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dc.contributor.authorAdıgüzel Mercangöz, Burcu
dc.contributor.authorYıldırım, Bahadır Fatih
dc.contributor.authorKuzu Yıldırım, Sultan
dc.date2019
dc.date.accessioned2020-05-07T18:55:09Z
dc.date.available2020-05-07T18:55:09Z
dc.date.issued2020
dc.identifier.citationAdıgüzel Mercangöz, B., Yıldırım, B. F., Kuzu Yıldırım, S. (2020). "Time Period Based COPRAS-G Method: Application on the Logistics Performance Index". LogForum, 16 (2), 239-250.tr_TR
dc.identifier.urihttp://hdl.handle.net/20.500.12627/615
dc.description.abstractBackground: Logistics is vital for the trades of countries. The inputs such as raw materials and energy that is needed for production and also the outputs of these processes are transported and distributed effectively as a result of an efficient logistics process. In order to measure the logistics performance of countries, The World Bank (WB) is publishing an index entitled Logistics Performance for every two years. Methods: The main value of this study is to provide logistics performance scores of the selected countries for a selected time period. Thus, periodic evaluations can be done for a selected time period. The grey numbers are used for determining a new dataset for a time period and implement to Complex Proportional Assessment of Alternatives (COPRAS) method. 28 European Union (EU) member states plus 5 EU Candidate Countries are ranked by using the COPRAS-Grey (COPRAS-G) method according to their logistics performance scores. In order to see if the ranking calculated by COPRAS-G is representing the past index data, the bilateral comparisons of the rankings are investigated by using the Spearman Rank and Kendall’s Tau Correlation methods. Results: The results showed that the dataset obtained by using grey numbers represent the LPI scores of the countries for the selected time period. Although there are slight differences between the Spearman and Kendall correlation coefficients, the ultimate result is the same. The ranking calculated by COPRAS-G has the strongest relationship with all rankings published by WB. Conclusions: By using the grey numbers combined with the COPRAS-G method, the LPI of Countries can be evaluated for a time period.tr_TR
dc.language.isoengtr_TR
dc.publisherPoznan School of Logisticstr_TR
dc.relation.isversionof10.17270/J.LOG.2020.432tr_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.subjectCorrelation Analysistr_TR
dc.subjectGrey COPRAStr_TR
dc.subjectGrey Numberstr_TR
dc.subjectLogistics Performance Indextr_TR
dc.titleTime Period Based COPRAS-G Method: Application on the Logistics Performance Indextr_TR
dc.typearticletr_TR
dc.relation.journalLogForumtr_TR
dc.contributor.departmentİstanbul Siyasal Bilgiler 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.contributor.authorID0000-0003-2250-1052tr_TR
dc.contributor.authorID0000-0002-0475-741Xtr_TR
dc.contributor.authorID0000-0001-6577-1584tr_TR
dc.identifier.volume16tr_TR
dc.identifier.issue2tr_TR
dc.identifier.startpage239tr_TR
dc.identifier.endpage250tr_TR


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