Smart, Secure, and Connected: A Blockchain-Supported Logistics Ecosystem for Saudi Arabia’s 2034 FIFA World Cup
Main Article Content
Abstract
This research examines how Saudi Arabia might achieve Vision 2030's broad goals while meeting the demands of significant events, such as the 2034 FIFA World Cup, by leveraging high-tech logistics hubs. It examines how supply chain resilience may be enhanced by artificial intelligence (AI) through safety stock, cross-docking for speedy delivery, and intelligent tracking. Using a mixed-methods approach that includes expert interviews, case studies, and performance measurements, the study illustrates how innovations boost productivity, reduce delays, and ensure a smooth flow of commodities. Beyond operations, the study explains how logistics innovation creates avenues for entrepreneurship, supporting start-ups in sustainable transport technology and AI logistics solutions. The study claims that the use of AI, crossdocking, and high-capacity logistics nodes enhances Saudi Arabia's ability to host international logistics events and solidifies its standing as a developing center for supply chain innovation and entrepreneurship.
Downloads
Article Details
Section

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
How to Cite
References
Nicoletti, B. (2025). AI transformation of logistics. In Artificial intelligence for logistics 5.0: From foundation models to agentic AI (pp. 107–131). Cham: Springer Nature Switzerland. DOI: https://doi.org/10.1007/978-3-031-94046-0_2
Saudi Vision 2030. (2025). Overview. https://www.vision2030.gov.sa/
Chan, H. K., Cheng, Y., Shi, Y., & Sheng, J. (2025). Guest editorial: Platform-enabled supply chain and logistics excellence: Research challenges and opportunities. International Journal of Physical Distribution & Logistics Management, 55(6), 569–581.
DOI: https://doi.org/10.1108/IJPDLM-07-2025-561
Alotaibi, F. J. (2022). Cost-benefit analysis of the Saudi Land Bridge Project (No. AFITENSMS22S054).
https://apps.dtic.mil/sti/trecms/pdf/AD1181252.pdf
Toorajipour, R., Sohrabpour, V., Nazarpour, A., Oghazi, P., & Fischl, M. (2021). Artificial intelligence in supply chain management: A systematic literature review. Journal of Business Research, 122, 502–517. DOI: https://doi.org/10.1016/j.jbusres.2020.09.009
Mohsen, B. M. (2023). Developments of digital technologies related to supply chain management. Procedia Computer Science, 220, 788–795. DOI: https://doi.org/10.1016/j.procs.2023.03.105
Kiani Mavi, R., Goh, M., Kiani Mavi, N., Jie, F., Brown, K., Biermann, S., & Khanfar, A. A. (2020). Cross-
Docking: A systematic literature review. Sustainability, 12(11), 4789. https://www.mdpi.com/2071-1050/12/11/4789#
Offiong, U. P., Szopik‐Depczyńska, K., & Ioppolo, G. (2025). FinTech innovations for sustainable development: A comprehensive literature review and future directions. Sustainable Development. https://onlinelibrary.wiley.com/doi/abs/10.1002/sd.70068
Baryannis, G., Validi, S., Dani, S., & Antoniou, G. (2019). Supply chain risk management and artificial intelligence: State of the art and future research directions. International Journal of Production Research, 57(7), 2179–2202. DOI: https://doi.org/10.1080/00207543.2018.1530476
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. DOI: https://doi.org/10.1016/j.eswa.2021.114702
Treiblmaier, H., & Rejeb, A. (2023). Exploring blockchain for disaster prevention and relief: A comprehensive framework based on industry case studies. Journal of Business Logistics, 44(4), 550–582. DOI: https://doi.org/10.1111/jbl.12345