考量競爭者訂價行為與承攬業者購買行為之航空貨運訂價決策模式

Abstract

航空貨物運輸在國際貿易中扮演著重要的角色，對部分航空公司之營收更具有顯著的貢獻。航空公司的航空貨運營收來自於有託運需求的承攬業者，而承攬業者在規劃期內分配給不同航空公司的託運量，會因為各航空公司的運價差異產生連動；因此航空公司難以估算訂價後被分配的貨運量。因航空公司沒有系統化工具的協助，實務上仍僅依賴經驗法則訂定航空貨運運輸價格。故本研究提出研究方法，協助航空公司能掌握承攬業者託運之貨量分配行為及競爭者的訂價行為，將有助於進行優質航空貨運訂價，達到利潤最大化。本研究建議運用ARIMAX模式及VAR模式預測一條航線的貨運總需求及個別承攬業者的總貨運需求。接著運用解釋型多元迴歸模式針對承攬業者之貨量分配行為建立模式；即探討航空公司與競爭者在訂價差改變時，承攬業者委託給各航空公司的貨量比例的改變。在上述方式掌握承攬業者貨量分配行為前提下，本研究建立一個非線性規劃模式，並且提出運用疊代方式進行求解可以最大化航空公司在規劃期間利潤之航空貨運訂價。本研究運用2012年1月至2016年12月航空公司及承攬業者之歷史資料驗證所提出決策架構與模式，可作為航空公司訂價決策之輔助與參考。

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.