6. Positioning of the cooperatives
A factorial analysis of the principal components was performed from the scores recorded for the characteristics
of the sector. This reduced the whole group of variables into a smaller number of mutually correlated
components. As a result, a series of quantitative indices was obtained.
The correlations between the variables demonstrated a degree of commonality in their explicative capacity. The
matrix of correlations was submitted to two tests: Bartlett’s spherificity test and the Kaiser-Meyer-Olkin (KMO)
index.
The Bartlett statistic, which had a value 2
= 430.088 with a critical significance level of 0.000, made it possible
to reject the null hypothesis of non-correlation between the observed variables. The Bartlett test confirmed the
existence of lineal dependence between the variables and justified continuing with the procedure.
An exploratory factor analysis was carried out and three factors or components were obtained. The Kaiser
criterion was used in their elaboration in such a way as to conserve only those factors that presented eigen values
of one or greater. The first three factors retained 64.2 percent of the initial variance—which represents a good
proportion given that each of the new components provided independent (and therefore unrepeated) information.
With the rotated component matrix (Varimax rotation method) it was possible to obtain weightings for each
factor in each of the variables. In Table 4, the first column presents items with highest saturations on the first
factor; the second column presents those mainly saturated on the second factor; and the last column is formed by
items more closely related with the third factor. Each factor had a high correlation with one group of variables
and a low correlation with the rest—thereby providing a more appropriate interpretation of the initial factors.
The factors derived from the analysis were assigned a ‘label’ and an index (or score). This index was the
arithmetic average of the items that formed it. The variables with high saturations (which appear in italics in the
previous rotated component matrix) corresponded to the following factors:
Factor 1 Orientation towards marketing and quality management: this is related to marketing research
attitude, presence on the Internet, presence in external markets, the establishment of guarantee of origin, and
a quality certification (score 3.72 on scale of 1–5).
Factor 2 Perceived risk: this is related to risk perceived with the entry of new countries to the EU, fear of
diminished subsidies, and concern regarding lack of qualified personnel (score 3.75 on scale of 1–5).
Factor 3 Closed mind: this is related to the general business mentality of the sector and attitudes towards the
promotion and communication activities of the sector (score 3.44 on scale of 1–5).
The three factors all scored above three (the mid-range value of the measurement scale of 1–5), but all three
scored values removed from the extreme values. This suggests that there is still room for increase in the first
factor, and room for a decrease in the other two factors.
6. Positioning of the cooperatives
A factorial analysis of the principal components was performed from the scores recorded for the characteristics
of the sector. This reduced the whole group of variables into a smaller number of mutually correlated
components. As a result, a series of quantitative indices was obtained.
The correlations between the variables demonstrated a degree of commonality in their explicative capacity. The
matrix of correlations was submitted to two tests: Bartlett’s spherificity test and the Kaiser-Meyer-Olkin (KMO)
index.
The Bartlett statistic, which had a value 2
= 430.088 with a critical significance level of 0.000, made it possible
to reject the null hypothesis of non-correlation between the observed variables. The Bartlett test confirmed the
existence of lineal dependence between the variables and justified continuing with the procedure.
An exploratory factor analysis was carried out and three factors or components were obtained. The Kaiser
criterion was used in their elaboration in such a way as to conserve only those factors that presented eigen values
of one or greater. The first three factors retained 64.2 percent of the initial variance—which represents a good
proportion given that each of the new components provided independent (and therefore unrepeated) information.
With the rotated component matrix (Varimax rotation method) it was possible to obtain weightings for each
factor in each of the variables. In Table 4, the first column presents items with highest saturations on the first
factor; the second column presents those mainly saturated on the second factor; and the last column is formed by
items more closely related with the third factor. Each factor had a high correlation with one group of variables
and a low correlation with the rest—thereby providing a more appropriate interpretation of the initial factors.
The factors derived from the analysis were assigned a ‘label’ and an index (or score). This index was the
arithmetic average of the items that formed it. The variables with high saturations (which appear in italics in the
previous rotated component matrix) corresponded to the following factors:
Factor 1 Orientation towards marketing and quality management: this is related to marketing research
attitude, presence on the Internet, presence in external markets, the establishment of guarantee of origin, and
a quality certification (score 3.72 on scale of 1–5).
Factor 2 Perceived risk: this is related to risk perceived with the entry of new countries to the EU, fear of
diminished subsidies, and concern regarding lack of qualified personnel (score 3.75 on scale of 1–5).
Factor 3 Closed mind: this is related to the general business mentality of the sector and attitudes towards the
promotion and communication activities of the sector (score 3.44 on scale of 1–5).
The three factors all scored above three (the mid-range value of the measurement scale of 1–5), but all three
scored values removed from the extreme values. This suggests that there is still room for increase in the first
factor, and room for a decrease in the other two factors.
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