Publications and Working Papers
The Marketing Group faculty are experts in online and offline consumer behavior, market response forecasting, distribution strategy, new product development, and globalization issues. A selection of publications and working papers are listed below.
For more publications, please visit our collections on the Social Science Research Network and MIT's DSpace.
Select Publications and Working Papers
"Introduction to the Special Issue on the Human-Algorithm Connection."
Caro, Felipe, Jean-Edouard Colliard, Elena Katok, Axel Ockenfels, Nicolas Stier-Moses, Catherine Tucker, and D. J. Wu. Management Sciences. Forthcoming.
"Privacy and Platform Governance: The Case of Apps For Young Children."
Cecere, Grazia, Fabrice Le Guel, Vincent Lefrere, Catherine E. Tucker, and Pai-Ling Yin. Academy of Management Perspectives. Forthcoming. SSRN Preprint.
"Scalable Bundle Recommendations: A Large-scale Field Experiment."
Kumar, Madhav, Dean Eckles, and Sinan Aral. Management Science. Forthcoming. arXiv.
"Small Talk as a Contracting Device: Trust, Cooperative Norms, and Changing Equilibria."
Cashman, Matthew, Boris Maciejovsky, and Birger Wernerfelt. Journal of Law, Economics, and Organization. Forthcoming. Download Preprint.
"Return-Aware Search: Jointly Modeling Clicks, Purchases, and Returns in Online Retail."
Topic: Marketing
Ibragimov, Marat, Siham El Kihal, John R. Hauser, and Raluca Ursu, MIT Sloan Working Paper 6967-24. Cambridge, MA: MIT Sloan School of Management, February 2026. Download Paper.
Keywords: Consumer search, Product returns, Discrete choices, Structural modeling, E-retailing
"Transforming the Voice of the Customer: Large Language Models for Identifying Customer Needs."
Topic: Marketing
Timoshenko, Artem, Chengfeng Mao, and John R. Hauser, MIT Sloan Working Paper 7233-25. Cambridge, MA: MIT Sloan School of Management, January 2026. Download Paper.
Keywords: Innovation, Voice of the Customer, Customer Needs, Marketing Research, Product Development, Innovation, Machine Learning, Generative AI, Large Language Models
"A Sample Size Calculation for Training and Certifying Targeting Policies."
Simester, Duncan, Artem Timoshenko, and Spyros I. Zoumpoulis. Management Science Vol. 71, No. 11 (2025): 9503-9522. SSRN Preprint.
"Optimizing Sustainable Choices: Evidence from a Large-Scale Randomized Field Experiment on Household Recycling."
Li, Linyi, Catherine Tucker, Rui Yan, and Rowan wang, Working Paper. October 2025.
Keywords: Sustainability, Field Experiment, Recycling, Framing, Monetary Incentives
"Combining Ad Targeting Techniques: Evidence from a Field Experiment in the Auto Industry."
Valenti, Albert, Chadwick J. Miller, and Catherine Tucker. Management Sciences Vol. 71, No. 10 (2025): 8586-8603.
"Household Portfolios and Retirement Saving over the Life Cycle."
Parker, Jonathan A., Antoinette Schoar, Allison Cole, and Duncan Simester. Journal of Finance Vol. 80, No. 5 (2025): 2739-2787.
"Decentralization, Blockchain, Artificial Intelligence (AI): Challenges and Opportunities."
Hui, Xiang and Catherine Tucker. Journal of Product Innovation Management Vol. 42, No. 5 (2025): 947-957.
"Frontiers: The Intended and Unintended Consequences of Privacy Regulation for Consumer Marketing."
Dubé, Jean-Pierre, John G. Lynch, Dirk Bergemann, Mert Demirer, Avi Goldfarb, Garrett Johnson, Anja Lambrecht, Tesary Lin, Anna Tuchman, and Catherine Tucker. Marketing Science Vol. 44, No. 5 (2025): 975-984.
"Optimizing Scalable Targeted Marketing Policies with Constraints."
Lu, Haihao, Duncan Simester, and Yuting Zhu. Marketing Science Vol. 44, No. 5 (2025): 1082-1103. Supplemental Material. SSRN.
"From Model Choice to Model Belief: Establishing a New Measure for LLM-Based Research."
Sun, Hongshen and Juanjuan Zhang, Working Paper. August 2025.
Keywords: Large Language Model (LLM), Model Belief, Synthetic Data, Generative Data, Generative Artificial Intelligence (GenAI), Choice Model
"Ambiguity and Confirmation Bias in Reward Learning."
Dorfman, Hayley and Rahul Bhui, Working Paper. August 2025.
Keywords: Reinforcement Learning, Confirmation Bias, Bayesian Inference, Reward, Ambiguity, Optimism