Date of Award

5-2025

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

College/School

College of Humanities and Social Sciences

Department/Program

Psychology

Thesis Sponsor/Dissertation Chair/Project Chair

Michael Bixter

Committee Member

Tina M. Zottoli

Committee Member

Jennifer D. Bragger

Abstract

This dissertation explored systematic susceptibility to four cognitive biases among individuals, dyads, triads, and tetrads in a series of tasks designed to simulate real-world business management scenarios. This included measuring representativeness bias, sunk costs, anchoring effects, and framing effects, each of which with historical and empirical prevalence in various managerial contexts. Using experimental data from undergraduate students, participants were prompted to act as surrogate members of a top management team simulation. Participants first completed each of the decision scenarios on their own and were subsequently brought together to collaborate and converge on a single decision preference on the same set of items. A follow-up survey probed participants’ experiences during the individual and collaboration phases. We also analyzed the influence of various individual-level characteristics (e.g., personality traits and decision styles) and team-level mediators and moderators (e.g., group size, process accountability, intragroup conflict, procedural rationality, and reflexivity). We also added text embeddings from a pre-trained large language model to quantify participants’ open-ended responses about their procedures during the decision task to examine if they added incremental validity to base regression models. We then tested a recently developed group aggregation framework to examine how the alignment within and across specific team member attributes differentially predicted bias susceptibility. This research was important in furthering the debate on group-level rationality, addressing whether teams can override cognitive tendencies often observed at the individual-level, and providing partial evidence of bias susceptibility in a naturalistic work context.

File Format

PDF

Available for download on Thursday, May 28, 2026

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