Abstract
The interaction of a hybrid transshipment policy and customer switching behaviour will exacerbate the complexity of the structure of a hybrid transshipment policy. To cope with this problem, a discrete-time dynamic programming model framework with customer switching behaviour is developed. Based on this framework, we demonstrate that the retailer can obtain more profits with a hybrid transshipment than without one. Next, the existence of a reactive and preventive transshipment policy is shown, respectively. We further analyse the structural property of the holdback policy of reactive transshipment and give the threshold of customer switching rate when always rejecting the request. Meanwhile, a dominant preventive transshipment policy is formulated by which the retailer can control the inventory regardless of the influence of the preventive transshipment policy of the other as long as the inventory is observed by developing an easy-to-implement optimal hybrid transshipment strategy. In addition, the existence of an ordering Nash equilibrium of two retailers is proven. Then, we also illustrate the existence of a transshipment area and analyse the impact of the transshipment cost and switching rate on ordering, the hybrid transshipment policy, and profit by using numerical examples. Finally, we find that the retailer is more willing to adjust inventory by ordering when there is a lower transshipment price and adjust inventory by hybrid transshipment when there is a higher transshipment price.
Highlights
A demanding variety in the categories of perishable products results in a higher uncertainty in the supply and demand for these products
As a remedy to this problem, some retailers attempted to adopt the strategy of reactive transshipment, with an aim to establish a new paradigm, which came to be known as one of “risk pooling.”
We describe a hybrid transshipment policy, which attempts to combine the best features of the two types of transshipment
Summary
A demanding variety in the categories of perishable products results in a higher uncertainty in the supply and demand for these products. Anticipating that some customers may switch from out-of-stock retailers and that retailers with a surplus typically face an inventory rationing decision, we pose the following question: Is it optimal to accept a request as long as there is available inventory, or is it more profitable to deny the request and reserve some inventory to avoid potential future stockouts? Since the profit generated from selling a product to customers is often higher than that from transshipment to another retailer, the retailer with a surplus has an incentive to reserve some inventory for potential switching demand in the future. Proofs for all of our mathematical results are provided in the Appendix
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