Mass Rapid Transit Ridership Forecast Based on Direct Ridership Models: A Case Study in Wuhan, China

Table 7

Direct ridership model (DRM) estimating daily ridership at the station level in Wuhan, China.

Independent variables	B	Beta
Intercept	−1215.182	—
Population	0.086	0.014
Employment	0.154	0.098
Com_Area	0.002	0.043
Offi_Area	0.023	0.192
Land_use_mix	16941.145	0.177
Restaurant_Num	6.950	0.039
College_Num	280.784	0.062
Hospital_Num	1408.537	0.181
Shopping_Num	1.477	0.018
Financial_Num	47.943	0.071
Parking_Num	43.409	0.026
Recreational_Num	10.473	0.032
Hotel_Num	21.267	0.029
Dis_to_centers	−0.071	−0.022
Bus_line_Num	−37.498	−0.039
Dummy_line_transfer	14960.126	0.272
Dummy_CBD	1396.449	0.059
J_Accessibility	0.151	0.039
P_Accessibility	0.092	0.028
Model statistics
F-statistic	126.988 (sig = 0.000)
Std. Error	4004.668
R^2	0.885
Adjusted R^2	0.878

B denotes the final coefficient in the regression function. Beta denotes the standardized coefficient in the regression function.