Multivariate Mapping of Hedonics

Multivariate analyses are commonly used to study differences among items in a multidimensional space and to relate these findings to hedonic assessments of the same items. But there are numerous methods in use and the purpose of this paper is to review these methods from a process standpoint. Specifically, this paper considers the process assumptions behind several of the popular methods for multivariate mapping of hedonic data and argues that experimenters should consider how their data arise so that they can correctly interpret their findings. Among the methods considered in this paper are models based on the hedonic continuum, internal and external preference mapping, and deterministic and probabilistic unfolding of preference and liking. Practical Applications Multivariate mapping of hedonic data has led to improved consumer products and a better understanding of consumer liking and choice. In this paper, practitioners will find guidance in their choice of methods through a consideration of the processes that generate their data. Without a process-based perspective, practitioners will not be able to optimally interpret results from the wide variety of available multivariate mapping methods. Multivariate Mapping of Hedonics