Algorithmic Management as a Double-Edged Form of Digital Work Design: Job Demands, Autonomy and Employee Outcomes across 35 European Countries

Abstract Computer-based managerial systems are part of the digital infrastructure of work, with potential implications for employee demands and discretion. Drawing on Job Demands-Resources theory, this study examines task allocation, work scheduling and performance monitoring as distinct functions and their parallel indirect associations with engagement and intention to quit through work intensity and autonomy. Weighted least squares mean- and variance-adjusted structural equation models were estimated for 26,504 employees in 35 European countries using the 2024 European Working Conditions Survey. The measures capture reported computer involvement rather than verified artificial intelligence capabilities. Engagement and autonomy were modelled as latent factors, and quit intention as an ordinal outcome. All three practices were positively associated with work intensity. Task allocation was positively associated with autonomy, whereas monitoring was negatively associated with autonomy; scheduling’s negative autonomy association was less robust to contextual fixed effects. Task allocation showed opposing indirect engagement associations through intensity and autonomy, whereas monitoring showed negative associations through both pathways. Intensity-related indirect associations with quit intention were consistently positive, while autonomy-related indirect associations were not statistically significant in the primary or fixed-effects models. Sensitivity analyses supported the main directional patterns, while exploratory country diagnostics indicated incomplete measurement invariance and heterogeneous slopes. The findings inform the evaluation of digital management by distinguishing functions associated with greater demands and greater autonomy from those associated with greater demands and reduced autonomy. The cross-sectional design does not establish causal mediation or uniform cross-country relationships.