Smart Logistics 5.0: Integrated Transportation Innovation for Global Supply Chain Efficiency
DOI:
https://doi.org/10.62872/22prmm50Keywords:
Integrated Transport, Smart Logistics 5.0, Supply ChainAbstract
Smart Logistics 5.0 represents the latest evolution in supply chain management, integrating digital
technologies (IoT, edge computing, AI, blockchain, big data) and physical automation (robotics,
autonomous vehicles, drones) with human-centered principles, sustainability, and resilience. This
systematic literature review examines publications from 2020–2025 to understand how multimodal
integrated transport innovations improve efficiency, transparency, and resilience in global supply chains.
The review methodology involved searches in major databases (Scopus, Web of Science, Google Scholar)
using keywords related to Industry 5.0, Smart Logistics, integrated transport, IoT, blockchain, and
autonomous logistics; records were then screened against clear inclusion criteria and analyzed
thematically. Findings indicate that IoT combined with edge computing enhances operational visibility and
real-time orchestration; AI and big data analytics improve forecasting accuracy and route optimization;
and blockchain supports traceability and administrative automation via smart contracts. Furthermore,
multimodal transport integration (sea, land, air, rail) enabled by digital platforms has been shown to lower
door-to-door costs, accelerate deliveries, and bolster network adaptability to disruptions. Major barriers
include fragmented data standards, high upfront investment needs, regulatory issues (notably for
autonomous vehicles and drones), and workforce skills gaps. Distinct from earlier reviews, this study
emphasizes the role of multimodal transport innovation within the Smart Logistics 5.0 framework as a key
driver of a more efficient, resilient, and sustainable global supply chain.
Downloads
References
1. Andres, B., Díaz-Madroñero, M., Soares, A. L., & Poler, R. (2024). Enabling Technologies to Support Supply Chain Logistics 5.0. IEEE Access, 12, 43889–43906. https://doi.org/10.1109/ACCESS.2024.3374194
2. Araz, O. M., Choi, T. M., Olson, D., & Salman, F. S. (2022). Improving the efficiency of last-mile package deliveries using hybrid driver helpers. Decision Sciences, 53(1), 5–20. https://doi.org/https://doi.org/10.1111/deci.12559
3. Azarian, M., Jafari, N., & Yu, H. (2022). Smart Logistics in Industry 5.0: History. MDPI Encyclopedia.
4. Bansal, M., Chana, I., & Clarke, S. (2020). A Survey on IoT Big Data. ACM Computing Surveys (CSUR), 53, 1–59. https://doi.org/10.1145/3419634
5. Bernardo, R., Sousa, J., & Gonçalves, P. (2022). Survey on robotic systems for internal logistics. Journal of Manufacturing Systems. https://doi.org/10.1016/j.jmsy.2022.09.014
6. Bhargava, A., Bhargava, D., Kumar, P., Sajja, G. S., & Ray, S. (2022). Industrial IoT and AI implementation in vehicular logistics and supply chain management for vehicle mediated transportation systems. International Journal of System Assurance Engineering and Management, 13, 673–680. https://doi.org/10.1007/s13198-021-01581-2
7. Bui, T.-D., Tsai, F.-M., Tseng, M., Tan, R., Yu, K., & Lim, M. (2020). Sustainable supply chain management towards disruption and organizational ambidexterity: A data driven analysis. Sustainable Production and Consumption, 26, 373–410. https://doi.org/10.1016/j.spc.2020.09.017
8. Cecil, P. (2024). Cross-Border Supply Chain Optimization: Strategies for Managing International Operations While Maintaining Speed and Cost Efficiency. International Journal of Scientific Research and Management (IJSRM), 12(05), 6565–6588. https://doi.org/10.18535/ijsrm/v12i05.em23
9. Daraojimba, A. I., Oriekhoe, O. I., Oyeyemi, O. P., Bello, B. G., Omotoye, G. B., & Adefemi, A. (2024). Blockchain in supply chain management: A review of efficiency, transparency, and innovation. International Journal of Science and Research Archive. https://doi.org/10.30574/ijsra.2024.11.1.0028
10. Deloitte. (2021). Using blockchain to drive supply chain transparency: Use cases and future outlook. Deloitte Insights. https://www2.deloitte.com/content/dam/Deloitte/us/Documents/us-ent-supply-chain-pov.pdf
11. Guerreiro, A. M., Maas, J., Kosch, M., Henke, M., Küster, T., Straube, F., & Albayrak, S. (2025). Autonomous Van and Robot Last-Mile Logistics Platform: A Reference Architecture and Proof of Concept Implementation. Logistics, 9(1), 1–15. https://doi.org/10.3390/logistics9010010
12. Hajjaji, Y., Boulila, W., Farah, I., Romdhani, I., & Hussain, A. (2021). Big data and IoT-based applications in smart environments: A systematic review. Comput. Sci. Rev., 39, 100318. https://doi.org/10.1016/j.cosrev.2020.100318
13. Han, X., Meng, Z., Xia, X., Liao, X., He, Y., Zheng, Z., Wang, Y., Xiang, H., Zhou, Z., Gao, L., Fan, L., Li, Y., & Jiaqi. (2024). Foundation Intelligence for Smart Infrastructure Services in Transportation 5.0. IEEE Transactions on Intelligent Vehicles, 9, 39–47. https://doi.org/10.1109/TIV.2023.3349324
14. Hirna, O. (2025). DIGITAL TECHNOLOGIES IN SUPPLY CHAIN MANAGEMENT. Economic Scope. https://doi.org/10.30838/ep.199.20-25
15. Hsu, C.-H., Cai, X.-Q., Zhang, T.-Y., & Ji, Y.-L. (2024). Smart Logistics Facing Industry 5.0: Research on Key Enablers and Strategic Roadmap. Sustainability. https://doi.org/10.3390/su16219183
16. Ibiyemi, M. O., & Olutimehin, D. O. (2024). Revolutionizing logistics: The impact of autonomous vehicles on supply chain efficiency. International Journal of Scientific Research Updates, 8(1), 009–026. https://doi.org/10.53430/ijsru.2024.8.1.0042
17. Idrissi, Z. K., Lachgar, M., & Hrimech, H. (2024). Blockchain, IoT and AI in logistics and transportation: A systematic review. Transport Economics and Management, 2, 275–285. https://doi.org/https://doi.org/10.1016/j.team.2024.09.002
18. Ivanov, D. (2022). Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic. Annals of Operations Research, 319(1), 1411–1431. https://doi.org/10.1007/s10479-020-03640-6
19. Jafari, N., Azarian, M., & Yu, H. (2022). Moving from Industry 4.0 to Industry 5.0: What Are the Implications for Smart Logistics? Logistics. https://doi.org/10.3390/logistics6020026
20. Kazim, A. M. J. H., & Baskaran, K. (2025). Examining How Integrated Smart Logistics Ecosystems Enhance E-Commerce Efficiency in the UAE Retail Sector. Journal of Posthumanism. https://doi.org/10.63332/joph.v5i5.1731
21. Kovács, G., & Sigala, I. F. (2020). Lessons learned from humanitarian logistics to manage supply chain disruptions. Journal of Supply Chain Management, 57. https://doi.org/10.1111/jscm.12253
22. Kurniawan, D. A. (2024). Multimodal Logistics for Resilient and Sustainable Global Supply Chains: Strategic Insights from Integrated Transport Systems. Sinergi International Journal of Logistics. https://doi.org/10.61194/sijl.v2i4.731
23. Lu, H. P., Hsu, C. L., & Hsu, H. Y. (2005). An empirical study of the effect of perceived risk upon intention to use online applications. Information Management and Computer Security, 13(2). https://doi.org/10.1108/09685220510589299
24. Mishra, R., & Pradhan, T. (2025). Smart Logistics: The AI Revolution in Supply Chain Optimization and its Challenges. International Journal of Advanced Research in Science, Communication and Technology. https://doi.org/10.48175/ijarsct-24915
25. 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
26. Ran, L., Shi, Z., & Geng, H. (2024). Blockchain Technology for Enhanced Efficiency in Logistics Operations. IEEE Access, 12, 152873–152885. https://doi.org/10.1109/ACCESS.2024.3458434
27. Samuels, A. (2024). Examining the integration of artificial intelligence in supply chain management from Industry 4.0 to 6.0: a systematic literature review. Frontiers in Artificial Intelligence, 7, 1477044. https://doi.org/10.3389/frai.2024.1477044
28. Sari, N., Azka, N. ., Praja, W. ., & Yudanta, R. (2023). TRAFFIC INFORMATION SYSTEM in Bunga Rampai Implementasi Sistem Transportasi Cerdas. CV. Media Sains Indonesia. https://store.medsan.co.id/detail/978-623-195-619-4-implementasi-sistem-transportasi-cerdas
29. Schlegelmilch, B. (2022). Global Supply Chains. Management for Professionals. https://doi.org/10.1007/978-3-030-90665-8_9
30. Sundari, G., Das, N., Kalra, H., Satapathy, S., Samrat, B., & R, M. (2025). Exploring the Potential of IoT and Sensor-Enabled Logistics Management for Supply Chain Optimization. 2025 International Conference on Automation and Computation (AUTOCOM), 386–391. https://doi.org/10.1109/AUTOCOM64127.2025.10956496
31. Szeredi, V. V., Trenka, Z., & Pogátsnik, M. (2024). Smart Logistics and Sustainability in Logistics 5.0. 2024 IEEE 6th International Symposium on Logistics and Industrial Informatics (LINDI), 109–114. https://doi.org/10.1109/LINDI63813.2024.10820412
32. Taj, S., Imran, A. S., Kastrati, Z., Daudpota, S. M., Memon, R. A., & Ahmed, J. (2023). IoT-based supply chain management: A systematic literature review. Internet of Things (Netherlands), 24(October), 100982. https://doi.org/10.1016/j.iot.2023.100982
33. Winkelhaus, S., & Grosse, E. H. (2020). Logistics 4.0: a systematic review towards a new logistics system. International Journal of Production Research, 58(1), 18–43. https://doi.org/10.1080/00207543.2019.1612964
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Kasrim (Author)
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
