Fachbereich: Betriebswirtschaftslehre
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Classification in Marketing Science
This paper explores the role of clustering and classification methods in
marketing beyond the prominent application of market segmentation (cf. Data analysis and decision support, Springer, Berlin, 157?176) Our study is based on a sample
of more than 1,900 articles chosen from international peer-reviewed marketing
journals. We apply a growing bisecting k-means for text classification to investigate the relation between the use of classification methods and the implications for
scholars and practitioners revealed in the articles under consideration. Moreover, we
evaluate the dependency between the use of classification techniques and the quality
ratings of the papers.

This study highlights the application gaps of classification and clustering with
respect to different areas of marketing science and, therefore, pinpoints domains
of marketing science lacking a strong empirical foundation. Additionally, we draw
implications for academic curricula.
Autor
Prof. Dr. Ralf Wagner
S. Scholz
 
ArtikelFachbereichFachrichtung
2009BetriebswirtschaftslehreMarketing/Absatz
 
Schlagwörter
Data Mining, stochastic Process, probability Theory, Classification Method, Knowledge Discovery