Concepts

Addressed studies

Shared characteristics

Future Research

Inter-municipal Tourism

Consortia

The studies by de Almeida and Viegas (2016) , Bueno and Leal (2017) , Ferreira and Pereira (2016) , Nogarotto and Marques (2019) , Pinto and Silva (2019) , Schmitz and Grande (2014) , and Vieira and Antonini (2014) analyze inter-municipal tourism consortia in Brazil and highlight their characteristics, challenges, and prospects for regional development. These research studies emphasize the importance of these consortia as instruments of cooperation between municipalities to strengthen tourism in a given region.

Municipal cooperation: inter-municipal consortia are forms of cooperation between different municipalities for the joint development of tourism.

Regional development: consortia aim to promote regional development through tourism, focusing on increasing the supply of tourism products and services, improving infrastructure and promoting destinations.

Integrated management: the studies emphasize the importance of integrated management in the consortia, covering aspects such as strategic planning, governance, tourism marketing, resource mobilization and partnerships.

Impact assessment: future research can focus on assessing the impact of inter-municipal tourism consortia on regional development, including economic, social, and environmental aspects.

Sustainability: studies can examine the incorporation of sustainable tourism practices into inter-municipal consortia, taking into account natural resource conservation, social inclusion, and balanced economic development.

Private sector participation: private sector participation in consortia, its contribution to tourism development, and public-private partnerships may be topics of interest for future research.

Artificial

Intelligence in Tourism

The studies of Buhalis and Amaranggana (2019) , Cai, McKenna, and Song (2020) , Chen, Li, and Lin (2019) , Li, Wang, and Liang (2018) , Ferreira, Kozak, Kim, and Buhalis (2020) , Nejati, Pourfakhimi, and Amini (2021) , and Wang, Li, Liang, and Huang (2019) explore the application of AI in tourism and address topics such as smart destinations, tourism demand forecasting, and personalized tourism marketing.

Smart tourism destinations: The studies shed light on the concept of smart tourism destinations, where AI is used to manage and enhance the tourism experience, optimize resource management, and promote sustainability. Tourist demand forecasting: AI is used in predicting tourism demand, using algorithms and predictive models to support strategic decisions, such as capacity planning, service supply, and resource allocation. Personalized marketing: AI is used to personalize tourism marketing offers and provide recommendations and experiences based on individual tourist preferences and characteristics.

Tourist Experience: Future research may explore the application of AI to further enhance the tourist experience, including real-time personalization, virtual assistants and chatbots for customer service, and the use of technologies such as augmented reality and virtual reality.

Data analytics and Big Data: AI can be used to extract valuable insights from large amounts of data collected in the tourism industry, enabling a deeper understanding of tourists’ behavior patterns, market trends and preferences.

Market Intelligence: Future research can explore how AI can be used to analyze the competitive environment in tourism, identify market opportunities, anticipate trends, and help formulate competitive strategies for destinations and tourism businesses.