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Applications: Airline, Health Care, High-tech, Hospitality, Operations and Finance Interface, Operations and Marketing Interface, Pricing and Revenue Management, Retailing, Supply Chain Management Methodologies: Causal Inference, Econometrics, Field Experiment, Linear and Nonlinear Panel Data Models, Network Analysis, Regression Discontinuity, Structural Modeling and Estimation Relevant Projects: NSF: Gaining Visibility into Supply Network Risks with Large-Scale Textual Analysis Connections:

Institute for Operations Research and the Management Sciences

Manufacturing & Service Operations Management Society

Revenue Management and Pricing Society

Jun Li

Assistant Professor, Technology and Operations

Jun Li’s main research interests are empirical operations management and business analytics, with special emphases on revenue management, pricing, consumer behavior, economic and social networks. She has worked extensively with large-scale data, including transactions, pricing, inventory and capacity, consumer online search and click stream data, supply chain relationships and disruptions, clinical and healthcare claims. She is the Winner ¬†of INFORMS Revenue Management and Pricing Practice Award for her close collaboration with retailing practitioners in implementing best response pricing algorithms. Her paper on airline pricing and consumer behavior is the finalist for Best Management Science Papers in Operations Management 2012 to 2014. She is also the principal investigator of a National Science Foundation funded project: “Gaining Visibility Into Supply Network Risks Using Large-Scale Textual Analysis”. Her work has enjoyed coverage by The Economist, New York Times and Forbes.

Supply Chain Risk Events

Supply Chain Risk Events