Evaluation of public transportation systems for sustainable cities using an integrated fuzzy multi-criteria group decision-making model

dc.contributor.authorGörçün, Ömer Faruk
dc.contributor.authorGorcun, Omer Faruk
dc.contributor.authorGarg, Chandra Prakash
dc.contributor.authorKucukonder, Hande
dc.contributor.authorCanakcioglu, Mustafa
dc.date.accessioned2023-10-19T15:12:37Z
dc.date.available2023-10-19T15:12:37Z
dc.date.issued2023
dc.department-temp[Kundu, Pradip] XIM Univ, Sch Comp Sci & Engn, Bhubaneswar, India; [Gorcun, Omer Faruk] Kadir Has Univ, Dept Int Logist & Trade, Cibali Av Kadir Has St Fatih, TR-34083 Istanbul, Turkiye; [Garg, Chandra Prakash] Indian Inst Management Rohtak, Dept Operat Management, Rohtak 124010, Haryana, India; [Kucukonder, Hande] Bartin Univ, Fac Econ & Adm Sci, Dept Numer Methods, Bartin, Turkiye; [Canakcioglu, Mustafa] Kadir Has Univ, Dept Accounting & Finance, Cibali Av Kadir Has St Fatih, TR-34083 Istanbul, Turkiyeen_US
dc.description.abstractIn this era of increasing demand for mobility and rapid urban growth, there is a pressing need for a public transit system that is safe, fast, reliable, well-connected, and sustainable. Furthermore, it is essential to reduce the external costs associated with urban transportation, including environmental pollution, noise, congestion, and accidents, to foster sustainable cities. Choosing the right urban transportation system can meet this goal, but it is not an accessible business for decision-makers in the face of several conflicting criteria and ambiguities in the evaluation process. To cope with this, the current paper suggests a multi-criteria group decision-making (MCGDM) framework consisting of fuzzy BWM (Best-Worst method) and fuzzy MAIRCIA (Multi-Attribute Ideal-Real Comparative Analysis) techniques. This extended MCGDM approach has been applied to evaluate six urban transport systems, namely, Trams, Light Rail Trams, Metro (Subway), Bus Rapid Transport, Commuter Trains, and Public Buses based on 11 selection criteria which we have determined after consultation with highly experienced professionals. The fuzzy BWM technique is employed to identify the weights of the criteria. The fuzzy MAIRCA technique is utilized for ranking the alternatives using the calculated weights of the criteria. The proposed approach's validation has been examined with an extensive robustness check. The study is conducted from a general perspective, i.e., not restricted to a particular city. However, with the identified selection criteria, the proposed decision-making procedure can be repeated for a specific city considering any specific requirements, constraints, or limitations of that city.en_US
dc.identifier.citation3
dc.identifier.doi10.1007/s10668-023-03776en_US
dc.identifier.issn1387-585X
dc.identifier.issn1573-2975
dc.identifier.scopus2-s2.0-85169040986en_US
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1007/s10668-023-03776
dc.identifier.urihttps://hdl.handle.net/20.500.12469/5494
dc.identifier.wosWOS:001060666400004en_US
dc.identifier.wosqualityN/A
dc.khas20231019-WoSen_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofEnvironment Development and Sustainabilityen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMcdm ApproachEn_Us
dc.subjectSelectionEn_Us
dc.subjectStrategiesEn_Us
dc.subjectFrameworkEn_Us
dc.subjectProjectsEn_Us
dc.subjectMobilityEn_Us
dc.subjectDistanceEn_Us
dc.subjectSupportEn_Us
dc.subjectTopsisEn_Us
dc.subjectMcdm Approach
dc.subjectSelection
dc.subjectStrategies
dc.subjectFramework
dc.subjectProjects
dc.subjectMobility
dc.subjectPublic transport systemsen_US
dc.subjectDistance
dc.subjectMulti-criteria group decision-makingen_US
dc.subjectSupport
dc.subjectUrban transportationen_US
dc.subjectTopsis
dc.subjectSustainabilityen_US
dc.titleEvaluation of public transportation systems for sustainable cities using an integrated fuzzy multi-criteria group decision-making modelen_US
dc.typeArticleen_US
dspace.entity.typePublication
relation.isAuthorOfPublication4d0f6004-dbe4-4e79-befd-457af3bb133f
relation.isAuthorOfPublication.latestForDiscovery4d0f6004-dbe4-4e79-befd-457af3bb133f

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