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Behavioral Market Segmentation of Binary Guest Survey Data with Bagged Clustering

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Artificial Neural Networks — ICANN 2001 (ICANN 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2130))

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Abstract

Binary survey data from the Austrian National Guest Survey conducted in the summer season of 1997 were used to identify behavioral market segments on the basis of vacation activity information. Bagged clustering overcomes a number of difficulties typically encountered when partitioning large binary data sets: The partitions have greater structural stability over repetitions of the algorithm and the question of the “correct” number of clusters is less important because of the hierarchical step of the cluster analysis. Finally, the bootstrap part of the algorithm provides means for assessing and visualizing segment stability for each input variable.

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Author information

Authors and Affiliations

  1. Department of Tourism and Leisure Studies, Vienna University of Economics and Business Administration, A-1090, Wien, Austria

    Sara Dolničar

  2. Department of Statistics and Probability Theory, Vienna University of Technology, A-1040, Wien, Austria

    Friedrich Leisch

Authors
  1. Sara Dolničar
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  2. Friedrich Leisch
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Editor information

Editors and Affiliations

  1. Dept. of Mecidal Cybernetics and Artificial Intelligence, University of Vienna, Freyung 6/2, 1010, Vienna, Austria

    Georg Dorffner

  2. Institute for Computer Aided Automation Pattern Recognition and Image Processing Group, Technical University of Vienna, Favoritenstr. 9/1832, 1040, Vienna, Austria

    Horst Bischof

  3. Institut für Statistik, Wirtschaftsuniversität Wien, Augasse 2-6, 1090, Wien, Austria

    Kurt Hornik

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© 2001 Springer-Verlag Berlin Heidelberg

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Dolničar, S., Leisch, F. (2001). Behavioral Market Segmentation of Binary Guest Survey Data with Bagged Clustering. In: Dorffner, G., Bischof, H., Hornik, K. (eds) Artificial Neural Networks — ICANN 2001. ICANN 2001. Lecture Notes in Computer Science, vol 2130. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44668-0_16

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  • DOI: https://doi.org/10.1007/3-540-44668-0_16

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42486-4

  • Online ISBN: 978-3-540-44668-2

  • eBook Packages: Springer Book Archive

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