Demand Management and Inventory Control for Substitutable Products

By Jing-Sheng Song, Zhengliang Xue. 2007

133 citations recorded by the source corpus.

This paper studies dynamic inventory and pricing decisions for a set of substitutable products over a flnite planning horizon. We present a general stochastic, price-dependent demand model that unifles many commonly used demand models in the literature. Unsatisfled demands are backlogged. There are linear purchasing, inventory-holding, and backordering costs. The objective is to maximize the total expected discounted proflt. The original formulation is not jointly concave in the decision variables and is therefore intractable. One key observation here is that the problem becomes jointly concave if we work with the inverse of the price vector { the market share vector. We characterize the optimal policy and develop algorithms to compute it. We establish conditions under which the optimal policy demonstrates certain monotonicity property, which, in turn, can greatly enhance computation. We also analyze the myopic policy and its optimality, and present a numerical study to illustrate the interplay of the pricing and inventory decisions.

Subfields: Computer Networks and Communications, Management Information Systems, Marketing

View Paper: https://www.semanticscholar.org/paper/b7150e54cce21d8658d29bf79277b89a0200252c

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In Computer Networks and Communications

Huseyin Topaloglu

In Management Information Systems

In Marketing

Citations in the corpus

Dynamic Pricing and Inventory Control of Substitute Products (2009, background): “Zhang and Cooper (2006) propose an approximation of the dynamic pricing of multi-substitutableflight problem, which uses a collection of one-flight problems and provides bounds to the optimal revenue.”
Assortment Planning Under the Multinomial Logit Model with Totally Unimodular Constraint Structures (2013, background): “…problems, Hanson and Martin (1996) observe that the expected revenue is not a concave function of prices when customers choose according to MNL, but Song and Xue (2007) and Dong et al. (2009) are able to recover a concave objective function by using the market share of each product as the decision…”
Assortment Optimization Under Variants of the Nested Logit Model (2014, background): “…that the expected revenue function fails to be concave in prices for the multinomial logit model, but significant progress was made by formulating the pricing problem in terms of market shares, as this results in a concave expected revenue function; see Song and Xue (2007) and Dong et al. (2009).”