Handling individual differences in preference mapping models

In this work we discuss an extension in preference mapping of the method proposed in Endrizzi et al. (2011) for accommodating both population averages and individual differences in the same model. The method, based on average estimates and residuals, is a combination of ANOVA, PCA and PLS-DA, which are well-known techniques that can be run in almost all statistical software packages. Main attention will be given to the relation between the double centered residual matrix which highlights differences between consumers in their relative position as compared to the average consumer values and the standard centering in preference mapping. This approach has been found particularly useful for highlighting differences in preference pattern among the consumers. Furthermore, the interpretation and the segmentation, that is here taking place based on differences in acceptance pattern, are graphically oriented. In addition, some possible alternatives to the generally used validation method in PCA are suggested. The approach is then illustrated using the data-set from a consumer study of berry fruit juices (Endrizzi et al.,2009), showing that when individual differences are analysed by the present method, interesting results regarding individual differences in response pattern were detected. Endrizzi, I., Menichelli, E., Johansen, S. B., Olsen, N. V., & Næs, T. (2011). Handling of individual differences in rating-based conjoint analysis. Food Quality and Preference, 22, 241-254. Endrizzi I., Pirretti G., Caló D.G., Gasperi F. (2009). A consumer study of fresh juices containing berry fruits. Journal of the Science of Food and Agriculture, 89, 1227-1235.