This session is organized around the broad theme of business intelligence and big data applications in tourism. As the main driver behind innovation capacity of tourism destinations, knowledge has been identified as the essential base for long-term competitiveness and sustainable development.
Furthermore, following the knowledge-based view of the firm (Grant 1996), an organization’s value is limited by the amount of knowledge within it. Information and communication technologies (ICTS) play a crucial role to increase the knowledge base of destinations and their stakeholders. Organizational learning and managerial effectiveness can particularly be enhanced by applying methods of business intelligence (BI).
Customers leave electronic traces during all travel-related activities, like searching and trip planning, reservation and booking, service consumption as well as feedback provision in community web-sites (e.g. social media platforms) or through online surveys. Consequently, a huge amount of data on customer needs and behavior as well as perception is stored in various knowledge sources at tourism destinations.
Despite that methods of business intelligence and knowledge extraction are employed in some travel and tourism domains, current applications usually deal with different business processes separately, which then lacks a cross-process analysis approach that cover all business processes of a destination and its stakeholders. Also, overall, in contrast to other branches, business intelligence (BI) applications are still a rarity in tourism destinations.
The main purpose of this session is to present research on business intelligence in tourism from various perspectives and disciplinary approaches as well as to critically discuss its implications and challenges. The session will also emphasize how methods of business intelligence can support in the development of new tourism products and services.
The session organizers welcome abstracts, but not exclusively, on the following topics: conceptual and architectural aspects of business intelligence applications in tourism, BI-based management information and decision support systems, big data, BI-based analysis on customer based brand equity for destinations, knowledge creation from user generated content, sentiment analysis in tourism, and network analysis.
Maria Lexhagen, Matthias Fuchs and Tatiana Chekalina
Department of Tourism Studies and Geography
Etour, Mid University, Sweden
University of Applied Sciences
831 25 Östersund
Telephone +46 10 142 83 39