A Study on the Improvement Direction of Artificial Intelligence Speakers Applying DeLone and McLean’s Information System Success Model
Table 7
Results of hypothesis testing.
Hypothesis
Unstandardized coefficients
Standardized coefficients
Result
Sig.
Collinearity statistics
B
Std. error
Beta
Tolerance
VIF
(constant)
1.712
.342
—
5.007
—
.000
—
—
H1: INFQLT ➔ USE
.289
.129
.334
2.246
S
.029
.529
1.890
H2: SERQLT ➔ USE
.179
.106
.238
1.695
N
.096
.595
1.680
H3: SYSQLT ➔ USE
.089
.122
.116
.723
N
.473
.455
2.195
H4: PERPN ➔ USE
.015
.114
.019
.133
N
.895
.584
1.711
, degree of ,, , adjusted , Durbin-
(constant)
-.373
.430
—
-.867
—
.390
—
—
H5: INFQLT ➔ USERSAT
-.180
.162
-.133
-1.112
N
.271
.529
1.890
H6: SERQLT ➔ USERSAT
.290
.133
.245
2.178
S
.034
.595
1.680
H7: SYSQLT ➔ USERSAT
.634
.154
.530
4.119
S
.000
.455
2.195
H8: PERPN ➔ USERSAT
.271
.144
.214
1.882
N
.065
.584
1.711
, degree of ,, , adjusted , Durbin-
(constant)
.687
.648
—
1.059
—
.294
—
—
H9: USE ➔ USERSAT
.672
.186
.429
3.618
S
.001
1.000
1.000
, degree of ,, , adjusted , Durbin-
(constant)
2.608
.239
—
10.904
—
.000
—
—
H10: USERSAT ➔ USE
.274
.076
.429
3.618
S
.001
1.000
1.000
, degree of ,, , adjusted , Durbin-
(constant)
.889
.545
—
1.631
—
.108
—
—
H11: USE ➔ NETBEN
.476
.171
.345
2.781
S
.007
.816
1.226
H12: USERSAT ➔ NETBEN
.249
.109
.283
2.281
S
.026
.816
1.226
, degree of ,, , adjusted , Durbin-
(constant)
2.322
.285
—
8.143
S
.000
—
—
H13: NETBEN ➔ USE
.338
.084
.467
4.019
S
.000
1.000
1.000
, degree of ,, , adjusted , Durbin-
(constant)
1.391
.456
—
3.051
S
.003
—
—
H14: NETBEN ➔ USERSAT
.490
.135
.431
3.641
S
.001
1.000
1.000
, degree of ,, , adjusted , Durbin-
S: support; N: reject; INFQLT: information quality; SYSQLT: system quality; SERQLT: service quality; PERPN: perceived playfulness; USE: use; USERSAT: user satisfaction; NETBEN: net benefits.
