Analysis of the use of artificial intelligence in the management of logistics processes: Approaches and benefits

This study explores artificial intelligence (AI) applications to improve logistics within the Belt and Road Initiative’s Middle Corridor, focusing on Ukraine amid geopolitical disruptions. Its objective is to quantify AI's impact on delivery times, inventory costs, fuel consumption, and network resilience in this complex region. Employing a mixed-method approach, the research combines Social Network Analysis (SNA) to identify key nodes and bottlenecks with simulation modelling based on empirical data from 2019 to 2023, including GPS tracking and port metrics. Results show AI integration reduces delivery times by 11,7 %, cuts inventory holding costs by 16,3 %, and lowers fuel consumption by 9,2 %. SNA reveals enhanced connectivity and efficiency at critical hubs such as Kyiv and Odesa, strengthening Ukraine’s strategic logistics role. The study concludes that AI-driven optimizations significantly boost corridor efficiency, resilience, and sustainability. It recommends future work on real-time data integration and broader AI applications to support adaptive, greener supply chains across politically sensitive trade routes.

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Publication Details

Journal
LatIA
Published
2025-08-25
DOI
https://doi.org/10.62486/latia2025279
Primary Topic
Economic and Technological Systems Analysis
Type
article
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article

Analysis of the use of artificial intelligence in the management of logistics processes: Approaches and benefits

Natalia Chaplynska, М. Б. Паласевич, Nataliia Sapotnitska, O. KUDRIAVTSEVA et al.
LatIA
Economic and Technological Systems Analysis
article

Analysis of the use of artificial intelligence in the management of logistics processes: Approaches and benefits

Natalia Chaplynska, М. Б. Паласевич, Nataliia Sapotnitska, O. KUDRIAVTSEVA, Juliia Rud
article en

Abstract

This study explores artificial intelligence (AI) applications to improve logistics within the Belt and Road Initiative’s Middle Corridor, focusing on Ukraine amid geopolitical disruptions. Its objective is to quantify AI's impact on delivery times, inventory costs, fuel consumption, and network resilience in this complex region. Employing a mixed-method approach, the research combines Social Network Analysis (SNA) to identify key nodes and bottlenecks with simulation modelling based on empirical data from 2019 to 2023, including GPS tracking and port metrics. Results show AI integration reduces delivery times by 11,7 %, cuts inventory holding costs by 16,3 %, and lowers fuel consumption by 9,2 %. SNA reveals enhanced connectivity and efficiency at critical hubs such as Kyiv and Odesa, strengthening Ukraine’s strategic logistics role. The study concludes that AI-driven optimizations significantly boost corridor efficiency, resilience, and sustainability. It recommends future work on real-time data integration and broader AI applications to support adaptive, greener supply chains across politically sensitive trade routes.

LatIAVol. 3
Khmelnytskyi National University (UA), Kharkiv National Automobile and Highway University (UA), Drohobych Ivan Franko State Pedagogical University (UA), Kremenchuk University of Economics Information Technology and Management (UA), Hong Kong Footwear Federation (CN)
Openalex Percentile: Top 69%
Economic and Technological Systems Analysis
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Analysis of the use of artificial intelligence in the management of logistics processes: Approaches and benefits — Natalia Chaplynska, М. Б. Паласевич, et al. · LatIA (2025) | TGRS Research Map | TGRS