Yusril Mahendra
Trunojoyo University Madura

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Analysis of Training, Motivation, and Discipline Configuration as Predictors of Employee Performance: An Empirical Study and Synthesis of the Systematic Literature Review (SLR) Lintang Praja Musti; M. Hotib Jailani; Bangbang Adi Satrio; Yusril Mahendra
Journal of Transformational Human Resource Management Vol. 1 No. 2: December 2025
Publisher : PT. Sativa Publishing Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64118/jthrm.v1i2.102

Abstract

This study examines the configuration of training, motivation, and work discipline as predictors of employee performance through an integrated hybrid approach combining empirical analysis and a Systematic Literature Review (SLR). The empirical component employs a quantitative non-experimental design using purposive sampling and Likert-scale questionnaires to analyze the effects of motivation and discipline on employee performance. Regression results indicate that both motivation and discipline significantly and positively influence performance, and their combined effect is stronger than their individual contributions. Complementing these findings, the SLR synthesizes research from 2019-2024 sourced from open-access scholarly databases, revealing consistent evidence that training enhances employee capability, motivation drives productive behavior, and discipline ensures behavioral consistency in achieving organizational standards. The integration of empirical and SLR findings produces a comprehensive performance model grounded in three key dimensions: ability (shaped by training), motivation (driving willingness to work), and behavioral control (maintained through discipline). This study contributes theoretically by offering an integrative predictor framework and practically by providing recommendations for human resource managers to design aligned interventions in training, motivation systems, and discipline enforcement. Future research is suggested to incorporate mediating or moderating factors such as leadership, organizational culture, and digital learning environments to expand the proposed model.