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Better, Faster, Cheaper: An Experimental Analysis of a Multiattribute Reverse Auction Mechanism with Restricted Information Feedback

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  • Ching-Hua Chen-Ritzo

    () (Smeal College of Business, The Pennsylvania State University, University Park, Pennsylvania 16802)

  • Terry P. Harrison

    () (Smeal College of Business, The Pennsylvania State University, University Park, Pennsylvania 16802)

  • Anthony M. Kwasnica

    () (Smeal College of Business, The Pennsylvania State University, University Park, Pennsylvania 16802)

  • Douglas J. Thomas

    () (Smeal College of Business, The Pennsylvania State University, University Park, Pennsylvania 16802)

Abstract

The majority of reverse auctions for procurement use a single-attribute (price) format while providing constraints on nonprice attributes such as quality and lead time. Alternatively, a buyer could choose to conduct a multiattribute auction where bidders can specify both a price and levels of nonprice attributes. While such an auction may provide higher theoretical utility to the buyer, it is not clear that this theoretical improvement will be realized given the increased complexity of the auction. In this research, we present an ascending auction mechanism for a buyer whose utility function is known and dependent on three attributes. Motivated by a supply chain procurement problem setting, we consider quality and lead time for the two attributes in addition to price. The auction mechanism provides the bidders with restricted feedback regarding the buyer's utility function. We explore, experimentally, the performance of this multiattribute auction mechanism as compared to a price-only auction mechanism. Compared with the price-only auction, we find that our mechanism design is effective in increasing both buyer utility and bidder (supplier) profits.

Suggested Citation

  • Ching-Hua Chen-Ritzo & Terry P. Harrison & Anthony M. Kwasnica & Douglas J. Thomas, 2005. "Better, Faster, Cheaper: An Experimental Analysis of a Multiattribute Reverse Auction Mechanism with Restricted Information Feedback," Management Science, INFORMS, vol. 51(12), pages 1753-1762, December.
  • Handle: RePEc:inm:ormnsc:v:51:y:2005:i:12:p:1753-1762
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    File URL: http://dx.doi.org/10.1287/mnsc.1050.0433
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    References listed on IDEAS

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