A Bibliometric Analysis of the Use of Technology in Employee Performance Evaluation: Trends and Implications

Abstract

This bibliometric analysis explores the integration and implications of technology in employee performance evaluations, emphasizing trends over the last few decades. As organizations globally adapt to rapid digital transformations, traditional performance appraisal systems are increasingly replaced with technologically advanced methods including AI, blockchain, and machine learning. This study systematically reviews literature from major scholarly databases to map the evolution of these technologies and their impact on human resource management practices. It identifies significant trends, such as the rise in digital solutions post-COVID-19 and the challenges associated with data privacy and algorithmic bias. The findings offer a comprehensive understanding of how technology reshapes employee performance evaluation, highlighting a transition from conventional methods to dynamic, real-time assessment processes. This research not only documents existing patterns but also pinpoints gaps in current studies, suggesting avenues for future exploration to enhance organizational effectiveness through technology.