Christina Johanna Liepold, Pedro Amorim, Maximilian Schiffer
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引用次数: 0
Abstract
Online retail platforms such as Amazon Marketplace, Zalando, or Hudson’s Bay are increasingly successful as they decrease transaction costs for both suppliers and customers. Online retail platforms act as intermediaries connecting suppliers and customers while usually carrying no stock. As their success depends on a sufficient customer and supplier count, platforms establish customer-friendly, benevolent return policies to attract customers and, in turn, increase their attractiveness towards suppliers. Thus, the likelihood of long-distance shipments and returns increases, which can result in severe economic and environmental costs. Mitigating the negative externalities of return shipments is a major challenge for internationally active platforms. We suggest utilizing the platform’s knowledge of global customer demand and its ability to foster information sharing among participating suppliers to allow for reduced return shipment distances and increased platform efficiency. We propose, implement, and evaluate a novel MArket-driven INter-supplier (MAIN) return policy, which mitigates financial and environmental externalities of returns in online retail platforms. Contrary to classical return shipments, the MAIN return policy allows the return of the product to any supplier conditional to maximizing the resale likelihood while minimizing the return shipment distance. We design an auction-based implementation where suppliers bid on customer-issued returns to increase their welfare while reducing negative return externalities. Implementing MAIN can mitigate the drawbacks of benevolent return policies for online retail platforms. Using a data set on retail platform transactions, we show that the resale value of returns increases on average by 2.5%; shipping distance and related emissions decrease by up to 94%.
期刊介绍:
The European Journal of Operational Research (EJOR) publishes high quality, original papers that contribute to the methodology of operational research (OR) and to the practice of decision making.