Algorithmic Management, Technostress, and Employee Mental Health in West Java

Abstract

This study examines the effect of algorithmic management on employee mental health and the mediating role of technostress, viewing artificial intelligence (AI) as a double-edged sword in the workplace. Data were collected through an online questionnaire from 300 employees in West Java, Indonesia, who had used algorithm-based work systems for at least three months and were selected through purposive sampling. The data were analyzed with partial least squares structural equation modeling (PLS-SEM) in SmartPLS 4.1. The structural model shows that algorithmic management has a significant direct effect on employee mental health and a strong effect on technostress, while technostress significantly affects mental health. The indirect effect through technostress is significant and accounts for about 61% of the total effect, indicating partial mediation. The model explains 78.3% of the variance in mental health and 64.7% of the variance in technostress. The findings show that algorithmic management can raise efficiency but also generates technostress that shapes employees' psychological condition. Organizations should combine AI-based control with human oversight, digital well-being policies, and technostress training. Keywords: Algorithmic Management; Technostress; Employee Mental Health; Artificial Intelligence; Mediating Effect