A Model for the Analysis of Asymmetric Data in Marketing Research

Over the last decade, numerous methods for the multidimensional scaling (MDS) of perceptions and preferences have been applied by researchers in marketing. However, one notable gap in MDS methodology has been the lack of suitable models for analyzing inherently asymmetric data relationships. Recently, Harshman (1978, 1982a) has proposed a new family of models-called DEDICOM (DEcomposition into DIrectional COMponents)-for analyzing data matrices that are intrinsically asymmetric. In this article, the single-domain DEDICOM model is described and applied to two illustrative cases in marketing research. The examples demonstrate that DEDICOM solutions will sometimes make more substantive sense and provide significantly better fits to asymmetric data than solutions obtained by factor analysis or MDS. DEDICOM also provides a novel type of information-a description of asymmetric relations among dimensions or clusters. Such information will often have useful marketing implications.