Summary
In this paper we develop a method to improve the performance of stochastic models of consumer behavior and adress two problems encountered in practical market research: a way to deal with low data-quality and small sample-sizes and a way to improve strategic marketing decision making. The approach allows the integration of verbally formulated market knowledge and stochastic models of consumer behavior. Formally we construct a random level set using the estimated parameters of the market model and combine it with the Fuzzy Set derived from the experts’ knowledge using the Theory of Natural Language Computations. An entropy-based measure of the difference between sources of information is given. Besides presenting the method we also discuss two empirical examples concerning buying behavior in the Austrian coffee market.
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© 1988 Springer-Verlag Berlin · Heidelberg
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Geyer-Schulz, A., Taudes, A., Wagner, U. (1988). Exploring the Possibilities of an Improvement of Stochastic Market Models by Rule-Based Systems. In: Gaul, W., Schader, M. (eds) Data, Expert Knowledge and Decisions. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-73489-2_6
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DOI: https://doi.org/10.1007/978-3-642-73489-2_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-73491-5
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