我国酒店业收益管理中关于过量预订的应用研究
发布时间：2018-07-22 11:13
【摘要】： 收益管理理论和方法最早起源于美国国内航空业。本文回顾了收益管理发展的历史，，认为酒店业收益管理是指在市场细分和需求预测的基础上，酒店管理者运用价格歧视的手段来引导需求．并对客房结构进行合理地调配，在满足各细分市场需求的同时，使客房尽可能以顾客可以接受的最高价出售，从而最大限度地提高酒店的收入。酒店业收益管理是一种精益营销管理方式。酒店收益管理系统是基于收益管理思想方法和管理信息系统的人工智能的机制，是收益管理在酒店中的具体应用形式和载体。 本文试图运用收益管理的理论，结合我国酒店业自身的特点，探讨在酒店中实施收益管理的途径和寻求实用性方法。 本文采用理论分析和实证研究相结合的方法，对需求预测、过量预订、大客户管理、淡旺季管理、酒店收益管理系统的建立等收益管理主要内容进行了分析。对需求预测，介绍了定性和定量的预测方法，并实证研究了季节指数预测法和增量逼近法；在过量预订方面，讨论了过量预订的原因、风险并提出确定过量预订额度的计算方法；在大客户管理方面，定义了大客户的范围，指出大客户的分类方法和对酒店的重要性，强调酒店要对大客户密切关注并进行评估；对于经营的淡旺季，本文认为，只要平时提前做好准备并不断挖掘需求，淡季给酒店带来的负面影响是可以消除的：为了做好收益管理，酒店还应该建立收益管理系统并使之正常运转。 通过详细的理论分析和实证研究，本文阐明了影响酒店业收益管理实施的内部和外部障碍，并提出了解决的对策。 收益管理适用于中国酒店业并具有实际可操作性，期望本文能对新时代下的酒店收益管理提供参考。
[Abstract]:The theory and method of revenue management originated from the domestic aviation industry in the United States. This paper reviews the history of revenue management, and holds that revenue management in hotel industry is based on market segmentation and demand forecasting, and hotel managers use price discrimination to guide demand, and make reasonable allocation of guest room structure. At the same time, the guest rooms can be sold at the highest price acceptable to the customers, so as to maximize the revenue of the hotel. Hotel revenue management is a lean marketing management method. The hotel revenue management system is based on the revenue management thought method and the management information system artificial intelligence mechanism, is the income management in the hotel concrete application form and the carrier. Based on the theory of revenue management and the characteristics of hotel industry in China, this paper attempts to explore the ways to implement revenue management in hotels and to seek practical methods. In this paper, the main contents of revenue management, such as demand forecasting, over-booking, large account management, weak season management and the establishment of hotel revenue management system, are analyzed by combining theoretical analysis and empirical research. The qualitative and quantitative forecasting methods are introduced, and the seasonal index forecasting method and incremental approximation method are empirically studied, and the reasons for excessive reservation are discussed. In the aspect of large account management, it defines the scope of the big customer, points out the classification method of the big customer and its importance to the hotel, and emphasizes that the hotel should pay close attention to the big customer and evaluate it. For the weak season, this paper believes that the negative effects of the off-season on hotels can be eliminated as long as they are prepared in advance and constantly excavated the demand: in order to do a good job of revenue management, The hotel should also establish a revenue management system and make it work properly. Through detailed theoretical analysis and empirical research, this paper expounds the internal and external obstacles that affect the implementation of revenue management in the hotel industry, and puts forward some countermeasures. Revenue management is applicable to the hotel industry in China and has practical maneuverability. It is expected that this paper can provide a reference for the hotel revenue management in the new era.
【学位授予单位】：贵州大学
【学位级别】：硕士
【学位授予年份】：2007
【分类号】：F719
本文编号：2137261
[Abstract]:The theory and method of revenue management originated from the domestic aviation industry in the United States. This paper reviews the history of revenue management, and holds that revenue management in hotel industry is based on market segmentation and demand forecasting, and hotel managers use price discrimination to guide demand, and make reasonable allocation of guest room structure. At the same time, the guest rooms can be sold at the highest price acceptable to the customers, so as to maximize the revenue of the hotel. Hotel revenue management is a lean marketing management method. The hotel revenue management system is based on the revenue management thought method and the management information system artificial intelligence mechanism, is the income management in the hotel concrete application form and the carrier. Based on the theory of revenue management and the characteristics of hotel industry in China, this paper attempts to explore the ways to implement revenue management in hotels and to seek practical methods. In this paper, the main contents of revenue management, such as demand forecasting, over-booking, large account management, weak season management and the establishment of hotel revenue management system, are analyzed by combining theoretical analysis and empirical research. The qualitative and quantitative forecasting methods are introduced, and the seasonal index forecasting method and incremental approximation method are empirically studied, and the reasons for excessive reservation are discussed. In the aspect of large account management, it defines the scope of the big customer, points out the classification method of the big customer and its importance to the hotel, and emphasizes that the hotel should pay close attention to the big customer and evaluate it. For the weak season, this paper believes that the negative effects of the off-season on hotels can be eliminated as long as they are prepared in advance and constantly excavated the demand: in order to do a good job of revenue management, The hotel should also establish a revenue management system and make it work properly. Through detailed theoretical analysis and empirical research, this paper expounds the internal and external obstacles that affect the implementation of revenue management in the hotel industry, and puts forward some countermeasures. Revenue management is applicable to the hotel industry in China and has practical maneuverability. It is expected that this paper can provide a reference for the hotel revenue management in the new era.
【学位授予单位】：贵州大学
【学位级别】：硕士
【学位授予年份】：2007
【分类号】：F719
【引证文献】
相关硕士学位论文 前3条
1 赵静宜;基于收益管理的饭店经营管理研究[D];东北财经大学;2011年
2 胡翔;中外旅游饭店收益管理对比与应用研究[D];山东师范大学;2012年
3 王邦花;酒店实施收益管理对顾客满意度影响的实证研究[D];青岛大学;2012年
本文编号：2137261
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