Modelling the evolution of a bi-partite network Peer referral in interlocking directorates
Johan Koskinen1, Christofer Edling2
1ReMiSS, Department of Politics and International Relations, University of Oxford, Manor Road, Oxford OX1 3UQ, United Kingdom & Nuffield College, New Road, Oxford, OX1 NF, United Kingdom.
Social Networks
|June 20, 2014
Summary
This study introduces a new model for analyzing evolving social networks, specifically focusing on how director recruitment shapes corporate interlocking directorates. Peer referral significantly drives the formation of these network ties.
Area of Science:
- Social network analysis
- Sociology
- Organizational studies
Background:
- Relational ties are formed through shared affiliations and events, reinforcing social bonds and group norms.
- Bipartite networks, representing relationships between two distinct sets of actors, are crucial for understanding group dynamics.
- Dynamic, not static, analysis of bipartite networks is essential to capture evolving social processes.
Purpose of the Study:
- To introduce a novel class of models and a Bayesian inference scheme for empirically modeling the evolution of bipartite networks.
- To extend existing stochastic actor-oriented models (SAOMs) from unimodal to bipartite graphs.
- To investigate the role of tie formation, specifically director recruitment, in shaping the structural properties of interlocking directorate networks.
Main Methods:
- Development of a Bayesian inference scheme for bipartite network evolution.
- Extension of stochastic actor-oriented models (SAOMs) to bipartite networks.
- Empirical application to interlocking directorates of boards on the Stockholm stock exchange.
Main Results:
- The proposed model successfully captures the dynamics of bipartite network evolution.
- Evidence suggests that peer referral is a significant mechanism in director recruitment for corporate boards.
- This mechanism generates multiple interlocks between different corporate boards.
Conclusions:
- Dynamic modeling of bipartite networks is crucial for understanding social structures.
- Peer referral plays a key role in the formation of interlocking directorates.
- The developed model provides a valuable tool for analyzing the evolution of complex social networks.
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