Kansei evaluation based on prioritized multi-attribute fuzzy target-oriented decision analysis

This paper deals with Kansei evaluation focusing on consumers’ psychological needs and personal taste. To do so, a preparatory study is conducted beforehand to obtain Kansei data of the products to be evaluated, in which products are assessed according to Kansei attributes by means of the semantic differential method and linguistic variables. These Kansei data are then used to generate Kansei profiles for evaluated products by means of the voting statistics. As consumers’ preferences on Kansei attributes of products vary from person to person and target-oriented decision analysis provides a good description of individual preference, the targetoriented decision analysis has been used and extended to quantify how well a product meets consumers’ preferences. Due to the vagueness and uncertainty of consumers’ preferences, three types of fuzzy targets are defined to represent the consumers’ preferences. Considering the priority order of Kansei attributes specified by consumers, a so-called prioritized scoring aggregation operator is utilized to aggregate the partial degrees of satisfaction for the evaluated products. As the aesthetic aspect plays a crucial role in human choice of traditional crafts, an application to evaluate Kanazawa gold leaf, a traditional craft in Ishikawa, Japan, has also been provided to illustrate how the proposed model works in practice.