Content Analysis of Information Exchange in Online Auctions

The literature on internet auctions focuses largely on the problem of information asymmetry and the steps taken to address the adverse selection problem. The central question for researchers is the issue of increasing efficiency of exchange through appropriate auction design mechanisms. Typically, the focus has been on either pre-transactional information (product descriptions, seller reputation, etc.) or post-transactional information (experience reviews). In this paper, we study the nature of information exchanged between auction participants while an auction is in progress. We examined 295 auctions of used cars that occurred over a two week period in a popular online auction site. By classifying the contents of this exchange into various categories, we analyze their effect on auction outcomes. Our models indicate that there is a significant role that such information can play in determining auction outcomes.