Abstract

Organizations more and more attempt to utilize employee survey data for evidence-based management and organizational change. However, employee survey models are often underdeveloped in structure and seldom systematically validated, what limits their value for these purposes. The aim of the presented thesis was to address this gap with three studies developing, validating and applying the first published integrative science-based employee survey process model. Based on a review of scientific employee survey models, in the first study, seven potential process models are proposed. These models are comparatively tested by applying structural-equation-modelling to a meta-analytical synthesis of N = 123 meta-analyses from psychology, management science and business research. We find evidence for a mediation model with two general dimensions of employees’ perceived work environment affecting their job attitudes and organizational outcomes. In the second study, this model is validated in three large-scale empirical field studies. The studies support causality of the models’ structural assumptions as well as its generalizability to an analysis on work unit level. With the third study, a case example of working with survey data generated with the newly developed model to acquire evidence for EbM in practice is presented. Overall, the research contributes to the employee survey literature by developing a first all-around scientifically sound employee survey model with validated causal model structure and offering first evidence for the relevance of multi-level modeling in employee survey models. Further, it contributes theoretically to the understanding of people outcomes and organizational adaptability emergence from employees’ work environment perceptions. In sum, this thesis provides a survey model with which organizations can apply survey data for EbM to improve organizational development and managerial decision-making.