Essays on Economic Decision-Making in the Era of Machine Intelligence

Erlei, Alexander

dc.contributor.advisor	Bizer, Kilian Prof. Dr.
dc.contributor.author	Erlei, Alexander
dc.date.accessioned	2025-04-09T17:50:05Z
dc.date.available	2025-04-17T00:50:10Z
dc.date.issued	2025-04-09
dc.identifier.uri	http://resolver.sub.uni-goettingen.de/purl?ediss-11858/15938
dc.identifier.uri	http://dx.doi.org/10.53846/goediss-11169
dc.format.extent	272	de
dc.language.iso	eng	de
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/
dc.subject.ddc	330	de
dc.title	Essays on Economic Decision-Making in the Era of Machine Intelligence	de
dc.type	doctoralThesis	de
dc.contributor.referee	Bizer, Kilian Prof. Dr.
dc.date.examination	2025-03-14	de
dc.description.abstracteng	This dissertation studies how human decision-makers react to and adopt novel technology, with a particular focus on algorithmic prediction systems and artificial intelligence. To that end, it combines theory-guided economic experiments with concepts from computer science. As machines increasingly permeate economic decision-making contexts, they operate in both strategic settings — where game-theoretic concepts become crucial — and individual decision environments where prediction quality is paramount. In strategic contexts, AI agents now participate in market interactions previously reserved for humans, raising important questions about cooperation, market efficiency, and welfare distribution. Of particular interest are expert markets characterized by information asymmetries, where AI prediction systems may significantly impact service quality and resource allocation across domains like medicine, finance, education, and law. In individual decision contexts, despite the superior predictive capabilities of algorithms compared to noisy human judgment, research consistently documents human under-utilization of artificial systems. This dissertation addresses these phenomena across seven chapters: Chapters 2 examines how experts' signaling concerns affect the dissemination of algorithmic decision aids on credence goods markets, while Chapter 3 analyzes the concurrent effects of generative AI on market efficiency and surplus distribution through price setting and consumer choices; Chapter 4 analyzes strategic interactions in AI-assisted bargaining; and Chapters 5-7 investigate fundamental explanations for algorithm aversion, exploring human reliance on prediction algorithms and large language models through rational choice theory and contextual multi-armed bandits. Together, these studies advance our understanding of human-AI interactions in increasingly automated economic environments.	de
dc.contributor.coReferee	Rau, Holger A. Prof. Dr.
dc.contributor.thirdReferee	Gadiraju, Ujwal Prof. Dr.
dc.subject.eng	experimental economics	de
dc.subject.eng	artificial intelligence	de
dc.subject.eng	prediction algorithms	de
dc.subject.eng	game theory	de
dc.subject.eng	rational choice	de
dc.subject.eng	social preferences	de
dc.subject.eng	computer science	de
dc.subject.eng	generative AI	de
dc.subject.eng	credence goods	de
dc.subject.eng	decision making	de
dc.subject.eng	human-AI interaction	de
dc.identifier.urn	urn:nbn:de:gbv:7-ediss-15938-8
dc.affiliation.institute	Wirtschaftswissenschaftliche Fakultät	de
dc.subject.gokfull	Wirtschaftswissenschaften (PPN621567140)	de
dc.description.embargoed	2025-04-16	de
dc.identifier.ppn	1922488941
dc.notes.confirmationsent	Confirmation sent 2025-04-09T19:45:01	de

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