JaeHwuen Jung

PhD Candidate
Information & Decision Sciences

Education

  • M.S. 2006
    Management Engineering, Graduate School of Management, KAIST

  • B.S. 2004
    Industrial Engineering, Korea Advanced Institute of Science and Technology

Expertise

  • Social & Economic Impact of Information Technology
  • Social Network, Viral Marketing, Social Learning, Mobile Internet and E-Commerce
  • Field Experiments, Econometrics, Panel Data Models, Causal Inference, Machine Learning

JaeHwuen Jung (Jae) is a is a Ph.D. Candidate in Information and Decision Sciences at the Carlson School of Management, University of Minnesota. The unifying theme of Jae's research is to causally examine the impact of new technology channels, digital platforms, and technology-enabled features on user behavior and firms’ outcomes. Specifically, he studies social influence at the mechanism level by drawing on theories from economics and social psychology. His recent papers address research questions including (1) how can firms optimally design referral programs to increase social contagion and word-of-mouth (dissertation topic), (2) how mobile app adoption impacts user behavior and outcomes and increases word-of-mouth for the firm, and (3) how social learning impacts user’s co-creation and engagement. Jae uses an interdisciplinary multi-method approach to understand the underlying mechanisms at work that support the causal inference.

Before joining the Ph.D program, Jae worked for 6.5 years as an IT application architect, serving in many capacities relating to project management, IT systems integration, and legacy systems migration. Jae received his M.S in Management Engineering and B.S. in Industrial Engineering from Korea Advanced Institute of Science and Technology (KAIST),

Selected Works

Current Activities