27  THE MODERATING EFFECT OF FAMILY-OWNERSHIP ON FIRM PERFORMANCE: AN EXAMINATION OF ENTREPRENEURIAL ORIENTATION AND SOCIAL CAPITAL Jeffrey M. Campbell The University of South Carolina jcampbell@hrsm.sc.edu Nathan Line The University of Tennessee, Knoxville nline@utk.edu Rodney C. Runyan The University of Tennessee, Knoxville rrunyan@utk.edu Jane L. Swinney Oklahoma State University jane.swinney@okstate.edu ABSTRACT Within the small business literature, a number of recent studies have examined the importance of entrepreneurial orientation (EO) and the development of social capital (SC) as each contributes to a firm’s performance. While it is generally accepted in previous studies that each of these constructs positively affects firm performance, relatively less attention has been paid to potential moderating factors that can affect these relationships. The purpose of our research is to address one such moderator, family ownership. Using structural equation modeling (SEM) to test the moderating effect of family ownership on the relationships among entrepreneurial orientation, social capital, and firm performance, our results show that the effects of EO and SC vary depending upon whether the firm is family-owned or non-family owned. Implications of these findings and future research directions are provided. Keywords: family ownership, entrepreneurial orientation, social capital, firm performance. INTRODUCTION Within entrepreneurship literature, the respective roles of social capital and entrepreneurial orientation as predictors of firm performance have been pursued extensively. Concerning social capital (SC), a recent meta-analysis of 65 articles published over the last 15 years found strong S TRATEG   Y  JOURNAL OF SMALL BUSINESS  mailto:jcampbell@hrsm.sc.edu mailto:nline@utk.edu mailto:rrunyan@utk.edu mailto:jane.swinney@okstate.edu Journal of Small Business Strategy Volume 21, Number 2 28  evidence for a link between SC and firm performance at the general firm level (Westlund and Adam, 2010). The particular domain in which this construct is explored, however, is often quite specific. Prior research has tended to model the relationship between SC and firm performance, making such varied analytical distinctions as spatial dimensions (Schutjens and Völker, 2010); industry (Maurer and Ebers, 2006); firm size (Wei-Ping and Alicia, 2005); strategic growth initiatives such as initial price offerings (Florin, Lubatkin, and Schulze, 2003); and economic conditions (Manev, Gyoshev, and Manolova, 2005). The emphasis on varying dimensions of firm categorization suggests that such distinctions are important and that the relationship between SC and firm performance may vary, based upon the domain in which the study is conducted. Thus, the generally accepted positive relationship between the two constructs may not be generalizable to every type of firm. Additionally, a number of recent studies have demonstrated the importance of entrepreneurial orientation (EO) as it relates to a firm’s performance (Kreiser and Davis, 2010; Runyan, Droge, and Swinney, 2008; Wiklund and Shepherd, 2005). Again, the preponderance of the literature suggests a positive relationship between the two. Similar to the findings for social capital, it is generally accepted that higher levels of EO are also associated with increased firm performance. Runyan, Huddleston, and Swinney (2006) found a positive relationship between EO and SC as predictors of firm performance, but found no significant differences between male- and female-owned firms. Research by Naldi, Nordqvist, Sjöberg, and Wiklund (2007) also considered potential moderators of the EO and firm performance relationship, reviewing both family and non-family firms. The researchers indicated that the organizational context is an important determinant to this relationship, and noted that risk-taking does not always lead to increased firm performance for family firms. Within the context of new venture performance, Stam and Elfring (2008) determined that elements of social capital, such as network relationships and bridging ties, moderate the relationship between EO and performance. Later work by Kreiser and Davis (2010) suggested that future research should consider other factors, such as organizational structure, as possible moderators of the EO/firm performance relationship. These findings suggest the importance of testing for moderation in the relationship between EO and firm performance. In sum, while the relationship between social capital and firm performance has generally been found to be positive (e.g., Morris, Kocak, and Ozer, 2007), research on this relationship has been constrained to specific domains. Additionally, the relationship of entrepreneurial orientation to firm performance is more ambiguous, especially when considering the effects of moderating variables such as organizational structure. In our assessment, the moderating conditions in which the relationships of EO, SC, and firm performance have heretofore gone under- researched represent a theoretical gap within the entrepreneurship literature. To address such a gap, we seek to add to the literature by exploring the roles of SC and EO, as each directly relates to firm performance in an important, but previously underdeveloped domain--that of the family-owned business. We consider the effect of family ownership structure because of the family firm’s relative dominance in the U.S. economy (Morck and Yeung, 2004). Family firms have been estimated to employ up to 80 percent of America’s workers and contribute 40 to 60 Journal of Small Business Strategy Volume 21, Number 2 29  percent of the country’s GNP (Neubauer and Lank, 1998; Sharma, Chrisman, and Chua, 1996). Despite such figures, explicit study of the family firm has only begun to receive widespread attention in the past decade (Chrisman, Chua, and Sharma, 2005). Previously, the assumption appears to have been that the results of general business research, including research on SC and EO, were equally generalizable across family- owned (FO) versus non-family-owned (NFO) enterprises. Recent research, however, has shifted away from this assumption (Arregle, Hitt, Sirmon, and Very, 2007; Chrisman et al., 2005). The research presented here follows the spirit of this shift in suggesting that the impact of SC and EO on firm performance is not the same across family vs. non-family ownership structure and that differences relating to strategic practices, processes and performance should be reviewed between family-owned and non- family-owned businesses (Ibrahim, Angelidis, and Parsa, 2008). In consideration of the above, the purpose of our research is twofold. We first seek to test the generally accepted roles of SC and EO in a model that incorporates the two constructs simultaneously. To our knowledge, no previous research has examined these constructs as concurrent predictors of firm performance. Naldi et al. (2007) did not address the role of SC in the study on family versus non-family firms while Stam and Elfring (2008) tested SC only as a moderator of the EO and firm performance relationship. Both social capital and entrepreneurial orientation, however, are believed to be important independent determinants of firm performance when firms can leverage their resources into a strategic competitive advantage. As the benefits of social capital may be realized indirectly through increased productivity (Florin et al., 2003), or by creating business opportunities that support entrepreneurial-oriented behaviors (Stam and Elfring, 2008; Ireland, Hitt, and Sirmon, 2003), there is a need to test both determinants of SC and EO simultaneously. Second, we explore whether these relationships remain constant when differentiating between FO versus NFO businesses. We test our hypotheses via the use of structural equation models by proposing a model to test the generally accepted positive relationships between SC, EO, and firm performance. We follow with a two-group analysis to assess the potential differences in this relationship when distinguishing between FO versus NFO enterprises. Following a discussion of these analyses, practical implications are considered and directions for future research are proposed.  THEORETICAL BACKGROUND Resource Based View of the Firm General theoretical foundations from the resource based view of the firm (Barney, 1991) suggest that competitive and sustainable advantages can be achieved by using resources and capabilities such as information, knowledge, human resources, and operational strategies (Chrisman et al., 2005; Runyan, Huddleston, and Swinney, 2007; Droege and Dong, 2008). Accordingly, Habbershon, Williams, and MacMillan (2003) argued for a systems approach in defining and analyzing the performance of family-owned businesses that encompasses interactions, strategic intent, and wealth creation that may result from a RBV strategy to create unique and intangible resources. Of particular importance to family-owned businesses are the embedded systematic resources not easily transferable (Miller and Shamsie, 1996), but available within the firm. Habbershon et al. (2003, p.459) referred to such resources as “path dependent resources, idiosyncratic organizational Journal of Small Business Strategy Volume 21, Number 2 30  processes, behavioral and social phenomena, or leadership and strategy making capabilities.” Unfortunately, research attempting to delineate between FO and NFO firms through operational or strategic approaches have produced limited results (Chua, Chrisman, and Sharma, 1999; Gudmundson, Hartman, and Tower, 1999), with even less empirical consideration of the effects of firm ownership on performance (Lee, 2004). Social Capital Bourdieu (1980) defined social capital as “the aggregate of the actual or potential resources which are linked to possession of a durable network of more or less institutionalized relationships of mutual acquaintance or recognition” (p.2). Further conceptualization of social capital as group action expectations (Portes and Sensenbrenner, 1993) or reciprocal relationships among members within a specific community (Runyan et al., 2007) suggests that social capital is a type of convertible resource that can increase competitive advantage for those who utilize it, particularly when group members and individuals benefit from the relationship (Adler and Kwon, 2002). Segregation of social capital into both family and organizational factors (Arregle et al., 2007) suggests that differences may occur in the levels of interaction, interdependence, and potential stability typically associated with family membership and that these relationships may differ across organizational settings. Accordingly, it becomes important to consider the nature of the family business and whether inherent characteristics influence social capital generation. Our research operationalizes social capital in the family-owned firm as the composite of reciprocity (Bubolz, 2001; Rudd, 2000) and homophily (McPherson, Smith-Lovin, and Cook, 2001). The concept of homophily, through which “social interactions tend to take place among similar lifestyles and socioeconomic characteristics” (Lin, 2001 p.39), is thought to be embedded into SC through normative interaction principles reflecting the individual and network actors that create the social relationships (Lin, 2001). As a result of these interactions, Nahapiet and Ghoshal (1998) argued that the development of social capital facilitates the creation of intellectual capital, which in turn, manifests itself in important organizational outcomes such as firm performance. Similarly, Tsai and Ghoshal (1998) determined that “investing in the creation of social capital inside a firm eventually creates value” (p.473), which subsequently leads to positive effects on firm innovation as well as firm performance. Research by Cooke and Wills (1999) supports the notion that innovation and firm embeddedness are created through increased social capital and lead to positive firm performance. Given these findings, we hypothesize that: H1: A positive relationship exists between the level of social capital present in a firm and the firm’s performance. Entrepreneurial Orientation Miller (1983) suggested that entrepreneurial orientation characterizes firms that “engage in product-market innovation, undertake somewhat risky ventures, and [are] first to come up with proactive innovations, beating competitors to the punch” (p.771). As such, entrepreneurial orientation is reflected in three strategic tendencies; innovativeness, risk taking, and proactiveness (Covin and Slevin, 1989; Miller, 1983). Miller (1983) found significant relationships between entrepreneurship and the three dimensions of EO across different firm types. Subsequent Journal of Small Business Strategy Volume 21, Number 2 31  research relating EO to firm performance (Covin and Slevin, 1989; Runyan et al., 2008; Wiklund and Shepherd, 2005) has similarly operationalized EO as a composite of these three dimensions. Accordingly, our study utilizes this composite operationalization of EO to understand the relationship between EO and firm performance as follows: Innovativeness: Early work by Schumpeter (1934) suggested that entrepreneurial innovation is the force behind economic development. Cole (1946) considered innovation to be a key strategic process that helps businesses to survive by differentiating their product or service from competitors. Correspondingly, our research conceptualizes innovativeness as the commitment to “engage in and support new ideas, novelty, experimentation, and creative processes that may result in new products, services, or technological processes” (Lumpkin and Dess, 1996, p.142). Risk taking: Baird and Thomas (1985) argued that the level of strategic risk taking and risk estimation varies across entrepreneurial operations. Risk taking reflects the “degree to which managers are willing to make large and risky commitments - i.e., those which have a reasonable chance of costly failure” (Miller and Friesen, 1982, p.923). Busenitz (1999) determined that the use of heuristics and biases helps entrepreneurs to deal with the risk associated with the implementation of new ideas. Our research adopts the above conceptualization as proposed by Miller and Friesen (1982) to determine the extent to which these heuristics and biases differ in FO vs. NFO businesses.   Proactiveness: Lumpkin and Dess (2001) defined proactiveness as an “opportunity- seeking, forward-looking perspective involving introducing new products or services ahead of the competition and acting in anticipation of future demand to create change and shape the environment” (p.431). They found proactiveness to be a distinct construct, and identified its positive relationship with firm performance. However, although Hausman (2005) identified a number of factors that affect innovativeness in family-owned firms, it is unclear if the effects of innovativeness on firm performance differ across firm ownership structures. In sum, EO is generally agreed upon as a three-factor structure as discussed above. From the preceding discussion of its component parts, we hypothesize that: H2: A positive relationship exists between the level of entrepreneurial orientation present in a firm and the firm’s performance. Family-owned Versus Non-family-owned Businesses In defining the family-owned business, our study utilizes Litz’s (1995) conceptualization that “a business firm may be considered a family business to the extent that its ownership and management are concentrated within a family unit” (p.101). While Sirmon and Hitt (2003) extended the principles of the resource based view of the firm to the domain of FO businesses, subsequent research has not adequately addressed whether ownership structure impacts the manner in which the strategic and operational resources associated with the resourced based view affect firm performance. Chrisman, Steier, and Chua (2008) noted, however, that the influence of family can have a moderating impact on company strategy and performance. Lee (2004) reviewed performance measures of FO versus NFO businesses and determined that increased performance of FO businesses over Journal of Small Business Strategy Volume 21, Number 2 32  NFO was related to efficiencies created in the organization, but did not necessarily translate into profitability. Further studies including Miller, Le Breton-Miller, and Scholnick (2008) compared small family and non-family businesses under the strategic perspectives of stewardship (network building) and stagnation (slow-growth, short- lived entities). Their findings determined that FBOs utilize stewardship more effectively than NFOs, although no significant differences existed for stagnation measures. Additionally, Pearson, Carr, and Shaw (2008) noted that the close interactions, networks ties, and information sharing may be greater for family firms. The results of such research suggest the importance of social networks in the strategies and practices of family-owned businesses, but do not adequately address other important strategic orientations (such as EO) that could help the business grow and increase performance. In sum, characteristics unique to FO versus NFO ownership structures may affect the relationships between SC/EO and firm performance, depending upon the strategies that the f rms undertake. We therefore hypothesize that: i   H3: The type of business (family-owned vs. non-family-owned) positively moderates the relationship of (a) social capital and (b) entrepreneurial orientation to firm performance, and (c) the moderation effect of family ownership will be larger for social capital than for entrepreneurial orientation. METHODOLOGY Sampling Procedure The sampling frame for this study was restricted to non-urban rural communities of small or medium size. We selected two Midwestern states, from which we took a sample of such cities. The cities included in the sample met the criteria outlined by the U.S. Census Bureau (U.S. Census Factfinder, 2004) for such a designation. That is, all towns had populations from 2,500 to 30,000 inhabitants and were located more than 30 miles from the nearest MSA. Within these cities, we chose to administer our questionnaire to business owners in each city’s downtown area, because communities of this size are unlikely to have a wide variety of shopping and entertainment choices outside this geographic boundary (Gorodesky and McCarron, 2003; Levy and Weitz, 2003). Additionally, we wished to make sure that business owners in each city were not so spatially removed from other owners so as to restrict their ability to answer questions concerning inter-firm social capital. In order to achieve more generalizable results, franchises were not excluded from sampling. All downtowns that fit our criteria in each state were identified, and the Downtown Development Authority (DDA) director for each city was e-mailed. A total of 21 downtown areas agreed to participate. In order to increase response rates, a pre- notification and an incentive were issued for participation in the study (Dillman, 2000). Each downtown’s DDA director provided an announcement of the upcoming study in either a weekly email, or a printed weekly update letter. As an incentive to increase participation, business owners were informed that the results from the local study would be provided to the DDA free of charge, supplying valuable statistical feedback. We advised the DDA directors that their enthusiastic participation would greatly increase response rates, rendering data gathered much more usable for their downtown. Directors who agreed to participate thus became project “champions,” Journal of Small Business Strategy Volume 21, Number 2 33  notifying firms of the study and advising owners that their participation was important to the downtown area as an economic entity. DDA directors collected the surveys at a pre- specified date. On this date, owners who had not completed the survey were given the option to complete it while pick-up continued, or to simply drop by the director’s office at a later time for submission. All surveys were distributed and collected over a three-week period. Relevant sample characteristics are reported in Table 1. Of the 2,300 surveys disseminated in the 21 participating communities, 503 were returned for a response rate of 22.0 percent. This is a respectable response rate, compared to those achieved in similar endeavors (e.g., Conant and White, 1999 at 13.1 percent; Runyan et al., 2008 at 23 percent). Table 1: Sample Characteristics (N = 503) Sample Characteristic Frequencies Percentage Male 256 50.9% Female 225 44.7% Gender No response 22 4.4% 40 or less years 11 2.2% 41 to 50 years 50 9.9% Age 51 years and over 442 87.9% High School graduate 60 11.9% Some college 132 26.2% College graduate 120 23.9% Post-graduate degree 121 24.1% Education Other (or no response) 70 13.9% Yes 353 70.2% Family Business No 150 29.8% 6 or less 113 22.5% 7 to 15 93 18.5% 16 to 30 159 31.6% Years Business has existed 31 or more 138 27.4% 6 or less 159 31.6% 7 to 15 92 18.3% 16 to 30 153 30.4% Years in downtown 31 or more 99 19.7% 6 or less 160 31.8% 7 to 15 187 37.2% 16 to 30 118 23.5% Years of current owner 31 or more 38 7.5% None 34 6.8% 1 to 2 198 39.4% 3 to 5 205 40.7% Full-time employees 6 or more 66 13.1% None 44 8.8% 1 to 2 158 31.4% 3 to 5 243 48.3% Part-time employees 6 or more 58 11.5%   Journal of Small Business Strategy Volume 21, Number 2 34  Measurement of SC Scales designed to measure the level of social capital generated by individual firms were developed according to focus group research conducted in four U.S. cities and subsequently operationalized in the Runyan et al. (2008) study. The results of this research indicated two important kinds of social capital; that which is built between the business and the consumption community, and that which is built between the business and other small business owners. Social capital built within the consumption community was measured by business owner perceptions of local customer behaviors and motivations. From the focus groups, the concept of reciprocity emerged as a common theme in the assessment of social capital built within the consumption community. Reciprocity was measured by four items including ‘We do favors for each other from time to time’ and ‘these people patronize my business because I support the community.’ Responses were made on seven-point Likert scales anchored by strongly disagree and strongly agree. Cronbach’s alpha for the items measuring consumption community reciprocity was .74. Social capital among fellow business owners was measured by owner reports of their relationships with other small business owners in the area. Two dimensions of inter-firm social capital were identified: homophily and reciprocity. These constructs were measured using the same rating scales as discussed above. Participants were asked to respond to questions keeping in mind their fellow business owners. The four items measuring homophily were designed to capture the perception of similarity to other business owners. Response items included ‘I am similar to these people in terms of my outlook on life’ and ‘I am similar to these people in terms of my business philosophy.’ The items measuring reciprocity among owners were the same as those discussed above regarding perceptions within the consumption community. Cronbach’s alpha for the 12 total items measuring SC was .84. Measurement of EO The measurement of entrepreneurial orientation was based on scales previously operationalized by Covin and Slevin (1989). Within a small business setting, these scales have been operationalized by many researchers (Rauch, Wiklund, Lumpkin, and Frese, 2009). In accordance with popular conceptualization, we operationalize EO as reflected in three factors; innovation, proactiveness, and risk-taking. Three items each measure these factors, yielding a nine- item unidimensional structure for the measurement of EO ( = .87) similar to the findings of Covin and Slevin (1989). Measurement of Firm Performance We chose to operationalize firm performance with subjective measures rather than objective financial measures, in order to decrease the incidence of non- response. Because small businesses often are reluctant to divulge financial information, subjective measures may be more effective in increasing response rates (Droge, Jayaram, and Vickery, 2004). Additionally, studies suggest a relatively high level of concordance between subjective and objective measurements of firm performance (Dess and Robinson Jr., 1984; Venkatraman and Ramanujam, 1986). That is, findings are similar whether one uses subjective measurements such as those discussed above, or more objective measurements such as ROA, ROI, and ROS. Richard, Devinney, Yip, and Johnson (2009), in a review of performance measurements across a variety of academic management journals, argued that the context through which the research is being completed should dictate whether subjective Journal of Small Business Strategy Volume 21, Number 2 35  or objective measures are most appropriate, and that strong construct validity can still be obtained through subjective measures. Based on such findings, we determined that little to no substance would be lost in the subjective measurement of firm performance. Respondents described the overall performance of their firm (1) compared to the previous year; (2) compared to major competitors; and (3) compared to other similar firms in the industry. Because results of the focus group indicated a common practice among business owners of going to neighboring downtowns to “shop the competition,” it is not surprising that respondents were able to answer performance questions without difficulty. Indeed, no respondent neglected to answer these items. The three items measuring firm performance were answered according to seven-point semantic differential scales, anchored poor to excellent ( = .87). Measurement of Family Ownership Within the survey, respondents were asked, “Is this a family owned business?” with categorical responses ranging from ‘Yes’ (N = 353) to ‘No’ (N = 150). The specific degree of family ownership within each business was not solicited as part of this research study, as it was believed little differences in responses relating to SC and EO would occur between complete family ownership of the firm (100%) versus majority ownership (> 50%). ANALYSIS AMOS 18.0 structural equation modeling (SEM) software with maximum likelihood estimation was used to evaluate and test the measurement model, structural model, and moderation model fits. SEM is considered an important analysis technique in both the confirmation of theory and in hypothesis testing, and is often preferred when simultaneously testing high level abstract hypotheses with multiple latent variables (Byrne, 2001; Kline, 2005). Maximum likelihood is identified as a robust estimation technique (Kline, 2005) that requires normal distribution of data, a relatively large sample size, and use of a continuous scale in measurements in order to be useful (Byrne, 2001). As our data met all of these criteria, we subsequently employed a two-step approach suggested by Anderson and Gerbing (1988) that included completion of confirmatory factor analysis prior to testing the structural model. To assess both the fit of the measurement and structural models, a number of diagnostic statistics were evaluated. These included the χ² statistic, the “discrepancy between the unrestricted sample covariance matrix and the restricted covariance matrix” (Byrne, 2001, p.79), root mean squared error of approximation (RMSEA), comparative fit index (CFI), and normed fit index (NFI). The CFI and NFI are incremental indexes that compare the hypothesized model to a baseline model, and that above .9 is considered a reasonably good fit (Kline, 2005). The RMSEA is affected by model complexity and is thus indicative of parsimony. A value of .08 or below is suggested as a reasonable model approximation (Browne and Cudeck, 1993; Kline, 2005). These values were established as our cutoff criteria for good model fit. Additionally, we also reviewed standardized residuals and modifications for suggested ways of improving the fit of hypothesized model. Covariance values above 2.58 for the standardized residual matrices were investigated (Jӧreskog and Sorbom, 1988), as were modification indices above 10.0. Only those suggested modifications that were supported by face Journal of Small Business Strategy Volume 21, Number 2 36  validity or prior theory were considered for adjustment. Measurement Model Results The measurement model was fit using the specified measurement variables for EO and SC. Results from the model (2 = 506.058, df = 176, p-value = .000, CFI = .914, NFI = .876, RMSEA =.061) indicated a good model fit. The specified indicators for both EO and SC loaded only on their respective constructs, thus eliminating the possibility of cross-loading on multiple constructs. To assess the convergent validity of the model, the average variance extracted (AVE) for each latent construct was measured. Values larger than .50 suggest convergent validity (Fornell and Larker, 1981). The AVE for EO (.512) and SC (.528) indicated convergent validity for each construct. To test for discriminant validity, the squared correlation coefficient (shared variance) between EO and SC (.003) was compared to the AVE values. Fornell and Larker (1981) noted that the squared correlation (shared variance) should be less than the AVE values to ensure that high inter-correlations between the observed measurement items do not exist across latent constructs. A comparison of the shared variance (.003) against the AVE values (.512, .528) indicated that this condition was also met. We therefore achieved adequate discriminant validity within the measurement model and no further model re-specification was necessary. All parameter estimates were significant at p < .05, a further indication of validity. Standardized parameter estimates and t- values for the measurement model are shown in Table 2. Structural Model Results (H1 and H2) Upon establishing the measurement model, we then fit the data to the proposed structural model. specification. The standardized parameter estimate of SC ( = .403, p = .102) as a predictor of firm performance was not significant at p <.05. Therefore, H1 is not supported. However, the standardized parameter estimate of EO ( = .915, p < .001) as a predictor of firm performance was found to be significant at p <.05, thus supporting H2. Standardized parameter estimates and t-values for the structural model are provided in Table 3. Moderation Model Results (H3) To test our hypotheses regarding the effects of SC and EO as moderated by ownership type, we specified a two-group nested SEM model. Group 1 (n = 353) included FO businesses, while Results from the model (2 = 604.570, df = 235, p-value = .000, CFI = .921, NFI = .878, RMSEA = .056) yielded a good model fit and did not require re- group 2 (n = 150) reflected NFO businesses. The two-group nested model was fit to determine if type of ownership (family versus non-family owned) moderates the relationships between EO and SC and firm performance. First, factor loadings for the measurement items and error covariances were specified and constrained as equal across both groups. Next, two separate models were created. The first model constrained the proposed structural paths between EO → FP and SC → FP as equal between the two nested groups (2 = 988.516, df = 508). In the second model, these paths were allowed to freely estimate (2 = 981.962, df = 506). The difference in chi-square values was 6.554 (df = 2), which is significant at p < .05. For the FO businesses, the EO → FP path reflected a large standard estimate (.883), and t-value (2.511), indicating a significant effect upon firm performance (p < .05). The SC → FP path was not significant ( = .117, t = .335). For the NFO businesses, EO had a large effect on firm performance, with a standard estimate Journal of Small Business Strategy Volume 21, Number 2 37  ( = .958, t = 2.242) indicating a significant effect at p < .05. For NFO businesses, SC also had a large and significant effect ( = .863, t = 2.991) on firm performance (p < .05). Table 2: Parameter Estimates for Measurement Model Indicator Standardized Estimate t-value* p < .05 EO-1 .289 5.659* EO-2 .467 9.540* EO-3 .463 9.460* EO-4 .489 9.424* EO-5 .684 14.708* EO-6 .581 12.213* EO-7 .616 13.053* EO-8 .480 9.782* EO-9 .439 8.842* SC-1 .192 4.003* SC-2 .165 3.424* SC-3 .272 5.732* SC-4 .237 4.967* SC-5 .237 4.956* SC-6 .758 18.466* SC-7 .729 17.453* SC-8 .769 18.964* SC-9 .794 19.778* SC-10 .551 12.423* SC-11 .470 10.303* SC-12 .491 10.863* (2 = 506.058, df = 176, p-value = .000, CFI = .914, NFI = .876, RMSEA =.061)   Based upon these results, we conclude that the type of business (FO vs. non NFO) has differential effects on the relationship of SC and EO to firm performance. For FO businesses, social capital (SC) did not have a significant positive effect on firm performance, but for NFO businesses a significant positive relationship was found. Thus, H3a is supported. The results however, were different for entrepreneurial orientation (EO): Both FO businesses and NFO businesses showed a significant positive relationship between EO and firm performance, with the standard estimates ( = .883 for FO;  = .958 for NFO, p < .05) suggesting that EO is a strong predictor to overall firm performance. Given that both effects were found to be significant, but different in value, we could conclude that the type of business only moderates the magnitude of the effect. Therefore, H3b is only partially supported. Finally, the difference in standard estimates for social capital (SC → FP) in FO vs. NFO businesses (Δ = .746) was larger than the difference for entrepreneurial orientation (EO → FP) in FO vs. NFO businesses (Δ = .075). This supported the H3c hypothesis of a larger moderation effect of ownership type (FO vs. NFO) for social capital and firm performance than that of entrepreneurial orientation and firm performance. . Journal of Small Business Strategy Volume 21, Number 2 38  Table 3: Parameter Estimates for Structural Model Indicator Standardized Estimate t-value* (p < .05) EO → FP .915 3.409* SC → FP .403 1.638 EO-1 .291 5.448* EO-2 .464 8.394* EO-3 .463 8.390* EO-4 .489 10.380* EO-5 .684 EO-6 .580 10.061* EO-7 .618 10.524* EO-8 .481 8.612* EO-9 .437 7.907* SC-1 .194 4.020* SC-2 .164 3.389* SC-3 .273 5.686* SC-4 .238 4.941* SC-5 .237 4.920* SC-6 .757 16.342* SC-7 .729 15.642* SC-8 .769 16.781* SC-9 .793 SC-10 .553 11.853* SC-11 .472 9.996* SC-12 .492 10.475* FP-1 .120 3.010* FP-2 .160 4.730* FP-3 .193 (2 = 604.570, df = 235, p-value = .000, CFI = .921, NFI = .878, RMSEA = .056) Note:   Variables EO-5, SC-9, and FP-3 were constructed as reference variables in AMOS 18.0 and set to a value of 1.0, thus no t-value was calculated. DISCUSSION For the overall sample, EO had a significant and positive effect on firm performance. These results support prior research (e.g., Kreiser and Davis, 2010; Runyan et al., 2008; Wiklund and Shepherd, 2005), identifying EO as an important predictor of firm performance. However, we proposed that firm ownership type might moderate this relationship, considering the value of social capital to the small firm (Macpherson and Holt, 2007; Manev et al., 2005; Runyan et al., 2007). The two-group model revealed differences between the FO and NFO groups with respect to the effect of EO and SC on firm performance. Although the relationship between EO and firm performance was significant for both groups, parameter estimates for this relationship were higher for NFO businesses. In contrast, the effects of SC on firm performance were only significant for NFO businesses. Journal of Small Business Strategy Volume 21, Number 2 39  Thus, for FO businesses, EO is a better predictor of firm performance than SC, perhaps because many FO business owners have been running the business for a relatively short period of time. Our data indicate that the average time that FO business respondents had owned their businesses was 14 years, while the average time the business had been in existence was 28 years. Many respondents, then, were running businesses started by others (although we do not know if the previous owner was a family member). Because the development of SC is a discrete phenomenon, SC created by a previous business owner is likely to be tied to that owner and not necessarily transferable to a new owner (in contrast to a brand name for example). Therefore, new firm owners faced with little SC upon which to rely are more likely to adopt EO as a strategic posture than more established owners (see also Runyan et al., 2008). In such cases, a strategic posture emphasizing EO would be more important than other strategies (e.g., the creation of social capital). Note, however, that we do not suggest that development of social capital is unimportant in these scenarios. Rather, a business owner engaged in innovative and risk-taking behavior is likely to be more inwardly focused on his/her business’ growth (Runyan et al., 2008) than on establishing social capital ties in a community. In contrast to FO businesses, we found that SC in NFO businesses had a significant effect on firm performance. Anecdotal reports point to companies with local managers (e.g., franchise chains, etc.) encouraging or requiring managers to join local trade and business groups (Teixeira, 2011) to build relationships with the local community, which results in social capital accumulation. In such cases, building social capital within the community may be a more effective way for NFO managers to increase their firms’ performance compared to FBOs. Considering the larger effect size of the relationship between EO and firm performance for NFOs, it appears that these small business managers are good at creating social capital as well as acting entrepreneurially. Implications The study concluded that while the level of a firm’s entrepreneurial orientation (EO) significantly impacts firm performance, the impact of social capital (SC) depends on family ownership. From these findings, a number of implications arise. First, based on ownership type (family-owned versus non-family owned), FO businesses have more success when they adopt an entrepreneurial posture. Specifically, new family owners who take over an existing business, and embrace risk to make innovative changes will likely increase firm performance. As mentioned earlier, many of the family-owned business respondents were relatively new owners that were running businesses started by others. Being owners, they were perhaps more likely to assess the risk and make strategic decisions to help grow, rather than simply maintain, the business through entrepreneurial endeavors. Thus, our results suggest that, especially in the beginning years of ownership, family-owned firms should adopt an EO strategic posture. Such firms should note, however, that as tenure of ownership increases, building social capital may become more important to increasing firm performance. Next, concerning NFO businesses, our research suggests that, although adopting an EO similarly increases firm performance, establishing social capital within both the business and consumption community is a Journal of Small Business Strategy Volume 21, Number 2 40  critical strategic component. Because NFO managers may have less freedom to implement innovative or risk taking strategies (i.e., take on an EO posture), they should seek to establish community capital ties through trade organizations in order to increase social awareness and establish themselves within the community. Managers of NFO businesses should recognize that building these relationships might be more important to overall firm performance than acting in an entrepreneurial manner, provided that they are able to effectively leverage this capital into tangible financial gain for the firm. However, NFO owners/managers should also understand that EO is a long-term strategic posture, and that once social ties have been created, adopting an EO perspective may further enhance performance. Limitations and Future Research Directions The researchers acknowledge limitations to the study. Primarily, the sample (N = 503) was drawn from only 21 small cities within two Midwestern states and may not adequately generalize across larger cities, urban areas, or states such as California or New York. Also, results may differ when compared to businesses located in a suburban area or shopping ‘mall-based’ setting, given that demographics unique to these environments may influence the impact of EO and SC on firm performance. Further research into other areas of the country may allow for comparative studies and provide insight into factors that are similar or different across cities, states, or area types (rural vs. urban). Another limitation is that the study considered only the moderating effect of family-owned versus non-family owned businesses, and did not address other potentially important moderators to the model, such as how firm longevity impacts the relationships of SC and EO to firm performance. Firms that increase in age and become more established in their respective communities may alter their strategies to become less entrepreneurial and growth- oriented and more concerned with maintaining their business and social connections. Understanding the moderating role of longevity for future studies may help to identify whether a particular ‘threshold’ of age influences the relationships of EO and SC on overall performance. CONCLUSION Our study tested three hypotheses based upon theoretical relationships among EO, SC, and family versus non-family-owned businesses and their relationships to firm performance. Hypotheses one and two were based upon literature supporting the positive relationship between SC and EO, respectively, as each relates to firm performance. Results of our analysis found support for hypothesis two only. That is, EO was found to significantly affect firm performance, while SC was not. Hypothesis three tested these relationships for the moderating effect of family ownership. We expected that a model that allowed relationships among the constructs to co- vary across groups would yield a better overall fit to the data. For both groups, EO remained a significant positive predictor of a firm’s performance. For FO businesses, SC remained a non-significant predictor of firm performance. For NFO businesses, owever, SC emerged as a significant redictor of firm performance. h p   REFERENCES Adler, P., & Kwon, S.K. (2002). Social capital: Prospects for a new concept, Journal of Small Business Strategy Volume 21, Number 2 41  The Academy of Management Review, 27(1): 17-40. Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach, Psychological Bulletin, 103(3): 411-423. Arregle, J-L, Hitt, M., Sirmon, D., & Very, P. (2007). 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(2004). http://factfinder.census.gov/ (accessed December 3, 2004). Dr. Jeffrey M. Campbell is an Assistant Professor in the Department of Retailing at the University of South Carolina. His teaching interests include the areas of retail strategy, small business organization and operation, and category management. His research interests include the areas of business strategy, consumer behavior, and social capital created between retail firms. Nathan Line is a Ph.D. Candidate in the Department of Retail, Hospitality, and Tourism Management at the University of Tennessee. His teaching interests include hospitality marketing, destination marketing/management, and entrepreneurship. His research interests include destination marketing organizations, sustainable tourism, and strategic orientations of hospitality and tourism firms. Dr. Rodney C. Runyan is an Associate Professor of Retail and Consumer Sciences at the University of Tennessee. His teaching interests include entrepreneurship, small business management, and retail technology. His research interests include small business, downtown retail districts, entrepreneurship, and international retailing. Dr. Jane L. Swinney is an Associate Professor of Merchandising at Oklahoma State University. Her teaching interests include merchandise analysis and product innovation. Her research interests include social capital, community social responsibility, and family business performance. http://factfinder.census.gov/ Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.