## Appendix A  
The results of models 1-4 compared with those of OLS models were shown in the following Tables A1-A4.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**Global(OLS)**} & \multicolumn{5}{c}{**Local(GWR)**} \\ \hline
**Variables** & **Estimate** & **Standard Error** & **t(Est/SE)** & **Min** & **Max** & **Mean** & **STD** \\ \hline
**Intercept** & 148,902.14 & 8373.14 & 17.78 & -220,846.06 & 1,259,330.97 & 230,997.13 & 231,395.86 \\ \hline
**Pop** & 29,682.08 & 9949.31 & 2.98 & -87,929.62 & 174,341.19 & 24,227.35 & 57,929.46 \\ \hline
**Betweenness** & 25,971.88 & 9096.29 & 2.86 & -75,396.67 & 122,215.16 & 30,440.91 & 53,705.86 \\ \hline
**Days open** & 36,322.47 & 8796.81 & 4.13 & -449,460.34 & 868,771.29 & 72,348.20 & 158,603.43 \\ \hline
**Shopping** & 15,242.75 & 9217.93 & 1.65 & -68,601.68 & 58,895.47 & 1474.80 & 29,877.34 \\ \hline
**Dis\_to\_center** & -10,074.73 & 9248.92 & -1.09 & -207,415.70 & 755,777.31 & 43,828.83 & 157,781.05 \\ \hline
**R-square** & 0.35 & & & 0.81 & & \\ \hline
**Adjusted R-** & 0.32 & & & 0.65 & & \\
**square** & 90,925.69 & & & 64,811.17 & & \\ \hline
**Sigma** & 9038.33 & & & 3035.27 & & \\ \hline
**Residual sum** & 925,957,952,739.49 & & & 269,172,991,697.74 & & \\
**of squares** & 6 & & & 37.83 & & \\ \hline
**Number of** & & & & & & \\
**parameters** & & & & & & \\ \hline
**GWR ANOVA Table** & & & & & & \\ \hline
**Source** & **SS** & **DF** & **MS** & **F** & _p_**-Value** \\ \hline
**Global Residuals** & 925,957,952,739.493 & 6.000 & & & & \\ \hline
**GWR Improvement** & 656,784,961,041.749 & 47.919 & 13,706,255,804.666 & & & \\ \hline
**GWR Residuals** & 269,172,991,697.743 & 64.081 & 4,200,487,280.123 & 3.263016 & 0.00000618 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Results of the model for Weekly_ridership.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**Global(OLS)**} & \multicolumn{5}{c}{**Local(GWR)**} \\ \hline
**Variables** & **Estimate** & **Standard Error** & **t(Est/SE)** & **Min** & **Max** & **Mean** & **STD** \\ \hline
**Intercept** & 21,069.11 & 1396.44 & 15.09 & -120,163.53 & 88,286.30 & 15,756.13 & 34,442.86 \\ \hline
**Pop** & 3315.04 & 1641.47 & 2.02 & -21,270.33 & 19,333.99 & 2360.82 & 7639.67 \\ \hline
**Degree** & 2650.45 & 1769.71 & 1.50 & -10,861.88 & 21,766.31 & 4363.04 & 8529.63 \\ \hline
**Betweenness** & 2015.18 & 1776.54 & 1.13 & -10,825.87 & 17,108.65 & 1367.15 & 5279.79 \\ \hline
**Days\_open** & 5339.96 & 1475.52 & 3.62 & -167,661.22 & 88,682.06 & \(-\)281.66 & 41401.46 \\ \hline
**Residence** & 1699.47 & 1726.48 & 0.98 & -15,025.38 & 17,648.50 & 3450.52 & 6192.10 \\ \hline
**Shopping** & 2358.64 & 1754.75 & 1.34 & -20,228.55 & 20,126.20 & \(-\)497.87 & 7419.68 \\ \hline
**R-square** & 0.29 & & & 0.86 & & \\ \hline
**Adjusted R-square** & 0.24 & & & 0.70 & & \\ \hline
**Sigma** & 15,165.28 & & & 9450.60 & & \\ \hline
**AICc** & 2616.89 & & & 2602.62 & & \\ \hline
**Residual sum** & & & & & & \\
**of squares** & 25,528,398,304.96 & & 5,143,828,231.09 & & & \\ \hline
**Number of** & & & & & & \\
**parameters** & & & & & & \\ \hline
**GWR ANOVA Table** & & & & & & \\ \hline
**Source** & **SS** & **DF** & **MS** & **F** & _p_**-Value** \\ \hline
**Global Residuals** & 17,730,610,368.116 & 6.000 & & & & \\ \hline
**GWR Improvement** & 11,783,480,835.168 & 40.665 & 289,772,173.512 & & & \\ \hline
**GWR Residuals** & 5,947,129,532.948 & 71.335 & 83,368,605.017 & 3.475795 & 0.00000205 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Results of the model for Weekend_ridership.