Moscow, Russian Federation
The aim of this study is to analyze the transformation of personnel motivation systems in the digital economy and develop a conceptual model for managing employee well-being using HR solutions. The methodological basis of the study is a systems analysis of leading domestic and international digital talent management platforms operating between 2023 and 2025. Herzberg's two-factor theory and Vroom's expectancy theory, interpreted in the context of the digital environment, serve as the theoretical foundation. Methods of classification, risk forecasting, and conceptual modeling are applied. The study identified key dysfunctions of the technocratic approach to digitalization (algorithmic bias, labor imbalance, and digital burnout). A "Digital Well-Being Contour" model is proposed, describing an algorithm for converting data from performance monitoring systems into personalized proactive personnel support interventions. A rationale for shifting from reactive retention models to predictive employee experience management based on integrated big data analysis is provided. It is proven that the effectiveness of digital motivation systems is achieved only by shifting the focus from KPI monitoring to supporting employee autonomy and competence. The proposed algorithm for implementing human-centric HR technologies and recommendations for reducing digital pressure can be used by HR department managers to minimize HR risks and increase employee engagement in the face of labor market shortages.
digital economy, employee motivation, employee well-being, algorithmic management, gamification, burnout prevention, artificial intelligence in HR, human resources management
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