Order Fulfillment Under Pick Failure in Omnichannel Ship-From-Store Programs
研究了零售商在全渠道门店发货中，因拣货失败需多阶段尝试时，如何最优排序门店以最小化成本，并提出了考虑拣货失败概率的在线订单接受策略，对全渠道零售商有显著节省成本的作用。
Problem definition: We consider the setting where a retailer with many physical stores and an online presence seeks to fulfill online orders using an omnichannel fulfillment program, such as buy-online ship-from-store. These fulfillment strategies try to minimize cost while fulfilling orders within acceptable service times. We focus on single-item orders. Typically, all online orders for the item are sent to a favorable set of locations to be filled. Failed trials are sent back for further stages of trial fulfillment until the process times out. The multistage order fulfillment problem is thus an interplay of the pick-failure probabilities at the stores where they may be shipped from and the picking, shipping, and cancellation costs from these locations. Methodology: We model the problem as one of sequencing the stores from which an order is attempted to be picked and shipped in the most cost-effective way over multiple stages. We solve the fulfillment problem optimally by taking into account the changing pick-failure probabilities as a result of other online order fulfillment trials by casting it as a network flow problem with convex costs. We incorporate this as the second stage of a two-stage online order acceptance problem and generalize earlier results to the case with pick failures at stores. Results: We investigate the real-world performance of our methods and models on real order data of several of the top U.S. retailers that use our collaborating e-commerce solutions provider to optimize their fulfillment strategies. Academic/Practical Relevance: Our work enables retailers to incorporate pick failure in their order management systems for ship-from-store programs. Our new online order-acceptance policies that take into account pick failures can thus create significant savings for omnichannel retailers. Supplemental Material: The online appendices are available at https://doi.org/10.1287/msom.2022.1164 .