An employee retention model using organizational network analysis for voluntary turnover

Contemporary research of employee social network analysis has grown far beyond the conventional wisdom of network and turnover theory; however, what is missing is a comprehensive review highlighting new perspectives and network constructs from a retention viewpoint. Since turnover is a concurrent component of retention, the analysis of the factors of quit propensity can result in a pre-emptive strategy for retention. This paper aims to capture the current state of the field and proposes a conceptual model for retention by exploring network position, centrality measures, network type, and the snowball effect. We identified 30 papers exploring voluntary turnover in social network constructs. Findings show that central network position is not always associated with negative turnover. Eigenvector, structural holes, and K-shell also prove to be a strong predictor of turnover. The snowball turnover of employees in similar network positions is pronounced in scenarios where employee sentiment is negative with poor group efficacy, entrepreneurship, and group values. This paper focuses on several themes to coalesce different determinants of an organizational network to demonstrate how social network theory has evolved to predict employee turnover. The resulting conceptual model suggests how to identify star performers and propose retention strategies.