The COVID-19 pandemic and the performance of healthcare supply chains

Majid Azadi, T. C.E. Cheng, Reza Kazemi Matin, Reza Farzipoor Saen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Recent pandemic outbreaks, including the COVID-19 and SARS, have revealed that supply chains (SCs) are unable to respond to such disasters. To mitigate the destructive impacts and improve the performance of SCs, Operations Research (OR) techniques have been applied to address the issues over the last two decades. The objective of this paper is to develop a network data envelopment analysis (NDEA) model to measure the resilience and sustainability of healthcare SCs in response to the COVID-19 pandemic outbreak. In the proposed NDEA model, for the first time, outputs’ weak disposability, chance-constrained programming (CCP), the convexity assumption, and the semi-oriented radial approach are aggregated. Moreover, a modified directional distance function (DDF) measure is developed to measure the overall and divisional efficiency scores. Furthermore, the proposed model can deal with different types of data such as integer-valued data, negative data, stochastic data, ratio data, and undesirable outputs. Also, several useful and interesting properties of the novel efficiency measure are presented. Finally, we measure the performance of 28 healthcare SCs to demonstrate the applicability and capability of our proposed approach.

Original languageEnglish
JournalAnnals of Operations Research
Early online date19 Jul 2023
Publication statusE-pub ahead of print - 19 Jul 2023

Bibliographical note

Copyright © Springer Science+Business Media, LLC, part of Springer Nature, 2023. This version of the article has been accepted for publication, after peer review and is subject to Springer Nature’s AM terms of use [], but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at:


  • COVID-19
  • Data envelopment analysis (DEA)
  • Healthcare supply chains
  • Network data envelopment analysis (NDEA)
  • Resilience and sustainability


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