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Identification and formation mechanism of key elements of supply chain resilience: Exploration based on grounded theory and verification of SEM

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  • Youan Ke
  • Lin Lu
  • Xiaochun Luo

Abstract

Supply chain resilience has garnered significant attention from both scholars and practitioners. However, the complex nature of the topic has resulted in a dearth of research on its key elements and formation mechanisms. To bridge this knowledge gap, we implemented grounded theory and conducted semi-structured interviews with 23 interviewees, which led to the identification of six key elements of supply chain resilience through open coding, axial coding, selective coding, and theoretical model saturation testing. These elements are product supply resilience, resource resilience, partner resilience, information response resilience, capital resilience, and knowledge resilience. Drawing from the key elements and the three phases of supply chain resilience (readiness, response, and recovery), we illustrated its formation mechanism and constructed a theoretical model of the influencing factors and pathways of supply chain resilience. We devised a questionnaire based on the coding results and confirmed its reasonableness and validity with a small sample of 109 questionnaires. Subsequently, a large sample of 409 questionnaires was used to test and validate the theoretical model using structural equation modeling, demonstrating that the identified key elements positively impact supply chain resilience. In sum, our paper enriches the comprehension of supply chain resilience by identifying its key elements and elaborating on its formation mechanism.

Suggested Citation

  • Youan Ke & Lin Lu & Xiaochun Luo, 2023. "Identification and formation mechanism of key elements of supply chain resilience: Exploration based on grounded theory and verification of SEM," PLOS ONE, Public Library of Science, vol. 18(11), pages 1-30, November.
    • Handle: RePEc:plo:pone00:0293741
    DOI: 10.1371/journal.pone.0293741
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    References listed on IDEAS

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