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dc.contributor.authorYıldırım, Bahadır Fatih
dc.contributor.authorYorulmaz, Özlem
dc.contributor.authorKuzu Yıldırım, Sultan
dc.date2021-07-01
dc.date.accessioned2021-07-06T08:08:27Z
dc.date.available2021-07-06T08:08:27Z
dc.date.issued2021-07-01
dc.identifier.issn2620-1747
dc.identifier.urihttp://hdl.handle.net/20.500.12627/167874
dc.description.abstractIn this paper, 81 Turkish provinces with different development levels were ranked using the TOPSIS method. To evaluate the ranking with TOPSIS, we presented an improvement to Mahalanobis distances, by considering a robust MM estimator of the covariance matrix to deal with the presence of outliers in the dataset. Additionally, the homogenous subsets, which were obtained from the robust Mahalanobis distance-based TOPSIS were compared with robust cluster analysis. According to our findings, robust TOPSIS-M scores reflect the inter-class differences in economic developments of provinces spanning from the extremely low to the extremely high level of economic developments. Considering indicators of economic development, which are often used in the literature, İstanbul ranked first, Ankara second, and İzmir third according to the Robust TOPSIS-M method. Moreover, with the Robust Cluster analysis, these provinces were diagnosed as outliers and it was seen that obtained clusters were compatible with the ranking of Robust TOPSIS-M.tr_TR
dc.language.isoengtr_TR
dc.publisherRegional Association for Security and crisis managementtr_TR
dc.relation.isversionof10.31181/oresta20402102ytr_TR
dc.rightsinfo:eu-repo/semantics/openAccesstr_TR
dc.rightsAttribution-NonCommercial 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/3.0/us/*
dc.subjectEconomic Developmenttr_TR
dc.subjectMahalanobis Distancetr_TR
dc.subjectOutlierstr_TR
dc.subjectRobust Clusteringtr_TR
dc.subjectRobust TOPSIS-Mtr_TR
dc.titleRobust Mahalanobis Distance based TOPSIS to Evaluate the Economic Development of Provincestr_TR
dc.typearticletr_TR
dc.relation.journalOperational Research in Engineering Sciences: Theory and Applicationstr_TR
dc.contributor.departmentİstanbul Üniversitesitr_TR
dc.contributor.departmentİstanbul İktisat Fakültesi, Ekonometri Bölümü, İstatistik Ana Bilim Dalıtr_TR
dc.contributor.departmentİstanbul İşletme Fakültesi, İşletme Bölümü, Sayısal Yöntemler Ana Bilim Dalıtr_TR
dc.contributor.departmentİstanbul Ulaştırma ve Lojistik Fakültesi, Ulaştırma ve Lojistik Bölümü, Lojistik Anabilim Dalıtr_TR
dc.identifier.volume4tr_TR
dc.identifier.issue2tr_TR
dc.identifier.startpage102tr_TR
dc.identifier.endpage123tr_TR


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