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Supply Chain Resilience: A Common Weights Efficiency Analysis with Non-discretionary and Non-controllable Inputs

Author

Listed:
  • Reza Kiani Mavi

    (Edith Cowan University)

  • Neda Kiani Mavi

    (Edith Cowan University)

  • Seyed Ashkan Hosseini Shekarabi

    (Edith Cowan University)

  • Matthew Pepper’s

    (University of Wollongong)

  • Sean Arisian

    (La Trobe Business School, La Trobe University)

Abstract

Supply chain resilience (SCRes) as the supply chain network's (SCN) capacity is essential to recover from disruptions. The economic, environmental, and geopolitical regional characteristics of the Pacific region present many challenges and opportunities for building supply chain resilience. This study aims to measure the resilience of supply chains (SCs) considering the characteristics of the network under which they operate. In this study, we proposed a new common set of weights (CSW) model in data envelopment analysis to evaluate the resilience of SCNs. Many external variables beyond decision-makers’ direct control impact SC operations and their resilience. Therefore, the proposed CSW model formulates the non-discretionary and non-controllable inputs in measuring the resilience of SCNs and provides a complete ranking with a higher discrimination power. To improve SCRes, SC managers are recommended to enhance the clustering coefficient and node degree of their SCN by establishing more connections with other SCNs in order to pinpoint the essential capabilities that companies should prioritise in order to develop a stronger and more adaptable SC in the post-COVID-19 pandemic.

Suggested Citation

  • Reza Kiani Mavi & Neda Kiani Mavi & Seyed Ashkan Hosseini Shekarabi & Matthew Pepper’s & Sean Arisian, 2023. "Supply Chain Resilience: A Common Weights Efficiency Analysis with Non-discretionary and Non-controllable Inputs," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 24(1), pages 77-99, December.
    • Handle: RePEc:spr:gjofsm:v:24:y:2023:i:1:d:10.1007_s40171-024-00380-5
    DOI: 10.1007/s40171-024-00380-5
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    1. Seyed Ashkan Zarghami & Jantanee Dumrak, 2024. "Evaluating Vulnerability of Supply Chain Networks to Capacity Reduction," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 25(3), pages 629-646, September.

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    Keywords

    Common weights; Data envelopment analysis; Disruption; Efficiency; Flexibility; Pacific region; Supply chain resilience; Vulnerability;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models

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