An employee retention model using organizational network analysis for voluntary turnover

Area of Science:

• Organizational Behavior
• Social Network Analysis
• Human Resource Management

Background:

• Employee turnover is a significant concern, impacting organizational stability and performance.
• Traditional turnover theories often overlook the influence of social networks within organizations.
• A comprehensive review linking social network analysis to employee retention is needed.

Purpose of the Study:

• To review current research on employee social network analysis and turnover.
• To propose a conceptual model for employee retention based on network constructs.
• To identify key network factors influencing quit propensity.

Main Methods:

• Systematic literature review of 30 papers on voluntary turnover and social network constructs.
• Analysis of network position, centrality measures, network type, and snowball effect.
• Development of a conceptual model for predicting employee turnover.

Main Results:

• Central network position does not always correlate with increased turnover.
• Eigenvector centrality, structural holes, and K-shell are significant predictors of turnover.
• Snowball turnover is amplified in negative employee sentiment, low group efficacy, and poor group values.

Conclusions:

• Social network analysis provides valuable insights into predicting and mitigating employee turnover.
• Understanding network structures can help identify at-risk employees and develop targeted retention strategies.
• The conceptual model offers a framework for proactive retention management.