Local Network Effects and Complex Network Structure

36 Pages Posted: 19 Jan 2005

See all articles by Arun Sundararajan

Arun Sundararajan

NYU Stern School of Business; New York University (NYU) - Center for Data Science

Date Written: August 2006


This paper presents a model of local network effects in which agents connected by a social network each value the adoption of a product by a heterogeneous subset of other agents in their 'neighborhood', and have incomplete information about the structure and strength of adoption complementarities between all other agents. I show that the symmetric Bayes-Nash equilibria of this network game are in monotone strategies, can be strictly Pareto-ranked based on a scalar neighbor-adoption probability value, and that the greatest such equilibrium is uniquely coalition-proof. Each Bayes-Nash equilibrium has a corresponding fulfilled-expectations equilibrium under which agents form local adoption expectations. Examples illustrate cases in which the social network is an instance of a Poisson random graph, when it is a complete graph, a standard model of network effects, and when it is a generalized random graph. A generating function describing the structure of networks of adopting agents is characterized as a function of the Bayes-Nash equilibrium they play, and empirical implications of this characterization are discussed.

Keywords: Complex networks, complex systems, network games, long tail, power law, network effects, network structure, network formation, small-world, random graph, coordination game, coalition-proof, global games

JEL Classification: C72, D80, D85

Suggested Citation

Sundararajan, Arun, Local Network Effects and Complex Network Structure (August 2006). Available at SSRN: https://ssrn.com/abstract=650501 or http://dx.doi.org/10.2139/ssrn.650501

Arun Sundararajan (Contact Author)

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