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

Zsolt Toth (), Alexandru-Silviu Goga and Mircea Boșcoianu
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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

Logistics, 2025, vol. 9, issue 4, 1-22

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.

Keywords: artificial intelligence integration; knowledge process capabilities; dynamic capabilities; logistics transformation; emerging markets; hybrid capability architectures (search for similar items in EconPapers)
JEL-codes: L8 L80 L81 L86 L87 L9 L90 L91 L92 L93 L98 L99 M1 M10 M11 M16 M19 R4 R40 R41 R49 (search for similar items in EconPapers)
Date: 2025
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