Page 211 - Hojnik, Jana. 2017. In Persuit of Eco-innovation. Drivers and Consequences of Eco-innovation at Firm Level. Koper: University of Primorska Press
P. 211
Results
Table 65: KMO and Bartlett’s test of sphericity (Competitive benefits)
KMO and Bartlett’s test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0.810
897.029
Approx. chi-square
6
Bartlett’s test of sphericity df 0.000
Sig.
The number of factors to be extracted was determined a priori based 211
on previous research works that used this scale. The number of extract-
ed factors should be one, while in the previous version with 12 items, two
factors were extracted, which in total explained 71.406% of variance. This
time we had four items, and only one factor was extracted, which is in
line with expectations. Moreover, this one factor explains 81.419% of var-
iance.
Therefore, we conducted a confirmatory factor analysis in order to
validate the findings of the exploratory factor analysis, which resulted in
one factor composed of four items. Figure 18 illustrates the main results
of the confirmatory factor analysis, related to the model goodness-of-fit
indexes and reliability coefficient (Cronbach’s alpha). In addition, all the
coefficients of the construct competitive benefits were found to be posi-
tive, high and significant. These are presented in Table 66 and Figure 18.
Table 66: Standardized coefficients and their squares (Competitive benefits)
Increased process/production efficiency. Standard. coeff. R-square
Increased productivity 0.87 0.76
Increased knowledge about effective ways of managing operations 0.91 0.83
Improved process innovations 0.92 0.85
0.92 0.85
Note: Standard. coeff. = Standardized coefficients; R-square = Coefficient of Determinati-
on.
Statistical information of the construct competitive benefits, per-
taining to reliability (reliability coefficients) and convergence (goodness-
of-fit model indexes) based on the overall sample (N = 223), is indicated
in the Figure 18. The construct competitive benefits showed good reli-
ability (Cronbach’s alpha = 0.946). In addition, the goodness-of-fit in-
Table 65: KMO and Bartlett’s test of sphericity (Competitive benefits)
KMO and Bartlett’s test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0.810
897.029
Approx. chi-square
6
Bartlett’s test of sphericity df 0.000
Sig.
The number of factors to be extracted was determined a priori based 211
on previous research works that used this scale. The number of extract-
ed factors should be one, while in the previous version with 12 items, two
factors were extracted, which in total explained 71.406% of variance. This
time we had four items, and only one factor was extracted, which is in
line with expectations. Moreover, this one factor explains 81.419% of var-
iance.
Therefore, we conducted a confirmatory factor analysis in order to
validate the findings of the exploratory factor analysis, which resulted in
one factor composed of four items. Figure 18 illustrates the main results
of the confirmatory factor analysis, related to the model goodness-of-fit
indexes and reliability coefficient (Cronbach’s alpha). In addition, all the
coefficients of the construct competitive benefits were found to be posi-
tive, high and significant. These are presented in Table 66 and Figure 18.
Table 66: Standardized coefficients and their squares (Competitive benefits)
Increased process/production efficiency. Standard. coeff. R-square
Increased productivity 0.87 0.76
Increased knowledge about effective ways of managing operations 0.91 0.83
Improved process innovations 0.92 0.85
0.92 0.85
Note: Standard. coeff. = Standardized coefficients; R-square = Coefficient of Determinati-
on.
Statistical information of the construct competitive benefits, per-
taining to reliability (reliability coefficients) and convergence (goodness-
of-fit model indexes) based on the overall sample (N = 223), is indicated
in the Figure 18. The construct competitive benefits showed good reli-
ability (Cronbach’s alpha = 0.946). In addition, the goodness-of-fit in-
