User Acceptance of Internet of Vehicles Services: Empirical Findings of Partial Least Square Structural Equation Modeling (PLS-SEM) and Fuzzy Sets Qualitative Comparative Analysis (fsQCA)

Table 3

Demographic characteristics and driving-related information.

Variables	Items	Frequency	Percentage
Gender	Male	186	51.38
	Female	176	48.62
Age	18∼25	121	33.43
	26∼30	66	18.23
	31∼40	131	36.19
	41∼50	32	8.84
	More than 51	12	3.31
Education	High school or less	8	2.21
	Junior college	16	4.42
	Bachelor degree	135	37.29
	Master degree	117	32.32
	Ph. D. and above	86	23.76
Occupation	Senior manager	55	15.19
	Professionals	93	25.69
	Civil servant	3	0.83
	Company employee	50	13.81
	Service worker	3	0.83
	Labor	2	0.55
	Private entrepreneurs	8	2.21
	Self-employer	10	2.76
	Student	118	32.60
	Unemployed	7	1.93
	Other	13	3.59
Monthly household income (¥)	Less than 3001	22	6.08
	3001–5000	45	12.43
	5001–10,000	111	30.66
	10,001–15,000	80	22.10
	15,001–20,000	47	12.98
	20,001–30,000	34	9.39
	More than 30,000	23	6.35
Driver’s license	Yes	318	87.85
	No	44	12.15
Car purchase experience	Yes	193	53.31
	No	169	46.69
Number of cars owned by the household	0	54	14.92
	1	206	56.91
	2	91	25.14
	3	8	2.21
	>3	3	0.83
IoV-based services most frequently used	Automatic parking assist	56	15.47
	Adaptive cruise control	73	20.17
	Collision avoidance system	51	14.09
	In-vehicle infotainment	81	22.38
	Human-machine interaction	168	46.41
	Intelligent navigation	109	30.11
	Unconscious pay	198	54.70
	Self-driving	9	2.49
	Other	79	21.82