The Right Auction at the Right Price

8 Pages Posted: 26 May 2006

See all articles by Matthew Reindorp

Matthew Reindorp

Drexel University - Department of Decision Sciences

Wolfgang Jank

University of Maryland - Decision and Information Technologies Department

Louiqa Raschid

University of Maryland - Decision and Information Technologies Department; University of Maryland - College of Computer, Mathematical and Natural Sciences; University of Maryland - Robert H. Smith School of Business

Date Written: 2005

Abstract

Research literature to date shows few attempts to formalize a successful method for bidding in online auctions. We have collected and analyzed data from approximately 5,000 eBay auctions of laptop computers, in order to develop a system that could guide an auction participant to winning without overpaying. As the foundation for our work, we construct three different models of final auction prices, one of which uses solely mean normalized price levels to make predictions. Next, we describe a strategy for using any one of our models in a live auction setting. The strategy is based on plausible assumptions about the general behavior and motivations of online auction participants. In the context of this strategy, we examine the performance of each of our models on test data. For the subset of test auctions that each model wins, we also examine the performance of the two alternative models, in order to quantify a user's incentive to switch from one model to another. Results for the model of mean normalized price levels are very promising, and our paper concludes with some discussion of this finding.

Keywords: online auctions, statistical models, price prediction, strategic bidding

Suggested Citation

Reindorp, Matthew and Jank, Wolfgang and Raschid, Louiqa, The Right Auction at the Right Price (2005). Robert H. Smith School Research Paper No. RHS-06-009. Available at SSRN: https://ssrn.com/abstract=904626 or http://dx.doi.org/10.2139/ssrn.904626

Matthew Reindorp (Contact Author)

Drexel University - Department of Decision Sciences ( email )

United States

Wolfgang Jank

University of Maryland - Decision and Information Technologies Department ( email )

Robert H. Smith School of Business
4300 Van Munching Hall
College Park, MD 20742
United States
301-405-1118 (Phone)

HOME PAGE: http://www.smith.umd.edu/faculty/wjank/

Louiqa Raschid

University of Maryland - Decision and Information Technologies Department ( email )

Robert H. Smith School of Business
4313 Van Munching Hall
College Park, MD 20815
United States

University of Maryland - College of Computer, Mathematical and Natural Sciences ( email )

2300 Symons Hall,
University of Maryland
College Park, MD 20742-3255
United States

University of Maryland - Robert H. Smith School of Business

College Park, MD 20742-1815
United States

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