Article

Risk Analysis of Air Cargo Discrepancies within the Air Freight Supply Chain by Utilizing Innovative Batch Mode, Blockchain, and Clustering Methods

Muhammad Salman ORCID
    Received
    30 Nov 2025
    Published
    03 Nov 2025

    Abstract

    There is no integration mechanism available between independent systems (sales and shipment), so it creates uncertainty in the air freight industry. Regarding the problems, freight forwarders or airline sales officers can make a manifest for the shippers; however, various airlines plan different routes for shipping services. But unfortunately, it provides transaction discrepancies between independent systems. The proposed methods integrate two datasets in a central repository and detect discrepancies between sales and shipment systems using novel batch mode, update, and blockchain methods. Furthermore, it provides output to clustering algorithms to highlight the risk factors or disruptions in two- or three-dimensional forms. In other words, the proposed mechanisms establish a bridge between freight forwarders and airline industries, so it minimizes the transaction discrepancies in the air freight system. Besides this, a managerial insights investigation revealed that data consistency, real-time transactions, technology, and supply chain disruptions are the most important topics. The findings indicate that the air freight industry increases the revenue and boosts the economy after implementing the proposed methods in the production environment. The proposed methods compute the theoretical and practical time complexities, which are about T (n) = n, so they are suitable for production environments. Statistically, it provides a significant result. Finally, it resolves inconsistent issues between independent systems. It establishes a balance in the air freight supply chain industry.

    Keywords

    Airline and Freight Forwarders, Batch Mode and Blockchain Methods, Clustering Algorithms, Detect Discrepancies between Sales and Shipment Systems, Supply Chain Disruptions, Uncertainty in the Air Freight Industry

    References
    1. [1] Matthews, R., Rutherford, B.N., Edmondson, D., et al., 2022. Uncertainty in Industrial Markets: The COVID-19 Pandemic. Industrial Marketing Management. 102, 364–376. DOI: https://doi.org/10.1016/j.indmarman.2022.02.006
    2. [2] Detwal, P.K., Soni, G., Jakhar, S.K., et al., 2023. Machine Learning-Based Technique for Predicting Vendor Incoterm (Contract) in Global Omnichannel Pharmaceutical Supply Chain. Journal of Business Research. 158, 113688. DOI: https://doi.org/10.1016/j.jbusres.2023.113688
    3. [3] Merkert, R., 2023. Air Cargo and Supply Chain Management. In: Sarkis, J. (Ed.). The Palgrave Handbook of Supply Chain Management. Palgrave Macmillan: Cham, Switzerland. pp. 1–18. DOI: https://doi.org/10.1007/978-3-030-89822-9_90-1
    4. [4] Shaban, I.A., Chan, F.T.S., Chung, S.H., 2021. A Novel Model to Manage Air Cargo Disruptions Caused by Global Catastrophes such as COVID-19. Journal of Air Transport Management. 95, 102086. DOI: https://doi.org/10.1016/j.jairtraman.2021.102086
    5. [5] Alexander, D.W., Merkert, R., 2021. Applications of Gravity Models to Evaluate and Forecast US International Air Freight Markets Post-GFC. Transport Policy. 104, 52–62. DOI: https://doi.org/10.1016/j.tranpol.2020.04.004
    6. [6] Zhang, L., Hou, M., Liu, Y., et al., 2022. Measuring Beijing’s International Air Connectivity and Suggestions for Improvement Post COVID-19. Transport Policy. 116, 132–143. DOI: https://doi.org/10.1016/j.tranpol.2021.11.015
    7. [7] Oum, T.H., Wu, X., Wang, K., 2024. Impact of Air Connectivity on Bilateral Service Export and Import Trade: The Case of China. Transport Policy. 148, 219–233. DOI: https://doi.org/10.1016/j.tranpol.2024.01.015
    8. [8] Subramaniam, G., Mahmoud, M.A., 2021. Fraud Detection in Shipping Industry Using K-NN Algorithm. International Journal of Advanced Computer Science and Applications. 12(4). DOI: https://doi.org/10.14569/IJACSA.2021.0120460
    9. [9] Smith, L.D., Bilir, C., 2023. Modelling Airline Operations at Major Commercial Airports for Strategic Decision Support. Transportation Development Research. 1, 242–256. DOI: https://doi.org/10.55121/tdr.v1i1.101
    10. [10] Zong, Z., Feng, T., Wang, J., et al., 2025. Deep Reinforcement Learning for Demand-Driven Services in Logistics and Transportation Systems: A Survey. ACM Transactions on Knowledge Discovery from Data. 19(4), 89. DOI: https://doi.org/10.1145/3708325
    11. [11] Nguyen, Q.H., Nguyen, I.V., 2025. The Relationship between Air Freight and International Trade. Journal of Southeast Asian Economies. 42(1), 70–92. DOI: https://www.jstor.org/stable/27378053
    12. [12] Hong, S.-J., Kim, W., Hiatt, B., 2025. Examining Airport Agility at Air Cargo Hub Airports. Journal of Air Transport Management. 122, 102710. DOI: https://doi.org/10.1016/j.jairtraman.2024.102710
    13. [13] Michielsen, S., Gevaers, R., Dewulf, W., 2025. A Historical Overview and Analysis of E-Commerce’s Milestones and Its Growing Connection with Air Transport. Journal of Shipping and Trade. 10(14). DOI: https://doi.org/10.1186/s41072-025-00203-5
    14. [14] Chung, S., Kim, H., Choi, D., 2025. Impacts of Internal and External Uncertainties on Logistics Service Flexibility in Cross-Border E-Commerce Logistics: Evidence from South Korea. Systems. 13(12), 1082. DOI: https://doi.org/10.3390/systems13121082
    15. [15] Ong, C.S., Ahmad, W.N.K.W., 2025. The Relationship between Challenges Faced by Logistics Industry in Johor and the Implementation of Sustainable Logistics Practices. Research in Management of Technology and Business. 6(2), 33–45. Available from: https://penerbit.uthm.edu.my/periodicals/index.php/rmtb/article/view/20062
    16. [16] Andrejić, M., Pajić, V., 2025. Strengthening the Sustainability and Resilience of Global Supply Chains: An Integrated Risk Assessment Framework for International Logistics Security. Opportunities and Challenges in Sustainability. 4(1), 56–69. DOI: https://doi.org/10.56578/ocs040105
    17. [17] Wu, J., 2025. The Evolution of Supply Chains: From Simple to Complex, from Linear to Network. Springer Series in Supply Chain Management. 26, 3–27. DOI: https://doi.org/10.1007/978-981-96-3228-2_1
    18. [18] Yang, Y.-C., Chen, Y.-C., 2025. Risk Management of Transaction Security Using Blockchain Technology in the International Logistics Industry. Sustainable Futures. 10, 101537. DOI: https://doi.org/10.1016/j.sftr.2025.101537
    19. [19] Gajdos, A., Gajdos, A., 2025. Trends in Logistics – Future Plans. Annales Universitatis Mariae Curie-Sklodowska, Sectio H – Oeconomia. 59(2), 57–92. DOI: https://doi.org/10.17951/h.2025.59.2.57-72
    20. [20] Rashid, A.A., See, K.F., Yu, M.-M., 2024. Measuring Airline Efficiency Using a Dynamic Network Data Envelopment Analysis in the Presence of Innovation Capital. Technological Forecasting and Social Change. 206, 123457. DOI: https://doi.org/10.1016/j.techfore.2024.123457
    21. [21] Raj, A., Mukherjee, A.A., Jabbour, A.B.L.S., et al., 2022. Supply Chain Management during and post COVID-19 Pandemic: Mitigation Strategies and Practical Lessons Learned. Journal of Business Research. 142, 1125–1139. DOI: https://doi.org/10.1016/j.jbusres.2022.01.037
    22. [22] Estima, J., da Cunha, P.R., Barata, J., 2025. Blockchain in Shipment Transportation. In Handbook of Blockchain Technology. Edward Elgar Publishing: Cheltenham, UK. pp. 261–276. DOI: https://doi.org/10.4337/9781803922805.00029
    23. [23] Lau, C.W., Liu, J., Ma, X., et al., 2024. Performance Analysis of a Blockchain-Based Messaging System Implementation for Air Cargo Supply Chains. International Journal of Production Research. 63(14), 5428–5451. DOI: https://doi.org/10.1080/00207543.2024.2407903
    24. [24] Haq, I., Nandal, V., Uppal, H., 2025. Blockchain Applications in Aviation: Securing Transactions, Streamlining Operations, and Improving Passenger Experience. Information Systems Engineering and Management. 57(14), 131–154. DOI: https://doi.org/10.1007/978-3-031-95341-5_7
    25. [25] Barua, B., Kaiser, M.S., 2025. A Next-Generation Approach to Airline Reservations: Integrating Cloud Microservices with AI and Blockchain for Enhanced Operational Performance. IET Blockchain. 5(1), e70020. DOI: https://doi.org/10.1049/blc2.70020
    26. [26] Javaid, M., Haleem, A., 2025. Role of Digital Twin and Blockchain in Logistics and Supply Chain Management. In: Nguyen, T.A. (Ed.). Digital Twin and Blockchain for Sensor Networks in Smart Cities. Elsevier: Amsterdam, Netherlands. pp. 243–264. DOI: https://doi.org/10.1016/B978-0-443-30076-9.00012-1
    27. [27] Zohourian, M.A., Pamidimukkala, A., Kermanshachi, S., 2025. Application of Blockchain Technology in the Transportation Industry. In Proceedings of the International Conference on Transportation and Development, Glendale, AZ, USA, June 8–11, 2025; pp. 261–276. DOI: https://doi.org/10.1061/9780784486191.033
    28. [28] Sarkis, J., Bai, C., Wang, Y., 2025. Multistakeholder Production and Logistics Management Through Blockchain Technology Applications. International Journal of Production Research. 63(14), 5031–5042. DOI: https://doi.org/10.1080/00207543.2025.2511567
    29. [29] Zineb, K.I., Hrimech, H., Lachgar, M., 2025. Blockchain in Logistics: The Case of TradeLens and Its Impact on Supply Chain Efficiency. In Proceedings of the 16th International Conference on Logistics and Supply Chain Management (LOGISTIQUA), Casablanca, Morocco, 28–30 May 2025;  pp. 1–7. DOI: https://doi.org/10.1109/LOGISTIQUA66323.2025.11122825
    30. [30] Sahoo, R., Bhowmick, B., Tiwari, M.K., 2021. Smart Integration of Blockchain in Air Cargo Handling for Profit Maximization. IFIP Advances in Information and Communication Technology. 631, 107–114. DOI: https://doi.org/10.1007/978-3-030-85902-2_12
    31. [31] Huang, Z., Zheng, H., Li, C., et al., 2024. Application of Machine Learning-Based K-Means Clustering for Financial Fraud Detection. Academic Journal of Science and Technology. 10(1), 33–39. DOI: https://doi.org/10.54097/74414c90
    32. [32] Salman, M., 2023. A Novel Clustering Method With Consistent Data in a Three-Dimensional Graphical Format Over Existing Clustering Mechanisms. Information Sciences. 649, 119634. DOI: https://doi.org/10.1016/j.ins.2023.119634
    33. [33] Vaghani, A., Sood, K., Yu, S., 2022. Security and QoS Issues in Blockchain-Enabled Next-Generation Smart Logistic Networks: A Tutorial. Blockchain: Research and Applications. 3(3), 100082. DOI: https://doi.org/10.1016/j.bcra.2022.100082
    34. [34] Yang, W., Wen, J., Wang, F., et al., 2025. Trade Dependency and Technological Specialization in the ICT Supply Chain: Structural Dynamics and Strategic Autonomy in Major Economies. Telecommunications Policy. 49(9), 103037. DOI: https://doi.org/10.1016/j.telpol.2025.103037
    35. [35] Çay, A., Bayram, B., Gökyılmaz, G., et al., 2025. Contextual Anomaly Detection in Logistics and Supply Chain Management. In Proceedings of the 2025 10th International Conference on Machine Learning Technologies (ICMLT), Helsinki, Finland, 23–25 May 2025; pp. 427–432. DOI: https://doi.org/10.1109/ICMLT65785.2025.11193370
    36. [36] Van Bockstaele, V., Buyle, S., Dewulf, W., 2023. Solving the Mystery of Discrepancies and Double Counting in Air Cargo through Demand and Supply Big Data Analysis. Journal of the Air Transport Research Society. 1(1), 81–100. DOI: https://doi.org/10.59521/6A961EF46EB809C5
    37. [37] Jurgelane-Kaldava, I., Effenberger, W.V., Batenko, A., et al., 2025. Digitalization of Air Cargo Supply Chains: A Case Study of Latvia. Systems. 13(6), 468. DOI: https://doi.org/10.3390/systems13060468
    38. [38] Hong, S.-J., Kim, H.W., Niranjan, S., 2023. Challenges to the Air Cargo Business of Combination Carriers: Analysis of Two Major Korean Airlines. Journal of Air Transport Management. 108, 102360. DOI: https://doi.org/10.1016/j.jairtraman.2023.102360
    39. [39] Sarker, S., Henningsson, S., Jensen, T., 2021. The Use of Blockchain as a Resource for Combating Corruption in Global Shipping: An Interpretive Case Study. Journal of Management Information Systems. 38(2), 338–373. DOI: https://doi.org/10.1080/07421222.2021.1912919
    40. [40] Poleshkina, I., 2021. Blockchain in Air Cargo: Challenges of New World. MATEC Web of Conferences. 341, 00021. DOI: https://doi.org/10.1051/matecconf/202134100021
    41. [41] Mofatteh, M.Y., Valilai, O.F., 2025. A Blockchain Ecosystem Model for a Sustainable Last-Mile Delivery Operation Management. Transportation Engineering. 21, 100379. DOI: https://doi.org/10.1016/j.treng.2025.100379
    42. [42] Drljača, M., Štimac, I., Vidović, A., et al., 2020. Sustainability of the Air Cargo Handling Process in the Context of Safety and Environmental Aspects. Journal of Advanced Transportation. 2020(1), 1232846. DOI: https://doi.org/10.1155/2020/1232846
    43. [43] Yadav, P., Bhosale, R., Sahoo, R., et al., 2022. Advances in Air Cargo Financing Using a Consortium Blockchain. IFAC-PapersOnLine. 55(10), 737–742. DOI: https://doi.org/10.1016/j.ifacol.2022.09.497
    44. [44] Lakhwani, T.S., 2025. Integrating 5PL Frameworks with Drone-Based Last-Mile Delivery: A Model for Future-Ready Logistics. Transportation Development Research. 3(1), 27–46. DOI: https://doi.org/10.55121/tdr.v3i1.449
    Back to top