Entrepreneurial orientation and social capital as small firm strategies: A study of gender differences from a resource-based view

Entrepreneurial orientation and social capitalas small firm strategies: A study of genderdifferences from a resource-based view

Rodney C. Runyan & Patricia Huddleston & Jane Swinney

Published online: 3 November 2006# Springer Science + Business Media, LLC 2006

Abstract Women entrepreneurs have recently been the subject of many studieswhich have revealed that though women possess some of the same resources as maleentrepreneurs, success levels are not the same. The current study looks at theresources utilized by small business owners within downtown business districts.Using a sample of 467 small business owners, we test differences in entrepreneurialorientation and social capital between men and women entrepreneurs. Thoughwomen actually reported higher levels of entrepreneurial orientation and socialcapital, there were no differences in their abilities to utilize these two resources inachieving firm performance. We offer discussion of why these findings are relevant,as well as research implications.

Keywords Small business . Entrepreneurship . Social capital . RBV

Women small business owners

In most industrialized countries, while great strides have been made by women in theworkforce, significant disparities continue to exist between men’s and women’ssalaries (MacRae, 2005). Reasons for these differences have been well documented,

Entrepreneurship Mgt. (2006) 2: 455–477DOI 10.1007/s11365-006-0010-3

R. C. Runyan (*)Department of Retailing, The University of South Carolina,2026E Coliseum, Columbia, SC 29208, USAe-mail: [email protected]

P. HuddlestonDepartment of Advertising, Public Relations and Retailing, Michigan State University,370 Communication Arts, East Lansing, MI, USAe-mail: [email protected]

J. SwinneyDesign, Housing and Merchandising, Oklahoma State University,445 HES Bldg, Stillwater, OK 74078, USAe-mail: [email protected]

including the proverbial “glass ceiling” in corporations and myths about womenbusiness owners (Brush, Carter, Gatewood, Greene, & Hart, 2001). Daniel observed:“Despite the fact that women make up 51 percent of the total U.S. population andrepresent 46 percent of the workforce, women represented only 12.2 percent of thecorporate officers among all the Fortune 500 companies” (Daniel, 2004).

Creating and owning a business is seen as one way to level the playing field byproviding an opportunity to achieve economic equality and generate higher incomesfor women. “Female-headed households with a business had an average income level2.5 times that of those without a business” (Daniel, 2004). An estimated 10.6 millionenterprises (48% of all U.S. businesses) are 50% or more owned by women (Centerfor Women’s Business Research, 2004). Since 1997, the Center for Women’sBusiness Research (2004) estimates that women-owned firms have grown at twicethe rate of all firms (17 vs. 9%). Women owned businesses employ one out of everyseven people in the U.S. and their estimated contribution to salaries in the U.S.economy is $491 billion per year (Center for Women’s Business, 2004).

Despite the aforementioned economic power of women owned businesses,differences exist between male and female owned firms. Small firms owned bywomen are characterized as having few employees, low revenues (Fischer, Reuber,& Dyke, 1993) and less access to financing than male owned firms (Domeisen,2003; Inman, 2000; Marlow & Patton, 2005). Female firm owners lack the sameaccess to venture capital resources as their male counterparts. Less than 5% of allventure capital investments in the U.S. were allocated to women led businesses,leading to the conclusion that women are being left out of the wealth creationprocess (Brush, Carter, Greene, Hart, & Gatewood, 2002). This disparity may notnecessarily reflect gender discrimination, but rather structural characteristics of thebusinesses women tend to own (e.g., low growth prospects), which reduce thelikelihood of gaining access to capital (Coleman, 2002).

There is conflicting evidence about the survival rate of female owned firms.Kalleberg and Leicht (1991) found that female owned firms are no more likely to goout of business than male owned firms, but Carter, Williams and Reynolds (1997), ina study of new retail firms found women owned businesses more likely to fail. Evenso, survival is not synonymous with prosperity. Financial performance of womenowned firms is not equal to that of male owned businesses. For example malebusiness owners have higher personal salaries and paid higher rates of benefits thanfemale owned firms (Brush & Hisrich, 2000). What contributes to the financialsuccess of women owned businesses is largely an unanswered question.

Business success is dependent on nonfinancial as well as financial resources.Daniel (2004) identified several characteristics which contribute to the success of afemale owned small business. Women have been shown to have better commu-nication and people skills. They also have superior web thinking, which refers to anability to gather data from the environment and construct intricate relationshipsbetween the pieces of information. Web thinking is a contrast to men who tend tocompartmentalize. Women are consensus builders and are able to build and nurturegood relationships (Daniel, 2004). These characteristics are indicative of socialcapital, which is a noneconomic resource resulting from networks and socialrelationships (Coleman, 1988; Nahapiet & Ghoshal, 1998). From a social capital

456 Entrepreneurship Mgt. (2006) 2: 455–477

view, the aforementioned skills should provide female business owners withnoneconomic resources with which to gain competitive advantages for their firms(Nahapiet & Ghoshal, 1998). Social capital plays a role in gaining access to financialresources like venture capital. However, Brush et al. (2002) posit that lack of socialties limit women’s access to venture capital financing.

Entrepreneurial behavior has been linked to business success (Covin&Slevin, 1989;Niehm, 2002, unpublished data; Stone, 1995) and much has been written in the pastdecade about women and entrepreneurship, (Brush, 1992; Brush et al., 2002; Fischeret al., 1993; Lerner & Almor, 2002). The literature suggests that there are fewdifferences between men and women business owners in their traits and motivations(Fagenson, 1993; Kalleberg & Leicht, 1991; Masters & Meier, 1988).Women havebeenfoundtobesimilartomenintermsofentrepreneurialtraits(Fagenson,1993; Masters& Meier, 1988). Therefore, both social capital and entrepreneurial skills should beresources that help small businesses be successful for both male and female owners.

Brush et al. (2002) note that there is scant research dealing with womenentrepreneurs and equity financing. They found a significant disconnect betweenwomen entrepreneurs and venture capitalists in high-growth industries, with a lackof social capital as a leading cause of this disconnect. This is a contributing factor tothe reported lack of success by women entrepreneurs in high-growth industries.Therefore this lack of built up social capital by women entrepreneurs has left littleupon which to base current research. This gap suggests an opportunity to investigateindustries in which women entrepreneurs have exhibited greater levels of success,for example retailing. Does social capital play a role in success for women in thoseindustries? In high-growth industries, social capital has been a resource for males butnot females (Brush et al., 2002). Is social capital gender neutral in industries wherethe number of women entrepreneurs is similar to the number of males?Entrepreneurial tendencies have been shown to contribute to small firm success(Covin & Slevin, 1989; Stone, 1995), and to be gender neutral (Kalleberg & Leicht,1991; Masters & Meier, 1988). If social capital is found to be a gender-neutralresource, it would be one upon which women entrepreneurs would want to focus inhigh-growth industries as well as other industries.

Because disparities exist in the financial performance of women owned businessesand with the growing economic significance of women owned businesses, we needto identify contributing factors to positive performance and assess similarities anddifferences between male and female owned firm success factors. Specifically, thefollowing questions need to be addressed: 1) what are the contributions of thenoneconomic resources of entrepreneurial orientation and social capital to firmsuccess? 2) are these noneconomic resources gender-neutral? These findings willinform public policy, and highlight factors that can be exploited to improve chancesof long-term prosperity for female entrepreneurs.

Women owned businesses are comparatively understudied in the entrepreneurialdomain (Menzies, Diochon, & Gasse, 2004). In particular, studies about the factorsinfluencing the performance of their businesses are “inconclusive and scarce” (Brush& Hisrich, 2000). Therehasbeenacall for research that transcends traditional economicmeasures of success and examines the influence of business styles, strategies andcultures on women owned businesses (Brush & Hisrich, 2000). The purpose of our

Entrepreneurship Mgt. (2006) 2: 455–477 457

study is to examine the contribution of nonfinancial resources (entrepreneurship andsocial capital) to the success of small firms and to pinpoint differences between maleand female owners.

First, we give a brief overview of resource based theory (RBV), then present areview of the relevant literature and discuss entrepreneurial orientation and socialcapital as they apply to small firms. We propose hypotheses concerning smallbusiness owner resources and the effects of those resources upon firm performance.A structural equation modeling technique is used to test our hypotheses. We thendiscuss the results and provide implications and suggestions for future research.

Theoretical frame

The resource-based view of the firm holds that firm performance is better ex-plained by differences in firm resources than in industry structure (Wernerfelt,1984). Resources can be tangible or intangible in nature. Tangible resourcesinclude capital, access to capital and location (among others). Intangible resourcesconsist of knowledge, skills and reputation, among others. Few studies haveconsidered small firms from a resource-based view (Lerner & Almor, 2002), yetsmall firms are likely those which must rely heavily on the resource of owner skills.This is particularly true with female small business owners, as those businesses tendto be in the service or retail sector, and 85% of those have no employees other thanthe owner (Adler, 1999).

The resource-based view (RBV) of the firm has become one of the most widelyused theoretical frameworks in the management literature. The foci of RBV arecompetitive advantages generated by the firm, from its unique set of resources(Barney, 1986, 1991; Peteraf, 1993; Wernerfelt, 1984). Barney (1991) identified fourkey attributes that a resource must have, in order to yield a sustainable competitiveadvantage. A resource must be: valuable, rare, imperfectly mobile, and nonsubs-titutable. This definition is used by most RBV authors to describe and operationalizeconstructs of competitive advantage. The key to competitive advantage is for firms tobe able to sustain the advantages gained from superior resources. Sustainedcompetitive advantage comes from a firm’s resources and capabilities that includemanagement skills, organizational processes and skills, information and knowledge(Barney, 1991). For small business owners, entrepreneurial orientation and socialcapital are management skills, and therefore are resources which lead to competitiveadvantages. While access to tangible resources may differ by gender (Brush et al.,2002; Domeisen, 2003; Inman, 2000; Marlow & Patton, 2005), the ability to exploitintangible resources may be a means to equalize the chances for success for womenowned businesses.

Entrepreneurial orientation

Entrepreneurial characteristics are viewed as resources to the entrepreneur as well asthe firm (Alvarez & Busenitz, 2001). In general, most researchers see entrepreneurs


as individuals who tend to be innovative risk takers (Baumol, 1993; Schumpeter,1934). Schumpeter (1934) described innovation as the single function that mostcharacterizes an entrepreneur. In fact, much of the extant entrepreneurship literatureassumes that entrepreneurs are a mostly homogeneous group (Stewart, Carland,Carland, Watson, & Sweo, 2003). Yet a search for an operational definition yields anumber of similar yet disparate versions. These include: one who is innovative andtakes initiative (Schumpeter, 1934); one who has a personal value orientation (Gasse,1982); one who is innovative and growth-oriented (Carland, Hoy, Boulton, &Carland, 1984); one who displays competitive aggressiveness (Covin & Slevin,1989); one who undertakes a “new entry” (Lumpkin & Dess, 1996); or one whosimply owns and actively manages a small business (Stewart & Roth, 2001).Depending on the frame with which one examines entrepreneurship, any of thesedefinitions may fit. For the purposes of this study, an entrepreneur is an “individualwho assumes risk” in a venture, and “provides management for the firm” (Kilby,1977). Most very small businesses (such as the ones in the current study) haveowners who also manage the business, thus fitting Kilby (1977) definition.

The concept of entrepreneurial orientation (EO) refers to the processes, practicesand decision activities leading to new entry or opportunity for an individual/firm(Covin & Slevin, 1989). Some of the constructs of EO were suggested by earlierauthors in the strategy domain. For example Miller and Friesen (1978) identified risktaking and innovation as effective management strategies. Fredrickson (1986)suggested proactiveness, risk taking and assertiveness. In the entrepreneurshipdomain, the construct of entrepreneurial orientation was operationalized by Miller(1983) and Covin and Slevin (1989). Their construct consisted of three dimensions:innovativeness, risk taking, proactiveness. We now discuss each dimension.

Innovativeness Based on Schumpeter’s (1934) early work, the concept of entrepre-neurs as innovators is accepted in the literature. Innovativeness is an indicator of afirm’s tendency to engage in and support new ideas, processes and creative methods.This type of activity may result in new processes, services or technologies (Lumpkin& Dess, 1996). Though the bulk of the extant innovation literature has focused ontechnology, innovation can occur in many areas. This includes managementprocesses, promotion, human resources, visual merchandising, and other aspects ofrunning a small business. These are all areas where a firm or small business ownercould employ innovative techniques to improve the performance of their business.Innovation is an important aspect of EO as it reflects the means by which firmsmight pursue new opportunities (Lumpkin & Dess, 1996).

Risk taking One of the earliest characteristics ascribed to entrepreneurs was thatof risk taking (Lumpkin & Dess, 1996). The very idea of working for “oneself”implies the risk of not only lost capital, but the opportunity cost of having earnedwages in the employ of another firm. The term risk has various meanings, dependingon the context of the application. Three types of strategic risk were identified byBaird and Thomas (1985) as: a) venturing into the unknown; b) investing a largeportion of assets; and c) heavy borrowing. The first of these types applies to small


business owners in the sense that it implies a sense of uncertainty, as is discussed inthe entrepreneurship literature in terms of social, personal or psychological risk(Gasse, 1982). Small business owners who adopt new ways of doing business or trya new product line are taking on risk to some degree.

Most studies of entrepreneurship have focused on the individual, rather than thefirm (Lumpkin & Dess, 1996). That fact is germane to this study, as theentrepreneurship component is measured at the individual rather than the businesslevel. EO has been used by Covin and Slevin (1989) and Miller (1983) to investigaterisk taking by individuals within firms. As is the case in most measures of behavior,there seems to be a range of risk taking (Lumpkin & Dess, 1996). Business ownerswill probably range from risk averse to risk prone. Female and male small businessowners have been found to have similar levels of risk-taking propensities as well asinnovativeness (Sonfield, Lussier, Corman, & McKinney, 2001).

Proactiveness Proactiveness is the act of anticipating problems or opportunitiesprior to their occurrence, in order to be prepared for the problems and takeadvantage of the opportunities. Miller (1983) suggests that entrepreneurial firms areones that are “first” to develop proactive innovations. This seems self-evident, as aninnovation is a new way of doing something, and thus by definition proactive.Although it is related to innovation, proactiveness is focused more on the pursuit ofopportunities and initiating activities (Covin & Slevin, 1989).

Proactive firms seek new operations that may or may not be related to theirpresent business, eliminate operations in declining stages of the life cycle, and bringin new products ahead of the competition (Venkatraman, 1989). They are willing tograb onto new market opportunities as leaders, even if they are not the first(Lumpkin & Dess, 1996). Lumpkin & Dess (1996) also characterize the oppositeof proactiveness as being “passive” rather than “reactive”. This too is an importantdistinction, as a small business owner with little foresight (i.e., not proactive), whononetheless reacts to a market change or opportunity is likely to be in better shapelong-term than the one who is passive and does nothing. Covin and Slevin (1989)describe one of the attributes of proactiveness as being competitively aggressive.Competitive aggressiveness describes the manner in which firms or business ownersrelate or respond to competitors. More specifically, it refers to a firm’s inclination todirectly challenge its competition with intensity (Lumpkin & Dess, 1996) or evenunconventional tactics (Cooper, Willard, & Woo, 1986). Utilizing unconventionalmethods to compete with others in the marketplace may be particularly important forsmall business owners (Cooper & Dunkelberg, 1986; Stone, 1995).

Entrepreneurial orientation as indicated by the three measures of innovativeness,proactiveness and risk taking, is posited to contribute to firm performance in smallbusinesses. Based on previous research, there is no reason to expect that malesmall business owners in this study should be more entrepreneurially oriented thanfemales. Following these findings then we propose that:

H1: There are no significant differences between males and females in theirreported levels of entrepreneurial orientation.


If females and males have similar levels of entrepreneurial orientation, then thisresource should lead to increased firm performance for both male and female smallbusiness owners. Thus we posit that:

H2: Entrepreneurial orientation is significantly and positively related to firmperformance for both male and female-owned small businesses.

Social capital

Portes and Sensenbrenner (1993) conceptualized social capital as the expectationsfor action within a group or organization, that affect economic goals of its members.Social capital is an intangible resource, and a term originally used to describerelational resources, occurring in cross-cutting personal ties (Tsai & Ghoshal, 1998).Social capital is manifest from social structures comprised of relationships (Putnam,1995). Close relationships can create trust and obligations, and define expectationsamong trading partners (Gulati, 1995). Coleman (1988) suggested that social capitalexists in organizations and communities alike. Like the economic version of capital,it is a productive resource for businesses (Burt, 1992; Coleman, 1990). Its value isderived from its focus on the positive outcomes of sociability (Portes, 1998).

While business owners can build up social capital amongst themselves, it is thecommunity aspect of social capital that is important in this study. Social capital mayhelp to create competitive advantage for a firm, through the exchange of informationamong members (Nahapiet & Ghoshal, 1998). Social capital can serve as a resourcefor small business owners, if it helps to increase the number of local consumers whopatronize a business. Social capital theory provides a means to help explain theinteraction of local consumers and small business owners. Putnam (1993) found thatthere is a positive relationship between the amount of available social capital in anarea, and the area’s economic well being. Miller and Kim (1999) found evidence thatsocial capital explains some of the “in-shopping” of local consumers in ruralcommunities. Social capital was found to be a positive influence on local consumers’attachment to a community (Miller & Kim, 1999).

The components of social capital that are salient to the current research are reciprocityand shared vision (Tsai & Ghoshal, 1998), and constructs of social networks(Granovetter, 1973) including density of network ties and social homophily.Relationships between individuals who have built reciprocity and commitmentthrough their networks create a competitive advantage (Burt, 1997; Tsai & Ghoshal,1998), leading to deeper and finer-grained information exchange. Small businessowners who develop dense social networks will also develop greater levels of trustin those networks (Greve, 1995). If a small business owner can develop these typesof relationships with local consumers, it may lead to better consumer feedback, andmarket knowledge.

Reciprocity Repciprocity refers to a “network” in which each member has somethingto provide to the other. When something is provided, there is an expectation of somesort of quid pro quo. Reciprocity contributes to social capital through network


members who amass favors, which can be called upon as resources when needed(Portes & Sensenbrenner, 1993). Miller and Kean (1997) refer to communityreciprocity as an expected exchange between local consumers and local retailers.They found that local consumers were more likely to shop with local retailers whenthose retailers expressed a high level of support for the community. Lumpkin, Hawesand Darden (1986) had similar findings, but also found that consumer attitudes aboutrelationships with local retailers were a more important determinant of patronagethan any other variable. Support for the relationship of reciprocity’s effect on smallbusiness owners was found by Miller (2001). In her study of consumers in two ruraltowns, consumer satisfaction with reciprocity levels was a significant predictor of in-shopping behavior. Thus, reciprocity helps small business owners to develop socialcapital with local consumers.

Shared vision This construct reflects the collective goals of a group, organization ora community (Tsai & Ghoshal, 1998). It is a part of social capital that pertains less tothe idea of economic transaction between business owner and customer (implied inthe constructs of reciprocity and trust), as it does to the collective interest or valuesof business owners. This construct is salient to the current study as the sample wastaken from small business owners within downtown business districts. In this sense,shared vision is a construct related to how members of a business district envisionthemselves as part of the downtown, and what common goals are shared. Not allbusiness owners may perceive themselves to be a cohesive group. In spite of this,shared vision can mitigate this perceived lack of cohesion, as studies have shownthat a shared vision can serve to hold together a loosely coupled system (Orton &Weick, 1990). Nahapiet and Ghoshal (1998) referred to shared vision as one thatfacilitates a common understanding of collective goals. Tsai and Ghoshal (1998)found that shared vision was a statistically significant and positive indicator of socialcapital.

Shared vision is also an important area with regards to the local community.Focus groups have shown that it is important for all stakeholders (especiallydowntown stakeholders) to support and “buy in” to marketing programs and imagecreation (Office of the Governor, 2003). To the extent that members of a communityand downtown business owners all view the importance of the downtown similarly,that downtown should be successful.

Small business owners who can build a trusting relationship with local consumerswill likely receive customer loyalty in return. If the loyalty from the consumer ismanifest in patronizing the small business, then reciprocity has occurred. These twocomponents of social capital should lead to success for the small business owner.When business owners in a downtown share the same goals, it may translate into amore unified image of the downtown to the consumer. If a shared vision exists, thenthe social capital manifested in the trust and reciprocity from consumers could havea “halo” effect for other downtown businesses. The successful small business thuscontributes to the success of the downtown through the development and use ofsocial capital.

Density Density of networks refers to the number of ties that link network members,compared to the total possible ties (Granovetter, 1973). It is an indication of the


interconnectedness of members in a network (Wellman, 1988). Density is an indicatorof cohesiveness, and helps to establish trust among network members (Axelrod, 1984;Greve, 1995). Cooperation, commitment and collaboration are enhanced throughdensity of network ties (Axelrod, 1984; Cross, Borgatti, & Parker, 2002).

Ties within networks (between individuals) are affected by the density ofthose ties and the perceived level of homophily between members (Cross et al.,2002; Granovetter, 1973;). How network norms and values are disseminated andadopted will be a function of the underlying structure of the network (Borgatti &Foster, 2003). Network density can help explain shared attitudes and culture throughinteraction. The diffusion of an idea or shared practice is modeled as a function ofinterpersonal transmission along some “durable” communication channel (Borgatti &Foster, 2003).

Perceptual homophily Perceptual homophily is the extent to which persons perceiveothers as being like themselves (Blau, 1961; Cross et al., 2002; Lazerfeld & Merton,1964). The notion that people tend to associatewith otherswhom they perceive as similaris supported in general in the trade media and scholarly journals alike (McPherson,Smith-Lovin, & Cook, 2001). Cross et al. (2002) see homophily as increasing thelikelihood of communication in groups. Frazier (2000, unpublished data) found that thelevels of perceived homophily among small retailers was a positive indicator ofnetwork ties, and through network ties, a contributor to social capital.

Research on the use of social capital by women small business owners has producedmixed results. Lacking equal access to financial and managerial resources, exploitingsocial capital could be a strategy for female-owned businesses to level the playing field.For example, a study of Israeli female entrepreneurs disclosed that affiliation with onenetwork was significantly related to profitability, while participation in multiplenetworks demonstrated an inverse relationship to revenues (Lerner, Brush, & Hisrich,1997). Though women are adept at turning social resources into human and economicresources (Inman, 2000), they tend to have fewer of these entering a business start-up(Brush et al., 2002). Specifically, Brush and her colleagues found that a lack of socialcapital and networks were key reasons why female entrepreneurs had less access toventure capital funding in high-growth industries. Smeltzer and Fann (1989) foundthat women business owners sought information from other women significantly moreoften than for men, perhaps limiting their access to financial resources controlled bymale dominated networks. Yet Menzies et al. (2004) found no differences betweenmale and female entrepreneurs in their reported social contacts used to build theirbusinesses. The lack of clear-cut findings on the contribution of social capital can beattributed to the extremely small amount of work on social capital and female-ownedbusinesses in the extant literature.

The extant literature points to a positive contribution to performance from theexistence and use of social capital by small business owners. There have been mixedresults when considering the effects of social capital on female-owned firmperformance, as well as whether or not women come into a business with similar levelsof social capital as men. Therefore we assert that:

H3: There are no significant differences between males and females in theirreported levels of social capital.


Though lack of social capital for females has been shown to negatively affectwomen’s ability to obtain venture funding in high-growth industries (Brush et al.,2002), their ability to nurture relationships and possession of superior people skills(Daniel, 2004) should be effective in a small business format. Access to financingmay not be as important for a very small business (as female-owned firms tend tobe), as for larger or high-growth firms. We propose:

H4: Social capital is a significant and positive indicator of firm performancefor both male and female-owned small businesses.

Methodology

A series of four focus group interviews with small business owners in downtownbusiness districts were conducted to inform survey development for the currentstudy. We used focus group feedback and theoretically supported measurementscales to develop our survey. Scales designed to measure the EO of business ownerswere developed and operationalized by Covin and Slevin (1989) and Miller andFriesen (1978) and further operationalized in a small business setting (Covin &Slevin, 1989; Miles, Covin, & Heeley, 2000; Niehm, 2002, unpublished data;Runyan & Huddleston, 2006). Our nine EO scales focus on innovation, proactive-ness and risk taking. Covin and Slevin (1989) factor analyzed the nine items andfound a distinct unidimensional EO with composite reliability of 0.87. Each item ismeasured on a seven-point Likert scale anchored from “strongly disagree” to“strongly agree”, with the mean rating on the items used as the small businessowner’s total EO score: the higher the score, the more entrepreneurially orientedthey are considered. The measures are found in Appendix.

Social capital constructs were measured utilizing previously operationalizedscales. Reciprocity is measured using a five item scale, three items from Miller andKean (1997), achieving a reliability of 0.85, and Frazier (2000, unpublished data)who reported a reliability of 0.87. Each item was measured on a seven-point Likertscale anchored from “strongly disagree” to “strongly agree”. The items wereintended to measure the extent to which small business owners feel that localconsumers patronize their business, due to built up social capital (i.e., returningfavors, quid pro quo, etc.). We added two items to the scale to measure whether thesmall business owner feels that their support of the community is directlyreciprocated by customers patronizing their business. Shared vision was measuredusing a three-item scale from Tsai and Ghoshal (1998). These items were measuredon a seven-point Likert scale, anchored from “strongly disagree” to “strongly agree”.The reliability reported by Tsai and Ghoshal (1998) was 0.71. Density is the numberof ties that network members maintain (Granovetter, 1973), and was measured on athree-item, seven-point summated rating scale anchored from “not true at all” to “verytrue”. Each item was intended to identify the degree to which network membersinteract with each other, and was designed for work on networks of small retailers. Thescales were also operationalized by Frazier (2000, unpublished data) and Niehm(2002, unpublished data), with reported reliabilities of 0.84 and 0.89 respectively.


Homophily is measured using scales devised by Frazier (2000, unpublished data) toinvestigate groups of small retailers. They are intended to measure the degree to whichrespondents feel that other network members share their outlook on life, values andbusiness philosophy. The scale contains four items, each measured on a seven-pointLikert scale anchored from “strongly disagree” to “strongly agree”, and obtained areported reliability of 0.76. The measures appear in Appendix.

Small business performance was measured using three indicators, adapted fromFrazier (2000, unpublished data) and Niehm (2002, unpublished data). The scalesask the respondent to describe the performance of their firm compared to last year,compared to major competitors and compared to other similar firms in the industry.The items are measured on a seven-point semantic differential scale, anchored from“poor” to “excellent”. The measures appear in the Appendix, along with scalereliability and variance extracted.

The sampling frame of our study was restricted to small/medium sized, nonurbanrural communities in two U.S. states (Michigan and Oklahoma). The towns includedin this sample fit the nonurban rural criteria used by the U.S. Census (2004), i.e.,populations of 5,000 to 30,000 and located more than 30 miles from a metropolitanstatistical area (MSA). There were a total of 467 respondents, from 21 separatecommunities. A total of 1,800 surveys were disseminated via a drop off and pick upprocedure. Four hundred sixty-seven usable surveys were returned, for a responserate of 25.9%. This response rate is higher than those of similar, previous studies ofsmall businesses (e.g., Brush et al., 2001—9.5%; Conant & White, 1999—13.1%;Frazier 2000, unpublished data—12.1%).

Sample description

The final sample consisted of 467 owners of small businesses within the centralbusiness district in 21 communities. The populations of these communities rangedfrom 2,972 to 25,496. In the sample, 76% of businesses had been in existence for 7or more years, 50% for 22 or more years, with 66% reporting that their business hadbeen downtown for more than 7 years. Forty-five percent had been located downtownfor 16 or more years. In general, the firms fit the profiles of small businesses asmeasured by the number of full and part-time employees: 58% reported having 2 orfewer full-time employees, including themselves and over 82% reported five or fewerpart-time employees, including themselves. Fifty-two percent of the respondents weremale. Table 1 reports the sample demographics.

Analyses and results

We used two types of analytical tools to test the four hypotheses. To test fordifferences between males and females in their reported levels of EO and SOCAP,we conducted one-way ANOVAs (Table 2). To test for the effects of EO and SOCAPon firm performance, and to test for differences in firm performance based ongender, we utilized structural equation modeling. Because we were working with a


large number of measurement variables (nine EO; fifteen SOCAP), we knew thatwhen moving to fitting the structural model that this could pose a problem. If thereare too many parameter estimates specified in a model, there is a danger ofunderspecification (Kline, 1998). A solution to this potential problem is to averagemanifest indicators into a smaller number of indicators for latent constructs (Yuan,Bentler, & Kano, 1997). We used this procedure after conducting confirmatory factoranalyses, which allowed us to confirm the reliability and construct validity of each ofthe scales.

We used structural equation modeling with LISREL 8.72 to test the fit of themeasurement and structural models using maximum likelihood (ML) estimation. MLwas chosen based on the normal distribution of the data, sample size and variables

Sample characteristic Frequency Percentagea

GenderMale 242 51.8Female 209 44.7Age40 or less years 85 23.241–50 years 106 28.851 years and over 176 48.0EducationHigh school graduate 59 14.3Some college 123 30.0College graduate 184 44.8Postgraduate degree 45 10.9Family businessYes 334 71.5No 117 25.1Years business has existed6 or less 100 22.57–15 87 19.516–30 122 27.431 or more 136 30.6Years in downtown6 or less 142 32.67–15 90 20.616–30 108 24.831 or more 139 32.0Years of current owner6 or less 148 37.97–15 96 24.516–30 103 26.331 or more 35 9.0Full-time employeesNone 35 9.21–2 186 48.83–5 99 26.06 or more 61 16.0Part-time employeesNone 43 12.61–2 156 45.63–5 86 25.06 or more 57 16.7

Table 1 Sample characteristics

a Less than 100% due to missingdata


measured using interval-level scales (Schermelleh-Engel, Moosbrugger, & Muller,2003). A two-step process was used, where confirmatory factor analyses (CFA) wereconducted on the measurement model (Anderson & Gerbing, 1988) before testing thestructural model. From the CFAs we were able to assess scale reliabilities, varianceextracted and validity of the constructs. Model fit was assessed using severalmethods. We assessed the χ2 statistic, which evaluates the difference between thespecified model’s covariance structure and the observed covariance structure (Bollen1989). Following this, we reviewed the standardized residual matrices to identifylarge residuals (positive or negative) which contributed most to poor fit. We alsoutilized several other statistics to assess model fit. These included root mean squareerror of approximation (RMSEA), comparative fit index (CFI), and adjustedgoodness of fit (AGFI). We used the following cutoff criteria in assessingacceptable model fit: RMSEA<0.08; AGFI>0.90; CFI>0.90; p>0.05, and goodmodel fit: RMSEA<0.06; AGFI>0.90; CFI>0.95. These criteria are generallyacknowledged as acceptable and good model fit criteria, respectively (Bagozzi & Yi,1988; Bollen, 1989; Hu & Bentler, 1999; Kline, 1998).

Measurement evaluation

We first conducted CFAs on both of the latent constructs of EO and SOCAP. EOencompassed innovativeness (INNOV 1,2,3), proactiveness (PROAC 1,2,3) and risktaking (RISK 1,2,3). All nine measurement variables loaded directly on the EOconstruct. Results of the CFA were (χ2=74.81, df=23, p=0.000; RMSEA=0.070;AGFI=0.93; CFI=0.97). All parameter estimates were significant at the p<0.05

Table 2 ANOVA: EO, SOCAP and gender

N Mean Std. deviation Sum of squares df F Sig.

INNOV Males 242 4.2982 1.33516Females 209 4.6587 1.17132

729.567 1,450 9.152 0.00PROAC Males 242 4.2720 1.11304

Females 209 4.3525 1.16146579.879 1,450 0.562 0.45

RISK Males 242 3.8753 1.01155Females 209 4.0662 1.00732

461.742 1,450 4.007 0.04RECIP Males 242 4.9785 1.02051

Females 209 5.1694 0.95057443.018 1,450 4.179 0.04

VIS Males 242 4.6970 1.45186Females 209 4.9553 1.34167

889.903 1,450 3.809 0.05DENSE Males 242 4.8492 1.20687

Females 209 5.0415 1.20424656.810 1,450 2.853 0.09

HOM Males 242 4.1684 1.15816Females 209 4.3517 1.11412

585.214 1,450 2.909 0.09


level, indicating convergent validity. The composite reliability for EO was 0.70, andvariance extracted was 0.404 (Appendix).

SOCAP included four latent constructs, including reciprocity (RECIP 1,2,3,4,5),shared vision (VIS 1,2,3), network density (DENSE 1,2,3) and homophily (HOM1,2,3,4). All 15 measurements were loaded on to their respective latent construct.Initially the fit was not acceptable. Standardized residuals showed that there werelarge problems with RECIP5 and several other variables. This variable was onewhich was added to the existing (and previously operationalized) scale. Fortheoretical reasons it made sense to eliminate it from further analyses. The modelwas thus respecified and the results of the CFA were (χ2=163.60, df=69, p=0.000;RMSEA=0.054; AGFI=0.93; CFI=0.95). All parameter estimates were significantat the p<0.05 level indicating convergent validity. The composite reliability for thescale was 0.711, and variance extracted was 0.501 (Appendix).

Following the fitting of the CFAs, the measurement model was fit. At this step wewere able to establish the nomological network for the model, testing for bothconvergent and discriminant validity. From the CFAs we were able to establish thateach of the observed measures loaded significantly on the specified theoreticalconstructs, with no cross loading between those and latent constructs. Therefore wewere confident that averaged variables created from those measures would be sound.Averaged variables have been found to be more robust than using marginal variables(Yuan et al., 1997). The measurement model was fit with the seven averagedvariables, and achieved good fit (χ2=18.93, df=13, p=0.125; RMSEA=0.031;AGFI=0.98; CFI=0.99). The parameter estimates were all significant at the p<0.05level indicating convergent validity. Each variable loaded on its respective latentconstruct indicating discriminant validity. Parameter estimates for the model arefound in Table 3.

Hypothesis testing

Hypotheses one and three dealt with differences in group means. Analysis ofvariance was conducted to test both H1 and H3. We utilized the averaged variablesfrom the CFAs to make the analyses more parsimonious. Hypothesis 1 stated thatthere would be no significant differences between males and females in theirreported levels of EO. Based on the analysis of variance, we reject H1. There weresignificant differences between the men and women on two of the three compositemeasures. The two variables in which there were significant differences were

Path label Parameterestimate

t value Standardizedestimate

INNOV-EO 0.96 15.03* 0.76PROAC-EO 0.83 14.68* 0.74RISK-EO 0.62 12.57* 0.62RECIP-SOCAP 0.37 7.28* 0.30VIS-SOCAP 0.91 13.10* 0.65DENSE-SOCAP 0.86 14.47* 0.72HOM-SOCAP 0.79 14.20* 0.70EO-SOCAP −0.02 −0.34 −0.02

Table 3 Parameter estimates formeasurement model

*p<0.05χ2 =18.93, df=13, n=467,p = 0 .125, RMSEA= 0.031,AGFI=0.98


innovativeness and risk taking. For INNOV, females (μ=4.66) reported higher levelsof innovativeness than did males (μ=4.30), p=0.00. Females (μ=4.07) reportedslightly higher levels on the RISK variable than did males (μ=3.87), p=0.04(Table 3).

In hypothesis three, we suggested that there were no significant differencesbetween male and female business owners in their reported levels of social capital.The analysis of variance revealed that females reported higher levels of social capitalthan males on all of the composite measures, and significantly higher levels on twoof the four constructs. For RECIP females had a mean score of 5.17 to that of 4.98for males (p=0.04). Females reported higher scores for VIS (μ=4.96) than did males(μ=4.70, p=0.05). Thus we must reject H3 as there are significant differences insome forms of social capital.

To test hypotheses two and four we fit the data to a structural model to firstestablish a baseline model. Initial specification of the model (Fig. 1) produced agood fit, with no modifications needed (χ2=42.10, df=32, p=0.110; RMSEA=0.026; AGFI=0.978; CFI=0.97).

All parameter estimates were significant, including the paths from EO to PERF(0.17) and from SOCAP to PERF (0.18) indicating that for the entire sample, bothEO and SOCAP were significant and positive indicators of firm performance(PERF). Parameter estimates for the structural model appear in Table 4. To test fordifferences by gender, we then fit the data to separate models for males and females.Measurement loadings were specified as invariant across groups. Two models werefit: (1) first the EO-PERF and SOCAP-PERF paths were specified as equal across

Fig. 1 Structural model—EO SOCAP PERF


groups and (2) second these paths were freed across groups. The difference betweenthe two models was χ2=1.25, df=2, which is not significant at the p<0.05 level.Therefore we conclude that there was no difference in the models, and that there wasnot a significant difference between males and female small business owners. Bothseem to utilize an entrepreneurial orientation and social capital to improve theperformance of their businesses.

Discussion and implications

The purpose of our study was to examine the contribution of nonfinancial, intangibleresources (entrepreneurship and social capital) to the success of small firms and topinpoint differences between male and female owned businesses. To examine ourresearch questions we collected data from small businesses in nonurban ruralcommunities in Michigan and Oklahoma.

We defined the constructs of entrepreneurial orientation as innovativeness, risktaking and proactiveness. Confirmatory factor analysis confirmed that these threeconstructs were statistically significant indicators of entrepreneurial orientation. Weidentified reciprocity, shared vision, network density and homophily as the indicatorsof social capital. Again, all were statistically significant indicators of social capital.

Contrary to what we hypothesized, analysis of variance revealed significantdifferences between males and females in their reported levels of entrepreneurialorientation. Specifically, risk taking and innovativeness, two of the three dimensionsof entrepreneurial orientation, were different between the genders. This is contrary toearlier work (Fagenson, 1993; Masters & Meier, 1988). However when examiningthe mean responses for both genders, we found that only one of the two significantlydifferent variables were meaningfully different. That variable was innovativeness,with females reporting a mean of 4.67 to that of 4.30 for males. For risk taking, thereported means were closer, with females at 4.07 and males at 3.87. The salient issuehere concerns the scaling of the measures. We used a seven-point Likert scale, sothat the means reported seem to be hovering around the neutral point. It seems thatneither males nor females in our sample are prone to risk taking. These two findingscould be a reflection of two aspects of our sample: First the fact that women in our

Path label Parameterestimate

t value Standardizedestimate

INNOV-EO 1.00 0.76PROAC-EO 0.87 10.62* 0.74RISK-EO 0.64 10.28* 0.61RECIP-SOCAP 1.00 0.30VIS-SOCAP 2.40 6.66* 0.64DENSE-SOCAP 2.29 6.80* 0.72HOM-SOCAP 2.10 6.78* 0.70EO-PERF 0.17 2.93* 0.17SOCAP-PERF 0.35 2.21* 0.18BPER1-PERF 1.00 0.76BPER2-PERF 1.20 18.20* 0.90BPER3-PERF 1.08 17.81* 0.83

Table 4 Parameter estimates forstructural model

*p<0.05χ2 =42.10, df=32, n=467,p = 0 .109, RMSEA= 0 .026,AGFI=0.97


sample were more likely to own retail businesses than men, may contribute to theinnovativeness scores. Two of the three measures for INNOV dealt with introducingnew products or product lines. For retail firms, new product introduction is a criticalsuccess factor. This supports the finding of Brush and Hisrich (2000) that womenowned businesses more often follow innovation strategies than men ownedbusinesses. Second, the size of firms in our study were generally very small andgenerally in low-growth sectors (e.g., retail, real estate, personal services, etc.).Therefore risk taking for both genders may be low, and any differences are reallymore about risk aversion than risk taking.

Women reported higher levels of social capital on all four composite measures.We found significant differences between males and females in their reported levelsof shared vision and reciprocity, with women reporting significantly higher levels ofthese dimensions. This coincides with Daniel’s (2004) observation that women havebetter networking skills and are better consensus builders than men. Their ability toexcel in relationship building by consulting with others (e.g., experts, employees andfellow owners) provides a logical segue to shared vision (Center for Women’sBusiness Research, 2004). Thus it is not surprising that women form reciprocalnetworks that they can count on. Our finding contradicts Brush et al. (2002) whofound women business owners to lack social capital. No significant differences werefound for network density (number of ties and the degree to which network membersinteract with each other) and homophily (the degree to which respondents feel othernetwork members share their outlook on life, values and business philosophy). Thus,it appears that both men and women business owners have equally cohesivenetworks. That we found no significant difference between men and women onnetwork density supports Menzies et al. (2004) who found no differences betweenmale and female entrepreneurs in reported social contacts when building a business.

We fit a structural model to test the relationship between entrepreneurialorientation, social capital and business performance. Our analysis revealed thatentrepreneurial orientation and social capital were positive and significant indicatorsof firm performance for both men and women. These results support previousempirical work (Covin&Slevin, 1989; Lerner et al, 1997; Niehm, 2002, unpublisheddata; Stone, 1995). Thus, both men and women use these intangible resources as ameans to gain a competitive advantage and are able to translate these resources intosuccessful performance.

Our findings lend credence to RBV, which posits that resources create competitiveadvantages for firms. We investigated nontangible resources of social capital andentrepreneurship and tied them to firm success. These resources contributed similarlyto the success of both male and female owned businesses.

While women exhibit higher levels of both entrepreneurial orientation and socialcapital, the lower levels reported by men do not appear to negatively affect their firms’performances. Do entrepreneurial orientation and social capital level the playing field?In this study, both seem to be gender neutral in terms of contributions to firmperformance. While women exhibited higher levels of both EO and SOCAP, neitherappear to provide a differential advantage for firm success over men. These findingsraise several questions: in certain industries (in this case, small service and retailfirms), do women achieve success levels similar to men due to greater levels of


entrepreneurial behavior? Have men and women learned to employ social capitalequally well in running their firms? Our study shows that in certain business settings,women are using these two sets of resources equally and achieving successful firmperformance.

Females seem to have made inroads in terms of ownership in the very smallbusiness sector, and are translating their resources into success. The gender breakdownin our sample was fairly evenly split, with 52%males and 48% females. In low-growthsectors, females have discovered how to use entrepreneurial skills and social capital.Does this mean that those resources can be leveraged in other sectors too? Or does thismean that women have not learned to exploit their differential advantage in socialcapital and translate it into business success in high-growth industries as Brush et al.(2002) note? Perhaps our results reflect the progress that women have made over thepast decade in accessing and utilizing both tangible and intangible resources (albeitin small firms).

High growth industries (e.g., extraction or transformation industries), where asignificant proportion of wealth creation occurs, are currently dominated by men. Yetprior to 30 years ago, the sector studied here was also dominated by men. If womenwant to share in the wealth creation opportunities of the current high-growthindustries, there must be a mechanism to help them gain access to significant financialresources. Sources of financial backing for entrepreneurs include personal wealth,bank loans, venture capital and funding from government sponsored programs such asthe SBA. However, previous research (Brush et al., 2002) has demonstrated thatwomen do not have equal access to financial resources from banks and venturecapitalists. Strategic use of social capital may be the first step in gaining equal accessto these resources. The knowledge that social capital is positively and significantlyrelated to business performance should provide impetus to decision makers to deviseways to broaden the social networks available to women entrepreneurs.

There are some limitations to our study which may affect the generalizability ofour results. First, our sample was drawn from small, nonurban rural towns in theMidwest, thus the results may differ for cities outside this area or to larger towns(e.g., 50,000+ population). Second, we employed a judgment sample, rather than arandom sample. Third, while we attempted to use established scales to measure theconstructs of interest, we developed some new items and further refinement may benecessary as some items did not seem to fit the model well during confirmatoryfactor analyses.

Future research should examine network composition and the extent to whichwomen rely on their networks as a resource. Our study did not examine sources ortypes of information gathered from their networks, nor did we identify the size andcomposition of their networks. Another promising avenue to pursue would be toexplore other tangible and intangible resources which contribute to firm success forboth men and women owned businesses. For example, how do they employ theirsocial capital to inform their business operations? A study of how social networksare used to gain access to venture capital would be another topic worthy ofinvestigation.

We conclude that men and women bring similar entrepreneurial tendencies to thebusiness environment. While both genders exhibited similar EO, it may be fruitful to


probe for subtle differences in innovative tendencies, particularly since women aremore likely than men to own and operate retail businesses, which depend oncontinuous product mix innovation for success. Does entrepreneurial orientationinfluence business strategy selection? The populations of towns in this study werepredominantly Caucasian. Future research should include towns with a more diversepopulation base and those located within metropolitan statistical areas.

Appendix

Table 5 Measurement scales: entrepreneurial orientation

Latentfactor

Measurement items and scale alpha

EO INNOV: Bipolar statementsINNOV1 Favor a strong emphasis on the marketing

of tried and true products or servicesOR A strong emphasis on R&D, technological

leadership and innovationINNOV2 Has introduced no new lines of products

or servicesOR Very many new lines of products or

servicesNNOV3 Changes in product or service lines have

been mostly of a minor natureOR Changes in product or service lines have

been quite dramaticPROAC: bipolar statements

PROAC1 Typically responds to actions whichcompetitors initiate

OR Typically initiates actions whichcompetitors then respond to

PROAC2 Is seldom the first business to introducenew products/services, administrativetechniques, operating technologies, etc.

OR Is very often the first to introduce newproducts/services, administrativetechniques, operating, technologies, etc.

PROAC3 Typically seeks to avoid competitiveclashes, preferring a “live-and-let-live”posture

OR Typically adopts a very competitive,“undo-the-competitors” posture

RISK: bipolar statementsRISK1 Strongly favor low-risk projects (with

normal and certain rates of return)OR Strongly favor high-risk projects (with

chances of very high return)RISK2 Believe that owing to the nature of the

environment, it is best to exploregradually via timid, incrementalbehavior

OR Believe that owing to the nature of theenvironment, bold, wide-ranging acts arenecessary to achieve my firm’sobjectives

RISK3 Typically adopt a cautious, “wait-and-see” posture in order to minimize theprobability of making costly decisions

OR Typically adopt a bold, aggressive posturein order to maximize the probability ofexploiting potential opportunities

Composite reliability = 0.700 Variance extracted 0.404

EO Entrepreneurial orientation, INNOV innovativeness, PROAC proactiveness, RISK risk taking

Table 6 Measurement scales: social capital

Latent factor Measurement items and scale alphas

SOCAP RECIP 1= strongly disagree; 7 = strongly agreeRECIP1 These people are generally fair in dealings with meRECIP2 These people would be willing to do me a favor if askedRECIP3 We do favors for each other from time to time


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DENSE 1= not true; 7= very trueDENSE1 They know each other by nameDENSE2 They talk to each other regularly about business/downtown issuesDENSE3 They see each other regularly in business/downtown situations

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Entrepreneurial orientation and social capital as small firm strategies: A study of gender differences from a resource-based view