| dc.description.abstract | 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-fromstore 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-fromstore 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. | en_US |
