航空货运收益管理与流程优化问题研究
|
摘要
随着全球一体化进程的发展和国际贸易的快速增长,我国航空货运已经迈入蓬勃发展的新阶段。在国家“天空开放”浪潮的推动下,我国航空公司的货运面临着巨大的发展机遇,同时也面临了严峻的挑战。如何提高航空货运的收益管理水平成为我国航空公司迫切需要解决的首要问题。为了提高我国航空公司货运的服务质量和竞争力,本文从目前我国航空货运管理中存在的主要问题出发,结合我国航空货运发展的实际情况展开航空货运收益管理研究。又因为航空货运流程是影响货运收益的重要因素之一,所以最后专门论述货运流程优化设计的方法。全文的主要内容如下:
在航空货运顾客需求分析方面,本文从顾客角度研究了航空货运的顾客价值特性,提出了航空货运顾客价值的决定因素与动态性变化的理论模型,运用结构方程方法对其检验,结果表明了时间因素和便捷性因素是影响货运顾客价值的首要要素,价格因素已退之其次,并且来自竞争者、服务商、顾客和宏观环境的变化都对顾客价值动态性变化有显著影响。本文又从企业、竞争者和顾客三个方面分析了航空货运顾客需求变化的原因,并据此构建顾客需求问题目标求解过程知识的语义模型,以及建立基于“规则+案例”的顾客需求知识模型,便于航空公司动态掌握顾客需求的变化。
在航空货运产品创新方面,本文分析了我国航空货运产品的现状,发现航空货运产品品种单一。本文将货运产品服务内容划分为不同层次,采用总线模块化方法对航空货运产品进行创新。
在航空货运定价方面,本文在考虑时间和价格是影响顾客价值的关键因素基础上,提出了以多种交货期为基础的等级价格体系,并有交货期承诺价格折扣机制,建立了与交货期时间相关的定价模型,通过算例探讨了模型参数对最优价格决策的影响,并能为本文提出的货运创新产品价格决策提供有益的参考。
在超售方面,本文提出了一种以航空公司的利润最大化为目标,同时考虑货运重量和体积二个维度的超售模型,由模型得出最优的超售水平与货物的Show-Up率相关,与订舱请求水平无关,因而该模型简单易行,便于航空公司在实践中运用。
在舱位控制方面,本文从长期和短期两个方面研究了舱位分配控制问题,首先研究了长期舱位销售合同对航空公司货运收益的影响,建立了舱位分配的数学模型,采用随机机会约束规划方法对其求解,确定了航空公司长期舱位分配的策略,并通过算例分析,表明了航空公司通过签订长期舱位销售合同,可以掌握更为准确的需求信息。在短期舱位控制方面,采用动态规划方法建立了单航段条件下的货运舱位动态控制的模型,研究了航空货运舱位动态优化控制的策略。
在货物运输路线方面,本文提出了一种基于Multi-Agent的航空货运路线模型和以期望净收入最优为目标的路线选择算法,通过算例说明了该模型算法简单且具有增量性。
在航空货运流程优化方面,本文应用六西格玛管理方法进行货运流程优化设计,研究了过程能力指数与合格率之间的关系,以及西格玛水平与过程能力指数之间的关系,以流程的操作时间为货运流程的绩效评价标准,建立了货运流程能力分配设计的数学模型,通过算例说明了模型的拉格朗日求解方法。
With development of global economic integration and international trade, China air cargo entered into a new stage of dramatic development. Under Chinese policy of“open sky”, Chinese airlines have been faced with tremendous development opportunities and challenges at the same time. How to improve air cargo revenue management level becomes the most important question for the civil aviation enterprises. In order to improve China air cargo service quality and increase air cargo revenue and strengthen competition advantage, this article studies China air cargo revenue management according to the airlines’fact and key problems of China air cargo management. The article specially studies the problem of air cargo process optimization at last. The main contents of the article are as follows:
In the analysis of air cargo customer demand, the article studies the characteristics of air cargo customer value based on customer perspective, and develops the theoretical model for deciding factors of customer value and its dynamic changes, using the structural equation model to examine it, the result shows that the factors of time and convenience are the core factors influencing air cargo customer value, and the factor of price has already become secondary, and the changes in competitor, service provider, customer and macro-environment all have remarkable effects on the dynamics of customer value. The article also analyzes the reasons of customer’s demand change based on enterprises, competitors and customers three aspects, and develops knowledge of the seek process of customer’s demand goal, and establishes customer’s demand knowledge expression pattern based on“Rule+Case”, which can catch dynamically customer demand.
The article analyzes the state of air cargo product, and finds that China air cargo products were simplex and the degree of product innovation was low-level, and combines buses modularization method with product innovation, dividing air cargo service into hiberarchy.
In the air cargo pricing system, the article puts forward the rank lead time-contingent pricing system and the price discount mechanism to pledge lead-time, which is found that time and price is key point of affecting the degree of customer value. It has established lead time-contingent pricing model and discount model. Through numerical example, the article discusses the impact of parameters in the model on optimal pricing decision. The results have special referece to decision-making of pricing for the third chapter suggested new air cargo products.
A two-dimensional (weight and volume) cargo overbooking model was developed with profit maximization as the objective. And the result of the model indicated that the optimal overbooking level is related to show-up rate greatly rather than booking requests. It was proved that the model is efficient and easy to be put into practice.
Cargo slot inventory control was studied from long term and short term. The article studies the effect of long-term contract on airlines cargo yield, develops a chance-constrained programming model with a profit maximization objective, which can control airlines slot allotment. Afterwards, a numerical example is given to illustrate the application of the proposed model, which shows that airlines obtain more accurate demand information. At last the article establishes a discrete-time dynamic programming model for air cargo short-term slot optimal control with a single-leg, and puts forward the optimal control policy of air cargo slot.
An air cargo routiong model on Mulit-Agent and the algorithm of routing choice aimed at maximum expected net revenue was developed, based on the characteristics of air cargo slot. A numerical example is given to show that the model is simple and incremental.
Six Sigma Management was applied to cargo process optimaization and design, and the artilce studies the relationship of six sigma level, process capability indices and qualified rate, develops the mathematical model of six sigma process ability assignment based on lowest time cost, and the method of Lagrange was used to solve the model. The model was tested with an example.
在航空货运顾客需求分析方面,本文从顾客角度研究了航空货运的顾客价值特性,提出了航空货运顾客价值的决定因素与动态性变化的理论模型,运用结构方程方法对其检验,结果表明了时间因素和便捷性因素是影响货运顾客价值的首要要素,价格因素已退之其次,并且来自竞争者、服务商、顾客和宏观环境的变化都对顾客价值动态性变化有显著影响。本文又从企业、竞争者和顾客三个方面分析了航空货运顾客需求变化的原因,并据此构建顾客需求问题目标求解过程知识的语义模型,以及建立基于“规则+案例”的顾客需求知识模型,便于航空公司动态掌握顾客需求的变化。
在航空货运产品创新方面,本文分析了我国航空货运产品的现状,发现航空货运产品品种单一。本文将货运产品服务内容划分为不同层次,采用总线模块化方法对航空货运产品进行创新。
在航空货运定价方面,本文在考虑时间和价格是影响顾客价值的关键因素基础上,提出了以多种交货期为基础的等级价格体系,并有交货期承诺价格折扣机制,建立了与交货期时间相关的定价模型,通过算例探讨了模型参数对最优价格决策的影响,并能为本文提出的货运创新产品价格决策提供有益的参考。
在超售方面,本文提出了一种以航空公司的利润最大化为目标,同时考虑货运重量和体积二个维度的超售模型,由模型得出最优的超售水平与货物的Show-Up率相关,与订舱请求水平无关,因而该模型简单易行,便于航空公司在实践中运用。
在舱位控制方面,本文从长期和短期两个方面研究了舱位分配控制问题,首先研究了长期舱位销售合同对航空公司货运收益的影响,建立了舱位分配的数学模型,采用随机机会约束规划方法对其求解,确定了航空公司长期舱位分配的策略,并通过算例分析,表明了航空公司通过签订长期舱位销售合同,可以掌握更为准确的需求信息。在短期舱位控制方面,采用动态规划方法建立了单航段条件下的货运舱位动态控制的模型,研究了航空货运舱位动态优化控制的策略。
在货物运输路线方面,本文提出了一种基于Multi-Agent的航空货运路线模型和以期望净收入最优为目标的路线选择算法,通过算例说明了该模型算法简单且具有增量性。
在航空货运流程优化方面,本文应用六西格玛管理方法进行货运流程优化设计,研究了过程能力指数与合格率之间的关系,以及西格玛水平与过程能力指数之间的关系,以流程的操作时间为货运流程的绩效评价标准,建立了货运流程能力分配设计的数学模型,通过算例说明了模型的拉格朗日求解方法。
With development of global economic integration and international trade, China air cargo entered into a new stage of dramatic development. Under Chinese policy of“open sky”, Chinese airlines have been faced with tremendous development opportunities and challenges at the same time. How to improve air cargo revenue management level becomes the most important question for the civil aviation enterprises. In order to improve China air cargo service quality and increase air cargo revenue and strengthen competition advantage, this article studies China air cargo revenue management according to the airlines’fact and key problems of China air cargo management. The article specially studies the problem of air cargo process optimization at last. The main contents of the article are as follows:
In the analysis of air cargo customer demand, the article studies the characteristics of air cargo customer value based on customer perspective, and develops the theoretical model for deciding factors of customer value and its dynamic changes, using the structural equation model to examine it, the result shows that the factors of time and convenience are the core factors influencing air cargo customer value, and the factor of price has already become secondary, and the changes in competitor, service provider, customer and macro-environment all have remarkable effects on the dynamics of customer value. The article also analyzes the reasons of customer’s demand change based on enterprises, competitors and customers three aspects, and develops knowledge of the seek process of customer’s demand goal, and establishes customer’s demand knowledge expression pattern based on“Rule+Case”, which can catch dynamically customer demand.
The article analyzes the state of air cargo product, and finds that China air cargo products were simplex and the degree of product innovation was low-level, and combines buses modularization method with product innovation, dividing air cargo service into hiberarchy.
In the air cargo pricing system, the article puts forward the rank lead time-contingent pricing system and the price discount mechanism to pledge lead-time, which is found that time and price is key point of affecting the degree of customer value. It has established lead time-contingent pricing model and discount model. Through numerical example, the article discusses the impact of parameters in the model on optimal pricing decision. The results have special referece to decision-making of pricing for the third chapter suggested new air cargo products.
A two-dimensional (weight and volume) cargo overbooking model was developed with profit maximization as the objective. And the result of the model indicated that the optimal overbooking level is related to show-up rate greatly rather than booking requests. It was proved that the model is efficient and easy to be put into practice.
Cargo slot inventory control was studied from long term and short term. The article studies the effect of long-term contract on airlines cargo yield, develops a chance-constrained programming model with a profit maximization objective, which can control airlines slot allotment. Afterwards, a numerical example is given to illustrate the application of the proposed model, which shows that airlines obtain more accurate demand information. At last the article establishes a discrete-time dynamic programming model for air cargo short-term slot optimal control with a single-leg, and puts forward the optimal control policy of air cargo slot.
An air cargo routiong model on Mulit-Agent and the algorithm of routing choice aimed at maximum expected net revenue was developed, based on the characteristics of air cargo slot. A numerical example is given to show that the model is simple and incremental.
Six Sigma Management was applied to cargo process optimaization and design, and the artilce studies the relationship of six sigma level, process capability indices and qualified rate, develops the mathematical model of six sigma process ability assignment based on lowest time cost, and the method of Lagrange was used to solve the model. The model was tested with an example.
引文
[1]苏宁.波音预测全球航空货运发展.中国民用航空,2006(5):28-29.
[2]杨占林,张晨梅.国际物流空运操作实务.北京:中国商务出版社,2004.
[3]刘功仕.发展与边缘化中的我国民航国际货运.中国民用航空,2005(6):19-23.
[4]刘少成,戈锐.中国航空货运发展的政策选择.中国民用航空,2006(8):35-38.
[5]Anming Zhang,Yimin Zhang. A model of air cargo liberalization: passenger vs. all-cargo carriers.Transportation Research Part E, 2002(38):175-191.
[6]Weatherford L R, Bodily S E. A taxonomy and research overview of perishable-asset revenue management: yield management, overbooking and pricing. Operations Research, 1992(40):831-844.
[7]Donaghy K, McMahon U, et al. Yield management: an overview. International Journal of Hospitality Management, 1995, 14(2):139-150.
[8]McGill J I, van Ryzin G J. Revenue management: research overview and prospects. Transportation Science, 1999(33): 233-256.
[9]R G Kasilingam. Air cargo revenue management: characteristics and complexities. European Journal of Operational Research, 1997(96):36-44.
[10]John S.Billings, Adriana G.Diener, Benson B.Yuen. Cargo revenue optimization. Journal of Revenue and Pricing Management, 2003(2):69-79.
[11]R. G. Kasilingam. An economic model for air cargo overbooking under stochastic capacity. Computer Industry Engineering, 1997(32):221-226.
[12]Littlewood, K. Forecasting and control of passengers. 12th AGIFORS Symposium Proceedings, 1972:103-105.
[13]Lee T C, M. Hersh. A model for dynamic airline seat inventory control with multiple seat bookings. Transportation Science, 1993, 27(3):252-265.
[14]McGill J I. Censored regression analysis of multi-class demand data subject to joint capacity constraints. The Annals of Operations Research, 1995(60):209-240.
[15]Bodily S, Pfeifer P E. Overbooking decision rules. Omaga, 1992(20):129-133.
[16]Robinson L W. Optimal and approximate control polices for airline booking with sequential fare class. Operations Research, 1995(43):252-263.
[17]Belobaba P P, Farkas A. Yield management impacts on spill estimation. Transportation Science, 1999, 33(2):217-232.
[18]Chatwin R E. Continuous time airline overbooking with time-dependent fares and refunds.Transportation Science, 1999, 33(2):182-191.
[19]Liang Y. Solution to the continuous time dynamic yield management mode. Transportation Science, 1999, 33(1):117-123.
[20]Feng Y, Gallego G. Optimal starting times for end-of-season sales and optimal stopping-times for promotional fares. Management Science, 1995(41):1371-1391.
[21]Feng Y, Gallego G. Perishable asset revenue management with markovian time dependent demand intensities. Management Science, 2000(46):941-956.
[22]Feng Y, Xiao B. Optimal policies of yield management with multiple predetermined prices. Operations Research, 2000a(48):332-343.
[23]Feng Y, Xiao B. A continuous-time yield management model with multiple prices and reversible price changes. Management Science, 2000b(46):644-657.
[24]Gallego G, van Ryzin G. Optimal dynamic pricing of inventories with stochastic demand over finite horizons. Management Science, 1994(40):999-1020.
[25]Gallego G, van Ryzin G. A multi-product dynamic pricing problem and its application to network yield management. Operations Research, 1997(45):24-41.
[26]Glover F R, Glover J L, Mcmillan C. The passenger-mix problem in the scheduled airlines. Interfaces, 1982(12):73-79.
[27]Belobaba P P. Airline yield management: an overview of seat inventory control. Transportation Science. 1987, 21(2):63-73.
[28]Belobaba P P. Application of a probabilistic decision model to airlines seat inventory control. Operations Research, 1989(37):183-197.
[29]Brumelle S L, McGill J I. Airlines seat allocation with multiple nested fare classes. Operations Research, 1993(41);127-137.
[30]Curry R. Optimal seat allocation with fare classes nested by origins and destinations. Transportation Science, 1990(24):193-204.
[31]Wollmer R D. A hub-spoke seat management model. Douglas Aircraft Company,McDonnel Douglas Corporation, Long Beach, CA, 1992.
[32]Lautenbatcher C J, Stidaham J R. The underlying markov decision process in the single-leg airline yield management problem. Transportation Science, 1999, 33(2):136-146.
[33]Subramanian J, S Stidham, C J Lautenbacher. Airline yield management problem with overbooking, cancellations and no shows. Transportation Science, 1999, 33(2):147-167.
[34]Do Boer S V, Freling R, Piersma N. Stochastic programming for multiple-leg network revenue management. European Journal of Operational Research, 2002(137):72-92.
[35]Talluri K T, Van Ryzin. An analysis of bid-price controls for network revenue management.Management Science, 1998, 44(11):1577-1593.
[36]Talluri K T, Van Ryzin. A randomized linear programming method for computing network bid prices. Transportation Science, 1999, 33(2):207-216.
[37]Talluri K T, Van Ryzin. Revenue management under a general discret choice model of consumer behavior. Management Science, 2004, 50(1):15-33.
[38]Chen V C, Gunther D, E L Johnson. A marokov decision problem based approach to the airline yield management problem. Working Paper, The Logistics Institute, Georgia Institute of Technology, Atlanta, GA, 1998.
[39]Bertsmias D, De Boer S. Simulation based optimization for airline network yield management. Working Paper, Massachusetts Institute of Technology, Cambridge, MA, 2001.
[40]Bertsmias D, Popescu I. Revenue management in a dynamic network environment. Transportation Science,2003, 37(3):257-277.
[41] Itlr Zeynep Karaesmen. Three essays on revenue management .UMI,2001.
[42]Kleywegt, A J, Papastavrou J D. The dynamic and stochastic knapsack problem, Operations Research, 1998(46):17-35.
[43] Kleywegt, A J, Papastavrou J D. The dynamic and stochastic knapsack problem with random sized items, Operations Research, 2001(49):26-41.
[44]Kevin Pak, Rommert Dekker. Cargo revenue management: bid-prices for a 0-1 multi-knapsack problem Working Paper, Erasmus University, 2004,6.
[45]Paul Bartodziej, Ulrich Derigs. On an experimental algorithm for revenue management for cargo airlines. Lecture Notes in Computer Science, 2004(3059):57-71.
[46] Bart Slager, Luuk Kapteijns. Implementation of cargo revenue management at KLM. Journal of Revenue and Pricing Management, 2004(3):80-90.
[47] P.Bartodziej, U.Derigs, M.Zils. O&D revenue management in cargo airlines-a mathematical programming approach. OR Spectrum, 2006, February online.
[48]Ek-Peng Chew, Huei-Chuen Huang, et al. Short-term booking of air cargo space. European Journal of Operational Research. 2006(174):1979-1990.
[49]Andreea Popescu, Pinar Keskinocak,etc. Estimation air-cargo overbooking based on a discrete show-up-rate distribution. Interfaces,2006(3):248-258.
[50]Kannapha Amaruchkul,William L. Cooper, Diwakar Gupta. Single-Leg air-cargo revenue management. working paper, University of Minnesota,2006.3.
[51]Yu-Hern Chang, Chung-Hsing Yeh. A survey analysis of service quality for domestic airlines. European Journal of Operational Research,2002(139):166-177.
[52]Jin-Woo Park,Rodger Robertson. The effect of airline service quality on passengers’behavioural intentions a Korean case study. Journal of Air Transport Management, 2004(10):435-439.
[53]Fang-Yuan Chen, Yu-Hern Chang. Examining airline service quality from a process perspective. Journal of Air Transport Management,2005(11):79-87.
[54]Anming Zhang. Analysis of an international air-cargo hub: the case of Hong Kong. Air Transport Management, 2003(9):123-138.
[55]Joseph Berechman, N. Adler. Airport quality and hub location question. Air Transport Management, 2001(5):67-74.
[56]Hiroshi Ohashi, Tae-Seun Kim. Choice of air cargo transshipment airport: an application to air cargo traffic to/from Northeast Asia. http://www.e.u-tokyo.ac.jp/cirje/research/03research.html
[57]Anming Zhang, Lawrence Leung. Air cargo alliance and competition in passenger markets. Transportation Research, 2004(40):83-100.
[58]Paul W Forster. Electronic integration in the air cargo industry: an information processing model of on-time performance. Transportation Journal, 2002, 40(4):46-61.
[59]Aaton L Nsakanda, Michel Turcotte. Air cargo operations evaluation and analysis through simulation. Proceedings of the 2004 Winter Simulation Conference, 2004:1790-1798.
[60]赵杨.低成本航空成为亚洲航空发展趋势.AMT研究院, http:www.amteam.org/static/49749.html,2004.10.13
[61]吴旭慧,储雪俭.论航空货运企业向空地一体化转型.物流技术,2005(1):19-21.
[62]吴昌勇.航空物流园区形成机理.中国民用航空,2004(8):56-57.
[63]王冬梅.机场与航空公司运营关系探讨.民航管理,2004(3):37-39.
[64]龚志峰,范守文,霍丽芙.航空物流中心系统动态布置设计.机械制造,2005(3):40-42.
[65]胡国丹.航空物流供应链的信息透明化.软件世界,2005(1):86-87.
[66]赵桂红.航空货运定价策略探讨.中国民航学院院报,2003(10):6-11.
[67]田建文.对航空货运运价的制定方法研究.民航经济与技术,2000(5):29-34.
[68]张永莉.航空货运运力的优化分配方法.中国民航学院学报,2005(1):15-18.
[69]Alexander Chemev and Gregory s. Carpenter. The role of market efficiency intuitions in consumer choice: a case of compensatory inference. Journal of Marketing Research, 2001(38):349-361.
[70]Bultz, Howard E, Jr and Leonard. Measuring customer value: gaining the strategic advantage. Organization Dynamics, 1996(24):63-77.
[71]Bayo′n, T., Gutsche, J., & Bauer, H. Customer equity marketing: touching the intangible. European Management Journal, 2002(3):213–222.
[72]Berger, P. D., & Nasr, N. I, Customer lifetime value: marketing models and applications.Journal of Interactive Marketing, 1998(12):17–30.
[73]Gupta, S., & Lehmann, D. R. Customers as assets. Journal of Interactive Marketing, 2003(17): 9–24.
[74] Roberts, M. L., & Berger, P. D. Direct marketing management. Prentice-Hall: Englewood Cliffs, NJ.1989.
[75]Dwyer, F. R. Customer lifetime valuation to support marketing decision making. Journal of Interactive Marketing, 1997.11(4), 6–13.
[76]Hansotia, B., & Rukstales, B. Incremental value modeling. Journal of Interactive Marketing, 2002.16(3): 35–46.
[77]Hyunseok Hwang, Taesoo Jung. An LTV model and customer segmentation based on customer value a case study on the wireless telecommunication industry. Expert Systems with Applications,2004(26):181-188.
[78]Daniel J.Flint Robert B.Woodruff. Customer value change in industrial marketing relationships: A call for new strategies and research. Industrial Marketing Management 1997(26):163-175.
[79]Vibhu Kalyan. Dynamic customer value management in a supply chain asset values under demand uncertainty using airline yield management techniques. I2 technology,1997.
[80]Prabakar Kothandaraman,David T.Wilson. The future of competition value-creating networks. Industrial Marketing Management 1997(30):379-389.
[81]Bob Brotherton , Gerrie Adler. An integrative approach to enhancing customer value and corporate performance in the international hotel industry. Hospitality Management,1999(18):261-272.
[82]Mitsuru Kodama. Customer value creation through community-based information networks. International Journal of Information Management,1999(19):495-508.
[83]Wolfgang Ulaga. Customer value in business markets: an Agenda for Inquiry. Industrial Marketing Management, 2001(30):315-319.
[84]Ke Wang Senqiang Zhou. Mining customer value: from association rules to direct marketing. Proceedings of the 19th International Conference on Data Engineering,2003.
[85]Saharon Rosset. Integrating customer value considerations into predictive modeling. Proceedings of the Third IEEE International Conference on Data Mining,2003.
[86]Ralph L. Keeney. Stimulating creative design alternatives using customer values. IEEE Transactions on systems Management and cybernetics,2004,11.
[87]Joseph M.Spiteri, Paul A.Dion. Customer value, overall satisfaction, end-user loyalty, and market performance in detail intensive industries. Industrial Marketing Management ,2004(33):675-687.
[88]Annie H.Liu, Mark P.Leach. Examining customer value perceptions of organizational buyers when sourcing from multiple vendors. Journal of Business Research,2005(58):559-568.
[89]荆冰彬,齐二石.产品的顾客价值及需求强度分析.天津大学学报(社会科学版),2001(9):51-253.
[90]李振华,王浣尘.基于顾客价值的旅客市场细分研究.工业工程与管理,2003(5):35-37.
[91]王锡秋.基于顾客价值的核心刚性量化分析.控制与决策,2005(1):87-90.
[92]Woodruff, Robert B, Gardial, Sarah F. Customer value change in industrial marketing relationships: a call for new strategies and research. Industrial Marketing Management, 1997,26(2):163-175.
[93]Woodruff, Robert B, Gardial, Sarah F. Know your customer: new approaches to customer value and satisfaction. Blackwell Publishers, Cambridge,MA,1996.
[94]Aranda D A, Monlina-Fernandez L M. Determinants of innovation through a knowledge-based theory lens. Industrial Management Data Systems Wembley,2002.
[95]Pearson R. Towards an historical model of services innovation: the case of the insurance industry 1700-1914. Economics Historical Review,1997(2):60-71.
[96]Den Hertog P. Knowledge intensive business services as co-producers of innovation. Dialogic, Utrecht, The Netherlands,2001.
[97]戴延寿.企业服务创新中的文化冲突及调适.企业经济,2003(4).
[98]许庆瑞,吕飞.服务创新初探.科学学与科学技术管理,2003(3):34-37.
[99]韩剑.论港口服务创新.港口经济,2003(2).
[100]聂文星,周茂荣.服务企业的研究与开发管理.经济管理-新管理,2003(6).
[101]张景银.世界航空货运回顾与展望.综合运输,2005(7):85-86.
[102]Fitzsimmons J A, Fitzsimmons M J.服务管理:运作、策略和信息技术.北京:机械工业出版社,2003.
[103]Ulrich K T, Turg K. Fundamentals of product modularity. Sban School of Management, MIT,1991.
[104]Peters L, Saidin H. IT and the mass customization of services: the challenge of implementation. International Journal of Information Management, 2000(20):103-119.
[105]Stalk G Jr. Time-the next source of competitive advantage. Harvard Business Review,1998,66(4):41-51.
[106]Daniels, N.C. and Essaides, G. Time-based competition. Economic Intelligence Unit,London,1993.
[107]Blackburn, J.D. Time-based competition: the next battleground in American manufacturing.Business One Irwin, Homewood, IL, 1991.
[108]S.Dewan, H.Mendelson. User delay costs and internal pricing for a service facility. Management Science,1990,36(12):1502-1517.
[109]A.Hill, I. Khosla. Models for optimal lead time reduction. Production and Operation Management,1992,1(2):126-132.
[110]K.L.Donohue. The economics of capacity and marketing measures in a simple manufacturing environment. Production and Operation Management, 1994(3): 78-99.
[111]A.H.Buss, S.R.Lawrence, D.H.Kropp. Volume and capacity interaction in facility design. IIE Transactions Design and Manufacturing, 1996,26(4): 36-49.
[112]Kut C.So, Jing-Sheng Song. Price, delivery time guarantees and capacity selection. European Journal of Operational Research, 1998(111): 28-49.
[113]Saibal Ray, E.M. Jewkes. Customer lead time management when both demand and price are lead time sensitive. European Journal of Operational Research, 2004(153): 769-781.
[114]P.J. Lederer, L.Li. Pricing production, scheduling, and delivery-time competition. Operations Research, 1997,45(3): 407-420.
[115]L.Li, Y.S. Lee. Pricing and delivery-time competition. Management Science, 1994,40(5):633-646.
[116]杨文胜,李莉.响应时间不确定下的交货期相关定价研究.中国管理科学,2005(4):56-62.
[117]Bhargara, H.,Sundaresan, S. Contingency pricing for information goods and services under industry wide performance standard. Journal of Management Information Systems, 2003,20(2):113-136.
[118]Lax D.A, Sebenius, J.K. The manager as negotiator: Bargaining for cooperation and competitive gain. Free Press, 1986.
[119]Luo S., M.Cakanyildrim. Overbooking models for air cargo management. Working paper, University of Texas at Dallas, 2005.
[120]Peter. P. Belobaba. Air travel demand and airline seat inventory management. Massachusetts Institute of Technology. May.1987
[121]Feng Y., Gallego G. Evaluating long-term contracts for airlines. Working paper, The Chinese University of Hong Kong, 2003.
[122]陈剑,肖勇波,刘晓玲.航空公司与旅行社的协作机制研究.中国管理科学,2004(3):107-114.
[123]Tang C.S., K.Rajarm, A.Alptekinoglu et al. The benefits of advance booking discount programs. Management Science, 2004,50(4):465-478.
[124]刘宝碇,赵瑞清,王刚.不确定规划及应用.北京:清华大学出版社,2003.
[125]高海军,俞国军,李振龙.基于agent的城市交通信号控制.控制与决策,2004(7):737-740.
[126]Jeffrey L.Adler, Goutam Satapathy,etc.A multi-agent approach to cooperative traffic management and route guidance. Transportation Research Part B, 2005(39):297-318.
[127]彼得S.潘德,罗伯特P.纽曼.6σ管理法:追求卓越的阶梯.北京:机械工业出版社, 2001.
[128]Kevin Linderman, Roger G.Schroeder, Srilata Zaheer, Adrian S.Choo. Six sigma: a goal-theoretic perspective. Journal of Operations Management,2003(21):193-203.
[129]Ayeni, Flora O. An empirical study of the impact of six sigma methodology on organization financial performance in the United States. PhD. UMI ProQuest Digital Dissertations,2004.
[130]P.N.Koch, R.J.Yang, L.Gu. Design for six sigma through robust optimization.Structural Multidisciplinary Optimization,2004(26):235-248.
[131]Kai Yang. Multivariate statistical methods and six-sigma. International Journal of Six Sigma and Competitive Advantage,2004(1):76-96.
[132]Danqian Yu, Peter B,Luh. Achieving reliable delivery in supply chains: the control of uncertainties. International Conferences on Robotics & Automation,2004.4.
[133]何桢,车建国.精益六西格玛:新竞争优势的来源.天津大学学报(社会科学版),2005(9):321-325.
[134]杜栋,莫箐.6σ与ERP中质量管理子系统的集成.数理统计与管理,2005(9):71-82.
[135]汤淑明,王飞跃.过程能力指数综述.应用概率统计,2004(5):207-216.
[2]杨占林,张晨梅.国际物流空运操作实务.北京:中国商务出版社,2004.
[3]刘功仕.发展与边缘化中的我国民航国际货运.中国民用航空,2005(6):19-23.
[4]刘少成,戈锐.中国航空货运发展的政策选择.中国民用航空,2006(8):35-38.
[5]Anming Zhang,Yimin Zhang. A model of air cargo liberalization: passenger vs. all-cargo carriers.Transportation Research Part E, 2002(38):175-191.
[6]Weatherford L R, Bodily S E. A taxonomy and research overview of perishable-asset revenue management: yield management, overbooking and pricing. Operations Research, 1992(40):831-844.
[7]Donaghy K, McMahon U, et al. Yield management: an overview. International Journal of Hospitality Management, 1995, 14(2):139-150.
[8]McGill J I, van Ryzin G J. Revenue management: research overview and prospects. Transportation Science, 1999(33): 233-256.
[9]R G Kasilingam. Air cargo revenue management: characteristics and complexities. European Journal of Operational Research, 1997(96):36-44.
[10]John S.Billings, Adriana G.Diener, Benson B.Yuen. Cargo revenue optimization. Journal of Revenue and Pricing Management, 2003(2):69-79.
[11]R. G. Kasilingam. An economic model for air cargo overbooking under stochastic capacity. Computer Industry Engineering, 1997(32):221-226.
[12]Littlewood, K. Forecasting and control of passengers. 12th AGIFORS Symposium Proceedings, 1972:103-105.
[13]Lee T C, M. Hersh. A model for dynamic airline seat inventory control with multiple seat bookings. Transportation Science, 1993, 27(3):252-265.
[14]McGill J I. Censored regression analysis of multi-class demand data subject to joint capacity constraints. The Annals of Operations Research, 1995(60):209-240.
[15]Bodily S, Pfeifer P E. Overbooking decision rules. Omaga, 1992(20):129-133.
[16]Robinson L W. Optimal and approximate control polices for airline booking with sequential fare class. Operations Research, 1995(43):252-263.
[17]Belobaba P P, Farkas A. Yield management impacts on spill estimation. Transportation Science, 1999, 33(2):217-232.
[18]Chatwin R E. Continuous time airline overbooking with time-dependent fares and refunds.Transportation Science, 1999, 33(2):182-191.
[19]Liang Y. Solution to the continuous time dynamic yield management mode. Transportation Science, 1999, 33(1):117-123.
[20]Feng Y, Gallego G. Optimal starting times for end-of-season sales and optimal stopping-times for promotional fares. Management Science, 1995(41):1371-1391.
[21]Feng Y, Gallego G. Perishable asset revenue management with markovian time dependent demand intensities. Management Science, 2000(46):941-956.
[22]Feng Y, Xiao B. Optimal policies of yield management with multiple predetermined prices. Operations Research, 2000a(48):332-343.
[23]Feng Y, Xiao B. A continuous-time yield management model with multiple prices and reversible price changes. Management Science, 2000b(46):644-657.
[24]Gallego G, van Ryzin G. Optimal dynamic pricing of inventories with stochastic demand over finite horizons. Management Science, 1994(40):999-1020.
[25]Gallego G, van Ryzin G. A multi-product dynamic pricing problem and its application to network yield management. Operations Research, 1997(45):24-41.
[26]Glover F R, Glover J L, Mcmillan C. The passenger-mix problem in the scheduled airlines. Interfaces, 1982(12):73-79.
[27]Belobaba P P. Airline yield management: an overview of seat inventory control. Transportation Science. 1987, 21(2):63-73.
[28]Belobaba P P. Application of a probabilistic decision model to airlines seat inventory control. Operations Research, 1989(37):183-197.
[29]Brumelle S L, McGill J I. Airlines seat allocation with multiple nested fare classes. Operations Research, 1993(41);127-137.
[30]Curry R. Optimal seat allocation with fare classes nested by origins and destinations. Transportation Science, 1990(24):193-204.
[31]Wollmer R D. A hub-spoke seat management model. Douglas Aircraft Company,McDonnel Douglas Corporation, Long Beach, CA, 1992.
[32]Lautenbatcher C J, Stidaham J R. The underlying markov decision process in the single-leg airline yield management problem. Transportation Science, 1999, 33(2):136-146.
[33]Subramanian J, S Stidham, C J Lautenbacher. Airline yield management problem with overbooking, cancellations and no shows. Transportation Science, 1999, 33(2):147-167.
[34]Do Boer S V, Freling R, Piersma N. Stochastic programming for multiple-leg network revenue management. European Journal of Operational Research, 2002(137):72-92.
[35]Talluri K T, Van Ryzin. An analysis of bid-price controls for network revenue management.Management Science, 1998, 44(11):1577-1593.
[36]Talluri K T, Van Ryzin. A randomized linear programming method for computing network bid prices. Transportation Science, 1999, 33(2):207-216.
[37]Talluri K T, Van Ryzin. Revenue management under a general discret choice model of consumer behavior. Management Science, 2004, 50(1):15-33.
[38]Chen V C, Gunther D, E L Johnson. A marokov decision problem based approach to the airline yield management problem. Working Paper, The Logistics Institute, Georgia Institute of Technology, Atlanta, GA, 1998.
[39]Bertsmias D, De Boer S. Simulation based optimization for airline network yield management. Working Paper, Massachusetts Institute of Technology, Cambridge, MA, 2001.
[40]Bertsmias D, Popescu I. Revenue management in a dynamic network environment. Transportation Science,2003, 37(3):257-277.
[41] Itlr Zeynep Karaesmen. Three essays on revenue management .UMI,2001.
[42]Kleywegt, A J, Papastavrou J D. The dynamic and stochastic knapsack problem, Operations Research, 1998(46):17-35.
[43] Kleywegt, A J, Papastavrou J D. The dynamic and stochastic knapsack problem with random sized items, Operations Research, 2001(49):26-41.
[44]Kevin Pak, Rommert Dekker. Cargo revenue management: bid-prices for a 0-1 multi-knapsack problem Working Paper, Erasmus University, 2004,6.
[45]Paul Bartodziej, Ulrich Derigs. On an experimental algorithm for revenue management for cargo airlines. Lecture Notes in Computer Science, 2004(3059):57-71.
[46] Bart Slager, Luuk Kapteijns. Implementation of cargo revenue management at KLM. Journal of Revenue and Pricing Management, 2004(3):80-90.
[47] P.Bartodziej, U.Derigs, M.Zils. O&D revenue management in cargo airlines-a mathematical programming approach. OR Spectrum, 2006, February online.
[48]Ek-Peng Chew, Huei-Chuen Huang, et al. Short-term booking of air cargo space. European Journal of Operational Research. 2006(174):1979-1990.
[49]Andreea Popescu, Pinar Keskinocak,etc. Estimation air-cargo overbooking based on a discrete show-up-rate distribution. Interfaces,2006(3):248-258.
[50]Kannapha Amaruchkul,William L. Cooper, Diwakar Gupta. Single-Leg air-cargo revenue management. working paper, University of Minnesota,2006.3.
[51]Yu-Hern Chang, Chung-Hsing Yeh. A survey analysis of service quality for domestic airlines. European Journal of Operational Research,2002(139):166-177.
[52]Jin-Woo Park,Rodger Robertson. The effect of airline service quality on passengers’behavioural intentions a Korean case study. Journal of Air Transport Management, 2004(10):435-439.
[53]Fang-Yuan Chen, Yu-Hern Chang. Examining airline service quality from a process perspective. Journal of Air Transport Management,2005(11):79-87.
[54]Anming Zhang. Analysis of an international air-cargo hub: the case of Hong Kong. Air Transport Management, 2003(9):123-138.
[55]Joseph Berechman, N. Adler. Airport quality and hub location question. Air Transport Management, 2001(5):67-74.
[56]Hiroshi Ohashi, Tae-Seun Kim. Choice of air cargo transshipment airport: an application to air cargo traffic to/from Northeast Asia. http://www.e.u-tokyo.ac.jp/cirje/research/03research.html
[57]Anming Zhang, Lawrence Leung. Air cargo alliance and competition in passenger markets. Transportation Research, 2004(40):83-100.
[58]Paul W Forster. Electronic integration in the air cargo industry: an information processing model of on-time performance. Transportation Journal, 2002, 40(4):46-61.
[59]Aaton L Nsakanda, Michel Turcotte. Air cargo operations evaluation and analysis through simulation. Proceedings of the 2004 Winter Simulation Conference, 2004:1790-1798.
[60]赵杨.低成本航空成为亚洲航空发展趋势.AMT研究院, http:www.amteam.org/static/49749.html,2004.10.13
[61]吴旭慧,储雪俭.论航空货运企业向空地一体化转型.物流技术,2005(1):19-21.
[62]吴昌勇.航空物流园区形成机理.中国民用航空,2004(8):56-57.
[63]王冬梅.机场与航空公司运营关系探讨.民航管理,2004(3):37-39.
[64]龚志峰,范守文,霍丽芙.航空物流中心系统动态布置设计.机械制造,2005(3):40-42.
[65]胡国丹.航空物流供应链的信息透明化.软件世界,2005(1):86-87.
[66]赵桂红.航空货运定价策略探讨.中国民航学院院报,2003(10):6-11.
[67]田建文.对航空货运运价的制定方法研究.民航经济与技术,2000(5):29-34.
[68]张永莉.航空货运运力的优化分配方法.中国民航学院学报,2005(1):15-18.
[69]Alexander Chemev and Gregory s. Carpenter. The role of market efficiency intuitions in consumer choice: a case of compensatory inference. Journal of Marketing Research, 2001(38):349-361.
[70]Bultz, Howard E, Jr and Leonard. Measuring customer value: gaining the strategic advantage. Organization Dynamics, 1996(24):63-77.
[71]Bayo′n, T., Gutsche, J., & Bauer, H. Customer equity marketing: touching the intangible. European Management Journal, 2002(3):213–222.
[72]Berger, P. D., & Nasr, N. I, Customer lifetime value: marketing models and applications.Journal of Interactive Marketing, 1998(12):17–30.
[73]Gupta, S., & Lehmann, D. R. Customers as assets. Journal of Interactive Marketing, 2003(17): 9–24.
[74] Roberts, M. L., & Berger, P. D. Direct marketing management. Prentice-Hall: Englewood Cliffs, NJ.1989.
[75]Dwyer, F. R. Customer lifetime valuation to support marketing decision making. Journal of Interactive Marketing, 1997.11(4), 6–13.
[76]Hansotia, B., & Rukstales, B. Incremental value modeling. Journal of Interactive Marketing, 2002.16(3): 35–46.
[77]Hyunseok Hwang, Taesoo Jung. An LTV model and customer segmentation based on customer value a case study on the wireless telecommunication industry. Expert Systems with Applications,2004(26):181-188.
[78]Daniel J.Flint Robert B.Woodruff. Customer value change in industrial marketing relationships: A call for new strategies and research. Industrial Marketing Management 1997(26):163-175.
[79]Vibhu Kalyan. Dynamic customer value management in a supply chain asset values under demand uncertainty using airline yield management techniques. I2 technology,1997.
[80]Prabakar Kothandaraman,David T.Wilson. The future of competition value-creating networks. Industrial Marketing Management 1997(30):379-389.
[81]Bob Brotherton , Gerrie Adler. An integrative approach to enhancing customer value and corporate performance in the international hotel industry. Hospitality Management,1999(18):261-272.
[82]Mitsuru Kodama. Customer value creation through community-based information networks. International Journal of Information Management,1999(19):495-508.
[83]Wolfgang Ulaga. Customer value in business markets: an Agenda for Inquiry. Industrial Marketing Management, 2001(30):315-319.
[84]Ke Wang Senqiang Zhou. Mining customer value: from association rules to direct marketing. Proceedings of the 19th International Conference on Data Engineering,2003.
[85]Saharon Rosset. Integrating customer value considerations into predictive modeling. Proceedings of the Third IEEE International Conference on Data Mining,2003.
[86]Ralph L. Keeney. Stimulating creative design alternatives using customer values. IEEE Transactions on systems Management and cybernetics,2004,11.
[87]Joseph M.Spiteri, Paul A.Dion. Customer value, overall satisfaction, end-user loyalty, and market performance in detail intensive industries. Industrial Marketing Management ,2004(33):675-687.
[88]Annie H.Liu, Mark P.Leach. Examining customer value perceptions of organizational buyers when sourcing from multiple vendors. Journal of Business Research,2005(58):559-568.
[89]荆冰彬,齐二石.产品的顾客价值及需求强度分析.天津大学学报(社会科学版),2001(9):51-253.
[90]李振华,王浣尘.基于顾客价值的旅客市场细分研究.工业工程与管理,2003(5):35-37.
[91]王锡秋.基于顾客价值的核心刚性量化分析.控制与决策,2005(1):87-90.
[92]Woodruff, Robert B, Gardial, Sarah F. Customer value change in industrial marketing relationships: a call for new strategies and research. Industrial Marketing Management, 1997,26(2):163-175.
[93]Woodruff, Robert B, Gardial, Sarah F. Know your customer: new approaches to customer value and satisfaction. Blackwell Publishers, Cambridge,MA,1996.
[94]Aranda D A, Monlina-Fernandez L M. Determinants of innovation through a knowledge-based theory lens. Industrial Management Data Systems Wembley,2002.
[95]Pearson R. Towards an historical model of services innovation: the case of the insurance industry 1700-1914. Economics Historical Review,1997(2):60-71.
[96]Den Hertog P. Knowledge intensive business services as co-producers of innovation. Dialogic, Utrecht, The Netherlands,2001.
[97]戴延寿.企业服务创新中的文化冲突及调适.企业经济,2003(4).
[98]许庆瑞,吕飞.服务创新初探.科学学与科学技术管理,2003(3):34-37.
[99]韩剑.论港口服务创新.港口经济,2003(2).
[100]聂文星,周茂荣.服务企业的研究与开发管理.经济管理-新管理,2003(6).
[101]张景银.世界航空货运回顾与展望.综合运输,2005(7):85-86.
[102]Fitzsimmons J A, Fitzsimmons M J.服务管理:运作、策略和信息技术.北京:机械工业出版社,2003.
[103]Ulrich K T, Turg K. Fundamentals of product modularity. Sban School of Management, MIT,1991.
[104]Peters L, Saidin H. IT and the mass customization of services: the challenge of implementation. International Journal of Information Management, 2000(20):103-119.
[105]Stalk G Jr. Time-the next source of competitive advantage. Harvard Business Review,1998,66(4):41-51.
[106]Daniels, N.C. and Essaides, G. Time-based competition. Economic Intelligence Unit,London,1993.
[107]Blackburn, J.D. Time-based competition: the next battleground in American manufacturing.Business One Irwin, Homewood, IL, 1991.
[108]S.Dewan, H.Mendelson. User delay costs and internal pricing for a service facility. Management Science,1990,36(12):1502-1517.
[109]A.Hill, I. Khosla. Models for optimal lead time reduction. Production and Operation Management,1992,1(2):126-132.
[110]K.L.Donohue. The economics of capacity and marketing measures in a simple manufacturing environment. Production and Operation Management, 1994(3): 78-99.
[111]A.H.Buss, S.R.Lawrence, D.H.Kropp. Volume and capacity interaction in facility design. IIE Transactions Design and Manufacturing, 1996,26(4): 36-49.
[112]Kut C.So, Jing-Sheng Song. Price, delivery time guarantees and capacity selection. European Journal of Operational Research, 1998(111): 28-49.
[113]Saibal Ray, E.M. Jewkes. Customer lead time management when both demand and price are lead time sensitive. European Journal of Operational Research, 2004(153): 769-781.
[114]P.J. Lederer, L.Li. Pricing production, scheduling, and delivery-time competition. Operations Research, 1997,45(3): 407-420.
[115]L.Li, Y.S. Lee. Pricing and delivery-time competition. Management Science, 1994,40(5):633-646.
[116]杨文胜,李莉.响应时间不确定下的交货期相关定价研究.中国管理科学,2005(4):56-62.
[117]Bhargara, H.,Sundaresan, S. Contingency pricing for information goods and services under industry wide performance standard. Journal of Management Information Systems, 2003,20(2):113-136.
[118]Lax D.A, Sebenius, J.K. The manager as negotiator: Bargaining for cooperation and competitive gain. Free Press, 1986.
[119]Luo S., M.Cakanyildrim. Overbooking models for air cargo management. Working paper, University of Texas at Dallas, 2005.
[120]Peter. P. Belobaba. Air travel demand and airline seat inventory management. Massachusetts Institute of Technology. May.1987
[121]Feng Y., Gallego G. Evaluating long-term contracts for airlines. Working paper, The Chinese University of Hong Kong, 2003.
[122]陈剑,肖勇波,刘晓玲.航空公司与旅行社的协作机制研究.中国管理科学,2004(3):107-114.
[123]Tang C.S., K.Rajarm, A.Alptekinoglu et al. The benefits of advance booking discount programs. Management Science, 2004,50(4):465-478.
[124]刘宝碇,赵瑞清,王刚.不确定规划及应用.北京:清华大学出版社,2003.
[125]高海军,俞国军,李振龙.基于agent的城市交通信号控制.控制与决策,2004(7):737-740.
[126]Jeffrey L.Adler, Goutam Satapathy,etc.A multi-agent approach to cooperative traffic management and route guidance. Transportation Research Part B, 2005(39):297-318.
[127]彼得S.潘德,罗伯特P.纽曼.6σ管理法:追求卓越的阶梯.北京:机械工业出版社, 2001.
[128]Kevin Linderman, Roger G.Schroeder, Srilata Zaheer, Adrian S.Choo. Six sigma: a goal-theoretic perspective. Journal of Operations Management,2003(21):193-203.
[129]Ayeni, Flora O. An empirical study of the impact of six sigma methodology on organization financial performance in the United States. PhD. UMI ProQuest Digital Dissertations,2004.
[130]P.N.Koch, R.J.Yang, L.Gu. Design for six sigma through robust optimization.Structural Multidisciplinary Optimization,2004(26):235-248.
[131]Kai Yang. Multivariate statistical methods and six-sigma. International Journal of Six Sigma and Competitive Advantage,2004(1):76-96.
[132]Danqian Yu, Peter B,Luh. Achieving reliable delivery in supply chains: the control of uncertainties. International Conferences on Robotics & Automation,2004.4.
[133]何桢,车建国.精益六西格玛:新竞争优势的来源.天津大学学报(社会科学版),2005(9):321-325.
[134]杜栋,莫箐.6σ与ERP中质量管理子系统的集成.数理统计与管理,2005(9):71-82.
[135]汤淑明,王飞跃.过程能力指数综述.应用概率统计,2004(5):207-216.