Using a principal factor solution and the Kaiser criterion, the resulting principal factor matrix was rotated to a
varimax solution converging in six iterations. Deleting all factors with an eigenvalue of less than 1.00, a principal
factor component analysis yielded four factors. The factor count was confirmed through visual inspection of the
scree plot. The cumulative percentage of variance explained in the four factors solution was 64%. The accepted
guideline for identifying factor loadings based on a sample size needed for .05 significance level is .45 for a
sample size of 150 respondents and .50 for a sample size of 120 respondents (Hair, Jr., et al., 1998). Since the
sample size for this research was 135 respondents, it was determined through extrapolation that the minimum
needed significant factor loading was .47. All but one of the 27 items loaded on exactly one of the four factors at
or above the .47 threshold. Table 3 contains the factor loading results showing the highest values from each item
loading on a single factor.