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Gizem Yalcin Williams

Assistant Professor

Department:     Marketing

Industry Areas:     Consumer Behavior

Research Areas:     Consumer Behavior, Judgment and Decision Making

Gizem Yalcin

Gizem Yalcin Williams (formerly Gizem Yalcin) is an assistant professor in the marketing department of the McCombs School of Business, the University of Texas at Austin. Prior to joining the McCombs faculty, she received her Ph.D. in Marketing and research master’s degree (with a specialization in marketing) from Erasmus University's Rotterdam School of Management (RSM). Gizem specializes in consumer behavior, and she is interested in understanding why consumers behave, think, or feel in the way they do. Her research mainly explores how consumers process and react to the information provided by humans (e.g., experts, friends) versus algorithms / artificial intelligence technologies. In addition to this line of inquiry, she studies prosocial behavior and moral judgment. For example, she investigates how consumers decide where to donate to and react to moral decisions made by others and companies. She employs a mix of methods to address her research questions, including lab and field experiments and secondary data analysis. Gizem’s research has been published in journals including the Journal of Marketing Research and Judgment and Decision Making.

ACADEMIC LEADERSHIP & AWARDS

2023

Finalist, Don Lehmann Award, American Marketing Association

Gizem Yalcin, and Stefano Puntoni. Sept/Oct 2023.
How AI Affects Our Sense of Self: And Why it Matters for Business.
Harvard Business Review 101(5).

Yalcin, Gizem, Sarah Lim, Stefano Puntoni, and Stijn van Osselaer (2022). Thumbs Up or Down: Consumer Reactions to Decisions by Algorithms versus Humans. Journal of Marketing Research, 54 (4), 696-717.

Paolacci, Gabriele and Gizem Yalcin (2020). Benevolent Partiality in Prosocial Preferences. Judgment and Decision Making, 15 (2), 173–81.

Yalcin, Gizem, Stefano Puntoni, Erlis Themeli, Stefan Philipsen, and Evert Stamhuis (2022). Perceptions of Justice by Algorithms. Artificial Intelligence & Law, https://doi.org/10.1007/s10506-022-09312-z.