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

MakaleAçık ErişimScopus SJRQ1
  • SDG 3 · Sağlık ve Kaliteli Yaşam

Özet

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.

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RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/munzur/2998Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.1007/s11069-021-05108-7Yayıncı resmi DOI adresi
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48
WoS
37
OpenAlex
51
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Tam Kayıt
AlanDeğerDil
dc.contributor.authorSaner, Halit Serdar
dc.contributor.authorYucesan, Melih
dc.contributor.authorGul, Muhammet
dc.date.accessioned2026-10-28T14:56:05.340503522Z
dc.date.available2026-10-28T14:56:05.340503522Z
dc.date.issued2022
dc.description.abstractHospitals 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.
dc.identifier.doi10.1007/s11069-021-05108-7
dc.identifier.eissn1573-0840
dc.identifier.endpage1635
dc.identifier.issn0921-030X
dc.identifier.issue2
dc.identifier.pmcidPMC8593641
dc.identifier.pmid34803219
dc.identifier.scopus2-s2.0-85119042094
dc.identifier.startpage1603
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/munzur/2998
dc.identifier.volume111
dc.identifier.wosWOS:000719242600004
dc.language.isoen
dc.publisherSpringer Science and Business Media B.V.
dc.relation.ispartofNatural Hazards
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectBayesian best–worst method
dc.subjectCredal ranking
dc.subjectHospital disaster preparedness
dc.subjectTOPSIS
dc.subjectVIKOR
dc.subject.classificationGeosciences, Multidisciplinary
dc.subject.classificationMeteorology & Atmospheric Sciences
dc.subject.classificationWater Resources
dc.subject.classificationGeology
dc.subject.otherBayesian analysis
dc.subject.otherdecision making
dc.subject.otherdisaster management
dc.subject.othermodeling
dc.subject.otheroptimization
dc.titleA Bayesian BWM and VIKOR-based model for assessing hospital preparedness in the face of disasters
dc.typeArticle
rdl.citation.openalex51
rdl.citation.scopus48
rdl.citation.wos37
rdl.departmentDepartment of Engineering Management, Munzur University, 62000 Tunceli, Turkey
rdl.departmentDepartment of Emergency Aid and Disaster Management, Munzur University, 62000 Tunceli, Turkey
rdl.oa.statusbronze
rdl.oa.statusgreen
rdl.oa.urlhttps://link.springer.com/content/pdf/10.1007/s11069-021-05108-7.pdf
rdl.scopus.quartileQ1
rdl.sdgSDG03
rdl.source.indexSCOPUS
rdl.source.indexWOS
rdl.source.indexPUBMED
rdl.wos.indexScience Citation Index Expanded (SCI-EXPANDED)