Journal of Marketing Research, Vol. 48, No. 4, pp. 713-728, 2011
17 Pages Posted: 17 Nov 2011
Date Written: August 2011
Firms are increasingly seeking to harness the potential of social networks for marketing purposes. Therefore, marketers are interested in understanding the antecedents and consequences of relationship formation within networks and in predicting interactivity among users. The authors develop an integrated statistical framework for simultaneously modeling the connectivity structure of multiple relationships of different types on a common set of actors. Their modeling approach incorporates several distinct facets to capture both the determinants of relationships and the structural characteristics of multiplex and sequential networks. They develop hierarchical Bayesian methods for estimation and illustrate their model with two applications: the first application uses a sequential network of communications among managers involved in new product development activities, and the second uses an online collaborative social network of musicians. The authors' applications demonstrate the benefits of modeling multiple relations jointly for both substantive and predictive purposes. They also illustrate how information in one relationship can be leveraged to predict connectivity in another relation.
Suggested Citation: Suggested Citation
Ansari, Asim and Koenigsberg, Oded and Stahl, Florian, Modeling Multiple Relationships in Social Networks (August 2011). Journal of Marketing Research, Vol. 48, No. 4, pp. 713-728, 2011 . Available at SSRN: https://ssrn.com/abstract=1960262