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A modification of technology acceptance model for investigating driver-vehicle interaction systems usage
Yichen Dong1, Makoto Itoh2,3
1Degree Program of Risk and Resilience Engineering, Graduate School of System and Information Engineering, University of Tsukuba, Tsukuba, Ibaraki, Japan.
Abstract:
This descriptive study investigated respondents' acceptance of driver-vehicle interaction systems by modifying the technology acceptance model using user experience concepts. A questionnaire survey was conducted, which including 15 variables and a Likert scale (1-5) range from 'strongly agree' to 'strongly disagree' was adopted for all variables. The questionnaire examined six constructs proposed in the modified technology acceptance model: perceived usefulness, perceived enjoyment, satisfaction, attitude, interactive media, and user interface. 495 samples aged from 21 to 82 years old (48.7 ± 12.5 years) including 279 males and 216 females were collected for data analysis. Confirmatory factor analysis demonstrated the reliability and validity of the model using several indices. Correlations between constructs were proven using path analysis (p < 0.05). Then, the influences of drivers' gender (male = 1 and female = 2) and age on the constructs were analyzed using linear regression analysis. Male drivers had higher perceived usefulness (Beta = 0.235, p < 0.01) and more positive attitudes (Beta = 0.087, p < 0.01) than female drivers. However, their perceived enjoyment of the system was lower than that of females (Beta = -0.135, p < 0.01). Older age led drivers to prefer a negative attitude toward driver-vehicle interaction systems (Beta = 0.072, p < 0.01) and dislike utilizing the user interface (Beta = 0.139, p < 0.01). Finally, four implications based on the analysis were proposed to guide the design of driver-vehicle interaction systems. This study clarified the feasibility of the modified technology acceptance model for investigating Japanese driver's opinions on driver-vehicle interaction systems and provided insights for designing vehicle human-machine interfaces to improve driver acceptance.
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