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date: 07 December 2019

Social Capital and Founder, Team, and Firm Networks in Entrepreneurship

Summary and Keywords

Entrepreneurial activity is facilitated by the ties that connect founders and their venture to a broader network of actors. This insight on the value of social capital has been enriched by a large body of research that builds on core concepts of network content, governance, and structure. Network content refers to the resources, information and social support that is exchanged or flows between actors. Governance encompasses the mechanisms that organize and regulate the exchange. Network structure refers to broader patterns created from the relationships between actors. With these building blocks, key findings that have emerged over 30 years of research can be organized into two domains: how networks influence entrepreneurial outcomes and how networks develop over the entrepreneurial process. Core findings regarding the performance consequences of social capital underscore its benefits while identifying limitations due to decreasing returns to growing and maintaining a large network or to contingencies tied to the stage of the venture’s growth. Our understanding of the sources of network evolution and the resulting patterns have also developed significantly. As a motor of network change, scholars have emphasized the goal-oriented behavior of the entrepreneur, but recognize social relationships also engender mutual concern, obligation, and emotional attachment. From a focus on founder and founding team ties to start-up, small firm networks, the literature now spans multiple levels and accounts for contextual variation between industries and institutional environments. Advances within each of these domains of inquiry have led to rich insights and greater conceptual complexity. Future research opportunities will arise that leverage cross-fertilization of the process and performance research streams.

Keywords: social capital, networks, entrepreneurship, entrepreneurial process, entrepreneurial outcomes, network content, network structure, network governance

Recognition of the importance of social capital in the entrepreneurial process reflects the view that entrepreneurs or business founders are not atomistic economic actors who rely solely on the resources that they develop and uniquely control. Instead, entrepreneurs are seen as intimately tied, through their social relationships, to a broader network of actors with resources that can be accessed and leveraged. The entrepreneurial process is intertwined with social relationships to such an extent that understanding the economic outcomes that result from entrepreneurial activity must account for this embeddedness (Adler & Kwon, 2002; Aldrich & Zimmer, 1986).

This article details how social capital contributes to entrepreneurial activity by focusing on key aspects of networks. Social networks are defined by a set of actors (individual, venture team, or organization) and the set of linkages between them. Three elements of networks are critical to theoretical and empirical research in this field: (a) network content refers to the nature of the content that is exchanged or flow between actors, (b) governance mechanisms organize and regulate the exchange, and (c) network structure refers to broader patterns created from the relationships between actors.

These three components shed light on the impact of networks on entrepreneurial outcomes typically viewed as positive consequences of the entrepreneurial process that result in wealth creation. They are also conceptual building blocks for an understanding of the network development process that occurs during entrepreneurial activity including opportunity identification, resource mobilization, and the creation of an organization (Shane & Venkataraman, 2000). In what follows, the academic literature1 is reviewed to shed light on the impact of social capital on entrepreneurial outcomes and insights regarding its development over time.

Core Elements

Network Content

A key feature of social capital as a mechanism for facilitating entrepreneurial activity lies in the resources that are accessible through social relations. Network content refers to the nature of the content that is exchanged or flows between individuals or organizations. Networks are a means of gaining access to capital including financing. They also provide access to information and advice. Studies highlight that entrepreneurs form and leverage social ties to get ideas and gather information to recognize entrepreneurial opportunities (Anderson, Park, & Jack, 2007; Florin, Lubatkin, & Schulze, 2003; Ozgen & Baron, 2007).

Network content can also encompass the emotional support for entrepreneurial risk-taking (Brüderl & Preisendörfer, 1998), and this in turn is thought to enhance persistence to remain in business (Gimeno, Folta, Cooper, & Woo, 1997). Social relationships can involve an affective component leading to shared sentiments including liking, concern, and obligation that can influence frequency and quality of interactions that in turn facilitate resource access for the entrepreneur.

In a study of nascent entrepreneurial activity in Sweden based on a representative sample of the population, Davidsson and Honig (2003) examined whether strong ties to parents, friends, and family were predictive of taking initial steps toward business founding. Their data show that ties likely to predate these activities are critical, successfully differentiating the group engaged in nascent activities from a control group. They also found that ties to business support and service organizations were predictive of nascent entrepreneurial activity.

The reliance on networks can extend beyond the start-up stage and the resource flow can be between organizations. Ties to venture capitalists and professional service organizations are a means whereby entrepreneurial firms tap into key talent and market information (Freeman, 1999) while ties to distributors, suppliers, competitors, or customer organizations can be important as conduits of information and know-how (Brown & Butler, 1995). Information and resources to internationalize can be gained from knowledgeable members of the network that can augment a firm’s own experience (Al-Laham & Souitaris, 2008; Tang, 2011). More generally, different patterns in how external and internal resources are combined have an important role in shaping firms’ subsequent growth (Rindova, Yeow, Martins, & Faraj, 2012).

Another view on network content moves beyond the tangible and intangible resources that may flow through the ties and instead sees networks as “prisms” that shape individuals’ interpretation of the entrepreneurial role. Network ties to new contacts can reinforce an emerging identity and can thus play a key role in the transition process of becoming an entrepreneur. For example, strong and dense networks ties outside the university context can support a role-identity shift increasing the likelihood that an academic will leave to start a venture (Nicolaou & Birley, 2003). Having ties to co-workers who have experience starting their own business can also facilitate entrepreneurial activity, possibly by increasing motivation and reducing fear of failure (Nanda & Sørensen, 2010). Leveraging data collected across 20 European countries, Klyver, Hindle, and Meyer (2008) concluded that having entrepreneurs in one’s social network increases the possibility of becoming an entrepreneur, although the magnitude of this effect varies across countries.

Relationships can also have reputational or signaling content from the perspective of other network participants or alters (Deeds, Mang, & Frandsen, 1997; Elfring & Hulsink, 2003; Higgins & Gulati, 2003; Shane & Cable, 1998; Stuart, Hoang, & Hybels, 1999). In the uncertain and dynamic conditions under which entrepreneurial activity occurs, resource holders (potential investors and employees) are likely to seek information that helps to gauge the underlying potential of a venture. Entrepreneurs thus seek legitimacy to reduce perceived risk by associating with or by gaining explicit certification from well-regarded individuals and organizations. Delmar and Shane (2003) found that, in the nascent period, engaging sooner in activities that yielded greater legitimacy has a positive impact on early venture survival. Due to signaling benefits, a firm’s links to prominent strategic alliance partners are associated with faster growth, measured empirically by the speed with which the firm goes public and its valuation at time of initial public offering (Stuart et al., 1999).

The layering of different types of exchange between two actors is termed multiplexity in network parlance. For example, ties between family members undertaking entrepreneurial activity or involved in a family firm may be best characterized as multiplex ties because they include emotional support as well as access to resources (e.g., advice and labor). The study of kinship ties suggests that multiplex relations may be advantageous because they provide timely access and resources are obtained at low cost (Anderson, Jack, & Dodd, 2005). The process by which ties initiated primarily for economic exchange becomes layered with social exchange and vice versa has been the focus of a number of theoretical and qualitative studies beginning with Human and Provan (1996) who showed that relationships among firms in the network can be characterized as multiplex, involving friendship, information, and business exchange.

Having a greater number of multiplex ties may ensure that entrepreneurs can be more effective in mobilizing resources as trust and confidence are more likely to underpin such ties (Newbert & Tornikoski, 2012). However, multiplex ties may also be sources of constraint and conflict as business demands can run counter to social obligations and expectations. Hence, contacts with more power may resist an entrepreneur’s efforts to layer business ties with social relations (Vissa, 2012). In family firms, role expectations may impede effective collaboration under different conditions (e.g., parent–child relation impedes entrepreneur–employee relation) (Aldrich & Kim, 2005). They may also limit growth when entrepreneurs seek multiple resources from the same readily available contacts but the support provided is ill-suited to the venture’s needs (Jack, 2005).

Network Governance

Governance of network exchange relationships is a second component of social capital that can facilitate entrepreneurial activity and outcomes. Trust between partners is often cited as a critical element of network exchange that undergirds and coordinates network exchange that in turn enhances the quality of the resource flows (Larson, 1992; Lorenzoni & Lipparini, 1999). Other scholars have also defined network governance by the reliance on “implicit and open-ended contracts” that are supported by social mechanisms, such as power and influence (Brass, 1984; Krackhardt, 1990; Thorelli, 1986) and the threat of ostracism and loss of reputation (Jones, Hesterly, & Borgatti, 1997; Portes & Sensenbrenner, 1998) rather than legal enforcement. A number of scholars have asserted that these distinctive elements of network governance can create cost advantages in comparison to coordination through market or bureaucratic mechanisms (Jarillo, 1988; Jones et al., 1997; Lipparini & Lorenzoni, 1993; Starr & MacMillan, 1990; Thorelli, 1986). In particular, mutual trust as a governance mechanism is based on the belief in the other partner’s reliability to meet obligations in an exchange (Pruitt, 1981). Trust allows both parties to assume that each will take actions that are predictable and mutually acceptable (Das & Teng, 1998; Powell, 1990; Uzzi, 1997). These expectations reduce transaction costs associated with monitoring and renegotiating the exchange, especially in highly complex tasks facing strong time constraints (Jones et al., 1997). For example, a qualitative study of vertical relationships involving the purchase and supply of goods or services between networked firms revealed that the nature of the information exchange extends far beyond a discussion of price and quantity (Uzzi, 1997). Because of its positive impact on information flows, trusting behavior is cited as a critical factor in enhancing innovation through interfirm collaboration and an integral reason for the longevity of networks (Lipparini & Lorenzoni, 1993; Saxenian, 1991).

Network Structure

A third defining characteristic of a network perspective within entrepreneurship research is a focus on the dynamics of social structures and their impact on entrepreneurial phenomena. Network structure is defined as the pattern of direct and indirect ties between actors. A general proposition is that actors’ differential positioning within a network structure has an impact on resource flows, and hence, on entrepreneurial outcomes. A variety of measures, drawn from the network analysis literature, have been utilized to uncover patterns within the social structure that can then be used to characterize the differential positions of entrepreneurs or their ventures in the network.

A widely used network measure is size. With the entrepreneur as the focus of analysis, size is typically defined as the number of direct links between a focal actor and other actors. Analyses of network size measure the extent to which resources can be accessed at the level of the entrepreneur (Aldrich & Reese, 1993; Hansen & Witkowski, 1995) and the team (Vissa & Chacar, 2009). At the firm level, network size has been equated with a firm’s alliance portfolio. A recent review of work on alliance portfolios finds some evidence that, beyond a certain size, there may be limited benefits to adding more ties and partners (Wassmer, 2010). This is due to increasing redundancy across alliances that undermines the value of the portfolio as a whole (Vassolo, Anand, & Folta, 2004). In contrast, firms may also form ties with partners who operate in different stages of the industry value chain, thus offering greater potential for complementarity rather than competitive overlap (Baum, Calabrese, & Silverman, 2000).

Typically, network-based entrepreneurship research focuses on ego networks bounded by direct ties between contacts to the entrepreneur or the entrepreneurial firm. With a whole network perspective, greater theoretical and empirical emphasis is placed on the indirect linkages that can connect the actors. A measure of network position that leverages the importance of indirect ties is centrality. While this measure is conceptually similar to size, it explicitly includes the ability to access (or control) resources through indirect as well as direct links. Centrality taps the ability of actors to “reach” other actors in their network through well-connected intermediaries (Milanov & Fernhaber, 2009).

While network size and centrality measure the amount of resources that an actor can access, other patterns in the network structure influence their access to a diversity of resources. Granovetter’s (1973) notion of weak ties, in particular, describes the extent to which actors can gain access to new information and ideas through ties that lie outside of their immediate network of contacts. Weak ties serve as bridges across clusters of strongly interconnected actors and are typically operationalized by infrequency and short duration of the contact and role relationship (acquaintance vs. close friend) (Evald, Klyver, & Svendsen, 2006). At the organizational level, Bae, Wezel, and Koo (2011) find that cross-cutting alliances that connect different geographical regions introduce novelty and beneficial knowledge spillovers to a focal region that can in turn foster nascent entrepreneurial activity. New ventures can also be perceived as more valuable to partners when they can connect diverse but interdependent firms together and facilitate coordinated action (Ozcan & Eisenhardt, 2009).

Complementary to the benefits of weak ties are the theorized benefits of bridging structural holes, defined as the absence of ties between actors. To observe a structural hole, there must be at least three actors (a triad) with information on the ties between them and a lack of closure (no tie) between two of the actors. By bridging structural holes, actors can profit from establishing ties that bridge these otherwise unconnected actors (cf. Burt, 1992). Occupying a bridging position provides an opportunity to wield power or influence those who are otherwise not connected to the broader network (Krackhardt, 1995). Given this opportunity for diverse, nonredundant contacts, spanning structural holes can also increase the focal actor’s exposure to novel information and can serve as a basis for identifying and exploiting new opportunities (Burt, 2000). Furthermore, entrepreneurial firms can leverage brokerage ties to spur learning and the development of internal capabilities that ultimately enhance their performance (Baum et al., 2000; Zaheer & McEvily, 1999).

A number of studies on entrepreneurial firms have operationalized brokerage by assessing (low) network density (Burt & Raider, 2000; Zaheer & McEvily, 1999) and heterogeneity among network contacts as proxies (Baum et al., 2000; Hara & Kanai, 1994; Silverman & Baum, 2002; Zhao & Aram, 1995). Density is measured by the extent to which an actor’s contacts are interconnected: the denser one’s network of contacts, the less likely that new resources will enter. At the personal network level, a study of entrepreneurs’ membership in voluntary associations highlights that a means of countering such homogeneity may arise when entrepreneurs become members of a number of different associations. This in turn increases the diversity of their network and decreases its density (Davis, Renzulli, & Aldrich, 2006).

Empirical research collects information about ties with varying levels of completeness concerning the relations that connect all actors within a network. Kirkels and Duysters (2010) identified a group of founders and directors of design and high-tech firms as the basis for snowball sampling over subsequent waves thereby allowing instances of brokerage to be inferred from reported connections across partners. The constraints of collecting complete information have given rise to other methods such as the position-generator research method. This method assesses whether individuals know people within different groups (occupational or functional) so that having members of different groups in one’s network indicates high content diversity (Batjargal, 2006; Davis et al., 2006; Mosey & Wright, 2007). In another variant, a resource generator method collects information on facilitating resources that can be accessed through one’s network with less focus on the social structure of the relationships (Van Der Gaag & Snijders, 2005).

Consequences of Networks

Networks play an important role in entrepreneurial outcomes, notably the venture’s growth rate and financial performance. Stearns (1996) focused on strategic alliances among a sample of high-technology firms and found that among new firms (under 7 years of age), the presence of a foreign strategic partner was associated with higher rates of growth. Among young firms (between the ages of 7 and 12 years), less diversity in the types of arrangements was associated with lower growth. Zhao and Aram (1995) found, in a sample of Chinese entrepreneurs, that the intense use of networks distinguished high-growth from low-growth firms. Silverman and Baum (2002) found that ties to other firms occupying the same position in the industry value chain increased a firm’s ability to access venture capital funding, but these ties were found to lead to lower levels of revenue and a higher likelihood of failure. In contrast to the potentially stronger competitive effects exerted by horizontal ties, they found that alliances with complementary (downstream) firms were more consistently beneficial by increasing revenues and lowering failure rates. It should be noted that a number of early studies have found null results (Aldrich & Reese, 1993; Butler, Phan, & Hansen, 1990).

Another variant of the structure-based arguments attributes advantage to occupying a bridging position within the network. Because of the likelihood that a firm occupying a bridging position will receive new, strategically important information sooner than others in the network, strategy researchers have examined the competitive consequences of occupying structural holes. In research on small to medium-sized firms, McEvily and Zaheer (1999) found that lower-density networks were associated with a greater acquisition and deployment of capabilities necessary for competitiveness in the metalworking segment of the automotive industry. The benefits of structural holes were also supported in research by Baum et al. (2000), which showed that alliance partner heterogeneity had a positive effect on firms’ subsequent financial performance (as measured by revenues) and their innovative capability (as captured by patenting).

Networks may lead ventures to accomplish important goals such as going public, mergers, acquisitions, the formation of alliances, and avoiding firm dissolution. Yu, Gilbert, and Oviatt (2011) found that greater cohesion rather than structural holes increased the speed with which firms achieved their first international sales. They argued that the market knowledge shared by a firm’s internationally experienced, foreign partners would remain relevant for a longer period of time thus increasing the benefits of rich information exchange relative to the demand for novel information. Another observable intermediate success indicator has focused on new product development performance. Alliance activity can facilitate new product development that can portend future success (Haeussler, Patzelt, & Zahra, 2012; Rothaermel & Deeds, 2006; Soh, 2003).

With the focus on obtaining the first sale and hiring an employee or obtaining finance, Newbert and Torniskoski (2012) found that achievement of these milestones among a nationally representative sample of U.S. nascents was more likely to result from larger networks as well as higher initial levels of multiplex ties. In a subsequent study from the same population, Newbert, Tornikoski, and Quigley (2013) found that growing heterogeneity in nascents’ network of contacts was linked to self-reports of establishing a new venture and reaching positive cash flows. These findings, which are echoed in work at the team and firm level, suggest that heterogeneity across ties can reduce problems associated with over- and under-embeddedness. In addition, comparisons between those who succeeded and those who did not indicate that the rate at which these networks become more heterogeneous has a significant impact on the final outcome.

The focus on entrepreneurial performance has been examined with respect to the benefits and liabilities of strong versus weak ties and fueled debate on their relative value. A large-scale survey conducted by Bruderl and Preisendorfer (1998) of more than 1,600 German founders found that strong ties were more critical than weak ties in explaining firm success as measured by firm survival. These results emerged from a study that controlled for environmental, firm, and individual characteristics such as owner’s education level and work experience. The network measures consisted of questions regarding the extent of social support from direct contacts. They found that strong ties, as proxied by self-reports of receiving support from friends and family, had a positive impact on business survival and a much smaller impact on sales growth. The results were stronger for survival, suggesting that the effects of strong ties may not be comparable across measures of entrepreneurial success. Weak ties, measured as support from business partners and acquaintances, were found to be a poor predictor of performance. In contrast, Uzzi (1997) argues that a balanced network, consisting of both weak and strong ties, may ultimately be more valuable. Uzzi studied the extended networks (i.e., the suppliers to their suppliers) of clothing manufacturing firms and found a curvilinear relationship between the extent of embedded ties within the broader network and firm survival: very weak or very strong extended networks had a negative effect on survival rates.

Additional evidence points to a contingency of firm’s stage of development on the relative value of each type of network. For instance, reputational networks at the founding stage significantly reduce firms’ time-to-break-even, while social network ties have no direct effect (Lechner et al., 2006). The relational mix emphasizing different types of ties (e.g., marketing, reputational, and social ties) are important at different stages of development and thus must change with a firm’s development or else they become a barrier to growth (Lechner & Dowling, 2003; Lechner et al., 2006). Kreiser, Patel, and Fiet (2013) found that the formation of strong ties in the nascent founding stage may reduce the subsequent rate of founding milestones achieved because of an overreliance on and growing obligations to contacts that divert attention and activity from building the business. In addition, the literature on career transitions and entrepreneurial transitions suggests that social ties that reinforce a current work-role identity can make a transition to entrepreneurship more challenging (Hoang & Gimeno, 2010).

While network ties bring beneficial results to new ventures by facilitating resource and information flow, it should be noted that initiating and maintaining them requires considerable resource input both for the firm and for the entrepreneur. A number of research articles uncovered a diminishing return on investment in network with regard to firm performance. That is, the relationship between networking and outcomes may not be linear, and excessive investment in creating or maintaining network may not improve firm performance. Semrau and Werner (2014) consider entrepreneurs’ network characteristics, measured by network size and relationship quality, and their impact on performance, as measured by access to knowledge and information, financial capital, and additional business contacts. The latter resources were more difficult to obtain when network size and relationship quality was low. Hence, different types of resources are acquired at different “costs” in terms of time and investment by the entrepreneur. Semrau and Werner (2012) provided evidence on the inverted-U relationship between nascent entrepreneur’s investment in relationship quality and success of new venture creation. Moreover, the impact of network size was positive although with declining marginal benefit.

One recent study finds that the structural holes within a teams’ external network positively affects performance outcomes (Vissa & Chacar, 2009), and this effect is moderated by greater strategic consensus and cohesiveness within the team. Therefore, not only individual entrepreneurs but entrepreneurial teams benefit from a network structure with more structural holes.

Although the network of the founder can determine firm growth, firm networks need to be actively managed. At the team level, the social competence of the team is argued to lead to new firm growth (Baron & Tang, 2009). Brinckmann and Hoegl (2011) empirically traced the relationship between team-level characteristics and firm-level performance. Initial relational capabilities of team members can foster resource acquisition by effectively and efficiently managing the exchange with its environment. The quality of collaboration of the entrepreneurial team with external partners was shown to have positive effects on firm growth, characterized by additions of team members, employment growth, and sales.

Properties of the firm can both directly and indirectly affect venture performance. A study of university spin-offs (Walter, Auer, & Ritter, 2006) showed that a firm’s networking capability positively relates to its performance as measured by sales growth. Network capability was captured by four factors: coordination, relational skills, partner specific knowledge, and internal communication. Viewed over time, the extent of a firm’s collaborative activity is thought to contribute to its experience and knowledge in that domain. Hence, an important consideration in explaining the extent to which a firm’s current network ties can be leveraged is to consider the extent of a firm’s alliance experience. In their study of research and development collaborations, Hoang and Rothaermel (2005) found that the extent of general alliance experience defined as the knowledge gained from selecting, negotiating, and managing collaborative relationships can enhance new venture success. In addition, the extent of prior ties with a focal partner increases the firm’s partner-specific experience, which was also found to contribute to collaborative success.

Scholars have also examined how contextual conditions may explain variation in how social capital influences financial performance. Rosenkopf and Schilling (2007) examined factors that may explain differences in alliance participation and the resulting structural network patterns across industries. In particular, clustering is evident when firms in a network tend to have partners that are also partnered with each other. Observed differences across industries such as between pharmaceutical and communication equipment sectors were linked to the need to cope with dynamism or pace of change in the underlying technology as well as uncertainty with regard to the direction of change. The extent of firm-level collaboration is also likely to be influenced by the underlying architecture of the technology platform and the extent of modularity between the technology’s subcomponents. Open rather than closed technology platforms and high levels of modularity create more opportunities for entrepreneurial ventures leading to higher rates of collaboration.

Echols and Tsai (2005) found that firms with distinctive products and operational processes (product and process niche) benefit from a high level of network embeddedness, as it provides a richer social context containing useful information and resource flows, which enables the firm to better exploit its position. These findings suggest that knowledge flows and technological dynamism and industry life cycle considerations may be relevant factors that impinge on firm performance outcomes.

Clarysse, Bruneel, and Wright (2011) conceptualize environmental complexity and environmental stability as critical features. Complexity describes how incumbents may control important complementary assets and access to customers increasing the need for ventures to initiate partnerships. They characterize stability as the extent to which the new venture will be able to appropriate the returns from their distinctive resources. They generate propositions based on case studies of new ventures that highlight how ventures should use partnerships to emphasize either technical or commercial access under different environmental conditions. Their work suggests that these conditions have implications for the scope of partnership choices and alliance portfolio structure which in turn affects subsequent firm-level performance.

A firm’s environment encompasses formal institutional actors including governments who seek to shape the regulations, policies, and practices by which firms compete. Attention to these factors and their impact on entrepreneurial activity is central to research on academic entrepreneurship and university spin-outs (Djokovic & Souiteris, 2008). In order to understand the impact of the institutional environment, researchers have also leveraged the construct of institutional polycentrism, which denotes spontaneous interactions of multiple institutional rules and norms, and mutual adjustments among institutional actors. Batjargal et al. (2013) studied how the confluence of multiple institutions (political, regulatory, and economic) affected entrepreneurs’ networks and new venture revenue growth. They posited that the confluence of weak and inefficient institutions contributes to the development of structural holes and positively moderates the relationship between entrepreneurs’ structural holes and revenue growth. A study of entrepreneurs and their ego networks in China, Russia, the United States, and France was supportive of their hypotheses.

Building on the corpus of empirical work in this area, Stam, Arzlanian, and Elfring (2014) were able to apply meta-analytic techniques on 59 empirical studies of small firm networks. In addition to confirming the overall positive relationship between social capital and performance, they examined the effects of multiple contextual factors on the impact of social capital measures on small firm performance. Differences in the efficacy of strong, weak, and diverse ties were explained by institutional differences related to whether the firm was operating in an emerging versus established economies. In addition, there was support for the importance of structural holes and diverse networks for small firms operating in high-technology sectors relative to low-technology sectors. Diverse networks had a positive performance benefit for new firms relative to older firms.

How Networks Develop

A significant body of social network research has emerged that attempts to account for how networks change over time and across different entrepreneurial stages. Within the domain of entrepreneurship research, the formation of new ties by individual entrepreneurs undertaking the entrepreneurial process and ties formed by entrepreneurial ventures is of prime interest because they are presumed to enable access to critical resources. Other types of network changes include tie deletion or culling that involves an explicit decision to stop investing in maintaining a relationship (Larson & Starr, 1993). The combination of tie formation and deletions has in turn implications for characteristics of a firm’s direct ties as well as the network as a whole (Koka, Madhavan, & Prescott, 2006). Finally, an established tie can be significantly reoriented or a dormant tie can be reactivated (Levin, Walter, & Murnighan, 2011; Vissa, 2011).

Building on the qualitative research of Starr and Macmillan (1990), Larson and Starr (1993) posit that the networks activated for new venture formation follow a three-stage sequence of development. Each stage in the network development process is characterized by distinctive changes in the content of the relationship and the governance mechanisms used to manage the relationship. Hite (2003) developed a detailed typology that considers the interrelated development of relational and structural characteristics and shows how variation in the quality of the relationship and bases for trust may lead to different types of embeddedness. The quality of the relationships are described by a number of attributes that characterize the economic and social dimensions of the focal relationship as well as the impact of the broader network. In turn, configurations of attributes were linked to unidimensional, bidimensional, or full embeddedness. Unidimensional embeddedness is based on only one social component (such as personal affect or friendship) and was theorized to evolve toward deeper embeddedness over time. Full embeddedness was reserved for relationships that were based on personal, economic, and network structure considerations. Bidimensional ties fell in between and included family ties because the relationships were based on trust and supporting network structures but were often not leveraged for business purposes.

Tie formation and tie reorientation are facilitated by goal oriented behavior. For example, qualitative study of firm networks has identified a wide range of motivations that support choices regarding network behavior including the motivation to access resources such as competitor and market information that can result in new or recurring business (Shaw, 2006) or that alter a firm’s resource profile (Hanna & Walsh, 2008) by accessing external rather than internally developed resources (Siu & Bao, 2008). Network tie formation can also be initiated with multiple firms simultaneously to create a favorable portfolio of ties that enhances a firm’s competitiveness.

Vissa (2011) proposes a matching theory to explain how and why entrepreneurs form new ties for economic exchange. This theory is based on the assumption that an intention to form a new tie follows an initial contact and precedes an economic exchange being realized. An entrepreneur’s intention to form an exchange relationship is based on an assessment of the likelihood of a successful match. Vissa found that relational characteristics, including social similarity factors that are thought to increase trust and facilitate communication between the entrepreneur and contacts, predict both the intention to form a new tie and subsequent economic exchange between them. The perceived requirements of the business were also found to impinge on this process such that the effect of social similarity was moderated by the degree to which the profile of the new contact would advance an entrepreneur’s current business goals (e.g., acquire new customer, supplier, etc.).

With the concept of networking style, Vissa (2012) further characterizes founders by their tendencies toward adding new ties and how existing ties are managed. The reliance on referrals from existing ties to generate new ties is related to an individual’s preference toward network deepening actions rather than broadening actions. Vissa found that a greater (lesser) reliance on referrals to initiate new tie formation was linked to fewer (more) useful economic exchanges for the venture. In contrast, when entrepreneurs engage in more network broadening actions while undertaking few network deepening actions, the result is greater network churn. Changes in the composition of the alters in a network can in turn result in a larger portfolio of organizations for the focal venture to access (Vissa & Bhagavatula, 2012).

Formation of Financing Ties

Receiving venture financing underscores the strategic, dynamic, and heterogeneous nature of tie formation. Financing, especially from venture capital firms and established companies, is an important element for success in firms with high growth potential that requires lengthy periods of development before gaining revenues. A number of studies highlight that the formation of financing ties significantly broadens a venture’s network and contributes to its diversity of ties. To explain it, scholars have differentiated between ties formed on the basis of pre-existing personal ties, via referrals, or by contacting an investor directly (Hallen, 2008; Zhang, Souitaris, Soh, & Wong, 2008). Hallen found that founders’ existing ties and human capital predicts the likelihood of tie formation between a new venture and its potential partners. In a survey of young, high-tech ventures in Singapore and Beijing, Zhang et al. found that, while the decision to use personal ties to connect to venture capitalists was the dominant choice, entrepreneurs with managerial and marketing experience were choosing to approach them directly.

Batjargal and Liu (2004) examine venture capital financing in the Chinese context and find that investors are not swayed to invest on the basis of relationships. Yet they do find that the time length of the negotiations were longer and subsequent terms of the deal were more favorable to the socially connected entrepreneur. Hallen and Eisenhardt (2012) also stress the benefits to the entrepreneur of using prior direct ties, but, in the absence of such ties, they elaborate on a number of strategic actions that are used to reduce the time and effort it takes to form investment ties. With the construct of formation efficiency, they also suggest that efficient tie formation better conceptualizes the source of high-performance network outcomes. They note some founders using information obtained through the network or through direct interaction are able to effectively form and then cull initial contacts to retain those most likely to commit to funding the venture.

Zahra (2010) finds that family firms with high organizational social capital (measured by items such as having a good reputation and being well connected to other firms in the industry) are more likely to have equity shareholding in new ventures launched by strangers and to hold a seat on the venture’s board. Such preferences are argued to enable greater learning and to facilitate opportunity identification and growth through weak ties.

Sources of Network Heterogeneity

Aldrich and Kim (2007) note the predilection of individuals to form ties to similar others and the greater costs of bridging different social worlds that can limit network heterogeneity. Thus there is an interest in understanding how multiplexity, and other network dimensions can contribute to heterogeneity in the resources accessed and diversity of contacts.

The different types of behaviors that lead to such diversity have been the focus of scholars examining network dynamics, but questions remain as to how such heterogeneity is managed. Building on the work of Baron and Markman (2003), Kreiser et al. (2013) examine the nascent stage and argue that characteristics of the founder, namely their social competence and entrepreneurial intensity, are important factors. Entrepreneurs with greater entrepreneurial intensity, defined as having the motivation and commitment to become an entrepreneur, are better able to limit the costs of growing tie strength as captured by multiplexity. They are able to convince contacts to share more valuable or tacit resources as a result of their commitment to being a founder. Kreiser et al. also find that those with higher social competence are better at leveraging the growth in their network in ways that facilitate an increase in firm founding activities.

Leveraging extensive work on traits as sources of individual difference, Oh and Kilduff (2008) find that self-monitoring is linked to greater nonredundant tie formation among a sample of ethnic small business owners. Self-monitoring characterizes a tendency to alter one’s affective state and behaviors to be in line with the social context rather than to be consistent with one’s inner state and attitudes. As a result, low self-monitors may be able to form a more diverse set of contacts that are likely to be unconnected to one another (Oh & Kilduff, 2008). Further work will link a wider array of individual characteristics such as group orientation, extraversion, and neuroticism to network structure including centrality (such as Kalish & Robins, 2006; Klein, Lim, Saltz, & Mayer, 2004).

Baron and Markman (2003) characterize social competence as involving adaptability to social situations and skill at impression management. They also include social expressiveness and social perceptiveness as additional dimensions that distinguish it from self-monitoring. Overall, social competence may reflect an ability that can be developed over time and contributes to differences observed across entrepreneurs in their network structure. Consistent with this, Batjargal (2010) finds that entrepreneurs’ self-reports of being effective and motivated networkers contributed to an increase in the number of structural holes or distant ties that were formed one year later.

There is a smaller body of empirical studies at the entrepreneurial team level and the work that has been done is often focused on ventures that pursue technologically driven, high-growth opportunities (Neergaard, 2005). In the case of academic spin-offs where such conditions typically apply (Nicolaou & Birley, 2003), the completeness of spin-off teams as represented by the diversity of the functional skills and the degree of role articulation has been linked to the networking behavior of founding teams (Grandi & Grimaldi, 2003). Li (2013) examined team size and diversity, captured by the extent of nonoverlapping prior organizational affiliations, to explain the formation of multiparty alliances. Similarly, relational and structural characteristics of new ventures’ board member ties that promoted range and diversity helped to explain early patterns of alliance formation resulting in diverse alliance portfolios (Beckman, Schoonhoven, Rottner, & Kim, 2014).

A focus on the team and board of director’s level may provide important nuance to the broad observed patterns regarding the culling and transformation of a firm’s portfolio of ties over the venture development process. A number of scholars argue that as the venture grows, the network management task does too, driven in part by the growing multiplexity of relationships and the increasing demands by a firm’s contacts (Steier & Greenwood, 2000). A qualitative inductive study of low versus high performing biotechnology ventures revealed that key elements of how networks were managed across the founding team allowed for greater adaptability. Specifically, teams that became more specialized in managing their relationships to key constituencies were able to reduce the relational and cognitive overload and increase their capacity to form diverse firm-level ties (Maurer & Ebers, 2006). Network specialization in turn requires greater internal integration within the team to facilitate coordinated action. In their performance oriented studies, Vissa and Chacar (2009) and Brinckmann and Hoegl (2011) confirmed the importance of team processes as captured by team’s degree of communication and cohesion through survey-based measures.

Conclusion

More than 30 years of research examining social capital in the entrepreneurial process has resulted in rich insights regarding its impact on the entrepreneurial processes. The conceptual building blocks of the work in this area have focused on network content, governance, and structure. (See Table 1 for a summary of our construct definitions and key findings.) These building blocks emphasize how entrepreneurial success depends on the relationships in which the entrepreneur is embedded and the broader social structure that is created from cross-cutting ties between actors.

Table 1. Construct Definitions and Summary Findings

Relational

Structural

Levels of Analysis

Content

Governance

Construct definition

The nature of the content that is exchanged or flow between actors, including both tangible (capital) and intangible resources (access to information and advice, emotional support, legitimacy signals), or the layering of multiple resources (multiplexity).

Mechanisms which organize and regulate network exchange, including contracts and trust between partners.

Pattern of direct and indirect ties between actors, at both individual and organizational level, measured by network size, centrality, density, strong/weak, bridging ties.

Founder: Personal social network

Team: Informal ties of individual team members and formal ties between firms (e.g., board ties)

Firm: Formal ties such as strategic alliances

Network as DV

Key findings

Relationships evolve over time based in part on the initial condition of the tie formation.

Multiplex ties are more likely to be underpinned by trust and confidence and therefore bring more effective resource exchange.

Goal-oriented behavior and matching between relational characteristics facilitate new tie formation; different relationship quality and bases of trust lead to different types of embeddedness.

Founder: Entrepreneurs’ various social skills, symbolic actions, and self-monitoring level are linked to new tie formation.

Firm: Firm capabilities shape the firms’ behavior of network formation and maintenance.

Team: The link between individual and team-level network processes is under explored.

Network as IV

Pre-existing ties predict future financial tie formation through strategic actions; multiplex ties help achieve milestone event; resource-role matching increases support received from network; relational mix: different types of ties are important at different stages.

Growth in network size and heterogeneity help achieve milestone events; initiating and maintaining network has opportunity cost and may result in diminishing or even negative marginal return; cohesion and structural holes are both demonstrated to enhance performance.

Founder: Founders’ social skills and social competence help obtain information and resources from network

Team: Social competence of the entrepreneurial team leads to new firm growth

Firm: Firms’ networking capability enhances performance.

More recently, our understanding of the sources of network evolution and the resulting patterns have also developed significantly. As a motor of network change, scholars have emphasized the goal-oriented behavior of the entrepreneur, but social relationships also engender mutual concern, obligation, and emotional attachment. Thus forming new ties, culling existing ties, and resurrecting dormant ties require investment and attention in order to manage network processes effectively. Moreover, as the venture grows, the ability of the venture team and the firm as a whole to manage a growing set of interorganizational relationships becomes increasingly important. Indeed, work in this area recognizes that social capital “scales” and can be leveraged by teams and firms. Hence, interest in the process of network development as it is linked to venture development grows as an area of future research.

The performance consequences of social capital and the impact of particular network configurations have been extensively examined. The findings lend support to the beneficial role of social capital and are bolstered by diverse samples and the use of different measures of strong and weak ties as well as structural holes. More recently, studies have identified important limitations to their benefits due to decreasing returns to growing and maintaining a large network or to contingencies tied to the stage of the venture’s growth.

In addition to crossing from the individual to the team and firm level, an understanding of the influence of social capital and networks has accounted for the broader conditions that determine when network benefits will be enhanced or dampened. Typically these conditions highlight industry and national-level variation that focus on the pace of knowledge and technology development and degree of formal institution and role of the state, respectively.

Overall, studies that examine the influence of social capital either examine how networks develop over time or examine the consequences of networks for entrepreneurial outcomes. Each of these domains has become enriched and more conceptually complex, which suggests future research opportunities will arise that come from cross-fertilization of these two research streams. Future work can explore how failure to achieve key milestones affects network development and reconfiguration. Such insights can assist founders and teams to develop more resilient strategies. Finally, further work can incorporate a broader array of environmental factors (e.g., institutional and technological) to reveal important boundary conditions to established relationships.

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Notes:

(1.) Consistent with the Entrepreneurship Division of the Academy of Management, papers were considered if they focused on the development and consequences of networks in the new venture creation process or focused on small to medium-sized firms and family firms.