COVID-19 safe campus evaluation for universities by a hybrid interval type-2 fuzzy decision-making model

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Özet

The fight against the COVID-19 pandemic, which has affected the whole world in recent years and has had devastating effects on all segments of society, has been one of the most important priorities. The Turkish Standards Institution has determined a checklist to contribute to developing safe and clean environments in higher education institutions in Turkey and to follow-up on infection control measures. However, this study is only a checklist that makes it necessary for decision-makers to make a subjective evaluation during the evaluation process, while the need to develop a more effective, systematic framework that takes into account the importance levels of multiple criteria has emerged. Therefore, this study applies the best-worst method under interval type-2 fuzzy set concept (IT2F-BWM) to determine the importance levels of criteria affecting the “COVID-19 safe campus” evaluation of universities in the context of global pandemic. A three-level hierarchy consisting of three main criteria, 11 sub-criteria, and 58 sub-criteria has been created for this aim. Considering the hierarchy, the most important sub-criterion was determined as periodic disinfection. The high contribution of the interval-valued type-2 fuzzy sets in expressing the uncertainty in the decision-makers’ evaluations and the fact that BWM provides criterion weights with a mathematical optimization model that produces less pairwise comparisons and higher consistency are the main factors in choosing this approach. Simple additive weighting (SAW) has also been injected into the IT2F-BWM to determine the safety level of any university campus regarding COVID-19. Thus, decision-makers will be better prepared for the devastating effects of the pandemic by first improving the factors that are relatively important in the fight against the pandemic. In addition, a threshold value will be determined by considering all criteria, and it will prepare the ground for a road map for campuses. A case study is employed to apply the proposed model, and a comparison study is also presented with the Bayesian BWM to validate the results of the criteria weights.

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RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/munzur/3060Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.1007/s11356-022-22796-1Yayıncı resmi DOI adresi
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3
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Tam Kayıt
AlanDeğerDil
dc.contributor.authorBaskak, Dilber
dc.contributor.authorOzbey, Sumeyye
dc.contributor.authorYucesan, Melih
dc.contributor.authorGul, Muhammet
dc.date.accessioned2026-10-28T14:56:10.050709402Z
dc.date.available2026-10-28T14:56:10.050709402Z
dc.date.issued2023
dc.description.abstractThe fight against the COVID-19 pandemic, which has affected the whole world in recent years and has had devastating effects on all segments of society, has been one of the most important priorities. The Turkish Standards Institution has determined a checklist to contribute to developing safe and clean environments in higher education institutions in Turkey and to follow-up on infection control measures. However, this study is only a checklist that makes it necessary for decision-makers to make a subjective evaluation during the evaluation process, while the need to develop a more effective, systematic framework that takes into account the importance levels of multiple criteria has emerged. Therefore, this study applies the best-worst method under interval type-2 fuzzy set concept (IT2F-BWM) to determine the importance levels of criteria affecting the “COVID-19 safe campus” evaluation of universities in the context of global pandemic. A three-level hierarchy consisting of three main criteria, 11 sub-criteria, and 58 sub-criteria has been created for this aim. Considering the hierarchy, the most important sub-criterion was determined as periodic disinfection. The high contribution of the interval-valued type-2 fuzzy sets in expressing the uncertainty in the decision-makers’ evaluations and the fact that BWM provides criterion weights with a mathematical optimization model that produces less pairwise comparisons and higher consistency are the main factors in choosing this approach. Simple additive weighting (SAW) has also been injected into the IT2F-BWM to determine the safety level of any university campus regarding COVID-19. Thus, decision-makers will be better prepared for the devastating effects of the pandemic by first improving the factors that are relatively important in the fight against the pandemic. In addition, a threshold value will be determined by considering all criteria, and it will prepare the ground for a road map for campuses. A case study is employed to apply the proposed model, and a comparison study is also presented with the Bayesian BWM to validate the results of the criteria weights.
dc.identifier.doi10.1007/s11356-022-22796-1
dc.identifier.eissn1614-7499
dc.identifier.endpage8153
dc.identifier.issn0944-1344
dc.identifier.issue3
dc.identifier.pmcidPMC9438885
dc.identifier.pmid36056282
dc.identifier.scopus2-s2.0-85137429615
dc.identifier.startpage8133
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/munzur/3060
dc.identifier.volume30
dc.identifier.wosWOS:000849164900015
dc.language.isoen
dc.publisherSpringer Science and Business Media Deutschland GmbH
dc.relation.ispartofEnvironmental Science and Pollution Research
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectBest-worst method
dc.subjectCOVID-19
dc.subjectInterval type-2 fuzzy set
dc.subjectSafe campus
dc.subject.classificationEnvironmental Sciences
dc.subject.classificationEnvironmental Sciences & Ecology
dc.subject.otherBayes Theorem
dc.subject.otherCOVID-19
dc.subject.otherFuzzy Logic
dc.subject.otherHumans
dc.subject.otherPandemics
dc.subject.otherUniversities
dc.subject.otherTurkey
dc.subject.otherbuilding
dc.subject.otherdecision making
dc.subject.otherdisinfection
dc.subject.otherhigher education
dc.subject.othersafety
dc.subject.otheruniversity sector
dc.subject.otherhuman
dc.subject.otherpandemic
dc.subject.otheruniversity
dc.titleCOVID-19 safe campus evaluation for universities by a hybrid interval type-2 fuzzy decision-making model
dc.typeArticle
rdl.citation.openalex2
rdl.citation.scopus4
rdl.citation.wos3
rdl.departmentFaculty of Health Sciences, Department of Emergency Aid and Disaster Management, Munzur University, Tunceli, Turkey
rdl.departmentSchool of Transportation and Logistics, Istanbul University, 34320, Avcılar-Istanbul, Turkey
rdl.oa.statushybrid
rdl.oa.statusgreen
rdl.oa.urlhttps://link.springer.com/content/pdf/10.1007/s11356-022-22796-1.pdf
rdl.scopus.quartileQ1
rdl.sdgSDG03
rdl.source.indexSCOPUS
rdl.source.indexWOS
rdl.source.indexPUBMED
rdl.wos.indexScience Citation Index Expanded (SCI-EXPANDED)