航空公司航班客位需求與訂位艙等規劃

Abstract

訂位艙等規劃係依不同費率等級的訂位需求，規劃同一等級座艙中、不同票價費率等級預留座位數，使得艙位作最有效利用，以獲取最大收益，其方式乃藉由低價與高價艙位配置數量間的調整來求取最大的期望利潤，以期航空公司在載客率與獲利能力間達到滿意的結果。然而最佳的訂位艙位規劃乃取決於準確的訂位需求預測，當訂位需求預測模式推測出各艙位可能的載客量及對應的機率時，即可經由收益最大化原則，選定最佳艙位規劃，與制定最適之開票期限及候補容量。 本研究以個別旅客的客位需求、個別旅客對機票效期所感受之不便成本價值，與航空公司所制定各類票價產品之時間限制、票價間之關係為基礎，構建一訂位艙等規劃之解析性模式。本研究提出新的航班客位需求模式，以個別旅客對機票效期時間價值之觀念來反映旅客真正之需求，不僅可分析旅客真正選擇其票價產品之機率，此外亦可分析旅客轉移至其他票價產品，以及轉移至其他競爭航空公司之機率。進一步在航空公司追求最大化收益之企業目標下，本研究將航空公司開放訂位時間切割成多個決策時段，藉由各票價產品所能吸引之旅運需求量及其對應的機率，以決定各決策時段、各費率等級之預留艙位數，及在航空公司預留各費率等級之艙位數限制，與已訂位旅客未出現開票之影響下，以決定航空公司之可供候補容量，與制定最適之開票日期。目的是欲探討影響供需兩面互動之重要因素，以分析航班客位需求並進行訂位艙等規劃，與制定最適開票時間。 最後，以目前台灣國籍航空公司之旅客訂位資料進行實證分析，以闡述本研究模式之應用。研究結果顯示，航空公司所制定之票價產品若無法符合航空旅客需求，將會降低航空公司之期望營收。而在考慮由候補旅客所獲得之期望營收上，本研究實證之結果較諸文獻方法所得結果更符合實際航空公司之營收，而當航空公司所制定之開票日期越接近航班起飛時間，則所能獲得之期望營收越高。本研究所發展的模式在實務上可供航空公司進行制定各類別票價與訂位艙等時間限制組合之艙等規劃之參考，及研擬與規劃相關之營收管理策略。

In order to improve revenues in a very competitive market, it is common for airlines to sell a pool of identical seats at different prices according to different booking classes. Under the circumstances, the airline booking inventory control seeks to maximize revenue by determining whether a booking request at a specific point should be accepted or denied. The objective of airline booking inventory control is to maximize the expected revenue by allocating the seats of different fare classes. Hopefully, it can reach satisfactory trade-off between the flight load rate and profit. However, optimum booking seat inventory control depends on accurate booking demand prediction. This paper brings up a new idea of flight passenger demand model by reflecting passengers’ actual demands with their values of time towards different fare class expiration dates. Through the formulation and results of flight passenger demand model, the paper can analyze and obtain not only the probabilities of passengers’ choice of their fare classes, but also the probabilities of diverting to other fare classes, and to other competitive airlines. Furthermore, this paper develops a booking seat inventory model by maximizing the airline’s revenues to decide the optimum booking policy, which can find the reservation level of each fare class at every decision period during the entire booking period. In addition, the model also can determine the most appropriate waiting capacity, and the deadline of passenger ticketing. Finally, an example using actual booking records of an international airline is used to demonstrate the model. The result shows that if the airline’s fare products do not satisfy passengers’ demands, its revenues will decline. With the consideration of booking cancellation and waiting capacities, the model result of the study is more coincide with actual data as compared with those using existing methods found in literature. Besides, the result also shows that when the deadline of passenger ticketing is closer to the date of flight departure, the airline’s expected revenue will increase. The results of the paper can be used as guidelines on determining the optimal revenue management plans for airline operators.