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Wie robust sind Methoden zur Präferenzmessung?

Author

Listed:
  • Adriane Hartmann

    (Universität Hamburg)

  • Henrik Sattler

    (Universität Hamburg)

Abstract

Summary There is empirical evidence that self-explicated preference measurement methods are surprisingly robust in comparison to conjoint analysis. However, there has been no broad comparison of self-explicated methods with Choice-Based Conjoint analysis. The latter method gains more and more importance in marketing research practice. This empirical study shows that choice-based conjoint analysis leads to decisively better predictive validity than self-explicated measurement. Furthermore, its predictive validity is better than that of a new non-compensatory preference measurement method called RSS and the widespread Adaptive Conjoint Analysis (ACA).

Suggested Citation

  • Adriane Hartmann & Henrik Sattler, 2004. "Wie robust sind Methoden zur Präferenzmessung?," Schmalenbach Journal of Business Research, Springer, vol. 56(1), pages 3-22, February.
    • Handle: RePEc:spr:sjobre:v:56:y:2004:i:1:d:10.1007_bf03372727
    DOI: 10.1007/BF03372727
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    References listed on IDEAS

    as
    1. Green, Paul E & Srinivasan, V, 1978. "Conjoint Analysis in Consumer Research: Issues and Outlook," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 5(2), pages 103-123, Se.
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    3. Peter J. Lenk & Wayne S. DeSarbo & Paul E. Green & Martin R. Young, 1996. "Hierarchical Bayes Conjoint Analysis: Recovery of Partworth Heterogeneity from Reduced Experimental Designs," Marketing Science, INFORMS, vol. 15(2), pages 173-191.
    4. V. Srinivasan & Allan Shocker, 1973. "Linear programming techniques for multidimensional analysis of preferences," Psychometrika, Springer;The Psychometric Society, vol. 38(3), pages 337-369, September.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    C25; C89; D12; M31;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C89 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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