Optimal Single-Period Product Allocation Under Uncertain Demand in a Prioritized Multisegment Market for a Monopolistic Retailer

In this article, we consider in the newsvendor context a problem facing a monopolistic retailer who strives to allocate a product optimally under uncertain demand to a prioritized multisegment market. The demand of each market segment is stochastic and depends upon the amount of the product available for allocation to that segment and beyond. The formulated problem is solved using dynamic programming (DP) producing the optimal allocation scheme and monotonically increasing prices charged to different market segments. A numerical experiment is designed and then conducted to examine the effects of simultaneous variations in key model parameters upon the retailer's optimal expected total profit and optimal order quantity available for allocation during the selling season. The importance rankings of the parameters' effects on the above two measures are also investigated. The study finds, among other novel results, that the optimal DP allocation scheme is more profitable, provides broader market coverage, and results in charging lower prices compared with a counterpart utilizing a similar order quantity. The modeling effort is extended to deal with a stochastic model of stock- and price-dependent demand.