## 5 Results and Discussion
### Assessment of Outer Model  
The assessment of the PLS-SEM model was conducted by evaluating the outer model by means of reflective and formative model/construct to assess the measurement model's reliability and validity. In this study, RB, RP, and PA were considered reflective constructs, while PC was categorized as a formative construct. In the latent construct of risky behavior, five out of fifteen behaviors remained in the model. The risky behaviors included (X1), frequently changing lanes to overtake the vehicle in front, (X4), riding fast on a bend, (X7), running a red light, (X8), racing with other vehicles, and (X10), failing to keep an appropriate distance from other vehicles. Table 5 summarizes the findings after eradicating the indicators with low factor loadings (\(\leq\)0.4) while meeting the recommended criteria of AVE (\(\geq\)0.5) and composite reliability (CR) (\(\geq\)0.6). The results show that riding fast on a bend had the highest factor loading (0.764), followed by racing with other vehicles, which had a factor loading of 0.745. The risky behavior with the lowest factor loading was found to be running a red light at 0.657. The findings also show that the AVE for the latent construct of risky behavior was 0.501 while the composite reliability was 0.834. Subsequently, the latent construct of risk perception had 14 indicators meeting the criteria for recommended factor loadings. All the indicators were included except for (Y9), riding during peak hours. The factor loadings ranged from 0.51 to 0.858, while the AVE and composite reliability of the construct were 0.609 and 0.956, respectively. Y3 (exceeding the speed limit even when feeling unsafe) had the highest factor loading, while Y15 (not switching on the headlights during the daytime) had the lowest loading factor. Figure 5: Mean comparison between risky behavior (RB), risk perception (RP), and positive affect (PA). However, eight out of ten indicators were retained in the SEM model for the positive affect latent construct. The retained indicators were Z1, Z2, Z3, Z4, Z8, Z10, Z11, and Z13. The factor loadings for the positive affect indicators ranged between 0.621 and 0.858. The findings reveal that Z13 had the lowest factor loading, while Z2 had the highest factor loading. In addition to the factor loadings, the results show that the AVE and composite reliability were 0.509 and 0.892, respectively. After assessing the reflective indicator loading, internal consistency reliability, and convergent validity, the final step was to examine the discriminant validity of the reflective model/construct using the heterotrait-monotrait (HTMT) ratio of the correlations. The findings showed that the HTMT value from the reflective construct ranged between 0.144 and 0.843, which is within the recommended limit of less than 0.85, as tabulated in Table 6. The highest HTMT value was found between constructs of risky behavior and positive affect. The lowest HTMT value was found between constructs of risk perception and risky behavior. This finding implies that the data sets included in the constructs were unrelated. In PLS-SEM, the collinearity of the formative indicators is determined by their variance inflation factor (VIF). The findings revealed that both indicators, age and gender, had a VIF value of 1.019, while indicators motorcycle type and trip distance had VIF values of 1.046 and 1.043, respectively. The results show no collinearity issues as the VIF values were below 5, as tabulated in Table 7. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Constructs** & **Positive Affect** & **Risky Behavior** \\ \hline Risky behavior & 0.843 & \\ Risk perception & 0.22 & 0.144 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Heterotrait-monotrait (HTMT) values.