As automation increasingly reshapes organizational workflows, the complexity of information flow in the workplace intensifies, posing significant challenges to employees' cognitive capacities. Based on Information Processing Theory (IPT), this study examines how coworker turnover affects employees' information processing, thus influencing their individual performance changes, and investigates the negative impact of work automation on this process. We employ a discontinuous mixed-effects growth model using 57 months of panel data from a Chinese manufacturing firm to analyze how employees adapt and recover their productivity after a coworker’s departure. Our findings reveal that peer turnover significantly reduces productivity, with this impact being more severe and recovery slower for employees in highly automated roles. By extending IPT to automated settings, this research contributes to understanding how technological advancements interact with human factors in the workplace and provides actionable insights for companies implementing automation.
