TY - CHAP
T1 - Model of Kawaii Cosmetic Bottle Evaluations by Thai and Japanese
AU - Laohakangvalvit, Tipporn
AU - Achalakul, Tiranee
AU - Ohkura, Michiko
N1 - Funding Information:
Part of this work was supported by Grant-in-Aid Scientific Research Number 26280104. We thank the students of Shibaura Institute of Technology and King Mongkut’s University of Technology Thonburi for their participation.
Publisher Copyright:
© 2019, Springer Nature Singapore Pte Ltd.
PY - 2019
Y1 - 2019
N2 - Affective values are critical factors for manufacturing in Japan. Kawaii, an affirmative adjective that denotes such positive meanings as cute or lovable, has become even more critical as an affective value and plays a leading role in the worldwide success of many products, such as Hello Kitty and Pokemon. Based on this success, we believe that kawaii will be a key factor in future product design. In our previous research, we proposed models of kawaii feelings for spoon designs and extracted the attributes of such designs and constructed models using the Support Vector Machine (SVM) algorithm. In this research, we used the Deep Convolutional Neural Network (CNN) algorithm because it can perform classification using images as input and studied the kawaiiness of cosmetic bottles. Then, we evaluated the candidates of effective attributes with our model to increase the kawaiiness of cosmetic bottles. Finally, we clarified the relationship among kawaii feelings, attributes, and eye movement indexes obtained from our previous research, and the prediction results of our constructed model. Our results clarified the effective attributes for increasing kawaiiness and the effectiveness of our constructed model to evaluate the kawaiiness of cosmetic bottles.
AB - Affective values are critical factors for manufacturing in Japan. Kawaii, an affirmative adjective that denotes such positive meanings as cute or lovable, has become even more critical as an affective value and plays a leading role in the worldwide success of many products, such as Hello Kitty and Pokemon. Based on this success, we believe that kawaii will be a key factor in future product design. In our previous research, we proposed models of kawaii feelings for spoon designs and extracted the attributes of such designs and constructed models using the Support Vector Machine (SVM) algorithm. In this research, we used the Deep Convolutional Neural Network (CNN) algorithm because it can perform classification using images as input and studied the kawaiiness of cosmetic bottles. Then, we evaluated the candidates of effective attributes with our model to increase the kawaiiness of cosmetic bottles. Finally, we clarified the relationship among kawaii feelings, attributes, and eye movement indexes obtained from our previous research, and the prediction results of our constructed model. Our results clarified the effective attributes for increasing kawaiiness and the effectiveness of our constructed model to evaluate the kawaiiness of cosmetic bottles.
KW - Affective value
KW - Cosmetic bottles
KW - Deep convolutional neural network (CNN)
KW - Eye tracking
KW - Kawaii
KW - Product attribute
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U2 - 10.1007/978-981-13-7964-2_12
DO - 10.1007/978-981-13-7964-2_12
M3 - Chapter
AN - SCOPUS:85069498664
T3 - Springer Series on Cultural Computing
SP - 195
EP - 223
BT - Springer Series on Cultural Computing
PB - Springer
ER -