## 2 Study Methodology
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**No.** & **Item** & **[PERSON]** **et al. [43]** & **[PERSON]** **et al. [45]** & **[PERSON]** [25] \\ \hline \multicolumn{5}{c}{Personal characteristics} \\ \hline
1 & Age & / & / \\
2 & Gender & / & / \\
3 & Riding experience & & \\
4 & Motorcycle type & / & \\
5 & Trip length & / & \\
6 & Trip purpose & & \\ \hline \multicolumn{5}{c}{Behavior measures} \\ \hline
1 & Frequently changing lanes to overtake the vehicle in front. & / & / \\
2 & Speeding up and suddenly braking. & / & / \\
3 & Exceeding the speed limit even when feeling unsafe. & & / \\
4 & Riding fast on a bend. & & / \\
5 & Continuing riding despite feeling sleepy. & & / \\
6 & Drinking alcohol before riding. & / & / \\
7 & Running a red light. & / & / \\
8 & Racing with other vehicles. & & / \\
9 & Riding during peak hours. & & / \\
10 & Failing to keep an appropriate distance from other vehicles. & / & \\
11 & Overtaking/turning without using turn signals. & / & / \\
12 & Riding without wearing a crash helmet. & & / \\
13 & Crossing a stop-junction without fully stopping. & & / \\
14 & Using a mobile phone while riding. & & / \\
15 & Not switching on the headlights during the daytime. & / & / \\
16 & Riding on the motorcycle prohibited lane (fast lane). & / & \\
17 & Riding or performing a turn that is not according to right-of-way rules & & \\  & in order to save time. & & \\
18 & Not yielding to buses that are signaling to change lanes. & & \\
19 & Not yielding to other vehicles as required by right-of-way rules. & / & \\
20 & Riding on a pedestrian walkway. & & / \\
21 & Riding on the opposite/wrong side of the road. & / & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison of personal characteristics and behavior measures between previous studies and the current study. Figure 1: Flowchart of study methodology. In this study, each behavior measure was represented by a different variable code, such as X for risky behavior, Y for perception of the behavior, and Z for positive affect toward the behavior for easy segregation for subsequent analysis, as shown in Table 3.  
Subsequently, for the principal survey, the questionnaire survey was designed with the input of results obtained from the preliminary survey by removing the least common risky behaviors. The participants in the principal survey were asked to score each segment's questions using a 5-point Likert scale. This first segment of the survey allowed respondents to rate the questions in terms of frequency of engagement in these 21 behaviors, rating from 1 (Never) to 5 (Always). In the subsequent segment, the respondents were asked about how unsafe they believed each of these 21 behaviors to be, with 1 being not risky at all to 5 being extremely risky. Lastly, in segment 3, respondents rated how much they enjoyed or disliked these 21 behaviors, with responses ranging from 1 (extremely disliked) to 5 (liking it very much). The questionnaire survey was designed as a simple question to the participants instead of plain numbers as tabulated in the study. For risk behaviors, participants were asked how often they engage in a particular behavior. For risk perception, participants were asked if they personally believed that particular behavior to be dangerous. Lastly, for positive affect, participants were asked whether they had benefited from the mentioned risky behavior. As this study used the PLS-SEM method, the overall causal model was constructed using PLS-SEM software, as illustrated in Figure 2. The collected survey data were subsequently coded in the model to perform causal relation analysis. A hypothesis model was initially defined to investigate the relationship among the latent measures as follows: