The product return rate (RR) is an important metric for retailers; even small RR changes can significantly impact retailers’ profit. Companies and researchers typically favor and employ one of three methods to calculate the RR: based on the number of returned items, these items’ revenue, or their profit contribution. Interviews with 24 managers and industry experts reveal that two methods, item-based and revenue-based, are often used. However, little is known about how much the interpretation of RRs depends on the calculation method. In this article, the authors rely on extensive datasets to investigate these potential differences empirically. Analyzing more than 8 million transactions at sixteen different retailers, the authors find that RRs calculated via the three methods differ on average by 24.3%. The size of these differences makes cross-sectional comparisons of RRs calculated via different methods difficult. In contrast, the authors find that the developments of the RRs over time are similar, which allows for a meaningful time-series comparison of RR developments, regardless of the method. Finally, this research shows that all three calculation methods result in RRs that are equally insightful (leading) indicators of relevant retailer performance metrics.

产品退货率 (RR) 是零售商的一个重要指标；即使是很小的 RR 变化也会显着影响零售商的利润。公司和研究人员通常喜欢并采用以下三种方法之一来计算 RR：基于退回物品的数量、这些物品的收入或它们的利润贡献。对 24 位经理和行业专家的访谈表明，经常使用两种方法，基于项目和基于收入。然而，人们对 RR 的解释在多大程度上取决于计算方法知之甚少。在本文中，作者依靠广泛的数据集从经验上研究这些潜在的差异。作者分析了 16 家不同零售商的超过 800 万笔交易，发现通过三种方法计算的 RR 平均相差 24.3%。这些差异的大小使得通过不同方法计算的 RR 的横截面比较变得困难。相比之下，作者发现 RR 随时间的发展是相似的，这允许对 RR 发展进行有意义的时间序列比较，而不管方法如何。最后，这项研究表明，所有三种计算方法都会产生同样具有洞察力（领先）的相关零售商绩效指标的 RR。