Replicating Online Yankee Auctions to Analyze Auctioneers' and Bidders' Strategies

Ravi Bapna (), Paulo Goes () and Alok Gupta ()
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Ravi Bapna: Department of Operations and Information Management, U-41 IM, School of Business, University of Connecticut, Storrs, Connecticut 06269
Paulo Goes: Department of Operations and Information Management, U-41 IM, School of Business, University of Connecticut, Storrs, Connecticut 06269
Alok Gupta: Information and Decision Sciences Department, 3-365 Carlson School of Management, University of Minnesota, 321-19th Avenue South, Minneapolis, Minnesota 55455

Information Systems Research, 2003, vol. 14, issue 3, 244-268

Abstract: We present a simulation approach that provides a relatively risk-free and cost-effective environment to examine the decision space for both bid takers and bid makers in web-based dynamic price setting processes. The applicability of the simulation platform is demonstrated for Yankee auctions in particular. We focus on the optimization of bid takers' revenue, as well as on examining the welfare implications of a range of consumer-bidding strategies—some observed, some hypothetical. While these progressive open discriminatory multiunit auctions with discrete bid increments are made feasible by Internet technologies, little is known about their structural characteristics, or their allocative efficiency. The multiunit and discrete nature of these mechanisms renders the traditional analytic framework of gametheory intractable (Nautz and Wolfstetter 1997). The simulation is based on theoretical revenue generating properties of these auctions. We use empirical data from real online auctions to instantiate the simulation's parameters. For example, the bidding strategies of the bidders are specified based on three broad bidding strategies observed in real online auctions. The validity of the simulation model is established and subsequently the simulation model is configured to change the values of key control factors, such as the bid increment. Our analysis indicates that the auctioneers are, most of the time, far away from the optimal choice of bid increment, resulting in substantial losses in a market with already tight margins. The simulation tool provides a test bed for jointly exploring the combinatorial space of design choices made by the auctioneer's and the bidding strategies adopted by the bidders. For instance, a multinomial logit model reveals that endogenous factors, such as the bid increment and the absolute magnitude of the auction have a statistically significant impact on consumer-bidding strategies. This endogeniety is subsequently modeled into the simulation to investigate whether the effects are significant enough to alter the optimal bid increments or auctioneer revenues. Additionally, we investigate hybrid-bidding strategies, derived as a combination of three broad strategies, such as jump bidding and strategic-at-margin (SAM) bidding. We find that hybrid strategies have the potential of significantly altering bidders' likelihood of winning, as well as their surplus.

Keywords: Dynamic Pricing; Online Auctions; Simulation (search for similar items in EconPapers)
Date: 2003
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Citations: View citations in EconPapers (20)

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