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Professor Troncoso's research explores problems related to digital marketplaces and the application of artificial intelligence in marketing. His work combines econometrics, causal inference, and machine learning toolkits. He has studied how design choices on platforms can lead to unintended consequences in user behavior, as well as how management responses to online review platforms can result in selective attrition among female reviewers. Through his research, he has also examined the effects of profile pictures in online labor marketplaces on service provider selection and utilized machine learning techniques to analyze product competition among extensive assortments. His notable achievements include being selected as a faculty fellow at the American Marketing Association 2021 AMA-Sheth Foundation Doctoral Consortium, and he was a finalist in the American Statistical Association 2021 Doctoral Dissertation Proposal Competition. Professor Troncoso has contributed to the academic community as a fellow at the INFORMS Doctoral Consortium in 2019, reflecting his engagement with emerging scholars in the field.
The PhD in Business Administration is the primary doctoral degree encompassing various areas of study including Business Economics, Accounting, and Strategy.