Kansei assessment of the constituent elements and the overall interrelations in car steering wheel design

摘要

In most studies on Kansei, the product form analysis model is based on the external features or elements of the product components. However, such an approach cannot completely convert consumer emotional perceptions into design elements. Therefore, this study combined the ergonomic technology used in Kansei engineering with the unique cognitive ability of humans to identify patterns and establish an emotional perception model that can integrate the overall interrelations of the constituent elements. Steering wheel design was used as the object of examination. Three types of adjectives were applied to describe the constituent elements. The first type was esthetic factors and involve external esthetics. The second type comprised two pairs of adjectives, sturdy/delicate and lightweight/heavy, called operational strength factors because they relate to form and strength. The third type comprised simplistic/changeful and artificial/spontaneous, called modernity factors because they pertain to the modern sense of beauty of the parts. Multiple linear regression analysis was used to construct a Kansei engineering model and compare the performance of individual elements and the product as a whole. The results show that the R-2 values in the overall model were greater than those in the element-oriented model, indicating that the integrated model outperformed the element-oriented model in variance explanation. The differences between the numerical values of the adjective pairs classic/fashionable (esthetic factors), sturdy/delicate (operational strength factors), and simplistic/changeful and artificial/spontaneous (modernity factors) were significant, demonstrating that the overall model is useful in predicting how consumers make assessments according to emotional perceptions. The R-2 increase of the modernity factors was the most obvious, indicating that the overall model assesses modernity more accurately. Comparing results and verifying test samples demonstrated that the overall model is more useful in predicting consumer appraisals that are based on emotional perception.