Improving Parameter Estimates and Model Prediction by Aggregate Customization in Choice Experiments
- 1 September 2001
- journal article
- Published by Oxford University Press (OUP) in Journal of Consumer Research
- Vol. 28 (2), 273-283
- https://doi.org/10.1086/322902
Abstract
We propose aggregate customization as an approach to improve individual estimates using a hierarchical Bayes choice model. Our approach involves the use of prior estimates to build a common design customized for the average respondent. We conduct two simulation studies to investigate conditions that are most conducive to aggregate customization. The simulations are validated by a field study showing that aggregate customization results in better estimates of individual parameters and more accurate predictions of individuals' choices. The proposed approach is easy to use, and a simulation study can assess the expected benefit from aggregate customization prior to its implementation.Keywords
This publication has 14 references indexed in Scilit:
- The Value of Purchase History Data in Target MarketingMarketing Science, 1996
- The Importance of Utility Balance in Efficient Choice DesignsJournal of Marketing Research, 1996
- Hierarchical Bayes Conjoint Analysis: Recovery of Partworth Heterogeneity from Reduced Experimental DesignsMarketing Science, 1996
- Incorporating Prior Knowledge into the Analysis of Conjoint StudiesJournal of Marketing Research, 1995
- Efficient Experimental Design with Marketing Research ApplicationsJournal of Marketing Research, 1994
- Experimental analysis of choiceMarketing Letters, 1994
- An Empirical Comparison of Ratings-Based and Choice-Based Conjoint ModelsJournal of Marketing Research, 1992
- Sampling-Based Approaches to Calculating Marginal DensitiesJournal of the American Statistical Association, 1990
- Design and Analysis of Simulated Consumer Choice or Allocation Experiments: An Approach Based on Aggregate DataJournal of Marketing Research, 1983
- IntroductionPublished by Springer Science and Business Media LLC ,1980