The Network Structure Of Social Capital

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ABSTRACT

This is a review of argument and evidence on the connection between social networks and social capital. My summary points are three: (1) Research and theory will better cumulate across studies if we focus on the network mechanisms responsible for social capital effects rather than trying to integrate across metaphors of social capital loosely tied to distant empirical indicators. (2) There is an impressive diversity of empirical evidence showing that social capital is more a function of brokerage across structural holes than closure within a network, but there are contingency factors. (3) The two leading network mechanisms can be brought together in a productive way within a more general model of social capital. Structural holes are the source of value added, but network closure can be essential to realizing the value buried in the holes.

Section snippets

INTRODUCTION

Social capital is fast becoming a core concept in business, political science, and sociology. An increasing number of research articles and chapters on social capital are appearing (look at the recent publication dates for the references to this chapter), literature reviews have begun to appear (e.g. Nahapiet and Ghoshal, 1998, Portes, 1998, Sandefur and Laumann, 1998, Woolcock, 1998, Foley and Edwards, 1999, Lin, 1999, Adler and Kwon, 2000), books are dedicated to it (e.g. Leenders and Gabbay,

SOCIAL CAPITAL METAPHOR

Figure 1 is an overview of social capital in metaphor and network structure. The figure is a road map through the next few pages, and a reminder that beneath the general agreement about social capital as a metaphor lie a variety of network mechanisms that make contradictory predictions about social capital.

Cast in diverse styles of argument (e.g. Coleman, 1990, Bourdieu and Wacquant, 1992, Burt, 1992, Putnam, 1993), social capital is a metaphor about advantage. Society can be viewed as a market

NETWORK MECHANISMS

Disagreements begin when the metaphor is made concrete in terms of network mechanisms that define what it means to be ‘better connected’. Connections are grounded in the history of a market. Certain people have met frequently. Certain people have sought out specific others. Certain people have completed exchanges with one another. There is at any moment a network, as illustrated in Fig. 2, in which individuals are variably connected to one another as a function of prior contact, exchange, and

EVIDENCE

Three kinds of empirical evidence support the argument that social capital is a function of brokerage across structural holes. Lab experiments with small-group exchange networks show that resources accumulate in brokers, people with exclusive exchange relations to otherwise disconnected partners (e.g. Cook and Emerson, 1978, Cook et al., 1983, Markovsky et al., 1988; see Willer, 1999, for review).

Census data on economic transactions have been used to describe how producer profit margins

NETWORK DIMENSIONS OF SOCIAL CAPITAL

My summary conclusion from the preceding section is that the social capital of structural holes can be found in research on diverse substantive questions. The studies reviewed, however, vary dramatically in the depth and precision of their measurement strategies. Broad conclusions are possible – networks across structural holes are clearly a form of social capital – but it is difficult to make exact comparisons across the studies (a problem made worse by population differences correlated with

CONTINGENCY FACTORS

The case is not as simple as implied by the evidence thus far. My final step in the review is to describe the contingent value of social capital. A contingency factor is a variable that affects the strength of association between social capital and performance. I review five contingency factors: personality and culture, kinds of relationships, peers and task uncertainty, network closure, and the distinction between insiders versus outsiders. These factors are productive to review because, as I

CONCLUSIONS

In conclusion, the network structure of social capital boils down to the three kinds of networks in Fig. 8. The natural evolution of networks left untended is toward a clique of people known to, and supporting, one another as friends of friends. Clique networks are small, dense, non-hierarchical networks associated with leisure activities, the lack of social capital, and poor manager performance. The most consistent empirical finding in this review has been that dense networks are associated

APPENDIX

The Appendix to this chapter, ‘Implications for Research Design’, contains four sections: One is about selecting a study population to get rich data on social capital and its effects (focus on places where competitive advantage would result from better access to, and control over, information). The second section is about network measures of social capital. The third is about positional measures (contacts are sorted into kinds, relations between contacts are typically unknown, and social

ACKNOWLEDGMENTS

Work on this chapter was supported by the Institute Européen d’Administration d’Affaires (INSEAD) and the University of Chicago Graduate School of Business. Portions of the material were presented in 1998 at a ‘Social Networks and Social Capital’ conference organized by Nan Lin and Karen Cook at Duke University, and a ‘Economic and Organizational Sociology’ conference organized by Mauro Guillén and Douglas Massey at the University of Pennsylvania, in 1999 at a ‘Local Standards and Global

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