Journal publications
Yeh, T-T., Xiao, Y., Daniel, S., & Nguyen, M. (2025). An empirical analysis of external and internal factors affecting manufacturing firm failure and resilience. Journal of Corporate Accounting & Finance, 36(3), 349-377. [Link]
Nguyen, M., Nguyen, B., & Lieu, M-L. (2024). Corporate financial distress prediction in a transition economy. Journal of Forecasting, 43(8), 3128-3160. [Link]
DeBaryshe, B., Im, S., Azuma, J., Stern, I., Nguyen, M., & Chen, Q. (2024). Close to home: Family-centered spatial analysis of access to early care and education. Early Childhood Research Quarterly, 68, 123-134. [Link]
Other publications
Nguyen, M., Nasrin, F., & Bui, Q-T. (2025). Topological framework for exploring imbalanced time series. [Accepted at 17th International Conference on Computational Collective Intelligence (ICCCI 2025)]
Nguyen, M. & Le, H. L. (2025). Measuring causal effects of online medical records on medical decision making using causal machine learning (Accepted at 17th International Conference on Computational Collective Intelligence (ICCCI 2025)) [Link]
Nguyen, M., Pham, H., Nguyen, T., Vu, D. T., Lam, Q. L., & Le, C. V. (2025). Effects of social media on religious belief: Causal machine learning approach" (Forthcoming in the Springer book titled Data Science for Econometrics and Related Topics). [Link] [Slides]
Nguyen, M., Cao-Van, K., Le, M. G., Bui, T. X., & Hong. S. (2025). Hybrid machine learning models using soft voting classifier for financial distress prediction. (Forthcoming in the Springer book titled Artificial Intelligence and Machine Learning for Econometrics: Applications and Regulation) [Link] [Slides] [code]
Best Paper Awards at the ECONVN2025 Conference.
Nguyen, M., Yeh, T-T., Xiao, Y., & Daniel S. (2023). Text as treatment from Form 10-K: Causal effects of perceived natural hazards on firm profitability. ICIS 2023 Special Interest Group on Big Data Proceedings. (Pre-ICIS) [Link] [Code]
Nguyen, M. (2023). Essays on Business Analytics and Game Theory, PhD Thesis, University of Hawaii. [Link]
Working papers
Combining causal and interpretable machine learning to understand health literacy and engagement in digital platforms (with Anjana Susarla, Xiao Liu & Rema Padman)
Presented at MSU Broad College Brown Bag Seminar
Presented at SCECR 2024
Submitted for the 2024 Pierskalla Best Paper Competition
p-hacking and publication bias in information systems research (with Mike Nguyen) [2nd round revision: Information Systems Research]
Presented at INFORMS 2024 (poster presentation)
Presented at MSU PhD Course in Empirical Methods for IS Research (invited talk)
Text as treatment from financial reports: Effects of natural hazard risk on firm profitability using causal machine learning. (with Ting-Tsen Yeh, Yuanzhang Xiao & Shirley Daniel)
From prediction to action: Using SHAP and DiCE to navigate financial distress. (with Thanh Ngo, Bang Nguyen & Sukhwa Hong) [Under review: Management Science]
Beyond stars: How review content and star ratings shape perceived review helpfulness in online marketplaces. (with Tien Nguyen & Arvind Tripathi) [Under review: Journal of the Association for Information Systems]
Natural disaster risk and firm performance: Text mining and machine learning approach. (with Ting-Tsen Yeh, Yuanzhang Xiao & Shirley Daniel) [Link]
Presented at INFORMS 2022
From view to gift and purchase: Unpacking impulsive behavior in livestream shopping. (with Loc Tran & Thuy-Tien Nguyen) [Link]
Work in progress
LLMs for health literacy (with Anjana Susarla, Xiao Liu & Rema Padman)
Know thyself: Does digital health capability and doctor's trust affect self health assessment? (with Long Le & Phuong Ai Hoang) [Target: Management Science]
Causal effects of medical wearable devices on health behaviors. (with Long Le) [Target: Health Communication]
Causal effects of cybersecurity readiness on firm performance: Evidence from conference calls. (with Jaekon Jung & Hiep Dang) [Target: Management Science]
Fund raising and anonymity (with Ngan Vo, Sara Quach Thaichon & Huy Pham).