Define and describe hybrid conjoint analysis

What will be an ideal response?

Hybrid conjoint analysis is an attempt to simplify the burdensome data-collection task required in traditional conjoint analysis. Each respondent evaluates a large number of profiles, yet usually only simple part-worths, without any interaction effects, are estimated. In the simple part-worths or main effects model, the value of a combination is simply the sum of the separate main effects (simple part-worths). In actual practice, two attributes may interact, in the sense that the respondent may value the combination more than the average contribution of the separate parts.

In the hybrid approach, the respondents evaluate a limited number generally no more than nine, of conjoint stimuli, such as full profiles. These profiles are drawn from a large master design, and different respondents evaluate different sets of profiles, so that over a group of respondents, all the profiles of interest are evaluated. In addition, respondents directly evaluate the relative importance of each attribute and desirability of the levels of each attribute. By combining the direct evaluations with those derived from the evaluations of the conjoint stimuli, it is possible to estimate a model at the aggregate level and still retain some individual differences.