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An integrated hybrid MCDM approach to evaluate countries’ COVID-19 risks

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  • Mete, Suleyman
  • Yucesan, Melih
  • Gul, Muhammet
  • Ozceylan, Eren

Abstract

To enable planning and early reaction efforts, it is important to identify the nations most at risk from COVID-19's health and humanitarian effects, which could exceed present national response capabilities. INFORM COVID-19 Risk Index developed by European Commission is one of the initiatives to meet the aforementioned need. However, the Index has 40 conflicting and comprehensive indicators (e.g., health system capacity, hygiene, vulnerability) and different countries that lead to a need for multicriteria decision-making (MCDM) approaches. This paper offers an integrated MCDM approach with two phases to re-assess the countries' COVID-19 risks based on INFORM COVID-19 Risk Index. In the first phase, the 40 indicators are prioritized using the Entropy-based multi-choice best-worst method (MC-BWM) to provide multiple viewpoints for the preferences values. In the second phase, 29 countries from different geographical regions are ranked using the COPRAS (Complex Proportional Assessment) method. Applying these three methods together on the COVID-19 risk assessment of countries is the most significant novelty for the relevant literature. The proposed approach has undergone a thorough comparative evaluation with the released INFORM COVID-19 Risk Index, and recommendations are provided based on different scenario analyses.

Suggested Citation

  • Mete, Suleyman & Yucesan, Melih & Gul, Muhammet & Ozceylan, Eren, 2023. "An integrated hybrid MCDM approach to evaluate countries’ COVID-19 risks," Socio-Economic Planning Sciences, Elsevier, vol. 90(C).
    • Handle: RePEc:eee:soceps:v:90:y:2023:i:c:s0038012123002562
    DOI: 10.1016/j.seps.2023.101744
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    References listed on IDEAS

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    1. Melih Yucesan & Suleyman Mete & Faruk Serin & Erkan Celik & Muhammet Gul, 2019. "An Integrated Best-Worst and Interval Type-2 Fuzzy TOPSIS Methodology for Green Supplier Selection," Mathematics, MDPI, vol. 7(2), pages 1-19, February.
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    5. Kumar, Anish & Mangla, Sachin Kumar & Kumar, Pradeep & Song, Malin, 2021. "Mitigate risks in perishable food supply chains: Learning from COVID-19," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    6. Rezaei, Jafar & Hemmes, Alexander & Tavasszy, Lori, 2017. "Multi-criteria decision-making for complex bundling configurations in surface transportation of air freight," Journal of Air Transport Management, Elsevier, vol. 61(C), pages 95-105.
    7. Opricovic, Serafim & Tzeng, Gwo-Hshiung, 2004. "Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS," European Journal of Operational Research, Elsevier, vol. 156(2), pages 445-455, July.
    8. Jarosław Brodny & Magdalena Tutak, 2021. "Assessing the level of digital maturity of enterprises in the Central and Eastern European countries using the MCDM and Shannon’s entropy methods," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-38, July.
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    1. Kara, Karahan & Yalçın, Galip Cihan & Simic, Vladimir & Baysal, Zeynep & Pamucar, Dragan, 2024. "The alternative ranking using two-step logarithmic normalization method for benchmarking the supply chain performance of countries," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).

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