Table 2. Description of sample data...

Table 2.

Description of sample data

Characteristics	Total	Average in total	the USA	(%)	China	(%)
Gender
Men	1,483	59	737	56	746	61
Women	1,049	41	580	44	469	39
Age
18–28	810	32	397	30	413	34
28–38	1,170	46	593	45	577	47
38–48	389	15	246	19	143	12
Above 48	163	6	81	6	82	7
Education
High school	173	7	63	5	110	9
College	416	16	195	15	221	18
Bachelor’s degree	1,666	66	926	70	740	61
Master’s degree	277	11	133	10	144	12
PhD	0	0	0	0	0	0
Income
Less $10,000	279	11	120	9	159	13
From $10,000 to $30,000	1,277	51	632	48	645	53
From $30,000 to $50,000	557	22	336	26	221	18
From $50,000 to $70,000	228	9	119	9	109	9
Above $70,000	191	8	110	8	81	7
Frequency of cryptocurrencies’ use in e-commerce (times in a month)
0	0	0	0	0	0	0
1–5	349	14	185	14	164	13
6–10	1305	51	696	53	609	50
11–2,015	358	14	175	13	183	15
16–20	267	11	152	12	115	9
>20	253	10	109	8	144	12

Characteristics	Total	Average in total	the USA	(%)	China	(%)
Gender
Men	1,483	59	737	56	746	61
Women	1,049	41	580	44	469	39
Age
18–28	810	32	397	30	413	34
28–38	1,170	46	593	45	577	47
38–48	389	15	246	19	143	12
Above 48	163	6	81	6	82	7
Education
High school	173	7	63	5	110	9
College	416	16	195	15	221	18
Bachelor’s degree	1,666	66	926	70	740	61
Master’s degree	277	11	133	10	144	12
PhD	0	0	0	0	0	0
Income
Less $10,000	279	11	120	9	159	13
From $10,000 to $30,000	1,277	51	632	48	645	53
From $30,000 to $50,000	557	22	336	26	221	18
From $50,000 to $70,000	228	9	119	9	109	9
Above $70,000	191	8	110	8	81	7
Frequency of cryptocurrencies’ use in e-commerce (times in a month)
0	0	0	0	0	0	0
1–5	349	14	185	14	164	13
6–10	1305	51	696	53	609	50
11–2,015	358	14	175	13	183	15
16–20	267	11	152	12	115	9
>20	253	10	109	8	144	12

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