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The model assumes that each product category is horizontally differentiated into several types of goods and that each bidder has a unit demand for only one type of the good. For example, a consumer may be shopping for one DVD of his or her favorite movie or for one unit of a specific brand and model of an MP3 player. Therefore, each bidder faces a trade-off between winning now and winning later, because the individual’s desired units are perfect substitutes; that is, the winner of each auction exits the marketplace and thus forgoes the expected surplus from participating in future auctions that also sell the desired good, possibly for a lower price. The future expected surplus forgone by the current winner is an opportunity cost of winning now, and rational, forward-looking bidders should reduce their bids relative to the myopic bidding strategy that would be optimal in the absence of future auctions.

The properties of the equilibrium bidding strategy depend on how much detail of the available information about near-future auctions the bidders actually use, that is, how sophisticated they are in taking the information into account. The author considers three nested levels of such information-usage sophistication. First, when bidders ignore the information completely, bids do not depend on short-term variation in the near-future frequency of auctions or on variation in the near-future incidence of specific product types. Second, frequency of near-future auctions is easier to discern than the specific attributes of the objects sold, so an intermediate level of sophistication involves bidders, who observe only the general frequency of auctions in the near future but not the types of the individual future objects. Such bidders should reduce their bids more whenever there are more auctions ending soon because this action would decrease the expected waiting time until another unit of their desired types comes up for sale. Third, each bidder can actually examine the near-future auctions closely and base his or her bidding strategy not only on timing but also on the types of objects actually coming up for sale. Then, the more personally desirable products coming up and the sooner they are coming up, the higher is the opportunity cost and, thus, the lower the bids.

How much detail of the available information about near-future auctions do actual eBay bidders use is an empirical question, and this article proposes an empirical strategy to answer this question using standard eBay data. The author uses two different data sets in the test, one from the MP3-player category, with each player brand–model combination considered a different type, and one from the DVD movie category, with different product types assigned to different movie titles. The empirical test on both product categories rejects the two nested, simpler models in favor of the “most sophisticated” model, in which bidders account for their personal preferences for specific future products. The author discusses implications of this phenomenon for optimal bidding and selling. 

Biography
Robert Zeithammer is an Assistant Professor of Marketing in the Graduate School of Business at the University of Chicago. He received a PhD in Marketing from the Sloan School of Management at the Massachusetts Institute of Technology. Before coming to Massachusetts Institute of Technology, he attended the University of Pennsylvania, earning an MA in Mathematics and a BA in Economics; he graduated summa cum laude and was a member of Phi Beta Kappa. He also holds a General Course Certificate from the London School of Economics and Political Science. His research focuses on sequential auction marketplaces, such as eBay. In other work, Robert analyzed the optimal selling strategy in the presence of strategic forward-looking bidders and has characterized the overall market equilibrium. He is currently working on understanding why the same products are sometimes sold by posted prices and other times by auctions.

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