Product-concept testing is a popular activity in marketing research. Often the number of new product/service concepts under study far exceeds the time available for any single respondent. Respondents therefore may receive only a subset of the concepts comprising the total design. Researchers are...

Ambiguity surrounds any importance measure in cases in which predictor variables are correlated. However, a new measure is proposed that has attractive properties, such as providing individual contributions that are both non-negative and sum to R2. The new measure is compared with four other...

While conjoint analysis has been applied to a wide variety of problems in preference analysis, it has heretofore not been used to analyze similarities data. A method for dealing with this problem is described and illustrated on a small set of empirical data

Increasingly, researchers are becoming interested in the relationship of part-worth functions, obtained from conjoint analysis, to other aspects of the respondents (e.g., their demographics, preferences for current brands, etc.). This paper describes a straight-forward procedure for determining...

Choice-constrained conjoint analysis (CCCA) is a new method for metric conjoint analysis studies. It computes part-worth utility functions that account for “revealed preference” — those products a respondent actually selects in an independent choice situation. CCCA uses an iterative...

In lieu of Abstract, here is the first paragraph: Jackson provides a clear statement of a basic (and noncontroversial) limitation of all "importance" measures in multiple regression-namely, there is no unambiguous measure of importance in the case of correlated predictor variables. Darlington...

A simple allocation model is developed in which response is assumed to be linear in the logs of the control variables. It is then shown that the optimal allocation of a fixed total resource is proportional to the partial regression weights when the linear-in-logs model is fitted by least...

Volume 1. MDS and positioning -- Volume 2. Clustering and Segmentation -- Volume 3. Conjoint Analysis: the Pioneering Years -- Volume 4. Conjoint Analysis: Advanced Methods -- Volume 5. Conjoint Analysis: Applications -- Volume 6. Marketing Research