29.01.2013 Views

University of Vaasa - Vaasan yliopisto

University of Vaasa - Vaasan yliopisto

University of Vaasa - Vaasan yliopisto

SHOW MORE
SHOW LESS

Create successful ePaper yourself

Turn your PDF publications into a flip-book with our unique Google optimized e-Paper software.

Factor Analysis<br />

811<br />

Before regression analysis, exploratory factor analysis have been conducted to<br />

reduce the number <strong>of</strong> variables and to extract the underlying dimensions in order to<br />

check questionnaires <strong>of</strong> reliability and validity. Principal component analysis (PCA)<br />

and the varimax rotation method were employed for factor extraction. Eigenvalue<br />

tests showed a five (relative advantage, compatibility, complexity, observability,<br />

levels <strong>of</strong> non-voluntariness) factors structure (eigenvalue=1.06–8.03) for independent<br />

variables, and these factors explained 73.3% <strong>of</strong> the total variance, respectively. The<br />

relatively high factor loading scores verified the construct validity in the<br />

questionnaires. The calculation <strong>of</strong> Kaiser-Meyer-Olkin (KMO) statistics <strong>of</strong> 0.85,<br />

which can be described as ‘meritorious’, indicated that data are very suitable for<br />

factor analysis. Also, Bartlertt’s test <strong>of</strong> sphericity (χ 2 =2172.28, df = 253, p

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!