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Gresilient supplier selection through Fuzzy Ordinal Priority Approach: decision-making in post-COVID era

Author

Listed:
  • Amin Mahmoudi

    (Southeast University)

  • Saad Ahmed Javed

    (Nanjing University of Information Science and Technology)

  • Abbas Mardani

    (University of South Florida)

Abstract

Because of the COVID-19 outbreak, the supply of both essential and non-essential goods and services has been unprecedentedly disrupted. In the absence of any playbook, the need for innovative technologies to aid recovery from the Supply Chain (SC) disruptions quickly and effectively becomes persistent. The study aims to develop an innovative decision-making technology to handle the supplier selection problems arising from the frequent impreciseness and incompleteness in the nowadays' SC reports within the framework of the gresilient supply chain management. Through the integration of green and resilience aspects of the SCs, the supply chain 'gresilience' has been conceptualized. In light of this construct and based on the data collected from a manufacturing firm, the study deploys a two-fold decomposition of the core algorithm of the Ordinal Priority Approach (OPA), one for attributes and other for alternatives. It extends the OPA to the Fuzzy OPA (OPA-F) for solving the supplier selection problems. The study illustrates how green and resilience aspects of the SC can be integrated to better understand the gresilient suppliers in the wake of the SC disruptions. A novel construct of SC Gresilience is also furnished along with a novel definition of SC Gresilience. It also provides an innovative SC decision-making technology to help procurement managers to evaluate their suppliers. The resultant framework can help them better prepare for the COVID-19 like disruptions in the future.

Suggested Citation

  • Amin Mahmoudi & Saad Ahmed Javed & Abbas Mardani, 2022. "Gresilient supplier selection through Fuzzy Ordinal Priority Approach: decision-making in post-COVID era," Operations Management Research, Springer, vol. 15(1), pages 208-232, June.
    • Handle: RePEc:spr:opmare:v:15:y:2022:i:1:d:10.1007_s12063-021-00178-z
    DOI: 10.1007/s12063-021-00178-z
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    Cited by:

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    3. Mohammad Aqil Sahil & Meenakshi Kaushal & Q. M. Danish Lohani, 2025. "A Novel Pythagorean Approach Based Sine-Shaped Fuzzy Data Envelopment Analysis Model: An Assessment of Indian Public Sector Banks," Computational Economics, Springer;Society for Computational Economics, vol. 65(3), pages 1373-1395, March.
    4. Lijing Shang & Saiful Aman & Abdulkhabir Rahmat, 2025. "An Evaluation to the Global Supply Chain Security Evidence from China’s High-End Manufacturing Sector," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(1), pages 2204-2221, January.
    5. Kamar Zekhnini & Abla Chaouni Benabdellah & Anass Cherrafi, 2024. "A multi-agent based big data analytics system for viable supplier selection," Journal of Intelligent Manufacturing, Springer, vol. 35(8), pages 3753-3773, December.

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