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Gacha Game: When Prospect Theory Meets Optimal Pricing

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  • Tan Gan

Abstract

I study the optimal pricing process for selling a unit good to a buyer with prospect theory preferences. In the presence of probability weighting, the buyer is dynamically inconsistent and can be either sophisticated or naive about her own inconsistency. If the buyer is naive, the uniquely optimal mechanism is to sell a ``loot box'' that delivers the good with some constant probability in each period. In contrast, if the buyer is sophisticated, the uniquely optimal mechanism introduces worst-case insurance: after successive failures in obtaining the good from all previous loot boxes, the buyer can purchase the good at full price.

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  • Tan Gan, 2022. "Gacha Game: When Prospect Theory Meets Optimal Pricing," Papers 2208.03602, arXiv.org, revised Aug 2023.
    • Handle: RePEc:arx:papers:2208.03602
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    1. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    2. Azevedo, Eduardo M. & Gottlieb, Daniel, 2012. "Risk-neutral firms can extract unbounded profits from consumers with prospect theory preferences," Journal of Economic Theory, Elsevier, vol. 147(3), pages 1291-1299.
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