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Measuring Risk Aversion in a Name-Your-Own-Price Channel

Author

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  • Ali E. Abbas

    (Department of Industrial and Enterprise Systems Engineering, College of Engineering, University of Illinois at Urbana--Champaign, Urbana, Illinois 61820)

  • Il-Horn Hann

    (Decision, Operations and Information Technologies, Robert H. Smith School of Business, University of Maryland, College Park, Maryland 20742)

Abstract

This paper measures the risk aversion coefficients exhibited by online customers at a name-your-own-price (NYOP) intermediary that allowed the submission of subsequent offers. We present a decision analytic model to determine the optimal sequence of offers for a decision maker with a constant risk aversion coefficient. We show how the optimal sequence of offers can be determined by simple sensitivity analysis. We then discuss the inverse problem of estimating the risk aversion coefficient from a sequence of offers placed by a customer. We provide a direct expression for the risk aversion coefficient in terms of the increments between each two successive offers. This expression separates the estimation of the risk aversion from the remaining model parameters and enables its calculation directly by observing a sequence of offers from a customer. We then use field data from an NYOP firm to estimate the risk aversion that is exhibited throughout the online process. We find that customers exhibit relatively high risk aversion coefficients on Internet sites. Based on three different product groups, we also find that risk aversion is a significant variable in the offer strategy of the customers. To our knowledge, this is the first work that empirically examines risk aversion in a nonexperimental Internet-based NYOP setting.

Suggested Citation

  • Ali E. Abbas & Il-Horn Hann, 2010. "Measuring Risk Aversion in a Name-Your-Own-Price Channel," Decision Analysis, INFORMS, vol. 7(1), pages 123-136, March.
  • Handle: RePEc:inm:ordeca:v:7:y:2010:i:1:p:123-136
    DOI: 10.1287/deca.1100.0173
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    References listed on IDEAS

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    Cited by:

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    2. Jianbin Li & Qifei Wang & Hong Yan & Stuart X. Zhu, 2016. "Optimal Remanufacturing and Pricing Strategies Under Name-Your-Own-Price Auctions and Stochastic Demand," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 33(01), pages 1-22, February.
    3. L. Robin Keller, 2010. "From the Editor..," Decision Analysis, INFORMS, vol. 7(3), pages 235-237, September.
    4. Krämer, Florentin & Schmidt, Klaus M. & Spann, Martin & Stich, Lucas, 2017. "Delegating pricing power to customers: Pay What You Want or Name Your Own Price?," Journal of Economic Behavior & Organization, Elsevier, vol. 136(C), pages 125-140.
    5. 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.
    6. Jason Shachat & Lijia Wei, 2012. "Procuring Commodities: First-Price Sealed-Bid or English Auctions?," Marketing Science, INFORMS, vol. 31(2), pages 317-333, March.
    7. Robert F. Bordley & Elena Katok & L. Robin Keller, 2010. "Honoring Michael H. Rothkopf's Legacy of Rigor and Relevance in Auction Theory: From the Editors," Decision Analysis, INFORMS, vol. 7(1), pages 1-4, March.
    8. L. Robin Keller & Kelly M. Kophazi, 2011. "From the Editors---Deterrence, Multiattribute Utility, and Probability and Bayes' Updating," Decision Analysis, INFORMS, vol. 8(2), pages 83-87, June.
    9. L. Robin Keller & Kelly M. Kophazi, 2010. "From the Editors..," Decision Analysis, INFORMS, vol. 7(2), pages 151-154, June.
    10. Chen, Yahong & Li, Jinlin & Huang, He & Ran, Lun & Hu, Yusheng, 2017. "Encouraging information sharing to boost the name-your-own-price auction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 108-117.

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