IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v37y1991i4p377-395.html
   My bibliography  Save this article

Resource Allocation Models with Risk Aversion and Probabilistic Dependence: Offshore Oil and Gas Bidding

Author

Listed:
  • Donald L. Keefer

    (Department of Decision and Information Systems, College of Business, Arizona State University, Tempe, AZ 85287-4206)

Abstract

Bidding for offshore U.S. oil and gas leases is a major corporate resource allocation problem involving enormous uncertainties and very high stakes. This paper presents two new, operationally useful decision analysis models to aid in bidding for oil and gas leases. They are unique in that they consider risk aversion and probabilistic dependence among the values of the leases, with both bid levels and partnership shares as (continuous) decision variables. They are suitable for use in evaluating proposed bidding policies or as objective functions in optimization formulations. Practicality of their data requirements is evidenced by use of one of the models for several years in a major oil company. Comparison of optimal solutions to these models on a small example, using actual oil-company data, demonstrates the importance of taking risk aversion and probabilistic dependence into account, and provides insight into the adequacy of independence and conditional dependence as approximations for dependence. These results are pertinent to other real-world allocation problems that share many of the characteristics of bidding problems, such as R&D funds allocation.

Suggested Citation

  • Donald L. Keefer, 1991. "Resource Allocation Models with Risk Aversion and Probabilistic Dependence: Offshore Oil and Gas Bidding," Management Science, INFORMS, vol. 37(4), pages 377-395, April.
    • Handle: RePEc:inm:ormnsc:v:37:y:1991:i:4:p:377-395
    DOI: 10.1287/mnsc.37.4.377
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.37.4.377
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.37.4.377?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. James E. Smith & Kevin F. McCardle, 1998. "Valuing Oil Properties: Integrating Option Pricing and Decision Analysis Approaches," Operations Research, INFORMS, vol. 46(2), pages 198-217, April.
    2. Li, Zhen & Kuo, Ching-Chung, 2011. "Revenue-maximizing Dutch auctions with discrete bid levels," European Journal of Operational Research, Elsevier, vol. 215(3), pages 721-729, December.
    3. Donald L. Keefer & Craig W. Kirkwood & James L. Corner, 2004. "Perspective on Decision Analysis Applications, 1990–2001," Decision Analysis, INFORMS, vol. 1(1), pages 4-22, March.
    4. Craig W. Kirkwood, 2004. "Approximating Risk Aversion in Decision Analysis Applications," Decision Analysis, INFORMS, vol. 1(1), pages 51-67, March.
    5. Zhen Li & Ching-Chung Kuo, 2013. "Design of discrete Dutch auctions with an uncertain number of bidders," Annals of Operations Research, Springer, vol. 211(1), pages 255-272, December.
    6. Zhou, P. & Ang, B.W. & Poh, K.L., 2006. "Decision analysis in energy and environmental modeling: An update," Energy, Elsevier, vol. 31(14), pages 2604-2622.
    7. James E. Smith & Detlof von Winterfeldt, 2004. "Anniversary Article: Decision Analysis in Management Science," Management Science, INFORMS, vol. 50(5), pages 561-574, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:37:y:1991:i:4:p:377-395. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.