Robust pricing with refunds
研究了卖家如何利用退款和随机折扣的组合机制，在买家购买体验品后学习产品匹配度的过程中最大化保证利润，对关注定价和机制设计的学者有参考价值。
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.