Research On Revenue Management Of Airline Alliance

With the continuous development of economy and the process of globalization,the market competition pattern of air transport industry has gradually changed.The competition among airlines has changed from simple competition among individuals to competition among aviation alliance,and among members of the alliance competition.This complex competitive environment poses new challenges to the operation and management of airlines.So it is a practical significance to study the revenue management of airlines in alliance environment and there are two main contents: 1.revenue sharing between airlines;2.the allocation and control of seats capacity.Revenue sharing refers to the distribution of airline tickets between the operating airlines,which directly determines the profit of the cooperative airlines and the stability of the airline alliance.The allocation and control of seats capacity means to determine the optimal number of seats to classed of ODFs for every company.This dissertation studied the both main problems,which contained the following sub-problems:First,in order to provide the data basis for the airline alliance agreement and ensure the profit for the airlines,we establish a random programming model to determine the transfer price for different number of transfer seats.Besides a multi-segment stochastic programming aiming to maximize the revenue of a single airline in the airline alliance model is established to allocate the seats capacity before booking horizon.Followed,if the airlines cannot reach a consensus on the revenue sharing agreement,a bargain model is established to get the transfer price by bargaining between the airlines under the complete and the incomplete information.The airlines may reject the request which benefit for airline alliance but not benefit for airlines.A multi-stage bargaining model is designed to solve the problem.The above two models deal with the revenue sharing problems existing and provides a theoretical basis for revenue sharing in airline alliance.By third,a framework is established to help airline alliances effectively allocate their seat capacity with the purpose of maximizing alliances' revenue under incomplete information.By assuming the airline alliance as the auctioneer and seat capacity in an itinerary as lots,the Combinational Auction Model is constructed to optimize the allocation of the seat,and the revenue sharing method is established to share revenue between partners by VCG mechanism.A multi-stage dynamic combinational auction is expanded to reduce the amount of calculation.The result of the numerical study show that the seat capacity allocation is effective even without information exchanging completely and the twofold revenue shares method is more excitation to sale higher price tickets for the airlines.Lastly,A Markov decision processes model is developed to formulate the dynamic control of seat capacity during the booking horizon.The proposed model is expected to maximize the revenue of the airline in an airline alliance,and the optimal strategy of every stage shows the seats capacity allocation to different classes of different ODFs for different airlines.The dissertation is a deep research on models and algorithms of revenue management in alliance.Several new allocation methods are proposed which provide a good theoretical reference value for airlines to implement revenue management in airline alliance environment.