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Sustainable Strategies to Reduce Logistics Costs Based on Cross-Docking—The Case of Emerging European Markets

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  • Mircea Boșcoianu

    (ITMI Faculty, Interdisciplinary Doctoral School, Transilvania University of Brașov, 500036 Brașov, Romania)

  • Zsolt Toth

    (ITMI Faculty, Interdisciplinary Doctoral School, Transilvania University of Brașov, 500036 Brașov, Romania)

  • Alexandru-Silviu Goga

    (ITMI Faculty, Interdisciplinary Doctoral School, Transilvania University of Brașov, 500036 Brașov, Romania)

Abstract

Cross-docking operations in Eastern and Central European markets face increasing complexity amid persistent uncertainty and inflationary pressures. This study provides the first comprehensive comparative analysis integrating economic efficiency with sustainability indicators across strategic locations. Using mixed-methods analysis of 40 bibliographical sources and quantitative modeling of cross-docking scenarios in Bratislava, Prague, and Budapest, we integrate environmental, social, and governance frameworks with activity-based costing and artificial intelligence analysis. Optimized cross-docking achieves statistically significant cost reductions of 10.61% for Eastern and Central European inbound logistics and 3.84% for Western European outbound logistics when utilizing Budapest location ( p < 0.01). Activity-based costing reveals labor (35–40%), equipment utilization (25–30%), and facility operations (20–25%) as primary cost drivers. Budapest demonstrates superior integrated performance index incorporating operational efficiency (94.2% loading efficiency), economic impact (EUR 925,000 annual savings), and environmental performance (486 tons CO 2 reduction annually). This is the first empirically validated framework integrating activity-based costing–corporate social responsibility methodologies for an emerging market cross-docking, multi-dimensional performance assessment model transcending operational-sustainability dichotomy and location-specific contingency identification for emerging market implementation. Findings support targeted infrastructure investments, harmonized regulatory frameworks, and public–private partnerships for sustainable logistics development in emerging European markets, providing actionable roadmap for EUR 142,000–EUR 187,000 artificial intelligence implementation investments achieving a 14.6-month return on investment.

Suggested Citation

  • Mircea Boșcoianu & Zsolt Toth & Alexandru-Silviu Goga, 2025. "Sustainable Strategies to Reduce Logistics Costs Based on Cross-Docking—The Case of Emerging European Markets," Sustainability, MDPI, vol. 17(14), pages 1-28, July.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:14:p:6471-:d:1702050
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    References listed on IDEAS

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    1. Manuel Woschank & Erwin Rauch & Helmut Zsifkovits, 2020. "A Review of Further Directions for Artificial Intelligence, Machine Learning, and Deep Learning in Smart Logistics," Sustainability, MDPI, vol. 12(9), pages 1-23, May.
    2. Alexandru-Silviu Goga & Zsolt Toth & Mihai-Alin Meclea & Ionela-Roxana Puiu & Mircea Boșcoianu, 2024. "The Proliferation of Artificial Intelligence in the Forklift Industry—An Analysis for the Case of Romania," Sustainability, MDPI, vol. 16(21), pages 1-25, October.
    3. Potoczki, Tobias & Holzapfel, Andreas & Kuhn, Heinrich & Sternbeck, Michael, 2024. "Integrated cross-dock location and supply mode planning in retail networks," International Journal of Production Economics, Elsevier, vol. 276(C).
    4. Amiri, Zahra & Heidari, Arash & Navimipour, Nima Jafari, 2024. "Comprehensive survey of artificial intelligence techniques and strategies for climate change mitigation," Energy, Elsevier, vol. 308(C).
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