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

Ching Chien Liang, Ya Hsueh Lee, Chun Heng Ho, Kuo Hsiang Chen

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


This study adopted a Kansei engineering methodology to examine users' Kansei values toward automotive interior designs by conducting experiments under two models: sensory experience and perceived value evaluation models. In the sensory experience model, 60 participants were recruited to experience using 27 vehicle samples and to assign scores to eight Kansei keywords. Hayashi's quantification theory type 1 was used to calculate the weight of 12 interior space items and 40 interior design categories. In the perceived value evaluation model, 60 participants completed a questionnaire on the influence levels of the Kansei keywords on their Kansei values from the perspectives of four consumer perceived value dimensions. The questionnaire scores were then evaluated using factor analysis to extract nine primary factors affecting participants' perceptions. This study determined that the interesting and dynamic perceptions corresponded to five design items under the Excitement Quality factors, vigorous and recreational perceptions corresponded to four items under the Relaxation and Comfort factor, and technological and luxurious perceptions corresponded to six items under the Luxury and Splendor factor and the Esteemed Image factor. These findings can help designers and researchers in the relevant sectors create automotive interior designs that fulfill the expectations of users.

Original languageEnglish
Pages (from-to)401-420
Number of pages20
JournalArtificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM
Issue number3
Publication statusPublished - 2020 Aug 1

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering
  • Artificial Intelligence

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