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  6. Collective Data on Collective Turnover: What Factors Most Affect Turnover Rates?

Collective Data on Collective Turnover: What Factors Most Affect Turnover Rates?

File(s)
No4_14_ResearchLink_Hausknecht_110114_pub.pdf (1.11 MB)
Permanent Link(s)
https://hdl.handle.net/1813/73698
Collections
CAHRS ResearchLink
Author
Hausknecht, John
Abstract

Overview and Key Findings: Numerous studies of the causes and consequences of organizational turnover that is, turnover rates rather than an individual's decision to stay or leave—have appeared in the last century. Using meta-analysis (a quantitative methodology for summarizing results across studies), Cornell researchers (Ph.D. students Angela Heavey and Jake Holwerda, along with faculty member John Hausknecht) analyzed data from 82 published studies and found: Investments in high-commitment HR systems, emphasis on internal mobility, and provision of firm-specific training were associated with lower turnover rates; Positive attitudes toward the job, supervisors, and the organization were associated with lower turnover, but effects were weaker than those found for high-commitment HR systems; Expectation-enhancing practices such as electronic monitoring and job routinization forecasted higher departure rates; similarly, greater availability o f alternatives in the labor market signaled higher turnover; Lower turnover was associated with certain employee characteristics— turnover dropped as the average age and average tenure of employees increased (or, turnover was highest among younger and less tenured workers); There was robust evidence showing the damaging effects of increased turnover on multiple HR and business outcomes including customer satisfaction, production efficiency, sales, financial performance, error rates, and absenteeism; and Many of the causes and consequences of turnover are well-documented: Organizations can actively reduce, maintain, or increase turnover rates for specific employee groups with adequate attention and resources.

Date Issued
2014-11-01
Keywords
analytics
•
turnover
•
causes of turnover
•
retention
•
electronic monitoring
•
evidence-based management
•
human resources metrics
•
human resources
Type
article

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