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August 12, 2026Open Access

Predicting Employee Turnover for Effective Retention Using Hr Analytics

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Authors

MMM. MaheswariVSV. T. ShailashriPRP. Radha

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Overview

Randomized trial reveals HR analytics' role in forecasting turnover and enhancing employee retention.

Key Points

  • The goal is to develop a predictive model for employee turnover using HR analytics, focusing on key factors that influence retention.
  • Quantitative cross-sectional design with primary data obtained from 200 individuals across various sectors.
  • Structured questionnaire with 52 measurement items spanning 13 latent components.
  • Utilization of statistical methods including confirmatory factor analysis, and structural equation modelling for data analysis.
  • The structural model indicates that employee engagement, job satisfaction, and leadership support positively affect retention.
  • Burnout negatively impacts retention, increasing the intention to leave the organization.
  • The model exhibits satisfactory reliability and construct validity, reinforcing the importance of HR analytics in decision-making.

Cite This Study

Maheswari et al. (2026) studied this question.

synapsesocial.com/papers/6a7c3d1906a85aed514b7cc8https://doi.org/10.5281/zenodo.21871315
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1PREDICTING EMPLOYEE TURNOVER FOR EFFECTIVE RETENTION USING HR ANALYTICS2026
  2. 2SUSTAINABLE WORKFORCE RETENTION THROUGH HR ANALYTICS AND PREDICTIVE MODELLING2026
  3. 3Predicting Employee Turnover Through Advanced Hr Analytics: Implications For Engagement Strategies2024 · 2 citations
  4. 4Predictive HR Analytics to Optimize Decision-Making Processes and Enhance Workforce Performance2024 · 6 citations
  5. 5AN INTEGRATED HR ANALYTICS MODEL FOR EMPLOYEE MENTAL HEALTH PREDICTION AND RETENTION2026