Dokument: Four essays on reactions to algorithmic decision-making and their boundary conditions in organizational contexts

Titel:	Four essays on reactions to algorithmic decision-making and their boundary conditions in organizational contexts
URL für Lesezeichen:	https://docserv.uni-duesseldorf.de/servlets/DocumentServlet?id=71917
URN (NBN):	urn:nbn:de:hbz:061-20260122-124610-7
Kollektion:	Dissertationen
Sprache:	Englisch
Dokumententyp:	Wissenschaftliche Abschlussarbeiten » Dissertation
Medientyp:	Text
Autor:	Moritz, Josephine Mago [Autor]
Dateien:	[Dateien anzeigen] Adobe PDF [Details] 3,72 MB in einer Datei [ZIP-Datei erzeugen] Dateien vom 16.01.2026 / geändert 16.01.2026
Beitragende:	Wehner, Marius Claus [Gutachter] Engelen, Andreas [Gutachter]
Dewey Dezimal-Klassifikation:	300 Sozialwissenschaften, Soziologie » 330 Wirtschaft
Beschreibung:	Algorithmic decision-making (ADM) is increasingly used in organizational contexts. While organizations implement ADM with the expectation of increasing efficiency, accuracy, and consistency, these benefits can only be realized if stakeholders perceive algorithmic decisions as fair and trustworthy. However, existing research on reactions to ADM is fragmented, theoretically heterogeneous, and yields inconclusive findings, particularly with regard to algorithm aversion and algorithm appreciation. Drawing on the stimulus–organism–response (SOR) model, this dissertation examines how external stimuli, internal perceptions, and subsequent responses shape stakeholder reactions to ADM in organizations. The dissertation makes four central contributions. First, it synthesizes fragmented evidence on reactions to ADM by providing a meta-analysis of prior findings and identifying key boundary conditions. Second, it demonstrates that interventions aimed at mitigating algorithm aversion—such as transparency and human-in-the-loop designs—have effects that are contingent on outcome favorability. Third, it shows that prior experiences of human and algorithmic discrimination differentially shape justice expectations and evaluations of ADM, thereby extending justice theory to human–algorithm interactions. Fourth, it advances understanding of algoactivism by explaining how perceived algorithmic discrimination and justice evaluations give rise to resistance behaviors over time. Overall, this dissertation offers an understanding of stakeholder reactions to ADM and provides theoretical and practical insights into the boundary conditions under which algorithmic systems are perceived as just in organizational settings.
Lizenz:	Dieses Werk ist lizenziert unter einer Creative Commons Namensnennung 4.0 International Lizenz
Fachbereich / Einrichtung:	Wirtschaftswissenschaftliche Fakultät
Dokument erstellt am:	22.01.2026
Dateien geändert am:	22.01.2026
Promotionsantrag am:	02.07.2025
Datum der Promotion:	10.12.2025