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Business intelligence for cross-process knowledge extraction at tourism destinations
University of Applied Sciences Ravensburg-Weingarten.
Mid Sweden University, Faculty of Human Sciences, Department of Tourism Studies and Geography. (Etour)ORCID iD: 0000-0003-3964-2716
University of Applied Sciences Ravensburg-Weingarten.
Mid Sweden University, Faculty of Human Sciences, Department of Tourism Studies and Geography. (Etour)ORCID iD: 0000-0002-6610-9303
2015 (English)In: Information Technology & Tourism, ISSN 1098-3058, E-ISSN 1943-4294, Vol. 15, no 2, p. 101-130Article in journal (Refereed) Published
Place, publisher, year, edition, pages
2015. Vol. 15, no 2, p. 101-130
Keywords [en]
business intelligence; tourism
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Other Social Sciences not elsewhere specified
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URN: urn:nbn:se:miun:diva-25799DOI: 10.1007/s40558-015-0023-2ISI: 000428928800001Scopus ID: 2-s2.0-84938302219Local ID: ETOUROAI: oai:DiVA.org:miun-25799DiVA, id: diva2:849218
Available from: 2015-08-27 Created: 2015-08-27 Last updated: 2025-09-25Bibliographically approved

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Fuchs, MatthiasLexhagen, Maria

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CiteExportLink to record
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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
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf