Efficiency in International Logistics: Trade, Emissions and the Case of Türkiye

Abstract

Purpose: This study examines the environmental efficiency of international logistics by exploring the relationships among trade volume, port infrastructure, energy intensity, and GHG emissions across countries. It aims to classify logistics typologies and evaluate the environmental impacts of trade-driven operations, with Türkiye as a focal case. Methodology: A cross-country empirical framework integrates data on per capita CO₂, methane, total GHG emissions, energy intensity, and trade volumes. The study uses data from the World Port Index (2019), TradeMap (2024), and Our World in Data (2024), the study applies K-means clustering to identify environmental logistics typologies and OLS regression to examine the effects of trade and energy intensity on CO₂ emissions. Türkiye is used as a comparative reference point. Findings: The study identifies three logistics typologies: environmentally efficient, transitional, and emissions-intensive. Regression results show energy intensity as the strongest predictor of CO₂ emissions (p < 0.001), while trade volume and its interaction are not significant. Türkiye falls within the transitional cluster, characterized by moderate energy consumption and relatively low emissions, even with high trade activity. Implications: The results underscore that sustainable trade hinges on energy-efficient logistics rather than reduced trade volumes. Policymakers should focus on optimizing energy use and modernizing infrastructure. Integrating emissions metrics into logistics and trade strategies can support greener transitions, especially in emerging economies. Limitations: The use of country-level data may obscure regional disparities and sector-specific emissions. Additionally, clustering may oversimplify complex logistics systems. Future research should incorporate subnational and logistics-specific data for greater precision.