EVALUATING LOGISTICS VILLAGES IN TURKEY USING HYBRID IMPROVED FUZZY SWARA (IMF SWARA) AND FUZZY MABAC TECHNIQUES

dc.authorwosidZolfani, Sarfaraz Hashemkhani/AAA-9918-2021
dc.authorwosidGorcun, Omer Faruk/ADF-0541-2022
dc.contributor.authorGörçün, Ömer Faruk
dc.contributor.authorGorcun, Omer Faruk
dc.contributor.authorKucukonder, Hande
dc.date.accessioned2023-10-19T15:13:01Z
dc.date.available2023-10-19T15:13:01Z
dc.date.issued2021
dc.department-temp[Hashemkhani Zolfani, Sarfaraz] Univ Catolica Norte, Sch Engn, Larrondo 1281, Coquimbo, Chile; [Gorcun, Omer Faruk] Kadir Has Univ, Fac Business, Cibaly, Fatih Istanbul, Turkey; [Kucukonder, Hande] Bartin Univ, Fac Econ, Merkez, Bartin, Turkeyen_US
dc.description.abstractPositioning in the right location for organizing logistics activities is a determinative factor in the aspect of costs, effectivity, productivity, and performance of these operations carried out by logistics firms. The proper logistics village selection is a crucial, complicated, and time-consuming process for decision-makers who have to make the right and optimal decision on this issue. Decision-makers need a methodological frame with a practical algorithm that can be implemented quickly to solve these decision-making problems. Within this scope, the current paper aims to present an evaluation tool, which provides more reasonable and reliable results for decision-makers to solve the logistics village selection problem that is very complicated and has uncertain conditions based on fuzzy approaches. In this study, we propose the Improved Fuzzy Step-Wise Weight Assessment Ratio Analysis (IMF SWARA), a modified and extended version of the traditional fuzzy Step-Wise Weight Assessment Ratio Analysis (F-SWARA) to identify the criteria weights. Also, we suggest applying the fuzzy Multi-Attributive Border Approximation area Comparison (F-MABAC) technique to determine the preference ratings of the alternatives. This combination has many valuable contributions. For example, it proposes to use a more reliable and consistent evaluation scale based on fuzzy sets. Hence, decision-makers can perform more reliable and reasonable pairwise comparisons by considering this evaluation scale. Besides, it presents a multi-attribute evaluation system based on the identified criteria weights. From this perspective, the proposed model is implemented to evaluate eight different logistics village alternatives with respect to nine selection criteria. According to the analysis results, while A8 is the most appropriate option, C1 Gross National Product (GNP) is the most significant criterion. A comprehensive sensitivity analysis was performed to test the robustness and validation of the proposed model, and the results of the analysis approve the validity and applicability of the proposed model. As a result, the suggested integrated MCDM framework can be applied as a valuable and practical decisionmaking tool to develop new strategies and improve the logistics operations by decision-makers.en_US
dc.identifier.citation25
dc.identifier.doi10.3846/tede.2021.16004en_US
dc.identifier.endpage1612en_US
dc.identifier.issn2029-4913
dc.identifier.issn2029-4921
dc.identifier.issue6en_US
dc.identifier.scopus2-s2.0-85121244323en_US
dc.identifier.scopusqualityQ1
dc.identifier.startpage1582en_US
dc.identifier.urihttps://doi.org/10.3846/tede.2021.16004
dc.identifier.urihttps://hdl.handle.net/20.500.12469/5590
dc.identifier.volume27en_US
dc.identifier.wosWOS:000741983200002en_US
dc.identifier.wosqualityQ1
dc.khas20231019-WoSen_US
dc.language.isoenen_US
dc.publisherVilnius Gediminas Tech Univen_US
dc.relation.ispartofTechnological and Economic Development of Economyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectDecision-MakingEn_Us
dc.subjectLocation SelectionEn_Us
dc.subjectSite SelectionEn_Us
dc.subjectTransportEn_Us
dc.subjectMooraEn_Us
dc.subjectModelEn_Us
dc.subjectAhpEn_Us
dc.subjectDecision-Making
dc.subjectLocation Selection
dc.subjectSite Selection
dc.subjectTransport
dc.subjectlogistics villagesen_US
dc.subjectMoora
dc.subjectImproved Fuzzy Step-Wise Weight Assessment Ratio Analysis (IMF SWARA)en_US
dc.subjectModel
dc.subjectMulti-Attributive Border Approximation Area Comparison (MABAC)en_US
dc.subjectAhp
dc.subjectmultiple criteria decision making (MCDM)en_US
dc.titleEVALUATING LOGISTICS VILLAGES IN TURKEY USING HYBRID IMPROVED FUZZY SWARA (IMF SWARA) AND FUZZY MABAC TECHNIQUESen_US
dc.typeArticleen_US
dspace.entity.typePublication
relation.isAuthorOfPublication4d0f6004-dbe4-4e79-befd-457af3bb133f
relation.isAuthorOfPublication.latestForDiscovery4d0f6004-dbe4-4e79-befd-457af3bb133f

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