Multi-criteria evaluation of medical waste management process under intuitionistic fuzzy environment: A case study on hospitals in Turkey

MakaleAçık Erişim
  • SDG 3 · Sağlık ve Kaliteli Yaşam
  • SDG 12 · Sorumlu Üretim ve Tüketim

Özet

Waste management has come to the fore in the whole world with the increasing impact of the Covid-19 pandemic along with concerns about human health, environmental threats, and socio-economic factors, etc. Medical waste is one of the waste types that need special management processes including particularly collection, storage, separation, and disposal. Healthcare activities create a great amount of medical waste deriving from the hospitals. This study aims to determine the hospital that carries out medical waste management in the most effective way in Erzurum, Turkey. To handle intense uncertainty in the evaluation process, the case is analyzed by Intuitionistic Fuzzy Multi-Criteria Decision-Making (IFMCDM) methods. The present study contributes to the literature by focusing on a real case problem under IF environment in a Group Decision-Making (GDM) framework. Additionally, based on the literature review and expert judgments, the evaluation criteria relevant to the case are defined in this paper. To this end, a four-phased integrated methodology that involves Intuitionistic Fuzzy Weighted Averaging (IFWA), IF Analytical Hierarchy Process (IFAHP), IF Technique for Order Preference by Similarity to Ideal Solution (IFTOPSIS) and One-Dimensional Sensitivity Analysis, is conducted. Firstly, IFWA is aimed to express the significance levels of decision makers (DMs) based on their knowledge, qualifications and experiences. Secondly, IFAHP is used to calculate the importance weights of the decision criteria and IFTOPSIS is preferred to rank the available hospitals. Then, sensitivity analysis is employed to display robustness. According to the results, the most important criteria are Qualified personnel, Health institution infrastructure, and Control of waste, respectively and the most efficient hospital is determined.

Anahtar Kelimeler

RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/gumushane/12820Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.1016/j.seps.2022.101499Yayıncı resmi DOI adresi
Tam Kayıt
AlanDeğerDil
dc.contributor.authorÇelik, Sefa
dc.contributor.authorPeker, İskender
dc.contributor.authorGök-Kısa, A. Cansu
dc.contributor.authorBüyüközkan, Gülçin
dc.date.accessioned2026-10-22T10:20:34.751906934Z
dc.date.available2026-10-22T10:20:34.751906934Z
dc.date.issued2023
dc.description.abstractWaste management has come to the fore in the whole world with the increasing impact of the Covid-19 pandemic along with concerns about human health, environmental threats, and socio-economic factors, etc. Medical waste is one of the waste types that need special management processes including particularly collection, storage, separation, and disposal. Healthcare activities create a great amount of medical waste deriving from the hospitals. This study aims to determine the hospital that carries out medical waste management in the most effective way in Erzurum, Turkey. To handle intense uncertainty in the evaluation process, the case is analyzed by Intuitionistic Fuzzy Multi-Criteria Decision-Making (IFMCDM) methods. The present study contributes to the literature by focusing on a real case problem under IF environment in a Group Decision-Making (GDM) framework. Additionally, based on the literature review and expert judgments, the evaluation criteria relevant to the case are defined in this paper. To this end, a four-phased integrated methodology that involves Intuitionistic Fuzzy Weighted Averaging (IFWA), IF Analytical Hierarchy Process (IFAHP), IF Technique for Order Preference by Similarity to Ideal Solution (IFTOPSIS) and One-Dimensional Sensitivity Analysis, is conducted. Firstly, IFWA is aimed to express the significance levels of decision makers (DMs) based on their knowledge, qualifications and experiences. Secondly, IFAHP is used to calculate the importance weights of the decision criteria and IFTOPSIS is preferred to rank the available hospitals. Then, sensitivity analysis is employed to display robustness. According to the results, the most important criteria are Qualified personnel, Health institution infrastructure, and Control of waste, respectively and the most efficient hospital is determined.
dc.description.sponsorshipInstitut National Polytechnique de Grenoble
dc.description.sponsorshipYükseköğretim Kurulu
dc.identifier.articlenumber101499
dc.identifier.doi10.1016/j.seps.2022.101499
dc.identifier.eissn1873-6041
dc.identifier.issn0038-0121
dc.identifier.pmid36540295
dc.identifier.scopus2-s2.0-85145000709
dc.identifier.startpage101499
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/gumushane/12820
dc.identifier.volume86
dc.identifier.wosWOS:000955340800001
dc.language.isoen
dc.publisherElsevier Ltd
dc.relation.ispartofSocio-Economic Planning Sciences
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectGDM
dc.subjectIFAHP
dc.subjectIFMCDM
dc.subjectIFTOPSIS
dc.subjectMedical waste management
dc.subject.classificationEconomics
dc.subject.classificationManagement
dc.subject.classificationOperations Research & Management Science
dc.subject.classificationBusiness & Economics
dc.subject.otherTurkey
dc.subject.otherfuzzy mathematics
dc.subject.otherhospital sector
dc.subject.othermulticriteria analysis
dc.subject.otherwaste management
dc.titleMulti-criteria evaluation of medical waste management process under intuitionistic fuzzy environment: A case study on hospitals in Turkey
dc.typeArticle
dspace.entity.typePublication
rdl.citation.openalex65
rdl.citation.scopus50
rdl.citation.wos48
rdl.departmentGumushane University, Department of Business Administration, Gümüşhane, Turkey
rdl.oa.statusgreen
rdl.oa.statuspreprint
rdl.oa.urlhttps://www.ncbi.nlm.nih.gov/pmc/articles/9754754
rdl.sdgSDG12
rdl.sdgSDG03
rdl.source.indexSCOPUS
rdl.source.indexWOS
rdl.source.indexPUBMED
rdl.wos.indexScience Citation Index Expanded (SCI-EXPANDED)
rdl.wos.indexSocial Science Citation Index (SSCI)