A new rough ordinal priority-based decision support system for purchasing electric vehicles

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dc.authoridErdogan, Nuh/0000-0003-1621-2748
dc.authoridDeveci, Muhammet/0000-0002-3712-976X
dc.authoridPamucar, Dragan/0000-0001-8522-1942
dc.authoridDelen, Dursun/0000-0001-8857-5148
dc.authorwosidErdogan, Nuh/GRS-9451-2022
dc.authorwosidDeveci, Muhammet/V-8347-2017
dc.authorwosidPamucar, Dragan/AAG-8288-2019
dc.authorwosidDelen, Dursun/AGA-9892-2022
dc.contributor.authorKucuksari, Sadik
dc.contributor.authorPamucar, Dragan
dc.contributor.authorDeveci, Muhammet
dc.contributor.authorErdogan, Nuh
dc.contributor.authorDelen, Dursun
dc.date.accessioned2024-05-19T14:39:31Z
dc.date.available2024-05-19T14:39:31Z
dc.date.issued2023
dc.departmentİstinye Üniversitesien_US
dc.description.abstractThis study proposes a novel multi-criteria decision-making (MCDM) model based on a rough extension of the Ordinal Priority Approach (OPA) to determine the order of importance of users' perspectives on Electric Vehicle (EV) purchases. Unlike conventional methods that rely on predefined ranks for criteria weighting coefficients, the proposed rough OPA method employs an aggregated rough linguistic matrix, enabling a more precise and unbiased calculation of interval values. Moreover, the model addresses inherent uncertainties by incorporating nonlinear aggregation functions, accommodating decision makers' risk attitudes for flexible decision -making. To validate the model's efficacy, a large-scale post-EV test drive survey is conducted, enabling the determination of relative criterion importance. Sensitivity analysis confirms the robustness of the model, demonstrating that marginal changes in parameters do not alter the ranking order. The results unveil the significance of the reliability criterion and reveal that vehicle-related characteristics outweigh economic and environmental attributes in the decision -making process. Overall, this innovative MCDM model contributes to a more accurate and objective analysis, enhancing the understanding of users' preferences and supporting informed decision-making in EV purchases.en_US
dc.identifier.doi10.1016/j.ins.2023.119443
dc.identifier.issn0020-0255
dc.identifier.issn1872-6291
dc.identifier.scopus2-s2.0-85167968871en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org10.1016/j.ins.2023.119443
dc.identifier.urihttps://hdl.handle.net/20.500.12713/4798
dc.identifier.volume647en_US
dc.identifier.wosWOS:001062190500001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevier Science Incen_US
dc.relation.ispartofInformation Sciencesen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.snmz20240519_kaen_US
dc.subjectBonferroni Functionen_US
dc.subjectDecision Support Systemsen_US
dc.subjectElectric Mobilityen_US
dc.subjectElectric Vehicle Adoptionen_US
dc.subjectMulti-Criteria Decision-Makingen_US
dc.subjectRough Numbersen_US
dc.titleA new rough ordinal priority-based decision support system for purchasing electric vehiclesen_US
dc.typeArticleen_US

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