Assessment of pre and post-disaster supply chain resilience based on network structural parameters with CVaR as a risk measure

Vijaya Dixit, Priyanka Verma and Manoj Kumar Tiwari

International Journal of Production Economics, 2020, vol. 227, issue C

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.

Keywords: Centrality; Connectivity; Conditional-value at risk; Density; Network size; Supply chain network resilience (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (27)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:proeco:v:227:y:2020:i:c:s0925527320300517

DOI: 10.1016/j.ijpe.2020.107655

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