Stability and learning in dynamic market systems.

Abstract

An Oligopoly is a special type of market system in which the number of producers is small and the interactions among them are significant. Since the interactions are significant, in order to reach higher profit it is very important for a producer to set up a prediction scheme to predict the decisions of the competitors and a good long-term strategy to occupy greater market share. To model and solve such problems, theoretical studies, field studies, and laboratory experiments (which include computer simulations), are the three major approaches. In this study, theoretical approach was used to develop four prediction schemes and study their stability conditions. Then laboratory experiments were conducted to study the decisions of the human subjects to identify the uses of these prediction schemes. The results of the experiments provided many important messages. In these experiments, not only the prediction schemes that developed by the theoretical approach have been actually used, but also from the strategies that developed by the experiment participants I saw the competitions have moved from the technical level to the psychological level. Based on the findings, I proposed some guidelines to develop a good decision model.