Most hospitality revenue management forecasting systems were built prior to the business intelligence and analytics movement. Only recently these systems have been enhanced to offer contemporary business intelligence and analytics functionalities. In addition, revenue management professionals are receiving support from standalone, supplementary business intelligence and analytics platforms. The purpose of this dissertation was to produce a holistic review of and establish the role of business intelligence and analytics within hospitality revenue management. Data was collected from twenty-three interviews; all participants were employed by hospitality organizations in revenue management specific positions. Grounded theory methodology was utilized. The results show that nearly all of revenue management tasks are supported by business intelligence and analytics functionalities, irrespective of where the functionalities are housed, in revenue management systems or in business intelligence and analytics tools. Also, opportunities to integrate more advanced functionalities into revenue management systems, including those relating to interfaces, were identified. As part of this inquiry, revenue managers’ beliefs and perceptions - including relative advantage, job-fit, and trust - were examined to determine which have influence on the usage of business intelligence and analytics within revenue management systems and as standalone tools. Overall, twenty-two categories/themes were formulated across four research questions. This dissertation contributes to the examination of the role of business intelligence and analytics in hospitality revenue management, but there is still much more to investigate, particularly as compatibility of hospitality systems and data management are improved
