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Big data analytics for knowledge generation in tourism destinations: A case from Sweden
Mid Sweden University, Faculty of Human Sciences, Department of Tourism Studies and Geography. (Etour)ORCID iD: 0000-0003-3964-2716
Univ Appl Sci Ravensburg Weingarten, Weingarten, Germany.
Mid Sweden University, Faculty of Human Sciences, Department of Tourism Studies and Geography. (Etour)ORCID iD: 0000-0002-6610-9303
2014 (English)In: Journal of Destination Marketing and Management, ISSN 2212-571X, Vol. 3, no 4, 198-209 p.Article in journal (Refereed) Published
Abstract [en]

This paper presents a knowledge infrastructure which has recently been implemented as a genuine novelty at the leading Swedish mountain tourism destination, Åre. By applying a Business Intelligence approach, the Destination Management Information System Åre (DMIS-Åre) drives knowledge creation and application as a precondition for organizational learning at tourism destinations. Schianetz, Kavanagh, and Lockington’s (2007) concept of the ‘Learning Tourism Destination’ and the ‘Knowledge Destination Framework’ introduced by Höpken, Fuchs, Keil, and Lexhagen (2011) build the theoretical fundament for the technical architecture of the presented Business Intelligence application.

After having introduced the development process of indicators measuring destination performance as well as customer behaviour and experience, the paper highlights how DMIS-Åre can be used by tourism managers to gain new knowledge about customer-based destination processes focused on pre- and post-travel phases, like “Web-Navigation”, “Booking” and “Feedback”. After a concluding discussion about the various components building the prototypically implemented BI-based DMIS infrastructure with data from destination stakeholders, the agenda of future research is sketched. The agenda considers, for instance, the application of real-time Business Intelligence to gain real-time knowledge on tourists’ on-site behaviour at tourism destinations.

Place, publisher, year, edition, pages
2014. Vol. 3, no 4, 198-209 p.
Keyword [en]
Big data analytics, Tourism destination, Destination management information system, Business intelligence, Data mining, Online Analytical Processing (OLAP)
National Category
Other Social Sciences not elsewhere specified
Identifiers
URN: urn:nbn:se:miun:diva-23763DOI: 10.1016/j.jdmm.2014.08.002ISI: 000349567300002Scopus ID: 2-s2.0-84922230793Local ID: ETOUROAI: oai:DiVA.org:miun-23763DiVA: diva2:771729
Funder
Knowledge Foundation, 20100260
Available from: 2014-12-15 Created: 2014-12-15 Last updated: 2016-11-21Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
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  • sv-SE
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More languages
Output format
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