UTAUT2. The resulting model has KMO values of 0.894,
whereas Tabachnick & Fidell’s (2007) test of sphericity was
significant (6466.97, p < 0.01). Principal component analysis
(PCA) indicated eight components with eigenvalues
exceeding one, explaining 75.95% of the variance. Therefore, the researcher is confident about the appropriateness of
factor analysis.
Table 7.3 shows the results from the EFA of all
constructs.
Table 7.3 shows the factor analysis of 31 items with eight
constructs. The highest eigenvalue is 9.995, the total variance explained is 75.75%, and Cronbach’s alpha is 0.922.
The correlations among all items were also inspected. The
correlation matrix shows that most variables are correlated
with each other. However, Cohen’s (1977) provided criteria
that correlations of 0.1 are taken as small, 0.3 is medium,
and 0.5 is large and reflects that healthy correlations are
observed among items from the same scale. After running an
Table 7.3 Component matrix
for the overall questionnaire–
factor analysis
Rotated component matrix
Items
Overall components of UTAUT2 model
1
2
3
4
5
6
7
8
BI1
0.684
BI2
0.697
BI3
0.727
PE1
0.832
PE2
0.873
PE3
0.89
PE4
0.812
PE5
0.807
EE1
0.821
EE2
0.83
EE3
0.829
EE4
0.787
EE5
0.824
SI1
0.83
SI2
0.826
SI3
0.773
SI4
0.832
SI5
0.829
FC1
0.802
FC2
0.794
FC3
0.797
FC4
0.817
M1
0.813
M2
0.881
M3
0.875
H1
0.702
H2
0.676
H3
0.751
UB1
0.831
UB2
0.88
UB3
0.897
Extraction method: principal component analysis, rotation method: varimax with Kaiser normalization,
rotation converged in six iterations
64
7 Empirical Evidence of LMS Adoption in the Middle East
whereas Tabachnick & Fidell’s (2007) test of sphericity was
significant (6466.97, p < 0.01). Principal component analysis
(PCA) indicated eight components with eigenvalues
exceeding one, explaining 75.95% of the variance. Therefore, the researcher is confident about the appropriateness of
factor analysis.
Table 7.3 shows the results from the EFA of all
constructs.
Table 7.3 shows the factor analysis of 31 items with eight
constructs. The highest eigenvalue is 9.995, the total variance explained is 75.75%, and Cronbach’s alpha is 0.922.
The correlations among all items were also inspected. The
correlation matrix shows that most variables are correlated
with each other. However, Cohen’s (1977) provided criteria
that correlations of 0.1 are taken as small, 0.3 is medium,
and 0.5 is large and reflects that healthy correlations are
observed among items from the same scale. After running an
Table 7.3 Component matrix
for the overall questionnaire–
factor analysis
Rotated component matrix
Items
Overall components of UTAUT2 model
1
2
3
4
5
6
7
8
BI1
0.684
BI2
0.697
BI3
0.727
PE1
0.832
PE2
0.873
PE3
0.89
PE4
0.812
PE5
0.807
EE1
0.821
EE2
0.83
EE3
0.829
EE4
0.787
EE5
0.824
SI1
0.83
SI2
0.826
SI3
0.773
SI4
0.832
SI5
0.829
FC1
0.802
FC2
0.794
FC3
0.797
FC4
0.817
M1
0.813
M2
0.881
M3
0.875
H1
0.702
H2
0.676
H3
0.751
UB1
0.831
UB2
0.88
UB3
0.897
Extraction method: principal component analysis, rotation method: varimax with Kaiser normalization,
rotation converged in six iterations
64
7 Empirical Evidence of LMS Adoption in the Middle East