentrepreneurial self-efficacy because individuals assess their entrepreneurial capacitiesin reference to perceived resources, opportunities, and obstacles in the environment.Personal efficacy is more likely to be developed and sustained in a supportive environ-ment than in an adverse one. A supportive environment is more likely to breed entrepre-neurial success, which in turn enhances entrepreneurial self-efficacy. Consistent withthis argument about the environmental effect, Krueger and Brazeal (1994) posited that

creating a congenial environment facilitates the perception of feasibility for entrepre-neurship. Toward that end, the authors recommended that communities should, amongother things, make resources both available and visible, publicize entrepreneurial suc-cesses, increase the diversity of opportunities, and avoid policies that create real or per-ceived obstacles.

Entrepreneurial self-efficacy is not a panacea but only one variable in the complexprocess of entrepreneurial decision and action. However, it is an individual characteris-tic that shows signs of being uniqueto the potential and actual entrepreneur. Incorporat-ing this construct into models of research, education, counseling, and community inter-vention may help us better understand entrepreneurial action and give us someadditional leverage to translate entrepreneurial potential into entrepreneurial reality.

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