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December 31, 2025Korea Association of Local Administration

A Study on Factors Influencing Turnover Intention - Applying Machine Learning and Explainable Artificial Intelligence -

Jungho Park Min-Han Kim

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Key Points

Turnover intention is significantly impacted by organizational commitment and perceived compensation fairness.
Analysis of 6,444 responses revealed nonlinear effects of job ambiguity on turnover intention, which traditional methods missed.
Machine learning, specifically CatBoost, and SHAP analysis were employed to understand complex interactions among variables.
Improving transparency in compensation systems and clarifying job roles may help reduce turnover in the public sector.

Implication

Explores factors affecting turnover intention in public employees, suggesting deeper analysis is needed for effective management.

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Cite This Study

Park et al. (2025) studied this question.

synapsesocial.com/papers/69a75c3ac6e9836116a24e00 https://doi.org/10.32427/klar.2025.22.3.169

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