Supply network disruption and resilience: A network structural perspective

概念化 节点(物理) 弹性(材料科学) 供应网络 网络分析 编队网络 业务 计算机科学 网络理论 风险分析(工程) 计算机网络 工程类 人工智能 数学 统计 热力学 电气工程 物理 万维网 结构工程 功率(物理) 量子力学
作者
Yusoon Kim,Yi‐Su Chen,Kevin Linderman
出处
期刊:Journal of Operations Management [Wiley]
卷期号:33-34 (1): 43-59 被引量:711
标识
DOI:10.1016/j.jom.2014.10.006
摘要

Abstract Increasingly, scholars recognize the importance of understanding supply network disruptions . However, the literature still lacks a clear conceptualization of a network‐level understanding of supply disruptions. Not having a network level understanding of supply disruptions prevents firms from fully mitigating the negative effects of a supply disruption. Graph theory helps to conceptualize a supply network and differentiate between disruptions at the node/arc level vs. network level. The structure of a supply network consists of a collection of nodes (facilities) and the connecting arcs (transportation). From this perspective, small events that disrupt a node or arc in the network can have major consequences for the network. A failure in a node or arc can potentially stop the flow of material across network. This study conceptualizes supply network disruption and resilience by examining the structural relationships among entities in the network. We compare four fundamental supply network structures to help understand supply network disruption and resilience. The analysis shows that node/arc‐level disruptions do not necessarily lead to network‐level disruptions, and demonstrates the importance of differentiating a node/arc disruption vs. a network disruption. The results also indicate that network structure significantly determines the likelihood of disruption. In general, different structural relationships among network entities have different levels of resilience. More specifically, resilience improves when the structural relationships in a network follow the power‐law . This paper not only offers a new perspective of supply network disruption, but also suggests a useful analytical approach to assessing supply network structures for resilience.
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