Coincident with the rapid growth of consumer returns and their corresponding importance in the retail marketplace, academic interest in the area of consumer return policy design has significantly increased. In fact, the growth in academic publications has been tremendous, with almost half of the published works appearing within the past 6 years. The influx of new and evolving research spans across multiple disciplines and various methodologies. To provide clarity for the continued evolution of the field, we provide a comprehensive review and classification of the literature predicated on a holistic conceptual framework. The scope of the review includes all peer reviewed journal articles published prior to the end of 2018, along with any working papers cited therefrom, that specifically address (a) managerial decision‐making related to return policies or (b) consumer behavior in response to such decision‐making. Examining the state of the literature and practice on return policy design through the lens of a unified conceptual framework—a framework that spans both analytical and empirical research—reveals numerous managerial and theoretical opportunities for future research.

Problem definition: We empirically examine a complementary behavioral source of the bullwhip effect that has been previously overlooked in the literature: that individuals order more aggressively (i.e., overreact) when they face shortages than when they hold inventory. Methodology/Results: We conduct a behavioral experiment using the beer distribution game. We estimate decision rules using multilevel modeling approaches that overcome several drawbacks of the estimation methods used in the earlier literature. We find robust evidence that, contrary to the overreaction when in backlog hypothesis and reports from popular press, decision makers order less aggressively and become insensitive to the scope of the problem when in backlog—a scope neglect phenomenon. Managerial implications: We propose a dual-process theoretical account predicated on affective reactions to explain this scope neglect. Our results suggest that affective reactions under novel operating conditions or dramatic events in supply chains, such as the COVID-19 pandemic, can overwhelm cognitive processing of managers and make them fail to recognize the full scope of the problems faced and update decision models accordingly. Understanding the cognitive-affective drivers of ordering behaviors that generate supply chain instability is important in designing interventions to mitigate their negative effects.

Due to the ongoing and dramatic growth in the volume of consumer returns, retailers continue to struggle with the trade-off in returns service strategies between implementing stricter return policies to lower operational costs and environmental footprint versus providing customers with lenient return policies to positively stimulate customers' value perceptions and patronage intentions. This paper argues that effective management of this trade-off requires a deep understanding of the process through which consumers perceive, evaluate, and respond to return policies that vary in terms of leniency across five key dimensions identified in the literature: monetary, time, effort, scope, and exchange. To this end, we theorize on a cognitive process model and empirically test the model using randomized experiments with diverse consumer samples. By viewing each of the five leniency dimensions as returns service design levers, we examine (1) how a retailer's return policy leniency across different levers impacts a consumer's intention to purchase from a retailer, through the influence of leniency on the perceptions regarding returns service quality and transaction costs that jointly form perceived returns service value, and (2) how different leniency levers are compared in terms of their impacts. We find significant heterogeneity in the effectiveness of different leniency levers in influencing consumers' purchase intentions through increased perceived service quality, reduced perceived transaction costs, and subsequently increased perceived service value.

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