Research
Research
Dongcheng Zhang, Kunpeng Zhang, Yi Yang and David Schweidel, “TM-OKC: An Unsupervised Topic Model for Text in Online Knowledge Communities.” (Accepted at MIS Quarterly)
Dongcheng Zhang, Hanchen Jiang, Maoshan Qiang, Kunpeng Zhang and Liangfei Qiu, “Time to Stop? An Empirical Investigation on the Consequences of Canceling Monetary Incentives on a Digital Platform.” (Accepted at Information Systems Research)
Dongcheng Zhang, Kunpeng Zhang and Yuan Liao, “Weighting-Based Treatment Effect Estimation via Distribution Learning.”
Dongcheng Zhang, Kunpeng Zhang and David Schweidel, “Customer Journey Analysis with Interpretable Deep Learning.”
Dongcheng Zhang, Bobby Zhou and Tianxin Zou, “Knowledge Monetization of Online Communities: A Blessing or a Curse?”
Dongcheng Zhang and Kunpeng Zhang, “Estimating the Distribution of Heterogeneous Treatment Effects via Normalizing Flows.”
“Interpretable and Theory-driven Machine Learning Algorithms for IS,” Mendoza College of Business, The University of Notre Dame, 2023 (Cancelled)
“Interpretable and Theory-driven Machine Learning Algorithms for IS,” School of Business and Management, The Hong Kong University of Science and Technology, 2023 (Cancelled)
“Interpretable and Theory-driven Machine Learning Algorithms for IS,” Antai College of Economics and Management, Shanghai Jiao Tong University, 2023
“Interpretable and Theory-driven Machine Learning Algorithms for Marketing,” CUHK Business School, The Chinese University of Hong Kong, 2023
“Interpretable and Theory-driven Machine Learning Algorithms for IS,” CUHK Business School, The Chinese University of Hong Kong, 2023
“Interpretable and Theory-driven Machine Learning Algorithms for IS,” Simon Business School, University of Rochester, 2023
“Interpretable and Theory-driven Machine Learning Algorithms for IS,” Warrington College of Business, University of Florida, 2023
“Interpretable and Theory-driven Machine Learning Algorithms for Marketing,” Darden School of Business, University of Virginia, 2023
“Interpretable and Theory-driven Machine Learning Algorithms for Marketing,” Fisher College of Business, The Ohio State University, 2023
“TM-OKC: An Unsupervised Topic Model for Text in Online Knowledge Communities,” Conference on Information Systems and Technology (CIST), 2023
“Customer Lifetime Value Prediction with Interpretable Deep Learning,” INFORMS Marketing Science Conference, 2023
“Commercialization of Online Communities: A Blessing or a Curse?” INFORMS Marketing Science Conference, 2021
“Commercialization of Online Communities: A Blessing or a Curse?” China Marketing International Conference, 2021