Yang Fan

Yang Fan is an Assistant Professor of Marketing at NEOMA Business School in France. She holds a Ph.D. in Marketing from the University of British Columbia, an MPhil in Industrial Engineering and Logistics Management from the Hong Kong University of Science and Technology, and a BSc in Mathematics and Applied Mathematics from Sun Yat-sen University. Her research focuses on causal inference, digital marketing, marketing analytics, and machine learning, with particular emphasis on applying statistical and machine learning tools to analyze marketing phenomena such as two-sided markets and big data-driven strategies.

Key academic contributions include studies presented at prestigious conferences like the INFORMS Marketing Science Conference and the UBC-UW Annual Marketing Conference. Her work examines topics such as vertical product differentiation in ride-hailing platforms and the effects of freight subsidies on high-value products.

Research Interests:

• Causal Inference Methodologies
• Machine Learning Applications in Marketing
• Structural Modeling of Market Dynamics
• Two-Sided Market Analysis

Recent academic activities include conference presentations on:

• Vertical Product Differentiation in Two-Sided Markets (2021, 2020)
• Freight Subsidy Impact Analysis (2018)