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A knowledge discovery method based on genetic-fuzzy systems for obtaining consumer behaviour patterns. An empirical application to a Web-based trust model

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  • Jorge Casillas
  • Francisco J. Martinez-Lopez

Abstract

This paper shows part of a larger interdisciplinary research focused on developing artificial intelligence-based analytical tools to aid the marketing managers' decisions on consumer markets. In particular, here it is presented and tested a knowledge discovery methodology based on genetic-fuzzy systems – a Soft Computing (SC) method that jointly makes use of fuzzy logic and genetic algorithms – to be applied in marketing modelling. Its characteristics are very coherent with the requirements that marketing managers currently demand to market analytical methods. Specifically, it has been paid attention to illustrate, in detail, how this proposed (Knowledge Discovery in Databases) KDD method performs with an empirical application to a Web-based trust consumer model.

Suggested Citation

  • Jorge Casillas & Francisco J. Martinez-Lopez, 2009. "A knowledge discovery method based on genetic-fuzzy systems for obtaining consumer behaviour patterns. An empirical application to a Web-based trust model," International Journal of Management and Decision Making, Inderscience Enterprises Ltd, vol. 10(5/6), pages 402-428.
    • Handle: RePEc:ids:ijmdma:v:10:y:2009:i:5/6:p:402-428
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    Cited by:

    1. Hadavandi, Esmaeil & Ghanbari, Arash & Shahanaghi, Kamran & Abbasian-Naghneh, Salman, 2011. "Tourist arrival forecasting by evolutionary fuzzy systems," Tourism Management, Elsevier, vol. 32(5), pages 1196-1203.

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