摘 要
在数字化快速发展的背景下，酒店行业面临日益激烈的市场竞争与消费者需求的深刻变革，传统的收益管理模式已难以满足现代酒店运营的需求。本研究旨在探讨数字化技术如何优化酒店收益管理策略，提升酒店经营效益与市场竞争力。通过梳理收益管理理论基础，结合大数据分析、人工智能算法及动态定价模型等方法，构建适用于酒店实际运营的收益管理优化框架。研究采用定量分析与案例研究相结合的方式，选取国内多家中高端酒店作为研究对象，利用历史预订数据与实时市场需求进行模型验证与策略测试。结果表明，基于数据驱动的动态定价策略能够显著提高客房平均收益率与入住率，同时通过客户细分与需求预测，有效提升了营销精准度与客户满意度。本研究的创新点在于将机器学习算法引入酒店收益管理领域，并结合实时市场反馈机制优化价格调整策略，为酒店提供了更具前瞻性和灵活性的决策支持工具。研究的主要贡献在于推动了酒店业从经验导向向数据驱动的转型，为数字化背景下的酒店收益管理提供了切实可行的优化路径与实践参考。
关键词：酒店收益管理；数字化技术；动态定价策略；机器学习算法；客户细分与需求预测
Optimization Strategies for Hotel Revenue Management in the Digital Era
Abstract: Against the backdrop of rapid digitalization, the hotel industry faces increasingly fierce market competition and profound changes in consumer demand, making traditional revenue management models inadequate to meet the needs of modern hotel operations. This study aims to explore how digital technologies can optimize hotel revenue management strategies and enhance operational efficiency and market competitiveness. By reviewing the theoretical foundations of revenue management and integrating methodologies such as big data analytics, artificial intelligence algorithms, and dynamic pricing models, this research constructs an optimized revenue management fr amework applicable to real-world hotel operations. The study adopts a mixed-methods approach combining quantitative analysis with case studies, selecting multiple mid- to high-end hotels in China as research subjects. Historical booking data and real-time market demand are utilized to validate the models and test the strategies. Results indicate that data-driven dynamic pricing strategies can significantly improve average room yield and occupancy rates, while customer segmentation and demand forecasting further enhance marketing precision and guest satisfaction. The innovation of this study lies in introducing machine learning algorithms into the domain of hotel revenue management and integrating a real-time market feedback mechanism to refine price adjustment strategies, thereby offering hotels more forward-looking and flexible decision-support tools. The primary contribution of this research is facilitating the transformation of the hotel industry from experience-based decision-making to data-driven management, providing practical and feasible optimization pathways for revenue management in the digital era.
Keywords: Hotel Revenue Management; Digital Technologies; Dynamic Pricing Strategies; Machine Learning Algorithms; Customer Segmentation and Demand Forecasting
目 录
1绪论 1
1.1研究背景和意义 1
1.2研究现状 1
1.3本文研究方法 1
2数字化转型对酒店收益管理的影响分析 2
2.1酒店行业数字化发展的主要趋势 2
2.2数字技术在收益管理中的应用演进 2
2.3数据驱动决策对收益管理模式的重构 3
2.4数字化背景下酒店收益管理面临的挑战 3
3基于大数据的酒店需求预测与价格优化策略 4
3.1大数据在酒店市场需求预测中的作用 4
3.2动态定价模型的设计与实现路径 4
3.3客户细分与个性化定价策略 5
3.4收益预测精度提升的技术手段 5
4智能系统支持下的酒店收益管理流程优化 6
4.1智能收益管理系统的核心功能模块 6
4.2收益管理流程的自动化与集成化改造 6
4.3人工智能在收益优化中的决策辅助机制 7
4.4系统实施效果评估与持续优化路径 7
结论 8
参考文献 9
致 谢 10
