Hostname: page-component-cd9895bd7-gxg78 Total loading time: 0 Render date: 2024-12-26T09:02:07.922Z Has data issue: false hasContentIssue false
  • English
  • Français

Investigating vehicle interior designs using models that evaluate user sensory experience and perceived value – CORRIGENDUM

Published online by Cambridge University Press:  18 December 2020

Ching-Chien Liang ,
Ya-Hsueh Lee ,
Chun-Heng Ho  and
Kuo-Hsiang Chen
Ching-Chien Liang
Affiliation:
Department of Industrial Design, National Cheng Kung University, No.1, University Rd., Tainan 701, Taiwan (ROC) Department of Popular Music Industry, Southern Taiwan University of Science and Technology, No. 1, Nan-Tai Street, Yongkang District, Tainan, Taiwan (ROC)
Ya-Hsueh Lee
Affiliation:
Department of Visual Communication Design, Southern Taiwan University of Science and Technology, No. 1, Nan-Tai Street, Yongkang District, Tainan, Taiwan (ROC)
Chun-Heng Ho
Affiliation:
Department of Industrial Design, National Cheng Kung University, No.1, University Rd., Tainan 701, Taiwan (ROC)
Kuo-Hsiang Chen
Affiliation:
School of Art and Design, Fuzhou University of International Studies and Trade, No. 28, Yuhuan Road, Shouzhan New District, Changle, Fuzhou City, Fujian Province, PR CHINA
Rights & Permissions [Opens in a new window]

Abstract

An abstract is not available for this content. As you have access to this content, full HTML content is provided on this page. A PDF of this content is also available in through the ‘Save PDF’ action button.
Type
Corrigendum
Information
AI EDAM , Volume 34 , Issue 4 , November 2020 , pp. 531
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

In the above-mentioned article by Reference Liang, Lee, Ho and ChenLiang et al. (2020), affiliation #4 was incorrect upon original publication. The affiliation has since been corrected in the published article.

References

Liang, C, Lee, Y, Ho, C, and Chen, K (2020) Investigating vehicle interior designs using models that evaluate user sensory experience and perceived value. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 34, 401–420. doi:10.1017/S0890060419000246CrossRefGoogle Scholar