On the Perceived Usefulness of Scaling Techniques in Market Analysis

Abstract

This study examines the perceived usefulness of alternative spatial and tree-based similarity scaling techniques in a market analysis task. These techniques are typically evaluated on their ability to fit or explain customer input data. The psychological reaction of individuals who use these techniques to analyze markets has been largely ignored. The study reveals that spatial representations are perceived as more useful than tree-based clustering techniques, even though the latter provide a better fit to customer perceptions. The results have implications for both the use and development of scaling techniques in psychology and marketing.