## 3 Data Collection  
For simplicity, each behavior measure is represented by a different variable code, such as X, Y, and Z, for easy categorization in the following sections. A total of 398 respondents from different states in Malaysia, such as Pulau Pinang, Johor, Kedah, Kelantan, Melaka, Negeri Sembilan, Pahang, Perak, Selangor, Sarawak, Terengganu, and Wilayah Persekutuan, participated in this survey between February and April 2019. All participants were informed about the purpose of the survey before asking for their permission and willingness to participate in the study. The samples were segregated into two different surveys, amounting to 194 samples collected in the initial survey and 204 samples in the second survey. The self-reporting method was chosen, as it is convenient for the respondents to answer with such a variety of risky behaviors [13].  
The data collected were first analyzed by creating a simple direct percentage chart to give a simple insight into the results by showing the motorcyclists' answers based on percentage. In this study, the self-reported risk perception, positive affect, and risky behavior were considered as the latent variables.  
The reliability test was conducted by determining the Cronbach's Alpha value prior to any other analysis in the study. To obtain the significance of each item's factor loading, the results were then analyzed using PCA with the construction of causal modeling showing a simplified version of the complex relationship among the variables of the data. Lastly, a model was created via SEM to present the relationship between the latent variables in a straightforward manner.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**No.**} & \multirow{2}{*}{**Behavior Measures**} & \multicolumn{3}{c}{**Variable Code**} \\ \cline{3-5}  & & **Risky Behavior** & **Risk Perception** & **Positive Affect** \\ \hline
1 & Frequently changing lane to overtake the vehicle in front. & X1 & Y1 & Z1 \\
2 & Speeding up and suddenly braking. & X2 & Y2 & Z2 \\
3 & Exceeding speed limit even when feeling unsafe. & X3 & Y3 & Z3 \\
4 & Riding fast on the curve. & X4 & Y4 & Z4 \\
5 & Continue riding although feeling sleepy. & X5 & Y5 & Z5 \\
6 & Taking alcohol before riding. & X6 & Y6 & Z6 \\
7 & Run a red light. & X7 & Y7 & Z7 \\
8 & Racing with other vehicles. & X8 & Y8 & Z8 \\
9 & Riding during peak hour. & X9 & Y9 & Z9 \\
10 & Fail to keep a proper distance with other vehicles. & X10 & Y10 & Z10 \\
11 & Overtaking/turning without using signal lights. & X11 & Y11 & Z11 \\
12 & Riding without wearing crash helmet. & X12 & Y12 & Z12 \\
13 & Crossing a stop-junction without fully stopping. & X13 & Y13 & Z13 \\
14 & Using mobile phone while riding. & X14 & Y14 & Z14 \\
15 & Not switching on the headlights during daytime. & X15 & Y15 & Z15 \\
16 & Riding on the motorcycle prohibited lane (fast lane). & X16 & Y16 & Z16 \\
17 & Riding or performing a turn that is not according to & X17 & Y17 & Z17 \\
18 & Not yielding to busses that are signaling to change lane. & X18 & Y18 & Y18 \\
19 & Not yielding to other vehicles as required by the & X19 & Y19 & Y19 \\  & right-of-way rules. & & X20 & Y20 & Z20 \\
20 & Riding on the pedestrian walkway. & X21 & Y21 & Z21 \\
21 & Riding on the opposite/wrong side of the road. & X21 & Y21 & Z21 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Behavior measures and variable codes.  
Overall, three major analyses, namely, Reliability Test, PCA and SEM, were conducted in order to understand the relationship among the variables. The reliability test was conducted using Cronbach's Alpha at first to test the reliability of the study. PCA was then used to determine the significance of the observed variables. Subsequently, SEM was constructed to determine the relationship among the variables.