PhD Final Thesis April 2013.pdf - Anglia Ruskin Research Online

Thesis Keith Gale 2013Table 9.15: Rotated component matrix for section 3 behaviour questionsComponent1 2Q25 Incentives .778Q23 Decision making .772Q21 Relationships .725Q29 Trust .636Q24 Knowledge transfer .608Q37 Motivation .602 .428Q22 Communication .486Q30 Empowerment .793Q35 Diversity .373 .715Q36 Satisfaction .395 .623Extraction Method: Principal Component Analysis.Rotation Method: Varimax with Kaiser Normalization. aa. Rotation converged in 3 iterations.Results from the component matrix (Table 9.15) are recalculated to provide loadingsfor each factor after rotation. Table 9.15 shows the output after a suppression of lessthan 0.3 was used – all variables exceeded this value. The variables are listed in orderof magnitude of factor loading. Three variables loaded onto two components, butthese were strongly biased toward one factor.Table 9.16: Total variance for section 3 behaviour questionsComponentRotation Sums of Squared LoadingsTotal % of Variance Cumulative %1 3.396 33.965 33.9652 1.924 19.244 53.209Extraction Method: Principal Component Analysis.Summation of the factor analysis results:Responses from participants to questions regarding ten behaviours for successfulgroup performance included within the questionnaire were subject to an examinationof suitability for factor analysis. Inspection of the correlation matrix revealed asignificant number of coefficients above .3 (68 out of 100). The KMO value was.861 and Bartlett’s test reached statistical significance supporting use of data forfactor analysis. Eigenvalues exceeded 1 for two components, explaining 42.7% and225