Bringing Political Skill into Social Networks: Findings from a Field Study of Entrepreneurs

INTRODUCTION

Creating and developing ventures is a social process in which both individuals and their social networks contribute to entrepreneurial success (e.g., Aldrich and Ruef, 2006; Baron, 2002; Baron and Markman, 2003). To date, entrepreneurship researchers have taken sociological and behavioural perspectives in their efforts to understand entrepre- neurial performance. Taking the sociological perspective, several researchers have exam- ined social networks effects on venture performance and have found that social networks are important in the creation, growth, and success of new ventures (e.g., Aldrich and Ruef, 2006; Batjargal and Liu, 2004; Hoang and Antoncic, 2003; Jack, 2005; Shane and Cable, 2002). Others taking the behavioural perspective have found that individual characteristics impact venture success (e.g., Baron and Tang, 2008; Ciavarella et al., 2004). Those prior studies have provided insights into the respective roles of entrepre- neurs’ social networks and individual factors in influencing venture performance.

However, our understanding of entrepreneurial processes within the social network context remains limited when we consider such processes by which entrepreneurs first construct social networks and gain access to social capital, and then use their networks for mobilizing social capital to enhance performance. Although research taking the socio- logical perspective has identified the important effects of social networks on venture

Address for reprints: Lei Chi, EmblemHealth, 55 Water Street, New York, NY 10041, USA (lchi@ emblemhealth.com).

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The second question pertains to entrepreneurs’ use of social networks. Empirical findings are still limited as to whether all entrepreneurs are equally capable of utilizing social capital (i.e., resources embedded in networks) for achieving the desired venture performance (Baron, 2007; Stuart and Sorenson, 2007). To date, research on the effects of entrepreneurial networks implicitly assumes that all entrepreneurs maximally utilize accessible social capital. Social capital scholars, however, have suggested that not all actors can fully use available social capital (Lin, 1999). Although social networks create opportunities for social capital transactions, their mere existence reveals little about whether their benefits will be realized (Adler and Kwon, 2002). Indeed, some studies have found that entrepreneurial networks significantly affect venture performance while others have failed to do so (see Hoang and Antoncic, 2003), suggesting that entrepre- neurs differ in their utilization of available social capital. As such, entrepreneurship scholars have called for empirical insights into whether entrepreneurs’ individual char- acteristics affect their ability to realize network-based advantages (Baron, 2007; Stuart and Sorenson, 2007). This line of inquiry on differences across entrepreneurs in how they leverage network resources will also extend our understanding of the development process of entrepreneurial networks.

In this study, we integrate the sociological perspective with the behavioural perspective to address those two under-explored questions in the entrepreneurship literature. Beyond the entrepreneurship context, emerging literature has identified that individual charac- teristics such as cognition and personality traits influence how people construct social networks in organizational settings (Burt et al., 1998; Klein et al., 2004; Mehra et al., 2001). For network usage, social capital scholars have suggested that individual differences determine how well people can utilize their social capital (Emirbayer and Goodwin, 1994; Stevenson and Greenberg, 2000). Personal characteristics affect how extensively and successfully they leverage their social networks (e.g., Anderson, 2008; Fang et al., 2011). Integrating the behavioural and sociological perspectives, we investigate the roles that individual characteristics play in influencing how entrepreneurs first gain access to social capital (network construction) and then mobilize social capital to enhance venture performance (network use). Social capital refers to social-network-embedded resources that can be accessed and mobilized for instrumental actions (Lin, 1999). Social capital must be accessed if it is to be subsequently mobilized (Lin, 1999). Therefore, we specifically address two fundamentally important yet under-studied questions in the entrepreneurship literature: (1) Why are some entrepreneurs better than others at developing resource-rich networks that

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177 3 allow them to access the social capital critical for venture performance? Do their individual characteristics

Bringing Political Skill into Social Networks Bringing Political Skill into Social Networks

influence their network construction? (2) Given the same level of accessible social capital, why do some entrepreneurs mobilize social capital better than others to achieve desirable venture performance? Do their individual characteristics affect their network usage? Answers to those questions will provide insights into the entrepreneurial process by which entrepreneurs construct and use their social networks to achieve desired venture performance.

To address the questions, we conducted field interviews with 28 entrepreneurs in ten different industries during a six-month period. Our findings suggest that political skill influences the entrepreneurial process within the social network context. Political skill reflects personal competency in social interactions and proficiency at applying situationally appropriate behaviour and tactics to influence others, especially in highly uncertain environments (Ferris et al., 2005, 2007). We see political skill as essential for entrepreneurs to be successful in entrepreneurial environments often characterized by high uncertainty levels. Following Eisenhardt’s (1989a) methods for building theory from case studies, we derive propositions from our field interviews and summarize our findings into an integrative model that depicts how political skill and social networks work together to affect venture performance. The empirical grounding of these propositions is the main subject of this paper.

Our study makes important theoretical and practical contributions to the entrepre- neurship literature. Theoretically, we show how individual characteristics – particularly political skill – influence entrepreneurs in the construction and use of social networks to enhance venture performance. By integrating sociological and behavioural perspectives, we elaborate and reveal the dynamic interplay between social networks and political skill, well-established constructs in entrepreneurship literature, in the entrepreneurial process. Consequently our qualitative research serves as ‘theory elaboration’ (Bluhm et al., 2011) by expanding our view into entrepreneurial processes within the social network context and filling gaps in current knowledge about entrepreneurial networks. Furthermore, our research advances theory on social capital and individual differences in the entrepre- neurial context. On a practical level, it is important that social networks and individual characteristics such as political skill are modifiable. As such, our results can assist in the development of training tools, policies, infrastructure, and mechanisms to help entrepre- neurs construct and use social networks for performance enhancement.

THEORETICAL BACKGROUND Sociological Perspective on Entrepreneurship

Entrepreneurial environments are highly uncertain and ambiguous (Lichtenstein et al., 2006). In starting and developing new ventures, entrepreneurs are heavily involved in tasks such as seeking market and growth opportunities, formulating business strategies and business models, negotiating new business deals, acquiring essential resources, and constructing effective relationships (Baron, 2008). However, new ventures are often information- and wealth-constrained (Shane and Cable, 2002). Entrepreneurs thus face substantial difficulty in responding to technology and demand uncertainties. Often they must rely on social relations to identify opportunities for launching new ventures and to garner crucial information and resources.

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Resources obtained through social relations are the foundation of social capital, which has two key components (Lin, 1999). First, social resources are embedded in social relations rather than in individuals – that is, social capital is distinct from other capital such as human and financial capital (Lin, 1999). Second, individuals can access and mobilize social capital only when they are cognitively aware of social ties in their networks and of resources those ties possess (e.g., Burt, 1992; Coleman, 1988; Lin, 1999). Social capital, in its various forms, facilitates information and knowledge flows, exerts influence, builds social credentials, and reinforces social identity and recognition (Lin, 1999). Those elements of social capital – information, influence, credentials, and reinforcement – help individuals and groups achieve desirable outcomes (Payne et al., 2011).

Taking the sociological perspective, entrepreneurship researchers have identified that social networks containing social capital are important at various stages of venture development. For example, during venture creation, entrepreneurs consistently use their social networks to gather information and ideas and to identify market opportunities (Ozgen and Baron, 2007; Singh, 2000; Smeltzer et al., 1991). Beyond the venture creation stage, entrepreneurs continue to rely on social networks for acquiring resources such as information, referral, advice, and technology (e.g., Batjargal and Liu, 2004; Jack, 2005; Lee et al., 2001; Shane and Cable, 2002). Social networks offer opportunities to obtain low-cost financial capital (Uzzi, 1999) and enable young ventures to move forward initial public offering (IPO) quickly and earn high IPO valuations (Stuart et al., 1999). Those studies are insightful in showing how social capital enhances venture perfor- mance. As described previously, however, they remain limited in addressing the two fundamentally important questions pertaining to entrepreneurial networks, that is, what roles do individual characteristics play in the access and mobilization of social capital to achieve desirable venture performance?

Behavioural Perspective on Entrepreneurship

Separately, researchers who take the behavioural perspective have found that entrepre- neurs’ individual characteristics such as personality, motivation, cognition, affect, social skill, and political skill have important effects on venture performance (e.g., Baron, 2007, 2008; Baron and Tang, 2008; Baum and Locke, 2004; Ciavarella et al., 2004; Tocher et al., 2012). For example, social skill, which reflects social competence and effectiveness in social interactions, has been found to be significantly related to venture success: more socially skilled entrepreneurs achieved greater financial success in their new ventures (Baron and Markman, 2003; Baron and Tang, 2008). More recently, political skill, a closely related concept, has also been found to be positively associated with entrepre- neurial performance (Tocher et al., 2012).

Individual characteristics such as political skill are suggested to help entrepreneurs shape and build resource-rich social networks, which, in turn, provide social capital critical for desirable venture performance (Baron, 2007; Baron and Markman, 2003; Tocher et al., 2012). This suggestion aligns with recent findings that entrepreneurs’ networking strategies influence the creation and development of resource-rich networks; that is, strategies such as networking orientation in building potentially valuable ties (Ebbers, in press), participation in heterogeneous industry events or bridging between

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179 5 events with few common participants (Stam, 2010), network-broadening and network-

Bringing Political Skill into Social Networks Bringing Political Skill into Social Networks

deepening networking styles (Vissa, 2012), and catalysing strategies for efficient tie formation (Hallen and Eisenhardt, 2012). As such, an in-depth understanding of how entrepreneurs’ individual characteristics influence their network construction and use will provide additional insights into entrepreneurs’ strategic networking actions. To our knowledge, however, no empirical investigations have considered the roles that individ- ual characteristics play in the entrepreneurial process within the social network context.

Integrating the Sociological and Behavioural Perspectives

Combined sociological and behavioural perspectives reveal that social networks and individual characteristics are important yet independent antecedents of entrepreneurial performance. Although outside the entrepreneurship context, emerging literature indi- cates that individual characteristics influence how people construct and use social net- works in organizational settings (e.g., Burt et al., 1998; Kalish and Robins, 2006; Klein et al., 2004; Mehra et al., 2001; Totterdell et al., 2008). For example, self-monitoring is related to network positions: employees high in self-monitoring are more likely than those low in self-monitoring to occupy central positions in their social networks (Mehra et al., 2001): they can ‘take advantage of their personality orientation to forge different types of network structures’ favourable for them (Mehra et al., 2001, p. 141). Individuals spanning many structural holes (i.e., sparse regions in the network with absence of ties between individuals) tend to be independent outsiders searching for change and author- ity; in contrast, individuals spanning few structural holes tend to be conformist, obedient, and oriented towards security and stability (Burt et al., 1998). Furthermore, individual differences can affect how people use their social networks (Emirbayer and Goodwin, 1994; Stevenson and Greenberg, 2000). For example, managers with higher level of need for cognition better utilize their social networks to search for relevant information (Anderson, 2008). New employees who have more positive core self-evaluations are better at capitalizing social capital for adjusting and assimilating (Fang et al., 2011).

Simultaneously, a recent study of the association of political skill and venture perfor- mance focuses on political skill as an individual characteristic that may influence how entrepreneurs construct and use their social networks (Tocher et al., 2012). Although highly correlated with social skill, political skill is more widely studied in organizational settings and refers to ‘the ability to effectively understand others at work and use such knowledge to influence others to act in ways that enhance one’s personal and/or organizational objectives’ (Ferris et al., 2005, p. 127). It allows individuals to form constructive and effective relationships with others and adapt to widely ranging social circumstances (Ferris et al., 2007, 2012). Studies on political skill and individual perfor- mance (e.g., Ferris et al., 2005) have suggested that political skill affects the ability to develop, maintain, and/or change social relationships, which perhaps explains why individuals with higher political skill tend to perform better in organizations. For instance, they tend to achieve better work performance as assessed by supervisors or peers (Ferris et al., 2005) and achieve better outcomes in managerial positions (Smith et al., 2009). Although some political skill aspects are dispositional, others can be trained and developed through formal and informal developmental experiences (Ferris et al., 2005). We believe

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that studying the role of political skill in the entrepreneurial process within the social network context adds value to the entrepreneurship literature and provides practical guidelines for entrepreneurs who seek to improve their venture performance.

Taken together, our study seeks to integrate sociological and behavioural perspectives by examining how entrepreneurs’ political skill contributes to their network building and their subsequent use of social networks to enhance venture performance.

METHOD

Our research design used a mixed approach involving qualitative and quantitative data. Qualitative data provide rich insights into the entrepreneurial process while quantitative data increase reliability and validity. To obtain the qualitative data, we followed Eisenhardt’s (1989a) methods on building theory from case studies and used a multiple- case design that allows the replication logic (Eisenhardt and Graebner, 2007). That is, we treated a series of cases as experiments with each case serving to confirm or disconfirm the inferences drawn from the others (Yin, 1994).

Table I summarizes the venture industries and relative venture performance – high versus low – of the entrepreneurs we interviewed. Their businesses ranged from indus- tries with relatively low technological/market uncertainty (e.g., garment tailoring, cater- ing, and restaurant industries) to industries with relatively high technological/market uncertainty (e.g., software, financial planning, and biotech industries). Because their ventures were in widely ranging industries and the objective venture performance data such as financial performance were so sensitive, we were challenged to use a common, single measure for assessing venture performance. We drew on all available information sources: entrepreneurs’ descriptions, our on-site observations, and data collected from survey questionnaires and secondary data sources. We assessed relative venture perfor- mance as high versus low from multiple aspects, such as perceived business growth, new business expansion, sales or revenue growth, and profit growth. For example, we con- sidered interviewee D3 to have relatively high venture performance. She started her restaurant about seven years ago. In the past five years, her sales rapidly grew from $250,000 to $1.3 million. Less than six months ago, she opened her second restaurant. The New York Times featured her restaurant twice. She was also invited to the Martha Stewart show. We sat in her restaurant from 10 am until noon on a regular business day and observed long lines and a packed restaurant. R2, who had a data communications business, showed another example of relatively high venture performance. For two years, his revenue doubled yearly and then tripled in the third year. In contrast, we considered S1 to have relatively low venture performance because her business lost money. Although some clients paid, most payments failed to cover the costs. We also assessed C2, the owner of a social media marketing business with no revenues in the past five years, as having relatively low venture performance.

Data Sources

Two members of the research team interviewed 28 entrepreneurs in ten different indus- tries during a six-month period. The entrepreneurs were all born and started their

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Table I. Venture industries and venture performances of interviewed entrepreneurs

Venture industry

Entrepreneurs with

Entrepreneurs with relatively high venture relatively low performance

venture performance 1. Non-profit organization

D1, R3 2. Corporate

C2, M2, M4, S3 communications/ entertainment and recreation/social media and marketing

C1, V1

3. Relocation management/

T1

automotive parts 4. Real estate

5. Financing and strategic

A2, J1, M6

planning consulting/ executive recruiting

6. Restaurants

D3, P1

7. Custom tailoring/catering M3, S1, E1 and personalized consulting/premium incentives

8. Enterprise software/online M2, M5 gaming software development

A1

9. Data communications

Note: Three entrepreneurs, D4 in strategic planning consulting industry, G1 in relocation management, and S2 in biotech industry, didn’t provide sufficient venture performance information that enabled us to make an assessment.

businesses in the United States. Their average age was 47.3 (SD = 10.6), ranging from 28 to 62 years of age. They had various educational levels: non-degree, bachelor’s, master’s, and PhD degrees. Their average industry experience was 16.2 years (SD = 9.3), ranging from 2.5 to 32 years. Their venture ages ranged from 3 to 5 years.

Gender, age, education, and prior industry experiences have shown mixed relation- ships with entrepreneurs’ venture performance (e.g., Jo and Lee, 1996; Van de Ven et al., 1984). Moreover, to our knowledge, no literature has evidenced whether those demographic factors are associated with political skill and social relations. For example, Aldrich et al. (1986) tested but found no gender differences in network size and amount of networking activity. Therefore, we are unconcerned about whether those factors significantly confounded our results.

As the interviews progressed, we adjusted the data collection instruments by adding questions to the semi-structured interview protocol and questionnaire (Eisenhardt, 1989b). Our interviews provided much evidence that advances our understanding of

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how political skill influences the construction and use of social networks. Our study includes: (1) semi-structured interviews with entrepreneurs, (2) questionnaires completed by entrepreneurs, and (3) secondary sources and other data.

Semi-structured interviews. Our semi-structured interviews began by asking the interviewees to summarize their businesses, to provide details regarding firm sizes, composition and extent of their social networks (i.e., personal contacts), relationships with key contacts, specific contexts of establishing relationships with contacts and purposes for using them, and the speed and cost of identifying and using the right contacts to meet their needs and objectives. If applicable, the interviewees described their financial objectives and business performance in terms of growth. Each interview lasted approximately two hours.

Two researchers met with the interviewees: one researcher asked questions and one took notes. Immediately after the interview, the researchers shared facts and impressions with each other and exchanged thoughts and ideas. They followed several previously suggested rules (Eisenhardt, 1989a, 1989b). First, detailed interview notes and impres- sions were completed within one to two days of the interview. Second, all data were included, regardless of their apparent importance at the time of the interview. All interviews were recorded and transcribed for detailed records. A third rule was to conclude the interview notes with ongoing impressions of each entrepreneur.

Questionnaires. At the end of each interview, entrepreneurs completed questionnaires rating their political skill, describing their direct ties with social contacts, and providing relevant backgrounds of the contacts in their personal networks.

To measure political skill, we used the 18-item political skill scale (Ferris et al., 2005), with response options ranging from 1 (Strongly Disagree) to 5 (Strongly Agree). Specifi- cally, political skill is categorized as: (1) social astuteness – the ability to understand social interactions well and identify with others; (2) networking ability – the ability to identify and develop diverse contacts and networks; (3) interpersonal influence – the ability to powerfully influence others; and (4) apparent sincerity – the ability to appear to others as having high integrity and as being authentic, sincere, and genuine (Ferris et al., 2005). The first two dimensions – social astuteness and networking ability – reflect interpersonal skills par- ticularly related to social networking ability in terms of how to read nuances in social interactions and how to develop networks of contacts. The other two dimensions – interpersonal influence and apparent sincerity – reflect the ability to obtain trust and credibility and to influence others to achieve desirable objectives. These four dimensions of political skill enable entrepreneurs to strategically adjust their behaviour to different and changing situational demands, to develop resource-rich networks, to occupy advan- tageous network positions with access to widely ranging network resources, and to more fully mobilize available resources to achieve desired entrepreneurial performance.

An entrepreneur’s personal social network includes direct ties with various social contacts the entrepreneur knows and contacts when needed. Social capital literature has examined social networks for their various structural characteristics capturing the amount of social capital individually accessible; for example, dyadic structures (e.g., Granovetter, 1973; Krackhardt, 1992; Lin, 1999), triadic structures (e.g., Simmel, 1955), network closure or cohesion (e.g., Coleman, 1988; Friedkin, 2004), and structural holes

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183 9 (e.g., Burt, 1992). For our initial inquiry about political skill in network building and use,

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we focus on dyadic ties or connections with contacts in the entrepreneur’s social net- works. As the most rudimentary yet important aspect of social networks, dyadic structure is the focus in much social capital literature (e.g., Lin, 1999) and enriches our under- standing of the antecedents and consequences of social relations. We specifically focus on number, extent, and strength of social ties.

We measured number of social ties by asking entrepreneurs to indicate the number of direct contacts in their social networks. We measured the extent of social ties by asking them to indicate the diversity of their contacts’ backgrounds, including occupation, job rank, education, expertise, and professional experience. The social capital literature has widely studied tie strength: ‘a combination of the amount of time, the emotional inten- sity, the intimacy, and the reciprocal services which characterize the tie’ (Granovetter, 1973, p. 1361). Researchers have measured tie strength using various indicators, includ- ing intimacy (Bian, 1997; Granovetter, 1973), interaction frequency (Granovetter, 1973), reciprocation of nomination (Friedkin, 2004), and role relations (relatives, friends, and acquaintances) (Lin et al., 1981). Among the indicators, intimacy is a key measure capturing tie strength (Marsden and Campbell, 1984). Thus, we particularly focused on the intimacy measure to capture tie strength between entrepreneurs and their contacts. The data were highly sensitive, so we measured average tie strength by asking the interviewees to indicate the average emotional intimacy or closeness with their contacts (Bian, 1997). We also asked each to indicate the average duration of relationships (in years and months) and the specific types of the relationships (e.g., acquaintances, friends, relatives, and/or family members), all indicators often used for measuring tie strength.

Secondary sources and other data. In addition to the interviews and questions, we collected secondary data about entrepreneurs’ backgrounds and businesses through the internet (e.g., company websites, LinkedIn), news reports, and on-site observations to validate the self-reported data. For example, we confirmed whether their self-reported numbers of contacts were generally consistent with the numbers indicated in their LinkedIn profiles. We found that some entrepreneurs who reported high levels of political skill received high recommendations from many friends. We often arranged to interview entrepre- neurs at their business sites to carefully observe their interactions.

Table II shows descriptive statistics of the self-reported political skills, including network ability, apparent sincerity, social astuteness, and interpersonal influence. We

Table II. Statistics of political skill dimensions (N = 28)

Maximum Political skill

4.21 0.55 2.33 5 Dimensions of political skill 1. Networking ability

3.97 0.68 2.67 5 2. Apparent sincerity

4.83 0.38 3.33 5 3. Social astuteness

4.03 0.72 1.8 5 4. Interpersonal influence

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then compared the statistics in our sample with those obtained in prior studies (e.g., Ferris et al., 2005). The comparison shows that the self-ratings of political skill in our sample are only slightly higher than those obtained using large samples. Given our small sample, we consider the scores to be relatively consistent with prior studies. In addition, our respondents’ political skills have a relatively wide range, suggesting considerable personal differences. Therefore, selection bias poses no serious concern. We are confi- dent that our sample is relatively representative, mitigating the potential concern that the interviewees who agreed to participate in our research are politically skilled and sociable. Although we cannot completely rule out the social desirability possibility that our interviewees self-inflated their political skill, we believe that social desirability did not distort our results given that several entrepreneurs in our sample reported very low political skill scores. Indeed, across multiple studies and different samples, political skill researchers have found that self-ratings of political skill are significantly correlated with supervisor and peer ratings (Blickle et al., 2011).

Among the four dimensions of self-reported political skill, most interviewees perceived themselves as highly sincere, and thus apparent sincerity has the smallest variation (SD = 0.33). Social astuteness, networking ability, and interpersonal influence show relatively wide variations and mostly explain differences in overall political skill scores. Therefore, we use a novel approach to visualize the political skill scores along these three most varied dimensions (Figure 1). This visual map allows us to effectively compare cases and contrast patterns of network construction and usage of entrepreneurs with different levels of political skill.

Data Analysis

Consistent with the research design of theory building and many prior studies (e.g., Elfring and Hulsink, 2007; Human and Provan, 2000; Jack, 2005), our study was largely qualitative, being based on data from in-depth interviews. For additional insights, we supplemented the qualitative findings with quantitative data from the questionnaire responses. We analysed our data following Eisenhardt (Eisenhardt, 1989a; Eisenhardt and Graebner, 2007). Specifically, the quantitative data, including scores of political skill, number of social ties, and average tie strength, were calculated and analysed for patterns. The qualitative responses were summarized around the key constructs of political skill, social capital (or social networks), and entrepreneurial performance. Once preliminary analyses were developed from both quantitative and qualitative data, we derived propo- sitions using methods of theory building from case studies.

In our analysis, we first divided the entrepreneurs into two groups based on their self-reported scores of political skill – entrepreneurs with relatively high political skill versus entrepreneurs with relatively low political skill. We based the splitting on the median score of political skill because it has a highly skewed distribution. We then coded the interview transcripts by extracting and summarizing verbal descriptions relevant to the process of network building and network use. Under each process, we further coded the verbal descriptions into social astuteness, networking ability, interpersonal influence, and apparent sincerity, based on words that reflected each dimension. The verbal accounts vividly described the entrepreneurs’ psychological characteristics or

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Figure 1. Scatterplot of political skill of the interviewed entrepreneurs (the original figure uses green–grey– red colours to represent different levels of political skill associated with entrepreneurs. For readers interested in the colour figures, please see http://onlinelibrary.wiley.com/doi/10.1111/joms.12107/abstract for the original figures)

Note: This scatterplot visualizes the self-reported political skill of the interviewed entrepreneurs along the three dimensions (social astuteness, network ability, and interpersonal influence) with wide variation. Each node represents an interviewed entrepreneur. X-axis gives social astuteness scores. Y-axis gives networking ability scores. Colour of the node represents interpersonal influence scores: green–grey–light red show a lower inter- personal influence; the light red–deep red show a higher interpersonal influence. Thus, the light blue shaded area presents the low-political-skill region, where entrepreneurs (E2, S1, D1, D2, M1, M2, C2, E1, R3, M3, M5, and G1) have relatively low political skill, especially in the two dimensions of social astuteness and networking ability. The light yellow shaded area presents the high-political-skill region, where entrepreneurs (A2, J1, D3, D4, P1, P2, R2, C1, R1, and M6) have relatively high political skill, especially in the two dimensions of social astuteness and networking ability.

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behavioural tendencies (e.g., sensitivity to subtleties in interaction and ability to read nuances or to develop large networks) and also provided detailed contexts of processes by which the entrepreneurs leveraged their political skill consciously or unconsciously. For example, A1 said: ‘I would say 30–40 per cent of my time . . . sort of target for investment in building the networks, expanding or feeding the existing network, to make sure the relationships are healthy and growing.’ The quote vividly conveyed A1’s networking ability and also explicitly suggested the context where he used his networking ability to strategically develop his personal network. In this case, we coded the descriptions into the ‘networking ability’ dimension of political skill under the process of ‘network building’.

In another example, J1 said: ‘I pick the contact in my network who I think most appropriate for the job given the situation.’ The quote clearly described the context of effectively using her network to get the work done. In addition, she conveyed her social astuteness in sensitivity to the subtle context of when, where, and whom to summon for the task. In this case, we coded the descriptions into the ‘social astuteness’ dimension of political skill under the process of ‘network use’. Overall, such coding allowed us to identify associations between political skill and social capital and to observe distinct, contrasting patterns in network construction and use between entrepreneurs with rela- tively high political skill and those with relatively low political skill. The patterns some- what suggest that political skill contributes to access and mobilization of social capital.

Per Eisenhardt (1989a, 1989b), we conducted detailed within-case and cross-case analyses between pairs of entrepreneurs to recognize distinct patterns from the data. As described above, we treated the cases as experiments, with each case serving to confirm or disconfirm the inferences drawn from the others (Yin, 1994). For cross-case analyses, we selected pairs of entrepreneurs and listed similarities and dissimilarities between each. We then categorized entrepreneurs according to the variables of interest, such as indus- try characteristics (e.g., high uncertainty versus low uncertainty) and venture perfor- mance (e.g., high versus low). The analyses allowed us to control for certain confounding factors in identifying the patterns and to derive tentative propositions. Then we revisited each case to see whether the data confirmed the propositions. If they did, we used the cases to improve our understanding of the underlying dynamics. After several rounds of iteration between the data and the propositions, we used the literature to sharpen insights yielded by the iterative process. Propositions linking political skill, social capital, and venture performance emerged in an integrative process model.

AN INTEGRATIVE MODEL OF POLITICAL SKILL AND SOCIAL CAPITAL

Access to Social Capital

The three characteristics of social ties that an entrepreneur develops and maintains with various contacts – number, strength, and extent – determine the amount of social capital the entrepreneur can access. Specifically, the number of social ties pertains to the number of contacts the entrepreneur knows and thinks of contacting when needed. The strength of social ties captures whether entrepreneurs and their contacts have strong or weak relationships. Strong ties, typically more reliable than weak ties, involve higher

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Table III. Contacts in core network vs. extended network

Core network

Extended network Core network vs. extended network

Mean SD

Mean

Mean difference Number of contacts 36.56 52.53 198.56 242.93 −3.98**

SD

Average tie strength 3.31 0.48 2.06 0.44 11.18***

Note: The mean differences are based on T-test; ** p < 0.01, *** p < 0.001.

trust, support, and emotional closeness (Granovetter, 1973; Marsden and Campbell, 1984). Thus, while weak ties are useful for transferring information that is highly scat- tered or unevenly distributed in the network but typically publicly available (e.g., market prices), strong ties are useful for transferring private information, generating new ideas, solving complex problems, or making critical decisions. Strong ties are also particularly useful for individuals in insecure positions (Granovetter, 1973) or changing environments (Krackhardt and Stern, 1988) where they need strong ties for protection and uncertainty reduction. The extent of social ties reflects the diversity of contacts’ backgrounds, includ- ing occupation, job rank, education, expertise, and professional experience. More exten- sive network ties increase access to broader information about potential markets, business locations, innovations, sources of financial capital, and potential investors (Aldrich and Ruef, 2006; Dubini and Aldrich, 1991; Renzulli and Aldrich, 2005).

Our data suggest that entrepreneurs’ personal networks of social ties vary considerably in number, strength, and extent. More important, entrepreneurs simultaneously main- tain two types of social networks: core and extended networks. Core networks typically include friends, colleagues, business partners, and sometimes family members with similar backgrounds and interests. In core networks, entrepreneurs tend to have strong ties, long-term, and stable relationships with social contacts they trust and rely on for obtaining information, referral, social influence, financial capital, and social support. In contrast, extended networks typically include weak ties with contacts who have more diverse backgrounds and interests and more distant and fluid relationships. Contacts in the extended network are good sources for information and referral of investors, clients, or business opportunities.

As Table III shows, core networks have significantly fewer contacts and stronger bonding. Figure 2 shows that core and extended networks together reflect ‘resource-rich networks’ (Uzzi, 1999). Uzzi (1999) examined arm’s-length versus embedded social ties to understand how social embeddedness affects organizations’ acquisition and financial capital costs in the middle-market banking industry, and found that arm’s-length ties are characterized by lean and sporadic transactions and ‘function without prolonged human or social contact between parties . . . [who] need not enter into recurrent or continuing relations as a result of which they would get to know each other well’ (Hirschman, 1982, p. 1473). In contrast to arm’s-length ties, embedded ties promoted mutual benefits ‘through the transfer of private resources and self-enforcing governance’ and ‘by

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Information Channels

Contact

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Figure 2. Core network vs. extended network

enacting expectations of trust and reciprocal obligation that actors espouse as the right and proper protocols for governing exchange with persons they come to know well’ (Uzzi, 1999, pp. 483–84). Uzzi (1999) captured the two types of ties based on the relationship between the firm and the lending bank: (a) duration of the relationship (in years); and (b) multiplexity of the relationship (number of business and personal bank services the entrepreneur used). He found that arm’s-length and embedded ties can complement each other’s advantages. Thus a mix of embedded ties and arm’s-length ties provides ‘resource-rich networks’ with optimal benefits, both increasing access to finan- cial capital and reducing costs relative to networks composed predominantly of arm’s- length or embedded ties. Uzzi’s definitions of arm’s-length and embedded ties are similar to the weak and strong ties defined in our study. As such, our finding of a beneficial mix of strong and weak ties with social contacts of diverse backgrounds in core and extended networks echoes well with Uzzi’s (1999) finding of ‘resource-rich networks’ comprising both embedded and arm’s-length ties. Taken together, differences between core and extended networks lead us to ask: As entrepreneurs strategically construct resource-rich networks, what factors provide differential access to social capital?

Politically skilled individuals can better understand social interactions, read nuances and hidden agendas in behaviour, and develop diverse contacts and networks (Ferris et al., 2012; Witt and Ferris, 2003). They combine social astuteness with the capacity to adjust their behaviour according to changing situational demands by appearing to be sincere, inspiring support and trust, and influencing and controlling responses (Ferris et al., 2005, 2007). Thus, political skill involves individual ability to interact with and influence others (Ferris et al., 2005, 2007). Accordingly, we expect that entrepreneurs with different levels of political skill will develop different patterns of social networks and

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Bringing Political Skill into Social Networks Bringing Political Skill into Social Networks

Table IV. Network comparison between entrepreneurs with high vs. low political skill

Extended network Low political

Core network

High political Low vs. skill

High political

Low vs.

Low political

skill high Number of contacts

235.87 1.27 (n.s.) Average tie strength

19.33 52.46 2.65 (n.s.)

2.00 2.20 0.69 (n.s.)

Notes: (1) The mean difference is based on T-test: * p < 0.05, ** p < 0.01, *** p < 0.001, n.s. = non-significant. (2) Political skill score is calculated based on a combination of its four dimensions. The classification of high and low political skill is based on the median score, which approximates the mean score of political skill in our sample.

thus have access to different amounts of social capital. We find that political skill is instrumental in enabling the development of resource-rich networks for gaining access to information, money, equipment, influence, and referral. Interestingly, our observationalso reveals that political skill is critical to core network stability and extended network mobility and changing dynamics.

Comparing and contrasting cases allows us to recognize the patterns more easily. Table IV summarizes the number of contacts and average tie strength across core and extended networks for entrepreneurs with high versus low political skill. Figures 3 and 4 present examples of five highly politically skilled entrepreneurs (A2, J1, R2, C1, and D3) and four less-politically skilled entrepreneurs (E2, S1, C2, and M2). We quoted their vivid descriptions of how they constructed their core and extended networks. The visual maps effectively contrast patterns of how entrepreneurs with different levels of political skill construct their networks.

Table IV and Figure 3 show that politically skilled entrepreneurs tend to maintain stable core networks of stronger ties than do less politically skilled entrepreneurs, although the social ties are similar in number. For instance, five within-case analyses of politically skilled entrepreneurs in our study (A2, J1, R2, C1, and D3) distinctly showed that they developed a cohesive core network allowing them to rely on their contacts to make key business decisions or important referrals, to provide financial support, and to get tasks accomplished quickly. As C1 said, ‘Whenever I’m in need, I can rely on them. They are willing to move around their schedules and even go out of their ways in order to get the things done for me.’

Table IV and Figure 4 further reveal that highly politically skilled entrepreneurs tend to dynamically update the contacts in their extended network on a need basis, as compared with less politically skilled entrepreneurs, although they do not differ in either the number or strength of social ties in their extended network. Dynamically updating the extended network enables the entrepreneurs to continually bring new information and novelty into their social networks by building social ties with contacts who have more extensive backgrounds, for example in occupation, job rank, prior education, expertise, and professional experience. The verbal accounts we gathered revealed consistent pat- terns among the politically skilled entrepreneurs: they actively ‘go to . . . events’ or ‘talk to different people’ to consciously ‘expand’, ‘grow’, or ‘feed’ their extended network. The

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Figure 3. Role of political skill in network construction (access to social capital): constructing core network (the original figure uses green–grey–red colours to represent different levels of political skill associated with entrepreneurs. For readers interested in the colour figures, please see http://onlinelibrary.wiley.com/doi/ 10.1111/joms.12107/abstract for the original figures)

Note: The original words of the interviewed entrepreneurs suggest that compared to entrepreneurs with low political skill (e.g., E2, C2, M2, and S1), entrepreneurs with high political skill (e.g., A2, J1, R2, C1, and D3) tend to maintain a stable core network, with which they tend to have stronger ties and more trustworthy relationships with social contacts.

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