Job satisfaction as mediator between job characteristics, personality traits, work engagement and voluntary turnover intention: a conceptual paper

• Main Authors: Fong, Wong Yee, Syed Abu Bakar, Syarifah Mastura, Hoo, Wong Chee, Alwie, Aryaty
• Format: Article
• Published: Human Resource Management Academic Research Society 2022
• Online Access: http://psasir.upm.edu.my/id/eprint/102027/; https://hrmars.com/index.php/IJAREMS/article/view/13243/Job-Satisfaction-as-Mediator-between-Job-Characteristics-Personality-Traits-Work-Engagement-and-Voluntary-Turnover-Intention-A-Conceptual-Paper

In today's workplace, the rate of turnover has risen. Employee turnover is divided into two categories, which defined as voluntary turnover and involuntary turnover. Due to the rising voluntary turnover rate, organizations are confronted with difficulties, since the issue of voluntary turnover has become a major concern for businesses all over the world. Thus, this study focus on investigating voluntary turnover and predicting factors which influence voluntary turnover intentions with job satisfaction as the mediator. Besides, this paper introduces a new conceptual framework to better understanding about voluntary turnover intentions. Most studies on turnover intention (dependent variable) focus on establishing the direct relationship between the independent variables (predictors) and the dependent variable. To date, there is not been sufficient research that examine the “indirect” relationship between the predictors and the dependent variable. Hence, the current study attempts to fill the gap by using job satisfaction as a mediator to determine whether an indirect relationship exist, which can have enhanced our understanding between the predictors and the dependent variable. The present study also fulfilled the gaps in adopting different factor models in predicting job satisfaction and voluntary turnover other than personality traits, which are job characteristics model and work engagement, as recommended by previous researcher that follow up analysis could investigate whether different factor models have greater goodness of fit in different groups. The present study adopted Partial Least Squares-Structural Equation Modeling (PLS-SEM) as the research method for data analysing in this paper, the expected output in this study is to determine whether the hypotheses tested are accepted or rejected, and the significance of output in this study is to contribute to literature on factors that can reduce voluntary turnover intentions.