Product form design of multiple user clusters based on Kansei engineering

To meet the emotional needs of users in specific market segments and facilitate large-scale personalized product design, this study integrates Kansei engineering with online product reviews, proposing a product form design method for multiple user clusters. Taking the example of a baby crib. Firstly, based on user online reviews, analyzing users' Kansei cognition and utilizing the term frequency-inverse document frequency index (IF-IDF) and semantic similarity calculation method to obtain Kansei words that describe users' Kansei images. Next, the representative product form is deconstructed to extract the elements of the product form design, an orthogonal design is then employed to establish typical product form samples. Subsequently, the Quantitative Theory I model is used to explore the mapping relationship between Kansei images and product form design elements, identifying key design elements for product form design targeting distinct user clusters. Finally, these key design elements are optimized to design baby cribs that cater to the emotional needs of different user clusters. The results demonstrate that this method helps designers comprehend the intrinsic relationship between users' emotional need in segmented markets and form design elements, thereby facilitating a more accurate and efficient emotional design for different user clusters.