Improving measurement and prediction in personnel selection through the application of machine learning
Year of publication: |
2023
|
---|---|
Authors: | Koenig, Nick ; Tonidandel, Scott ; Thompson, Isaac ; Albritton, Betsy ; Koohifar, Farshad ; Yankov, Georgi ; Speer, Andrew ; Hardy, Jay H. ; Gibson, Carter ; Frost, Chris ; Liu, Mengqiao ; McNeney, Denver ; Capman, John ; Lowery, Shane ; Kitching, Matthew ; Nimbkar, Anjali ; Boyce, Anthony ; Sun, Tianjun ; Guo, Feng ; Min, Hanyi ; Zhang, Bo ; Lebanoff, Logan ; Phillips, Henry ; Newton, Charles |
Published in: |
Personnel psychology : a journal of applied research. - Malden, Mass. [u.a.] : Wiley-Blackwell, ISSN 1744-6570, ZDB-ID 2066879-X. - Vol. 76.2023, 4, p. 1061-1123
|
Subject: | artificial intelligence/big data/machine learning | selection-methods | selection-validation | Künstliche Intelligenz | Artificial intelligence | Lernprozess | Learning process | Personalauswahl | Personnel selection | Prognoseverfahren | Forecasting model |
-
Campion, Michael A., (2023)
-
Personnel selection : a review of ways to maximize validity, diversity, and the applicant experience
Van Iddekinge, Chad H., (2023)
-
Quality of hire : expanding the multi-level fit employee selection using machine learning
Shet, Sateesh, (2022)
- More ...
-
Guo, Feng, (2021)
-
Guo, Feng, (2024)
-
Wisdom from the crowd : can recommender systems predict employee turnover and its destinations?
Min, Hanyi, (2024)
- More ...