Background

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, and Ph.D. programs.

Areas of Expertise

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

Education

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

Publications

 

       Citation Counts: Google Scholar 1922; Web of Science 536.

 

  1. Bai, Chunguang, H. Alice Li, and Yongbo Xiao “Industry 4.0 technologies: Empirical impacts and decision framework,” Production and Operations Management, forthcoming.
  2. 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.
  3. Li, Hongshuang (Alice) and Liye Ma (2020), “Charting the Path to Purchase using Topic Models,” Journal of Marketing Research, 57(6), 1019-1036.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.

Courses

  • 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 8252 - Marketing Models

    A study of recent model-based research in the marketing literature; emphasis on the strengths and weaknesses of various modeling approaches in specific problem areas and evaluation of model-based research. Prereq: Doct standing in BusAdm, or permission of instructor. Not open to students with credit for 951. Repeatable to a maximum of 8 cr hrs or 4 completions. This course is progress graded.

  • BUSOBA 7257 - Data Analysis and Visualization

    Designed to equip students with competencies in translating real-world problems into forms that such technologies can assist with, to portray/visualize these translations in ways that enhance the understanding of the dynamics of these problems, to structure mechanisms that derive suggested solutions, to clearly convey the justification and practicality of final solutions to others. Prereq: Enrollment in the MBA or WPMBA program; or permission of instructor.