Modeling the Commuting Travel Activities within Historic Districts in Chinese Cities

Table 6

Direct and indirect effects between exogenous and endogenous variables of SEM for outside commuters.

Variable	Effect	Age	Occupation	Gender	Preschool children	Household annual income	Automobile	Household size	Number of trip chains	Number of trips
Number of trips	Overall effect	—	0.124	—	—	—	—	—	—	—
	Direct effect	—	0.124	—	—	—	—	—	—	—
	Indirect effect	—	0	—	—	—	—	—	—	—
Commute trip number	Overall effect	—	0.055	—	—	—	0.091	—	—	—
	Direct effect	—	0.039	—	—	—	0.086	—	—	—
	Indirect effect	—	0.016	—	—	—	0.005	—	—	—
Commute time	Overall effect	—	—	—	—	−4.809	—	—	11.691^*	44.507^*
	Direct effect	—	—	—	—	−4.554	—	—	11.691^*	44.507^*
	Indirect effect	—	—	—	—	−0.255	—	—	0	0
Mode choice	Overall effect	—	0.121	−0.504^*	−0.429	0.215	0.878^*	—	0.55	—
	Direct effect	—	0.121	−0.504^*	−0.429	0.215	0.878^*	—	0.55	—
	Indirect effect	—	0	0	0	0	0	—	0	—
Trip chain	Overall effect	—	0.087	0.155	—	—	—	—	—	—
	Direct effect	—	0.087	0.155	—	—	—	—	—	—
	Indirect effect	—	0	0	—	—	—	—	—	—
Number of trip chains	Overall effect	—	—	—	—	—	—	—	—	—
	Direct effect	—	—	—	—	—	—	—	—	—
	Indirect effect	—	—	—	—	—	—	—	—	—
Duration of the commuting	Overall effect	—	—	—	—	—	—	—	—	—
	Direct effect	—	—	—	—	—	—	—	—	—
	Indirect effect	—	—	—	—	—	—	—	—	—

Notes: ; , df = 26, /df = 1.227; GFI = 0.982; AGFI = 0.927; RMSEA = 0.03.
“—” indicates no significant influence; “*” indicates ; other values indicate .