Fuzzy Clustering Analysis in Geomarketing Research

George Grekousis and Thomas Hatzichristos
Additional contact information
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

Environment and Planning B, 2013, vol. 40, issue 1, 95-116

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.

Keywords: geomarketing analysis; fuzzy clustering; Gustafson–Kessel algorithm; geographical information systems (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1068/b37137 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:envirb:v:40:y:2013:i:1:p:95-116

DOI: 10.1068/b37137

Access Statistics for this article

More articles in Environment and Planning B
Bibliographic data for series maintained by SAGE Publications ().