Professor Li joined the Fisher College of Business at the Ohio State University in 2017. Prior to being a Buckeye, she was on the faculty at Indiana University from 2014 to 2017. She received her Ph.D. in Marketing from the University of Maryland – College Park in 2014.

Professor Li’s research focuses on the consumer’s path to purchase. She is interested in understanding the consumer’s touchpoints on their path to purchase, for which Professor Li has developed attribution models to help firms assign conversion credit to each marketing channel in a multi-channel environment. Professor Li also studies firms’ free sampling strategies that get consumers started on their purchase journey, and external shocks to consumers’ purchase journey due to radical innovations or disruptions. In Professor Li’s research, she applies Bayesian statistics, econometrics, machine learning, and causal inference methods to real-world data from hotel chains, software providers, book publishers, etc.

Professor Li is a recipient of the MSI Young Scholar. Her work was selected twice as the Paul Green Award finalist, IJRM Best Article Award, Adobe Digital Marketing Research Award, MSI Research Grant, National Center of the Middle Market Research Fellowship, the MSI Alden G. Clayton Dissertation Proposal Competition Winner, and University of Maryland Distinguished Dissertation Award. Professor Li’s research has appeared in prestigious journals, including Marketing ScienceJournal of Marketing Research, Production and Operations ManagementInternational Journal of Research in Marketing, and Journal of Behavioral Decision Making.

At Fisher, Professor Li is teaching in the undergraduate, SMBA, Executive, and Ph.D. programs.

Areas of Expertise

  • Airlines
  • Retail
  • Services
  • Advertising
  • Applied Bayesian Modeling in Marketing
  • E-commerce
  • Quantitative Marketing
  • Statistics
Production/Operations Management
  • Operations Marketing Interface
  • Technology Management


  • Ph.D., University of Maryland
  • M.S., University of Illinois, Urbana Champaign
  • B.S., Renmin University of China



      Google Scholar Citations: 2753.

      SSRN downloads: 7356.


  1. Zhang, Judy, H. Alice Li, and Greg Allenby. “Using Text Analysis in Parallel Mediation Analysis.” forthcoming at Marketing Science.
  2. Wan, Xiang and H. Alice Li, “The Spillover Effect in Product Variety: Gaining from Losing a Competition,” forthcoming at Production and Operations Management.
  3. Bai, Chunguang, H. Alice Li, and Yongbo Xiao “Industry 4.0 technologies: Empirical impacts and decision framework,” Production and Operations Management, forthcoming.
  4. Li, H. Alice and Wan, Xiang (2023), “Impact of Conflict Delisting and Relisting on Remaining Products in Retail Stores - Sales Gains across Products Categories and Spillovers to Nearby Stores,” Production and Operations Management, 32(7), 2264-2282.
  5. Li, Hongshuang (Alice) (2022), “Converting Free Users to Paid Subscribers in SaaS Contexts – The Impact of Marketing Touchpoints, Message Content, and Usage,” Production and Operations Management, 31(5), 2185-2203.
  6. Li, Hongshuang (Alice) and Liye Ma (2020), “Charting the Path to Purchase using Topic Models,” Journal of Marketing Research, 57(6), 1019-1036.
  7. Li, Hongshuang (Alice), Sanjay Jain, and P.K. Kannan (2019), “Optimal Design of Free Samples for Digital Products and Services,” Journal of Marketing Research, 56(3): 419–438.
  8. P.K. Kannan and Hongshuang (Alice) Li (2017), “Digital Marketing: A Framework, Review and Research Agenda,” International Journal of Research in Marketing, 34 (1): 22-45.
  9. Li, Hongshuang (Alice), P.K. Kannan, Siva Viswanathan and Abhishek Pani (2016), “Attribution Strategies and Return on Keyword Investment in Paid Search Advertising,” Marketing Science, 35(6), 831-848.
  10. Michel Wedel, Jin Yan, Eliot L. Siegel, and Hongshuang (Alice) Li (2016), “Nodule Detection in Chest X-Rays with Eye Movements,” Journal of Behavioral Decision Making, 29 (2-3): 254–270.
  11. Li, Hongshuang (Alice), and P.K. Kannan (2014), “Attributing Conversions in Multichannel Online Marketing Environment: An Empirical Model and a Field Experiment,” Journal of Marketing Research, 51 (1), 40–56.


BUSML 4202 - Marketing Research
Course examines the role of marketing research in the formulation and solution of marketing problems. Emphasis is placed on problem formulation, research design, data collection methods (instruments, sampling, operations) and analysis techniques. Prereq: 3250, AcctMIS 2200, 2300, BusOBA 2320, and 2321; and BusMHR 2291 or 2292.
BUSML 7245 - Analytics of Micro Marketing Data
Focus on the analytics of disaggregate marketing data including appropriate measurement scales and techniques for specific data types. Emphasis on modeling techniques and tools, such as textual analysis, utility-based analysis, and attribution models, to solve marketing problems in corporate setting. Prereq: Enrollment in the SMB-Analytics program, or permission of instructor.
BUSML 8254 - Selective topics in Quantitative Marketing
This course is required for all marketing PhD students. In this course, students will delve into understanding consumer and firm behaviors, enabling them to provide insights to support managerial decision-making in various areas like market structure, market demand, pricing, advertising, product design, and distribution. Prereq: Doct standing in BusAdm, or permission of instructor. Repeatable to a maximum of 8 cr hrs or 4 completions. This course is progress graded.