Crossref Citations
This article has been cited by the following publications. This list is generated based on data provided by
Crossref.
Stanek, Kevin C.
2019.
Starting with the basics: Getting turnover rates right.
Industrial and Organizational Psychology,
Vol. 12,
Issue. 3,
p.
314.
McCloy, Rodney A.
Purl, Justin D.
and
Banjanovic, Erin S.
2019.
Turnover modeling and event history analysis.
Industrial and Organizational Psychology,
Vol. 12,
Issue. 3,
p.
320.
Putka, Dan J.
McCloy, Rodney A.
Van Iddekinge, Chad H.
and
Le, Huy
2019.
The other published literature: Attrition modeling in the U.S. military as a bridge between turnover science and practice.
Industrial and Organizational Psychology,
Vol. 12,
Issue. 3,
p.
334.
Woo, Sang Eun
2019.
Big data opportunities for advancing turnover theory: A case for inductive and abductive research.
Industrial and Organizational Psychology,
Vol. 12,
Issue. 3,
p.
330.
Obenauer, William G.
2019.
Are all voluntary attritions created equally? Understanding the need to incorporate employee diversity into attrition modeling.
Industrial and Organizational Psychology,
Vol. 12,
Issue. 3,
p.
302.
Gibson, Carter
Koenig, Nick
Griffith, Jennifer
and
Hardy, Jay H.
2019.
Selecting for retention: Understanding turnover prehire.
Industrial and Organizational Psychology,
Vol. 12,
Issue. 3,
p.
338.
Castille, Christopher M.
and
Castille, Ann-Marie R.
2019.
Disparate treatment and adverse impact in applied attrition modeling.
Industrial and Organizational Psychology,
Vol. 12,
Issue. 3,
p.
310.
Rothausen, Teresa J.
and
Henderson, Kevin E.
2019.
Two messages from the other side of the turnover coin: “Here to stay or go?” and “Should I stay or should I go?”.
Industrial and Organizational Psychology,
Vol. 12,
Issue. 3,
p.
306.
Garcia‐Alcaraz, Cristian
Roesch, Scott C.
Calhoun, Elizabeth
Wightman, Patrick
Mohan, Prashanthinie
Battaglia, Tracy A.
Cobian Aguilar, Rosa
Valverde, Patricia A.
and
Wells, Kristen J.
2022.
Exploring classes of cancer patient navigators and determinants of navigator role retention.
Cancer,
Vol. 128,
Issue. S13,
p.
2590.
Sarpong, David
Maclean, Mairi
and
Hassan, Wuraola
2022.
A Notsie narrative perspective on turnover in the UK financial services industry.
Africa Journal of Management,
Vol. 8,
Issue. 4,
p.
425.
Ballesteros-Leiva, Felix
St-Onge, Sylvie
and
Dufour, Marie-Ève
2023.
Furloughed Employees’ Voluntary Turnover: The Role of Procedural Justice, Job Insecurity, and Job Embeddedness.
International Journal of Environmental Research and Public Health,
Vol. 20,
Issue. 9,
p.
5664.
Zhang, Nan
Wang, Mo
Xu, Heng
Koenig, Nick
Hickman, Louis
Kuruzovich, Jason
Ng, Vincent
Arhin, Kofi
Wilson, Danielle
Song, Q. Chelsea
Tang, Chen
Alexander, Leo
and
Kim, Yesuel
2023.
Reducing subgroup differences in personnel selection through the application of machine learning.
Personnel Psychology,
Vol. 76,
Issue. 4,
p.
1125.
Yang, Yumei
Thu Hue, Hannah Mai
and
Takeda, Sachiko
2024.
Turnover intention among Vietnamese millennials in the workplace.
Evidence-based HRM: a Global Forum for Empirical Scholarship,
Vol. 12,
Issue. 3,
p.
592.
Chang, Yu-Ling
and
Ke, Jie
2024.
Socially Responsible Artificial Intelligence Empowered People Analytics: A Novel Framework Towards Sustainability.
Human Resource Development Review,
Vol. 23,
Issue. 1,
p.
88.
Zhang, Chunyang
and
Han, Wenjing
2024.
Ensembles of decision trees and gradient-based learning for employee turnover rate prediction.
PeerJ Computer Science,
Vol. 10,
Issue. ,
p.
e2387.
Gričnik, Ana Marija
Mulej, Matjaž
and
Žižek, Simona Šarotar
2024.
Balancing Human Rights, Social Responsibility, and Digital Ethics.
p.
82.
Latorre, Paolo
López-Ospina, Héctor
Maldonado, Sebastián
Guevara, C. Angelo
and
Pérez, Juan
2024.
Designing employee benefits to optimize turnover: A prescriptive analytics approach.
Computers & Industrial Engineering,
Vol. 197,
Issue. ,
p.
110582.
Speer, Andrew B.
2024.
Empirical attrition modelling and discrimination: Balancing validity and group differences.
Human Resource Management Journal,
Vol. 34,
Issue. 1,
p.
1.