Managing consumer returns with technology-enabled countermeasures

•There is no need to adopt technology-enabled return authorization systems if retailers can charge high restocking fees.•Adopting a customer profiling technology is favorable only if the additional hassle cost arising from privacy concerns is below a certain level.•Adopting a product tracking technology is favorable only if the increase in the procurement cost is below a certain level.•Although return fraud is mostly ignored by academics, the joint impact of return fraud and return abuse meaningfully changes a retailer’s optimal decisions and profit, from what would be observed if only return abuse was present. This paper examines retail return abuse with respect to both opportunistic and fraudulent consumer behavior. The decisions of interest are the retailer’s price for purchases and refund amount for returns. Our analysis provides managerial insight into how a retailer makes these decisions to mitigate return abuse. Including both forms of return abuse in a base model, we find that there is an interaction effect that meaningfully changes a retailer’s optimal decisions and profit, from what would be observed if only opportunism was present. We also evaluate two innovative technology-enabled countermeasures designed to mitigate return abuse: customer profiling and product tracking. A customer profiling system identifies opportunistic customers by using their personal identification and transaction history. In contrast, a product tracking system identifies fraudulent returns by recording each transaction of a product through the use of unique identifiers. We develop prescriptive models for these technologies and investigate the value of making such investments. Our analyses demonstrate the conditions in which it is advantageous to adopt these technologies and when such investments should be avoided. We find that when a retailer is able to charge restocking fees, it is well equipped to mitigate opportunism and fraud with only its price and refund decisions. Hence, the value of consumer profiling and product tracking technologies is limited. However, when a retailer is constrained to offer a full refund due to market dynamics, employing these technologies may hold significant value. Our analysis details the determinants of value, model sensitivity, and comparisons between models. We also address how these countermeasures impact a retailer’s profitability, demand structure, and decisions with respect to price and refund amount.