This study presents an innovative methodology to predict employee turnover by integrating Artificial Neural Networks (ANN) with clustering techniques. We focus on hyperparameter tuning with various input parameters to obtain optimal ANN models. By segmenting data, the study identifies critical...

This study proposes an integrated Decision Support System (DSS) with Multi-Criteria Decision-Making (MCDM) to evaluate trainers in organizations and choose the most suitable one(s) for a training program. The clustering stage determines the most appropriate number of trainees to be assigned to a...

Employees are often more likely to use social media for job searching, which sometimes causes withdrawal behaviour. This study proposes an ensemble learning model for predicting the intention to quit (IQ) based on selected features, such as job Involvement (JI), organizational commitment (OC),...

"The landscape of human resource management (HRM) is evolving more rapidly than ever. Human resource managers are facing new and previously unimagined challenges ranging from the rise of artificial intelligence to the shift to work-from-home arrangements. As the HR profession changes, research...

"Elgar Research Agendas outline the future of research in a given area. Leading scholars are given the space to explore their subject in provocative ways, and map out the potential directions of travel. They are relevant but also visionary. This Research Agenda explores the crucial role of HR...