抄録
In the field of marketing, companies often carry out a questionnaire
to consumers for grasping their impressions of products. Analyzing the evaluation
data obtained from consumers enables us to grasp the tendency of the market
and to find problems and/or to make hypotheses that are useful for the development
of products. Semantic Differential (SD) method is one of the most useful
methods for quantifying human-impressions to the objects. The purpose of this
study is to develop a method for visualization of individual features in data. This
paper proposes the Clustering method based on Orthogonal Procrustes Analysis
(COPA). The proposed method can cluster subjects among whom the distributed
structures of the SD evaluation data are similar. The analysis by this method leads
to discovery of majority/minority groups and/or groups which have unique features.
In addition, it enables us to analyze the similarity/difference of objects and
impression words among clusters and/or subjects by comparing the cluster centers
and/or transformation matrices. This paper applies the proposed method to an
actual SD evaluation data. It shows that this method can investigate the similar relationships
among the objects in each group and compare the similarity/difference
of impression words used for the evaluation of objects among subjects in the same
cluster.
