Social Network Metrics: The Boardex Case Study

Abstract

Social networks and methods for their analysis have attracted considerable interest in various research areas. One type of social networks that has been the subject of extensive analysis, especially in the corporate governance literature, is networks between company directors and firms, between directors and between firms (board interlock). The purpose of this paper is to discuss social network metrics for such types of networks and examine their interpretation and correlations from a domain-specific viewpoint. This work will help position, review and compare previous literature, especially in finance/corporate governance area that examines such types of networks.For the purposes of this paper, the BoardEx dataset is used to define the social networks between directors and firms and their corresponding metrics. This dataset keeps information about individuals, mainly from USA and Europe, who work in publicly quoted firms and major private firms at board and executive management levels. The information includes in-depth profiles such as academic qualifications, current and past job positions, membership to professional and other bodies, peer esteem indicators such as awards and honorary positions, etc.In addition to a detailed description of the dataset, the different types of networks that could be created are defined based on network theory. Furthermore, five node level metrics have been chosen to be analysed, namely degree, closeness, betweenness, eigenvector and clustering coefficient. These metrics are defined theoretically based on the network theory literature and their application and interpretation is elaborated. Finally, the correlations between these metrics is discussed theoretically and exemplified through the case study.