航空公司乾/濕租策略聯盟之機隊規劃

Abstract

航空產業對於全球景氣波動的敏感度非常高，航空公司的機隊容量對於其營運成本亦有很大的影響，因此如何因應景氣循環，做最適當的機隊規劃以降低航空公司營運成本與增加營收一直是個很重要的課題。近年來航空公司利用策略聯盟的方式，藉由資訊與設備共享降低營運成本已有顯著的成效；實務上聯盟方式多半採用共用班號(code sharing)與航機/設備/人員相互承租之乾租(dry lease)/濕租(wet lease)聯盟方式，然而相關研究多著重共用班號與實務分析，尚未從機隊規劃的角度，構建數學模式深入探討。若航空公司能在機隊規劃上加以考慮策略聯盟，不僅能提供更大的規劃彈性，更能精簡機隊，節省成本，達到更高的成本效益。 若以全球的航空市場觀點而言，各家航空公司所服務的市場需求波動可能不盡相同，故產生容量不足或過剩的程度亦不一致。若航空公司於機隊容量過剩/不足時，能將航機出租/承租給聯盟的夥伴航空公司，則出租者可藉此賺取租金，避免航機閒置，節省維修成本，提高航機利用率；承租者亦可減少購買新航機或向航機租賃公司承租航機所產生的巨額成本。本研究從機隊規劃的角度切入，考慮聯盟後航機相互租賃與聯合維修所產生的成本效益，分別建立相關的成本函數，將研究時段分為數個決策時區，以動態規劃模式構建航空公司在每個決策時點，配合未來旅客預測量之波動狀態，應如何決策其機隊容量與乾/濕租協定內容。由所建立的相關成本函數可估算直接、間接營運成本，再以聯盟後兩家航空公司的個別總成本最小為目標，並將個別航空公司聯盟前成本做為上限，在滿足聯盟後個別航空公司的總成本小於聯盟前的條件，及容量供給大於預測需求下，求解聯盟後之機隊規劃妥協解，模式中的決策變數包含：機型、航機架數、租金、租約期限等決策，其後本研究並模擬兩照航空公司決策者以聯盟之協商互動規劃步驟反映兩家航空公司就規劃目標間之相互協商(bargaining)互動過程，並增加或放鬆原模式之限制式，進而求解得到航空公司聯盟協議下之機隊規劃之協商妥協解。 本研究以範例闡述模式之應用，所得結果可得乾/濕租策略聯盟協議下之聯盟航空公司機隊規劃妥協解。透過所求得之妥協解，可得知航空公司配合不同的需求量變動，於不同的決策時點之最適機隊規劃與聯盟內容。藉由航空公司聯盟前後及協商互動前後的成本比較，顯示聯盟確實能使雙方成本減少，然由於聯盟整體最佳解未必為雙方所接受，故協商互動後之妥協解為雙方可接受卻非為聯盟整體之最佳解。由成本決策分析可推得聯盟乾/濕租年租金之上下限，而敏感度分析則顯示在不同之航機持有期間內，機隊規劃四項決策之成本臨界範圍。本模式不僅可提供航空公司決策者進行機隊規劃之參考，亦可提供聯盟雙方決策者於協商互動過程中，談判聯盟租金、租期與共同負擔維修比例等聯盟參數之依據。

Airline industry is highly sensitive to economic cycle, and the operation costs of airline are deeply influenced by the fleet capacity. Therefore, it is important for airlines to make the optimal fleet planning decisions to reduce operation costs and increase revenues. Recently, airlines have been forming alliance and successfully decrease operation costs by sharing markets, information, human resource, fleet and facilities. Code sharing, dry lease, and wet lease are commonly used strategies for airline alliance. Previous literature on airline alliance usually focused on flight code sharing problems, however, little literature has been focused on fleet planning which takes combined dry lease and wet lease into account. Furthermore, no theoretical model has been formulated on analyzing airline fleet planning with lease alliance in response to passenger demand fluctuation. This research aimed on fleet planning for airlines by incorporating the influence of strategy alliance, including dry and wet lease of fleet. The model dealt with issures regarding fleet purchase, lease, dry lease, wet lease, and disposal, and divides the entire study period into several stages. Then, we formulate a multi-objective model by minimizing total fleet planning cost using dynamic programming to determine the initial optimal numbers and types of aircraft for dry/wet lease, purchase and lease in fleet planning decision. Further, the study simulates step-by-step bargaining process for two of airlines’ decision makers. Through bargaining process, airlines’ decision makers could adjust alliance related parameters to trim their profit differences and obtain the final bargaining compromise solution which are accepted by both airlines. An empirical study is provided to illustrate the application of the model and simulate bargaining process of two airlines’ decision makers to show its usefulness. The study also conducts the sensitivity analyses which demonstrate the effects of key variables on the solution of the alliance model. The results also show the price ceiling and floor of fleet dry/wet lease and the critical price of fleet purchase, lease, dry lease and wet lease. The model we developed can not only determise among decisions on fleet planning solution for airlines alliance, but also provide a bargaining plan for airlines’ decision makers to obtain the bargaining compromise solution.