ARTIFICIAL INTELLIGENCE IN LOGISTICS: ADOPTION PATTERNS, PERFORMANCE EFFECTS, AND MARKET STRUCTURE
DOI:
https://doi.org/10.68302/std2026.vol2.27Keywords:
AI Adoption, KPI, Logistics Sector, Performance ImprovementAbstract
The aim of the paper is to analyse the impact of AI implementation on logistics performance and to develop an action framework that can be used to measure the improved efficiency achieved with AI in an environment of scarce available data. This paper examines the use of AI in the logistics sector in Bulgaria. The study assesses revenue distribution and market concentration to determine when the introduction of AI can be expected to have significant positive effects. A methodological approach is also proposed for the analysis of AI and operational efficiency, and a basis for future research is provided when better information becomes available. Furthermore, the present study focuses on large logistics companies that have the technological and economic means to build AI-based solutions at different levels in their operations. Performance measures, including delivery time, fuel consumption and forecast reliability, are used to highlight the efficiency improvements that are available through the adoption of AI. This article offers an assessment of the efficiency gains from artificial intelligence in logistics operations and proposes that from a scientific perspective, artificial intelligence should be used to consider efficiency gains in order to analyse the limited empirical data.
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[1] D.M. Tran, V.V. Thai, N.P. Nguyen, S. Rahman, L.T.N. Nguyen, T.K. Nguyen, T. Nguyen "The nexus of supply chain managerial competence expectation and possession in the new era: the case of Vietnam". The International Journal of Logistics Management, Vol. 36 No. 7, 2025, pp. 63–98, https://doi.org/10.1108/IJLM-11-2023-0488
[2] L. Y. Koh and K.F. Yuen, “Emerging competencies for logistics professionals in the digital era: A literature review”, Frontiers in Psychology, Vol. 13, 2022, https://doi.org//10.3389/fpsyg.2022.965748
[3] L. Zhu, X. Sheng, “On Image-Processing-Based Identification Method of Express Logistics Information”, Traitement du Signal, 2022, https://doi.org//10.18280/ts.390329
[4] I.Katib, M. Ndiaye, A. Acquaye, “Enhancing Resilience in Logistics-Based Business Models amid Disruptions: A Qualitative Exploration of the UAE Market”, International Journal of Service Science, Management, Engineering, and Technology (IJSSMET)15(1), p.23, 2024, https://doi.org//10.4018/IJSSMET.361596
[5] A. Garg and S. Vemaraju, "Artificial Intelligence Applications in Predictive Maintenance for Sustainable Logistics," 2024 IEEE 4th International Conference on ICT in Business Industry & Government (ICTBIG), Indore, India, 2024, pp. 1-5, https://doi.org// 10.1109/ICTBIG64922.2024.10911124.
[6] Y. Liu, "A Study of Logistics Customer Service Satisfaction Evaluation in the Context of Human-Robot Collaboration: Compatibility of AI Self-Service Q&A Robot," 2024 International Conference on Digital Technology and Intelligent Education (ICDTIE), Shenzhen, China, 2024, pp. 42-48, https://doi.org//10.1109/ICDTIE65977.2024.00015.
[7] S. C. Shu and T. H. Xing, "Application of AI in Modern Logistics Systems," 2021 11th International Conference on Information Technology in Medicine and Education (ITME), Wuyishan, Fujian, China, 2021, pp. 21-26, https://doi.org//10.1109/ITME53901.2021.00015
[8] M. Woschank, Manuela, D. Steinwiedder, A. Kaiblinger, P. Miklautsch, C. Pacher, H. Zsifkovits, “The Integration of Smart Systems in the Context of Industrial Logistics in Manufacturing Enterprises”, Procedia Computer Science, 2022, https://doi.org//10.1016/j.procs.2022.01.271
[9] C. Wan, “Modern intelligent logistics management paradigm based on management information system model”, International Seminar on Computer Science and Engineering Technology, SCSET 2022, https://doi.org//10.1109/SCSET55041.2022.00045
[10] D. Petrova, D. et al., “Modeling Business Process Reengineering in the Digital Era of Industry 4.0”, Aip Conference Proceedings, Open source preview, 2024, https://doi.org/10.1063/5.0185275
[11] H. M. A. Al rejal et al., "The Role of Smart Logistics Toward Sustainable Logistics: A Review,", 1st International Conference on Logistics (ICL), Jeddah, Saudi Arabia, 2024, pp. 1-5, https://doi.org//10.1109/ICL62932.2024.10788584
[12] A. Y. A. Bani Ahmad, M. Allahham, W. I. Almajali, F. T. Ayasrah and S. Sabra, "Smart Logistics Services: How Artificial Intelligence Transforms Decision-Making,", 25th International Arab Conference on Information Technology (ACIT), Zarqa, Jordan, 2024, pp. 1-4, https://doi.org//10.1109/ACIT62805.2024.10876978
[13] D. Petrova and N. Nikolova, “Innovative Development and Competitiveness of the Industrial Sector in Bulgaria”, Environment Technology Resources Proceedings of the 16th International Scientific and Practical ConferenceOpen source preview, 2025, 4, pp. 297–304, https://doi.org//10.17770/etr2025vol4.8397
[14] Speedy, „Annual financial report 2023“, https://www.speedy.bg/en/financial-reports?year=2024 Speedy
[15] Bulgarian Posts, „Annual report 2023“, Annual report for the year 2023.pdf
[16] Gopet Trans, „Press release: Annual turnover of 181 million euros for 2022“, https://gopettrans.com/press-releases/ Gopet Trans
[17] Geopost/DPD Group, „Annual results 2023“, https://www.geopost.com/en/news/geopost-2023-annual-results/ Geopost
[18] Transpress Delivery Ltd, „Annual financial statements 2020“, Bulgarian Commercial Register, https://finansi.bg/compare-balance/202337769?years=10
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Copyright (c) 2026 Siyka Demirova
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