Dengfeng Yan is an Associate Professor of Marketing at NYU Shanghai and a Global Network Associate Professor at the Leonard N. Stern School of Business at NYU. Before joining NYU Shanghai, he was an Associate Professor of Marketing with tenure at the University of Texas at San Antonio. Dengfeng’s research focuses on understanding how consumers respond to numerical information (such as prices and attribute specifications) and how consumer judgment and preferences vary as a function of psychological distance. His research has been published in top-tier journals including Journal of Consumer Research, Journal of Marketing Research, Journal of Consumer Psychology, and Journal of Personality and Social Psychology. He currently serves on the Editorial Review Boards of Journal of Consumer Research and Journal of Consumer Psychology.
Select Publications
- Yan, Dengfeng, Suhas Vijayakumar, and Jiewen Hong (2024), “The Effects of Psychological Distance on Numerical Comparative Judgment,” Journal of Marketing Research, 61 (6), 1171-1182.
- Pena-Marin, Jorge and Dengfeng Yan (2021), “Reliance on Numerical Precision: Compatibility between Accuracy versus Efficiency Goals and Numerical Precision Level Influence Attribute Weighting in Two‐Stages Decisions,” Journal of Consumer Psychology, 31 (1), 22-36.
- Yan, Dengfeng and Jaideep Sengupta (2021), “The Effects of Numerical Divisibility on Loneliness Perceptions and Consumer Preferences,” Journal of Consumer Research, 47 (5), 755-771.
- Yan, Dengfeng (2019), “Subtraction or Division: Evaluability Moderates Reliance on Absolute Differences versus Relative Differences in Numerical Comparisons,” Journal of Consumer Research, 45 (5), 1103-1116.
- Yan, Dengfeng and Jorge Pena-Marin (2017), “Round Off the Bargaining: The Effects of Offer Roundness on Willingness to Accept,” Journal of Consumer Research, 44 (2), 381-395.
Education
- PhD, Marketing
HKUST - M. Phil, Marketing
Hong Kong Baptist University - BA, Political Science
Nanjing University
- Numerical Information
- Digital marketing
- Consumer Behavior
- Research for Customer Insights
- Digital Marketing