Working Paper: CEPR ID: DP14615
Authors: Toomas Hinnosaar; Keiichi Kawai
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 best take 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.
Keywords: Optimal Pricing; Robustness; Return Policies; Refunds; Monopoly; Information Design; Mechanism Design
JEL Codes: D82; C79; D42
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Generous Refund Policy (H43) | Increased Buyer Confidence (D19) |
| Increased Buyer Confidence (D19) | Higher Prices Charged by Seller (D49) |
| Generous Refund Policy (H43) | Higher Prices Charged by Seller (D49) |
| Random Nonrefundable Discounts (H43) | Increased Profit Margins for Sellers (D40) |
| Combination of Refund and Discount Policies (L42) | Best Guaranteed Profit for Seller (D44) |
| Generous Refund Policy (H43) | Increased Guaranteed Profit (D33) |
| Increased Buyer Confidence (D19) | Increased Guaranteed Profit (D33) |
| Random Nonrefundable Discounts (H43) | Capture Profits from Buyers (D41) |