Article ID: | iaor20171239 |
Volume: | 63 |
Issue: | 4 |
Start Page Number: | 1026 |
End Page Number: | 1041 |
Publication Date: | Mar 2017 |
Journal: | Management Science |
Authors: | Shen Zuo-Jun Max, Lim Michael K, Mak Ho-Yin |
Keywords: | design, combinatorial optimization, decision, demand, location, distribution, simulation |
Strategic supply chain design decisions are critical to the long‐term success of a business. Traditional facility location models for supply chain design focus on the trade‐offs between the costs and benefits of proximity, i.e., the distance between facilities and customers. These strategic‐focused models do not consider the supply chain’s agility, i.e., its ability to quickly respond to unexpected fluctuations in customer needs. In this paper, we study the problem of designing a supply chain distribution network under demand uncertainty and analyze how the optimal design characteristics of proximity and agility depend on various input parameters. We are able to draw managerial insights on how agility considerations may invalidate well‐established and widely accepted qualitative results derived from traditional models. In particular, we show that it is optimal to increase the density of distribution centers (DCs) when the shortage penalty cost increases, and to decrease the density of DCs when a certain unit transportation cost parameter increases. Through these findings, our work conveys the message that traditional, proximity‐based facility location models can be inadequate for designing modern responsive supply chains, and calls for the need to develop a new class of models for the task.