Is Job Satisfaction of Social Sciences Scholars Predicted by Emotions, Job Performance, Work Events, and Workplace Features? A Demonstration of a Data-Driven Policy-Making Approach

Abstract

This study, using affective events theory (AET) as a framework of reference, focuses on job satisfaction and job performance of academics with social sciences backgrounds working in Malaysian universities and colleges. More specifically, it aims at examining the influence of workplace features such as involvement, workload, and welfare on job satisfaction through role conflict, as a work event, and positive affect. In addition, the mediating role of job performance on the relationship between positive affect and job satisfaction was considered. Data were collected from 1000 academics via an online platform, and partial least squares structural equation modeling (PLS-SEM) method was adopted for data analysis. While all the four hypotheses were empirically supported, the results highlighted the considerable role of workload in increasing role conflict and the negative impact of role conflict on positive affect. We extended the results using finite mixture partial least squares (FIMIX-PLS) segmentation method, as a recommended PLS robustness check, and importance-performance map analysis (IPMA), to identify the major areas of improvement to be addressed by management activities on the grounds of the proposed model. Implications, limitations, and recommendations were discussed too.