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

Table 3

Variable setting.

(a)

Searching subject term	Literature database	Variable	Searching subject term	Literature database	Variable	Searching subject term	Literature database	Variable	Searching subject term	Literature database	Variable
“E-Commerce”	ProQuest	X01	“Business Intelligence Analytics”	WoS	X11	“Apriori”	WoS	X21	“Clustering Algorithm” and “Big Data”	WoS	X31
	WoS	X02		CNKI	X12		CNKI	X22		CNKI	X32
	CNKI (all)	X03	“Big Data Model”	WoS	X13	“-means” and “Big Data”	WoS	X23	“Cloud” and “Big Data”	WoS	X33
	CNKI	X04		CNKI	X14		CNKI	X24		CNKI	X34
	CNKI (master’s & doctoral dissertation)	X05	“Big Data Algorithm”	WoS	X15	“SVM” and “Big Data”	WoS	X25	“Regression” and “Big Data”	WoS	X35
	ProQuest	X06		CNKI	X16		CNKI	X26		CNKI	X36
“E-Commerce” and then “Big data”	WoS	X07	“Hadoop”	WoS	X17	“Machine Learning” and “Big Data”	WoS	X27	“Decision Analytics” and “Big Data”	WoS	X37
	CNKI (all)	X08		CNKI	X18		CNKI	X28		CNKI	X38
	CNKI	X09	“MapReduce”	WoS	X19	“Deep Learning” and “Big Data”	WoS	X29	“Optimization” and “Big Data”	WoS	X39
	CNKI (master’s & doctoral dissertation)	X10		CNKI	X20		CNKI	X30		CNKI	X40
“Genetic Algorithm” and “Big Data”	WoS	X41	“Classifier” and “Big Data”	WoS	X49	“Online Consumer Behavior”	WoS	X57	“Cloud Computing & E-Commerce”	WoS	X65
	CNKI	X42		CNKI	X50		CNKI	X58		CNKI	X66
“Neural Networks” and “Big Data”	WoS	X43	“Social Network” and “Big Data”	WoS	X51	“Online Consumer Behavior & Big Data”	WoS	X59	“Artificial Intelligence & Big Data & E-Commerce”	WoS	X67
	CNKI	X44		CNKI	X52		CNKI	X60		CNKI	X68
“Text Analysis” and “Big Data”	WoS	X45	“Prediction Model” and “Big Data”	WoS	X53	“Internet of Things & E-Commerce”	WoS	X61	“Quantum Computing”	WoS	X69
	CNKI	X46		CNKI	X54		CNKI	X62		CNKI	X70
“Association Rules” and “Big Data”	WoS	X47	“E-commerce & Big Data Analytics”	WoS	X55	“Mobile Technology & E-Commerce”	WoS	X63
	CNKI	X48		CNKI	X56		CNKI	X64

(b)

Object	Content	Variable	Object	Content	Variable	Object	Classification	Variable	Object	Classification	Variable
U.S.	Total retail sales	Y01	China	Total retail sales	Y05	Founded number of data companies in the U.S.	Total	Y09	Founded number of data companies in China	Total	Y14
	Retail e-commerce sales	Y02		Retail e-commerce sales	Y06		Data/technology	Y10		Data/technology	Y15
	Proportion of e-commerce in total retail	Y03		Proportion of e-commerce in total retail	Y07		Business analytics	Y11		Business analytics	Y16
	Growth rate of retail e-commerce	Y04		Growth rate of retail e-commerce	Y08		Industrial application	Y2		Industrial application	Y17
							Research/consulting	Y13		Research/consulting	Y18

Notes: the default of “WoS” stands for “WoS (Core Collection)” and “CNKI” stands for “CNKI (periodical).”