Research Interests
Quantitative modeling of social influence and shared consumption, Firm and user generated contents, Bayesian statistical inference, Machine learning, Business networks, Entertainment industry
Research
Ph.D. Office during Michigan years
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The two main research streams that I am broadly interested in are (1) Quantitative modeling of firm- and user-generated contents and (2) Quantitative modeling of social influence in business and consumer settings. Please see a list of selected projects below. For the full list of on-going projects, please refer to CV.
I have experience with a wide range of quantitative research methods, ranging from working with network data, image processing, to running experiments using surveys and physiological measures. |
Quantitative modeling of firm and user generated contents
"The Moral Significance of Aesthetic Quality in Nature Imagery"
- Published at Psychological Science, 33 (9) 2022 - with Julia Lee Cunningham & Anocha Aribarg
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"Does Topic Consistency Matter? A Study of Critic and User Reviews in the Movie Industry"
- Published at Journal of Marketing, 2023 - with Annie Ding, Xin (Shane) Wang & Shijie Lu
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Quantitative modeling of social influence
"Social versus Economic Factors in Network Formation: An Empirical Analysis of the Multi-level Marketing Industry"
- with Puneet Manchanda (working paper)
- with Puneet Manchanda (working paper)
"The Impact of Network and Spatial Embeddedness on Salespeople Inactivity in Direct Selling Organizations"
- with Puneet Manchanda (working paper)
- with Puneet Manchanda (working paper)
"How Shared Consumption Enhances Entertainment Experiences"
- with Anocha Aribarg & Natasha Zhang Foutz
- Featured in Marketing Science Institute ( MSI ) Working Paper Series, Report No. 16 - 126
- with Anocha Aribarg & Natasha Zhang Foutz
- Featured in Marketing Science Institute ( MSI ) Working Paper Series, Report No. 16 - 126