
O'Brien Hall, 448G
MilwaukeeWI53201United States of America(414) 288-6899jungmin.lee@marquette.eduCurriculum VitaeJungmin (Jeremy) Lee is an Assistant Professor of Information Systems and Analytics in the College of Business Administration at 黑料论坛. Dr. Lee holds a Ph.D. in Computer Information Systems from Georgia State University and an MBA from the University of Illinois at Urbana-Champaign. His work is driven by a passion for understanding how technology, data, and artificial intelligence transform decision-making for individuals and organizations. He is committed to helping students develop both a critical understanding of the role of information systems and analytics in business and practical skills for the digital economy.
Introduction to Information Systems, Database Management Systems
His research explores how humans interact with and adopt algorithmic systems in decision-making contexts, with a particular emphasis on the cognitive mechanisms that shape trust, reliance, and resistance toward artificial intelligence. He investigates how algorithmic solutions influence individual and organizational choices, as well as the factors such as algorithm literacy, explainability, and perceived control that determine user acceptance and effectiveness. His work spans applications from healthcare decision-making and retail empowerment to bias in AI systems and the use of generative AI for education and financial forecasting.
Association for Information Systems (AIS)
Human-Algorithm Interaction in Decision Making, Cognitive Mechanisms of Algorithm Adoption
Lee, M. Keil, J. S. Lee, A. Baird, H.-Y. Choi, et al., 鈥淕ender Effects on the Impact of Colorectal Cancer Risk Calculators on Screening Intentions: Experimental study,鈥 JMIR Formative Research, vol. 7, no. 1, p. e37553, 2023.
J. Lee, M. Keil, A. Baird, and J. S. Lee, 鈥淓xplaining the Lackluster Impacts of Colorectal Cancer (CRC) Risk Calculators,鈥 in Academy of Management Proceedings, Academy of Management, vol. 2021, no. 1, p. 11468, 2021.
Cui, J. M. Lee, and J. P.-A. Hsieh, 鈥淎n Integrative 3c Evaluation Framework for Explainable Artificial Intelligence,鈥 in Americas Conference on Information Systems (AMCIS) 2019 Proceedings, 2019.
X. Cui, J. Lee, and J. P.-A. Hsieh, 鈥淗ow may I Persuade you to Trust AI? Promote customized Explainable AI through information vividness,鈥 in Pre-ICIS Workshop on HCI Research in MIS, 2019.