AHFE Open AccessAvatar design focusing on kawaii motions
Abstract
Avatars and agents are one of the important products in the metaverse. Kawaii value could potentially enhance the sales of avatars. This study aims to identify the kawaii motions of avatar and to examine the relationship between kawaii motions and purchase intention via Kansei (affective) engineering methodologies. We made the anime-like female avatar with six kawaii motions. The semantic differential (SD) method was used to measure their motions. As a result of principal component analysis (PCA), two PCs were extracted. PC1 has “enjoyable”, “kawaii”, and “charming.” PC2 has “elegant”, “beautiful”, and “stylish.” We visualized the relationship between the two PCs and each motion. Correlation analysis further indicated that kawaii motions were positively correlated with purchase intention (r = .67, p < .001). This study showed that the impression of avatar changes with kawaii motions. Designing the motions of avatar is likely to help them sell more. Avatar creators should design the kawaii motions to draw out the appeal of avatars.
Keywords: Kansei (affective) engineering, Motions of avatar, Impression evaluation, Kawaii engineering, Metaverse
DOI: 10.54941/ahfe1004232
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