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A Bayesian BWM and VIKOR-based model for assessing hospital preparedness in the face of disasters

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  • Halit Serdar Saner

    (Munzur University)

  • Melih Yucesan

    (Munzur University)

  • Muhammet Gul

    (Munzur University)

Abstract

Hospitals are the first point of contact for people in the face of disasters that interfere with the daily functioning of life and endanger health and social life. All preparations should be made considering the worst possible conditions and the provided service should continue without interruption. In this study, a multi-criteria decision-making model was developed to evaluate disaster preparedness of hospitals. This decision model includes Bayesian best–worst method (BBWM), the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and technique for order preference by similarity to ideal solution (TOPSIS) methods. With the proposed decision model, six main criteria and 34 sub-criteria related to disaster preparedness of hospitals were considered. The criteria and sub-criteria evaluated in pairwise comparison manner by the experts were weighted with BBWM. These weight values and the data obtained from the six Turkish hospitals were combined to provide inputs for VIKOR and TOPSIS. In addition, a comparative study and sensitivity analysis were carried out using weight vectors obtained by different tools. BBWM application results show that the “Personnel” criterion was determined as the most important criterion with an importance value of 26%. This criterion is followed by “Equipment” with 25%, “Transportation” with 14%, “Hospital building” and “Communication” with 12%, and “Flexibility” with 11%. Hospital-2 was determined as the most prepared hospital for disasters as a result of VIKOR application. The VIKOR Q value of this hospital was obtained as 0.000. According to the results of the comparative study, Hospital-2 was determined as the most disaster-ready hospital in all six different scenarios. This hospital is followed by Hospital-4 (Q = 0.5661) and Hospital-5 (Q = 0.7464). The remaining rankings were Hospital-6, Hospital-3 and Hospital-1. The solidity of the results was checked with TOPSIS. Based on TOPSIS application results, Hospital-2 was again found the most-ready hospital. The usage of BBWM in this study enabled the expert group’s views to be combined without loss of information and to determine the criteria and sub-criteria weights with less pairwise comparisons in a probabilistic perspective. Via the “Credal ranking”, which is the contribution of BBWM to the literature, the interpretation of the hierarchy between each criterion has been performed more precisely.

Suggested Citation

  • Halit Serdar Saner & Melih Yucesan & Muhammet Gul, 2022. "A Bayesian BWM and VIKOR-based model for assessing hospital preparedness in the face of disasters," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(2), pages 1603-1635, March.
    • Handle: RePEc:spr:nathaz:v:111:y:2022:i:2:d:10.1007_s11069-021-05108-7
    DOI: 10.1007/s11069-021-05108-7
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    References listed on IDEAS

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    1. Yi, Pengfei & George, Santhosh K. & Paul, Jomon Aliyas & Lin, Li, 2010. "Hospital capacity planning for disaster emergency management," Socio-Economic Planning Sciences, Elsevier, vol. 44(3), pages 151-160, September.
    2. Wan-Chi Jackie Hsu & Huai-Wei Lo & Chin-Cheng Yang, 2021. "The Formulation of Epidemic Prevention Work of COVID-19 for Colleges and Universities: Priorities and Recommendations," Sustainability, MDPI, vol. 13(4), pages 1-19, February.
    3. 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.
    4. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    5. Muhammet Gul & Melih Yucesan, 2021. "Hospital Preparedness Assessment against COVID-19 Pandemic: A Case Study in Turkish Tertiary Healthcare Services," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-18, January.
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    Cited by:

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    2. Göçmen Polat, Elifcan & Yücesan, Melih & Gül, Muhammet, 2023. "A comparative framework for criticality assessment of strategic raw materials in Turkey," Resources Policy, Elsevier, vol. 82(C).

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