Kansei Decision Tree: Proposal of a Modeling Method for Decision-making Processes

Abstract

This study proposes a method of modeling a decision-making process using the decision tree. A simulation experiment was conducted to collect cases of decision making. Then, a modeling method using the decision tree was applied to the experimental results. The obtained decision tree enabled the authors to visually identify the differences in Kansei depending on the person. Finally, the authors compared and examined the differences in the number of nodes in the decision tree according to whether there was a particular attachment to the products. The results confirmed that the differences in Kansei were reflected in the differences in the structure of the decision tree. Using this Kansei decision tree method, it was possible to extract and quantitatively evaluate the factors that influence its structure. This was attained by expressing the Kansei decision-making process using the decision tree and comparing its structure.