Substantive: Online Search, Advertising, Loyalty Programs, Recommendation System, User Generated Content, Social Network, Pricing, Product Recalls, Product Assortments, Supply Chain, Behavioral Economics, Big Data Analytics, Blockchain

Methodological: Topic Modeling, Natural Language Processing, Machine Learning, Deep/Graph Neural Networks, Bayesian Methods, Causal Inference, Lab/Field Experiments

LIU Jia holds a joint appointment between Department of Industrial Engineering and Decision Analytics and Department of Marketing at HKUST. Her research interests have covered a broad range of areas, including consumer search, advertising, pricing, recommender system, user generated content, social media, big data analytics, product assortment, supply chain management, and blockchain. Her research has been published in leading journals (e.g., Marketing Science, Journal of Marketing Research, Management Science, and Quantitative Marketing & Economics). Professor Liu is on the editorial review board of both Marketing Science and the Journal of Marketing Research. Her research has won 2018 John Little award for best marketing paper published in Marketing Science or Management Science. Prior joining HKUST, Professor Liu was a Postdoc researcher at Microsoft Research (NYC). She holds a Ph.D. in Marketing from Columbia University, a M.S. in Statistics, and a B.S. in Mathematics.

Research

• Winner, John Little award for best INFORMS Marketing paper, 2018
• Finalist, Frank M. Bass outstanding dissertation award, 2018
• Best paper award at the Sixth China Marketing International Conference, 2018

Education

• Winner, Vitha R. and Saroj V. Rao ISMS Doctoral Dissertation Award (Ziwei Cong), 2021
• Runner-up, Shankar-Spiegel Dissertation Proposal Award (Ziwei Cong), 2020
• Finalist, American Statistical Association Statistics in Marketing Best Doctoral Dissertation
• Proposal Competition (Ziwei Cong), 2021

Career

• Dean’s Fellowship, HKUST Business School, 2021
• The HKUST Faculty Recognition Award, 2019

Prior to Doctoral Graduation

• Fellow, AMA Sheth Foundation Doctoral Consortium, 2016
• Fellow, Marketing Science Doctoral Consortium, 2015
• Fellow, Quantitative Marketing & Structural Econometrics Workshop, Duke University, 2013
• Student Representative, UH Annual Doctoral Symposium, University of Houston, 2015
• Best Discussant Award, Haring Doctoral Symposium, Indiana University, 2014
• Student Representative, Haring Doctoral Symposium, Indiana University, 2014
• Luxury Education Foundation Award (US$14,000), Columbia Business School, 2015
• Deming Doctoral Research Fellowship (US$10,000), Columbia Business School, 2014
• Full Graduate Fellowship, Columbia University, 2011-2016
• Full Scholarship, Michigan State University, 2008-2010
• Summer Fellowship, Michigan State University, 2008

1. Liu, Jia, and Ziwei Cong (2022), “The Daily Me versus The Daily Others: How Do Recommendation Systems Change User Interests? Evidence from a Knowledge-Sharing Platform” forthcoming at Journal of Marketing Research


2. Liu, Jia, Olivier Toubia, and Shawndra Hill (2021), “Content-based Model of Web Search Behavior: An Application to TV Show Search” Management Science, 67 (10), 6378-6398.
   - Best paper award at the 2018 China Marketing International Conference


3. Liu, Jia, and Shawndra Hill (2021), “Frontiers: Moment Marketing: Measuring Dynamics in Cross-channel Ad Effectiveness” Marketing Science, 40(1), January–February, pp. 13–22.
   - One of the first few papers accepted by the Marketing Science Frontiers section


4. Liu, Jia and Asim Ansari (2020) “Understanding Consumer Dynamic Decision Making Under Competing Loyalty Programs” Journal of Marketing Research, April, 57(3), 422-444.


5. Liu, Jia, and Olivier Toubia (2020) “Search Query Formation by Strategic Consumers” Quantitative Marketing and Economics, 18, 155-194.


6. Liu, Jia and Olivier Toubia (2018) “A Semantic Approach for Estimating Consumer Content Preferences from Online Search Queries,” Marketing Science, 37 (6), 930-952.
   - Winner, 2018 John Little award for best marketing paper published in Marketing Science, Management Science, or other INFORMS journal
   - Finalist, 2018 Frank M. Bass outstanding dissertation award
   - Chosen for INFORMS press release by Editor-in-Chief of Marketing Science