Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/108477
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dc.contributorDepartment of Industrial and Systems Engineering-
dc.creatorJeevaraj, S-
dc.creatorGokasar, I-
dc.creatorDeveci, M-
dc.creatorDelen, D-
dc.creatorZaidan, BB-
dc.creatorWen, X-
dc.creatorShang, WL-
dc.creatorKou, G-
dc.date.accessioned2024-08-19T01:58:39Z-
dc.date.available2024-08-19T01:58:39Z-
dc.identifier.issn0952-1976-
dc.identifier.urihttp://hdl.handle.net/10397/108477-
dc.language.isoenen_US
dc.publisherElsevier Ltden_US
dc.rights© 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication S, J., Gokasar, I., Deveci, M., Delen, D., Zaidan, B. B., Wen, X., Shang, W.-L., & Kou, G. (2023). Adoption of energy consumption in urban mobility considering digital carbon footprint: A two-phase interval-valued Fermatean fuzzy dominance methodology. Engineering Applications of Artificial Intelligence, 126, 106836 is available at https://doi.org/10.1016/j.engappai.2023.106836.en_US
dc.subjectDecision support systemsen_US
dc.subjectDominance methoden_US
dc.subjectGHGsen_US
dc.subjectInterval-valued fermatean fuzzy setsen_US
dc.subjectMulti-criteria decision-makingen_US
dc.subjectUrban mobilityen_US
dc.titleAdoption of energy consumption in urban mobility considering digital carbon footprint : a two-phase interval-valued Fermatean fuzzy dominance methodologyen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume126-
dc.identifier.doi10.1016/j.engappai.2023.106836-
dcterms.abstractInterval-valued Fermatean fuzzy sets play a significant role in modelling decision-making problems with incomplete information more accurately than intuitionistic fuzzy sets. Various decision-making methods have been introduced for the different classes IFSs. In this study, we aim to introduce a novel two-phase interval-valued Fermatean fuzzy dominance method which suits the decision-making problems modelled under the IVFFS environment well and study its applications in the adoption of energy consumption in Urban mobility considering digital carbon footprint. The proposed method considers the importance and performance of one alternative with respect to all others, which is not the case with many available decision-making algorithms introduced in the literature. Transportation is one of the most significant sources of global greenhouse gas (GHG) emissions. Numerous potential remedies are proposed to reduce the quantity of GHG generated by transportation activities, including regulatory measures and public transit digitalization initiatives. Decision-makers, however, should consider the digital carbon footprint of such projects. This study proposes three alternatives for reducing GHG emissions from transportation activities: incremental adoption of digital technologies to reduce energy consumption and greenhouse gases, disruptive digitalization technologies in urban mobility, and redesign of urban mobility using regulatory approaches and economic instruments. The proposed novel two-phase interval-valued Fermatean fuzzy dominance method will be utilized to rank these alternative projects in order of advantage. First, the problem is converted into a multi-criterion group decision-making problem. Then a novel two-phase interval-valued Fermatean fuzzy dominance method is designed and developed to rank the alternatives. The importance and advantage of the proposed two-phase method over other existing methods are discussed by using sensitivity and comparative analysis. The results indicate that rethinking urban mobility through governmental policies and economic tools is the least advantageous choice, while incremental adoption of digital technologies is the most advantageous.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationEngineering applications of artificial intelligence, Nov. 2023, v. 126, 106836-
dcterms.isPartOfEngineering applications of artificial intelligence-
dcterms.issued2023-11-
dc.identifier.scopus2-s2.0-85166251029-
dc.identifier.eissn1873-6769-
dc.identifier.artn106836-
dc.description.validate202408 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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