Institute of Transportation, MOTC

       Air cargo plays an important role in the international trading, and it also has significant impact on the revenue of some air carriers. The revenue of air carriers results from cargo demands of forwarders, but the allocation of a forwarder’s demands could vary with the charges offered by the carriers. Therefore, it could be too complicated and difficult for the carriers to estimate the allocated amount of freight from forwarders. Since the carriers usually do not have systematic tools to assist their decision-making, most of them reply only on rules of thumb in practice. Therefore, we would propose methodology to assist the carriers to characterize forwarders’ shipping behavior and competitors’ pricing behavior, so that they would be able to make good pricing so as to maximize their profit. This study proposes to apply an ARIMAX model and a VAR model for the forecasting of the demand of individual forwarders and total demand in a particular route. Then, we employed a multiple-regression model to characterize a forwarder’s behavior in the allocation of cargo demand given difference unit-prices from the carriers. Finally, given the forwarder’s shipping behavior as above, we propose a nonlinear programming model and an iterative scheme to bring up with an optimal pricing to maximize a cargo carrier’s profit in the planning horizon. This study used the historical data from 2012 to 2016 to verify the proposed framework and models, we conclude that it may serve as support tools for the air-cargo carriers in pricing decision-making.