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Conjoint Measurement pp 225–251Cite as

A Multi-trait Multi-Method Validity Test of Partworth Estimates

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Abstract

Conjoint analysis has already been widely accepted by marketing researchers as a popular instrument for the measurement of consumer preferences. Typical applications of conjoint analysis include new product design based on the relationship between product features and predicted choice behavior, benefit segmentation based on attribute preferences, etc. The popularity of conjoint analysis among marketing researchers hinges on the belief that it produces valid measurements of consumer preferences for the features of a product or service, and that it provides accurate predictions of choice behavior.

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References

  • Akaah, I. P. (1991), Predictive Performance of Self-Explicated, Traditional Conjoint and Hybrid Conjoint Models Under Alternative Data Collection Modes, Journal of the Academy of Marketing Science, 19, 309–314.

    Article  Google Scholar 

  • Bagozzi, R. P. and Yi, Y. (1991), Multitrait-Multimethod Matrices in Consumer Research, Journal of Consumer Research, 17, 426–439.

    Article  Google Scholar 

  • Browne, M. W. (1992), MUTMUM User’s Guide, Version of April, 1992, The Ohio State University, Department of Psychology, Columbus, Ohio.

    Google Scholar 

  • Browne, M. W. (1984), The Decomposition of Multitrait-Multimethod Matrices, British Journal of Mathematical and Statistical Psychology, 37, 1–21.

    Article  Google Scholar 

  • Campbell, D. T. and Fiske, D. F. (1959), Convergent and Discriminant Validation by the Multitrait-Multimethod Matrix, Psychological Bulletin, 56, 81–105.

    Article  Google Scholar 

  • Campbell, D. T. and O’Connell, E. J. (1967), Method Factors MultitraitMultimethod Matrices: Multiplicative Rather than Additive?, Multivariate Behavioral Research, 2, 409–426.

    Article  Google Scholar 

  • Darmon, R. Y. and Rouzies, D, (1991), Internal Validity Assessment of Conjoint Estimated Attribute Importance Weights, Journal of the Academy of Marketing Science, 19, 315–322.

    Article  Google Scholar 

  • Darmon, R. Y. and Rouzies, D. (1994), Reliability and Internal Validity of Conjoint Estimated Utility Functions Under Error-Free Versus Error-Full Conditions, International Journal of Research in Marketing, 11, 465–476.

    Article  Google Scholar 

  • DeSarbo, W. S., Wedel, M., Vriens, M. and Ramaswamy, V. (1992), Latent Class Metric Conjoint Analysis, Marketing Letters, 3, 273–289.

    Article  Google Scholar 

  • Green, P. E. and Helsen, K. (1989), Cross-Validation Assessment of Alternatives to Individual-Level Conjoint Analysis: A Case Study, Journal of Marketing Research, 26, 346–350.

    Article  Google Scholar 

  • Green, P. E., Krieger, A. M. and Agarwal, M. K. (1993), A Cross Test of Four Modelsfor Quantifying Multiattribute Preferences, Marketing Letters, 4, 369–380.

    Article  Google Scholar 

  • Green P. E., Krieger, A. and Schaffer, C. M. (1993), An Empirical Test of Optimal Respondent Weighting in Conjoint Analysis, Journal of the Academy of Marketing Science, 21, 345–351.

    Article  Google Scholar 

  • Hagerty, M. R. (1985), Improving the Predictive Power of Conjoint Analysis: The Use of Factor Analysis and Cluster Analysis, Journal of Marketing Research, 22, 168–184.

    Article  Google Scholar 

  • Hagerty, M. R. (1993), Can Segmentation Improve Predictive Accuracy in Conjoint Analysis? Journal of the Academy of Marketing Science, 21, 353–355.

    Article  Google Scholar 

  • Jain, A. K., Acito, F., Malhotra, N. K. and Mahajan, V. (1979), A Comparison of the Internal Validity of Alternative Parameter Estimation Methods in Decompositional Multiattribute Preference Models, Journal of Marketing Research, 16, 313–322.

    Article  Google Scholar 

  • Kalleberg, A. L. and Kluegel, J. R. (1975), Analysis of the MultitraitMultimethod Matrix: Some Limitations and an Alternative, Journal of Applied Psychology, 60, 1–9.

    Article  Google Scholar 

  • Kamakura, W. A. (1988), A Least Squares Procedure for Benefit Segmentation with Conjoint Experiments, Journal of Marketing Research, 25, 157–167.

    Article  Google Scholar 

  • Kamakura, W. A., Wedel, M. and Agrawal, J. (1994), Concomitant Variable Latent Class Models for Conjoint Analysis, International Journal of Research in Marketing, 11, 451–464.

    Article  Google Scholar 

  • Krishnamurthi, L. (1989), Conjoint Models of Family Decision Making, International Journal of Research in Marketing, 5, 185–198.

    Article  Google Scholar 

  • Kumar, A. and Dillon, W. R. (1992), An Integrative Look at the use of Additive and Multiplicative Covariance Structure Models in the Analysis of MTMM Data, Journal of Marketing Research, 29, 51–64.

    Article  Google Scholar 

  • Lastovicka, J. L., Murry, J. P., and Joachimsthaler, E. A. (1990), Evaluating the Measurement Validity of Lifestyle Typologies with Qualitative Measures and Multiplicative Factoring, Journal of Marketing Research, 27, 11–23.

    Article  Google Scholar 

  • Lee, S. Y. (1980), Estimation of Covariance Structure Models with Parameters Subject toFunctional Constrains, Psychometrika, 45, 309–324.

    Article  Google Scholar 

  • Leigh, T. W., MacKay, D. B. and Summers, J. 0. (1984), Reliability and Validity of Conjoint Analysis and Self-Explicated Weights: A Comparison, Journal of Marketing Research, 21, 456–462.

    Article  Google Scholar 

  • Marsh, H. W. and Hocevar, D. (1983), Confirmatory Factor Analysis of Multimethod-Multitrait Matrices, Journal of Educational Measurement, 20, 231–248.

    Article  Google Scholar 

  • Morwitz, V. G., Johnson, E. and Schmittlein, D. (1993), Does Measuring Intend Change Behavior? Journal of Consumer Behavior, 20, 1–16.

    Google Scholar 

  • Ogawa, K. (1987), An Approach to Simultaneous Estimation and Seg- mentation in Conjoint Analysis, Marketing Science, 6, 66–81.

    Article  Google Scholar 

  • Srinivasan, V. and Park, C. (1997), Surprising Robustness of the Self-Explicated Approach to Consumer Preference Structure Measurement, Journal of Marketing Research, 34, 286–291.

    Article  Google Scholar 

  • Wedel, M. and Steenkamp, J. B. (1989), Fuzzy Clusterwise Regression Approach to Benefit Segmentation, International Journal of Research in Marketing, 6, 241–258.

    Article  Google Scholar 

  • Vriens, M., Wedel, M. and Wilms, T. (1996), Metric Conjoint Segmentation Methods: A Monte Carlo Comparison, Journal of Marketing Research, 33, 73–85.

    Google Scholar 

  • Wothke, W. and Browne, M. W. (1990), The Direct Product Model for the MTMM Matrix Parameterized as a Second Order Factor Analysis Model, Psychometrika, 55, 255–262.

    Article  Google Scholar 

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Authors
  1. Wagner Kamakura
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  2. Muammer Ozer
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© 2000 Springer-Verlag Berlin Heidelberg

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Kamakura, W., Ozer, M. (2000). A Multi-trait Multi-Method Validity Test of Partworth Estimates. In: Conjoint Measurement. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-06395-8_10

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  • DOI: https://doi.org/10.1007/978-3-662-06395-8_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-06397-2

  • Online ISBN: 978-3-662-06395-8

  • eBook Packages: Springer Book Archive

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