Biography
Qing Liu is the UW Foundation Chairman Orr – Bascom Professor and an associate professor in Department of Marketing at Wisconsin School of Business. Her research focuses on the development of statistical theories and methods for the study of marketing problems that are of practical relevance. Her research interests include consumer choice, experimental design, conjoint analysis, Bayesian statistics and big data analytics.
Qing’s research has been published in journals such as Marketing Science, Journal of Marketing Research, Journal of Marketing, Quantitative Marketing and Economics, and Statistica Sinica. She has also been the recipient of numerous awards, including the Best Paper Award for the AMA ART Forum in 2010, and the Junior Researcher Awards for Design and Analysis of Experiments in 2012, 2009, and 2007.
Qing is the recipient of the Gaumnitz Distinguished Faculty Teaching Award in Wisconsin School of Business in 2022. She has taught Data Visualization for Business Analytics for the MSBA and MBA/Professional MBA programs, and Marketing Research for both Undergraduate and graduate students.
Prior to her academic career, Qing worked at JPMorgan Chase as a vice president in risk and knowledge management. She also worked at Cendant Corporation as a manager in database marketing, and at Capital One as a senior statistician manager in marketing and analysis.
Qing received her Ph.D. and M.S. in statistics with a minor in marketing from The Ohio State University, and her B.S. from the University of Science and Technology of China.
Research
Selected Published Journal Articles
Zhang, Q. & Chien, P. & Liu, Q. & Xu, L. & Hong, Y. (2021). Mixed-input Gaussian process emulators for computer experiments with a large number of categorical levels Journal of Quality Technology
Chen, Y. & Qi, Y. & Liu, Q. & Chien, P. (2018). Sequential Sampling Enhanced Composite Likelihood Approach to Estimation of Social Intercorrelations in Large-scale Networks Quantitative Marketing and Economics
Chandukala, S. & Dotson, J. & Liu, Q. (2017). An Assessment of When, Where and Under What Conditions In-Store Sampling is Most Effective Journal of Retailing
Henderson, T. & Liu, Q. (2017). Efficient Design and Analysis for a Selective Choice Process Journal of Marketing Research
Xu, X. & Qian, P. & Liu, Q. (2016). Samurai Sudoku-Based Space-Filling Designs for Data Pooling The American Statistician
Mallapragada, G. & Chandukala, S. & Liu, Q. (2016). Exploring the Effects of What (Product) and Where (Website) Characteristics on Online Shopping Behavior Journal of Marketing
Liu, Q. & Tang, E. (2015). Construction of Efficient Heterogeneous Choice Designs: A New Approach Marketing Science
Chandukala, S. & Dotson, J. & Liu, Q. & Conrady, S. (2014). Exploring the Relationship Between Online Search and Offline Sales for Better “Nowcasting” Customer Needs and Solutions
Liu, Q. & Dean, A. & Allenby, G. (2012). Bayesian Designs for Hierarchical Linear Models Statistica Sinica
Liu, Q. & Dean, A. & Bakken, D. & Allenby, G. (2009). Studying the Level-Effect in Conjoint Analysis: An Application of Efficient Experimental Designs for Hyper-parameter Estimation Quantitative Marketing and Economics
Liu, Q. & Dean, A. & Allenby, G. (2007). Design for Hyperparameter Estimation in Linear Models Journal of Statistical Theory and Practice
Liu, Q. & Otter, T. & Allenby, G. (2007). Investigating Endogeneity Bias in Marketing Marketing Science
Teaching
Undergraduate Courses
Marketing Research (MKT 310), Fall 2021.
Systematic and objective search for and analysis of information relevant to the identification and solution of problems in marketing.
Graduate Courses
Data Visualization for Business Analytics (BUS 720), Fall 2021.
Introduce students to principles of data visualization and provide hands-on experience using data visualization tools and techniques for business applications. Develop proficiency in current visualization software tools, and leverage these tools for data exploration, insight into decision-making, and data presentation.
Marketing Research (MKT 710), Fall 2021.
An overview of the marketing research process from a methodological perspective. Topics: Research design, data collection procedures, sampling and data analysis.
Learning/Teaching Oriented Publications
Liu, Q. (2010). Models for upper levels of a hierarchy Bayesian Analysis in Marketing: A breakthrough in customer analytics
Liu, Q. & Otter, T. & Allenby, G. (2009). Measurement of Self- and Cross-price Effects Handbook on Research on Pricing
Service
Editorial and Reviewing Activities
Journal of Retailing – Since June 2022
Editorial Board Member
Quantitative Marketing and Economics – Since February 2021
Associate Editor
Annals of Applied Statistics – Since January 2021
Ad Hoc Reviewer
Information Systems Journal – Since September 2020
Ad Hoc Reviewer
Management Science – Since January 2017
Ad Hoc Reviewer
Marketing Letters – Since January 2017
Ad Hoc Reviewer
Journal of Marketing Research – Since January 2017
Ad Hoc Reviewer
Journal of Marketing – Since January 2016
Ad Hoc Reviewer
Journal of Business Research – Since January 2016
Ad Hoc Reviewer
Journal of American Statistical Association – Since January 2015
Ad Hoc Reviewer
Journal of Consumer Research – Since January 2014
Ad Hoc Reviewer
Customer Needs and Solutions – Since January 2013
Editorial Board Member
International Journal of Research in Marketing – Since October 2012
Ad Hoc Reviewer
Journal of Business and Economic Statistics – Since September 2007
Ad Hoc Reviewer
Communications in Statistics: Theory and Methods – Since March 2007
Ad Hoc Reviewer
Marketing Science – Since January 2007
Ad Hoc Reviewer