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

Mavi, Reza Kiani; Mavi, Neda Kiani; Shekarabi, Seyed Ashkan Hosseini; Pepper’s, Matthew; Asian, Sobhan

doi:10.26181/25287475.v1

1540926_Kiani,M_2023.pdf (632.59 kB)

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

journal contribution

posted on 2024-04-18, 05:54 authored by Reza Kiani Mavi, Neda Kiani Mavi, Seyed Ashkan Hosseini Shekarabi, Matthew Pepper’s, Sobhan AsianSobhan Asian

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.

History

Publication Date

2024-02-24

Journal

Global Journal of Flexible Systems Management

Volume

24

Issue

Suppl 1

Pagination

23p. (p.77-99)

Publisher

Springer Science and Business Media LLC

ISSN

0972-2696

Rights Statement

© The Author(s) 2024. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.