Application of Discrete Choice Methods in Consumer Preference Analysis

  • Andrzej Bąk
  • Aneta Rybicka
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)


Stated consumer preferences refer to hypothetical market behaviour of consumers. In this case the analytical methods are based on data collected a priori by means of surveys to register intentions stated by consumers at the moment of survey taking. The methods used for stated preference analysis include, for instance, discrete choice methods. The general concept of discrete choice methods results from random utility theory. The consumer preference analysis by means of discrete choice methods is based on probability regression models. In this paper a conditional logit model is used to analyse consumer preferences measured against a nominal scale. An example discussed is the result of analysing the preferences of light beer consumers on the basis of a sample of 235 respondents.


Discrete Choice Consumer Preference Full Factorial Design Conjoint Analysis Choice Probability 
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  1. GREEN, P.E. and SRINIVASAN, V. (1990): Conjoint Analysis in Marketing: New Developments with Implications for Research and Practice. Journal of Marketing, October, 54, 3–19.Google Scholar
  2. HAAIJER, R. and WEDEL, M. (2000): Conjoint Choice Experiments: General Characteristics and Alternative Model Specifications. In: A. Gustafsson, A. Herrmann and F. Huber (Eds.): Conjoint Measurement: Methods and Applications. Springer, Berlin, 319–360.Google Scholar
  3. KUHFELD, W.F. (2001): Multinomial Logit, Discrete Choice Modeling. URL:, SAS Institute.Google Scholar
  4. LOUVIERE, J.J. and WOODWORTH, G. (1983): Design and Analysis of Simulated Consumer Choice or Allocation Experiments: An Approach Based on Aggregate Data. Journal of Marketing Research, November, 20, 350–367.Google Scholar
  5. MCFADDEN, D. (1974): Conditional Logit Analysis of Qualitative Choice Behavior. In: P. Zarembka (Ed.): Frontiers in Econometrics. Academic Press, New York-San Francisco-London, 105–142.Google Scholar
  6. ZWERINA, K. (1997): Discrete Choice Experiments in Marketing. Heidelberg-New York, Physica-Verlag.Google Scholar

Copyright information

© Springer-Verlag Berlin · Heidelberg 2005

Authors and Affiliations

  • Andrzej Bąk
    • 1
  • Aneta Rybicka
    • 1
  1. 1.Wroclaw University of EconomicsWroclawPoland

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