Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/287972 
Erscheinungsjahr: 
2023
Quellenangabe: 
[Journal:] International Journal of Selection and Assessment [ISSN:] 1468-2389 [Volume:] 31 [Issue:] 2 [Publisher:] Wiley [Place:] Hoboken, NJ [Year:] 2023 [Pages:] 252-266
Verlag: 
Wiley, Hoboken, NJ
Zusammenfassung: 
Algorithms might prevent prejudices and increase objectivity in personnel selection decisions, but they have also been accused of being biased. We question whether algorithm‐based decision‐making or providing justifying information about the decision‐maker (here: to prevent biases and prejudices and to make more objective decisions) helps organizations to attract a diverse workforce. In two experimental studies in which participants go through a digital interview, we find support for the overall negative effects of algorithms on fairness perceptions and organizational attractiveness. However, applicants with discrimination experiences tend to view algorithm‐based decisions more positively than applicants without such experiences. We do not find evidence that providing justifying information affects applicants—regardless of whether they have experienced discrimination or not.
Schlagwörter: 
diversity and inclusion
fairness
organizational justice
selection
Persistent Identifier der Erstveröffentlichung: 
Creative-Commons-Lizenz: 
cc-by-nc-nd Logo
Dokumentart: 
Article
Dokumentversion: 
Published Version

Datei(en):
Datei
Größe
955.13 kB





Publikationen in EconStor sind urheberrechtlich geschützt.