© 1996 Oxford University Press
research-article |
Decision Rules and Market Share: Aggregation in an Information Contagion Model
Department of Political Economy, University of Modena Viale Berengario 51, I-41100 Modena, Italy
Abstract
In the Arthur—Lane information contagion model, agents choose sequentially between two competing products, basing their decisions upon information obtained from a sample of previous adopters. The market shares that each product obtains depend upon the true difference in performance between the products, but also on the number of previous adopters each agent samples and the way in which agents use the sample information to guide their product choice. We highlight some surprising features of these dependencies, when the number of agents the large. First, it is not socially optimal for agents to be Bayesian optimizers, in the sense that a simple rule-of-thumb always leads to an asymptotic market share of 100% for the better product, while Bayesian optimization can result in substantial market share for the inferior product. Second, we show that giving individual agents access to more information can lead to smaller market share for the superior product. Third, we show that the ability to predict limiting market shares for the two products, even given knowledge of how the products actually perform and how agents process information, depends upon features of agent psychology and their decision rules.