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Artificial Intelligence-Driven Logistics and Supply Chain Management: Industry Applications and Future Perspectives

Yıl 2025, Cilt: 8 Sayı: 2, 217 - 240, 25.10.2025
https://doi.org/10.51513/jitsa.1569385

Öz

In recent years, the digitalization of logistics and supply chain management has accelerated, bringing significant advancements through the utilization of artificial intelligence (AI). AI, which offers a broad range of applications, is now integral to enhancing operational efficiency in logistics and supply chains. This paper explores the various applications of AI in these domains, supported by both real-world industry examples and academic literature. The research employs a combined methodology of systematic literature review (SLR) and field research to achieve its objectives. The study aims to identify where AI solutions are applied within logistics and supply chains and to correlate these applications with real-world examples. Findings indicate that AI usage in logistics is categorized within a theoretical framework encompassing 12 distinct domains. The paper details AI applications in prominent companies, including Walmart, Amazon, UPS, DHL, Ocado, Alibaba, Maersk, Siemens, FedEx, Kuehne + Nagel, and DB Schenker. Ultimately, this paper examines how AI has revolutionized logistics and supply chain management, illustrating the transformation through industry applications and academic literature. The results demonstrate a clear trend of AI becoming increasingly integrated into logistical processes, underscoring its growing impact day by day.

Kaynakça

  • Aghazadeh, H., & Khoshnevis, M. (2024). Martechs and Digital Marketing+ (Types of Digital Marketing). Digital Marketing Technologies (pp. 187-226). Singapore: Springer Nature Singapore.
  • Aliyev, A. G., Shahverdiyeva, R. O., & Hagverdiyeva, U. H. (2024). Modernization of E-Commerce and Logistics Platforms of Enterprises Based on Artificial Intelligence Technology. Artificial Intelligence, Medical Engineering and Education (pp. 170-181). IOS Press.
  • Aljazzar, S. M. (2023). Harnessing Artificial Intelligence for Supply Chain Optimization: Enhanced Demand Prediction and Cost Reduction. In 2023 2nd International Engineering Conference on Electrical, Energy, and Artificial Intelligence (EICEEAI) (pp. 1-6). IEEE.
  • Amosu, O. R., Kumar, P., Ogunsuji, Y. M., Oni, S., & Faworaja, O. (2024). AI-driven demand forecasting: Enhancing inventory management and customer satisfaction. World Journal of Advanced Research and Reviews, 23(2), 708-719.
  • Annanth, V. K., Abinash, M., & Rao, L. B. (2021). Intelligent manufacturing in the context of industry 4.0: A case study of siemens industry. In Journal of Physics: Conference Series (Vol. 1969, No. 1, p. 012019). IOP Publishing.
  • Bharadiya, J. (2023). Artificial intelligence in transportation systems a critical review. American Journal of Computing and Engineering, 6(1), 34-45.
  • Bogue, R. (2022). Warehouse robot market boosted by Covid pandemic and technological innovations. Industrial Robot: the international journal of robotics research and application, 49(2), 181-186.
  • Bogue, R. (2024). The role of robots in logistics. Industrial Robot: the international journal of robotics research and application, 51(3), 381-386.
  • Boršoš, P., & Koman, G. (2025). Overview of Current Research on Artificial Intelligence in Logistics. LOGI: Scientific Journal on Transport and Logistics, 16(1), 13-24.
  • Boute, R. N., & Udenio, M. (2022). AI in logistics and supply chain management. Global logistics and supply chain strategies for the 2020s: Vital skills for the next generation (pp. 49-65). Cham: Springer International Publishing.
  • Brintrup, Alexandra. (2020). Artificial Intelligence in the Supply Chain: A Classification Framework and Critical Analysis of the Current State, in Thomas Y. Choi, and others (eds), The Oxford Handbook of Supply Chain Management, Oxford Academic.
  • Călinescu, G. (2022). The Applications of Blockchain and Artificial Intelligence in Logistics. The Romanian Economic Journal, 69, 84.
  • Cao, L. (2021). Artificial intelligence in retail: applications and value creation logics. International Journal of Retail & Distribution Management, 49(7), 958-976.
  • Chang, Y., Iakovou, E., & Shi, W. (2020). Blockchain in global supply chains and cross border trade: a critical synthesis of the state-of-the-art, challenges and opportunities. International Journal of Production Research, 58(7), 2082-2099.
  • Davenport, T. H. (2018). From analytics to artificial intelligence. Journal of Business Analytics, 1(2), 73-80.
  • De Andrade Junqueira, C. A. (2023). Recent Customs Reforms in Brazil. Global Trade and Customs Journal, 18(11/12).
  • De Langen, P. W., & Chouly, A. (2009). Strategies of terminal operating companies in changing environments. International Journal of Logistics: Research and Applications, 12(6), 423-434.
  • Dekhtyaruk, M. T., Shao, M., Yang, S., Kontrobayeva, Z. D., & Vashchilina, E. (2021). Automated system of freight traffic optimisation in the interaction of various modes of transport. Periodicals of Engineering and Natural Sciences, 9(3), 844-857.
  • Dhieb, N., Ghazzai, H., Besbes, H., & Massoud, Y. (2020). A secure AI-driven architecture for automated insurance systems: Fraud detection and risk measurement. IEEE Access, 8, 58546-58558.
  • Drissi Elbouzidi, A., Ait El Cadi, A., Pellerin, R., Lamouri, S., Tobon Valencia, E., & Bélanger, M. J. (2023). The role of AI in warehouse digital twins: literature review. Applied Sciences, 13(11), 6746.
  • Du, P., He, X., Cao, H., Garg, S., Kaddoum, G., & Hassan, M. M. (2023). AI-based energy-efficient path planning of multiple logistics UAVs in intelligent transportation systems. Computer Communications, 207, 46-55.
  • Durlik, I., Miller, T., Kostecka, E., Łobodzińska, A., & Kostecki, T. (2024). Harnessing AI for Sustainable Shipping and Green Ports: Challenges and Opportunities. Applied Sciences, 14(14), 5994.
  • Dwivedi, D. N. (2024). The use of artificial intelligence in supply chain management and logistics. In Leveraging AI and Emotional Intelligence in Contemporary Business Organizations (pp. 306-313). IGI Global.
  • El Makhloufi, A. (2023). AI Application in Transport and Logistics: Opportunities and Challenges (An Exploratory Study). (2023 ed.) CoE City Net Zero, Faculty of Technology, Amsterdam Univeristy of Applied Sciences.
  • Eldred, M. E., Thatcher, J., Rehman, A., Gee, I., & Suboyin, A. (2023, January). Leveraging AI for inventory management and accurate forecast–an industrial field study. In SPE Middle East Intelligent Oil and Gas Symposium (p. D011S001R001). SPE.
  • Eyo-Udo, N. (2024). Leveraging artificial intelligence for enhanced supply chain optimization. Open Access Research Journal of Multidisciplinary Studies, 7(2), 001-015.
  • Falcone, E., Kent, J., & Fugate, B. (2020). Supply chain technologies, interorganizational network and firm performance: A case study of Alibaba Group and Cainiao. International Journal of Physical Distribution & Logistics Management, 50(3), 333-354.
  • Gayam, S. R., Yellu, R. R., & Thuniki, P. (2021). Optimizing Supply Chain Management through Artificial Intelligence: Techniques for Predictive Maintenance, Demand Forecasting, and Inventory Optimization. Journal of AI-Assisted Scientific Discovery, 1(1), 129-144.
  • Gołąbek, Ł., Pliszczuk, D., Maj, M., Bogacki, S., & Rzemieniak, M. (2023). Artificial intelligence in a distributed supply chain control model for the personalization and identification of products in real-time. Innovation in the Digital Economy (pp. 85-97). Routledge.
  • Gong, X. (2022, December). Optimization algorithm of logistics warehousing and distribution path based on artificial intelligence technology. In 2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE) (pp. 371-375). IEEE.
  • Gruzauskas, V., & Ragavan, D. (2020). Robotic process automation for document processing: A case study of a logistics service provider. Journal of Management, 36(2), 119-126.
  • Gupta, S., Ghardallou, W., Pandey, D. K., & Sahu, G. P. (2022). Artificial intelligence adoption in the insurance industry: Evidence using the technology–organization–environment framework. Research in International Business and Finance, 63, 101757.
  • Halme, E., Agbese, M., Alanen, H. K., Antikainen, J., Jantunen, M., Khan, A. A., & Abrahamsson, P. (2021). Implementation of ethically aligned design with ethical user stories in SMART terminal digitalization project: Use case passenger flow. arXiv Preprint arXiv:2111.06116.
  • Hryhorak, M. Y., Harmash, O. M., & Popkowski, T. (2023). Artıfıcıal Intellıgence in Supply Chaın Management: Opportunıtıes and Threats for Professıonal Competence. Electronic Scientific and Practical Publication in Economic Sciences, 24.
  • Hu, H., Zhang, Y., Wei, J., Zhan, Y., Zhang, X., Huang, S.,& Jiang, S. (2022). Alibaba vehicle routing algorithms enable rapid pick and delivery. INFORMS Journal on Applied Analytics, 52(1), 27-41.
  • Hunt, W., & O'Reilly. (2020). An Investigation of the Use of Artificial Intelligence and Machine Learning in Store-level Hiring at Walmart, United States of America [Data Collection]. Colchester, Essex: UK Data Service.
  • Ifty, M. E. S. (2025, July). The Use of Artificial Intelligence in Logistics. In Young Scientist, Conference/Jaunasis mokslininkas, konferencija (pp. 172-177).
  • Iyer, L. S. (2021). AI enabled applications towards intelligent transportation. Transportation Engineering, 5, 100083.
  • Jha, J., Vishwakarma, A. K., Chaithra, N., Nithin, A., Sayal, A., Gupta, A., & Kumar, R. (2023, February). Artificial intelligence and applications. In 2023 1st International Conference on Intelligent Computing and Research Trends (ICRT) (pp. 1-4). IEEE.
  • Kafando, I. (2020). How can Customs better leverage emerging AI technologies for more sustainable and smarter operations?. World Customs Journal, 14(2).
  • Kamau, E., Njeri, I., Abuko, L., & Mutua, J. M. (2024). Artıfıcial Intelligence-Powered Chatbots And Logistics Pricing at MAERSK Line Company. African Journal of Emerging Issues, 6(10), 1-9.
  • Karpova, N. P., & Evtodieva, T. E. (2023, April). Innovative Logistics in the Cumulative Knowledge System and Its Implementation Technology. In International Conference Engineering Innovations and Sustainable Development (pp. 178-184). Cham: Springer International Publishing.
  • Kern, J. (2021). The digital transformation of logistics: A review about technologies and their implementation status. The Digital Transformation of Logistics: Demystifying Impacts of the Fourth Industrial Revolution, 361-403.
  • Khopade, V. E., Shegokar, Y. M., Kale, V. V., Harane, S. A., & Umekar, M. J. (2023). Application Of Ai Tool In Pharmaceutical Warehouse Management: A Comprehensive Review. Journal of Research Administration, 5(2), 8052-8060.
  • Kmiecik, M. (2023). ChatGPT in third-party logistics–The game-changer or a step into the unknown?. Journal of Open Innovation: Technology, Market, and Complexity, 9(4), 100174.
  • Kriouich, M., Sarir, H., & Mahboub, O. (2023). Application of Artificial Intelligence in the Supply Chain: A Systematic Literature Review. In International Conference On Big Data and Internet of Things (pp. 388-401). Springer, Cham.
  • Krisknakumari, S. (2024). Artificial intelligence in enhancing operational efficiency in logistics and SCM. International Journal of Scientific Research in Science and Technology, 11(5), 316-323.
  • Kumar, P., Choubey, D., Amosu, O. R., & Ogunsuji, Y. M. (2024). AI-enhanced inventory and demand forecasting: Using AI to optimize inventory management and predict customer demand. World Journal of Advanced Research and Reviews, 23(1), 1931-1944.
  • Kuo, H. T., & Choi, T. M. (2024). Metaverse in transportation and logistics operations: An AI-supported digital technological framework. Transportation Research Part E: Logistics and Transportation Review, 185, 103496.
  • Kyrychenko, O. V., & Tursunov, H. M. (2023). Automated Systems for Classıfyıng Goods for Customs Purposes. Організаційний комітет, 264.
  • Lari, H. A., Vaishnava, K., & Manu, K. S. (2022). Artifical intelligence in E-commerce: Applications, implications and challenges. Asian Journal of Management, 13(3), 235-244.
  • Le, P. T., Do, T. M. T., Nguyen, T. T. H., Tran, N. B. M., Paramasivam, P., Le, T. T., ... & Chau, T. H. (2024). An insight into the Application of AI in maritime and Logistics toward Sustainable Transportation. JOIV: International Journal on Informatics Visualization, 8(1), 158-174.
  • Lior, A. (2021). Insuring AI: The role of insurance in artificial intelligence regulation. Harv. JL & Tech., 35, 467.
  • Liu, B. (2022). Artificial Intelligence and Machine Learning Capabilities and Application Programming Interfaces at Amazon, Google, and Microsoft (Doctoral dissertation, Massachusetts Institute of Technology).
  • Lysenko, S., Makovoz, O., & Perederii, T. (2023). The impact of artificial intelligence in logistics management on sustainability development of e-business. In European Dimensions of the Sustainable Development and Academic–Business Forum: Let's Revive Ukraine Together.
  • Madancian, M., Taherdoost, H., Javadi, M., Khan, I. U., Kalantari, A., & Kumar, D. (2023). The Impact of Artificial Intelligence on Supply Chain Management in Modern Business. In The International Conference on Artificial Intelligence and Smart Environment (pp. 566-573). Cham: Springer Nature Switzerland.
  • Malhotra, G., & Kharub, M. (2025). Elevating logistics performance: harnessing the power of artificial intelligence in e-commerce. The International Journal of Logistics Management, 36(1), 290-321.
  • Manocha, A., & Harnal, A. K. (2022). Optimization of Resources of Walmart Stores using Retail Analytics. FORE School of Management.
  • Mathur T., Kavitha S.N. (2024). Reviewing Optimization Techniques in Supply Chains: AI and Blockchain Perspectives. International Journal of Scientific Research in Engineering and Management. Volume: 08 Issue: 06.
  • Mediavilla, M. A., Dietrich, F., & Palm, D. (2022). Review and analysis of artificial intelligence methods for demand forecasting in supply chain management. Procedia CIRP, 107, 1126-1131.
  • Mohsen, B. M. (2023). Impact of artificial intelligence on supply chain management performance. Journal of Service Science and Management, 16(1), 44-58.
  • Mora Lozano, P. E., & Montoya-Torres, J. R. (2024). Global Supply Chains Made Visible through Logistics Security Management. Logistics, 8(1), 6.
  • Mukhtarov, A. (2023). The Role of Artificial Intellıgence, Sensors, And Other Innovations In Facilitating Logistics Processes In The United States. Věda a Perspektivy, (11 (30)).
  • Negruţiu, C., Onea, A., & Bădescu, R. (2020). Innovation trends in Romanian logistics providers industry. In Proceedings of the International Conference on Business Excellence (Vol. 14, No. 1, pp. 807-818).
  • Newman, N. (2018). Can blockchain transform transport?. Engineering & Technology, 13(6), 58-61.
  • Nguyen, A. (2020). How Artificial Intelligence can affect postal and parcel industry. Bachelor’s thesis School of Technology Degree Programme in International Logistics, JAMK University of Applied Sciences.
  • Nishar, S. (2024). Intelligent Decision-Making in Warehouse Management: How AI Automation Improves Inventory Tracking, Order Fulfillment, and Logistics Efficiency Compared to Drone Technology. Intelligent Control and Automation, 15(1), 1-8.
  • Nuruzzaman, M., & Hussain, O. K. (2018). A survey on chatbot implementation in customer service industry through deep neural networks. In 2018 IEEE 15th international conference on e-business engineering (ICEBE) (pp. 54-61). IEEE.
  • Olaoye, G., & Henry, E. (2024). Automated Route Optimization and Delivery Scheduling Using AI Algorithms. Machine learning overview. New Advances in Machine Learning, 2, 16-16.
  • Olomu Babatunde, F. S. I. (2023). The Role of Artificial Intelligence, Machine Learning and Data Analytics in Leveraging the Operations of the Nigeria Customs Service. International Journal of Latest Research in Humanities and Social Science (IJLRHSS), Volume 06 - Issue 11.
  • Pandey, B. K., Paramashivan, M. A., Kanike, U. K., Mahajan, D. A., Mahajan, R., George, A. S., & Hameed, A. S. H. (2024). Impacts of Artificial Intelligence and Machine Learning on Intelligent Supply Chains. In AI and Machine Learning Impacts in Intelligent Supply Chain (pp. 57-73). IGI Global.
  • Parveen, S., Chadha, R. S., Noida, C., Kumar, I. P., & Singh, J. (2022). Artificial Intelligence in Transportation Industry. Int. J. Innov. Sci. Res. Technol, 7, 1274-1283.
  • Pereira, E. T., & Shafique, M. N. (2023). The Implementation of Artificial Intelligence in Supply Chain. In International Conference On Innovative Computing And Communication (pp. 497-504). Singapore: Springer Nature Singapore.
  • Petriashvili, L., Kaishauri, T., & Otkhozoria, N. (2024). Artificial Intelligence for Decision Making in the Supply Chain. Journal of Technical Science and Technologies, 8(1), 30-34..
  • Ping, G., Zhu, M., Ling, Z., & Niu, K. (2024). Research on Optimizing Logistics Transportation Routes Using AI Large Models. Applied Science and Engineering Journal for Advanced Research, 3(4), 14-27.
  • Praveen, U., Farnaz, G., & Hatim, G. (2019). Inventory management and cost reduction of supply chain processes using AI based time-series forecasting and ANN modeling. Procedia Manufacturing, 38, 256-263.
  • Protic, S. M., Fikar, C., Voegl, J., & Gronalt, M. (2020). Analysing the impact of value added services at intermodal inland terminals. International Journal of Logistics Research and Applications, 23(2), 159-177.
  • Radovanovic, D. (2024). Some Information Communication Technologies in Logistics and Supply Chains. (Z. Cekerevac, Ed.) MEST Journal, 12(1), 72-79. doi:10.12709/mest.12.12.01.10
  • Rane, N., Choudhary, S., & Rane, J. (2024). Artificial intelligence for enhancing resilience. Journal of Applied Artificial Intelligence, 5(2), 1-33.
  • Rane, J., Amol Chaudhari, R., & Rane, N. (2025). Artificial Intelligence and Machine Learning for Supply Chain Resilience: Risk Assessment and Decision Making in Manufacturing Industry 4.0 and 5.0. Artificial Intelligence and Machine Learning for Supply Chain Resilience: Risk Assessment and Decision Making in Manufacturing Industry, 4.
  • Razzaq, A., Quach, S., & Thaichon, P. (2022). Artificial intelligence (AI)-integrated operation; insights into supply chain management. In Artificial Intelligence for Marketing Management (pp. 96-119). Routledge.
  • Riahi, Y., Saikouk, T., Gunasekaran, A., & Badraoui, I. (2021). Artificial intelligence applications in supply chain: A descriptive bibliometric analysis and future research directions. Expert Systems with Applications, 173, 114702.
  • Richey Jr, R. G., Chowdhury, S., Davis‐Sramek, B., Giannakis, M., & Dwivedi, Y. K. (2023). Artificial intelligence in logistics and supply chain management: A primer and roadmap for research. Journal of Business Logistics, 44(4), 532-549.
  • Rodríguez, C. B. R., Cañizares, D. R. G., González, J. A. K., Delgado, A. V. S., & Pérez, G. D. H. (2023). Artificial Intelligence Contribution to the Development of Cuban Port Logistics Chains. In Ibero-American Congress of Engineering and Project Management (pp. 257-273). Cham: Springer Nature Switzerland.
  • Sahoo, S. (2024). Demystifying AI-enabled Information Systems for Smarter Business Decisions. Paradigm, 09718907241243112.
  • Sarıoğlu, D. Ö. (2023). Predicting with AI (Artificial Intelligence)-Based Applications in Supply Chain. In: Korkmaz, E. V. (ed.), Selected Articles in the Field of Management and Organization II. Özgür Publications. DOI: https://doi.org/10.58830/ozgur.pub396.c1648
  • Schoepflin, D., Koch, J., Gomse, M., & Schüppstuhl, T. (2021). Smart material delivery unit for the production supplying logistics of aircraft. Procedia Manufacturing, 55, 455-462.
  • Schulte, P., & Lee, D. K. C. (2019). AI & Quantum Computing for Finance & Insurance: Fortunes and Challenges for China and America (Vol. 1). World Scientific.
  • Shah, I. A., Jhanjhi, N. Z., & Ray, S. K. (2024). Artificial Intelligence Applications in the Context of the Security Framework for the Logistics Industry. In Advances in Explainable AI Applications for Smart Cities (pp. 297-316). IGI Global.
  • Shahriar, A. (2023). A study on the environment and operations of Kuehne+ Nagel Bangladesh Limited. Bachelor Thesis of Business Administration, Brac Business School, Brac University.
  • Shatat, A. S., & Shatat, A. S. (2025). The dynamic support of artificial intelligence techniques in managing logistics activities. Human Systems Management, 44(3), 503-521.
  • Shobhana, N. (2024). AI-powered supply chains towards greater efficiency. In Complex AI Dynamics and Interactions in Management (pp. 229-249). IGI Global.
  • Shubailat, O., Al-Zaqeba, M., Madi, A., & Ababneh, A. (2024). Customs intelligence and risk management in sustainable supply chain for general customs department logistics. Uncertain Supply Chain Management, 12(1), 387-398.
  • Sied, A. (2024). Factors Influencing Digital Warehousing and AI Utilization in Modern Supply Chains: Implications for Warehouse Maintenance Costs and Product Pricing. International Journal of Financial Management and Research, 6(2), 30-45.
  • Sierszen, A., & Drabek, D. (2024). Learning Artificial Intelligence/Machine Learning Technologies Based On Amazon Web Services Solutions. In INTED2024 Proceedings (pp. 6798-6805). IATED.
  • Sirotic, M., & Jugovic, A. (2023). Revisiting Port Supply Chain Integration Complexity From the Perspective of Systems Leadership: A Bibliometric Analysis and Future Research Directions. Human Systems Engineering and Design (IHSED 2023): Future Trends and Applications, 112(112).
  • Skender, H. P., Ribarić, E., & Zaninović, P. A. (2022). Intelligent Solutions in the Supply Chains: Challenges for 3PL Providers. In Sustainable Logistics (pp. 139-156). Productivity Press.
  • Sohrabi, M. (2023). Artificial Intelligence in Logistic Industry. Implementation of Disruptive Technologies in Supply Chain Management, 73.
  • Soumpenioti, V., & Panagopoulos, A. (2023). AI Technology in the Field of Logistics. In 2023 18th International Workshop on Semantic and Social Media Adaptation & Personalization (SMAP) (pp. 1-6). IEEE.
  • Spindler, C., & Hoffmann, C. H. (2019). Data logistics and AI in insurance risk management. International Data Spaces Association.
  • Starkina E. S., Slepenkova E. V., Sobolev D. Y. (2023). Improving Retail Supply Chains Using Integrated Logistics Planning Technologies. Scientific Research and Development-Economics of the Firm. (4), 37-42. DOI: https://doi.org/10.12737/2306-627X-2023-12-4-37-42 Retrived from (Date of access 29.08.2024)
  • Subramanian, M., Agalya, M., Divya, V., & Harini, R. (2023). AI Based Warehouse Management System. In 2023 Intelligent Computing and Control for Engineering and Business Systems (ICCEBS) (pp. 1-5). IEEE.
  • Surabhi, S. N. R. D., & Buvvaji, H. V. (2024). The AI-Driven Supply Chain: Optimizing Engine Part Logistics For Maximum Efficiency. Educational Administration: Theory and Practice, 30(5), 8601-8608.
  • Tanish Mathur. (2024). Reviewing Optimization Techniques in Supply Chains: AI and Blockchain Perspectives. Indian Scientific Journal of Research in Engineering and Management, Vol. 08, Iss: 06, pp 1-5.
  • Tanyaş, M. (2008). "Lojistik Yönetimi." Lecture Notes, Okan University, İstanbul.
  • Toe Teoh, T., & Jin Goh, Y. (2023). AI in Supply Chain Management. In Artificial Intelligence in Business Management (pp. 225-255). Singapore: Springer Nature Singapore.
  • Tse, T., & Pun, N. (2024). Infrastructural capitalism in China: Alibaba, its corporate culture and three infrastructural mechanisms. Global Media and China, 9(1), 11-30.
  • Tsou, J. C. (2024). AI-Driven Automatıon In Warehouse Management Enhancing Efficiency And Accuracy. International Journal of Information, Business and Management, 16(4), 138-149.
  • Tung, T. M., Oanh, V. T. K., Cuc, T. T. K., & Lan, D. H. (2024). AI-Powered Innovation: How Entrepreneurs Can Leverage Artificial Intelligence for Business Success. Naturalista Campano, 28(1), 605-618.
  • Vandermerwe, S., & Erixon, D. (2023). Servitization of business updated: Now, new, next. European Management Journal, 41(4), 479-487.
  • Vanoy, R. J. A. (2023). Logistics 4.0: Exploring Artificial Intelligence Trends in Efficient Supply Chain Management. Data and Metadata, 2, 145-145.
  • Vinay, Sagar Yadav, Attul Kumar, Renu Narwal. (2024). Synergizing Intelligence: Revolutionizing Supply Chains with Blockchain and AI. International Journal of Advanced Research in Science, Communication and Technology. Volume 4, Issue 6, April 2024.
  • Wang, T., & Wijesinghe Mudiyanselage, G. M. (2024). The impact of companies’ using of new technologies on the quality of customer relationships: A study within logistics industry. Master Thesis , International Business Strategy, Linnaeus University.
  • Weber, F. D., & Schütte, R. (2019). State-of-the-art and adoption of artificial intelligence in retailing. Digital Policy, Regulation and Governance, 21(3), 264-279.
  • Woschank, M., Rauch, E., & Zsifkovits, H. (2020). A review of further directions for artificial intelligence, machine learning, and deep learning in smart logistics. Sustainability, 12(9), 3760.
  • Xiaoyu Xue. (2023). Analysis of the Impact and Application of Artificial Intelligence on the Development of Supply Chain Technology in Large Enterprises. Modern Economics & Management Forum, 4(5), pp.142-146.
  • Ying, W., & Dayong, S. (2005). Multi-agent framework for third party logistics in E-commerce. Expert Systems with Applications, 29(2), 431-436.
  • Younesse, O., Soumia, Z., & Souad, L. N. (2025). Advancing supply chain management through artificial intelligence: a systematic literature review. Indonesian Journal of Electrical Engineering and Computer Science, 38(1), 321-332.
  • Younis, H., Sundarakani, B., & Alsharairi, M. (2022). Applications of artificial intelligence and machine learning within supply chains: systematic review and future research directions. Journal of Modelling in Management, 17(3), 916-940.
  • Zeng, X., & Yi, J. (2023). Analysis of the Impact of Big Data and Artificial Intelligence Technology on Supply Chain Management. Symmetry, 15(9), 1801.

Yapay Zekâ Tabanlı Lojistik ve Tedarik Zinciri Yönetimi: Sektörel Uygulamalar ve Gelecek Perspektifleri

Yıl 2025, Cilt: 8 Sayı: 2, 217 - 240, 25.10.2025
https://doi.org/10.51513/jitsa.1569385

Öz

Son yıllarda lojistik ve tedarik zinciri yönetiminin dijitalleşmesi hız kazanmış ve yapay zekâ (YZ) kullanımıyla önemli ilerlemeler kaydedilmiştir. Geniş bir uygulama yelpazesi sunan yapay zekâ, lojistik ve tedarik zincirlerinde operasyonel verimliliğin artırılmasında önemli bir unsur haline gelmiştir. Bu makale, bu alanlardaki yapay zekâ uygulamalarını, hem gerçek dünya endüstri örnekleri hem de akademik literatür ile destekleyerek incelemektedir. Araştırma, sistematik literatür taraması (SLR) ve saha araştırmasını birleştiren bir metodoloji kullanmaktadır. Çalışmanın amacı, lojistik ve tedarik zincirlerinde yapay zekâ çözümlerinin nerelerde uygulandığını belirlemek ve bu uygulamaları gerçek dünya örnekleri ile ilişkilendirmektir. Bulgular, lojistikte yapay zekâ kullanımının 12 farklı alanı kapsayan teorik bir çerçeve içerisinde sınıflandırıldığını göstermektedir. Makalede Walmart, Amazon, UPS, DHL, Ocado, Alibaba, Maersk, Siemens, FedEx, Kuehne + Nagel ve DB Schenker gibi önde gelen şirketlerdeki yapay zekâ uygulamaları ayrıntılı olarak ele alınmaktadır. Sonuç olarak, bu makale yapay zekânın lojistik ve tedarik zinciri yönetiminde nasıl bir devrim yarattığını incelemekte ve bu dönüşümü hem endüstri uygulamaları hem de akademik literatür aracılığıyla ortaya koymaktadır. Elde edilen sonuçlar, yapay zekânın lojistik süreçlere giderek daha fazla entegre olduğunu ve etkisinin gün geçtikçe arttığını göstermektedir.

Etik Beyan

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Destekleyen Kurum

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Teşekkür

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Kaynakça

  • Aghazadeh, H., & Khoshnevis, M. (2024). Martechs and Digital Marketing+ (Types of Digital Marketing). Digital Marketing Technologies (pp. 187-226). Singapore: Springer Nature Singapore.
  • Aliyev, A. G., Shahverdiyeva, R. O., & Hagverdiyeva, U. H. (2024). Modernization of E-Commerce and Logistics Platforms of Enterprises Based on Artificial Intelligence Technology. Artificial Intelligence, Medical Engineering and Education (pp. 170-181). IOS Press.
  • Aljazzar, S. M. (2023). Harnessing Artificial Intelligence for Supply Chain Optimization: Enhanced Demand Prediction and Cost Reduction. In 2023 2nd International Engineering Conference on Electrical, Energy, and Artificial Intelligence (EICEEAI) (pp. 1-6). IEEE.
  • Amosu, O. R., Kumar, P., Ogunsuji, Y. M., Oni, S., & Faworaja, O. (2024). AI-driven demand forecasting: Enhancing inventory management and customer satisfaction. World Journal of Advanced Research and Reviews, 23(2), 708-719.
  • Annanth, V. K., Abinash, M., & Rao, L. B. (2021). Intelligent manufacturing in the context of industry 4.0: A case study of siemens industry. In Journal of Physics: Conference Series (Vol. 1969, No. 1, p. 012019). IOP Publishing.
  • Bharadiya, J. (2023). Artificial intelligence in transportation systems a critical review. American Journal of Computing and Engineering, 6(1), 34-45.
  • Bogue, R. (2022). Warehouse robot market boosted by Covid pandemic and technological innovations. Industrial Robot: the international journal of robotics research and application, 49(2), 181-186.
  • Bogue, R. (2024). The role of robots in logistics. Industrial Robot: the international journal of robotics research and application, 51(3), 381-386.
  • Boršoš, P., & Koman, G. (2025). Overview of Current Research on Artificial Intelligence in Logistics. LOGI: Scientific Journal on Transport and Logistics, 16(1), 13-24.
  • Boute, R. N., & Udenio, M. (2022). AI in logistics and supply chain management. Global logistics and supply chain strategies for the 2020s: Vital skills for the next generation (pp. 49-65). Cham: Springer International Publishing.
  • Brintrup, Alexandra. (2020). Artificial Intelligence in the Supply Chain: A Classification Framework and Critical Analysis of the Current State, in Thomas Y. Choi, and others (eds), The Oxford Handbook of Supply Chain Management, Oxford Academic.
  • Călinescu, G. (2022). The Applications of Blockchain and Artificial Intelligence in Logistics. The Romanian Economic Journal, 69, 84.
  • Cao, L. (2021). Artificial intelligence in retail: applications and value creation logics. International Journal of Retail & Distribution Management, 49(7), 958-976.
  • Chang, Y., Iakovou, E., & Shi, W. (2020). Blockchain in global supply chains and cross border trade: a critical synthesis of the state-of-the-art, challenges and opportunities. International Journal of Production Research, 58(7), 2082-2099.
  • Davenport, T. H. (2018). From analytics to artificial intelligence. Journal of Business Analytics, 1(2), 73-80.
  • De Andrade Junqueira, C. A. (2023). Recent Customs Reforms in Brazil. Global Trade and Customs Journal, 18(11/12).
  • De Langen, P. W., & Chouly, A. (2009). Strategies of terminal operating companies in changing environments. International Journal of Logistics: Research and Applications, 12(6), 423-434.
  • Dekhtyaruk, M. T., Shao, M., Yang, S., Kontrobayeva, Z. D., & Vashchilina, E. (2021). Automated system of freight traffic optimisation in the interaction of various modes of transport. Periodicals of Engineering and Natural Sciences, 9(3), 844-857.
  • Dhieb, N., Ghazzai, H., Besbes, H., & Massoud, Y. (2020). A secure AI-driven architecture for automated insurance systems: Fraud detection and risk measurement. IEEE Access, 8, 58546-58558.
  • Drissi Elbouzidi, A., Ait El Cadi, A., Pellerin, R., Lamouri, S., Tobon Valencia, E., & Bélanger, M. J. (2023). The role of AI in warehouse digital twins: literature review. Applied Sciences, 13(11), 6746.
  • Du, P., He, X., Cao, H., Garg, S., Kaddoum, G., & Hassan, M. M. (2023). AI-based energy-efficient path planning of multiple logistics UAVs in intelligent transportation systems. Computer Communications, 207, 46-55.
  • Durlik, I., Miller, T., Kostecka, E., Łobodzińska, A., & Kostecki, T. (2024). Harnessing AI for Sustainable Shipping and Green Ports: Challenges and Opportunities. Applied Sciences, 14(14), 5994.
  • Dwivedi, D. N. (2024). The use of artificial intelligence in supply chain management and logistics. In Leveraging AI and Emotional Intelligence in Contemporary Business Organizations (pp. 306-313). IGI Global.
  • El Makhloufi, A. (2023). AI Application in Transport and Logistics: Opportunities and Challenges (An Exploratory Study). (2023 ed.) CoE City Net Zero, Faculty of Technology, Amsterdam Univeristy of Applied Sciences.
  • Eldred, M. E., Thatcher, J., Rehman, A., Gee, I., & Suboyin, A. (2023, January). Leveraging AI for inventory management and accurate forecast–an industrial field study. In SPE Middle East Intelligent Oil and Gas Symposium (p. D011S001R001). SPE.
  • Eyo-Udo, N. (2024). Leveraging artificial intelligence for enhanced supply chain optimization. Open Access Research Journal of Multidisciplinary Studies, 7(2), 001-015.
  • Falcone, E., Kent, J., & Fugate, B. (2020). Supply chain technologies, interorganizational network and firm performance: A case study of Alibaba Group and Cainiao. International Journal of Physical Distribution & Logistics Management, 50(3), 333-354.
  • Gayam, S. R., Yellu, R. R., & Thuniki, P. (2021). Optimizing Supply Chain Management through Artificial Intelligence: Techniques for Predictive Maintenance, Demand Forecasting, and Inventory Optimization. Journal of AI-Assisted Scientific Discovery, 1(1), 129-144.
  • Gołąbek, Ł., Pliszczuk, D., Maj, M., Bogacki, S., & Rzemieniak, M. (2023). Artificial intelligence in a distributed supply chain control model for the personalization and identification of products in real-time. Innovation in the Digital Economy (pp. 85-97). Routledge.
  • Gong, X. (2022, December). Optimization algorithm of logistics warehousing and distribution path based on artificial intelligence technology. In 2022 International Symposium on Advances in Informatics, Electronics and Education (ISAIEE) (pp. 371-375). IEEE.
  • Gruzauskas, V., & Ragavan, D. (2020). Robotic process automation for document processing: A case study of a logistics service provider. Journal of Management, 36(2), 119-126.
  • Gupta, S., Ghardallou, W., Pandey, D. K., & Sahu, G. P. (2022). Artificial intelligence adoption in the insurance industry: Evidence using the technology–organization–environment framework. Research in International Business and Finance, 63, 101757.
  • Halme, E., Agbese, M., Alanen, H. K., Antikainen, J., Jantunen, M., Khan, A. A., & Abrahamsson, P. (2021). Implementation of ethically aligned design with ethical user stories in SMART terminal digitalization project: Use case passenger flow. arXiv Preprint arXiv:2111.06116.
  • Hryhorak, M. Y., Harmash, O. M., & Popkowski, T. (2023). Artıfıcıal Intellıgence in Supply Chaın Management: Opportunıtıes and Threats for Professıonal Competence. Electronic Scientific and Practical Publication in Economic Sciences, 24.
  • Hu, H., Zhang, Y., Wei, J., Zhan, Y., Zhang, X., Huang, S.,& Jiang, S. (2022). Alibaba vehicle routing algorithms enable rapid pick and delivery. INFORMS Journal on Applied Analytics, 52(1), 27-41.
  • Hunt, W., & O'Reilly. (2020). An Investigation of the Use of Artificial Intelligence and Machine Learning in Store-level Hiring at Walmart, United States of America [Data Collection]. Colchester, Essex: UK Data Service.
  • Ifty, M. E. S. (2025, July). The Use of Artificial Intelligence in Logistics. In Young Scientist, Conference/Jaunasis mokslininkas, konferencija (pp. 172-177).
  • Iyer, L. S. (2021). AI enabled applications towards intelligent transportation. Transportation Engineering, 5, 100083.
  • Jha, J., Vishwakarma, A. K., Chaithra, N., Nithin, A., Sayal, A., Gupta, A., & Kumar, R. (2023, February). Artificial intelligence and applications. In 2023 1st International Conference on Intelligent Computing and Research Trends (ICRT) (pp. 1-4). IEEE.
  • Kafando, I. (2020). How can Customs better leverage emerging AI technologies for more sustainable and smarter operations?. World Customs Journal, 14(2).
  • Kamau, E., Njeri, I., Abuko, L., & Mutua, J. M. (2024). Artıfıcial Intelligence-Powered Chatbots And Logistics Pricing at MAERSK Line Company. African Journal of Emerging Issues, 6(10), 1-9.
  • Karpova, N. P., & Evtodieva, T. E. (2023, April). Innovative Logistics in the Cumulative Knowledge System and Its Implementation Technology. In International Conference Engineering Innovations and Sustainable Development (pp. 178-184). Cham: Springer International Publishing.
  • Kern, J. (2021). The digital transformation of logistics: A review about technologies and their implementation status. The Digital Transformation of Logistics: Demystifying Impacts of the Fourth Industrial Revolution, 361-403.
  • Khopade, V. E., Shegokar, Y. M., Kale, V. V., Harane, S. A., & Umekar, M. J. (2023). Application Of Ai Tool In Pharmaceutical Warehouse Management: A Comprehensive Review. Journal of Research Administration, 5(2), 8052-8060.
  • Kmiecik, M. (2023). ChatGPT in third-party logistics–The game-changer or a step into the unknown?. Journal of Open Innovation: Technology, Market, and Complexity, 9(4), 100174.
  • Kriouich, M., Sarir, H., & Mahboub, O. (2023). Application of Artificial Intelligence in the Supply Chain: A Systematic Literature Review. In International Conference On Big Data and Internet of Things (pp. 388-401). Springer, Cham.
  • Krisknakumari, S. (2024). Artificial intelligence in enhancing operational efficiency in logistics and SCM. International Journal of Scientific Research in Science and Technology, 11(5), 316-323.
  • Kumar, P., Choubey, D., Amosu, O. R., & Ogunsuji, Y. M. (2024). AI-enhanced inventory and demand forecasting: Using AI to optimize inventory management and predict customer demand. World Journal of Advanced Research and Reviews, 23(1), 1931-1944.
  • Kuo, H. T., & Choi, T. M. (2024). Metaverse in transportation and logistics operations: An AI-supported digital technological framework. Transportation Research Part E: Logistics and Transportation Review, 185, 103496.
  • Kyrychenko, O. V., & Tursunov, H. M. (2023). Automated Systems for Classıfyıng Goods for Customs Purposes. Організаційний комітет, 264.
  • Lari, H. A., Vaishnava, K., & Manu, K. S. (2022). Artifical intelligence in E-commerce: Applications, implications and challenges. Asian Journal of Management, 13(3), 235-244.
  • Le, P. T., Do, T. M. T., Nguyen, T. T. H., Tran, N. B. M., Paramasivam, P., Le, T. T., ... & Chau, T. H. (2024). An insight into the Application of AI in maritime and Logistics toward Sustainable Transportation. JOIV: International Journal on Informatics Visualization, 8(1), 158-174.
  • Lior, A. (2021). Insuring AI: The role of insurance in artificial intelligence regulation. Harv. JL & Tech., 35, 467.
  • Liu, B. (2022). Artificial Intelligence and Machine Learning Capabilities and Application Programming Interfaces at Amazon, Google, and Microsoft (Doctoral dissertation, Massachusetts Institute of Technology).
  • Lysenko, S., Makovoz, O., & Perederii, T. (2023). The impact of artificial intelligence in logistics management on sustainability development of e-business. In European Dimensions of the Sustainable Development and Academic–Business Forum: Let's Revive Ukraine Together.
  • Madancian, M., Taherdoost, H., Javadi, M., Khan, I. U., Kalantari, A., & Kumar, D. (2023). The Impact of Artificial Intelligence on Supply Chain Management in Modern Business. In The International Conference on Artificial Intelligence and Smart Environment (pp. 566-573). Cham: Springer Nature Switzerland.
  • Malhotra, G., & Kharub, M. (2025). Elevating logistics performance: harnessing the power of artificial intelligence in e-commerce. The International Journal of Logistics Management, 36(1), 290-321.
  • Manocha, A., & Harnal, A. K. (2022). Optimization of Resources of Walmart Stores using Retail Analytics. FORE School of Management.
  • Mathur T., Kavitha S.N. (2024). Reviewing Optimization Techniques in Supply Chains: AI and Blockchain Perspectives. International Journal of Scientific Research in Engineering and Management. Volume: 08 Issue: 06.
  • Mediavilla, M. A., Dietrich, F., & Palm, D. (2022). Review and analysis of artificial intelligence methods for demand forecasting in supply chain management. Procedia CIRP, 107, 1126-1131.
  • Mohsen, B. M. (2023). Impact of artificial intelligence on supply chain management performance. Journal of Service Science and Management, 16(1), 44-58.
  • Mora Lozano, P. E., & Montoya-Torres, J. R. (2024). Global Supply Chains Made Visible through Logistics Security Management. Logistics, 8(1), 6.
  • Mukhtarov, A. (2023). The Role of Artificial Intellıgence, Sensors, And Other Innovations In Facilitating Logistics Processes In The United States. Věda a Perspektivy, (11 (30)).
  • Negruţiu, C., Onea, A., & Bădescu, R. (2020). Innovation trends in Romanian logistics providers industry. In Proceedings of the International Conference on Business Excellence (Vol. 14, No. 1, pp. 807-818).
  • Newman, N. (2018). Can blockchain transform transport?. Engineering & Technology, 13(6), 58-61.
  • Nguyen, A. (2020). How Artificial Intelligence can affect postal and parcel industry. Bachelor’s thesis School of Technology Degree Programme in International Logistics, JAMK University of Applied Sciences.
  • Nishar, S. (2024). Intelligent Decision-Making in Warehouse Management: How AI Automation Improves Inventory Tracking, Order Fulfillment, and Logistics Efficiency Compared to Drone Technology. Intelligent Control and Automation, 15(1), 1-8.
  • Nuruzzaman, M., & Hussain, O. K. (2018). A survey on chatbot implementation in customer service industry through deep neural networks. In 2018 IEEE 15th international conference on e-business engineering (ICEBE) (pp. 54-61). IEEE.
  • Olaoye, G., & Henry, E. (2024). Automated Route Optimization and Delivery Scheduling Using AI Algorithms. Machine learning overview. New Advances in Machine Learning, 2, 16-16.
  • Olomu Babatunde, F. S. I. (2023). The Role of Artificial Intelligence, Machine Learning and Data Analytics in Leveraging the Operations of the Nigeria Customs Service. International Journal of Latest Research in Humanities and Social Science (IJLRHSS), Volume 06 - Issue 11.
  • Pandey, B. K., Paramashivan, M. A., Kanike, U. K., Mahajan, D. A., Mahajan, R., George, A. S., & Hameed, A. S. H. (2024). Impacts of Artificial Intelligence and Machine Learning on Intelligent Supply Chains. In AI and Machine Learning Impacts in Intelligent Supply Chain (pp. 57-73). IGI Global.
  • Parveen, S., Chadha, R. S., Noida, C., Kumar, I. P., & Singh, J. (2022). Artificial Intelligence in Transportation Industry. Int. J. Innov. Sci. Res. Technol, 7, 1274-1283.
  • Pereira, E. T., & Shafique, M. N. (2023). The Implementation of Artificial Intelligence in Supply Chain. In International Conference On Innovative Computing And Communication (pp. 497-504). Singapore: Springer Nature Singapore.
  • Petriashvili, L., Kaishauri, T., & Otkhozoria, N. (2024). Artificial Intelligence for Decision Making in the Supply Chain. Journal of Technical Science and Technologies, 8(1), 30-34..
  • Ping, G., Zhu, M., Ling, Z., & Niu, K. (2024). Research on Optimizing Logistics Transportation Routes Using AI Large Models. Applied Science and Engineering Journal for Advanced Research, 3(4), 14-27.
  • Praveen, U., Farnaz, G., & Hatim, G. (2019). Inventory management and cost reduction of supply chain processes using AI based time-series forecasting and ANN modeling. Procedia Manufacturing, 38, 256-263.
  • Protic, S. M., Fikar, C., Voegl, J., & Gronalt, M. (2020). Analysing the impact of value added services at intermodal inland terminals. International Journal of Logistics Research and Applications, 23(2), 159-177.
  • Radovanovic, D. (2024). Some Information Communication Technologies in Logistics and Supply Chains. (Z. Cekerevac, Ed.) MEST Journal, 12(1), 72-79. doi:10.12709/mest.12.12.01.10
  • Rane, N., Choudhary, S., & Rane, J. (2024). Artificial intelligence for enhancing resilience. Journal of Applied Artificial Intelligence, 5(2), 1-33.
  • Rane, J., Amol Chaudhari, R., & Rane, N. (2025). Artificial Intelligence and Machine Learning for Supply Chain Resilience: Risk Assessment and Decision Making in Manufacturing Industry 4.0 and 5.0. Artificial Intelligence and Machine Learning for Supply Chain Resilience: Risk Assessment and Decision Making in Manufacturing Industry, 4.
  • Razzaq, A., Quach, S., & Thaichon, P. (2022). Artificial intelligence (AI)-integrated operation; insights into supply chain management. In Artificial Intelligence for Marketing Management (pp. 96-119). Routledge.
  • Riahi, Y., Saikouk, T., Gunasekaran, A., & Badraoui, I. (2021). Artificial intelligence applications in supply chain: A descriptive bibliometric analysis and future research directions. Expert Systems with Applications, 173, 114702.
  • Richey Jr, R. G., Chowdhury, S., Davis‐Sramek, B., Giannakis, M., & Dwivedi, Y. K. (2023). Artificial intelligence in logistics and supply chain management: A primer and roadmap for research. Journal of Business Logistics, 44(4), 532-549.
  • Rodríguez, C. B. R., Cañizares, D. R. G., González, J. A. K., Delgado, A. V. S., & Pérez, G. D. H. (2023). Artificial Intelligence Contribution to the Development of Cuban Port Logistics Chains. In Ibero-American Congress of Engineering and Project Management (pp. 257-273). Cham: Springer Nature Switzerland.
  • Sahoo, S. (2024). Demystifying AI-enabled Information Systems for Smarter Business Decisions. Paradigm, 09718907241243112.
  • Sarıoğlu, D. Ö. (2023). Predicting with AI (Artificial Intelligence)-Based Applications in Supply Chain. In: Korkmaz, E. V. (ed.), Selected Articles in the Field of Management and Organization II. Özgür Publications. DOI: https://doi.org/10.58830/ozgur.pub396.c1648
  • Schoepflin, D., Koch, J., Gomse, M., & Schüppstuhl, T. (2021). Smart material delivery unit for the production supplying logistics of aircraft. Procedia Manufacturing, 55, 455-462.
  • Schulte, P., & Lee, D. K. C. (2019). AI & Quantum Computing for Finance & Insurance: Fortunes and Challenges for China and America (Vol. 1). World Scientific.
  • Shah, I. A., Jhanjhi, N. Z., & Ray, S. K. (2024). Artificial Intelligence Applications in the Context of the Security Framework for the Logistics Industry. In Advances in Explainable AI Applications for Smart Cities (pp. 297-316). IGI Global.
  • Shahriar, A. (2023). A study on the environment and operations of Kuehne+ Nagel Bangladesh Limited. Bachelor Thesis of Business Administration, Brac Business School, Brac University.
  • Shatat, A. S., & Shatat, A. S. (2025). The dynamic support of artificial intelligence techniques in managing logistics activities. Human Systems Management, 44(3), 503-521.
  • Shobhana, N. (2024). AI-powered supply chains towards greater efficiency. In Complex AI Dynamics and Interactions in Management (pp. 229-249). IGI Global.
  • Shubailat, O., Al-Zaqeba, M., Madi, A., & Ababneh, A. (2024). Customs intelligence and risk management in sustainable supply chain for general customs department logistics. Uncertain Supply Chain Management, 12(1), 387-398.
  • Sied, A. (2024). Factors Influencing Digital Warehousing and AI Utilization in Modern Supply Chains: Implications for Warehouse Maintenance Costs and Product Pricing. International Journal of Financial Management and Research, 6(2), 30-45.
  • Sierszen, A., & Drabek, D. (2024). Learning Artificial Intelligence/Machine Learning Technologies Based On Amazon Web Services Solutions. In INTED2024 Proceedings (pp. 6798-6805). IATED.
  • Sirotic, M., & Jugovic, A. (2023). Revisiting Port Supply Chain Integration Complexity From the Perspective of Systems Leadership: A Bibliometric Analysis and Future Research Directions. Human Systems Engineering and Design (IHSED 2023): Future Trends and Applications, 112(112).
  • Skender, H. P., Ribarić, E., & Zaninović, P. A. (2022). Intelligent Solutions in the Supply Chains: Challenges for 3PL Providers. In Sustainable Logistics (pp. 139-156). Productivity Press.
  • Sohrabi, M. (2023). Artificial Intelligence in Logistic Industry. Implementation of Disruptive Technologies in Supply Chain Management, 73.
  • Soumpenioti, V., & Panagopoulos, A. (2023). AI Technology in the Field of Logistics. In 2023 18th International Workshop on Semantic and Social Media Adaptation & Personalization (SMAP) (pp. 1-6). IEEE.
  • Spindler, C., & Hoffmann, C. H. (2019). Data logistics and AI in insurance risk management. International Data Spaces Association.
  • Starkina E. S., Slepenkova E. V., Sobolev D. Y. (2023). Improving Retail Supply Chains Using Integrated Logistics Planning Technologies. Scientific Research and Development-Economics of the Firm. (4), 37-42. DOI: https://doi.org/10.12737/2306-627X-2023-12-4-37-42 Retrived from (Date of access 29.08.2024)
  • Subramanian, M., Agalya, M., Divya, V., & Harini, R. (2023). AI Based Warehouse Management System. In 2023 Intelligent Computing and Control for Engineering and Business Systems (ICCEBS) (pp. 1-5). IEEE.
  • Surabhi, S. N. R. D., & Buvvaji, H. V. (2024). The AI-Driven Supply Chain: Optimizing Engine Part Logistics For Maximum Efficiency. Educational Administration: Theory and Practice, 30(5), 8601-8608.
  • Tanish Mathur. (2024). Reviewing Optimization Techniques in Supply Chains: AI and Blockchain Perspectives. Indian Scientific Journal of Research in Engineering and Management, Vol. 08, Iss: 06, pp 1-5.
  • Tanyaş, M. (2008). "Lojistik Yönetimi." Lecture Notes, Okan University, İstanbul.
  • Toe Teoh, T., & Jin Goh, Y. (2023). AI in Supply Chain Management. In Artificial Intelligence in Business Management (pp. 225-255). Singapore: Springer Nature Singapore.
  • Tse, T., & Pun, N. (2024). Infrastructural capitalism in China: Alibaba, its corporate culture and three infrastructural mechanisms. Global Media and China, 9(1), 11-30.
  • Tsou, J. C. (2024). AI-Driven Automatıon In Warehouse Management Enhancing Efficiency And Accuracy. International Journal of Information, Business and Management, 16(4), 138-149.
  • Tung, T. M., Oanh, V. T. K., Cuc, T. T. K., & Lan, D. H. (2024). AI-Powered Innovation: How Entrepreneurs Can Leverage Artificial Intelligence for Business Success. Naturalista Campano, 28(1), 605-618.
  • Vandermerwe, S., & Erixon, D. (2023). Servitization of business updated: Now, new, next. European Management Journal, 41(4), 479-487.
  • Vanoy, R. J. A. (2023). Logistics 4.0: Exploring Artificial Intelligence Trends in Efficient Supply Chain Management. Data and Metadata, 2, 145-145.
  • Vinay, Sagar Yadav, Attul Kumar, Renu Narwal. (2024). Synergizing Intelligence: Revolutionizing Supply Chains with Blockchain and AI. International Journal of Advanced Research in Science, Communication and Technology. Volume 4, Issue 6, April 2024.
  • Wang, T., & Wijesinghe Mudiyanselage, G. M. (2024). The impact of companies’ using of new technologies on the quality of customer relationships: A study within logistics industry. Master Thesis , International Business Strategy, Linnaeus University.
  • Weber, F. D., & Schütte, R. (2019). State-of-the-art and adoption of artificial intelligence in retailing. Digital Policy, Regulation and Governance, 21(3), 264-279.
  • Woschank, M., Rauch, E., & Zsifkovits, H. (2020). A review of further directions for artificial intelligence, machine learning, and deep learning in smart logistics. Sustainability, 12(9), 3760.
  • Xiaoyu Xue. (2023). Analysis of the Impact and Application of Artificial Intelligence on the Development of Supply Chain Technology in Large Enterprises. Modern Economics & Management Forum, 4(5), pp.142-146.
  • Ying, W., & Dayong, S. (2005). Multi-agent framework for third party logistics in E-commerce. Expert Systems with Applications, 29(2), 431-436.
  • Younesse, O., Soumia, Z., & Souad, L. N. (2025). Advancing supply chain management through artificial intelligence: a systematic literature review. Indonesian Journal of Electrical Engineering and Computer Science, 38(1), 321-332.
  • Younis, H., Sundarakani, B., & Alsharairi, M. (2022). Applications of artificial intelligence and machine learning within supply chains: systematic review and future research directions. Journal of Modelling in Management, 17(3), 916-940.
  • Zeng, X., & Yi, J. (2023). Analysis of the Impact of Big Data and Artificial Intelligence Technology on Supply Chain Management. Symmetry, 15(9), 1801.
Toplam 120 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Yapay Zeka (Diğer), Lojistik, Tedarik Zinciri Yönetimi
Bölüm Makaleler
Yazarlar

İlknur Yardımcı Coşkun 0000-0002-7183-6142

Erken Görünüm Tarihi 22 Ekim 2025
Yayımlanma Tarihi 25 Ekim 2025
Gönderilme Tarihi 17 Ekim 2024
Kabul Tarihi 17 Eylül 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 8 Sayı: 2

Kaynak Göster

APA Yardımcı Coşkun, İ. (2025). Artificial Intelligence-Driven Logistics and Supply Chain Management: Industry Applications and Future Perspectives. Akıllı Ulaşım Sistemleri ve Uygulamaları Dergisi, 8(2), 217-240. https://doi.org/10.51513/jitsa.1569385