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Nutzenermittlung in wahlbasierter Conjoint-Analyse: Ein Vergleich von Latent-Class- und hierarchischem Bayes-Verfahren

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  • Thorsten Teichert

    (Universität Bern)

Abstract

Summary Two different concepts of disentangling noise from systematic deviations in Choice-Based Conjoint evaluations are compared: The Latent Class Technique and the Hierarchical Bayes procedure. In addition, a probabilistic interpretation of LC estimates is presented as an interims model. Conceptual differences between these models are discussed and hypotheses on resulting differences in estimates are derived. These are tested in a large-scale empirical study. The relative performance is evaluated in two distinct application areas: segment/level and individual/level estimates. The expected patterns are confirmed only partly by empirical evidence. It is shown that the structure of the underlying heterogeneity concept influences the achievable outcomes. Contrary to expectations it is shown that the segment-level estimates are highly stable across methods. While individual Hierarchical Bayes estimates are often of questionable quality, they are to be preferred against the Latent Class estimates, because they detect outliers reasonably well and provide more flexibility in the data evaluation.

Suggested Citation

  • Thorsten Teichert, 2001. "Nutzenermittlung in wahlbasierter Conjoint-Analyse: Ein Vergleich von Latent-Class- und hierarchischem Bayes-Verfahren," Schmalenbach Journal of Business Research, Springer, vol. 53(8), pages 798-822, December.
    • Handle: RePEc:spr:sjobre:v:53:y:2001:i:8:d:10.1007_bf03372669
    DOI: 10.1007/BF03372669
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    References listed on IDEAS

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    1. Neeraj Arora & Greg M. Allenby & James L. Ginter, 1998. "A Hierarchical Bayes Model of Primary and Secondary Demand," Marketing Science, INFORMS, vol. 17(1), pages 29-44.
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    3. Louviere, Jordan J., 1991. "Experimental choice analysis: Introduction and overview," Journal of Business Research, Elsevier, vol. 23(4), pages 291-297, December.
    4. 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.
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    More about this item

    Keywords

    M31; C81;

    JEL classification:

    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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