Steven D. Shaw, PhD
Wharton Postdoctoral Researcher
I study why we consume—uncovering the biological, psychological, and technological forces that shape consumer decision-making. My work reveals how emerging data and innovative methods can expose the hidden drivers of our choices, from everyday purchases (e.g., spending on recreation) to life-defining commitments (e.g., mate choice).
I am a Postdoctoral Researcher in the Marketing Department at
The Wharton School of the University of Pennsylvania.
My research integrates emerging technologies, novel data sources, and interdisciplinary methods to advance marketing theory and practice. I examine how innovations—from generative AI to genomic and epigenetic data—reshape consumer psychology, segmentation, and strategy.
My job market paper introduces Tri-System Theory of Cognition, and demonstrates the rise of "cognitive surrender": deference to AI without verification. Other work introduces biological age (BioAge) as a next-generation demographic variable, using epigenetic clocks to reveal insights into the aging consumer. Another project explores how large language models (LLMs) can enhance the generalizability of experiments through the automated creation of stimulus universes. I also study consumer neuroscience, including how neural activity can forecast market trends.
I hold a Ph.D. in Marketing and an M.A. in Statistics from the University of Michigan, Ann Arbor and dual B.Sc. degrees in Genetics & Psychology and Animal Behavior from the University of Western Ontario, Canada.
The Wharton School of the University of Pennsylvania.
My research integrates emerging technologies, novel data sources, and interdisciplinary methods to advance marketing theory and practice. I examine how innovations—from generative AI to genomic and epigenetic data—reshape consumer psychology, segmentation, and strategy.
My job market paper introduces Tri-System Theory of Cognition, and demonstrates the rise of "cognitive surrender": deference to AI without verification. Other work introduces biological age (BioAge) as a next-generation demographic variable, using epigenetic clocks to reveal insights into the aging consumer. Another project explores how large language models (LLMs) can enhance the generalizability of experiments through the automated creation of stimulus universes. I also study consumer neuroscience, including how neural activity can forecast market trends.
I hold a Ph.D. in Marketing and an M.A. in Statistics from the University of Michigan, Ann Arbor and dual B.Sc. degrees in Genetics & Psychology and Animal Behavior from the University of Western Ontario, Canada.
