Robust pricing with refunds

Hinnosaar, Toomas; Kawai, Keiichi

Abstract

Before purchase, a buyer of an experience good learns about the product's fit using various information sources, including some of which the seller may be unaware of. The buyer, however, can conclusively learn the fit only after purchasing and trying out the product. We show that the seller can use a simple mechanism to take best advantage of the buyer's post-purchase learning to maximize his guaranteed-profit. We show that this mechanism combines a generous refund, which performs well when the buyer is relatively informed, with non-refundable random discounts, which work well when the buyer is relatively uninformed.

Citation

Hinnosaar, T., & Kawai, K. (2020). Robust pricing with refunds. RAND Journal of Economics, 51(4), 1014-1036. https://doi.org/10.1111/1756-2171.12348

• Journal Article Type: Article
• Acceptance Date: Apr 15, 2020
• Online Publication Date: Dec 4, 2020
• Publication Date: 2020-12
• Deposit Date: Jun 22, 2020
• Publicly Available Date: Dec 5, 2021
• Journal: The RAND Journal of Economics
• Print ISSN: 0741-6261
• Electronic ISSN: 1756-2171
• Peer Reviewed: Peer Reviewed
• Volume: 51
• Issue: 4
• Pages: 1014-1036
• DOI: https://doi.org/10.1111/1756-2171.12348
• Keywords: optimal pricing; robustness; return policies; refunds; monopoly; in- formation design; mechanism design
• Public URL: https://nottingham-repository.worktribe.com/output/4699607
• Publisher URL: https://onlinelibrary.wiley.com/doi/10.1111/1756-2171.12348
• Additional Information: Published: 2020-12-04