Managing customer returns effectively in the supply chain

大多数零售商提供宽松的退货政策作为售后服务，以留住忠诚的客户，确保良好的购物体验。然而，产品退货对零售业来说代价非常高昂。根据美国零售联合会最近的一份报告，2020年零售客户的平均退货率为10.6%(加拿大类似)，即美国的4280亿美元。在线退货率甚至更高，因为技术的发展和大流行鼓励了在线购物的扩张。产品退货不仅影响卖家(直接处理退货)，还影响供应链中的制造商(设计和生产产品)。因此，从整个供应链的角度有效和协调地管理客户退货是一个系统性和关键性的问题。然而，大多数关于客户退货的研究都集中在退货政策下卖家的价格和订货量决策，以及单一退货管理行动的影响，而没有从供应链的角度考虑退货管理。到目前为止，还没有研究评估销售商和制造商如何(通过什么行动和机制)最有效地管理客户退货，也没有研究从供应链的角度考虑有效的客户退货管理。在过去的6年里，随着我的NSERC资助的探索，我已经确定了文献中的重大差距，将在拟议的研究中解决。我建议阐明：1)卖家如何有效地管理客户退货，包括通过使用数据分析和机器学习技术对客户群进行细分，通过定制商店/渠道服务来定制退货政策，以及通过提高在线产品评论的效率来更好地在购买前告知客户，从而降低退货率；2)如何设计激励和机制，让制造商通过提高产品质量/适合度来管理退货，以及协调和整合供应链上下的退货管理的激励和机制，从而影响供应链的可持续性；3)如何设计一个最优的整个供应链协调的退货政策。他说，这项研究将带来重大的学术和实践成果。首先，从供应链的角度丰富了有效客户退货管理的理论。其次，它将为卖家和供应链提供有效的客户退货管理的新见解，为运营战略提供信息并做出合理的决策，最终更好地服务客户并提高运营效率。最后，拟议的研究将为不同背景的本科生和研究生提供公平、包容和可获得的机会。这一研究项目的成功可以帮助加拿大公司在全球经济中具有竞争力和可持续性。

Most retailers provide lenient returns policies as post-sale service, to retain loyal customers and ensure good shopping experiences. Product returns, however, are very costly to the retail industry. According to a recent report by the National Retail Federation, the average retail customer returns rate is 10.6% (similar in Canada), or $428 billion in the US in 2020. The returns rate online is even higher, as technology enables and the pandemic encourages the expansion of online shopping.     Product returns affect not only sellers (who handle returns directly), but also manufacturers (designing and producing products) in the supply chain. Managing customer returns effectively and in coordination from the perspective of the whole supply chain is thus a systemic and critical issue.     Most studies on customer returns have focused on sellers' price and order quantity decisions under a returns policy, and the effects of single returns management actions, and have failed to consider returns management from the supply chain perspective. No study has as yet evaluated how (by what actions and mechanisms) sellers and manufacturers can most effectively manage customer returns, and no study has yet considered effective customer returns management from a supply chain perspective. Over the past 6 years with my NSERC funded explorations, I have identified significant gaps in the literature, to be addressed in the proposed research. I propose to elucidate: 1) how sellers can effectively manage customer returns, including through customization of returns policies by segmentation of the customer base using data analytics and machine learning techniques, through customization of store/channel services, and by improving the efficacy of online product reviews to better inform customers pre-purchase and thus decrease the rate of returns; 2) how to design incentives and mechanisms for the manufacturer to manage returns by improving product quality/fitness, and incentives and mechanisms to coordinate and integrate returns management up and down the supply chain, with impact on supply chain sustainability; 3) how to design an optimal whole-supply-chain coordinated returns policy.     This research will lead to significant academic and practical outcomes. First, it will enrich theories on effective customer returns management from the perspective of the supply chain. Second, it will provide new insights into effective customer returns management for both sellers and supply chains, informing operations strategies and enabling sound decisions, ultimately to serve customers better and improve operational efficiency. Finally, the proposed research will provide equitable, inclusive, and accessible opportunities for undergraduate and graduate students of diverse backgrounds. Success in this research program can help Canadian companies to be competitive and sustainable in the global economy.