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Industrial and Corporate Change, Volume 12, Number 4, pp. 697-725
© 2003 Oxford University Press

Where do small worlds come from?

Joel A. C. Baum, Andrew V. Shipilov and Tim J. Rowley

J. A. C. Baum, Rotman School of Management, University of Toronto, 105 St George Street, Toronto ON M5S 3E6, Canada. Email: baum{at}rotman.utoronto.ca; shipilov{at}rotman.utoronto.ca; rowley{at}rotman.utoronto.ca.

Abstract

Interfirm networks often take on characteristics consistent with the notion of a small world—they are locally clustered into dense sub-networks or cliques that are sparsely connected by a small number of ties that cut across the cliques, linking network members through a relatively small number of intermediaries. Are these characteristics an emergent property of interfirm networks that result from chance connections among firms, or more strategic partnering by firms to improve or protect their network positions? After outlining a behavioral account for this frequently observed network topology, we show that the evolving investment bank syndicate network in Canada exhibited small world properties from 1952 to 1990. We then identify the investment bank cliques comprising the network and the ‘spanning’ ties that cut across them, and test three distinct scenarios that may explain the formation of these ties, which are responsible for the small worldliness of the network: (i) chance partnering of firms in different cliques; (ii) insurgent partnering by peripheral firms to destabilize the network and improve their network positions; and (iii) control partnering by core firms to maintain the network status quo and their positions within it. All three scenarios played a role in explaining the formation of clique-spanning ties; however, chance and insurgent partnering played a greater role in our empirical setting. Our analysis of how small world structures emerge and evolve over time offers new insight into the origins of a prevalent interfirm network topology, and a baseline for constructing future models of interfirm network evolution and dynamics.


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