Time period based COPRAS-G method: application on the logistics performance index

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 p...

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Main Authors: Burcu Adiguzel Mercangoz, Bahadir Yildirim, Sultan Kuzu Yildirim
Format: Article
Language:English
Published: Poznań School of Logistics 2020-06-01
Series:LogForum
Subjects:
Online Access:http://www.logforum.net/vol16/issue2/no5/16_2_5_20.pdf
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spelling doaj-d483ccfb6ece431080a766ffdf1c4c122020-11-25T01:41:01ZengPoznań School of LogisticsLogForum1734-459X2020-06-01162Time period based COPRAS-G method: application on the logistics performance indexBurcu Adiguzel Mercangoz0Bahadir Yildirim1Sultan Kuzu Yildirim2Istanbul University, Istanbul, TurkeyIstanbul University, Istanbul, TurkeyIstanbul University, Istanbul, TurkeyBackground: 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.http://www.logforum.net/vol16/issue2/no5/16_2_5_20.pdfcopras-glogistics performancemulti criteria decision makinggrey numberscorrelation analysis
collection DOAJ
language English
format Article
sources DOAJ
author Burcu Adiguzel Mercangoz
Bahadir Yildirim
Sultan Kuzu Yildirim
spellingShingle Burcu Adiguzel Mercangoz
Bahadir Yildirim
Sultan Kuzu Yildirim
Time period based COPRAS-G method: application on the logistics performance index
LogForum
copras-g
logistics performance
multi criteria decision making
grey numbers
correlation analysis
author_facet Burcu Adiguzel Mercangoz
Bahadir Yildirim
Sultan Kuzu Yildirim
author_sort Burcu Adiguzel Mercangoz
title Time period based COPRAS-G method: application on the logistics performance index
title_short Time period based COPRAS-G method: application on the logistics performance index
title_full Time period based COPRAS-G method: application on the logistics performance index
title_fullStr Time period based COPRAS-G method: application on the logistics performance index
title_full_unstemmed Time period based COPRAS-G method: application on the logistics performance index
title_sort time period based copras-g method: application on the logistics performance index
publisher Poznań School of Logistics
series LogForum
issn 1734-459X
publishDate 2020-06-01
description 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.
topic copras-g
logistics performance
multi criteria decision making
grey numbers
correlation analysis
url http://www.logforum.net/vol16/issue2/no5/16_2_5_20.pdf
work_keys_str_mv AT burcuadiguzelmercangoz timeperiodbasedcoprasgmethodapplicationonthelogisticsperformanceindex
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AT sultankuzuyildirim timeperiodbasedcoprasgmethodapplicationonthelogisticsperformanceindex
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