Understanding City-Wide Ride-Sourcing Travel Flow: A Geographically Weighted Regression Approach

Table 5

Estimation results of the GWR model.

Explanatory variable		Average coefficient	Min coefficient	Max coefficient	STD coefficient
NA	Constant	0.000	0.000	0.001	0.000
Residential area variables	O_pop	0.102	−0.061	0.729	0.164
	D_pop	0.205	−0.210	0.690	0.281
POIs variables	O_education	−0.245	−1.298	0.497	0.402
	D_education	−0.106	−1.346	1.044	0.579
	O_enterprise	0.216	−0.857	1.012	0.402
	D_enterprise	0.223	−1.470	0.959	0.560
	O_hotel	0.165	−0.052	0.607	0.130
	D_hotel	0.271	−0.315	1.021	0.297
	O_entertainment	−0.013	−1.099	2.367	0.743
	D_entertainment	0.201	−1.913	1.531	0.814
	O_spots	0.012	−0.202	0.353	0.110
	D_spots	−0.107	−0.623	0.172	0.151
Bus station variables	O_bus	0.527	−0.866	2.015	0.657
	D_bus	0.276	−1.179	1.684	0.613
Subway station variables	O_subway	−0.202	−0.596	0.209	0.175
	D_subway	−0.222	−0.879	0.070	0.178
−2 log-likelihood:		−52,874.39
AIC		−52,653.16
BIC		−51,934.47
AICc		−52,648.00