RESUMO
In this study, we examine the relationships between proactive personality, work locus of control, and vocational satisfaction. Moreover, we argue that these relationships vary depending on employees' levels of education (i.e., employees with academic degrees versus without academic degrees). Drawing on Trait Activation Theory, we expected more pronounced relationships of proactive personality and work locus of control with vocational satisfaction for employees with academic degrees. We collected data of N = 2068 employees with a broad range of occupational backgrounds to test our assumptions. A partial disaggregation model revealed that both proactive personality and work locus of control were positively related to vocational satisfaction and that these relationships differed depending on the level of education. Regarding the relationship between proactive personality and vocational satisfaction, we only found evidence among employees with academic degrees. Although work locus of control and vocational satisfaction were significantly related among both groups of employees, the relationship was even more pronounced among employees without academic degrees. Consequently, our results underline the importance of taking inter-individual differences, such as the level of education, into consideration when looking at the effects of proactive personality and work locus of control on work-related well-being.
RESUMO
We investigated by means of a simulation study how well methods for factor rotation can identify a two-facet simple structure. Samples were generated from orthogonal and oblique two-facet population factor models with 4 (2 factors per facet) to 12 factors (6 factors per facet). Samples drawn from orthogonal populations were submitted to factor analysis with subsequent Varimax, Equamax, Parsimax, Factor Parsimony, Tandem I, Tandem II, Infomax, and McCammon's minimum entropy rotation. Samples drawn from oblique populations were submitted to factor analysis with subsequent Geomin rotation and a Promax-based Tandem II rotation. As a benchmark, we investigated a target rotation of the sample loadings toward the corresponding faceted population loadings. The three conditions were sample size (n = 400, 1,000), number of factors (q = 4-12), and main loading size (l = .40, .50, .60). For less than six orthogonal factors Infomax and McCammon's minimum entropy rotation and for six and more factors Tandem II rotation yielded the highest congruence of sample loading matrices with faceted population loading matrices. For six and more oblique factors Geomin rotation and a Promax-based Tandem II rotation yielded the highest congruence with faceted population loadings. Analysis of data of 393 participants that performed a test for the Berlin Model of Intelligence Structure revealed that the faceted structure of this model could be identified by means of a Promax-based Tandem II rotation of task aggregates corresponding to the cross-products of the facets. Implications for the identification of faceted models by means of factor rotation are discussed.
