Table 3.

Prediction of use, ease of use, and perceived ease of use based on binary logistic regression and linear regression analysis

Predictors	Public transportation ticket machine			Cash machine (bank)			Self-scanner cash registers in grocery stores
	Usea	Ease of useb	Perceived ease of usec	Usea	Ease of useb	Perceived ease of usec	Usea	Ease of useb	Perceived ease of usec
	OR	Beta	Beta	OR	Beta	Beta	OR	Beta	Beta
Age	0.955***	0.038	− 0.234**	0.919***	− 0.011	− 0.041	0.926***	− 0.030	− 0.115*
Female (ref. male)	0.712	0.021	0.001	0.959	0.046	0.043	0.785	0.044	0.008
Educationd	1.465**	0.112**	0.097	2.266***	0.058	0.234	1.570***	0.035	0.090
Incomee	1.154	0.161***	0.076	1.175	0.128**	0.038	1.430**	0.057	0.050
Lives alone (ref. does not live alone)	1.040	0.124**	0.079	0.871	0.079	− 0.121	0.707	0.078	0.016
Rural area (ref. nonrural area)	0.831	− 0.011	− 0.111	0.912	− 0.001	0.008	0.891	− 0.013	− 0.052
Subjective healthf	1.081	0.101*	0.041	1.004	0.103**	− 0.066	1.042	0.091	0.094
Interest in technologyg	1.046	0.088*	0.204**	1.348**	0.054	0.013	1.262***	0.028	0.101
Model fit	CS (8, 886) = 41.280; p < 0.001; NR2 = 0.067	F(8, 644) = 6.582; p < 0.001; corrected R2 = 0.065	F(8, 183) = 3.779; p < 0.001; corrected R2 = 0.108	CS (8, 901) = 80.242; p < 0.001; NR2 = 0.178	F(8, 803) = 4.149; p < 0.001; corrected R2 = 0.030	F(8, 67) = .653; p = 0.730; corrected R2 = 0.004	CS (8, 895) = 112.772; p < 0.001; NR2 = 0.159	F(8, 352) = 0.875; p = 0.538; corrected R2 = 0.003	F(8, 320) = 2.642; p = 0.008; corrected R2 = 0.039

Predictors	Contactless payment			Self-checkout apps or machines
	Usea	Ease of useb	Perceived ease of usec	Usea	Ease of useb	Perceived ease of usec
	OR	Beta	Beta	OR	Beta	Beta
Age	0.952***	0.016	− 0.181**	0.945**	0.125	− 0.172**
Female (ref. male)	1.116	0.146*	− 0.083	0.681	− 0.076	− 0.021
Educationd	1.520***	0.104	0.033	1.575*	0.005	0.103
Incomee	1.422**	0.094	0.114	1.274	0.088	0.092
Lives alone (ref. does not live alone)	0.880	− 0.018	0.080	0.806	− 0.060	0.079
Rural area (ref. nonrural area)	0.860	− 0.110*	− 0.072	0.465**	− 0.158	− 0.070
Subjective healthf	0.949	0.078	0.175**	1.016	− 0.052	0.070
Interest in technologyg	1.179*	0.103	0.131*	1.219	0.217	0.119*
Model fit	CS (8, 887) = 82.357; p < 0.001; NR2 = 0.120	F(8, 335) = 2.990; p = 0.003; corrected R2 = 0.045	F(8, 283) = 5.457; p < 0.001; corrected R2 = 0.112	CS (8, 875) = 39.400; p < 0.001; NR2 = 0.089	F(8, 84) = 1.245; p = 0.285; corrected R2 = 0.023	F(8, 321) = 4.351; p < 0.001; corrected R2 = 0.077

^*p < 0.05. **p < 0.01. ***p < 0.001

^aUse (scale: 1 = users, 0 = nonusers)

^bEase of use (only users, scale: 1 = very difficult to 5 = very easy)

^cPerceived ease of use (only nonusers, scale: 1 = very difficult to 5 = very easy)

^dEducation (3 = tertiary, 2 = secondary, 1 = primary level)

^eHousehold income (1 = less than CHF 2000; 2 = 2000–4000, 3 = 4001–8000, 4 = more than CHF 8000)

^fSubjective health (1 = does not apply at all to 5 = fully applies)

^gGeneral interest in technology (1 = does not apply at all to 5 = fully applies)