Tailored Supply Chain Decision-Making Under Price-Sensitive Stochastic Demand and Delivery Uncertainty
Management Science, Vol. 51, No. 12, pp. 1873-1891, 2005
19 Pages Posted: 9 Jan 2007
In this paper, we study a serial two-echelon supply chain selling a procure-to-stock product in a price-sensitive market. Our analytical modelling framework incorporates optimal pricing and stocking decisions for both echelons in the presence of stochastic demand and random delivery times. We focus on understanding how these decisions for the chain are affected by its management paradigm (centralized or decentralized), and its business characteristics - price sensitivity, demand uncertainty, and delivery time variability. A novel combination of transformations enables us to analyze the framework and determine the unique optimal choices for centralized and wholesale price-based decentralized supply chains. More detailed investigation reveals that, in general, the business characteristics influence both the behavior and the optimal values of the decision variables, while the management paradigm primarily governs the optimal values. We illustrate the significance of these results in terms of how managers should tailor their decisions to align with their business requirements. Subsequently, comparison of the optimal profits between the channel partners and the management paradigms provides implications for decentralization strategy. A decentralized chain is most inefficient for moderately price-sensitive customers and uncertain environments, but is relatively more effective when dealing with mature products. We propose a contracting scheme that can improve the decentralized chain profit in reliable delivery time settings. The salient modelling insight of this paper is that ignoring the randomness of delivery time trivializes the interaction between pricing and stocking decisions. On the other hand, from a managerial viewpoint, we establish that optimal pricing policies provide the means to increase revenue and also act as strategic tools for tackling uncertainty.
Keywords: pricing, stochastic demand, random delivery times,multiechelon inventory,customized supply
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