Jaewon Yoo

Before joining NTHU, I was a visiting postdoc fellow at the Center of Business Education and Research, New York University (NYU) Shanghai where I was advised by Dr. Yuxin Chen. I received my Ph.D. from the School of Business and Technology Management, KAIST College of Business, KAIST where I was advised by Dr. Wonjoon Kim.

My research investigates the following question:

How do platform and technology design choices shape user/consumer behavior and market outcomes through frictions in decision-making and execution, such as search and evaluation costs, transaction costs, uncertainty, and attention allocation?

Substantively, I study this question in digital platform and technology-enabled market settings, including online media platforms, digital advertising and customer journey interventions, and retail technologies. Across these contexts, my work examines how platform and technology design changes (e.g., participation features, information structures, and intervention formats) alter decision environments, reallocate cognitive and transactional frictions, and in turn affect outcomes such as engagement, choice difficulty, conversion, consumption variety, spending, and firms’ strategic behavior.

Methodologically, my work is grounded in causal inference. I rely on large-scale field experiments (RCTs), conducted through industry collaborations, as well as quasi-experimental designs such as regression discontinuity (RD) and difference-in-differences (DiD) variants, e.g., Synthetic DiD. I also incorporate causal machine learning (ML) tools, such as double/debiased ML (DML) and meta learners, when high-dimensional adjustment is required and when uncovering systematic treatment effect heterogeneity (HTE) is central to the research question.

In parallel, I pursue cross-disciplinary research on counterfactual reasoning at the intersection of causal inference and explainable artificial intelligence (XAI), with work that is naturally positioned for ML venues and methodological journal outlets. This research examines how credible counterfactuals, both for estimating causal effects and for producing interpretable, actionable counterfactual explanations (CFEs), can be constructed when clean control groups, defensible adjustment sets, or transparent decision rules are difficult to obtain. For more detailed information on my publications and ongoing projects, please visit the research section of my webpage.

I serve as an ad hoc reviewer for leading journals in information systems and marketing, including MIS Quarterly (UTD24/FT50 journal) and Journal of Business Research (SSCI/NSTC Mgmt. II Top Journal List), and also contribute to the peer review process at field-facing conferences, such as the Conference on Information Systems and Technology (CIST). I am also a member of the Editorial Board of Asia Marketing Journal, the flagship journal of the Korean Marketing Association.

For prospective students:

Students who are interested in pursuing research under my supervision are strongly encouraged to have first completed at least one of my courses. Familiarity with the material from ISS5096 is particularly beneficial.

When reaching out, please include a cover letter detailing your research interests and proposed topic area, accompanied by your CV and academic transcript. You may want to browse my completed and ongoing supervisions to get a sense of potential research directions.

Guidelines for Letter Recommendations:

I provide recommendation letters for students who have completed a minimum of two courses under my instruction and have engaged with me academically for at least one full semester.