Local Network Effects and Complex Network Structure

36 Pages Posted: 19 Jan 2005

See all articles by Arun Sundararajan

Arun Sundararajan

New York University (NYU) - Leonard N. Stern School of Business

Date Written: August 2006

Abstract

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)

New York University (NYU) - Leonard N. Stern School of Business ( email )

Harold Price Professor of Entrepreneurship
44 West 4th Street
New York, NY NY 10012
United States

HOME PAGE: http://digitalarun.io/

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
659
Abstract Views
4,495
Rank
82,118
PlumX Metrics