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Developing an integrated revenue management and customer relationship management approach in the hotel industry

机译:在酒店行业开发集成的收入管理和客户关系管理方法

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Revenue management (RM) and customer relationship management (CRM) are the standard strategies of many hotels to increase their profitability. Although the objectives and time horizons of RM and CRM are different, they can be considered as complimentary business strategies. However, the integration has received little attention both practically and theoretically. In this study, we develop an approach to jointly make the capacity allocation and overbooking decisions considering CRM strategies over a hotel network. Hotel customers are divided based on their lifetime value into two major groups of occasional and loyal customers. Price discounts and room availability guarantee (RAG) are offered to loyal customers, who are the hotel's essential source of profit. The main problem is tackled by a stochastic dynamic programming model whose expected value of objective function is approximated by two deterministic linear programming-based algorithms. The computational results indicate that the loyalty programs may lead to decrease in short-term net revenue. However, another analysis is required to decide upon cost-effectiveness of loyalty programs in an extended planning horizon. On the basis of an estimated discount-RAG response function, the cost-effectiveness of different loyalty programs is compared, which shows potential increase in hotel expected net revenue up to 3.5 per cent. The analytical long-term evaluation of loyalty programs introduced is capable of determining the most appropriate loyalty program factors. Moreover, it suggests discount-RAG response function and the level of tightness as sensitive parameters.
机译:收入管理(RM)和客户关系管理(CRM)是许多酒店提高盈利能力的标准策略。尽管RM和CRM的目标和时间范围不同,但可以将它们视为免费的业务策略。但是,集成在实践上和理论上都很少受到关注。在这项研究中,我们开发了一种方法,可以结合酒店网络上的CRM策略共同制定容量分配和超量预订决策。酒店客户根据其终生价值分为偶然客户和忠实客户两大类。价格折扣和客房供应保证(RAG)提供给忠诚的客户,这些客户是酒店的主要利润来源。主要问题是通过随机动态规划模型解决的,该模型的目标函数的期望值通过两种基于确定性线性规划的算法来近似。计算结果表明,忠诚度计划可能会导致短期净收入减少。但是,还需要进行另一项分析,才能在扩展的计划范围内确定忠诚度计划的成本效益。根据估计的折扣RAG响应函数,比较了不同忠诚度计划的成本效果,这表明酒店预期的净收入可能增长至3.5%。对忠诚度计划进行的分析性长期评估能够确定最合适的忠诚度计划因素。此外,它建议采用折扣RAG响应函数和紧密度作为敏感参数。

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