The drive to satisfy customers in narrowly defined market segments has led firms to offer wider arrays of products and services. Delivering products and services with the appropriate mix of features for these highly fragmented market segments requires understanding the value that customers place...

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...