Professor Troncoso's research explores problems related to digital marketplaces and AI applications in marketing, and combines toolkits from econometrics, causal inference, and machine learning. She has studied how different platform design choices can lead to unintended consequences on their users' behavior, including how management responses in online review platforms can lead to selective attrition of female reviewers, and how using profile pictures in online labor marketplaces affects the choice of service providers.
Professor Troncoso's research has also explored how to leverage machine learning methods to study product competition in today's large product assortments.
Isamar Troncoso
Assistant Professor of Business Administration
Assistant Professor of Business Administration
Isamar Troncoso is an Assistant Professor of Business Administration in the Marketing Unit at HBS. She teaches the Marketing course in the MBA required curriculum.
Professor Troncoso studies problems related to digital marketplaces and new technologies. She leverages toolkits from econometrics, causal inference, and machine learning for her research. Her work has studied the unintended consequences of different platform designs on users' behavior, and the use of representation learning methods to model consumer choices in large assortments.
She earned a Ph.D. in Business Administration (Marketing) from the Marshall Business School at the University of Southern California. She also earned an Industrial Engineering degree from the University of Chile.
- Journal Articles
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- Troncoso, Isamar, and Lan Luo. "Look the Part? The Role of Profile Pictures in Online Labor Markets." Marketing Science (forthcoming). (Pre-published online December 29, 2022.) View Details
- Proserpio, Davide, Isamar Troncoso, and Francesca Valsesia. "Does Gender Matter? The Effect of Management Responses on Reviewing Behavior." Marketing Science 40, no. 6 (November–December 2021): 1199–1213. View Details
- Working Papers
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- Zhang, Mengxia, and Isamar Troncoso. "Beyond the Hype: Unveiling the Marginal Benefits of 3D Virtual Tours in Real Estate." Harvard Business School Working Paper, No. 24-003, July 2023. View Details
- Chen, Fanglin, Xiao Liu, Davide Proserpio, and Isamar Troncoso. "Product2Vec: Leveraging Representation Learning to Model Consumer Product Choice in Large Assortments." NYU Stern School of Business Research Paper Series, July 2022. View Details
- Research Summary
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- Awards & Honors
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Selected as an AMA-Sheth Foundation Doctoral Consortium Faculty Fellow by the American Marketing Association in 2021.Finalist in the 2021 American Statistical Association Best Doctoral Dissertation Proposal Competition (Marketing Section).Selected as an INFORMS Doctoral Consortium Fellow in 2019.
- Areas of Interest
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- analytics
- artificial intelligence
- electronic commerce
- machine learning
- marketing
- big data
- econometrics
- e-commerce industry
- high technology
- retailing
Additional TopicsIndustries