Predicting bidders' willingness to pay in online multiunit ascending auctions: Analytical and empirical insights
Bapna, R and Goes, P and Gupta, A and Karuga, G (2008) Predicting bidders' willingness to pay in online multiunit ascending auctions: Analytical and empirical insights. INFORMS Journal on Computing, 20 (3). pp. 345-355.
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we develop a real-time estimation approach to predict bidders' maximum willingness to pay in a multiunit ascending uniform-price and discriminatory-price (Yankee) online auction. Our two-stage approach begins with a bidder classification step, which is followed by an analytical prediction model. The classification model identifies bidders as either adopting a myopic best-response (MBR) bidding strategy or a non-MBR strategy. We then use a generalized bid-inversion function to estimate the willingness to pay for MBR bidders. We empirically validate our two-stage approach using data from two popular online auction sites. Our joint classification-and- prediction approach outperforms two other naive prediction strategies that draw random valuations between a bidder's current bid and the known market upper bound. Our prediction results indicate that, on average, our estimates are within 2% of bidders' revealed willingness to pay for Yankee and uniform-price multiunit auctions. We discuss how our results can facilitate mechanism-design changes such as dynamic-bid increments and dynamic buy-it-now prices.
| Affiliation: | Indian School of Business |
|---|---|
| ISB Creiators: |
ISB Creators ORCiD Bapna, R UNSPECIFIED |
| Item Type: | Article |
| Uncontrolled Keywords: | Dynamic-mechanism design; Online auctions; Predicting willingness to pay |
| Subjects: | Business and Management |
| Depositing User: | Veeramani R |
| Date Deposited: | 01 Nov 2014 14:48 |
| Last Modified: | 11 Feb 2019 15:39 |
| URI: | http://eprints.exchange.isb.edu/id/eprint/115 |
| Publisher URL: | http://dx.doi.org/10.1287/ijoc.1070.0247 |
| Publisher OA policy: | http://www.sherpa.ac.uk/romeo/issn/1091-9856/ |
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