Relationships between employee retention factors and attitudinal antecedents of voluntary turnover : an extended structural equation modelling approach

Abstract

ORIENTATION : Gaining a full understanding of employee retention (ER) management requires studying multiple retention factors in tandem. Many empirical studies that use conventional structural equation modelling (SEM) include only a single retention factor or a subset of factors, making it impossible to assess the relative embeddedness of these factors in ER practices. RESEARCH PURPOSE : The purpose was to gain a better understanding of the relationships between multiple ER factors and attitudinal antecedents of voluntary turnover. MOTIVATION FOR THE STUDY : This research aimed to address the need for more comprehensive latent multivariate approaches to studying ER by using extended SEM techniques. RESEARCH APPROACH/DESIGN AND METHOD : The researchers used a cross-sectional survey design and obtained a convenience sample of 272 skilled employees from public and private organisations. The first stage of the study entailed using the exploratory structural equation model (ESEM) within the confirmatory factor analysis to test a model measuring ER factors. The second stage involved using plausible values for latent variables in an SEM analysis of the relationship between attitudinal antecedents of voluntary turnover (i.e. affective commitment, job satisfaction and turnover intention) and ER factors. MAIN FINDINGS : The findings indicated that affective commitment and job satisfaction differentially mediated the relationship between ER factors and turnover intention, partially supporting existing research and providing new insights into ER. PRACTICAL/MANAGERIAL IMPLICATIONS : This study suggested that in order for management to effectively manage ER, they must understand the relative embeddedness of a range of ER factors and prioritise motivational and empowerment-enhancing bundles of practice (e.g. compensation, job characteristics, work–life balance and career opportunities) to impact on attitudinal antecedents of voluntary turnover. CONTRIBUTION/VALUE-ADD : This study indicated that the use of extended SEM modelling techniques could provide valuable insights into the multivariate relationships between ER factors and attitudinal antecedents of voluntary turnover.