Methodological Advances in the Analysis of Bipartite Networks

Abstract

Network-based research in the management field largely assumes one-mode (unipartite) networks, despite the widespread presence of two-mode (bipartite) networks. In empirical work, scholars usually project a bipartite network onto a unipartite network, ignoring issues related to the interdependence of ties and potential loss of information. Yet new advances in measures and methods related to bipartite networks in the fields of sociology, physics, and biology may make such tactics unnecessary. This article presents an overview of three research streams related to bipartite networks, namely, (a) refinements related to the projections of bipartite networks onto unipartite networks; (b) the extension of networks measures from unipartite networks to bipartite networks, with a focus on clustering coefficients; and (c) approaches unique to bipartite networks, such as nestedness. We apply these approaches and compare the findings of a traditional unipartite network analysis using both a simple example and a sample of 10,223 directors of 1,528 Indian firms in 2009.