The Predictive Machine Learning Model towards Effect of Human Resources Management Practices and Job Performances Among Academic Librarians in Malaysia

Abstract

Job performance is a vital component of organizational success, directly impacting productivity, efficiency, and overall workplace effectiveness. For academic librarians, job performance is especially crucial in delivering high-quality library services, supporting academic programs, and fostering a conducive learning environment. However, there is a lack of literature on job performance in the context of academic librarianship in Malaysia. By conducting a thorough literature review and utilizing empirical research, this study aims to provide insights into the factors influencing job performance and strategies to enhance the job performance of academic librarians. In addition, the target population was the entire librarian’s public university libraries in Malaysia with 20 public university libraries involved. Primary data for 287 respondents of academic library was analysing using multiple linear regression analysis (MLR). The software used for analysing is Statistical Package for the Social Sciences (SPSS). In a conclusion, the findings of this study found many factors contribute to job performance of academic library. This study provides recommendations to ultimately improving job performance among academic librarians in Malaysia.