Systems Intelligence and Job Autonomy in Managing Stressors and Performance: A Time-Lagged Study in Multinational Firms

This study examines how job demands, personal resources, and job resources influence work outcomes, focusing on the role of job autonomy and systems intelligence. Drawing on Job Demand–Resource and Job Demand–Control Models, we hypothesize that job autonomy moderates the negative effects of job stressors (work overload, managerial pressure, and time pressure) on job performance. Additionally, we propose that systems intelligence mediates the relationship between job stressors and job performance. Data were collected from employees in multinational firms in Pakistan through two time-lagged survey waves. The results show that job stressors at time 1 (work overload, managerial pressure, time pressure) negatively affect perceived job performance at time 2 but not supervisor-rated performance. Job autonomy at time 2 weakens the negative impact of managerial pressure on perceived performance but does not mitigate work overload or time pressure at time 1. Systems intelligence at time 2 directly influences perceived job performance (time 2) but does not mediate the relationship between job stressors (time 1) and performance outcomes (time 2), challenging existing mediation models. These findings underscore the importance of the “buffer hypothesis” in reducing the negative effects of job demands on performance. Systems intelligence consistently predicts increased job autonomy across both time points and reduces managerial pressure, work overload, and time pressure at time 2. This research contributes valuable insights into optimizing employee performance and well-being amidst complex workplace stressors, emphasizing that job resources (such as autonomy) and personal resources (such as systems intelligence) can work together or independently to support positive outcomes.