INTERPRETING MULTIDIMENSIONAL DATA WITH COGNITIVE DIFFERENTIATION ANALYSIS

The interpretation of multidimensional data in consumer research has t raditionally required property fitting to determine the structure unde rlying the data. As an alternative, Cognitive Differentiation Analysis (CDA) regresses a matrix of pairwise product judgments on vectors of product-attribute ratings. The estimated multiple regression equation indicates the degree of differentiation in the pairwise data that is a ccounted for by each attribute. In this article CDA is applied to the analysis of simulated multidimensional data and to actual data from a benefit segmentation study. The implications of improved interpretabil ity of multidimensional data for understanding the competitive environ ment are discussed. (C) 1995 John Wiley and Sons, Inc.