Revenue Management and Pricing Optimization in Hospitality and Tourism Consulting: A Systematic Literature Review

Revenue management (RM), the collection of strategies that firms use to scientifically manage demand for their products and services, is considered as one of the most successful application areas of operations research. This systematic literature review (SLR) explores revenue management techniques in the hospitality and tourism. Such techniques include dynamic pricing algorithms, forecasting demand with urbane statistical models, overbooking strategies, ancillary revenue optimization, and the impact of behavioral economics on pricing decisions. The study conducted an SLR using the PRISMA model and identified 365 Scopus indexed documents. Descriptive analyses, citation analysis, co-citation analysis, and keyword co-occurrence analysis were used to investigate the intellectual structure of the revenue management literature. Findings showed that the concept of RM has been globally examined since 1989 with greater interest over time. According to co-citation analysis, three schools of thought are identified, including customer orientation, operational performance, and revenue management technique. Most highly influential documents are conceptual papers. Results also reveal that 6 dominant topics in the research field of RM such as dynamic pricing, tourism, hotel, hospitality, machine learning, and consumer behavior, have recently been examined in the literature. This review concludes that RM techniques can significantly improve price optimization and foster data-driven decision making in the management of businesses in the hospitality sector. Limitations of RM strategies such as the potential lack of understanding of specific hospitality contexts, reliance on outdated data, and challenges in accurately forecasting demand and managing distribution channels are also discussed. Similarly, there can be disconnect between theoretical models and practical application, especially regarding human resources and the impact of external factors like economic conditions. It also suggests future research directions for further enhancing RM techniques and pricing optimization in the hospitality and tourism consulting.