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AI Integration in Fundamental Logistics Components: Advanced Theoretical Framework for Knowledge Process Capabilities and Dynamic Capabilities Hybridization

Author

Listed:
  • Zsolt Toth

    (Engineering and Industrial Management, The Faculty of Technological Engineering and Industrial Management, Transilvania University of Brașov, 500036 Brașov, Romania)

  • Alexandru-Silviu Goga

    (Engineering and Industrial Management, The Faculty of Technological Engineering and Industrial Management, Transilvania University of Brașov, 500036 Brașov, Romania)

  • Mircea Boșcoianu

    (Engineering and Industrial Management, The Faculty of Technological Engineering and Industrial Management, Transilvania University of Brașov, 500036 Brașov, Romania)

Abstract

Background : Despite significant technological advances, many logistics organizations in emerging markets struggle to realize the transformative potential of artificial intelligence, with reported success rates below 65% and limited theoretical understanding of the organizational capabilities. This study develops and proposes an integrated theoretical framework examining how knowledge process capabilities and dynamic capabilities interact to enable successful artificial intelligence adoption in logistics organizations within emerging market contexts. Methods : Through comprehensive literature review and theoretical synthesis, we propose a hybrid capability framework that integrates knowledge-based view perspectives with dynamic capabilities theory. Results : Theoretical analysis suggests that knowledge combination capabilities may be the strongest predictor of artificial intelligence implementation success, while dynamic reconfiguring capabilities could mediate the relationship between artificial intelligence adoption and performance outcomes. The proposed framework indicates that organizations with hybrid capability architecture may achieve superior implementation success compared to traditional approaches. Environmental uncertainty is theorized to strengthen the knowledge process capabilities—artificial intelligence adoption relationship. Conclusions : The framework suggests that successful artificial intelligence integration requires simultaneous development of knowledge-based and adaptive capabilities rather than sequential capability building. The hybrid capability framework provides theoretical guidance for managers in emerging markets, while highlighting the critical role of environmental context in shaping transformation strategies.

Suggested Citation

  • Zsolt Toth & Alexandru-Silviu Goga & Mircea Boșcoianu, 2025. "AI Integration in Fundamental Logistics Components: Advanced Theoretical Framework for Knowledge Process Capabilities and Dynamic Capabilities Hybridization," Logistics, MDPI, vol. 9(4), pages 1-22, October.
    • Handle: RePEc:gam:jlogis:v:9:y:2025:i:4:p:140-:d:1765437
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    References listed on IDEAS

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    1. 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.
    2. 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).
    3. Radicic, Dragana & Petković, Saša, 2023. "Impact of digitalization on technological innovations in small and medium-sized enterprises (SMEs)," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    4. 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.
    5. 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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