Abstract

One of the key issues in the current research on supply chain (SC) networks is the need for planning the nature of the inventory policy at each echelon of the SC network structure. Given the inherent uncertainties pervading the operational environment within real-world SC networks, it becomes imperative therefore, for each partnering echelon to focus on its individual inventory review policy from the viewpoint of global optimisation of the overall SC performance. Two key factors contributing to the aforementioned uncertainty are the lead time and their standard deviations, and the extant literature has often advocated the adoption of demand information-sharing between the partnering echelons to mitigate the deleterious impact of these factors on system performance. In this paper, we explicitly focus attention on these factors through their manifestation within two different hypothetical SC networks, and study their impact on the average fill rate performance of the assumed systems with and without demand information-sharing. Towards this end, we develop discrete event simulation models of the hypothetical SC structures and exploit the Taguchi experimental design procedure as a vehicle for conducting the simulation experiments and analysing its outcome. While simulation results highlight the impact of the assumed factors on system-wide performance, the Taguchi paradigm further helps identify appropriate combinations of these factors for optimal fill rate performance. Key results reveal that sharing of demand information between partnering echelons should not automatically be taken for granted as a direction for performance enhancement.

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