Products classification in emotional design using a basic-emotion based semantic differential method

Abstract

Consumer’s emotional requirements, or the so-called Kansei needs, have become one of the most important concerns in product design nowadays. In this regard, the semantic differential (SD) method has been widely used in emotional product design and Kansei engineering to address the relationships between emotions and products. However, the conventional SD method assumes that the survey participants’ understandings on Kansei adjectives or tags are consistent, which might not be true for all design cases. As a result, classification of products using Kansei tags may not reflect a consumer’s genuine opinions. Accordingly, a basic-emotion based semantic differential method is proposed in this work. The proposed method improves the conventional SD method by taking variances of Kansei tags into consideration for better products classification in emotional design. It incorporates basic-emotion systems to identify Kansei variance and mapping functions in determining transformed values on Kansei-tag dimensions. Therefore, the adjusted Kansei mean values, which help classify products using Kansei tags, are obtained. The proposed approach is presented and illustrated using a case study of perfume bottle design. The results reveal that the proposed method is promising for handling product classifications in emotional design. Relevance to industryThis study presents a generic method to establish the relationships between consumers’ Kansei needs and products for new product development. The knowledge gained from the method is beneficial in assisting the mapping of product domain into Kansei domain when applying Kansei engineering. Especially it helps to suggest a quantified range of each Kansei tag for product designers so that the links between products and Kansei requirements can be more clarified to them. It appears that the proposed method can be utilized to better classify products under Kansei tags as well as to facilitate decision-making in practical industrial design cases.