Innovation in Employee Performance Appraisal Based on Intelligent Algorithms: A Systematic Qualitative Review
Keywords:
Performance appraisal, artificial intelligence, machine learning, digital HR, intelligent algorithms, digital transformationAbstract
Objective: This study aims to identify innovative components and models in employee performance appraisal based on intelligent algorithms within digital-driven organizations.
Methods and Materials: This qualitative systematic review used thematic analysis to examine 12 peer-reviewed articles published between 2015 and 2025. Articles were selected based on their relevance to performance appraisal, artificial intelligence, machine learning, and digital transformation in HR. Data were analyzed using NVivo 14 software through open, axial, and selective coding until theoretical saturation was reached.
Findings: The thematic analysis revealed three main categories: (1) the use of intelligent algorithms in analyzing and predicting employee performance, (2) the digital transformation of performance evaluation processes using behavioral data, and (3) the development of innovative performance indicators and models emphasizing algorithmic fairness, personalized feedback, and strategic alignment. These categories were further divided into 16 subthemes and over 80 open codes.
Conclusion: Findings highlight that intelligent algorithms can enhance the accuracy, transparency, and efficiency of performance evaluation systems. However, ethical considerations, algorithmic transparency, and employee training are crucial for successful implementation. Organizations are encouraged to redesign their performance appraisal systems using behavioral analytics and machine learning grounded in fairness and data-driven decision-making.
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