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"Can Large Language Models Extract Customer Needs as well as Professional Analysts?" Timoshenko, Artem, Chengfeng Mao, and John R. Hauser, MIT Sloan Working Paper 7233-25. Cambridge, MA: MIT Sloan School of Management, February 2025.

"Supply Side Considerations When Using Conjoint Analysis in Litigation," Befurt, Rene, Felix Eggers, and John R. Hauser (2024), Handbook of Marketing Analytics: Methods and Applications in Marketing, Public Policy, and Litigation (Edward Elgar), Natalie Mizik and Dominique Hanssens, Eds. Download Paper.

"From Click to Purchase to Return: Website Browsing and Product Returns," Ibragimov, Marat, Siham El Kihal, and John R. Hauser (2024), (Cambridge, MA: MIT Sloan School of Management). Download Paper.

"Product Aesthetic Design: A Machine Learning Augmentation," Burnap, Alex, John R. Hauser, and Artem Timoshenko (2023), Marketing Science, 42(6):1029-1056.

"Leveraging the Power of Images in Predicting Product Return Rates," Dzyabura, Daria, Siham El Kihal, John R. Hauser, and Marat Ibragimov (2023), Marketing Science 42(6):1125-1142.

"Real-time Adaptive Randomization of Clinical Trials," Liberali, Gui, Eric Boersma, Hester Lingsma, Jasper Brugts, Diederik Dippel, Jan Tijssen, and John R. Hauser (2025), Journal of Clinical Epidemiology, Vol. 178: 111612. Download Paper. Appendix. Visual Summary.

"Identifying Customer Needs from User Generated Content." ​Timoshenko, Artem and John R. Hauser. Marketing Science Vol. 38, No. 1 (2019): 1-20. Download Paper.