Here we discuss two streams of relevant research—the first deals with manufacturer’s returns while the second with consumer returns. The literature on manufacturer’s returns policies is quite extensive and examines the impact of a variety of factors. Marvel and Peck (1995), for instance, show that the decision to accept returns by manufacturers depends on the nature of demand uncertainty. Specifically, uncertainty over customer arrivals favors returns since returns compensate the retailers for holding risky inventory and result in optimal stock levels; in contrast, when the uncertainty is over consumer’s valuation, a no-returns policy is recommended to avoid price distortion. Padmanabhan and Png (1995) provide a summary of the various explanations for the use of manufacturer’s returns policies, including the need to (a) share the risk with the retailers when demand is uncertain, (b) safeguard the brand name, and (c) facilitate the distribution of new product information. More recently, Tsay (2002) shows how risk sensitivity affects the manufacturer’s optimal returns policy.
Next, abstracting from the insurance role of manufacturer’s returns policies, Pellegrini (1986) considers returns policies as an effective competitive tool for channel coordination when products are close substitutes and retailers are risk-neutral. The channel-coordination role of manufacturer’s returns policies is also explored by Pasternack (1985), who explores how a partial credit for unsold stock can achieve channel coordination. Next, the manu-facturer’s returns policy can serve as a tool either to signal the quality of the new product when it is not observable by the retailers (as in Chu 1993) or to learn the demand for a new product (as in Sarvary and Padmanabhan 2001). Finally, Kandel (1996) provides arguments for offering returns based on the optimal allocation of responsibility for unsold inventory between the manufacturer and the retailers. His research discusses six factors that affect the choice of returns, including: (i) optimal inventory, (ii) capability to dispose of unsold stocks, (iii) risk-sharing, (iv) incentives to provide marketing efforts in terms of quality, service, and promotions, (v) beliefs about sales distribution–when there is asymmetric information between the manufacturer and the retailer, and (vi) costs of returns.
Perhaps the most relevant papers for our analysis are Padmanabhan and Png (1997, 2004) and Wang (2004). These papers raise the intriguing possibility that manufacturer returns may sometimes lead to more intense competition at the retail level. Wang (2004), for example, qualifies the results of Padmanabhan and Png (1997) to show that when demand is certain, there is no difference in stocking levels, retail prices, and profits between accepting and not accepting returns. Padmanabhan and Png (2004) identify conditions, under demand uncertainty, when a manufacturer’s returns policy does intensify competition and raise profit.
In contrast to Padmanabhan and Png (1997, 2004) and Wang (2004), our paper consid-ers a setting in which the retailconsid-ers may choose to accept returns from consumconsid-ers. In the presence of consumer returns, we show that even though the nature of competition remains Cournot-like, manufacturer’s returns may nevertheless intensify retail competition under some conditions. In that sense, our analysis adds to this stream of literature.
We now turn to the second stream of literature, i.e., the one focusing on consumer returns policies. Che (1996) investigates the role of consumer returns policy in screening for high-valuation customers. He finds that when the retail cost is high and consumers are risk-averse, the retailer can protect its margin by selling only to high-valuation customers under a returns policy. Next, from a signaling perspective, Moorthy and Srinivasan (1995) (MS) argue that money-back guarantees, i.e., accepting returns from consumers, can credibly signal product quality. MS identify conditions under which money-back guarantees are necessary to signal quality; they also identify conditions under which these guarantees serve as a useful supplement to price in signaling quality.
Hess et al. (1996) investigate the role of a non-refundable charge in attenuating the moral hazard problem associated with accepting returns from consumers. That is the case when some consumers purchase the product with the intention of returning it after extracting some free value out of it. They find that the retailer is better off imposing a non-refundable charge when the trial value, the overall valuation, or the probability of consumer finding a matched product is high. Such a charge is also recommended when consumers’ transaction cost or the salvage value of the returned product is low. Next, Chu et al. (1998) study the impact of consumers’ opportunistic behavior, which results in abusive returns, on the firms’ optimal compensation policy. By investigating the trade-off between an increase in consumers’ willingness-to-pay and opportunistic behavior due to a returns policy, they find that a no-questions-asked refund policy is optimal; however, a full refund is not always rec-ommended. Specifically, partial refund are more likely to be offered when (a) the probability of dissatisfaction is low, (b) usage rate during product trial is high, (c) consumers’ cost of complaining is low, and (d) salvage value is low. Davis et al. (1995, 1998) and Yalabik et al.
(2005) determine the optimal returns policy for the retailer in various settings. For instance, Davis et al. (1995) suggest using full-returns policies either when the transaction cost is low, the salvage value of the returned product is significant, or the probability of the match
between consumers’ expectation and the product’s performance is small. Researchers in the operations management area are also interested in consumer returns with the focus on the impact of consumer returns on the design of the supply chain.
While this stream of research provides considerable insights, the focus is mainly on the risk-sharing role of consumer returns in a monopolistic environment. Our paper extends this literature by investigating the impact of consumer returns when retailers compete. We show, for instance, that even when consumers are risk-neutral, the retailers can benefit from accepting consumer returns. Overall, our paper contributes to the understanding of returns policies by investigating the strategic interaction between manufacturer’s returns and consumer returns.