## 4 Results and Discussion
### Model 1--Intentions to Use Public Transport during COVID-19 Pandemic
The relative values of the coefficients for factor categories can help in explaining the effects of the categorical explanatory variables. The sign of a coefficient for a factor category indicates the effect of a particular factor category relative to the reference category. Age, profession, car ownership, motorbike ownership, education and the four underlying factors were found to be significant explanatory variables (i.e., \(p\)-values \(<0.05\)). The signs of the coefficients indicate that the underlying factors, \"attitudes\", \"responsibility\" and \"difficulty\" had an inverse relationship whereas, \"awareness\" had a direct relationship with the intentions to use public transport during the pandemic. It means that those with higher awareness about the disease and its transmission may use public transport more frequently during the pandemic. Whereas, those who consider it to be their responsibility to take precautionary measures may avoid the use of public transport altogether to promote self-isolation. Similarly, those experiencing difficulties while following the necessary precautions may also reduce the use of public transport during the pandemic. The value of coefficients for [marital status = single] is positive (0.081), which suggests that singles are more likely to use public transport as compared to married people during the pandemic. Similarly, the coefficients for various categories (31-40 and 41-50 years) of age indicated that those in the younger age groups are more likely to use public transport during the pandemic relative to those in the oldest age category (i.e., above 50). It could be attributed to the fact that the virus has been found to be particularly dangerous for older people and therefore, they may use public transport less frequently during the pandemic [53]. Students and government and public employees are more likely to use public transport during the pandemic relative to others which may include housewives and retired personnel. In addition, government and public employee are more likely to use public transport during the pandemic relative to students. It can be explained by the fact that educational institutions were closed in Lahore during the pandemic. Car owners and motorbike owners are less likely to use public transport relative to non-car owners and non-motorbike owners. Since the virus spreads through close contact with other people and infected surfaces causing public transport to be more risky, private cars and motorbike offer alternative travel choices with lower chances of infection. The positive coefficients for all the categories of education variable indicate that those with lower educational qualifications are more likely to use public transport during the pandemic. The descriptive analysis showed that those with lower educational qualifications have lower household income and are less likely to own a private car or a motorbike making them captive public transport user. Model 2--Intenttions to Use Public Transport during COVID-19 Pandemic While Adhering to Safety Precautions  
The items 3 to 4 of Section 2 of the questionnaire (How often would you use public transport while you have to maintain a social distance? How often would you use public transport while you have to wear a facemask? and How often would you use public transport while you have to use hand sanitizers or disinfectants?) represent the intentions to adhere to safety precautions while using public transport during COVID-19 pandemic. A single factor underlying these items was extracted using exploratory factor analysis and the corresponding regression factor scores were computed (Table 5). A multiple linear regression model was then developed by treating the underlying factor as a dependent variable. SEDs and the underlying factors namely, attitudes, awareness, responsibility,  
\begin{table}
\begin{tabular}{l l l l l l l l l} \hline \hline \multirow{2}{*}{**Model**} & \multicolumn{1}{c}{**Estimate**} & \multicolumn{1}{c}{**Std.