Abstract The present study assesses supply chain resilience based on network structural parameters. Resilience is computed as a composite effect of density, centrality, connectivity, and network size of the network. A simulation-based approach is adopted, wherein networks of 23 firms operating in India are subjected to risk combinations of five mutually inclusive independent scenarios of probability levels and five mutually exclusive and exhaustive impact levels. The worst-case performance of the supply chain network when subjected to high impact and low probability risks is captured using conditional-value at risk (CVaR). Results reveal that the firm which has the lowest density and centrality and the highest connectivity and network size, exhibits the highest resilience. Whereas, the firm which has the highest density and high centrality due to an aggregation node exhibits the lowest resilience. The two main contributions of the present study are as follows. First, it derives insights for practicing managers from actual instead of theoretical networks. Second, it captures the worst-case performance of the supply chain network using CVaR, which has not been reported by any study in the supply chain network structure domain. The simulation-based approach can be easily adopted by the managers to assess the resilience of their supply chain networks and their preparedness to face potential risks. The information available in the form of CVaR is an important input to practicing managers to evaluate whether their supply chain network can face severe disruptions or not. The managers can then make informed decisions on how to increase the resilience of their supply chain networks.

中文翻译：

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基于网络结构参数的灾前和灾后供应链弹性评估，以 CVaR 作为风险度量

摘要 本研究基于网络结构参数评估供应链弹性。弹性被计算为网络的密度、中心性、连通性和网络规模的复合效应。采用基于模拟的方法，其中在印度运营的 23 家公司的网络受到五个相互包含的独立概率水平和五个相互排斥和详尽的影响水平的风险组合。当受到高影响和低概率风险时，供应链网络的最坏情况性能是使用条件风险价值 (CVaR) 捕获的。结果表明，具有最低密度和中心性以及最高连通性和网络规模的公司表现出最高的弹性。然而，由于聚合节点而具有最高密度和高中心性的公司表现出最低的弹性。本研究的两个主要贡献如下。首先，它从实际而不是理论网络中为实践管理者提供见解。其次，它使用 CVaR 捕获了供应链网络的最坏情况性能，这在供应链网络结构领域的任何研究中都没有报道过。管理人员可以轻松采用基于模拟的方法来评估其供应链网络的弹性以及他们应对潜在风险的准备情况。以 CVaR 形式提供的信息是实践管理者评估其供应链网络是否会面临严重中断的重要输入。