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Evaluating Resiliency of Supply Chain Network: A Data Envelopment Analysis Approach

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  • Pourya Pourhejazy

    (Graduate School of Logistics, INHA University, Incheon 22212, Korea
    LAMIH UMR CNRS 8201, UVHC, Le Mont Houy, 59313 Valenciennes Cedex 9, France)

  • Oh Kyoung Kwon

    (Graduate School of Logistics, INHA University, Incheon 22212, Korea)

  • Young-Tae Chang

    (Graduate School of Logistics, INHA University, Incheon 22212, Korea)

  • Hyosoo (Kevin) Park

    (Graduate School of Logistics, INHA University, Incheon 22212, Korea)

Abstract

Supply chains can be vulnerable to sudden disruptions, especially when it emphasizes efficient operation. In this regard, supply chain resilience (SCR) has received attention recently to cope with disruptions and improve competitiveness. This paper presents a novel methodology to measure resilience between different configurations of a supply chain network (SCN), based on a number of influential factors. For this reason, data envelopment analysis (DEA) is employed to identify the best-practice and less-performing SCN configurations among a group of alternatives. On this basis, the extent to which a current configuration can improve its resiliency is also measured. The methodology is applied to the case of E1, a liquefied petroleum gas (LPG) company in Korea. Topological and operational measures were used as variables to assess resilience. The results suggest that the LPG supply chain in the case study requires an addition in the number and capacity of supply nodes in its network.

Suggested Citation

  • Pourya Pourhejazy & Oh Kyoung Kwon & Young-Tae Chang & Hyosoo (Kevin) Park, 2017. "Evaluating Resiliency of Supply Chain Network: A Data Envelopment Analysis Approach," Sustainability, MDPI, vol. 9(2), pages 1-19, February.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:2:p:255-:d:90085
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    5. Pourya Pourhejazy, 2020. "Destruction Decisions for Managing Excess Inventory in E-Commerce Logistics," Sustainability, MDPI, vol. 12(20), pages 1-12, October.
    6. Maureen S. Golan & Laura H. Jernegan & Igor Linkov, 2020. "Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic," Environment Systems and Decisions, Springer, vol. 40(2), pages 222-243, June.
    7. Sebastian Lozano & Belarmino Adenso-Diaz, 2018. "Network DEA-based biobjective optimization of product flows in a supply chain," Annals of Operations Research, Springer, vol. 264(1), pages 307-323, May.
    8. Shashi & Piera Centobelli & Roberto Cerchione & Myriam Ertz, 2020. "Managing supply chain resilience to pursue business and environmental strategies," Business Strategy and the Environment, Wiley Blackwell, vol. 29(3), pages 1215-1246, March.
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    11. Lijuan Huang & Guojie Xie & John Blenkinsopp & Raoyi Huang & Hou Bin, 2020. "Crowdsourcing for Sustainable Urban Logistics: Exploring the Factors Influencing Crowd Workers’ Participative Behavior," Sustainability, MDPI, vol. 12(8), pages 1-20, April.
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