Factor Analysis for Human Capital Components

The 17 questionnaire items used in this study were designed to measure four elements of human capital theory: education, experience and skill, training and

development, and organisational engagement. Prior to performing PCA with varimax rotation using SPSS Version 15, the suitability of data for factor analysis was assessed. Given the sample of 930, factor loading of 0.4 and higher was considered significant for interpretative purposes. The cut-off point was set somewhat low to illustrate the factor interpretation process with as many significant loadings as possible. The KMO value was 0.87, exceeding the recommended value of 0.6 (Kaiser 1974) and Bartlett’s test of sphericity (Bartlett 1954) reached statistical significant (p<.05), supporting the factorability of the correlation matrix.

Research findings illustrate that Kaiser’s criterion is accurate when the number of variables is less than 30 and the resulting communalities (after extraction) are all greater than 0.7. Kaiser’s criterion is also accurate when the sample exceeds 250 and the average communality is greater than or equal to 0.6 (Andy 2005). Hair et al. (2006) state that loadings exceeding +0.70 and above are considered indicative of well-defined structure and are the goal of any factor analysis.

Principal components analysis revealed the presence of two components with eigenvalues exceeding 1. The two factors solution explained a total of 36.03 per cent of the variance in the observed values. Items loaded on factor 1, organisational engagement, contained 9 items. Factor 1 was thus designated organisational engagement, based on the recommendation of Hair et al. (2006), that variables with higher loadings influence the name or label selected to represent a factor. The organisational engagement factor accounted for 27.34 per cent of the variance in the observed values. Factor 2, training and development, contained 3 times representing the training environment (further details see Table 7.13) and accounted for 8.39 per cent of the variance in the observed values. According to Hair et al. (2006) there is no absolute threshold adopted for all applications; where component analysis for each variable contributes a value of 1 to the total eigenvalue. Thus, only factors having latent roots or eigenvalues greater than 1 were considered significant and used in this study. Most items loaded quite strongly (above 0.4) on the first two components, with fewer items loaded on components 3, 4 and 5. Therefore, the PCA was rerun based on two factors instead of four, as some components loaded fewer than three items and this outcome is weaker and generally unstable; 5 or more strongly loading items are desirable and indicates a stronger factor (Costello & Osborne 2005). Further, theoretically meaningful factors were sought, together with the most efficient factor structure.

However, this preparation does not change the underlying findings; it presents the pattern of loading in a manner that is easier to interpret. The result eventually shows a marked pattern of variables where significant loadings for each factor are evident. Factor 1 (organisational engagement) has nine variables with significant loadings, and factor 2 (training and development) has three variables. Any dual loadings or variables (items) that did not load to any factor were discarded. Overall, five items were omitted from the human capital analysis, questions 3, 1, 51, 53 and 12, variables with higher loadings are considered more important and have greater influence on the name or label selected to represent a factor (Hair et al. 2006). Thus, all the significant variables were examined for a particular factor and, placing greater emphasis on those variables with higher loadings, a name or label was assigned to a factor to accurately reflect the variables loading on that factor, as shown below.

Factor 1: Organisational engagement: questions 13, 8, 42, 31, 45, 34, 17, 41, and 49

Factor 2: Training and development: questions 33, 38 and 36. The variance analysis is set out at Table 7.10 below.

Table 7.10: Total Variance of Human Capital Components

Component

Initial Eigenvalues Rotation Sums of Squared Loadings Total Percentage of Variance Cumulative Percentage Total Percentage of Variance Cumulative Percentage Organisational engagement 4.70 27.64 27.64 3.349 19.700 19.70 Training and development 1.42 8.39 36.03 2.777 16.336 36.03 The tests of adequacy and sphericity are shown at Table 7.11.

Table 7.11: KMO and Bartlett's Tests of Human Capital Components

KMO Measure of Sampling Adequacy. .874

Bartlett's Test of Sphericity Chi-square approximations 3702.452 Degrees of freedom 136

Sig. .000

Cronbach’s alpha .833

The comparison value between eigenvalues and parallel analysis are summarised below. Only those factors that were larger than the criterion value from the parallel

analysis were retained, if less, then they were rejected. Thus, the significant variables for a particular factor were determined and, placing greater emphasis on those variables with higher loadings, a name or label was assigned to each factor. These are described at Table 7.12.

Table 7.12: Human Capital: Comparison Analysis of Eigenvalues Components (PCA) with Corresponding Criterion Values from Parallel Analysis. Component

Number

Actual Eigenvalue from PCA

Criterion Value from Parallel Analysis Decision 1 4.700 1.24 Accept 2 1.426 1.19 Accept 3 1.341 1.15 Reject 4 1.128 1.12 Reject 5 1.038 1.09 Reject

The outcomes from the rotated component matrix of scale for factor 1, organisational engagement and factor 2, training and development are set out in Table 7.13.

Table 7.13 Rotated Component Matrix of Scale Items for Human Capital

Variable Scale items Mean SD Factor

loading No. items in set Reliability Overall reliability Organisational engagement

13. Frequently, I think of quitting my job. 2.97 1.20 .674 9 .771 _0.77

8. I would be very happy to spend the rest of my career with this organisation 2.76 1.15 .666 .754 42. There is a sense of being a part of a family in this organisation. 2.38 1.03 .660 .747 31. My organisation values skill and experience when recruiting and promoting

employees. 2.86 1.16 .573 .752

45. This organisation has a poor future unless it attracts better managers. 3.21 1.24 .556 .790 34. My organisation does what it can to ensure the well being of its employees. 2.84 1.08 .536 .752 17. I do not feel emotionally attached to this organisation. 2.70 1.13 .523 .789 41. I believe employees really care about each other in this organisation. 2.73 1.00 .492 .762 49. My organisation supports employees to balance work and family

responsibilities.

2.87 1.06 .430 .767

Training and development

33. My organisation provides me with training opportunities enabling me to

extend my range of skills and abilities. 2.49 1.15 .703 3 .745 0.79

38. My organisation is committed to the training and development of its

employees 2.28 0.97 .674 .677

36. My organisation supports my attempts to acquire additional training or

Component Number 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 16 17 5 4 3 2 1 0

The following Figure 7.1 illustrates the results for this test.

Figure 7.1: Eigenvalue Plot for Scree Test Criterion for Human Capital Components Reliability for each multi-item scale was assessed using Cronbach’s Alpha. Results of the reliability analysis are reported in Table 7.13 above. Overall, strong reliability is demonstrated with Cronbach alpha ranging from 0.677 to 0.790 and overall human capital components have α =0.833. None of the items shown would substantially affect reliability if they were deleted, with the exception of question 45: deleting this question would increase Cronbach’s Alpha from 0.83 to 0.84. Nevertheless, this increase is not dramatic and both values reflect a reasonable degree of reliability.

The result indicates that all items are positively contributing to the overall reliability. The overall Cronbach’s Alpha is also excellent (0.83), above 0.8, which indicates good reliability. According to Cavana et al. (2001), reliability of less than 0.6 is considered poor, those in the 0.7 ranges are acceptable, and those over 0.8 are preferred. Other studies including Malhotra (1993) suggest 0.6 and above is acceptable, especially for initial investigations (see Table 7.14).

Table 7.14: Mean and Standard Deviation for Human Capital Components

Factor Mean SD

Organisational engagement 2.81 .679

Training and development 2.40 .879

Human capital factors 2.71 .654

Table 7.14 shows the means and standard deviations of organisational engagement (M=2.81, SD=0.67), training and development (M=2.40, SD=.87), and overall human capital variables (M=2.71, SD=0.65)