Using latent profile analysis to advance job demands–resources theory: An empirical demonstration in the sales context

Abstract While Job Demands–Resources (JD-R) Theory has proliferated over the last 25 years, empirical applications have stagnated, leaving key propositions of the theory untested. In response, we propose a new empirical approach to JD-R theory using Latent Profile Analysis (LPA) and Latent Transition Analysis (LTA). Leveraging a six-month, four-wave survey, we demonstrate the usefulness of these methods using the sales context. We identify four distinct salesperson subgroups (i.e., JD-R profiles) that are associated with adverse outcomes (e.g., burnout, turnover). Supplemental analyses with observed turnover and a replication sample provide robust support for this typology. We also find that sales role factors and critical events (e.g., hitting quota) shape the likelihood of being in a specific JD-R profile across time. Our research provides a nuanced empirical approach for scholars to employ when testing JD-R theory and provides managerial insight to proactively diagnose burnout and turnover dynamics within a sales force.