A study on internet auctions using agent based modeling approach

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 ascending-bid, second-price auction is the most widely used e-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 ascending-bid types. This problem has been studied theoretically in economics in various static auction mechanisms where perfect rationality of participants is assumed. To overcome the limitations of this approach, the new agent based modeling methodology in which researchers use simulations to investigate the behavior and interactions of autonomous, heterogeneous, bounded rational adaptive population of agents in the social and economical environments, has been emerged. In this paper we adapt the bottom-up agent based modeling methodology to investigate the behavior of participants in electronic markets. On the other hand, since observing the biding strategies of individuals is almost impossible in laboratory or field experiments, we developed a simulation model to understand the welfare effects of different bidding strategies. To some extend sensitivity of the auction outcome on auction rules and market design parameters are also investigated. In our experiments the strategies where the agents update their bid increments in proportion to the differences between their reservation price and current bid are found to be the winning strategies where the duration of the auction is shorter. As the duration of the auction increases all the strategies converged to the same average payoffs.