Optimal restocking fees and information provision in an integrated demand-supply model of product returns

Product returns cost U.S. companies more than $100 billion annually. The cost and scale of returns management issues necessitate a deeper understanding of how to deal with product returns. We develop an analytical model that describes how consumer purchase and return decisions are affected by a seller's pricing and restocking fee policy. Taking into account the consumers' strategic behavior, we derive the seller's optimal policy as a function of consumer preferences, consumer uncertainty about product attributes, consumer hassle cost for returns, and the effectiveness of the seller's forward and reverse channel capability. We allow for two sources of consumer uncertainty and show how the seller may use its price and restocking fee as a means of targeting a segment of consumers who know their product consumption utilities. We find that even if it is possible to eliminate returns costlessly through the provision of information about the fit between consumer preferences and product characteristics, returns can nevertheless be part of an optimal product sales process. That is, we identify conditions under which it is (or is not) optimal to provide product fit information to consumers. We show that the marginal value of information to the seller is decreasing in the operational efficiency of the seller's forward and reverse logistics process as well as the level of product uncertainty. We identify the impact of multiple product options and sources of consumer uncertainty on the model's results. The analysis generates testable hypotheses about how consumer-level and seller-level parameters affect the return policies observed in the marketplace.