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

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.