Good employees through good jobs: a latent profile analysis of job types and employee outcomes in the Belgian electricity sector

The question of what constitutes a good job concerns employers, employees and policymakers alike. Given the multiple possible contingencies, this study applies a latent profile analysis (LPA) to employee data from the Belgian electricity sector to identify different job types based on the combinations of various job demands and resources. These job types are subsequently related to employee outcomes in terms of work engagement and innovative work behaviour, for which threshold values are computed using relative operating characteristic (ROC) analysis. The combination of both methods reveals that low-strain jobs with high resources and reasonable demands perform the best in terms of work engagement. For innovative work behaviour, they perform equally well as active jobs which combine high demands with high resources. Employees in jobs with low resources and high demands (high-strain and very high-strain jobs) are less likely to be engaged and innovative.

Publication year:2017

BOF-keylabel:yes

IOF-keylabel:yes

BOF-publication weight:1

CSS-citation score:1

Authors from:Private, Higher Education

Accessibility:Open