As the post-pandemic workplace gets increasingly volatile and complex, employee well-being has become one of the most pressing challenges. Meanwhile, organizations are increasingly using advanced analytics and AI solutions to track employee well-being. This opens new chances to investigate how well-being changes over time. By exploring patterns, trajectories, and regularities of well-being indicators, this dynamic perspective provides crucial window to understand what constitutes adaptive and maladaptive functioning at work.
This project aims to shed light on the nature of well-being dynamics at work, as well as the individual and contextual drivers. Moreover, this project aims to understand how to apply AI in well-being management-to enable more nuanced detection, foster trust and implement efficient interventions.