Segal, Gerry


With increasing numbers of entrepreneurial ventures, we recognized the need for more reliable predictors of firm performance. To augment existing explanations of small firm performance, we used entrepreneurial self-efficacy and goal setting as predictor variables. We tested Bandura’s concept of self-efficacy and Locke and Latham’s model of goal setting with small firms. Though these models have been tested and accepted as reliable in large organizations, we saw a need to establish their “fit” in the entrepreneurial context. We expected founders with high self-efficacy to set higher goals that resulted in better firm performance. A survey of founder-managed natural food stores validated our hypotheses.


A small firm is a reflection of the founder’s vision and value system (Chandler & Jansen, 1992; Eskew, 2004). Venture capitalists emphasize founders’ quality and track records in their investment decisions (Goslin & Barge, 1986). However, previous research on demographic (e.g., education, experience) and psychological (e.g., locus of control, need for achievement) characteristics of entrepreneurs does not provide conclusive evidence of a meaningful relationship between the entrepreneur’s demographic and psychological characteristics and small firm performance (Baum & Locke, 2004; Honjo, 2004; Krueger, Reilly, & Carsrud, 2000; Robb, 2002).

With calls to develop and apply theoretical constructs to the field of entrepreneurship (Bygrave & Hofer 1991; Clark & Sorensen, 2002, Jelinek & Litterer, 1994), we recognize the need to import and test theoretical constructs from other academic fields. This paper expands current knowledge by applying the concept of self-efficacy and goal setting with roots from sociology, psychology, and organizational behavior literature to explain entrepreneurmanaged firm performance.


Founder Self-Efficacy

Self-efficacy is the extent to which one believes he or she possesses the knowledge, skills, and ability to accomplish a goal in the face of difficulty. People’s beliefs in their selfefficacy influence their choices, aspirations, exertions of effort, perseverance in the face of difficulty, cognitive abilities, and stress levels (Bandura & Locke, 2003; Gist & Mitchell, 1992). Sadri and Robertson (1993) examined the results of 21 studies and found a significant relationship between self-efficacy and work performance.

Bandura (2000) found that people with a strong sense of self-efficacy will persevere in the face of failure and setbacks and view obstacles as challenges rather than as reflections of personal deficiencies. Entrepreneurship research (Chandler & Jansen, 1992); Crane & Sohl, 2004) found the determination to succeed – drive – an important predictor of entrepreneurial performance. Entrepreneurs with strong self-efficacy should exhibit high levels of drive, resulting in better firm performance.

Lindsley, Brass and Thomas (1995) reviewed the effect of self-efficacy on performance. They proposed that the efficacy-performance relationship is a positive, cyclic one with reciprocal causation. Due to the reciprocal causation, these iterative loops often become “deviationamplifying.” For example, in a deviation-amplifying loop, a deviation in one variable (decrease in self-efficacy) leads to a similar deviation in the other variable (lower performance), which, in turn, continues to amplify. Thus, the cyclic nature of the self-efficacy-performance relationship can result in a downward (decreasing) or upward (increasing) spiral.

Krueger and Dickson (1993) manipulated self-efficacy with positive or negative performance feedback, then assigned decision-making exercises involving dilemmas and gambles. Perceptions of self-efficacy directly correlated with perceptions of situational opportunity and inversely related to perceptions of situational threat. Similarly, as events unfold during the entrepreneurship process, the entrepreneur may perceive various situations that arise as opportunities or threats.

Entrepreneurs with strong entrepreneurial self-efficacy may view an event as an opportunity and put themselves in a position to exploit it. Entrepreneurs with low self-efficacy may perceive a similar event as a threat and overreact or become paralyzed with fear, with either reaction potentially leading to detrimental consequences. Because the ability to recognize and take advantage of opportunity has been referred to as the core of entrepreneurship (Timmons, Muzyka, Stevenson, & Bygrave, 1987), a clear explanation of the mechanism linking selfefficacy and entrepreneurial performance is established. Applying Lindsley et al.’s (1995) theory of reciprocal causation, we recognize that entrepreneurial self-efficacy and firm performance are linked.

Goal Setting

A well-established finding in the organizational behavior literature is that specific, challenging goals lead to better task performance than no goals, “do-your-best” goals, or specific, easy goals (Latham, 2000; Locke & Latham, 1990, 2002; Mento, Steel, & Karren, 1987; Tubbs, 1986). Goal setting theory is considered one of the most valid and useful theories of motivation (Early & Lee, 1992; Locke & Latham, 1990; Miner, 1984). Pinder (1984, 1998) concluded that goal-setting theory had shown more scientific validity than any other work motivation theory. Studies report that difficult (but attainable) and specific goals are strongly related to motivation and performance (Chesney & Locke, 1991; Knight, Durham, & Locke, 2001) but little is explored regarding the applicability of goal setting to the entrepreneurial firm (Tracy, 1992; Collins, Hanges, & Locke, 2004). Goal-setting studies have typically involved large organizations or small groups of people.

Shane and Delmar (2004) used goal-setting theory to test the value of business planning in the new venture initiation process. Their findings indicated that the completion of a written business plan prior to initiating marketing efforts led to lower new venture termination rates. There is a clear need to validate the use of goal-setting techniques to predict the performance of established entrepreneurial firms. Locke and Latham’s (1990, 2002) model of goal setting lends itself to testing in the entrepreneurial environment. The model accounts for individual attributes, organizational support, level of goal difficulty, and commitment to performance.

Goal Setting and Self-Efficacy

Perceived self-efficacy for goal attainment raises the level of self-set goals (Locke, 2001). Conversely, if an individual concludes that he or she is not really in control of the situation, does not really understand the task, or attained the previous outcomes by luck, self-efficacy may be low, leading to lower future goals (Bandura, 1997; Vancouver, Thompson, & Williams, 2001).

The Founder Self-Efficacy and Goal Setting Model

Locke and Latham (1990) assert that, while goal setting directly affects performance, selfefficacy affects performance not only directly but also indirectly through mediation of goals. Locke and Latham examined thirteen studies with 2,285 respondents which measured each of the three relationships. For these studies, the relationships and their weighted mean correlations were as follows: (1) self-efficacy and self-set goals, r =.39, (2) self-efficacy and performance, r =.39, and (3) self-set goals and performance, r =.42.

While the Locke and Latham (1990) model has been shown to explain individual performance, it has not been used to explain entrepreneurial performance. To address the ability of entrepreneurial self-efficacy and goal setting to explain firm performance, we propose the Founder Self-Efficacy and Goal Setting Model.

Figure 1 illustrates the specific interrelatedness of the three main variables of the Founder Self-Efficacy and Goal Setting Model. These core variables are Founder Goaf-Setting, Founder Self-Efficacy, and Firm Performance.

Based on this model, we hypothesize as follows:

H1: Founder Self-Efficacy has a positive influence on Founder Goal-Setting.

H2: Founder Goal-Setting has a positive influence on Founder Firm Performance.

H3: Founder Self-Efficacy has a positive influence on Firm Performance.


This section examines the sample data and variables employed in this study.

Sample Data

We obtained the sample data for this study from a random sampling of members of the National Nutritional Foods Association (NNFA), a trade association for the U.S. natural food industry. From our mailing of 500 surveys, the U.S. Postal Service returned thirty-seven surveys as undeliverable, leaving a working sample size of 463. Respondents returned 103 questionnaires, resulting in a 22.2% response rate. For this study, we focused on the 63 of the 103 firms that were founder-managed. These 63 firms represented 13.6% of our mailing.

To detect non-response bias, we contacted by telephone a random sample of founders that did not respond to the mailing to record their goals, self-efficacy, and performance. We contacted 26 firms to obtain complete data for 10 founder-managed firms.

We established a 95% prediction interval for performance as a function of goals and selfefficacy from the 63 respondents. We entered goal and self-efficacy measures obtained from the 10 telephone interviews of non-respondents into the prediction model. In every case, performance measures fell within the ±2 standard deviation prediction intervals, indicating that the relationships for the non-response group did not differ from the response group.

Dependent Variables

This research measured the dependent variable founder firm performance using the criteria Chandler and Hanks (1993) found relevant to entrepreneurs, growth in: (1) earnings, (2) net worth, (3) cash flow, (4) market share, and (5) sales volume. We asked respondents to provide this data for their firm’s most current fiscal year using Chandler and Hanks’ method of asking for data in broad categories. Our survey instrument used the following 7-category scale: (1) decreased, (2) held constant, (3) increased less than 2%, (4) increased 2% to 5%, (5) increased 5% to 10%, (6) increased 10% to 25%, and (7) increased more than 25%. We summed the responses to each of these questions to create an index we used as our firm performance variable. We used Cronbach’s Alpha to assess the reliability of this combination and obtained an Alpha coefficient of 0.90. Crano and Brewer (1986) suggest that the degree of internal consistency is considered acceptable if the Alpha coefficient is 0.75 or better.

As shown previously in Figure 1, founder goal-setting functioned both as a dependent variable and as an independent variable in this study. Founder goal-setting is an independent variable in terms of its relationship with founder firm performance and a dependent variable in terms of its relationship with founder self-efficacy. Respondents were asked to provide their goals for growth in profitability as of the beginning of the current fiscal year based on (1) earnings, (2) net worm, (3) cash flow, (4) market share, and (5) sales volume. Because sample firms were small and respondents were actively involved in daily operations, it was assumed that founder and organizational goals were synonymous. Responses to the questionnaire were scored using the 7-point scale as described above. We summed the responses to each of the five goal questions to create an index we used as our founder goal-setting variable. Again, we used Cronbach’s Alpha to assess the reliability of this combination and found an Alpha coefficient of 0.78.

Our final variable, founder self-efficacy, functioned as an independent variable in terms of its relationship with both founder goal-setting and founder firm performance. As suggested by Mone (1994), we used outcome (rather than process) measures of self-efficacy to increase validity. Founders reported their self-efficacy by indicating their degree of confidence to achieve various levels of growth in (1) earnings, (2) net worth, and (3) cash flow (4) market share, and (5) sales volume. Consistent with prior research (Bandura, Cioffi, Taylor, & Brouillard, 1988; Frayne & Latham, 1987; Robertson & Sadri, 1993), the self-efficacy instrument used a 10-point scale over a 100-point range [from 0 (not at all confident) to 100 (completely confident)] rather than the 7-point scale used to measure the other two variables of interest as described above. We summed the responses to each of the five confidence questions to create an index we used as our founder self-efficacy variable. Again, we used Cronbach’s Alpha to assess the reliability of this combination and obtained an Alpha coefficient of 0.94.

Research Design

After identifying and computing variables necessary for evaluating the usefulness of the model, we tested the model as previously described in Figure 1.

We used regression analysis to assess the ability of the model to explain founder firm performance, the dependent variable. The model predicted that founder goal-setting was positively related to founder firm performance. Furthermore, the model predicted that founder self-efficacy was positively related to founder firm performance both directly and indirectly through its effect on founder goal-setting.

Model Results

The Founder Self-Efficacy and Goal Setting Model results are presented in Figure 2 and Table 1. Figure 2 shows significant and complete support for the Model. The adjusted r^sup 2^ for the regression was .769 (p

H^sub 1^: Founder Self-Efficacy has a positive influence on Founder Goal-Setting.

It is apparent from Table 1 that founders’ goal-setting was significantly positively correlated with the independent variable founder self-efficacy with a significant (p

H^sub 2^: Founder Goal-Setting has a positive influence on Firm Performance.

Firm performance was significantly positively correlated with the independent variable founder goal-setting. Setting higher goals was associated with higher firm performance with a significant Pearson correlation coefficient of 0.772 (p

H^sub 3^: Founder Self-Efficacy has a positive influence on Firm Performance.

Firm performance was significantly positively correlated with the independent variable founder self-efficacy. Greater founder self-efficacy was associated with greater/inn performance with a significant Pearson correlation coefficient of 0.825 (p


Discussing the entrepreneurial firm, Mintzberg (1988) wrote: “All revolves around the entrepreneur. Its goals are his goals, its strategy his vision of its place in the world” (p. 534). Our research puts credit for entrepreneurial performance where it belongs – on the founder.

R^sup 2^s in the regression model were high enough to make the following prediction: Entrepreneurs who feel confident about their ability to attain high performance and who actually set goals for high performance will tend to achieve high levels of performance. This finding implies that goal setting and self-efficacy theories provide powerful potential for entrepreneurial self-empowerment. Thus, well-supported theories from the social psychology discipline have provided a new perspective for understanding entrepreneurial success.

Founders’ confidence in their ability to attain high levels of performance strongly predicted actual performance outcomes. The correlation of founder self-efficacy with performance, 0.83, was the highest of any found in this study. This figure is comparable to correlations of 0.73 found by Meyer and Gellatly (1988) and 0.74 found by Garland (1985).

Correlations between founders’ self-efficacy and goal setting were 0.65, which corresponds to Bandura’s (2000) observation that individuals with high self-efficacy seek challenges, whereas individuals with low self-efficacy avoid difficult activities, which may provide negative self-evaluations in the event of failure.

The correlation of founders’ goals with firm performance, 0.77, demonstrates the importance of “thinking big.” The literature distinguishes between opportunistic and income replacement entrepreneurs (Dunkleberg, Cooper, Woo, & Dennis, 1987). The primary difference between these two types of founders may be their goals, not their knowledge, skills, or abilities. Their goals determine whether they are establishing a hamburger stand versus a McDonald’s, a video store versus a Blockbuster’s, or a print shop versus a Kinko’s.

Our survey does not account for interim processes that help explain the transfer of founder self-efficacy to subordinate motivation and ultimate firm performance. Though increased self-efficacy levels result in an increased level of performance, several intervening processes were not captured by the survey. These intervening processes include:

1. Vicarious learning: a high self-efficacy level of the founder may produce higher efficacy levels among subordinates, where the founder acts as role model (Bandura 1986), resulting in an increased collective efficacy of the whole organization (Lindsley et al., 1995);

2. Increased organizational support: more difficult goals and high self-efficacy may result in an increased level of organizational support to subordinates to attain these new goals; founder may increase rewards (extrinsic and intrinsic) to account for goal difficulty;

3. Changed hiring practices: founder may look for similarity in values and self-efficacy levels in new hires, which may result in an increased subordinate goal commitment to founder’s goals;

4. Feedback: timely, specific, and accurate feedback plays an important role in affecting subordinate motivation; verbal persuasion consistent with performance enhances reciprocal causation between efficacy and performance (Lindsley et al., 1995).


That entrepreneurial goal setting leads to better small-firm performance implies a benefit to incorporating goal setting for self-management into entrepreneurship educational programs and recommending its use in entrepreneurial practice. Supporting entrepreneurs in learning goalsetting techniques becomes an important tool to enhance the performance of their firms.

That higher entrepreneurial self-efficacy leads to better small-firm performance has several practical implications. According to Bandura (1986), self-efficacy in an activity such as entrepreneurship develops through four processes: (1) enactive mastery or repeated performance accomplishments, (2) vicarious experience or modeling, (3) verbal persuasion, and (4) autonomic or physiological arousal. Teachers and other supporters of potential entrepreneurs, as well as practicing entrepreneurs themselves, may make use of Bandura’s suggestions in a variety of ways.

Entrepreneurs may experience enactive mastery and “learn by doing” by starting with small, low-risk ventures. The positive feedback of task achievement increases self-efficacy levels. Positive feedback creates an upward efficacy-performance relationship (Lindsley et al., 1995). After gaining confidence, they could gradually move into larger, riskier endeavors. Student venture initiation programs sponsored by educational institutions may be used to facilitate enactive mastery.

Entrepreneurial performance could also be enhanced through modeling. Entrepreneurial mentoring programs could be established at educational institutions. Student cooperative programs could put aspiring entrepreneurs in close contact with practicing entrepreneurs. Governmental agencies may institute mentoring programs to pursue social objectives, such as increasing minority and female entrepreneurship.


Our study was cross-sectional, not longitudinal. Respondents were asked their goals and self-efficacy for their most current fiscal year. Then they were asked to report performance actually attained that year. A cross-sectional design yields correlational rather than causal evidence. Does new venture success derive from high goals and high self-efficacy, or do high goals and high self-efficacy derive from success? We are planning a laboratory study with student subjects to explore this research question.

Internal validity threats may have resulted from the use of survey data in this study. It was not possible to verify the accuracy and honesty of the founders’ self-reported data, or even that the questionnaires were actually completed by the founders themselves. Because the sample consisted of small firms, no objective secondary financial data were available.

Because this study used data from small natural food stores, the issue of external validity and generalizability arose. These findings may not generalize to other occupations and industries.


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Gerry Segal Dan Borgia Jerry Schoenfeld

Florida Gulf Coast University


Gerry Segal received the Ph.D. in Management from Virginia Commonwealth University. His entrepreneurial experience began when he started a commercial real estate brokerage and property management firm. Later, he founded two leading-edge grocery stores featuring natural and gourmet foods. Currently an Assistant Professor of Management and Director of the Institute for Entrepreneurship at Florida Gulf Coast University, Gerry’s teaching and research interest is in the area of entrepreneurship and small business management.

Dan Borgia, discipline Leader for the Finance Department and Associate Professor of Finance, received his Ph.D. from Kent State University. Dan is a registered investment advisor and i s involved in financial planning. He has published in the areas of exporting and firm size and economic development. His interest in developing the finance curriculum at FGCU has resulted in research output in the area of technology use in the finance classroom.

Jerry Schoenfeld is the Chair of the Management and Marketing Department and an Associate Professor of Management in the College of Business at Florida Gulf Coast University. He is also Director of the Institute for Advances in Human Resources, which is part of FGCU’s Center of Leadership and Innovation. Jerry earned his doctorate degree from the University of Pittsburgh. His research interests are in the areas of career development and performance management.

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