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Fuzzy Clustering Analysis in Geomarketing Research

Author

Listed:
  • George Grekousis

    (Department of Environmental Resources and Engineering, College of Environmental Science and Forestry, State University of New York, Syracuse, NY 13210, USA)

  • Thomas Hatzichristos

    (Department of Geography and Regional Planning, National Technical University of Athens, I. Polytechniou 9, 15786 Zografou, Greece)

Abstract

In this study we use geographic information systems (GIS) and computational intelligence for geomarketing analysis. GIS technology offers a powerful set of tools for the input, management, and output of data, whereas computational intelligence is used for the analysis and the clustering of data by the use of unsupervised fuzzy clustering and the Gustafson–Kessel algorithm. The advantage of fuzzy geomarketing segmentation is that a customer is not assigned exclusively to one segment only, but rather with a membership value to each cluster. The proposed methodology is applied to the metropolitan area of Athens, Greece. A dataset describes 130 demographic, lifestyle, and economy variables, and the results are analysed and discussed.

Suggested Citation

  • George Grekousis & Thomas Hatzichristos, 2013. "Fuzzy Clustering Analysis in Geomarketing Research," Environment and Planning B, , vol. 40(1), pages 95-116, February.
  • Handle: RePEc:sae:envirb:v:40:y:2013:i:1:p:95-116
    DOI: 10.1068/b37137
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    References listed on IDEAS

    as
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    4. Thomas Maloutas & Nikos Karadimitriou, 2001. "Vertical Social Differentiation in Athens: Alternative or Complement to Community Segregation?," International Journal of Urban and Regional Research, Wiley Blackwell, vol. 25(4), pages 699-716, December.
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