Retailing has changed dramatically from single-channel brick-and-mortar stores to multi-channel and omnichannel retailers over the last few decades. Omnichannel retailers employ different strategies to integrate online and offline sales channels as well as order fulfillment processes. Among these strategies, the ship-from-store is the most popular and widely accepted among retailers. It enables retailers to use inventory from store locations to fulfill online demand. An omnichannel retailer with a distribution center and a retail store has to make important, interlinked decisions — (1) how much inventory to keep at the retail store, and (2) where to fulfill the online demand from and how much. In this work, we model the integrated inventory replenishment and online demand allocation decisions for an omnichannel retailer employing the ship-from-store strategy. We analyze this problem for both single-period and multi-period settings. We extend the analytical framework of the single-period problem by providing a finite-horizon Markov decision process (MDP) formulation for the multi-period problem. Our findings suggest that for a single-period setting, decentralized inventory replenishment and demand allocation system maximizes the profit of the omnichannel retailer for low values of the incentive for fulfilling the online demand through store inventory, while for sufficiently high values of the incentive, a pooled system provides the optimal profit. An increment in the discount factor has the same effect on the optimal decisions in a multi-period setting as that of salvage value in a single-period setting for a given value of the incentive for the ship-from-store strategy. We also provide several extensions (such as cross selling, endogenous and correlated demand streams) of our analytical framework for the multi-period problem.

中文翻译：

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为采用店内发货策略的全渠道零售商提供集成库存补货和在线需求分配决策

在过去的几十年里，零售业发生了巨大变化，从单渠道实体店转变为多渠道和全渠道零售商。全渠道零售商采用不同的策略来整合线上和线下销售渠道以及订单履行流程。在这些策略中，从商店发货是最受零售商欢迎和广泛接受的。它使零售商能够使用商店位置的库存来满足在线需求。拥有配送中心和零售店的全渠道零售商必须做出重要的、相互关联的决策 - (1) 零售店保留多少库存，以及 (2) 在哪里满足在线需求以及满足多少。在这项工作中，我们为采用从商店发货策略的全渠道零售商建模了集成库存补货和在线需求分配决策。我们针对单周期和多周期设置来分析这个问题。我们通过为多周期问题提供有限视野马尔可夫决策过程（MDP）公式来扩展单周期问题的分析框架。我们的研究结果表明，对于单周期设置，分散的库存补货和需求分配系统可以在通过商店库存满足在线需求的激励值较低的情况下最大化全渠道零售商的利润，而在激励值足够高的情况下，池化系统提供最优利润。对于从商店发货策略的激励给定值，折扣因子的增量对多周期设置中的最优决策的影响与单周期设置中残值的影响相同。我们还为多周期问题的分析框架提供了多种扩展（例如交叉销售、内生和相关需求流）。