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Prospect theory in a dynamic game: Theory and evidence from online pay-per-bid auctions

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  • Brünner, Tobias
  • Reiner, Jochen
  • Natter, Martin
  • Skiera, Bernd

Abstract

Abundant evidence exists that expected utility theory does not adequately describe decision making under risk. Although prospect theory is a popular alternative, it is rarely applied in strategic situations in which risk arises through individual interactions. This study fills this research gap by incorporating prospect theory preferences into a dynamic game theoretic model. Using a large field data set from multiple online pay-per-bid auction sites, the authors empirically show that their proposed model with prospect theory preferences makes a better out-of-sample prediction than a corresponding expected utility model. Prospect theory also provides a unified explanation for two behavioral anomalies: average auctioneer revenues above current retail prices and the sunk cost fallacy. The empirical results indicate that bidders are loss averse and overweight small probabilities, such that the expected revenue of the auction exceeds the current retail price by 25.46%. The authors illustrate and empirically confirm a managerial implication for how an auctioneer can increase revenue by changing the details of the auction design.

Suggested Citation

  • Brünner, Tobias & Reiner, Jochen & Natter, Martin & Skiera, Bernd, 2019. "Prospect theory in a dynamic game: Theory and evidence from online pay-per-bid auctions," Journal of Economic Behavior & Organization, Elsevier, vol. 164(C), pages 215-234.
  • Handle: RePEc:eee:jeborg:v:164:y:2019:i:c:p:215-234
    DOI: 10.1016/j.jebo.2019.05.032
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    More about this item

    Keywords

    Internet auction; Prospect theory; Dynamic game; Pricing; Penny auction;

    JEL classification:

    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

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