An EDAS Method-Based Clustering Study to Assess the Logistics Performances of Selected Countries

Abstract

The importance of environmentally friendly logistics activities is increasing day by day due to the intensifying globalization and increasing trade volumes of countries. Undoubtedly, the logistics industry contributes positively to national economies; however, this increasing contribution brings environmental concerns. The total amount of CO₂ emissions caused by transportation varies depending on the countries’ efforts on green strategies. In this case, it is thought that clustering countries based on their logistics performance indices and CO₂ emissions from transportation may contribute to the sustainable development goals of actors that play an active role in global trade movements. This research study investigates Turkey's position in global trade logistics relative to its competitors, taking into account the Logistics Performance Index (LPI) and the total CO₂ emission values from transportation. For this purpose, the hierarchical K-means clustering analysis was conducted using the six criteria of the LPI published by the World Bank in 2018 and the CO₂ transport-related emission values of 44 countries. The R programming language was used for clustering analysis. According to the analysis results of the study, 44 countries were divided into 4 clusters in terms of their logistics performance and CO₂ emissions sourced by transportation. In addition, performance evaluations of clustered countries were carried out with the EDAS method, which is one of the Multi-Criteria Decision Making (MCDM) methods on each cluster basis. According to the results obtained from the EDAS method, the countries within each cluster are ranked from the best to the worst. This study can provide a practical framework for countries to improve their logistics performance with low carbon footprint applications.