Inventory Integration with Rational Consumers

Retailers have increasingly pursued initiatives to combine inventory located throughout their enterprise into a single stock from which customers anywhere in their distribution network may purchase. Also known as inventory pooling, this practice is well known to generate operational value by reducing inventory requirements and stock-outs. In “Inventory Integration with Rational Consumers,” Aflaki and Swinney examine a different consequence of pooling: how it influences customer purchasing behavior. They show that integration can lead to behavioral consequences resulting from changing customer purchasing incentives, especially for seasonal goods that are sold in end-of-season clearance sales. These behavioral effects can be negative, and can even outweigh the operational benefits of pooling, if pooling leads to an increase in clearance sale inventory availability that encourages more customers to wait for discounts before buying. Specific conditions that lead to negative (or positive) behavioral value of integration are discussed. Overall, the results illustrate that the ways customers react to inventory pooling can be just as important as its operational consequences.

Sensitivity Analysis of the Optimal Inventory-Pooling Strategies According to Multivariate Demand Dependence

Inventory-pooling (IP) is an effective tool to mitigate demand uncertainty and variability, to reduce operational costs, and consequently to increase the profit. The major assumptions of the previous works in literature on IP include the following: (1) Independents demand, which satisfy the typical normal independent and identically distributed (iid) random variables; (2) dependents (correlated) symmetric demands, which follows to a multivariate normal distribution. The effect of the dependent asymmetric demand is not yet studied. The aim of this paper is to consider this more realistic case. Indeed, the contribution of this paper is twofold. Firstly, it analyzes both the sensitivity of dependence structure and the levels of skewness of distributions on IP policies in terms of optimal total cost and demand satisfaction constraint. Secondly, both symmetric and asymmetric demand distributions are modeled using various beta distribution and the dependance between demands are modeled using various copulas. A newsvendor problem inspired by the literature, with two decentralized locations and two centralized locations, is considered the empirical study. For each dependance situation, three IP models are considered: inventory centralization, regular transshipments, and independent systems. The results suggest divergences in the decisions in about 9% of cases. Bad choice of marginal distributions given that the copula is appropriate can lead to divergences that vary between 2.2% and 4%, depending on whether the demand distributions are symmetric or asymmetric.