The Influence of Algorithm-Based Performance Appraisal on Employee Trust

Abstract

The study background stems from the fact that organizations are increasingly implementing algorithm-based performance appraisal systems. The Human Resource Management (HRM) digital transformation will result in changes that affect employee trust. AI systems provide greater objectivity and efficiency, but their impact on trust in organizational environments warrants further investigation. The research investigates how perceived algorithmic objectivity and system transparency, together with procedural justice, affect employee trust. The research used an explanatory quantitative method together with a cross-sectional survey approach to study 200 permanent employees who had experienced algorithm-based performance assessments. The researchers collected data via Likert-scale questionnaires and analyzed them using Partial Least Squares Structural Equation Modeling (PLS-SEM). The research results show that all examined factors positively impact employee trust, with procedural justice as the strongest factor (β = 0.41), and algorithmic objectivity (β = 0.32) and system transparency (β = 0.21) as the next strongest factors. The model explains 63% of the variance in trust (R² = 0.63). The study contributes through its research, which combines organizational justice theory with algorithmic management to show how trust develops in formal organizational settings, and provides practical guidance for building evaluation systems that maintain fairness, transparency, and accountability