social information processing approach to starting a new venture

A SOCIAL INFORMATION PROCESSING APPROACH TO NEW VENTURE CREATION Linda F. Edelman Assistant Professor – Strategic Management Bentley College 175 Forest Street Waltham, MA 02xxx (O) 781/891-2530 (F) 781-894-4257 e-mail ledelman@bentley.edu October 2004 The author is grateful to Tatiana Manalova, Helena Yli-Renko, and Candy Brush for their helpful suggestions. 2 A SOCIAL INFORMATION PROCESSING APPROACH TO NEW VENTURE CREATION ABSTRACT Only half of all potential business founders succeed in creating a new enterprise, and over 20% of those entrepreneurs that create new firms will go out of business within the first two years. Yet, despite these distressing statistics, in 2002, approximately 8 percent of the U.S population, or over 2.3 million individuals, took some action to start a new business. This raises the question of why, in the face of such adversity, do entrepreneurs continue to start new firms. To better understand the motivations behind new venture creation, entrepreneurship researchers have recently begun to apply a cognitive perspective by examining the underlying human factors that influence the start-up decision. In this paper, we also use a cognitive approach to examine the attitudes that nascent entrepreneurs have towards starting a new venture. To do this, we employ social information processing theory, which emphasizes the importance of the social environment in the development of individual attitudes. Our findings demonstrate strong support for adopting a social information processing perspective to understanding the attitudes of nascent entrepreneurs and therefore lend support to a cognitive approach to understanding entrepreneurship. 3 A SOCIAL INFORMATION PROCESSING APPROACH TO NEW VENTURE CREATION 1. INTRODUCTION In 2002, approximately 8 percent of the U.S. population, or over 2.3 million individuals, took some action to start a new business and 40 percent of American adults are self employed during their lifetime (Reynolds & While 1997; Reynolds, el al, 2002). However, only half of all potential business founders succeed in creating a new enterprise and fewer than one in ten of them are able to make their organizations grow (Duncan & Handler, 1994; Reynolds & White, 1997). In addition, of those that are able to actually create a new venture, statistics indicate that over 20% of these are likely to fail within the first two years. So why do entrepreneurs continue to create new firms? The emerging literature on entrepreneurial cognition offers some insight on the fundamental question of why individuals choose to become entrepreneurs (Baron, 2004). While previous new venture literature has primarily focused on the activities undertaken by entrepreneurs when starting new ventures (Reynolds & Miller, 1992; Gatewood, Shaver & Carter, 1995; ;Carter, Gartner & Reynolds, 1996; Reynolds, 1997), research on organizational cognitive examines “how organization members model reality and how such models interact with behaviors” (Academy of Management, 1998). Therefore, using entrepreneurial cognition as a lens to better understand new venture creation offers the promise of answering questions that examine the underlying motivations of nascent entrepreneurs. 4 One cognitive model that has been widely used in social science research is the social information processing model (Salancik & Pfeffer 1978). The social information processing model emphasizes the role that the social situation plays in the formation of individual attitudes. The model suggests that individual characteristics, in conjunction with perceived characteristics of the social environment, lead to the development of individual attitudes. In this paper, we employ a social information processing framework and examine the factors that influence the nascent entrepreneur’s attitudes towards entrepreneurship. In doing so, we apply a new theoretical lens to the fundamental question of new venture formation. In addition, we also answer recent calls for a more cognitive approach to the study of entrepreneurship (Baron, 2004, Pitt, 1998). 2. THEORY 2.1 Cognition and the New Venture Creation Literature One of the seminal questions in entrepreneurship is “what leads people to become entrepreneurs?” Initially, it was addressed by looking at what has become to be known as “trait research.” Emerging from the early psychological research on needs (McClelland, 1961); entrepreneurial trait research focused on the search for a set of stable personality characteristics that distinguished entrepreneurs. Trait factors included characteristics such as age, marital status, and family background. While the best of these studies compared entrepreneurs to non-entrepreneurs (i.e., Collins & Moore, 1964) or compared groups of entrepreneurs (i.e., Smith, 1967), the general consensus is that research on entrepreneurial traits did little to advance our knowledge of entrepreneurship, and that 5 entrepreneurship researchers would be better served focusing on what entrepreneurs did as opposed to who they were (Gartner, 1988; Shaver & Scott, 1991). While the majority of recent research on entrepreneurship has focused on the actions of the entrepreneur and the entrepreneurial firm, it can be argued that that the research on new ventures has in some way continued to have at its core an emphasis on the cognitive aspects of the entrepreneur. For example, the notion of entrepreneurial intentions – which is the view that individuals beliefs influence the intentions of the entrepreneur (Shapero, 1982) - can be found in the well regarded model of new venture creation by Katz and Gartner (1988) as well as the theoretical work of Bird (1988); Katz (1992), and Krueger and Brazeal (1994). In addition empirical work by Kolvereid (1997) provides support for the importance of entrepreneurial intentions to start-up success. Moving away from intentions, other scholars have used the idea of entrepreneurial cognition in their work as well. In the international context, McGrath and MacMillan (1992) found that the content of entrepreneurial beliefs is similar across cultures. Cooper et al (1988) found the entrepreneurs believe their own chances for success are very high – higher than the success chances they perceive for other firms. Gatewood et al (1995) found that the cognitive beliefs associated with entrepreneurial persistence vary by gender and Markman, Balkin and Baron (2000) found significant differences in selfefficacy between technical and non-technical entrepreneurs. Therefore, while recent scholarship calls for a focus on the cognitive aspects of entrepreneurial behavior (Baron, 2004), it can be argued that cognition has always been an important element of the research on new venture creation (see Forbes, (1999) for a comprehensive review of the cognitive, new venture creation literature). 6 2.2 The Social Information Processing Approach The social information processing approach was developed by Salancik and Pfeffer (1978) with the intention to add the importance of the social environment to the literature on individual motivation. Prior motivation literature had focused on needssatisfaction (Maslow, 1942; McClelland, 1961). In these previous models, individual attitudes and behaviors are a function of the personal characteristics of the individual. Situational elements were addressed as to their potential to assist in, or frustrate the attainment of a particular need. Therefore motivation was viewed as a function of both the need as well as the need-fulfilling or frustrating properties of the situation. In contrast to the needs-satisfaction framework, the social information processing perspective begins with the premise that individuals adapt their attitudes and beliefs to their social environment as well as to the reality of their own past and present behavior and situation (Salancik & Pfeffer 1978:226). This suggests that to learn about an individual’s attitudes one should begin by examining the past behavior and the social environment in which that individual is operating. Perceived Social Environment. Individual attitudes are developed as a function of the relevant information that is available to the individual at the time that they display the attitude. Relevant information can differ from individual to individual, but all relevant information must be salient, in that the individual must be aware of the information at the time at which they are forming their particular attitude. One critical source of information is the individual’s social environment. The social environment provides cues which individuals use to interpret events, as well as providing information which helps develop attitudes. In addition, the social environment affects the individual’s perception 7 of prior experiences, in that it can either enhance or alternatively downplay those experiences. In conjunction with past behavior and the social environment, individual attitudes are also influenced by the task environment in which the individual operates. While the task environment is not the central focus of the social information processing model, Salancik and Pfeffer (1978) recognize the importance of the organization’s immediate environment on the development of individual attitudes and actions. While Salancik and Pfeffer (1978) provide researchers with a starting point with respect to including social and cognitive dimensions to our overall understanding of organizational processes, their model leaves many unanswered questions. In an enhancement to original Social Information Processing theory, Blau and Katerberg (1982) argue that the process of developing the social cues that lead to the individual’s perception of a social environment are not well articulated in the Salancik and Pfeffer (1978) model. They argue that in addition to previous experience of the individual, the salience of the social cue, the credibility of the source, the ambiguity of the task and differences in the personality of the individual as well as possible moderation effects, need to be considered when examining the social environment. While like Salancik and Pfeffer, (1978) Blau and Katerberg (1982) limit their social context to job design, and hence their antecedents of the social environment are not germane across all contexts, their work offers important extensions to the original model. In addition to Blau and Katerberg (1982), Thomas and Griffin (1983) review 10 articles using the social information processing framework to understand employee perception of a particular task. While they find problematic measurement issues around 8 the issue of task design, more importantly for our research, they argue that that the social information processing framework be expanded to other areas of organizational studies outside the strict confines of job related issues. Breaking out of the confines of job design, Rice and Aydin (1991) apply a social information processing framework to attitudes towards new technologies. They examine network proximity and conclude that individual attitudes are influenced by the attitudes of proximate sources of social information. More recently, Gundlach, Douglas and Martinko (2003) use a social information processing perspective to develop their theory on whistle blowing in organizations. They posit that individual’s attributions and responsibility judgments in conjunction with a cost/benefit analysis with respect to acting each contribute to the decision to blow the whistle on wrongdoing in organizations. In each of these studies we see extensions to the original social information processing framework. The first two studies follow Salancik and Pfeffer (1978) in their focus on job design, but expand the original framework. The second set of studies moves beyond the confines of job design, applying a social information processing approach to other areas of organizational studies. However, to date, no one has used the social information processing approach to study the cognitive and social environment surrounding attitudes of nascent entrepreneurs towards new venture creation. It is to that task that we now turn. 3. HYPOTHESES In developing our social information processing framework, we draw on the original relationships suggested by Salancik and Pfeffer (1978). However, as suggested by Blau and Katerberg (1982) we augment those relationships by adding the previous 9 experience of the entrepreneur, the credibility of the source of the information, the personal characteristics of the entrepreneur, and the interaction between the entrepreneur’s past experience and personal characteristics. 3.1a. Previous Experience of the Entrepreneur One of the key elements of entrepreneurial attitude is the previous behavior or past experience of the entrepreneur. In his theory of self-perception, Bern (1972) argued that behavior can serve as an important source of information when constructing attitude statements. Past experience affects entrepreneurial attitudes in two important ways. Past experience of the entrepreneur directly affects entrepreneurial attitudes in that entrepreneurs draw on their own unique set of previous experiences when developing their attitudes about starting a new venture. For example, Johannisson (1988) in a study of Swedish entrepreneurship found that over half of the new ventures that were formed supplied either their previous employers or their previous employer’s customers. Cooper and Dunkelberg (1987) found that 39 percent of the 890 members of the National Federation of Independent Businesses were in the same product/service line and another 27 percent were in a similar line. Finally, in the German high technology sector, Picot et al (1989) found that most founders had previous work experiences in their own industrial sector. Therefore we hypothesize: Hypothesis 1a: The previous experience of the entrepreneur has a positive and significant impact on the entrepreneur’s attitudes about starting a new venture. However, in the social information processing model, the past experience of the entrepreneur also indirectly affects entrepreneurial attitudes of the social environment. By this we mean that the entrepreneur draws on his past experiences to construct the 10 social environment of which he is a part (Berger & Luckman, 1967; Weick, 1977). Therefore, it is the past experiences of the entrepreneur which shapes the current and future perceptions of the social environment of the entrepreneur. Hence we propose: Hypothesis 1b: The previous experience of the nascent entrepreneur has a positive and significant impact on the perceived social environment of the entrepreneur. 3.2b. Source Credibility During start-up, a nascent entrepreneur relies on formal as well as informal advice. Formal advice comes from sources such as accountants, lawyers, potential customers and suppliers, as well as from published sources such as Dun and Bradstreet, and Moody’s who publish reports on the industry level as well as on specific firms (Timmons, 1990). In contrast, informal advice for fledging entrepreneurs is often provided by former business colleagues, as well as by family and friends (Colbert & Butler, 2004). All of the sources have the potential to influence the perceptions of nascent entrepreneurs. Therefore: Hypothesis 2: The greater the creditability of the source of information the more likely that information source will positively affect the perceived social environment of the nascent entrepreneur. 3.2c. Self-Efficacy of the Entrepreneur Self-efficacy is the individual’s cognitive estimate of his or her “capabilities to mobilize the motivation, cognitive resources and courses of action needed to exercise control over event in their lives” (Wood & Bandura, 1989). A central tenet in social learning theory (Bandura, 1977a, 1982), is that people with high self-efficacy are more 11 willing to expend effort on a particular task and show more persistence in the face of obstacles. Recently, research on self-efficacy has been extended to entrepreneurship. Extending Bird’s (1988) framework of conscious and intended actions in new venture creation, Boyd and Vozikis (1994) argue that self-efficacy is an important explanatory variable that determines both the strength of entrepreneurial intentions as well as the likelihood that those intentions will translate into entrepreneurial actions. More recently, in a study on career aspirations of entrepreneurs versus managers, Chen, Greene and Crick (1998) found that business founders have high self-efficacy in the areas of risktaking and innovation than did non-business founders. Building upon Chen et al, Markman, Balkin and Baron (2002) found that self-efficacy was a distinguishing factor between technological entrepreneurs and technological non-entrepreneurs. Therefore, we suggest that Hypothesis 3a: The self-efficacy of the entrepreneur has a positive and significant impact on the entrepreneur’s attitudes about starting a new venture. However, the social information processing model not only predicts direct effects between the individual’s cognitive resources and attitudes, it also argues that the selfefficacy of the entrepreneur also affects the entrepreneur’s perception of the social environment. Therefore: Hypothesis 3b: Greater-self-efficacy will have a positive and significant effect on the entrepreneur’s perception of the social environment. Hypothesis 3b: Greater self-efficacy coupled with the past experience of the entrepreneur, will have a positive and significant effect on the entrepreneur’s perception of the social environment 12 3.2d. Perception of the Social Environment Similar to past experience, the social environment in which the entrepreneur is starting the new venture has both a direct and indirect effect on the entrepreneur’s attitudes about the start-up process. With respect to the direct effect of social environment on attitudes, consider the nascent entrepreneur who perceives that individuals who are self-employed, are well respected in the community. If the nascent entrepreneur is motivated by a desire to be respected, then the perception of respect has a direct effect on the attitudes that the entrepreneur has about starting up a new venture. Hence we hypothesize: Hypothesis 4a: The perceived social environment has a positive impact on the attitudes of the entrepreneur about starting a new venture. However, not only does the social environment affect the attitudes of nascent entrepreneurs it also affects the nascent entrepreneur’s perception of the task environment. Salancik and Pfeffer (1978) suggest that the social environment provides cues which individuals use to interpret events. Examples of these events for nascent entrepreneurs include the entrepreneur’s perception of potential customers, suppliers, and competitors. Therefore we hypothesize: Hypothesis 4b: The perceived social environment has a positive impact on the entrepreneur’s perception of the task environment of the new venture. 3.2e. Task Environment Following the Industrial Organization Economics tradition, the five critical elements of the task environment, as identified by Porter (1980; 1985), have proved significant in shaping a generation of strategic management researchers. The field of 13 entrepreneur has focused on the task environment as well, in studies that examine generic strategies (Chaganti, et al., 1989; Carter, Stearns, Reynolds & Miller, 1994; McDougall, et al., 1994). While empirical studies have linked elements of the task environment to firm performance, the perception of the relative strength of the various elements which comprise the task environment, are a critical factor is determining attitudes towards entrepreneurship among nascent entrepreneurs. Therefore: Hypothesis 5: The task environment has a positive impact of the attitudes of the entrepreneur about starting a new venture. 4. METHODS 4.1 Sources of Data. The PSED is a longitudinal study of randomly selected nascent entrepreneurs across all industrial sectors. Motivated by a lack of understanding of who starts businesses, what process they undertake when starting a new business, and why some new businesses succeed, while others fail, the objective of the PSED is to gain an introspective understanding of how nascent entrepreneurs create new businesses and what activities and behaviors they engage in during the process of enterprise creation. Nascent entrepreneurs were defined as individuals involved in attempting to start a new business within the past 12 months on their own (i.e., autonomous startups) as opposed to those doing so with sponsorship from existing firms. Further, to qualify for inclusion in the sample, the effort had to have still been in the startup or gestation phase at the time of initial contact (i.e., established infant firms were not eligible). This screen eliminated 27% of the initial pool of autonomous startups. The nascent entrepreneurs were identified from an earlier representative large scale screening of national population of 14 adults (18 years or older) residing in the 48 contiguous states of the USA. The nascent entrepreneur respondents, who were given a monetary inducement of $25 for survey completion, were asked a series of questions about the developmental details of their business in interviews that lasted between 35 to 90 minutes (60 minutes was average). The data used in our paper is from the mixed gender sample only (n = 446). It then reduces to n = 338, based on a series of selection rules developed by Shaver, Carter Gartner and Reynolds, (2001) to ensure a nascent-only sample. It is on this data that we present descriptive statistics and our analysis. 4.2 Measures Both nominal (i.e., dichotomous) as well as continuous (ordinal and interval) operational measures are utilized in this study. Previous Experience of the Entrepreneur. The experience of the entrepreneur was measured by two questions that examined the previous work experience and the entrepreneur’s previous experience starting a business. These questions were dichotomous, objective measures and were summed; no alpha calculations are available for this variable. Source Credibility. Following Blau and Katerberg (1982) we define source credibility as expertise and/or trustworthiness of the source of the information. To measure the credibility of the source of the information we used a set of four questions that asked about the influence of friends and family, potential or existing customers, existing supplier or distributors, and potential or existing investors/lenders on the creation of the business idea. These questions were dichotomous measures and were summed; no alpha calculations were available for this variable. 15 Self Efficiency of the Entrepreneur. Following Markman el al (2001) who found that self efficiency – belief in ones ability to muster and implement necessary resources, skills and competencies to attain a certain level of achievement on a given task – was a key explanatory factor in the propensity of patent holders to start a new business We used a set of six questions to examine the entrepreneur’s perception of his personal abilities; I can do anything I set my mind on doing, I do every job as thoroughly as possible, I have no trouble making and keeping friends, plans are almost certain to work, I usually know what is appropriate, I am a good judge of other people. The measure was factor and reliability analyzed. Factor loadings were a minimum of .45 and Cronbach’s alpha was .69 about the minimum threshold set for reliability (Nunnally, 1970) (see Table 1). Previous Experience X Self Efficacy. Following Blau and Katerberg (1982) we tested for interaction effects among the antecedents of perception of the social environment. While we tested for all possible interactions, for parsimony we only included the significant interaction terms in our model. Perception of the Social Environment. Following the definition of social environment by Salancik and Pfeffer (1978:226) - providing cues which individuals use to interpret events - we used a set of six questions that examined the nascent entrepreneur’s perception of the fledgling firm’s ability to attract employees, obtain start-up capital, obtain working capital, deal with distributors, obtain bank’s help and obtain venture capitalists’ help. The measure was factor and reliability analyzed. Factor loadings were a minimum of .54 and Cronbach’s alpha was .79, above the minimum threshold set for reliability (Nunnally, 1970) (see Table 1). 16 Task Environment. The importance of the task environment has been well documented in the strategic management literature (Porter, 1980, 1985). To measure the fledging firm’s task environment we used a set of six questions that asked the examined the nascent entrepreneur’s perception of the importance of quality product and services, serving markets missed by others, superior location and customer convenience, contemporary attractive products, developing new or advanced product technology and developing new or advanced process technology. The measure was factor and reliability analyzed. Factor loadings were a minimum of .43 and Cronbach’s alpha was .65, above the minimum threshold set for reliability (Nunnally, 1970) (see Table 1). Entrepreneurial Attitudes. The dependent variable - attitudes about entrepreneurship follow Salancik and Pfeffer’s (1978) who argue that attitudes are a function of the social and task environments in which the new venture will operate. To measure the nascent entrepreneur’s attitudes about entrepreneurship we used a set of 10 questions that examined the entrepreneurs perception with respect to the level of encouragement that young people get to start their own business, the level support provided by community groups, bankers and investors and the state and local government towards entrepreneurs, the respect that people who start their own business receive, whether friends and family have started their own firms, how well the local media does in covering new businesses and whether community leaders are people who own their own businesses. The measure was factor and reliability analyzed. Factor loadings were a minimum of .49 and Cronbach’s alpha was .75, above the minimum threshold set for reliability (Nunnally, 1970). 17 Table 1 presents mean, standard deviation, Cronbach’s alpha scores and correlation matrix for the independent variables. -----------------------------------Insert Table 1 about here -------------------------------------- 5. ANALYSIS AND RESULTS 5.1 Descriptive Statistics and the Structural Equation Model The sample is comprised of nascent entrepreneurs; that is those individuals who are actively in the process of creating a new venture but have not yet started a new firm. There are more men starting a business in this sample (n = 205) as compared with women (n = 133) and while all ages were in the process of starting a new venture, 31.4% of nascent entrepreneurs were between the ages of 35 and 41. With respect to race and education, the majority of the sample was white (73.4%) and the majority of nascent entrepreneurs in the sample finished high school and had some form of further education, but not a formal college degree (33.4%). Finally, 58.3% of the respondents were married at the time of the inquiry. To best capture the theoretical interdependencies between the independent and dependent variables, we analyzed the data using Structural Equation Modeling (AMOS 5.0 statistical package). This procedure allows for a fine-grained analysis of the hypothesized relationships with the context of the entire model. Structural equation modeling is a particularly attractive choice when testing mediating variables in that all of the relevant paths are directly tested and complications such as measurement error and feedback are directly incorporated into the model (Baron & Kenny, 1986). 18 Before running the model, we checked our data for possible abnormalities. We followed Kline (1998:89) and checked the data for missing data points, the normality of the data distribution, and multi-colinearity using the SPSS statistical data analysis package. To handle the problem of missing data, we used mean substitution, which is a technique in which variable means are used to replace missing values (Afifi & Elashoff, 1966). Mean substitution is a popular method of managing missing values in structural equation modeling. In addition, it is a conservative technique in that it makes the data less reactive. To increase the robustness of our analysis, we checked the data for multicollinearity. We found multicollinearity with the interaction term and so we centered the term to eliminate this problem. After centering, we rechecked the variance inflation factor (VIF) statistic, and found it was less than 1.1, which is well under the 10.0 cut-off that indicates problematic data collinearity (Kleinbaum, Kupper & Muller, 1988). Therefore, we can conclude that our data do not violate any multicollinearity assumptions. To test our hypothesized relationships we ran a structural equation model. The hypothesized model tests the relationship between the observed variables previous experience of the entrepreneur, source credibility, personal skills of the entrepreneur, the interaction term, previous experience and personal characteristics, the perception of the social environment, the effects of the task environment on the dependent variable attitudes about entrepreneurship. For the hypothesized model, the chi-square is not significant (χ2 = 16.63), indicating that the model fits the data. 19 We assessed the model’s fit to the data using multiple model-fit criteria to rule out measuring biases inherent in the various methods (Hair, Anderson, Tatham & Black, 1995). The chi-square divided by the degrees of freedom is .1.66, which is under the suggested ratio of two, for the hypothesized indirect model, and the p-value is .08, which is greater than the suggested .05 (Schumacker & Lomax, 1996). The model’s adjusted goodness of fit (AGFI) was .96, indicating a good fit with the data (Hoyle, 1995). The goodness of fit index (GFI) was .99, well above the .90 acceptable level (Hair, et al., 1995). Hotelling’s critical N was 471, well over the 200 mark considered acceptable indicating that the data fits well with the model (Schumacker & Lomax, 1996). Table 2 shows the multiple fit statistics for the hypothesized model; figure 1 illustrates the structural equation model. ------------------------------------------Insert Table 2 and Figure 1 about here -------------------------------------------In hypotheses 1-5 we make predictions about the specific paths in the hypothesized model. To test these hypotheses we examined the path coefficients, and the p-values. In hypothesis 1a we predicted that the previous experience of the entrepreneur will have a positive effect on the entrepreneur’s attitudes about entrepreneurship. The path is not significant (path estimate = .004; one-tailed p-value = .90) indicating no support for this hypothesis. In hypothesis 1b we predicted that the previous experience of the entrepreneur will have a positive impact on the entrepreneur’s perception of the social environment. The path is not significant (path estimate = .05; one-tailed p-value is .08) indicating no support for this hypothesis. 20 In hypothesis 2 we predicted that the greater the credibility of the source of information, the more likely that the information from that source will positively affect the entrepreneur’s perception of the social environment. The path for this hypothesis is significant (path estimate = -49; one-tailed p-value is .05) but negative indicating that the relationship between source credibility and the social environment is different than we predicted. In hypothesis 3a we predicted that the greater the self-efficacy of the entrepreneur, the more likely that this will positively affect the entrepreneur’s attitudes about entrepreneurship. This path is not significant, (path estimate = .16; one-tailed pvalue = .14), indicating no support for this hypothesis. In hypothesis 3b we predicted that the greater the self-efficacy of the entrepreneur the more likely that this will positively affect the entrepreneur’s perception of the social environment. The path is highly significant for this hypothesis (path estimate = .30; one-tailed p-value = .002) indicating strong support for this hypothesis. In hypothesis 3b we predicted that the interaction variable personal abilities coupled with past experience would positively affect the entrepreneur’s perception of the social environment. The path is significant for this hypothesis (path estimate = .82; one-tailed p-value = .02) indicating support for this hypothesis as well. In hypothesis 4a we predicted that greater perception of the social environment is positively related to the entrepreneur’s attitudes about entrepreneurship. This hypothesis is the essence of the social information processing model. The path is significant for this hypothesis (path estimate = .13; one-tailed p-value = .02) indicating support for this hypothesis. In hypothesis 4b we predicted that the entrepreneur’s perception of the social 21 environment would positively influence his perception of the task environment. The path is not significant for this hypothesis (path estimate = -.01; one-tailed p-value = .69) indicating no support for this hypothesis. In hypothesis 5 we predicted that the entrepreneur’s perception of the task environment will positively affect his attitudes towards entrepreneurship. The path is significant (path estimate = .14; one-tailed p-value = .04) indicating support for this hypothesis. In summary, we find good support for our overall model indicating that the social environment is a critical component in the entrepreneur’s overall attitudes about entrepreneurship. In addition, we find significant support for many of the individual paths in the model, thereby lending support to many of the tenets of the social information processing approach. 6. DISCUSSION Our goal in this paper was to apply a social information processing framework to the phenomena of new venture creation in order to gain to gain new insights about the role of entrepreneurial cognition in the development of attitudes about entrepreneurship held by nascent entrepreneurs. We drew upon ideas that emphasized the importance of the social environment (Slancik and Pfeffer, 1978; Blau and Katerberg, 1982) to jointly examine the effects and interrelationship between individual characteristics, individual perceptions, the social and task environments and the development of attitudes about entrepreneurship. In doing so, we have attempted to extend our understanding with respect to the motivations of nascent entrepreneurs in starting a new venture. Our findings indicate a number of theoretical and practical implications in three key areas: the 22 importance of self-efficacy; the distinction between the social and the task environment and the interplay between the social context and the task environment in the development of entrepreneurial attitudes. The importance of self-efficacy, source credibility and previous work experience. Consistent with previous work in self-efficacy (Chen, et al, 1998; Markman, et al 2002) our findings indicate that self-efficacy plays a critical role in the development of the nascent entrepreneur’s perception about the social context in which the new firm will be operating. We found that self-efficacy was significantly related to social context and the self-efficacy coupled with previous experience was also a significant predictor of social context. This finding is consistent with behavioral psychology which predicts a positive linkage between self-efficacy and the entrepreneur’s perceived control (Shaver & Scott, 1991) as well as with the literature on entrepreneurial risk taking which argues that activities undertaken by entrepreneurs to mitigate risk may act as a barrier to start-up (Bird, 1989; Baron, 1998). Interestingly, there was no significance between self-efficacy and attitudes about starting a new venture. This may be due to the dynamic differences in these two concepts. Attitude is a passive, intellectual concept that describes how a person thinks or feels about a particular subject. In contrast, self-efficacy is an active “can-do” approach that describes the abilities of the entrepreneur. It may be that an active confident style that is projected by the actions of the nascent is different than the more passive attitudes that the person possesses. However, defying theory was the significant negative relationship that we found between source credibility and social context. While it is possible that this is a function 23 of our data, in that we only examined source credibility from the informal perspective of friends and family, it is also possible that this is a reality of the entrepreneurial process. It seems likely that when a nascent entrepreneur becomes committed to a start-up idea, they are single-minded in the pursuit of their dream. Hence they discount to a great extent, any information that may sway them from reaching their objective, no matter how credible the source. The popular press is replete with stories of how tenacious entrepreneurs started highly successful enterprises which were deemed impossible in the initial phases 1 . Therefore, at least with respect to the social environment of new venture creation, it seems plausible that source credibility is less important than in other contexts. Perceptions of social context are distinct from perceptions of the task environment. Our findings indicate that the nascent entrepreneur’s perceptions of the social context are not directly related to perceptions of the task environment. This suggests a modification in the social information processing model as proposed by Salancik and Pfeffer (1978), who posit a relationship between the perception of the social context and the task environment. This finding, while inconsistent with theory, is not surprising. As information has become easier and cheaper to obtain, it is unproblematic for even resource-strapped nascent entrepreneurs to acquire credible, objective information about the task environment. This suggests that information availability, in this case about the task environment, alters individual’s perceptions; which is a fundamental proposition of information systems research (Howells, 1966). The importance of the social environment and the task environment in determining nascent entrepreneur’s attitudes towards entrepreneurship. Finally, our findings indicate Consider the beginning of Federal Express in which the founder proposed the idea in a graduate school course and received a “D” on his paper, or alternatively, the beginning of U-Haul, where an enterprising entrepreneur started a successful moving company on almost no resources (Dew & Sarasvarthy, 2001) 1 24 strong support for the relationship between social environment, task environment and attitudes towards entrepreneurship. This is consistent with social information processing theory which predicts a direct and positive relationship among these variables. Therefore, as suggested by Salancik and Pfeffer (1978), examining the social dynamics of a particular situation, in conjunction with the more objective elements of the task environment, is critical for developing an understanding of attitudes. In addition to supporting the social information processing model, this finding also lends support for adopting a cognitive perspective on new venture creation. A cognitive approach focuses directly on the cognitive mechanisms through which individuals acquire, store and transfer information (e.g., Matlin, 2002). Cognitive approaches to entrepreneurship are potentially beneficial due to the importance of the individual and specifically, the owner/founder in entrepreneurial ventures. If, as suggested (Baron, 2004), the cognitive approach can shed light on key aspects of human behavior, then it has the potential to make a substantial contribution to our understanding of the start-up process. This paper makes an important contribution to the existing research on entrepreneurial cognition by applying an established framework in organizational theory to the difficult and ongoing issues of new venture creation. One of the most perplexing questions in entrepreneurship is the question of why new ventures are created. This study adds a cognitive perspective to that question by looking at the attributes of the entrepreneur coupled with the social and task environment and how they relate to nascent entrepreneurs attitudes about starting a new venture. 25 7. IMPLICATIONS AND CONCLUSIONS Each year a substantial number of individuals are going to be engaged in the process of starting a new venture. However, many these individuals will never start a business, or if they do start a firm, will go out of business within six years. This indicates that the process of starting a new firm is fraught with uncertainty, so why do people engage in start-up activities? While there is no single answer to this question, the social information processing framework provides an established theoretical lens through which to examine the attitudes of nascent entrepreneurs – those individuals who are engaged in the start-up process. From our study of the start-up attitudes of 338 nascent entrepreneurs who are, by definition, in the process of starting a new venture, we have two main conclusions: (1) the importance of self-efficacy on developing perceptions and (2) the independently significant relationship between the social environment, the task environment and entrepreneurial attitudes As with all studies, this study has limitations. We chose to stay within the confines of the social information processing framework as articulated by Salancik and Pfeffer, (1978) and extended by Blau and Katerberg (1982). In doing so, we did not include resources in our analysis. However, given the strong support that the resourcebased view has received in entrepreneurship research (c.f. Chandler, & Hanks, 1994; Brush & Chaganti,. 1999, Edelman, Brush & Manolova, forthcoming) it seems likely that resource levels and timing of acquisition of resource profiles could have a significant impact on nascent entrepreneur’s attitudes about starting a new venture. An interesting extension to this work would be to include resource levels in the framework and see if 26 attitudes towards creating a new venture are resource dependent, or if nascent entrepreneur’s attitudes are more in line with the theories suggesting that entrepreneurs are bricoleurs (Baker, Miner & Eesley, 2003; Garud & Karnøe, 2003). In addition to a contribution to scholarship, this study has important implications for nascent entrepreneurs who are engaged in the process of starting a new venture. 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The Social Psychology of Organizing, Reading, MA: Addison-Wesley 31 Table 1 Descriptive Statistics, Reliability and Zero-Order Correlations a b c Scale Source Credibility Self Efficacy/ Previous Experienced Self Efficacy Previous Experience Task Environment Social Environment Mean .66 1.53 1.95 5.9 2.19 2.02 SD .93 .73 2.69 8.4 3.4 5.06 1 NA 2 .082 NA 3 -.076 .163** .69 4 .009 .285** .056 NA 5 -.058 -.082 .080 -.027 .65 6 -.090 .154** .185** .119* -.022 .79 a. n = 338; alpha correlations replace all 1 values b. * Correlation is significant at the 0.05 level (2-tailed); ** Correlation is significant at the 0.01 level (2tailed) c The variable range for self efficacy, task environment and social environment is between 1 – 5. d. The interaction term self-efficacy and past experience is presented using the logarithmic function. 32 Table 2 Structural Parameters, Hypotheses and Model Measurement Values a Path H1a. Previous experience → Attitudes about entrepreneurship H1b Previous experience → Perceived social environment H2: Source Credibility → Perceived social environment H3a: Self-efficacy → Attitudes about entrepreneurship H3b: Self-efficacy → Perceived social environment H3c: Self-efficacy /Previous Experience → Perceived social environment H4: Perceived social environment → Attitudes about entrepreneurship H4a: Perceived social environment → Perceived task environment H5: Perceived task environment → Attitudes about entrepreneurship Recommended value (Hair et. al., 1995) 16.63 10 1.6 .08 .99 .96 .92 471 ≤ 2.0 ≥ .05 ≥ .90 ≥ .90 ≥ .90 ≥ 200 (1) Hypothesized model .45 .08 -.05* .07 .002** .02* .01** .34 .04* Model statistics χ2 degrees of freedom χ2/df P GFI AGFI IFI Hotellings Critical N * p < .05; ** p < .01; *** p < .001; a. Recommended values derived from Hair, Anderson, Tatham, & Black, 1995 33 Figure 1 A SOCIAL INFORMATION PROCESSING MODEL OF NASCENT ENTREPRENEUR’S ATTITUDES b TOWARDS ENTREPRENEURSHIP H4a SELF EFFICIACY/ PREVIOUS EXPERIENCE SOURCE CREDIBILITY H2 H3b SELF EFFICIACY H1b H1a PREVIOUS EXPERIENCE H3a H3c H4b SOCIAL CONTEXT TASK ENVIRONMENT H5 ATTITUDES a The figure depicts a structural model with standardized maximum likelihood estimates. Path coefficients for error terms were set at one. b Solid lines indicate significant paths.