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

Majid Azadi (), Zohreh Moghaddas (), Reza Farzipoor Saen (), Angappa Gunasekaran (), Sachin Kumar Mangla () and Alessio Ishizaka ()
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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

Annals of Operations Research, 2023, vol. 328, issue 1, No 5, 107-150

Abstract: 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.

Keywords: COVID-19 pandemic; Healthcare supply chains; Efficiency measurement; Sustainability and resilience; Network data envelopment analysis (NDEA) (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10479-022-05020-8

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