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A Multiattribute Sealed-Bid Procurement Auction with Multiple Budgets for Government Vendor Selection

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  • Jay Simon

    (Defense Resources Management Institute, Naval Postgraduate School, Monterey, California 93943)

  • Francois Melese

    (Defense Resources Management Institute, Naval Postgraduate School, Monterey, California 93943)

Abstract

This paper offers a new approach to government vendor selection decisions in major public procurements. A key challenge is for government purchasing agents to select vendors that deliver the best combination of desired nonprice attributes at realistic funding levels. The mechanism proposed in this paper is a multiattribute first-price, sealed-bid procurement auction. It extends traditional price-only auctions to those in which competition takes place exclusively over attribute bundles. The model is a multiattribute auction in which a set of possible budget levels is specified. This model reveals the benefits of defining a procurement alternative in terms of its value to the buyer over a range of possible expenditures, rather than as a single point in budget-value space. This new approach leads to some interesting results. In particular, it suggests that in a fiscally constrained environment, the traditional approach of eliminating dominated alternatives could lead to suboptimal decisions. Finally, an extension of the model explicitly examines the buyer's decision problem under budget uncertainty by applying a utility function assessed over the value measure.

Suggested Citation

  • Jay Simon & Francois Melese, 2011. "A Multiattribute Sealed-Bid Procurement Auction with Multiple Budgets for Government Vendor Selection," Decision Analysis, INFORMS, vol. 8(3), pages 170-179, September.
    • Handle: RePEc:inm:ordeca:v:8:y:2011:i:3:p:170-179
    DOI: 10.1287/deca.1110.0210
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    References listed on IDEAS

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    Cited by:

    1. Lance W. Saunders & J. Paul Brooks & Jason R. W. Merrick & Chad W. Autry, 2020. "Addressing Economic/Environmental Sustainability Trade‐offs in Procurement Episodes with Industrial Suppliers," Production and Operations Management, Production and Operations Management Society, vol. 29(5), pages 1256-1269, May.
    2. L. Robin Keller & Ali Abbas & J. Eric Bickel & Vicki M. Bier & David V. Budescu & John C. Butler & Philippe Delquié & Kenneth C. Lichtendahl & Jason R. W. Merrick & Ahti Salo & George Wu, 2011. "From the Editors ---Probability Scoring Rules, Ambiguity, Multiattribute Terrorist Utility, and Sensitivity Analysis," Decision Analysis, INFORMS, vol. 8(4), pages 251-255, December.
    3. Gregory E. Kersten, 2014. "Multiattribute Procurement Auctions: Efficiency and Social Welfare in Theory and Practice," Decision Analysis, INFORMS, vol. 11(4), pages 215-232, December.
    4. repec:syb:wpbsba:06/2013 is not listed on IDEAS
    5. Gediminas Adomavicius & Shawn P. Curley & Alok Gupta & Pallab Sanyal, 2020. "How Decision Complexity Affects Outcomes in Combinatorial Auctions," Production and Operations Management, Production and Operations Management Society, vol. 29(11), pages 2579-2600, November.
    6. L. Robin Keller, 2011. "From the Editor ---Multiattribute and Intertemporal Preferences, Probability, and Stochastic Processes: Models and Assessment," Decision Analysis, INFORMS, vol. 8(3), pages 165-169, September.
    7. James E. Smith & James S. Dyer, 2021. "On (Measurable) Multiattribute Value Functions: An Expository Argument," Decision Analysis, INFORMS, vol. 18(4), pages 247-256, December.

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