Selection of alternative fuel taxis: A hybridized approach of life cycle sustainability assessment and multi-criteria decision making with neutrosophic sets

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dc.authorid0000-0003-1411-0369
dc.contributor.authorKuşakcı, Ali Osman
dc.contributor.authorKuşakcı, Ali Osman
dc.contributor.authorAboushaqra, Nour N. M.
dc.contributor.authorOnat, Nuri Cihat
dc.contributor.authorKucukvar, Murat
dc.contributor.authorHamouda, A. M. S.
dc.contributor.authorKuşakcı, Ali Osman
dc.contributor.authorAyvaz, Berk
dc.contributor.otherYönetim Bilimleri Fakültesi, İşletme Bölümü
dc.date.accessioned2021-08-01T09:45:52Z
dc.date.available2021-08-01T09:45:52Z
dc.date.issued2021
dc.departmentİHÜ, Yönetim Bilimleri Fakültesi, İşletme Bölümü
dc.description.abstractThis study presents a combined application of hybrid life cycle sustainability assessment and multi-criteria decision-making, aiming to further advance an integrated sustainability assessment and decision-making for the selection of alternative-fuel taxis. First, a multiregional hybrid life cycle sustainability assessment model is built to evaluate macro-level sustainability impacts of various vehicle types: conventional gasoline vehicles, compressed natural gas vehicles, hybrid, and battery electric vehicles. Second, considering the subjective nature of the evaluation process, the intervalvalued neutrosophic sets-based analytic hierarchy process is suggested to assess the results obtained from the life cycle model to determine the weight of each evaluation criterion. Then, the technique for order preference by similarity to the ideal solution is used to rank the sustainability performance. Two different charging scenarios are also tested. The results show that solar-powered BEVs are the best in the environmental impacts with the exceptions of water consumption and land use. Solar-powered BEVs are superior in human health impact, while, ICVs are the best in compensation and employment generations. The ranking results reveal that solar-powered BEVs are the best alternatives when all indicators are considered, followed by CNG vehicles. The proposed method provides a practical and life cycle-based decision-making approach to support and prioritize effective policies for more sustainable transportation.
dc.identifier.citationAboushaqrah, N. N. M., Onat, N. C., Kucukvar, M., Hamouda, A. M. S., Kusakcı, A. O., ve Ayvaz, B. (2021). Selection of alternative fuel taxis: A hybridized approach of life cycle sustainability assessment and multi-criteria decision making with neutrosophic sets. International Journal of Sustainable Transportation.
dc.identifier.doi10.1080/15568318.2021.1943075
dc.identifier.issn1556-8318
dc.identifier.issn1556-8334
dc.identifier.scopus2-s2.0-85111631929
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1080/15568318.2021.1943075
dc.identifier.urihttps://hdl.handle.net/20.500.12154/1532
dc.identifier.wosWOS:000677910600001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakScopus
dc.indekslendigikaynakWeb of Science
dc.institutionauthorKuşakcı, Ali Osman
dc.institutionauthorid0000-0003-1411-0369
dc.language.isoen
dc.publisherTaylor & Francis Online
dc.relation.ihupublicationcategory114
dc.relation.ispartofInternational Journal of Sustainable Transportation
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectElectric Taxis
dc.subjectLife Cycle Sustainability Assessment
dc.subjectMulti-Criteria Decision Making
dc.subjectMulti Region Input–Output Analysis
dc.subjectNeutrosophic Sets
dc.subjectSustainable Transportation
dc.titleSelection of alternative fuel taxis: A hybridized approach of life cycle sustainability assessment and multi-criteria decision making with neutrosophic sets
dc.typeArticle
dspace.entity.typePublication
relation.isAuthorOfPublication21653521-557b-4059-b2be-1fb429b3258a
relation.isAuthorOfPublication.latestForDiscovery21653521-557b-4059-b2be-1fb429b3258a
relation.isOrgUnitOfPublicationc9253b76-6094-4836-ac99-2fcd5392d68f
relation.isOrgUnitOfPublication.latestForDiscoveryc9253b76-6094-4836-ac99-2fcd5392d68f

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