An Inverse-Optimization-Based Auction Mechanism to Support a Multiattribute RFQ Process

Damian R. Beil () and Lawrence M. Wein ()
Additional contact information
Damian R. Beil: University of Michigan Business School, Ann Arbor, Michigan 48109-1234
Lawrence M. Wein: Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142

Management Science, 2003, vol. 49, issue 11, 1529-1545

Abstract: We consider a manufacturer who uses a reverse, or procurement, auction to determine which supplier will be awarded a contract. Each bid consists of a price and a set of nonprice attributes (e.g., quality, lead time). The manufacturer is assumed to know the parametric form of the suppliers' cost functions (in terms of the nonprice attributes), but has no prior information on the parameter values. We construct a multiround open-ascending auction mechanism, where the manufacturer announces a slightly different scoring rule (i.e., a function that ranks the bids in terms of the price and nonprice attributes) in each round. Via inverse optimization, the manufacturer uses the bids from the first several rounds to learn the suppliers' cost functions, and then in the final round chooses a scoring rule that attempts to maximize his own utility. Under the assumption that suppliers submit their myopic best-response bids in the last round, and do not distort their bids in the earlier rounds (i.e., they choose their minimum-cost bid to achieve any given score), our mechanism, indeed, maximizes the manufacturer's utility within the open-ascending format. We also discuss several enhancements that improve the robustness of our mechanism with respect to the model's informational and behavioral assumptions.

Keywords: Inverse Optimization; Multiattribute Auctions; Mechanism Design (search for similar items in EconPapers)
Date: 2003
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (58)

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.49.11.1529.20588 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:49:y:2003:i:11:p:1529-1545

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().