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Remaining within-cluster heterogeneity: a meta-analysis of the "dark side" of clustering methods

Franke, Nikolaus and Reisinger, Heribert and Hoppe, Daniel (2009) Remaining within-cluster heterogeneity: a meta-analysis of the "dark side" of clustering methods. Journal of Marketing Management, 25 (3-4). pp. 273-293. ISSN 0267-257X

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Abstract

In a meta-analysis of articles employing clustering methods, we find that little attention is paid to remaining within-cluster heterogeneity and that average values are relatively high. We suggest addressing this potentially problematic "dark side" of cluster analysis by providing two coefficients as standard information in any cluster analysis findings: a goodness-of-fit measure and a measure which relates explained variation of analysed empirical data to explained variation of simulated random data. The second coefficient is referred to as the Index of Clustering Appropriateness (ICA). Finally, we develop a classification scheme depicting acceptable levels of remaining within-cluster heterogeneity. (authors' abstract)

Item Type: Article
Additional Information: To see the final version of this paper please visit the publisher's website. Access to the published version may require a subscription.
Keywords: remaining within-cluster heterogeneity / meta-analysis / goodness-of-fit / cluster analysis
Divisions: Departments > Strategy and Innovation > Entrepreneurship und Innovation > Franke
Version of the Document: Accepted for Publication
Variance from Published Version: Minor
Depositing User: Dissertation Administrator
Date Deposited: 12 May 2011 10:07
Last Modified: 30 Dec 2014 17:06
Related URLs:
FIDES Link: https://bach.wu.ac.at/d/research/results/43289/
URI: http://epub.wu.ac.at/id/eprint/3088

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