Optimal Design of Customer Returns Policy and its Impact on Supply Chain

产品退货已成为零售业的一大挑战，因为它们既重要又昂贵；2013年，加拿大的平均客户退货率为8.9%，退货的货币价值为280亿美元。一些时尚单品的退货率可高达74%。然而，研究表明，只有大约5%的客户退货是由于缺陷。客户退货政策的范围从“100%退款保证”到“不退款”。它们影响客户的购买和退货决策以及零售商的定价和订单决策，从而影响供应链的绩效和盈利能力。产品的退回、加工、转售、再利用和/或处置也会产生环境和社会后果，因此对供应链的可持续性至关重要。 近年来，顾客退货引起了学术界和实务界的广泛关注。然而，关于最优客户退货政策结构的设计及其对供应链的影响的研究相当有限。通过过去几年的探索，我发现了与客户退货相关的重要研究空白，我建议阐明：1)更准确的客户退货模型，包括购买前和购买后的客户估值，以及相关的最优客户退货策略；2)定制的动态退货策略，在不同的客户和不同的时间段提供不同的策略；3)当供应链成员面临竞争时，结合库存和定价决策的客户退货策略的优化设计；4)多渠道供应链中制造商的回购策略和零售商的客户退货策略的整合；5)最优客户退货策略设计对供应链可持续性的影响。这些将通过数学建模，使用最优化和博弈论等定量方法来完成。 本研究将与产品退货相关的经济和环境重要性因素量化，并通过客户退货政策的优化设计来缓解客户退货的负面影响。提出的研究方案在考虑现有文献中没有讨论或新出现的关于最优退货政策设计的因素和问题方面是新颖和创新的：客户前后价值的变化、供应链竞争和可持续性、定制和动态的客户退货政策以及与回购政策的整合。该研究计划通过设计最优退货政策，为供应链成员提供了更有效和更可持续的战略机会。它还将通过填补知识的重大空白，提供培训未来研究人员的机会，并帮助加拿大公司在日益复杂的全球经济中竞争，从而使学术界和工业界都受益。

Product returns have become a major challenge in the retail industry, as they are both significant and costly; the average customer returns rate is 8.9% and the monetary value of returns was $28 billion in 2013 in Canada. Return rates of some fashion items can be as high as 74%. Research, however, shows that only about 5% of customer returns are due to defects. Customer returns policies range from “100% Money Back Guarantees” to “no refunds.” They influence customers' purchase and returns decisions as well as retailers' pricing and order decisions, and thus impact the performance and profitability of supply chains. The return, processing, resale, reuse, and/or disposal of products also have environmental and social consequences, and are therefore critical to supply chain sustainability. Customer returns have recently attracted much attention in both academia and practice. Studies of the design of optimal customer returns policy structures and their impact on supply chains, however, are rather limited. Through my explorations over the past several years, I have identified significant research gaps related to customer returns, and I propose to elucidate: 1) a more accurate customer returns model, incorporating customer valuations prior to and after purchase, and the associated optimal customer returns policy; 2) customized and dynamic returns policies, offering different policies to different customers and in different time periods; 3) optimal design of customer returns policy in conjunction with inventory and pricing decisions when supply chain members face competition; 4) integration of a manufacturer's buyback policy and retailers' customer returns policies in the multi-channel supply chain; and 5) impact of the optimal customer returns policy design on supply chain sustainability. These will be done through mathematical modelling, using quantitative methods, such as optimization and game theory. The proposed research quantifies factors of economic and environmental significance associated with product returns, and mitigates the negative impact of customer returns through optimal design of customer returns policies. The research program proposed is novel and innovative in considering factors and issues either not discussed or newly emerging in the existing literature on design of optimal returns policy: change of customers' prior and posterior values, supply chain competition and sustainability, customized and dynamic customer returns policies, and integration with buyback policies. The research program provides strategic opportunities for supply chain members to be more efficient and sustainable through the design of optimal returns policies. It will also benefit both academia and industry, by filling significant gaps in knowledge, providing opportunities to train future researchers, and helping Canadian companies compete in an increasingly complex global economy.