
Alice Li
Background
Area of Expertise
- Artificial Intelligence
- Machine Learning
- Causal Inference
- Multi-Touch Attribution
- Marketing Mix Model
Professor Alice Li joined the Fisher College of Business at The Ohio State University in 2017, after serving on the faculty at Indiana University from 2014 to 2017.
Professor Li is actively immersing herself in recent developments in AI, eager to integrate its advancements into her research and share new insights with her students. She is deeply invested in understanding its underlying mechanisms and customizing AI solutions for businesses of all sizes. Her research focuses on the consumer purchase journey, tackling challenges such as the curse of dimensionality, fragmented data, and adapting to a cookie-free environment. Additionally, her work includes initiating the consumer journey through acquisition strategies like sampling, free trials, and freemium models, as well as guiding firms through disruptions and radical innovations in the consumer landscape. She collaborates across industries, including hospitality, software, banking, and publishing.
Professor Li’s research has earned over 3,600 Google Scholar citations and 14,000 SSRN downloads. She is a recipient of the MSI Scholar in 2024, MSI Young Scholar Award in 2021, and a two-time finalist for the Paul Green Award. Additionally, she has received the IJRM Best Article Award, the Adobe Digital Marketing Research Award, and several research fellowships and grants. Her work is published in leading journals, including Marketing Science, Journal of Marketing Research, and Production and Operations Management.
In service to the field, she contributes to committees for MSI, ASA, and AMA, and serves as an associate editor or reviewer for multiple prestigious journals. She frequently reviews for dissertation awards, conferences, and journals in operations management and information systems.
At The OSU, Professor Li is among the 2023-24 cohort of the President and Provost’s Leadership Institute. At Fisher, she received Christine A. Poon and Michael F. Tweedle Faculty Award Fund, Pace Setters Research Award, and the Faculty Service Recognition Award. She teaches several courses across undergraduate, SMBA, Executive, and Ph.D. programs and enjoys coaching students on solving challenging marketing research problems and celebrating their achievements.
Education
- Ph.D., University of Maryland
- M.S., University of Illinois, Urbana Champaign
- B.S., Renmin University of China
Publications
Google Scholar Citations: 3,686.
SSRN downloads: 14,416.
1. Libai, Barak, Ana Babic Rosario, Maximilian Beichert, Bas Donkers, Michael Haenlein, Reto Hofstetter, P. K. Kannan, Ralf van der Lans, Andreas Lanz, H. Alice Li, Dina Mayzlin, Eitan Muller, Daniel Shapira, Jeremy Yang, and Lingling Zhang. “Influencer Marketing Unlocked: Understanding the Value Chains Driving the Creator Economy.” Journal of the Academy of Marketing Science, 53, no. 1 (2025): 4-28.
- Influencer marketing, creator economy, user-generated content, social media, customer lifetime value, customer equity, platforms, followers
2. Bai, Chunguang, H. Alice Li, and Yongbo Xiao “Industry 4.0 technologies: Empirical impacts and decision framework,” Production and Operations Management, forthcoming.
- Production disruption, improved efficiency, financial performance, stock market reaction.
3. Zhang, Judy, H. Alice Li, and Greg Allenby. “Using Text Analysis in Parallel Mediation Analysis.” Marketing Science, 43, no. 5 (2024): 953-970.
- Topic modeling, lexical priors, semi-supervised LDA, machine learning, heterogeneous effects.
4. Wan, Xiang, and H. Alice Li. “The Spillover Effect in Product Variety: Gaining from Losing a Competition.” Production and Operations Management., 33, no. 2 (2024): 577-594.
- Product variety, innovation, sales dispersion, long-tail product, causal inference.
5. Churchill, Victor, H. Alice Li, and Dongbin Xiu. “Unraveling Consumer Purchase Journey Using Neural Network Models.” Journal of Machine Learning for Modeling and Computing, 5, no.1 (2024): 69-83.
- Marketing mix model, consumer purchase journey, deep learning, multi-channel marketing, Shapley value, short lookback window.
6. 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.
- Marketplace disruption, back to normal, old vs new normal, causal inference, machine learning.
7. 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.
- Software-as-a-service, free-trial acquisition, media mix model, digital touchpoints, software usage.
8. Li, Hongshuang (Alice) and Liye Ma (2020), “Charting the Path to Purchase using Topic Models,” Journal of Marketing Research, 57(6), 1019-1036.
- Path to purchase, search phrase, textual analysis, machine learning, topic model, hidden Markov model.
9. 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.
- Digital content, software as a service, free sample, freemium, field experiment.
10. 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.
- Digital marketing, mobile marketing, search engine, user generated content, omni-channel marketing.
11. 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.
- Last-touch attribution, first-touch attribution, purchase funnel, paid search advertising, ROI, budget allocation.
12. 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.
- Eye tracking, partially invisible Markov model, regions of interest.
13. 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.
- Multi-touch attribution, Shapley value, Bayesian, field experiment, carryover, spillover.
Courses
- 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 7247 - Analytics for Macro Marketing Data
- A 'macro' approach to understanding the marketing decision process with implications stretching beyond the firm: i.e., consumers privacy, search and recommendation. Emphasis on data structures arising from online platforms and marketplaces as well as the prevalent technological and regulatory landscape in the industry. Prereq: Enrollment in SMB-Analytics program.