scholarly journals The effects of predictor method factors on selection outcomes: A modular approach to personnel selection procedures.

2017 ◽  
Vol 102 (1) ◽  
pp. 43-66 ◽  
Author(s):  
Filip Lievens ◽  
Paul R. Sackett

1984 ◽  
Vol 13 (4) ◽  
pp. 409-415 ◽  
Author(s):  
Charles B. Schultz

Tests and other personnel selection procedures help in selecting good employees. Test utility studies show the value of selection for increasing productivity. Information about a test and about productivity of the workers can be used to quantify the gain that can be achieved by selecting the better workers. Increasing productivity by $5,000 per year per hire is not too much to expect.



2006 ◽  
Vol 19 (3) ◽  
pp. 219-251 ◽  
Author(s):  
Lonneke A. L. de Meijer ◽  
Marise Ph. Born ◽  
Gert Terlouw ◽  
Henk T. van der Molen


2013 ◽  
Vol 98 (2) ◽  
pp. 326-341 ◽  
Author(s):  
Anne Jansen ◽  
Klaus G. Melchers ◽  
Filip Lievens ◽  
Martin Kleinmann ◽  
Michael Brändli ◽  
...  




2010 ◽  
Vol 18 (1) ◽  
pp. 17-27 ◽  
Author(s):  
Cornelius J. König ◽  
Ute-Christine Klehe ◽  
Matthias Berchtold ◽  
Martin Kleinmann


2021 ◽  
Vol 12 ◽  
Author(s):  
Jessica Schick ◽  
Sebastian Fischer

Recently, with the increase in technological capabilities and the need to reduce bias in candidate selection processes, artificial intelligence (AI)-based selection procedures have been on the rise. However, the literature indicates that candidate reactions to a selection process need to be considered by organizations that compete for employees. In this study, we investigate reactions to AI-based selection procedures in a three-dimensional vignette study among young adults in Germany. By investigating the effects of the dimensions of AI complexity, intangibility, and reliability on the perceived quality of assessment of potential candidates, we found that AI complexity and intangibility impact the perceived quality of assessment negatively when the candidates’ knowledge, strengths, and weaknesses should be assessed. We also found interactive relationships of all three dimensions for the assessment of motivation. In sum, results indicate that candidates are skeptical toward the assessment quality of AI-intense selection processes, especially if these assess complex assessment criteria such as personality or a job performance forecast. Hence, organizations need to be careful when implementing AI-based selection procedures. HR implications are made on the basis of these results to cope with negative candidate perceptions.



2012 ◽  
Vol 28 (2) ◽  
Author(s):  
Eline Nievers ◽  
Iris Andriessen ◽  
Laila Faulk

Why employers prefer Mark to Mohammed Why employers prefer Mark to Mohammed In personnel selection procedures, Dutch employers prefer Dutch candidates to those with a non-western minority background with same educational level, age and work experience. We conducted 106 in-depth interviews to examine why employers and other personnel selectors in the Dutch labour market prefer Dutch candidates. Results show that employers associate workers of Moroccan and of Antillean descent with employment risks, such as trouble on the work floor. As the consequence, these candidates are put in the back of the labour queue. Employers have more positive associations with people from a Surinamese or Turkish background, but, nevertheless, prefer candidates from a Dutch background. Dutch candidates are more familiar and therefore the safer choice. We conclude that the preference for employees with a Dutch ethnic background is the result of risk avoiding behavior, based upon personal experience and images of ethnicity in media and society.



1978 ◽  
Author(s):  
James L. Raney ◽  
Paul J. Duffy ◽  
Arthur C. F. Gilbert


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