# Modeling User Acceptance of In-Vehicle Applications for Safer Road Environment
## 5 Data Analysis and Results
### Construct Items  
In this study, a total of seven constructs, i.e., the SC, SI, T, PU, EU, AT and BI, were involved, and the responses were collected based on the survey items as in Table 6. The [PERSON]'s Alpha tests were performed to assess the reliability of the multiple-question Likert scale used to measure the latent variable structure of psychological measures as single items derived from the respondents. The [PERSON]'s Alpha value presents how reliable a set of test items are to validate and authenticate the response for the TAM constructs, i.e., 0.91-1.00 (excellent), 0.81-0.90 (good), 0.71-0.80 (good and acceptable), 0.61-0.70 (acceptable) and 0.01-0.60 (not acceptable). We found that the scale system is highly reliable for all constructs where the average is 0.7872. All variables have a value of [PERSON]'s Alpha higher than 0.7 except for the target variable, i.e., BI, which is 0.6294 (Table 8). Nevertheless, the items for the BI are still acceptable. Increasing the number of items under this construct may increase the internal consistency.  
The Kaiser-Meyer-Olkin (KMO) test value of 0.791 indicates that the sample is adequate and has sufficient information to estimate factor solutions. In addition, [PERSON]'s  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Personal Characteristics (PCs)** & **Response Category (\(n\))** \\ \hline Gender & Male (113); Female (195) \\ \hline Age & 18–25 years old (152), 26–34 years old (38), 35–54 years old (82), 55–64 years old (25), \\  & above 64 years old (11) \\ \hline Driver’s License & Yes (264), No (44) \\ \hline Accident Experience & Yes (155), No (153) \\ \hline Locality & Rural (53), Suburban (110), \\  & Urban (145) \\ \hline Knowledge about in-vehicle applications & No (79), Yes (229) \\ \hline Self-reported capabilities & Limited (141), Not Limited (167) \\ \hline Driving distance per week & less 100 km (195), 100–200 km (62), 201–300 km (23), 301–400 km (3), more than 400 km (25) \\ \hline \hline \end{tabular}
\end{table}
Table 7: Details of respondents (\(n=308\)).  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Variables** & **T** & **SC** & **SI** & **PU** & **EU** & **AT** & **BI** \\ \hline Cronbach’s \(\alpha\) & 0.7100 & 0.8161 & 0.9733 & 0.8586 & 0.7522 & 0.7712 & 0.6294 \\ \hline \hline \end{tabular}
\end{table}
Table 8: Reliability and validity analysis on variables.  
test \(p\)-value is less than 0.001 which is significant to reject the null hypothesis. Hence, there exists some level of correlation among the items to estimate the factor loadings. A Confirmatory Factor Analysis was performed using JASP 0.16.1. The factor loadings of each item are shown in Figure 3.  
In addition, we calculated the Average Variance Extracted (AVE) and determined the convergent validity as well as the discriminant validity. We conclude that there is a convergent validity when the AVE is 0.5 and above. Moreover, the discriminant validity exists when the square root of AVE is more that the correlation value. The results are shown in Table 9. Evidence of both the convergent and discriminant validity demonstrates the constructs' validity.