" The AI & I "
As the massive AI wave approaches, PhD students must navigate it safely by leveraging their unique research strengths. Together with six engaging mentors—each bringing their own distinct and vibrant expertise—we will explore the challenges ahead and develop strategies to ride this wave successfully.
Mentors in Alphabetical order
Name, Affiliation, Areas of expertise & What to say to PhD students
Yeongin Kim, Wake Forest University
Domain: Healthcare, Digital Platforms, Artificial Intelligence/ Method: Game Theory, Econometrics, Applied ML and Optimization
"헬스케어 및 디지털 플랫폼 맥락에서 Economics of IS 관련 주제들을 연구하고 있습니다. 최근에는 Patient Portals, Patient-Generated Health Data (PGHD), 그리고 Health GenAI 등, consumer-facing technology에 대한 관심을 바탕으로 연구를 진행하고 있습니다."
I'm conducting research on topics related to the Economics of Information Systems (IS) in the context of healthcare and digital platforms. Recently, my work has focused on consumer-facing technologies such as patient portals, patient-generated health data (PGHD), and Health GenAI
Youngjin Kwon, Washington State University
Field/Lab Exepriments, Discriminatory issues on online platforms, Organizational impact of IS
"필드/랩 실험 기반으로 IS 와 관련한 discriminatory issue 에 대한 연구를 주로 합니다."
My research primarily explores discriminatory issues related to Information Systems (IS), with a focus on field and lab experiments.
Junyeong Lee, Chungbuk National University
Structural Equation Model, Survey Methodology, Qualitative Content Analysis, Human behavior/Group dynamics in IS, Ethics and policy implications
"서베이 기반의 구조방정식 모형을 주로 사용하였고, 질적 연구(특히, 질적 내용 분석)도 일부 수행해 본 경험이 있습니다. IT와 그룹과 같은 집단의 역학에 관심이 있고, 최근엔 디지털 기술의 정책적/윤리적 시사점을 고민해보고 있습니다."
I have primarily used survey-based structural equation modeling in my research and have some experience with qualitative research, particularly qualitative content analysis. I am interested in the dynamics of groups, such as IT teams, and more recently, I have been exploring the policy and ethical implications of digital technologies.
Gangmin Park, Kookmin University
Simulation Experiment (Genetic Algorithm), Societal and Firm-Level Impact of AI, Digital Transformation and Innovation
"유전 알고리즘(Genetic Algorithm)을 활용한 시뮬레이션 분석 방법론을 주로 사용해왔습니다. 최근에는 빅데이터를 기반으로 한 실증 분석에도 집중하고 있습니다. 특히, 분석 방법론의 엄밀성(rigor)을 넘어, 연구 결과가 기업과 사회에 어떤 실질적 영향을 미치는지를 중요하게 생각합니다."
I have primarily employed simulation-based analytical methods using genetic algorithms in my research. More recently, I have also been focusing on empirical analysis based on big data. Beyond ensuring methodological rigor, I place strong emphasis on the practical impact of research findings on both businesses and society.
Jiyong Park, University of Georgia
Econometric analysis, Causal inference, Green IS/IT, Societal impacts of digital platforms, IT value
"디지털기술의 사회적, 환경적 영향에 대한 실증연구를 수행하면서 인과추론 방법론을 통해 사회현상과 기업활동에서의 원인과 결과를 분석하는 일을 합니다. 인과추론의 저변을 확대하고자 매년 여름 ‘Korea Summer Workshop on Causal Inference’를 조직하고 있으며, 유튜브 채널 〈인과추론의 데이터과학〉을 운영 중입니다."
I conduct empirical research on the social and environmental impacts of digital technology, using causal inference methodologies to analyze cause-and-effect relationships in social phenomena and corporate activities. To promote broader understanding and application of causal inference, I organize the annual Korea Summer Workshop on Causal Inference each summer. I also run a YouTube channel titled <인과추론과 데이터과학>.