A study on sequential internet auctions using agent-based modeling approach

Abstract

With widespread use of the Internet, Internet auctions (e-auctions) become more popular in order to trade increasing number of goods as Internet provides both almost perfect market information and an infrastructure for executing auctions at lower administrative costs. The sequential auctions are the most widely used auction format. The aim of this study is to present a dynamic model of an e-auction so as to investigate how the welfare of buyers is affected by different bidding strategies. This problem has been studied in economics by conducting laboratory and field experiments and theoretically in various static auction mechanisms where perfect rationality of participants is assumed. On the other hand, observing the biding strategies of individuals is almost impossible in laboratory or field experiments. To overcome the limitations of these approaches, the new agent-based modeling methodology in which researchers use simulations to investigate the behavior and interactions of autonomous, heterogeneous, boundedly rational adaptive population of agents in the social and economical environments, has been emerged. In the study, the bottom-up agent-based modeling and simulation methodology is adapted to investigate the behavior of participants in electronic markets. A simulation model is developed to understand the effects of different bidding and bid increment strategies on the welfare of the bidder. To some extend sensitivity of the auction outcome on auction rules and market design parameters are also investigated.