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A hybrid Z-number data envelopment analysis and neural network for assessment of supply chain resilience: a case study

Author

Listed:
  • Reza Yazdanparast

    (University of Tehran)

  • Reza Tavakkoli-Moghaddam

    (University of Tehran
    Arts et Métiers ParisTech, LCFC)

  • Razieh Heidari

    (University of Tehran)

  • Leyla Aliabadi

    (University of Tehran)

Abstract

Today’s complex supply chains are increasingly susceptible to the turbulent and fast-changing business environment and their economic implications. Resilience as an effective strategic planning during disturbances is a way to mitigate supply chain vulnerabilities. After reviewing the literature on the topic of a resilient supply chain, this paper extracts a complete series of 16 resilience enablers. These identified enablers form the foundation of a questionnaire distributed among over 150 experts and staffs of a real case associated with an Iranian automotive supply chain. The reliability and validity of the questionnaire are evaluated by statistical tests and Cronbach’s alpha. Then, a hybrid of the Z-number data envelopment analysis and neural network is employed for the efficiency score calculation, separately. Finally, the associated results are combined and the final efficiency scores are obtained. The case study findings indicate that by improving the resilience enablers, especially ones with the greatest influence on the supply chain performance, firms can be less vulnerable in times of supply chain disruptions. The framework proposed in this study may find a broad practical application in all types of supply chains.

Suggested Citation

  • Reza Yazdanparast & Reza Tavakkoli-Moghaddam & Razieh Heidari & Leyla Aliabadi, 2021. "A hybrid Z-number data envelopment analysis and neural network for assessment of supply chain resilience: a case study," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(2), pages 611-631, June.
    • Handle: RePEc:spr:cejnor:v:29:y:2021:i:2:d:10.1007_s10100-018-0596-x
    DOI: 10.1007/s10100-018-0596-x
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    Cited by:

    1. María Arquer & Borja Ponte & Raúl Pino, 2022. "Examining the balance between efficiency and resilience in closed-loop supply chains," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(4), pages 1307-1336, December.
    2. Jiakuan Chen & Haoyu Wen, 2023. "The application of complex network theory for resilience improvement of knowledge-intensive supply chains," Operations Management Research, Springer, vol. 16(3), pages 1140-1161, September.
    3. Xiaohong Yu & Wengao Lou, 2023. "An Exploration of Prediction Performance Based on Projection Pursuit Regression in Conjunction with Data Envelopment Analysis: A Comparison with Artificial Neural Networks and Support Vector Regressio," Mathematics, MDPI, vol. 11(23), pages 1-29, November.
    4. Yazdanparast, R. & Jolai, F. & Pishvaee, M.S. & Keramati, A., 2022. "A resilient drop-in biofuel supply chain integrated with existing petroleum infrastructure: Toward more sustainable transport fuel solutions," Renewable Energy, Elsevier, vol. 184(C), pages 799-819.
    5. Zohreh Sadeghi & Reza Farzipoor Saen & Mahdi Moradzadehfard, 2022. "RETRACTED ARTICLE: Developing a network data envelopment analysis model for appraising sustainable supply chains: a sustainability accounting approach," Operations Management Research, Springer, vol. 15(3), pages 809-824, December.
    6. Gaurav Kumar Badhotiya & Gunjan Soni & Vipul Jain & Rohit Joshi & Sameer Mittal, 2022. "Assessing supply chain resilience to the outbreak of COVID-19 in Indian manufacturing firms," Operations Management Research, Springer, vol. 15(3), pages 1161-1180, December.
    7. Bhavya Sharma & Murari Lal Mittal & Gunjan Soni & Bharti Ramtiyal, 2023. "An Implementation Framework for Resiliency Assessment in a Supply Chain," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 24(4), pages 591-614, December.

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