Lojistik Sektöründe Yapay Zeka: Verimlilik, Otomasyon ve Günümüz Trendleri

Alkinani, M. H., Almazroi, A. A., Adhikari, M., & Menon, V. G. (2022). Artificial intelligence-empowered logistic traffic management system using empirical intelligent XGBoost technique in vehicular edge networks. IEEE Transactions on Intelligent Transportation Systems, 24(4), 4499-4508.

Baryannis, G., Validi, S., Dani, S., & Antoniou, G. (2018). Supply chain risk management and artificial intelligence: state of the art and future research directions. International Journal of Production Research, 57(7), 2179–2202. https://doi.org/10.1080/00207543.2018.1530476

Blecken, A. (2010), "Supply chain process modelling for humanitarian organizations", International Journal of Physical Distribution & Logistics Management, Vol. 40 No. 8/9, pp. 675-692. https://doi.org/10.1108/09600031011079328

Chottani, A., Hastings, G., Murnane, J., & Neuhaus, F. (2018). McKinsey. https://www.mckinsey.com/industries/travel-logistics-and-infrastructure/our-insights/distraction-or-disruption-autonomous-trucks-gain-ground-in-us-logistics#/

Dey, A., LaGuardia, P. and Srinivasan, M. (2011), "Building sustainability in logistics operations: a research agenda", Management Research Review, Vol. 34 No. 11, pp. 1237-1259. https://doi.org/10.1108/01409171111178774

DHL. (2023). Freight Connections. https://dhl-freight-connections.com/en/trends/logistics-trends-2023-2024/

Dong, K., Romanov, I., Mclellan, C., & Esen, A. F. (2022). Recent text-based research and applications in railways: A critical review and future trends. Engineering Applications of Artificial Intelligence, 116, 105435. https://doi.org/10.1016/j.engappai.2022.105435

Hangl, J., Behrens, V. J., & Krause, S. (2022). Barriers, drivers, and social considerations for AI adoption in supply chain management: a tertiary study. Logistics, 6(3), 63.

Hompel, M., & Schmidt, T. (2006). Warehouse management: automation and organisation of warehouse and order picking systems. Springer Science & Business Media.

HUAWEI. (2024). Amplifying Industrial Digitalization & Intelligence Practice White Paper. Huawei Technologies Co. Ltd.

Ivanov, D., & Dolgui, A. (2020). A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0. Production Planning & Control, 32(9), 775–788. https://doi.org/10.1080/09537287.2020.1768450

Jebbor I, Benmamoun Z, Hachmi H. (2024). Revolutionizing cleaner production: The role of artificial intelligence in enhancing sustainability across industries. Journal of Infrastructure, Policy and Development. 8(10): 7455. https://doi.org/10.24294/jipd.v8i10.7455

Jindal, A., Sharma, S. K., Sangwan, K. S., & Gupta, G. (2021). Modelling supply chain agility antecedents using fuzzy DEMATEL. Procedia CIRP, 98, 436-441. https://doi.org/10.1016/j.procir.2021.01.130

Kumar, V., Mishra, N., Chan, F. T. S., & Verma, A. (2011). Managing warehousing in an agile supply chain environment: an F-AIS algorithm based approach. International Journal of Production Research, 49(21), 6407–6426. https://doi.org/10.1080/00207543.2010.528057

Li, F. (2022). [Retracted] Logistics Distribution Path Optimization Algorithm Based on Intelligent Management System. Computational Intelligence and Neuroscience, 2022(1), https://doi.org/10.1155/2022/3699990.

Li, X., Ng, X. Y. C., Zhou, Y., & Yuen, K. F. (2021). A ranking of critical competencies for shore-based maritime logistics executives in the digital era. Technology Analysis & Strategic Management, 35(7), 919–934. https://doi.org/10.1080/09537325.2021.1988920

Minea, M., Dumitrescu, C. M., & Dima, M. (2021). Robotic Railway Multi-Sensing and Profiling Unit Based on Artificial Intelligence and Data Fusion. Sensors (Basel, Switzerland), 21(20), 6876. https://doi.org/10.3390/s21206876

Mohsen, B. (2023) Impact of Artificial Intelligence on Supply Chain Management Performance. Journal of Service Science and Management, 16, 44-58. https://doi.org/10.4236/jssm.2023.161004

Morales, V. E., Sanchez, J., Escalera, J., Sharma, V., & Wheeler, B. (2024). Artificial intelligence & aviation: Content analysis of research publications from 2013-2023. https://doi.org/10.62704/10057/28469

Pandey (2023). Digital Transformation In Supply Chain Management: Role of IoT. International Journal of Advanced Research in Management and Social Sciences. 12(12), 55-62.

Pandian, A. P. (2019). Artificial intelligence application in smart warehousing environment for automated logistics. Journal of Artificial Intelligence, 1(02), 63-72. https://doi.org/10.36548/jaicn.2019.2.002

Phusakulkajorn, W., Núñez, A., Wang, H., Jamshidi, A., Zoeteman, A., Ripke, B., ... & Li, Z. (2023). Artificial intelligence in railway infrastructure: Current research, challenges, and future opportunities. Intelligent Transportation Infrastructure, 2, liad016. https://doi.org/10.1093/iti/liad016

Pilon, R. V. (2023). Artificial Intelligence in Commercial Aviation: Use cases and emerging strategies. Routledge.

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. https://doi.org/10.1111/jbl.12364

Rosendorff, A., Hodes, A., & Fabian, B. (2021). Artificial Intelligence for last-mile logistics-Procedures and architecture. The Online Journal of Applied Knowledge Management (OJAKM), 9(1), 46-61.

Sadou, A. M., & Njoya, E. T. (2023). Applications of artificial intelligence in the air transport industry: a bibliometric and systematic literature review. Journal of Aerospace Technology and Management, 15. https://doi.org/10.1590/jatm.v15.1312

Tang, R., De Donato, L., Besinović, N., Flammini, F., Goverde, R. M., Lin, Z., ... & Wang, Z. (2022). A literature review of Artificial Intelligence applications in railway systems. Transportation Research Part C: Emerging Technologies, 140. https://doi.org/10.1016/j.trc.2022.103679

Tsidulko, J. (2024). Oracle. https://www.oracle.com/scm/ai-supply-chain/#challenges

Tsolakis, N., Niedenzu, D., Simonetto, M., Dora, M., & Kumar, M. (2021). Supply network design to address United Nations Sustainable Development Goals: A case study of blockchain implementation in Thai fish industry. Journal of Business Research, 131, 495-519. https://doi.org/10.1016/j.jbusres.2020.08.003

Wang, Y., Yao, Y., & Li, Y. (2022). The Impact of Artificial Intelligence Development on the Logistics Industry Talent Demand and Countermeasures. In DMI (pp. 349-359). https://doi:10.3233/FAIA230035

Zhang, H., Hu, R., Chen, A., Lei, Y., & Qu, H. (2024, June). Enhancing Concrete Supply Chain Efficiency in Civil Engineering through Digital Transformation: A Comprehensive Review. In 2024 8th International Conference on Civil Architecture and Structural Engineering (ICCASE 2024) (pp. 741-753). Atlantis Press. https://doi.org/10.2991/978-94-6463-449-5_73

Zhang, J., & Zhang, J. (2023). Artificial intelligence applied on traffic planning and management for rail transport: a review and perspective. Discrete Dynamics in Nature and Society, 2023(1). https://doi.org/10.1155/2023/1832501

Zhu, X., Liu, N., & Shi, Y. (2022). Artificial intelligence technology in modern logistics system. International Journal of Technology, Policy and Management, 22(1-2), 66-81. https://doi.org/10.1504/IJTPM.2022.122537