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Personnel Psychology – Winter 2023 Special Issue on Machine Learning

  • 1.  Personnel Psychology – Winter 2023 Special Issue on Machine Learning

    Posted 11-26-2023 10:35

    Dear Careers Division colleagues,

    I am pleased to announce that the Winter 2023 issue of Personnel Psychology is now published.  This issue has our Special Issue on Machine Learning Applications to Personnel Selection. The second part of the Machine Learning, AI, and Big Data special issue will be in Spring 2024.

    Thanks to the effort of our Guest Editors Michael Campion and Emily Campion, this special issue has a great collection of five articles. They have important implications for future research, application, and policies on AI and Machine Learning. 

    In addition, there are two regular issue articles (ideological contract breach and mindful work relationships), this year's award announcement (Best Article and Best Reviewer Awards; presented to winners during the AOM conference), and a thank-you note to our ad-hoc reviewers. All these articles are Open Access. Enjoy this issue of Personnel Psychology!

    Early View articles and content alert sign-ups are available on this page.

    Special Issue Articles: Machine Learning Applications to Personnel Selection

    Machine learning applications to personnel selection: Current illustrations, lessons learned, and future research (linkOpen Access

    Michael A. Campion,  Emily D. Campion

    The AI-IP: Minimizing the guesswork of personality scale item development through artificial intelligence (linkOpen Access

    Ivan Hernandez,  Weiwen Nie

    A simulation of the impacts of machine learning to combine psychometric employee selection system predictors on performance prediction, adverse impact, and number of dropped predictors (linkOpen Access

    Richard N. Landers,  Elena M. Auer,  Lily Dunk,  Markus Langer,  Khue N. Tran

    Improving measurement and prediction in personnel selection through the application of machine learning (linkOpen Access

    Nick Koenig,  Scott Tonidandel,  Isaac Thompson,  Betsy Albritton,  Farshad Koohifar,  Georgi Yankov,  Andrew Speer,  Jay H. Hardy III,  Carter Gibson,  Chris Frost,  Mengqiao Liu,  Denver McNeney,  John Capman,  Shane Lowery,  Matthew Kitching,  Anjali Nimbkar,  Anthony Boyce,  Tianjun Sun,  Feng Guo,  Hanyi Min,  Bo Zhang,  Logan Lebanoff,  Henry Phillips,  Charles Newton

    Reducing subgroup differences in personnel selection through the application of machine learning (linkOpen Access

    Nan Zhang,  Mo Wang,  Heng Xu,  Nick Koenig,  Louis Hickman,  Jason Kuruzovich,  Vincent Ng,  Kofi Arhin,  Danielle Wilson,  Q. Chelsea Song,  Chen Tang,  Leo Alexander III,  Yesuel Kim

    Regular Issue Articles

    Serving the cause when my organization does not: A self-affirmation model of employees' compensatory responses to ideological contract breach (linkOpen Access

    Hong Deng,  Jacqueline Coyle-Shapiro,  Yanting Zhu,  Chia-huei Wu

    A mindful relating framework for understanding the trajectory of work relationships (linkOpen Access

    Christopher S. Reina,  Maura J. Mills,  Dana McDaniel Sumpter

    Book Reviews

    The power of experiments: Decision making in a data-driven world By Michael Luca, Max H. Bazerman, Cambridge, Massachusetts, USA: The MIT Press, 2021, 232 pp, $19.95, paperback (link)

    Egor Bronnikov

    Be Data Literate: The Data Literacy Skills Everyone Needs to Succeed By Jordan Morrow, Kogan Page, 2021, 215 pp, $15.99 (link)

    Brad Ward

    Flexible working practices and approaches (link)

    Joseph J. Mazzola

    Editorial

    Personnel Psychology Awards (link)

    List of ad-hoc reviewers for Personnel Psychology (link)



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    Zhen Zhang, Ph.D.
    Editor, Personnel Psychology
    Edwin L. Cox School of Business
    Southern Methodist University
    zhenzhang@smu.edu
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