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Knowledge-Based Selection and Application of Quantitative Models of Consumer Behavior

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Information Systems and Data Analysis

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Summary

Starting from the proposition of a comprehensive set of market diagnostics and a flexible data model, which is well suited for the representation of both these diagnostics and different types of panel data, we shall discuss selected aspects of consumer behavior modeling to motivate a new goal- and data-oriented approach for model selection. The simulation framework presented in this context constitutes an essential extension of traditional applications of quantitative models of consumer behavior. The relationships between panel data, models, and market diagnostics mentioned in this essay can be taken as a starting point for knowledge-based analyses and simulations of consumer buying behavior.

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Author information

Authors and Affiliations

  1. Institut für Entscheidungstheorie und Unternehmensforschung, Universität Karlsruhe, Kollegium am Schloß, D-7500, Karlsruhe, Germany

    Reinhold Decker

Authors
  1. Reinhold Decker
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Editor information

Editors and Affiliations

  1. Institut für Statistik, Rheinisch-Westfälische Technische Hochschule Aachen (RWTH), Wüllnerstr. 3, D-52056, Aachen, Germany

    Hans-Hermann Bock

  2. Forschungsstelle “Mathematische Logik” der Heidelberger Akademie der Wissenschaften Fachbereich Informatik, Universität Kaiserslautern, Erwin-Schrödinger-Str. 57, D-67653, Kaiserslautern, Germany

    Wolfgang Lenski

  3. Fachbereich Informatik, Universität Kaiserslautern, Erwin-Schrödinger-Str. 57, D-67653, Kaiserslautern, Germany

    Michael M. Richter

  4. Deutsches Forschungszentrum für Künstliche Intelligenz GmbH (DFKI), Erwin-Schrödinger-Str. 57, D-67653, Kaiserslautern, Germany

    Michael M. Richter

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© 1994 Springer-Verlag Berlin · Heidelberg

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Decker, R. (1994). Knowledge-Based Selection and Application of Quantitative Models of Consumer Behavior. In: Bock, HH., Lenski, W., Richter, M.M. (eds) Information Systems and Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-46808-7_38

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  • DOI: https://doi.org/10.1007/978-3-642-46808-7_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-58057-7

  • Online ISBN: 978-3-642-46808-7

  • eBook Packages: Springer Book Archive

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