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Please use this identifier to cite or link to this item: http://hdl.handle.net/10119/18814

Title: Avatar Design Focusing on Kawaii Motions
Authors: Kawakita, Teru
Nishimura, Takuichi
Keywords: Kansei (affective) engineering
Motions of avatar
Impression evaluation
Kawaii engineering
Issue Date: 2023-12
Publisher: AHFE Open Access
Magazine name: AHFE International
Volume: 114
Start page: 158
End page: 165
DOI: 10.54941/ahfe1004232
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.
Rights: Copyright (c) 2023 Authors. Teru Kawakita and Takuichi Nishimura. AHFE International, Vol. 114, 2023, 158-165. This is an Open Access article distributed under the terms of Creative Commons Licence CC-BY [http://creativecommons.org/licenses/by/4.0/]. Original publication is available on AHFE Open Access via https://doi.org/10.54941/ahfe1004232.
URI: http://hdl.handle.net/10119/18814
Material Type: publisher
Appears in Collections:a11-1. 会議発表論文 (Conference Papers)

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