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Selecting for retention: Understanding turnover prehire

Published online by Cambridge University Press:  13 November 2019

Carter Gibson ,
Nick Koenig ,
Jennifer Griffith  and
Jay H. Hardy III
Carter Gibson*
Affiliation:
Modern Hire
Nick Koenig
Affiliation:
Modern Hire
Jennifer Griffith
Affiliation:
University of New Hampshire
Jay H. Hardy III
Affiliation:
Oregon State University
*
*Corresponding author. Email: carter.gibson@shakercg.com
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Type
Commentaries
Information
Industrial and Organizational Psychology , Volume 12 , Issue 3 , September 2019 , pp. 338 - 341
Copyright
© Society for Industrial and Organizational Psychology 2019 

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References

Austin, J. T., & Villanova, P. (1992). The criterion problem: 1917–1992. Journal of Applied Psychology, 77(6), 836–874.CrossRefGoogle Scholar
Barrick, M. K., & Mount, M. K. (1996). Effects of impression management and self-deception on the predictive validity of personality constructs. Journal of Applied Psychology, 81(3), 261–272.CrossRefGoogle ScholarPubMed
Doshi-Velez, F., & Kim, B. (2017) Towards a rigorous science of interpretable machine learning. Cornell University. arXiv:1702.08608v2.Google Scholar
Holtom, B. C., Mitchell, T. R., Lee, T. W., & Eberly, M. B. (2008). Turnover and retention research: A glance at the past, a closer review of the present, and a venture into the future. Academy of Management Annals, 2(1), 231–274.CrossRefGoogle Scholar
Porter, C., Holtom, B., Maertz, C., Allen, D., Hausknecht, J., & Woo, S. (2019, April). What’s next for turnover research and practice? Where we are and where we should go. Panel presented at the 34th Annual Conference of the Society for Industrial and Organizational Psychology, Washington, DC.Google Scholar
Ribeiro, M. T., Singh, S., & Guestrin, C. (2016, August). Why should I trust you? Explaining the predictions of any classifier. Presented at the 22nd Annual International Conference on Knowledge Discovery and Data Mining, San Francisco, CA.CrossRefGoogle Scholar
Speer, A. B., Dutta, S., Chen, M., & Trussell, G. (2019). Here to stay or go? Connecting turnover research to applied attrition modeling. Industrial and Organizational Psychology: Perspectives on Science and Practice, 12(3), 272–296.CrossRefGoogle Scholar