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February 2, 20260 citations

Differentiated macroeconomic drivers of sustainable logistics: evidence from selected advanced and transition economies in the European Union

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MKMagdalena KowalskaAMAnna Misztal

Key Points

  • The goal is to analyze the macroeconomic factors influencing sustainable logistics in advanced and transition economies in the EU.
  • Constructed a synthetic sustainable logistics index from 18 environmental, economic, and social variables.
  • Performed OLS regression for each of the six analyzed countries.
  • Utilized fixed-effect panel models for developed versus transition economies.
  • GDP positively impacts sustainable logistics across all countries studied.
  • In developed economies, inflation and growth dynamics are key factors.
  • Wages and trade balance significantly influence sustainable logistics in transition economies.

Abstract

Sustainable development in logistics involves integrating economic, social, and environmental goals within transport and storage. In practice, it means reducing greenhouse gas emissions through eco-friendly fleets and green storage solutions. In the context of the EU Green Deal and the "Fit for 55" package, analyzing macroeconomic factors influencing sustainable logistics (SDLog) is crucial. This study compares six EU countries between 2008–2023: three developed (France, Germany, the Netherlands) and three transition economies (Czech Republic, Poland, Romania). A synthetic SDLog index was built from 18 variables covering environmental, economic, and social dimensions. The analysis followed two stages: OLS regression for each country and fixed-effect panel models for the two groups. Results show GDP has a universally positive effect on sustainable logistics. In developed economies, inflation and growth dynamics also matter, while in transition economies, wages and trade balance are more significant. The findings underline the importance of tailoring public policies and logistics strategies to country-specific macroeconomic conditions. Future research should expand the analysis to include institutional and technological factors, as well as apply dynamic models to capture long-term development paths.

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Cite This Study

Kowalska et al. (2025) studied this question.

synapsesocial.com/papers/6980ff49c1c9540dea8122adhttps://doi.org/10.19192/wsfip.sj4.2025.4
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