The Influence of Big Data Analytics on E-Commerce: Case Study of the U.S. and China

Table 17

Coefficients for Y08^a.

Model		Unstandardized coefficients		Standardized coefficients		Sig.	Correlation			Collinearity statistics
			Std. error	Beta			Zero-order	Partial	Part	Tolerance	VIF
1	(Constant)	196.791	9.301		21.159	0.000
	X04	-0.220	0.023	-0.879	-9.383	0.000	-0.879	-0.879	-0.879	1.000	1.000
2	(Constant)	199.906	8.734		22.887	0.000
	X04	-0.317	0.048	-1.268	-6.631	0.000	-0.879	-0.798	-0.576	0.206	4.844
	X68	4.175	1.828	0.437	2.284	0.031	-0.693	0.416	0.198	0.206	4.844

^aDependent variable: Y08, where model 1 is 0.772 and model 2 is 0.811; low VIF values indicate low collinearity; the standardized residuals are approximately normally distributed. X04: searching subject term “E-Commerce” in CNKI (periodical); X68: searching subject term “Artificial Intelligence & Big Data & E-Commerce” in CNKI (periodical); Y08: growth rate of retail e-commerce for China.