... machine learning framework. Multiple predictive models are implemented and evaluated, including linear regression, decision trees, ensemble methods (Random Forest, Gradient Boosting, XGBoost), support vector machines, k-nearest neighbors and artificial neural networks, to compare their ability...

..., Switzerland and Austria, including human resource (HR) records, employee satisfaction surveys and performance data. A machine learning model was used to predict employee turnover. Findings The results show that turnover prediction is most accurate when performance data is included, with an accuracy score...

...Adil Benabou; Fatima Touhami Purpose This study aims to examine employee turnover using machine learning models, focusing on both predictive performance and practical application. Its aim is to identify the main factors influencing turnover and evaluate the effectiveness of classification...

...Aakanksha Uppal; Yashmita Awasthi; Anubha Srivastava Purpose This study focuses on enhancing the accuracy and efficiency of employee performance prediction to enhance decision making and improve organisational productivity. By introducing advance machine learning (ML) techniques, this study aims...

...Dee Birnbaum; Mark Somers Purpose The purpose of this paper is to explore parallels between scientific management and the new scientific management to gain insight into applications of machine learning and artificial intelligence (AI) to human resource management and employee assessment. Design...

... the recruitment costs and the time taken to extend an offer to the right talent, the HR function has to inevitably adopt data analytics and machine learning for employee selection. This paper aims to propose the “Quality of Hire” concept for employee selection using the person-environment (P-E) fit theory...

...Youngkeun Choi; Jae Won Choi Purpose Job involvement can be linked with important work outcomes. One way for organizations to increase job involvement is to use machine learning technology to predict employees’ job involvement, so that their leaders of human resource (HR) management can take...