Reactivity based model to study online auctions dynamics

Online auctions have challenged many assumptions and results from the traditional economic auction theory. Observed bidder behavior in online auctions often deviates from equilibrium strategies postulated by economic theory. In this research, we consider an online auction as an information system that provides a long-duration, information-rich, dynamic application environment in which users (bidders) interact with the system in a feedback loop, in what we term reactivity. Bidders react to the observed conditions of the auction and events triggered by actions of other bidders. In this work we propose a new characterization model with the purpose of isolating the segments of the auction in which users react to the auction conditions and events. Through this model, it is possible to enrich the auction characterization. Despite the existence of other bidding characterization models, none of them is enough for understanding the factors that characterize and explain the auction dynamics. We present results which demonstrate the advantages of applying our methodology. The final objective is to gain an understanding of what drives the dynamics of online auctions, the role of reactivity in the auction dynamics, and how the outcome of the auction is affected by the particular dynamics of the system.