Explaining the structure of inter-organizational networks using exponential random graph models

Abstract

A key question raised in recent years is what factors determine the structure of interorganizational networks. Most research so far has focused on different forms of proximity between organizations, namely geographical, cognitive, social, institutional and organizational proximity, which are all factors at the dyad level. However, recently, factors at the node and structural network levels have been highlighted as well. To identify the relative importance of factors at these three different levels for the structure of inter-organizational networks that are observable at only one point in time, we propose the use of exponential random graph models. Their usefulness is exemplified by an analysis of the structure of the knowledge network in the Dutch aviation industry in 2008, for which we find factors at all different levels to matter. Out of different forms of proximity, only institutional and geographical proximity remains significant once we account for factors at the node and structural levels.