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A Multiple Method Approach for Discrimination and Classification in Marketing Research

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Book cover Classification, Automation, and New Media
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Abstract

This proposal suggests the complementary use of multiple methods in marketing research. In particular, the results obtained from the CHi-square Automatic Interaction Detector (CHAID) are both combined and integrated with several techniques of discrimination and classification. The approach is demonstrated by an empirical example from the automotive industry.

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References

  • Anders, U. (1997): Statistische neuronale Netze, Vahlen, München.

    Google Scholar 

  • BOCK, H.-H. (1974): Automatische Klassifikation, Vandenhoeck & Ruprecht, Göttingen.

    MATH  Google Scholar 

  • Chan, P. K.; Stolfo, S. J.; Wolpert, D. (1999): Guest editors’ introduction to special issue on integrating multiple learned models, Machine Learning, 36, 5–7.

    Article  Google Scholar 

  • Decker, R.; Temme, T. (2001): CHAID als Instrument der Werbemittelgestaltung und Zielgruppenbestimmung im Marketing, to appear in: Wilde, K.; U. Küsters; H. Hippner; M. Meyer (Hrsg.): Handbuch Data Mining im Marketing, Vieweg, Braunschweig.

    Google Scholar 

  • Green, P. A. (1978): An AID/Logit procedure for analyzing large multiway contingency tables, Journal of Marketing Research, 15, 132–136.

    Article  Google Scholar 

  • Hand, D. J. (1997): Construction and assessment of classification rules, Wiley, Chichester.

    MATH  Google Scholar 

  • Hosmer, D. W.; Lemeshow, S. (1989): Applied logistic regression, Wiley, New York.

    Google Scholar 

  • Huberty, C. J. (1994): Applied Discriminant Analysis, Wiley, New York.

    MATH  Google Scholar 

  • Kass, G. V. (1980): An exploratory technique for investigating large quantities of categorical Data. Applied Statistics, 29, 119–127.

    Article  Google Scholar 

  • Kuhnert, P. M.; Do, K.-A.; Mcclure, R. (2000): Combining non-parametric models with logistic regression: an application to motor vehicle injury data, Computational Statistics & Data Analysis, 34, 371–386.

    Article  MATH  Google Scholar 

  • Kuncheva, L. I. (2000): Fuzzy classifier design, Physica, Heidelberg.

    Book  MATH  Google Scholar 

  • Malhotra, K. K.; Sharma, S.; Nair, S. S. (1999): Decision making using multiple models, European Journal of Operational Research, 114, 1–14.

    Article  MATH  Google Scholar 

  • Merz, C. J. (1999): Using correspondence analysis to combine classifiers, Machine Learning, 36, 33–58.

    Article  Google Scholar 

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© 2002 Springer-Verlag Berlin Heidelberg

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Temme, T. (2002). A Multiple Method Approach for Discrimination and Classification in Marketing Research. In: Gaul, W., Ritter, G. (eds) Classification, Automation, and New Media. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55991-4_42

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  • DOI: https://doi.org/10.1007/978-3-642-55991-4_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43233-3

  • Online ISBN: 978-3-642-55991-4

  • eBook Packages: Springer Book Archive

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