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Using network data envelopment analysis to assess the sustainability and resilience of healthcare supply chains in response to the COVID-19 pandemic

Author

Listed:
  • Majid Azadi

    (Deakin University)

  • Zohreh Moghaddas

    (Islamic Azad University)

  • Reza Farzipoor Saen

    (Sultan Qaboos University)

  • Angappa Gunasekaran

    (Penn State Harrisburg)

  • Sachin Kumar Mangla

    (O P Jindal Global University)

  • Alessio Ishizaka

    (NEOMA Business School)

Abstract

The widespread outbreak of a new Coronavirus (COVID-19) strain has reminded the world of the destructive effects of pandemic and epidemic diseases. Pandemic outbreaks such as COVID-19 are considered a type of risk to supply chains (SCs) affecting SC performance. Healthcare SC performance can be assessed using advanced Management Science (MS) and Operations Research (OR) approaches to improve the efficiency of existing healthcare systems when confronted by pandemic outbreaks such as COVID-19 and Influenza. This paper intends to develop a novel network range directional measure (RDM) approach for evaluating the sustainability and resilience of healthcare SCs in response to the COVID-19 pandemic outbreak. First, we propose a non-radial network RDM method in the presence of negative data. Then, the model is extended to deal with the different types of data such as ratio, integer, undesirable, and zero in efficiency measurement of sustainable and resilient healthcare SCs. To mitigate conditions of uncertainty in performance evaluation results, we use chance-constrained programming (CCP) for the developed model. The proposed approach suggests how to improve the efficiency of healthcare SCs. We present a case study, along with managerial implications, demonstrating the applicability and usefulness of the proposed model. The results show how well our proposed model can assess the sustainability and resilience of healthcare supply chains in the presence of dissimilar types of data and how, under different conditions, the efficiency of decision-making units (DMUs) changes.

Suggested Citation

  • Majid Azadi & Zohreh Moghaddas & Reza Farzipoor Saen & Angappa Gunasekaran & Sachin Kumar Mangla & Alessio Ishizaka, 2023. "Using network data envelopment analysis to assess the sustainability and resilience of healthcare supply chains in response to the COVID-19 pandemic," Annals of Operations Research, Springer, vol. 328(1), pages 107-150, September.
    • Handle: RePEc:spr:annopr:v:328:y:2023:i:1:d:10.1007_s10479-022-05020-8
    DOI: 10.1007/s10479-022-05020-8
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