dc.contributor.author | Adıgüzel Mercangöz, Burcu | |
dc.contributor.author | Yıldırım, Bahadır Fatih | |
dc.contributor.author | Kuzu Yıldırım, Sultan | |
dc.date | 2019 | |
dc.date.accessioned | 2020-05-07T18:55:09Z | |
dc.date.available | 2020-05-07T18:55:09Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | Adıgüzel 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.uri | http://hdl.handle.net/20.500.12627/615 | |
dc.description.abstract | Background: 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.iso | eng | tr_TR |
dc.publisher | Poznan School of Logistics | tr_TR |
dc.relation.isversionof | 10.17270/J.LOG.2020.432 | tr_TR |
dc.rights | info:eu-repo/semantics/openAccess | tr_TR |
dc.rights | Attribution-NonCommercial 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc/3.0/us/ | * |
dc.subject | Correlation Analysis | tr_TR |
dc.subject | Grey COPRAS | tr_TR |
dc.subject | Grey Numbers | tr_TR |
dc.subject | Logistics Performance Index | tr_TR |
dc.title | Time Period Based COPRAS-G Method: Application on the Logistics Performance Index | tr_TR |
dc.type | article | tr_TR |
dc.relation.journal | LogForum | tr_TR |
dc.contributor.department | İstanbul Siyasal Bilgiler Fakültesi, İşletme Bölümü, Sayısal Yöntemler Ana Bilim Dalı | tr_TR |
dc.contributor.department | İstanbul Ulaştırma ve Lojistik Fakültesi, Ulaştırma ve Lojistik Bölümü, Lojistik Anabilim Dalı | tr_TR |
dc.contributor.authorID | 0000-0003-2250-1052 | tr_TR |
dc.contributor.authorID | 0000-0002-0475-741X | tr_TR |
dc.contributor.authorID | 0000-0001-6577-1584 | tr_TR |
dc.identifier.volume | 16 | tr_TR |
dc.identifier.issue | 2 | tr_TR |
dc.identifier.startpage | 239 | tr_TR |
dc.identifier.endpage | 250 | tr_TR |