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- Hotel demand forecasting models and methods using artificial intelligence: a systematic literature reviewPublication . Henriques, Henrique; Pereira, Luis Nobre; Henriques, Henrique; Nobre Pereira, LuisThis systematic literature review (SLR) explores current state-of-the-art artificial intelligence (AI) methods for forecasting hotel demand. Since revenue management (RM) is crucial for business success in the hotel industry, this study aims to identify state-of-the-art effective AI -based solutions for hotel demand forecasting, including machine learning (ML), deep learning (DP), and artificial neural networks (ANNs). The study conducted an SLR using the PRISMA model and identified 20 papers indexed in Scopus and the Web of Science. It addresses the gaps in the literature on AI -based demand forecasting, highlighting the need for clarity in model specification, understanding the impact of AI on pricing accuracy and financial performance, and the challenges of available data quality and computational expertise. The review concludes that AI technology can significantly improve forecasting accuracy and empower data -driven decisions in hotel management. Additionally, this study discusses the limitations of AI -based demand forecasting, such as the need for high -quality data. It also suggests future research directions for further enhancing AI forecasting techniques in the hospitality industry.
- The application of Artificial Intelligence in the tourism industry: a systematic literature review based on prisma methodologyPublication . Henriques, Henrique; Ribeiro de Almeida, Claudia; Ramos, CeliaTourism is one of the biggest industries in the world and its contribution to the global economy has continued to grow. Due to the rapid development of technology, tourism has seen some critical changes in how people interact with the industry. By applying artificial intelligence (AI) to different aspects of the tourism business, it is possible to increase efficiency by using resources more effectively. This paper aims to provide insights into how AI technologies can be applied to different aspects of tourism operations and services to improve the customer experience both online and offline and at service providers such as hotels. A literature review is conducted based on the PRISMA methodology by running searches on databases Scopus and Web of Science. This research contributes to providing an overview of how current AI technologies are used in the tourism industry and how they may be used in the fu- ture to enhance customers' experiences when interacting with different aspects of tourism. It also examines various concerns that need further investigation before adoption can occur. The review shows that the application of AI technologies can improve numerous facets of tourism operations and services, resulting in numerous advantages.