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Ranking Models in Conjoint Analysis

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  • Lam, K.Y.
  • Koning, A.J.
  • Franses, Ph.H.B.F.

Abstract

In this paper we consider the estimation of probabilistic ranking models in the context of conjoint experiments. By using approximate rather than exact ranking probabilities, we do not need to compute high-dimensional integrals. We extend the approximation technique proposed by \\citet{Henery1981} in the Thurstone-Mosteller-Daniels model for any Thurstone order statistics model and we show that our approach allows for a unified approach. Moreover, our approach also allows for the analysis of any partial ranking. Partial rankings are essential in practical conjoint analysis to collect data efficiently to relieve respondents' task burden.

Suggested Citation

  • Lam, K.Y. & Koning, A.J. & Franses, Ph.H.B.F., 2010. "Ranking Models in Conjoint Analysis," Econometric Institute Research Papers EI 2010-51, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:20937
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    References listed on IDEAS

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    1. Albert Maydeu-Olivares, 1999. "Thurstonian modeling of ranking data via mean and covariance structure analysis," Psychometrika, Springer;The Psychometric Society, vol. 64(3), pages 325-340, September.
    2. Ben-Akiva, Moshe & Morikawa, Takayuki & Shiroishi, Fumiaki, 1992. "Analysis of the reliability of preference ranking data," Journal of Business Research, Elsevier, vol. 24(2), pages 149-164, March.
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    Cited by:

    1. Kornprom Satraphand & Supeecha Panichpathom, 2018. "Willingness to Pay for Senior Wellness Center," ERES eres2018_21, European Real Estate Society (ERES).

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    Keywords

    conjoint experiments; partial rankings; thurstone order statistics model;
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