抄録
In the field of marketing, companies often carry out a questionnaire to consumers to grasp 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 to quantify human-impressions to the objects. The purpose of this study is to develop a method based on an individuality.
This paper proposes a clustering method based on Orthogonal Procrustes Analysis (OPA). 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.
