国内航空公司收益管理的应用和研究
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摘要
中国经济持续发展带来民用航空业的繁荣局面,三大航空集团、地方航空公司和低成本航空公司在国内市场的竞争愈发激烈。依据中国在加入WTO时的承诺,国外航空公司逐步进入中国市场,在世界航空业低迷不振之时,对于在中国的业务扩展踌躇满志,面对内忧外患的双重压力,国内航空公司在探求应对的解决方案。欧美航空公司的发展历程中显示,收益管理理论的研究、发展和应用推动了欧美航空业整体管理和经营水平的一次飞跃式提高,不仅仅提升了企业竞争力,甚至成为企业的核心竞争力。因此,亟待进一步提高我国航空公司收益管理的研究和应用水平,深入理解收益管理理论,完善收益管理系统的开发。
本文主要在成熟的收益管理理论基础上,吸取国外航空公司的成功经验,针对国内航空市场的实际情况,探讨在国内实施收益管理及开发收益管理系统等方面的问题。
在对收益管理的概念和基本内容简要介绍的基础上,对比国内外收益管理的发展历程,提出国内航空公司实施收益管理的重要意义。进一步引入航空运输客运市场的经济特点,通过对需求细分和消费者决策的研究,多等级票价体系的应用成为收益管理的基础,以此成为航空公司销售的票价结构。
预测、超售和座位优化是收益管理的基本方法。给出原始数据收集的方法和结构以及依照数据特性调整数据的方法,重点讨论了不同的预测模型的应用及预测结果的经验评估。虽然超售在国内应用起来比较谨慎,但超售可以带来收入,对航空公司超售的原因及超售手段做简单介绍,同时给出确定超售水平的模型。分析运用嵌套理论和期望边际收益理论对多等级舱位的座位优化控制方法,分别介绍了基于航节和基于网络的座位优化控制方法。
以收益管理理论为基础,对符合国内航空市场环境开发的收益管理系统做出总体结构设计的介绍,并在系统开发和使用过程中积累了宝贵经验,成功应用收益系统成为进一步研究和开发收益管理的良好开端。
Revenue Management has been developed rapidly and applied successfully in many airlines in the world since the deregulation of U.S. airline industry. At that time, the "fare war" immediately followed and price competition caused economic loss among most airlines except for few airlines which practiced revenue management strategies. Recent years, Chinese airlines are facing with the same problem in domestic aviation market. In the circumstance, Major domestic airlines have bought the revenue management system to cope with these changes in China and challenge to entrance of overseas airlines. Studies on the successful experience of foreign advanced airlines which made use of revenue management system, both operational and managerial innovation have had been occurred. So it is important to focus on not only the theory research but also the application experience for domestic airlines when using a proper revenue management system.
The thesis based on the revenue management theory those have had been applied entirely and aimed at discussing the application and development of revenue management system in domestic aviation market.
Hence, in the thesis, conception and the evolution of revenue management are introduced. With the first step of deregulation in China, airlines fell into an awkward economic predicament, it is necessary to improve the abilities on airline management and operation. So airline revenue management suitable for Chinese airlines is emphasized after deep consideration. Furthermore the economic characteristic of aviation market is and analyses on the air travel demand and consumer decisions leads to the multi-fare structure.
Major procedure in revenue management is forecasting, overbooking and seat inventory control. Data collection methods are the base of forecasting and then several reservations forecasting modules are simulated. Traditional demand forecasting modules are still useful and efficient according to the Chinese airline market nowadays. The demand forecasting methods picked are means model, added pick-up model, multiplicative pick-up model, linear regression, logarithmic regression, ESP and ARIMA.
Overbooking performs another role in revenue management. Although overbooking is hardly acceptable in China, the evidence shows that overbooking can also maximize the revenue. Simple description is made on cost-based overbooking and overbooking without consideration of cost.
Seat inventory control focuses on the leg-based and O&D seat inventory control. With the restriction of Inventory Control System (ICS) in China, much attention is paid to leg-based EMSR and multi segment control. For the long run, O&D seat inventory control will be applied. Four methods on origin-destination network are mentioned: GVN, DAVN, HBP and ProBP.
It is shows that application on revenue management system which is proper for Chinese airline can improve airline's revenue. It is the challenge for domestic airline to apply revenue management on domestic aviation market successfully with the revenue management system developed by our own. Application and research of revenue management support decision system is beginning in our nation. Suitable and stable system should be improved as the actual conditions changes.
本文主要在成熟的收益管理理论基础上,吸取国外航空公司的成功经验,针对国内航空市场的实际情况,探讨在国内实施收益管理及开发收益管理系统等方面的问题。
在对收益管理的概念和基本内容简要介绍的基础上,对比国内外收益管理的发展历程,提出国内航空公司实施收益管理的重要意义。进一步引入航空运输客运市场的经济特点,通过对需求细分和消费者决策的研究,多等级票价体系的应用成为收益管理的基础,以此成为航空公司销售的票价结构。
预测、超售和座位优化是收益管理的基本方法。给出原始数据收集的方法和结构以及依照数据特性调整数据的方法,重点讨论了不同的预测模型的应用及预测结果的经验评估。虽然超售在国内应用起来比较谨慎,但超售可以带来收入,对航空公司超售的原因及超售手段做简单介绍,同时给出确定超售水平的模型。分析运用嵌套理论和期望边际收益理论对多等级舱位的座位优化控制方法,分别介绍了基于航节和基于网络的座位优化控制方法。
以收益管理理论为基础,对符合国内航空市场环境开发的收益管理系统做出总体结构设计的介绍,并在系统开发和使用过程中积累了宝贵经验,成功应用收益系统成为进一步研究和开发收益管理的良好开端。
Revenue Management has been developed rapidly and applied successfully in many airlines in the world since the deregulation of U.S. airline industry. At that time, the "fare war" immediately followed and price competition caused economic loss among most airlines except for few airlines which practiced revenue management strategies. Recent years, Chinese airlines are facing with the same problem in domestic aviation market. In the circumstance, Major domestic airlines have bought the revenue management system to cope with these changes in China and challenge to entrance of overseas airlines. Studies on the successful experience of foreign advanced airlines which made use of revenue management system, both operational and managerial innovation have had been occurred. So it is important to focus on not only the theory research but also the application experience for domestic airlines when using a proper revenue management system.
The thesis based on the revenue management theory those have had been applied entirely and aimed at discussing the application and development of revenue management system in domestic aviation market.
Hence, in the thesis, conception and the evolution of revenue management are introduced. With the first step of deregulation in China, airlines fell into an awkward economic predicament, it is necessary to improve the abilities on airline management and operation. So airline revenue management suitable for Chinese airlines is emphasized after deep consideration. Furthermore the economic characteristic of aviation market is and analyses on the air travel demand and consumer decisions leads to the multi-fare structure.
Major procedure in revenue management is forecasting, overbooking and seat inventory control. Data collection methods are the base of forecasting and then several reservations forecasting modules are simulated. Traditional demand forecasting modules are still useful and efficient according to the Chinese airline market nowadays. The demand forecasting methods picked are means model, added pick-up model, multiplicative pick-up model, linear regression, logarithmic regression, ESP and ARIMA.
Overbooking performs another role in revenue management. Although overbooking is hardly acceptable in China, the evidence shows that overbooking can also maximize the revenue. Simple description is made on cost-based overbooking and overbooking without consideration of cost.
Seat inventory control focuses on the leg-based and O&D seat inventory control. With the restriction of Inventory Control System (ICS) in China, much attention is paid to leg-based EMSR and multi segment control. For the long run, O&D seat inventory control will be applied. Four methods on origin-destination network are mentioned: GVN, DAVN, HBP and ProBP.
It is shows that application on revenue management system which is proper for Chinese airline can improve airline's revenue. It is the challenge for domestic airline to apply revenue management on domestic aviation market successfully with the revenue management system developed by our own. Application and research of revenue management support decision system is beginning in our nation. Suitable and stable system should be improved as the actual conditions changes.
引文
[1]P.P.Beiobaba.Air Travel Demand and Airline Seat Inventory Management[D].Cambridge (MA):Flight Transportation Laboratory,Massachusetts Institute of Technology,May 1987.
[2]Rigas Doganis.Flying Off Course:The Economies of International Airlines 2nd Edition [M].London:Routledge,1991.Chapter 3 and 4.
[3]B.C.Smith,J.F.Leimkuhler,R.M.Darrow.Yield Management at American Airlines[R].Interfaces,Jan/Feb 1992,22(1);8-31.
[4]C.Barnhart,P.P.Belobaba and A.R.Odoni.Applications of Operations Research in the Air Transport Industry[J].Transportation Science,2003,37(4);368-391.
[5]A.O.Lee.Airline Reservations Forecasting:Probabilistic and Statistical Models of the Booking Process[D].Cambridge(MA):Hight Transportation Laboratory,Massachusetts Institute of Technology,1990.
[6]Catherine H.Bohutinsky.The Sell up Potential of Airline Demand[D].Cambridge(MA):Flight Transportation Laboratory,Massachusetts Institute of Technology,June 1990.
[7]Richard H.Zeni.Improving Forecast Accuracy by Unconstraining Censored Demand Data [R].Bangkok:AGIFORS Reservation and Yield Management Study Group,May 2001.
[8]Thomas O.Gorin.Revenue Management:Sell-up and Forecasting Algorithms[D].Cambridge(MA):Flight Transportation Laboratory,Massachusetts Institute of Technology,June 2000.45-49.
[9]Jeffrey S.Zickus.Forecasting for Airline Network Revenue Management:Revenue and Competitive Impacts[D].Cambridge(MA):Flight Transportation Laboratory,Massachusetts Institute of Technology,1988.
[10]Arjan Westerhof.Seasons for Demand Forecasting[R].London:AGIFORS Reservation and Yield Management Study Group,April 1999.
[11]R.R.Wickham.Evaluation of Forecasting Techniques for Short-Term Demand of Air Transportation[D].Cambridge(MA):Flight Transportation Laboratory,Massachusetts Institute of Technology,June 1995.
[12]E.L'Heureux.A New Twist in Forecasting Passenger Short-term Pickup[R].London:26~# AGIFORS Annual Symposium Proceedings,1986.248-261.
[13]Larry R.Weatherford.Forecast Aggregation and Disaggregation[R].Toronto:IATA Revenue Management Conference Proceedings,1999.
[14]Richard H.Zeni.Improved Forecast Accuracy in Revenue Management by Unconstraining Demand Estimates from Censored Data[D].Newark(NJ):Graduate School-Newark,Rutgers,the State University of New Jersey,2001
[15]Daniel Kew Skwarek.Competitive Impacts of Yield Management Systems Components:Forecasting and Sell-up Models[D].Cambridge(MA):Flight Transportation Laboratory,Massachusetts Institute of Technology,June 1996.91-94.
[16]约翰.E.汉克,迪恩.W.威切恩.商业预测[M].胡晓凤等译.第8版.北京:清华大学出版社,2006年7月.73-75.
[17]P.P.Belobaba.Flight Overbooking:Models and Practice[Z].http://ocw.mit.edu/NR/rdonlyres/Aeronautics-and-Astronautics/16-75JSpring-2006/E2A09BF6-E275-431B-9C07-2C98BEAS0541/0/lect19.pdf,April 24,2006.
[18]P.P.Belobaba.Optimal vs.Heuristic Methods for Nested Seat Allocation.Brussels:AGIFORS Reservation and Yield Management Study Group,1992.
[19]E.L.Williamson.Airline Network Seat Inventory Control:Methodologies and Revenue Impacts[D].Cambridge(MA):Flight Transportation Laboratory,Massachusetts Institute of Technology,June 1992.
[20]R.W.Simpson.Using Network Flow Techniques to Find Shadow Prices for Market and Seat Inventory Control[Z].Cambridge(MA):MIT Flight Transportation Laboratory,1989.
[21]B.C.Smith and C.W.Penn.Analysis of Alternative Origin-Destination Control Strategies.New Seabury(MA):28~# AGIFORS Symposium Proceeding,1988.
[22]P.P.Belobaba.The Evolution of Airline Yield Management:Fare Class to Origin-Destination Seat Inventory Control[C].New York:the Aviation Weekly Group of the McGraw-Hill Companies,1998.285-302.
[23]Stephane Bratu.Network Value Concept in Airline Revenue Management[D].Cambridge (MA):Flight Transportation Laboratory,Massachusetts Institute of Technology,1998.
[2]Rigas Doganis.Flying Off Course:The Economies of International Airlines 2nd Edition [M].London:Routledge,1991.Chapter 3 and 4.
[3]B.C.Smith,J.F.Leimkuhler,R.M.Darrow.Yield Management at American Airlines[R].Interfaces,Jan/Feb 1992,22(1);8-31.
[4]C.Barnhart,P.P.Belobaba and A.R.Odoni.Applications of Operations Research in the Air Transport Industry[J].Transportation Science,2003,37(4);368-391.
[5]A.O.Lee.Airline Reservations Forecasting:Probabilistic and Statistical Models of the Booking Process[D].Cambridge(MA):Hight Transportation Laboratory,Massachusetts Institute of Technology,1990.
[6]Catherine H.Bohutinsky.The Sell up Potential of Airline Demand[D].Cambridge(MA):Flight Transportation Laboratory,Massachusetts Institute of Technology,June 1990.
[7]Richard H.Zeni.Improving Forecast Accuracy by Unconstraining Censored Demand Data [R].Bangkok:AGIFORS Reservation and Yield Management Study Group,May 2001.
[8]Thomas O.Gorin.Revenue Management:Sell-up and Forecasting Algorithms[D].Cambridge(MA):Flight Transportation Laboratory,Massachusetts Institute of Technology,June 2000.45-49.
[9]Jeffrey S.Zickus.Forecasting for Airline Network Revenue Management:Revenue and Competitive Impacts[D].Cambridge(MA):Flight Transportation Laboratory,Massachusetts Institute of Technology,1988.
[10]Arjan Westerhof.Seasons for Demand Forecasting[R].London:AGIFORS Reservation and Yield Management Study Group,April 1999.
[11]R.R.Wickham.Evaluation of Forecasting Techniques for Short-Term Demand of Air Transportation[D].Cambridge(MA):Flight Transportation Laboratory,Massachusetts Institute of Technology,June 1995.
[12]E.L'Heureux.A New Twist in Forecasting Passenger Short-term Pickup[R].London:26~# AGIFORS Annual Symposium Proceedings,1986.248-261.
[13]Larry R.Weatherford.Forecast Aggregation and Disaggregation[R].Toronto:IATA Revenue Management Conference Proceedings,1999.
[14]Richard H.Zeni.Improved Forecast Accuracy in Revenue Management by Unconstraining Demand Estimates from Censored Data[D].Newark(NJ):Graduate School-Newark,Rutgers,the State University of New Jersey,2001
[15]Daniel Kew Skwarek.Competitive Impacts of Yield Management Systems Components:Forecasting and Sell-up Models[D].Cambridge(MA):Flight Transportation Laboratory,Massachusetts Institute of Technology,June 1996.91-94.
[16]约翰.E.汉克,迪恩.W.威切恩.商业预测[M].胡晓凤等译.第8版.北京:清华大学出版社,2006年7月.73-75.
[17]P.P.Belobaba.Flight Overbooking:Models and Practice[Z].http://ocw.mit.edu/NR/rdonlyres/Aeronautics-and-Astronautics/16-75JSpring-2006/E2A09BF6-E275-431B-9C07-2C98BEAS0541/0/lect19.pdf,April 24,2006.
[18]P.P.Belobaba.Optimal vs.Heuristic Methods for Nested Seat Allocation.Brussels:AGIFORS Reservation and Yield Management Study Group,1992.
[19]E.L.Williamson.Airline Network Seat Inventory Control:Methodologies and Revenue Impacts[D].Cambridge(MA):Flight Transportation Laboratory,Massachusetts Institute of Technology,June 1992.
[20]R.W.Simpson.Using Network Flow Techniques to Find Shadow Prices for Market and Seat Inventory Control[Z].Cambridge(MA):MIT Flight Transportation Laboratory,1989.
[21]B.C.Smith and C.W.Penn.Analysis of Alternative Origin-Destination Control Strategies.New Seabury(MA):28~# AGIFORS Symposium Proceeding,1988.
[22]P.P.Belobaba.The Evolution of Airline Yield Management:Fare Class to Origin-Destination Seat Inventory Control[C].New York:the Aviation Weekly Group of the McGraw-Hill Companies,1998.285-302.
[23]Stephane Bratu.Network Value Concept in Airline Revenue Management[D].Cambridge (MA):Flight Transportation Laboratory,Massachusetts Institute of Technology,1998.