ALGORITHMIC MANAGEMENT AND EMPLOYEE WELL-BEING IN PAKISTANI HIGHER EDUCATION INSTITUTIONS: THE MODERATING ROLE OF PSYCHOLOGICAL EMPOWERMENT

Abstract

Algorithmic management has emerged as a vital tool for reforming efficiency and monitoring performance with the increasing adoption of digital technologies in organizational management. Although algorithmic management systems offer operational benefits, their impact on employee well-being remains under explored, especially in academic institutions of developing countries. This study empirically examines the impact of algorithmic management on well-being of workers in Pakistani HEIs, evaluating the moderating role of psychological empowerment. By employing quantitative research design, the study collected data from 800 administrative and academic staff of 14 private and 18 public higher educational institutions using structured questionnaire. PLS-SEM (Partial Least Squares Structural Equation Modeling was applied following outlier analysis, data screening and CMB (Common-Method-Bias Assessment).The measurement model was examined through Cronbach’s alpha, CR (Composite Reliability), Indicator Loadings, AVE (Average Variance Extracted), and HTMT (Heterotrait-Monotrait) ratio. Using bootstrapping (5000 resamples) and path coefficients Q2, R2 and F2 the study assessed structural model. Moderation analysis evaluated cushioning role of psychological empowerment. The results depict that algorithmic management has a significant negative effect on employees’ well-being while psychological empowerment significantly weakens the negative relationship between employees’ well-being and algorithmic management. Algorithmic management control systems have less effect on the employees who have high psychological empowerment. The study provides empirical evidence from a developing-country higher-education context and offers practical implications for designing technologically advanced yet employee-centered workplaces.