Research Area: Knowledge generation through methods of Business Intelligence in Tourism

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Description of this research area

In contrast to other branches, Business Intelligence (BI) applications are still a rarity in tourism destination practice and research. Thus, a major goal in this research area is to apply, test, and implement methods of BI to generate new knowledge from various types of customer- and supplier-based data sources available in destinations. For instance, by analysing tourists’ search behaviour at destination web-sites and by mining social media content, new knowledge is gained which, in turn serves as the input for intelligent customer services, like context-sensitive e-customer cards. Finally, this knowledge gained from destination processes, like customers’ web-search, booking and feedback (i.e. via social media and surveys) can be disseminated by an all-stakeholder encompassing Destination Management Information System. A current project studying tourism economic impacts strives to use a recently implemented knowledge platform and Data Warehouse model to make accessible statistical data and analysis outcomes on economic effects from tourism activities in the Swedish region of Jämtland

Keywords

Business Intelligence, data mining, big data analytics, destination management information system, data warehousing

Institution

ETOUR

Researchers

Prof. Dr. Matthias Fuchs

Dr. Maria Lexhagen

MSc. Kai Kronenberg

Research projects in this research area

Customer based innovation in tourism (CBIT)

Engineering the Knowledge Destination

Publications published by this institute characterizing this research area

Fuchs, M., Abadzhiev, A., Svensson, B, Höpken, W. & Lexhagen, M. (2013). A Knowledge Destination Framework for Tourism Sustainability – A Business Intelligence Application from Sweden, Tourism - An Interdisciplinary Journal, 61(2): 121-148.

Fuchs, M., Höpken, W. Lexhagen, M. (2015): Applying Business Intelligence for Knowledge Generation in Tourism Destinations – A Case from Sweden, In: Pechlaner H. & Smeral. E. (eds.), Tourism and Leisure - Current Issues and Perspectives of Development in Research and Business, Springer. pp. 161-174.

Fuchs, M., Höpken, W. & Lexhagen, M. (2015): Big Data Analytics for Knowledge Generation in Tourism Destinations – A Case from Sweden, Journal of Destination Marketing & Management DOI: 10.1016/j.jdmm.2014.08.002 (in print)

Höpken, W., Fuchs, M., Keil, D. & Lexhagen, M. (2011): The Knowledge Destination – A Customer Information-based Destination Management Information System, In: Law, R., Fuchs, M. & Ricci, F. (eds.), Information and Communication Technologies in Tourism 2011, Springer, New York: 417-429.

Höpken, W., Fuchs, M., Höll, G. Keil, D. & Lexhagen, M. (2013): Multi-Dimensional Data Modelling for a Tourism Destination Data Warehouse, In: Cantoni, L. & Xiang, Ph. (eds.) Information and Communication Technologies in Tourism 2013, Springer, New York: 157-169.

Höpken, W., Fuchs, M. & Lexhagen, M. (2014): The Knowledge Destination – Applying Methods of Business Intelligence to Tourism destinations. In Wang, J. (ed.) Encyclopaedia of Business Analytics and Optimization, IGI Global, 307-321.

Pitman, A., Zanker, M., Fuchs, M. & Lexhagen, M. (2010): Web Usage Mining in Tourism – A Query Term Analysis and Clustering Approach. In: Gretzel, U, Law, R. & Fuchs, M. (eds.), Information and Communication Technologies in Tourism 2010, Springer, New York: 393-403.

Schmunk, S., Höpken, W., Fuchs, M. & Lexhagen, M. (2014): Sentiment Analysis – Implementation and Evaluation of Methods for Sentiment Analysis with Rapid-Miner®, In Xiang, Ph. & Tussyadiah, I. (eds.) Information and Communication Technologies in Tourism 2014, Springer, New York: 253-265.