Yixiang Xu

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yixiang-xu@berkeley.edu

YIXIANG XU

徐祎翔

I'm a PhD candidate in Quantitative Marketing at UC Berkeley's Haas School of Business.

My research investigates how AI and digital technologies shape firm strategy, consumer engagement, and platform performance. I study how theory-driven AI can transform marketing in data-scarce and diverse markets, and how the design and algorithmic features of digital platforms can foster more engaging user experiences. My research combines large-scale field experiments and causal inference techniques with economics principles and behavioral insights.

My dissertation won the RRBM Dare to Care Dissertation Scholarship Award (winner, 2025), and also received recognition from the Ipsos-CARD Dissertation Proposal Award (runner-up, 2025) and the MSI Alden G. Clayton Doctoral Dissertation Proposal Competition (honorable mention, 2024).

I am on the 2025–2026 academic job market.

Job Market Paper

''AI Personalization in Data-Scarce Markets''

Publications

''Paralanguage Classifier (PARA): An Algorithm for Automatic Coding of Paralinguistic Nonverbal Parts of Speech in Text,'' with Andrea W. Luangrath and Tong Wang (2023), Journal of Marketing Research, 60 (2), 388-408. [Paper]

''Observing Product Touch: The Vicarious Haptic Effect in Digital Marketing and Virtual Reality,'' with Andrea W. Luangrath, Joann Peck and William Hedgcock (2022), Journal of Marketing Research, 59 (2), 306-326. [Paper]

"Distributed Bayesian Inference in Linear Mixed-Effects Models," with Sanvesh Srivastava (2021), Journal of computational and graphical statistics 30.3 (2021): 594-611. [Paper]

Working Paper

''Algorithmic Targeting of At-Risk Sales Agents: Evidence from Emerging Markets''

Finalist, 2025 Artificial Intelligence in Management Conference Best PhD Paper Award

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