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Studying the level-effect in conjoint analysis: An application of efficient experimental designs for hyper-parameter estimation

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Abstract

Research in marketing, and business in general, involves understanding when effect-sizes are expected to be large and when they are expected to be small. An example is the understanding of the level-effect in marketing, where the effect of product attributes on utility is positively related to the number of levels present among choice alternatives. Knowing when consumers are sensitive to the competing levels of attributes is an important aspect of merchandising, selling and promotion. In this paper, we propose a model and a method for studying the level-effect in conjoint analysis. The model combines perceptual theories in psychology to arrive at a non-linear specification of hyper-parameters in a hierarchical model. The method applies an experimental design criterion for efficient estimation of hyper-parameters. The proposed model and method are validated using a national sample of respondents.

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Acknowledgements

We would like to thank the two anonymous referees and the editor Peter Rossi for helpful comments which led to a much improved paper.

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Correspondence to Greg M. Allenby.

Appendices

Appendix 1: Survey designs and corresponding model matrices

Table 7 Full-factorial design for stimuli construction in part 1 of the study and corresponding model matrix under dummy coding
Table 8 Four versions of designs for stimuli construction in part 2 of the study
Table 9 Corresponding model matrix (X 2, dummy-coded) in part 2 of the study
Table 10 Three versions of designs for stimuli construction in part 3 of the study
Table 11 Corresponding model matrix (X 3, dummy-coded) in part 3 of the study
Table 12 Covariate matrices for the three parts of the study

Appendix 2: Prediction validation results

Table 13 Predictions of mean profile ratings in holdout study version 1
Table 14 Predictions of mean profile ratings in holdout study version 2
Table 15 Predictions of mean profile ratings in holdout study version 3

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Liu, Q., Dean, A., Bakken, D. et al. Studying the level-effect in conjoint analysis: An application of efficient experimental designs for hyper-parameter estimation. Quant Mark Econ 7, 69–93 (2009). https://doi.org/10.1007/s11129-008-9045-9

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  • DOI: https://doi.org/10.1007/s11129-008-9045-9

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