Page 160 - Hojnik, Jana. 2017. In Persuit of Eco-innovation. Drivers and Consequences of Eco-innovation at Firm Level. Koper: University of Primorska Press
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Pursuit of Eco-innovation
ined and indicated similar results; specifically, the KMO value was 0.909,
which indicates an excellent sample adequacy.
The number of expected factors was one, and the extracted factor was
one. In addition, the scree plot of the initial run indicated one factor as
an appropriate number. Further, one factor explains 53.902% of variance.
After consideration of each item’s communality index and its contri-
bution, we retained all the items (the lowest communality after extrac-
tion was 0.335). In the process of analysis, researchers usually delete or
exclude items that have low communalities after extraction – below the
threshold of 0.20.
Table 28: KMO and Bartlett’s test of sphericity (Expected benefits)
160 KMO and Bartlett’s test 0.909
1190.240
Kaiser-Meyer-Olkin Measure of Sampling Adequacy
36
Approx. chi-square 0.000
Bartlett’s test of sphericity df
Sig.
Table 29: Standardized coefficients and their squares (Expected benefits)
To reduce costs (energy, material, etc.) Standard. coeff. R-square
To improve profitability
To increase productivity 0.58 0.34
To increase market share 0.76 0.58
To enter new markets 0.77 0.59
To improve firm reputation 0.85 0.72
To strengthen the brand 0.80 0.64
Competitive advantage 0.62 0.38
Adjustment to EU 0.77 0.59
0.85 0.72
0.53 0.28
Note: Standard. coeff. = Standardized coefficients; R-square = Coefficient of Determinati-
on.
A confirmatory factor analysis was conducted in order to validate
the findings of the exploratory factor analysis, which resulted in one fac-
tor composed of nine items. This was also confirmed by the confirmato-
ry factor analysis. The eco-innovation determinant of expected benefits
ined and indicated similar results; specifically, the KMO value was 0.909,
which indicates an excellent sample adequacy.
The number of expected factors was one, and the extracted factor was
one. In addition, the scree plot of the initial run indicated one factor as
an appropriate number. Further, one factor explains 53.902% of variance.
After consideration of each item’s communality index and its contri-
bution, we retained all the items (the lowest communality after extrac-
tion was 0.335). In the process of analysis, researchers usually delete or
exclude items that have low communalities after extraction – below the
threshold of 0.20.
Table 28: KMO and Bartlett’s test of sphericity (Expected benefits)
160 KMO and Bartlett’s test 0.909
1190.240
Kaiser-Meyer-Olkin Measure of Sampling Adequacy
36
Approx. chi-square 0.000
Bartlett’s test of sphericity df
Sig.
Table 29: Standardized coefficients and their squares (Expected benefits)
To reduce costs (energy, material, etc.) Standard. coeff. R-square
To improve profitability
To increase productivity 0.58 0.34
To increase market share 0.76 0.58
To enter new markets 0.77 0.59
To improve firm reputation 0.85 0.72
To strengthen the brand 0.80 0.64
Competitive advantage 0.62 0.38
Adjustment to EU 0.77 0.59
0.85 0.72
0.53 0.28
Note: Standard. coeff. = Standardized coefficients; R-square = Coefficient of Determinati-
on.
A confirmatory factor analysis was conducted in order to validate
the findings of the exploratory factor analysis, which resulted in one fac-
tor composed of nine items. This was also confirmed by the confirmato-
ry factor analysis. The eco-innovation determinant of expected benefits
