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T o retain old customers and promote sales, firms offer trade-in programs in which consumers bring in an old product and receive a trade-in rebate when buying a new one. However, after buying the new product, the consumer who has traded in (the "trade-in consumer") may return the new product and claim a refund for it if she/he is not satisfied with it. In this situation, under a full-trade-in-return (FTR) policy, trade-in consumers receive a generous refund that includes a trade-in-rebate for them to redeem if they purchase again in future. Alternatively, some firms have a partial-trade-in-return (PTR) policy under which trade-in consumers who return a newly purchased product only receive a refund for the amount of money they paid (without including the trade-in-rebate). In this study, we build stylized analytical models to explore the optimal choice of a trade-in-return policy. We find that there is no difference to the firm between an FTR and a PTR policy when no trade-in consumers keep unsatisfactory new products. In the case of a relatively medium residual value of the used product, FTR is always the better choice for the firm. When some trade-in consumers keep unsatisfactory new products, we show that FTR (PTR) is the better choice when the used product's durability is sufficiently low (high). We also show that the firm may not reduce its trade-in rebate when the "average new product satisfaction rate" of trade-in consumers increases. In the extended models, we find that, the firm is more likely to prefer PTR to FTR under the online-offline dualchannel retailing mode, but tends to prefer FTR to PTR when there is a competitive secondhand market, and should make the same optimal trade-in return policy when there are two selling periods.

Considering consumers are increasingly shopping online nowadays and the online sales market is dominated by e‐commerce giants, traditional retailers need to choose whether to enter e‐commerce platforms. Moreover, traditional retailers need to determine whether to offer offline return services considering online return services are very popular. To address these challenges, we explore a retailer's optimal offline return strategy and channel choice of whether or not to enter a platform in the contexts of symmetric information and asymmetric information, respectively. We present conditions for the retailer to share information. Interestingly, we find that the retailer in some conditions has no motivation to improve customer satisfaction rate of offline store. Most important, we find that the retailer's channel choice depends on the magnitude of the annual service fee that is affected by offline return strategy and asymmetric information, and the offline return strategy depends on the magnitude of the average residual value of returned products.

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