The Character and Economic Preference of City Network of China: A Study Based on the Chinese Global Fortune 500 Enterprises

Table 7

Regression results.

Variable	Model
	1	2	3	4	5	6	7	8	9	10	11	12	13	14
K (capita)	0.334	0.332	0.328	0.325	0.602	0.531	0.558	0.549
H (human capita)	−0.163	−0.186	−0.19	−0.207
I (institute)	−0.146	−0.124	−0.127	−0.138		−0.13	−0.103	−0.128				−0.62	−0.382	−0.546
T (facilities)	0.033	0.029	0.031	0.029	−0.105	−0.09	−0.098	−0.082	0.803			0.482		−0.374
P (FDI)	−0.035	−0.033	−0.033	−0.034								−0.406		0.473
C (quality of urban life)	0.309	0.305	0.302	0.28								−0.314		−0.278
N (technology innovation)	0.067	0.064	0.067	0.065	0.449	0.348	0.351	0.337
S (industrial structure)	−0.045	−0.04	−0.04	−0.037
Self-contained centrality				0.051		0.135				0.853
Urban agglomeration centrality							0.103
Provincial centrality		0.039											0.157
National centrality I								0.121
National centrality II			0.037								0.864			0.215
_cons	0.274	−0.035	−0.41	0.2	9.291	9.105	9.074	8.880	15.15 3	16.718	13.759	16.062	15.529	14.659
N	311	311	311	311	74	74	74	74	10	10	10	48	48	48
Adjustment R^2	0.976	0.977	0.977	0.977	0.907	0.92	0.916	0.92	0.6	0.69	0.72	0.52	0.55	0.5
Finspection	4.882	3.964	4.478	3.963	7.067	6.099	4.851	7.474	14.530	21.350	23.623	6.805	4.128	11.021
D-W statistic	1.852	1.801	1.798	1.806	1.904	2.01	1.895	1.877	2.18	3.42	3.26	1.64	1.665	2
VIF maximum	8.59	8.61	8.641	9.14	2.788	3.52	3.624	3.661	1	1	1	1.42	1.442	1.2
Regression sum of squares	8331	8338.9	8338.4	8344	18.08	18.4	18.291	18.36	2.38	2.68	2.75	10.3	11	9
The sum of squared residuals	201.9	193.56	194.05	188.7	1.764	1.43	1.548	1.478	1.31	1	0.93	8.13	7.405	9.4

, , and indicate , , and , respectively.