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

Table 4

Coefficients of SAM and OLS.

Independent variables		SAM		OLS
		Coefficient	t-statistic	Coefficient	t-statistic
NA	Constant	0.000	0.781	0.000	3.823
Residential area variables	O_pop	0.103	1.688	0.147	−0.541
	D_pop	0.100	2.668	0.145	−0.568
POIs variables	O_education	−0.243	1.696	−0.277	0.584
	D_education	−0.211	2.147	−0.243	26.971
	O_enterprise	0.182	1.782	0.334	3.010
	D_enterprise	0.165	2.265	0.315	−5.423
	O_hotel	0.131	2.025	0.104	−9.575
	D_hotel	0.124	2.439	0.092	−7.252
	O_entertainment	0.010	1.467	−0.263	5.473
	D_entertainment	0.012	1.247	−0.262	1.849
	O_spots	0.005	2.336	0.032	4.972
	D_spots	0.007	2.041	0.036	21.145
Bus station variables	O_bus	0.450	1.856	0.898	−6.016
	D_bus	0.447	1.443	0.900	3.183
Subway station variables	O_subway	−0.156	0.877	0.040	−0.948
	D_subway	−0.158	1.563	0.038	−13.232
Spatial variables	Distance	−0.221	0.913	−1.312	2.259
		0.007	1.798	NA	NA
		0.007	2.013	NA	NA
		−0.005	−1.923	NA	NA
−2 log-likelihood:		−14,933.8		−13,559.3
AIC		−14,891.8		−13,523.3
BIC		−14,755.3		−13,406.4
AICc		−14,891.6		−13,523.2

0.05 level; 0.1 level; NA: not applicable.