Page 171 - Hojnik, Jana. 2017. In Persuit of Eco-innovation. Drivers and Consequences of Eco-innovation at Firm Level. Koper: University of Primorska Press
P. 171
Results
Table 36: Descriptive statistics for determinant Customer demand
N Mean St. Dev. Skew St. Err. Kurt St. Err.
223 Skew Kurt
223
Environment is a 223 4.69 1.703 -0.353 0.163 -0.716 0.324
critical issue for 223
our important cus- 4.33 1.762 -0.246 0.163 -0.933 0.324
tomers.
4.54 1.710 -0.319 0.163 -0.751 0.324
Our important cus-
tomers often bring 171
up environmental
issues. 4.24 1.764 -0.065 0.163 -0.870 0.324
Customer demands
motivate us in our
environmental ef-
forts.
Our customers have
clear demands re-
garding environ-
mental issues.
Note: N = number of observations; Mean = mean value on the Likert scale, which ranges
from 1 to 7 (1 = strongly disagree, 7 = strongly agree); St. Dev. = standard deviation; Skew =
skewness; St. Err. of Skew = standard error of skewness; Kurt = kurtosis; St. Err. Kurt = stan-
dard error of kurtosis.
Continuing, an exploratory factor analysis (the method of extraction
was the Maximum Likelihood Method, and the selected rotation was Di-
rect Oblimin rotation) was also conducted for this construct. Before the
analysis, all measurement items were checked for normality of distribu-
tion (see Table 36). Results have shown that the ratio of standard errors
of kurtosis and skewness range between values of -2 and 2, which implies
normality of distribution.
The appropriateness of factor analysis was determined by examining
the correlation matrix of customer demand items. The Bartlett’s test of
sphericity showed that the correlation matrix has significant correlations
(p < 0.05) and, the Kaiser-Meyer-Olkin measure of sampling adequacy
was 0.867, which indicates an excellent sample adequacy.
The number of expected factors was one, and the extracted factor was
one, explaining 79.711% of variance. After consideration of each item’s
communality index and its contribution, we retained all the items (the
lowest communality after extraction was 0.721).
Table 36: Descriptive statistics for determinant Customer demand
N Mean St. Dev. Skew St. Err. Kurt St. Err.
223 Skew Kurt
223
Environment is a 223 4.69 1.703 -0.353 0.163 -0.716 0.324
critical issue for 223
our important cus- 4.33 1.762 -0.246 0.163 -0.933 0.324
tomers.
4.54 1.710 -0.319 0.163 -0.751 0.324
Our important cus-
tomers often bring 171
up environmental
issues. 4.24 1.764 -0.065 0.163 -0.870 0.324
Customer demands
motivate us in our
environmental ef-
forts.
Our customers have
clear demands re-
garding environ-
mental issues.
Note: N = number of observations; Mean = mean value on the Likert scale, which ranges
from 1 to 7 (1 = strongly disagree, 7 = strongly agree); St. Dev. = standard deviation; Skew =
skewness; St. Err. of Skew = standard error of skewness; Kurt = kurtosis; St. Err. Kurt = stan-
dard error of kurtosis.
Continuing, an exploratory factor analysis (the method of extraction
was the Maximum Likelihood Method, and the selected rotation was Di-
rect Oblimin rotation) was also conducted for this construct. Before the
analysis, all measurement items were checked for normality of distribu-
tion (see Table 36). Results have shown that the ratio of standard errors
of kurtosis and skewness range between values of -2 and 2, which implies
normality of distribution.
The appropriateness of factor analysis was determined by examining
the correlation matrix of customer demand items. The Bartlett’s test of
sphericity showed that the correlation matrix has significant correlations
(p < 0.05) and, the Kaiser-Meyer-Olkin measure of sampling adequacy
was 0.867, which indicates an excellent sample adequacy.
The number of expected factors was one, and the extracted factor was
one, explaining 79.711% of variance. After consideration of each item’s
communality index and its contribution, we retained all the items (the
lowest communality after extraction was 0.721).
