A Two-Stage SEM—Artificial Neural Network Analysis of the Engagement Impact on Employees’ Well-Being

Abstract

Employees’ engagement (EE) and well-being (WB) are considered two interesting issues by many scientific researchers and practitioners within organizations. Most research confirms a positive correlation between EE and WB. EE is an essential premise for specific dimensions of employees’ WB. At the same time, satisfied and physically and mentally healthy employees increase EE, both EE and WB thus being fundamental to individual and organizational performance. This paper aims to evaluate the relationships between EE and WB and between the dimensions of these two complex constructs. These relationships were assessed based on data obtained from a sample of 269 employees in Romania, using as a method a mix of analyses based on structural equation modeling (SEM) and artificial neural network analysis (ANN). The results highlighted a positive two-way relationship between EE and WB. Among the dimensions of EE, motivation and work environment are those that ensure a more pronounced perception of WB by the employee. Emotional WB, occupational WB, and social WB are the dimensions of WB with a significant influence on the general level of EE.