Digital technologies and modelling for enhancing supply chain efficiency in international road transport

Autores

  • Vasyl Onyshchuk PhD in Technical Sciences, Associate Professor, Head of the Department of Automobiles and Transport Technologies of LNTU, Faculty of Transport and Mechanical Engineering, Lutsk National Technical University, Lutsk, Ukraine https://orcid.org/0000-0002-5316-408X
  • Oleksandr Dubytskyi PhD in Technical Sciences, Associate Professor, Department of Automobiles and Transport Technologies, Faculty of Transport and Mechanical Engineering, Lutsk National Technical University, Lutsk, Ukraine https://orcid.org/0000-0002-4863-4040
  • Volodymyr Bodak Candidate of Technical Sciences, Associate Professor, Department of Automobiles and Transport Technologies, Faculty of Transport and Mechanical Engineering, Lutsk National Technical University, Lutsk, Ukraine https://orcid.org/0000-0003-2521-7305
  • Irina Pavlova PhD, Associate Professor, Department of Automobiles and Transport Technologies, Faculty of Transport and Mechanical Engineering, Lutsk National Technical University, Lutsk, Ukraine https://orcid.org/0000-0003-1506-6064
  • Nataliia Riabykh PhD in Law, Associate Professor, Department of Law, Faculty of Business and Law, Lutsk National Technical University, Lutsk, Ukraine https://orcid.org/0009-0007-4177-698X

DOI:

https://doi.org/10.20397/2177-6652/2025.v25i1.3114

Palavras-chave:

international road transport; , supply chains, digital technologies, artificial intelligence, digital twins.

Resumo

International road transport is a critical part of international supply chains, and it faces issues like increasing costs, environmental regulations, and unevenly developed infrastructure. The emergence of new digitalisation opportunities for logistics processes creates excellent opportunities to enhance transport efficiency and flexibility; therefore, research in this area is very relevant. The study investigates the influence of digital technologies such as the Internet of Things, digital twins, and artificial intelligence on the optimisation of international road transport. The paper uses system analysis, mathematical modelling and linear programming to assess the effectiveness of logistics solutions. The findings indicate that digital technologies can cut transportation costs by 18 per cent on average by optimising routes and avoiding logistics risks. Digital twins used in route modelling increase process transparency and decision-making efficiency. Predictive analytics based on artificial intelligence allows for more efficient inventory management and minimisation of delivery delays. The practical significance of the work lies in developing algorithms that can be implemented by both large logistics companies and small businesses, subject to adaptation to their needs. The data obtained can be used to improve logistics systems further and integrate innovative technologies into international transport.

 

Biografia do Autor

Vasyl Onyshchuk, PhD in Technical Sciences, Associate Professor, Head of the Department of Automobiles and Transport Technologies of LNTU, Faculty of Transport and Mechanical Engineering, Lutsk National Technical University, Lutsk, Ukraine

PhD in Technical Sciences, Associate Professor, Head of the Department of Automobiles and Transport Technologies of LNTU, Faculty of Transport and Mechanical Engineering, Lutsk National Technical University, Lutsk, Ukraine

Oleksandr Dubytskyi, PhD in Technical Sciences, Associate Professor, Department of Automobiles and Transport Technologies, Faculty of Transport and Mechanical Engineering, Lutsk National Technical University, Lutsk, Ukraine

PhD in Technical Sciences, Associate Professor, Department of Automobiles and Transport Technologies, Faculty of Transport and Mechanical Engineering, Lutsk National Technical University, Lutsk, Ukraine

Volodymyr Bodak, Candidate of Technical Sciences, Associate Professor, Department of Automobiles and Transport Technologies, Faculty of Transport and Mechanical Engineering, Lutsk National Technical University, Lutsk, Ukraine

Candidate of Technical Sciences, Associate Professor, Department of Automobiles and Transport Technologies, Faculty of Transport and Mechanical Engineering, Lutsk National Technical University, Lutsk, Ukraine

Irina Pavlova, PhD, Associate Professor, Department of Automobiles and Transport Technologies, Faculty of Transport and Mechanical Engineering, Lutsk National Technical University, Lutsk, Ukraine

PhD, Associate Professor, Department of Automobiles and Transport Technologies, Faculty of Transport and Mechanical Engineering, Lutsk National Technical University, Lutsk, Ukraine

Nataliia Riabykh, PhD in Law, Associate Professor, Department of Law, Faculty of Business and Law, Lutsk National Technical University, Lutsk, Ukraine

PhD in Law, Associate Professor, Department of Law, Faculty of Business and Law, Lutsk National Technical University, Lutsk, Ukraine

Referências

Ambalov, V., & Heim, I. (2020). Investments in the digital silk road. In Heim, I. (Ed.), Kazakhstan's diversification from the natural resources sector. Euro-Asian Studies (pp. 125-146). Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-37389-4_5

Boute, R. N., & Udenio, M. (2023). AI in logistics and supply chain management. In Merkert, R., & Hoberg, K. (Eds.), Global Logistics and Supply Chain Strategies for the 2020s. Springer. https://doi.org/10.1007/978-3-030-95764-3_3

Chan, L., Hogaboam, L., & Cao, R. (2022). AI in supply chain and logistics. In Applied Artificial Intelligence in Business. Springer. https://doi.org/10.1007/978-3-031-05740-3_10

Cui, Q., Hu, X., & Ni, W. (2022). Vehicular mobility patterns and their applications to Internet-of-Vehicles: A comprehensive survey. Science China Information Sciences, 65, 211301. https://doi.org/10.1007/s11432-021-3487-x

D'Andrea, C., et al. (2024). 6G wireless technologies. In Loscri, V., Chiaraviglio, L., & Vegni, A. M. (Eds.), The Road Towards 6G: Opportunities, Challenges, and Applications. Springer. https://doi.org/10.1007/978-3-031-42567-7_3

Dhaliwal, A. (2024). Towards AI-driven transport and logistics. In Kathuria, A., Karhade, P. P., Zhao, K., & Chaturvedi, D. (Eds.), Digital Transformation in the Viral Age. Springer. https://doi.org/10.1007/978-3-031-60003-6_8

Feng, B., & Ye, Q. (2021). Operations management of smart logistics: A literature review and future research. Frontiers of Engineering Management, 8(3), 344-355. https://doi.org/10.1007/s42524-021-0156-2

Ivanov, D., Tsipoulanidis, A., & Schönberger, J. (2021). Digital supply chain, smart operations and Industry 4.0. In Global Supply Chain and Operations Management. Springer. https://doi.org/10.1007/978-3-030-72331-6_16

Ivanov, D., Tsipoulanidis, A., & Schönberger, J. (2021). Operations and supply chain strategy. In Global Supply Chain and Operations Management. Springer. https://doi.org/10.1007/978-3-030-72331-6_4

Kang, P. S., Wang, X., Son, J. Y., & Jat, M. (2024). Analytics models for customer-centric service-based supply chains. In Service 4.0. SpringerBriefs in Service Science. Springer. https://doi.org/10.1007/978-3-031-63875-6_3

Kiviharju, M. (2024). On the cybersecurity of logistics in the age of artificial intelligence. In Sipola, T., Alatalo, J., Wolfmayr, M., & Kokkonen, T. (Eds.), Artificial Intelligence for Security. Springer. https://doi.org/10.1007/978-3-031-57452-8_9

Kochhar, N. (2023). Leading the transformation in the automotive industry through the digital twin. In Crespi, N., Drobot, A. T., & Minerva, R. (Eds.), The Digital Twin. Springer. https://doi.org/10.1007/978-3-031-21343-4_27

Lozano-Oviedo, J., Cortés, C. E., & Rey, P. A. (2024). Sustainable closed-loop supply chains and their optimisation models: A review of the literature. Clean Technologies and Environmental Policy, 26(5), 999-1023. https://doi.org/10.1007/s10098-023-02730-w

Nandi, M. L., Nandi, S., & Dave, D. (2024). Applying artificial intelligence in the supply chain. In Sarkis, J. (Ed.), The Palgrave Handbook of Supply Chain Management. Palgrave Macmillan. https://doi.org/10.1007/978-3-031-19884-7_77

Palander, T., Tokola, T., & Borz, S. A. (2024). Forest supply chains during digitalisation: Current implementations and prospects in the near future. Current Forestry Reports, 10(3), 223-238. https://doi.org/10.1007/s40725-024-00218-4

Quayson, M., Bai, C., Effah, D., & Ofori, K. S. (2023). Machine learning and supply chain management. In Sarkis, J. (Ed.), The Palgrave Handbook of Supply Chain Management. Palgrave Macmillan. https://doi.org/10.1007/978-3-030-89822-9_92-1

Rziki, M. H., Bourray, H., El Ouadghiri, M. D., El Hadbi, A., Belkadi, R., & Sedra, M. B. (2024). On the role of big data and artificial intelligence for the sustainability of complex logistics networks of offshore companies. In Ezziyyani, M., Kacprzyk, J., & Balas, V. E. (Eds.), AI2SD 2023 (Vol. 931). Springer. https://doi.org/10.1007/978-3-031-54288-6_15

Shah, A., Che Mat, C. R., Ibrahim, A., Zhang, Y., & Muzammil, S. (2024). Understanding digital supply chains in the context of industrial ecology. In Industrial Ecology. Springer. https://doi.org/10.1007/978-981-97-3619-5_4

Sinitsyna, A., & Nekrasov, A. (2024). Digital transformation tools for sustainable supply chains in the life cycle processes. In Sari, M., & Kulachinskaya, A. (Eds.), Digital Transformation: What Are the Smart Cities Today? (Vol. 846). Springer. https://doi.org/10.1007/978-3-031-49390-4_15

Stark, R. (2022). The role of digital technology vendors. In Virtual Product Creation in Industry. Springer. https://doi.org/10.1007/978-3-662-64301-3_19

Sun, X., Yu, H., & Solvang, W. D. (2022). The application of Industry 4.0 technologies in sustainable logistics: A systematic literature review (2012-2020) to explore future research opportunities. Environmental Science and Pollution Research, 29(6), 9560-9591. https://doi.org/10.1007/s11356-021-17693-y

Triantafyllou, M., Al-Bazi, A., & Ahmad, M. A. (2024). Digital twins: Revolutionising automotive supply chains. In Benadada, Y., Mhada, F. Z., Boukachour, J., Ouzayd, F., & El Hilali Alaoui, A. (Eds.), Proceeding of the 7th International Conference on Logistics Operations Management, GOL'24 (Vol. 1104). Springer. https://doi.org/10.1007/978-3-031-68628-3_1

Vrana, J., & Singh, R. (2023). Modelling digital penetration of the industrialised society and its subsequent transformation. Digital Industrial Society Online, 2, 54. https://doi.org/10.1007/s44206-023-00084-w

Zhang, G., Yang, Y., & Yang, G. (2023). Smart supply chain management in Industry 4.0: The review, research agenda and strategies in North America. Annals of Operations Research, 322(3), 1075-1117. https://doi.org/10.1007/s10479-022-04689-1

Zrelli, I., Rejeb, A., & Abusulaiman, R. (2024). Drone applications in logistics and supply chain management: A systematic review using latent Dirichlet allocation. Arabian Journal for Science and Engineering, 49(12), 12411-12430. https://doi.org/10.1007/s13369-023-08681-0

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Publicado

2025-03-08

Como Citar

Onyshchuk, V., Dubytskyi, O., Bodak, V., Pavlova, I., & Riabykh, N. (2025). Digital technologies and modelling for enhancing supply chain efficiency in international road transport. Revista Gestão & Tecnologia, 25(1), 168–185. https://doi.org/10.20397/2177-6652/2025.v25i1.3114

Edição

v. 25 n. 1 (2025)

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ARTIGO

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