This dissertation examines the interaction of human cognition and technological introduction in today’s manufacturing environment. Its central argument is that human cognitive biases are the most significant barriers to successful AI integration, and these biases stem from systematic cognitive deviations from the rationality framework by Behavioural Operations Management (BOM). Through a tripartite method, divided into conceptual foundations, systematic literature review (SLR), and empirical validation, this thesis presents that cognitive biases mediate the relationship between AI’s potential and its realised performance in the manufacturing sector.
This dissertation examines the interaction of human cognition and technological introduction in today’s manufacturing environment. Its central argument is that human cognitive biases are the most significant barriers to successful AI integration, and these biases stem from systematic cognitive deviations from the rationality framework by Behavioural Operations Management (BOM). Through a tripartite method, divided into conceptual foundations, systematic literature review (SLR), and empirical validation, this thesis presents that cognitive biases mediate the relationship between AI’s potential and its realised performance in the manufacturing sector.
Behavioral Operations in the Age of AI: A Study of Cognitive Biases and AI Technologies
HOLZER, GIULIA
2024/2025
Abstract
This dissertation examines the interaction of human cognition and technological introduction in today’s manufacturing environment. Its central argument is that human cognitive biases are the most significant barriers to successful AI integration, and these biases stem from systematic cognitive deviations from the rationality framework by Behavioural Operations Management (BOM). Through a tripartite method, divided into conceptual foundations, systematic literature review (SLR), and empirical validation, this thesis presents that cognitive biases mediate the relationship between AI’s potential and its realised performance in the manufacturing sector.| File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12608/94654