Ratings based versus choice-based latent class conjoint models - An empirical comparison

Traditional ratings- or rankings-based conjoint analysis has been very popular in commercial practice. Recently, the choice-based conjoint approach has become an attractive alternative for measuring preference structures. However, little is known about the extent to which both approaches produce similar results or about how they compare in terms of predictive accuracy. This paper presents a conceptual and empirical comparison of ratings-based and choice-based conjoint approaches. The authors add to previous empirical investigations by comparing both approaches with respect to differences in relative attribute importances and predictive accuracy while controlling for task order. In particular, the authors compare segment-level (latent class) models.

The results show substantial differences in the segment-level relative attribute importances. These results are consistent with previous research and the prominence hypothesis. At the segment and aggregate level the choice-based approach clearly outperforms the ratings-based approach.