Guohou Shan's current research focuses on understanding the impact of platform and firm policies, including the adoption of fact-checking, AI, and digital nudges, on user behavior.

Shan's teaching interests include both technical courses and management-related courses. He has taught courses like Data Science, Machine Learning, and Text Mining and served as TAs for Business Applications.

Shan currently serves as the editorial member for the Journal of Association of Information Systems and the Journal of Database Management. Shan also served as the mini-track chair for the Generative and Conversational AI in Information Systems Research and Education: Opportunities and Challenges, HICSS 2024-2025, and Real-Time Digital Feedback in the Evolving Digital Workplace, AMCIS 2024.

Education

  • Ph.D. Management Information Systems, Temple University
  • M.S. Information Systems, University of Maryland
  • M.S. Management Science and Engineering, University of Science and Technology of China
  • B.S. E-commerce, Hefei University of Technology

Awards and Recognition

  • Dean's Outstanding Publication Award (Fox School of Business at Temple University)
  • Conference Best Paper Award (HR Division of AOM)

Selected Publications

  • Roth, P. L., Bobko, P., Shan, G., Roth, R. W., Ferrise, E., & Thatcher, J. B. (2024). Doxing, political affiliation, and type of information: Effects on suspicion, perceived similarity, and hiring-related judgments. Journal of Applied Psychology, 109(5), 730.
  • Tarafdar, M., Shan, G., Thatcher, J.B., & Gupta, A. (2022). Intellectual diversity in IS research: Discipline-based conceptualization and an illustration from Information Systems Research. Information Systems Research, 33(4), 1490-1510.

Selected Presentations

  • Shan, G., Bauman, K., & Wattal, S. (2023). PURM: Project Uncertainty Recommendation Method for Improving Crowdfunding Project Description. Conference on Information Systems and Technology. Phoenix, Arizona.
  • Shan, G., Pienta, D., & Thatcher, J.B. (2023). Investigating the Relative Impact of Generative AI vs. Humans on Voluntary Knowledge. Conference on Information Systems and Technology. Phoenix, Arizona.