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

Table 15

Model summary for the moderation effect^d.

Model		square	Adjusted square	Std. error of the estimate	Change statistics					Durbin-Watson
					square change	change	df1	df2	Sig. change
1	0.949^a	0.901	0.897	42.48186	0.901	235.664	1	26	0.000
2	0.959^b	0.921	0.914	38.73184	0.020	6.278	1	25	0.019
3	0.973^c	0.946	0.934	33.92368	0.026	3.530	3	22	0.032	1.783

^aPredictors: (constant), X63; ^bpredictors: (constant), X63, X69; ^cpredictors: (constant), X63, X69, Y13, X69 × Y13, X63 × Y13, and the Sig. of interaction term X69 × Y13 in the regression model is 0.025, less than 0.05; ^ddependent variable: Y02; X63: searching subject term “Mobile Technology & E-Commerce” in the WoS (Core Collection). X69: searching subject term “Quantum Computing” in the WoS (Core Collection). Y13: founded number of data companies in the U.S. classified as research/consulting. Y02: retail e-commerce sales for the U.S.