Meta-Analytic Review of Employee Turnover as a Predictor of Firm Performance


Julie I. Hancock, David G. Allen, University of Memphis, Frank A. Bosco, Marshall University, Karen R. McDaniel, Arkansas State University, and Charles A. Pierce, University of Memphis, published “Meta-Analytic Review of Employee Turnover as a Predictor of Firm Performance” on October 24th, 2011 in the Journal of Management’s OnlineFirst section. To read other OnlineFirst articles, please click here.

The abstract:

Previous research has primarily revealed a negative relationship between collective employee turnover and organizational performance. However, this research also suggests underlying complexity in the relationship. To clarify the nature of this relationship, the authors conduct a meta-analytic review in which they test and provide support for a portion of Hausknecht and Trevor’s model of collective turnover. The authors’ meta-analysis includes 48 independent samples reporting 157 effect size estimates (N = 24,943), tests six hypothesized moderator variables, and provides path analyses to test alternative conceptualizations of the turnover– organizational performance relationship. Results indicate that the mean corrected correlation between turnover and organizational performance is –.03, but this relationship is moderated by several important variables. For example, the relationship is stronger in manufacturing and transportation industries (–.07), for managerial employees (–.08), in midsize organizations (–.07), in samples from labor market economies (–.05), and when organizational performance is operationalized in terms of customer service (–.10) or quality and safety (–.12) metrics.In addition, proximal performance outcomes mediate relationships with financial performance. The authors discuss implications of their results for theory and practice and provide directions for future research.

If you would like to learn more about the Journal of Management, please follow this link.

Are you interested in receiving email alerts whenever a new article or issue becomes available online? Then click here!

Bookmark and Share

Tags: , ,

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s

%d bloggers like this: