Machine Learning Analysis of High-Performance Work Systems: The Role of Employee Engagement and Growth Mindset

Abstract

This paper reviews High-Performance Work Systems (HPWS), employee engagement, and job performance with a focus on the role of growth mindset as a moderator. Using machine learning algorithms Decision Trees, Random Forest, and Support Vector Machines (SVM), we extracted 217 employees working at software companies in Lahore, Pakistan. The findings of this study point to the interaction between HPWS and both job performance as well as engagement, which is significantly moderated by a growth mindset. This study contributes to the solution of the research question and contributes to the numerous area of research and modern data Driven human resource management for better performance of the workforce and overall improved organizational results.