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Analyzing operational risks of digital supply chain transformation using hybrid ISM-MICMAC method

Author

Listed:
  • Aliakbar Hasani

    (Shahrood University of Technology)

  • Gholamreza Haseli

    (School of Engineering and Sciences
    University College Dublin)

  • Muhammet Deveci

    (National Defence University
    University College London
    Lebanese American University)

Abstract

Identifying and prioritizing risks is crucial for the successful digital transformation of a supply chain's key processes without disruption. An organized and comprehensive risk assessment framework will significantly ensure a sustainable transformation to a digital supply chain. In this study, digital transformation risks are identified and prioritized using a hybrid fuzzy multi-criteria decision-making (MCDM) method under uncertainty. Additionally, appropriate risk mitigation strategies for the top-ranked risks are presented, and potential relationships among them are addressed. Initially, potential risks in digital transformation were identified based on expert opinions. A fuzzy hierarchical and analytic network process was then applied to determine the importance of evaluation criteria and the final ranking of potential risks, respectively. Efficient risk mitigation strategies were proposed, and interrelationships among them were assessed using interpretive structural modeling and a matrices impacts croisés multiplication appliquée à un classement (MICMAC) analysis. The results indicate that information technology risk, supply chain management risk, and financial risks are the top three risks in the identified ranking. Furthermore, implementing an integrated data strategy and proposing comprehensive business agreements with supply chain players are considered the most impactful strategies for risks with top ranks.

Suggested Citation

  • Aliakbar Hasani & Gholamreza Haseli & Muhammet Deveci, 2025. "Analyzing operational risks of digital supply chain transformation using hybrid ISM-MICMAC method," OPSEARCH, Springer;Operational Research Society of India, vol. 62(2), pages 583-607, June.
    • Handle: RePEc:spr:opsear:v:62:y:2025:i:2:d:10.1007_s12597-024-00792-y
    DOI: 10.1007/s12597-024-00792-y
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