Working Papers

Our research group focuses on the impacts of AI and IT in business and society. Specifically, we are examining how firms develop AI and robot strategies for innovation, how advanced AI technologies (e.g., generative AI, deep learning, computer vision) affect tech platforms, and how we can mitigate the unintended consequences of AI and IT. For some papers, we share interactive visualization and datasets. Working papers are available upon request.


Park, Jaecheol, Arslan Aziz, Gene Moo Lee (2024) Do Incentivized Reviews Poison the Well? Evidence from a Natural Experiment at Amazon.com. R&R, Information Systems Research.

[WISE ’21, PACIS ’22, SCECR ’22, BU ’22, CIST ’22, BIGS ’22] #onlinereviews #incentives #platform #amazon


Lee, Myunghwan, Gene Moo Lee, Hasan Cavusoglu, Marc-David Seidel (2024) Strategic Competitive Positioning: A Structural Hole-based Firm-level Opportunity Construct for Information Systems Research. R&R, Journal of Management Information Systems.

[Visualization] [CIST ’19, DS ’21, KrAIS ’21]  #strategy #competition


Lee, Myunghwan, Timo Sturm, Gene Moo Lee (2024) Exploring the Influence of Machine Learning on Organizational Learning: An Empirical Analysis of Publicly Listed Organizations. Under Review.

[JUSWIS ’24, KrAIS ’24] #ai #org-learning #exploration #performance


Park, Jiyong, Myunghwan Lee, Yoonseock Son, Gene Moo Lee (2024) The New Industrial Revolution: AI, Labor Unions, and the Future of Work. Under Review.

[CIST ’24, WISE ’24] #ai #labor #unionization #value


Zhang, Xiaoke, Mi Zhou, Gene Moo Lee (2024) AI Voice in Online Video Platforms: A Multimodal Perspective on Content Creation and Consumption. Under Review.

[DS ’22, WITS ’22, KrAIS ’23, CSWIM ’23, KrAIS ’23, CIST ’23] [API Sponsored by Ensemble Data] #AI #video #creativity #TTS #tiktok


Zhang, Xiaoke, Myunghwan Lee, Mi Zhou, Gene Moo Lee (2024) News Quality vs. Promptness: Investigating Large Language Models’ Impact on the Institutional Press. Under Review.

[DS ’24, CIST ’24] #ai #journalism #llm


Park, Jaecheol, Myunghwan Lee, Gene Moo Lee (2024) The Effect of Mobile Device Management on Work-from-home Productivity: Insights from U.S. Public Firms. Preparing for Journal Submission.

[MSISR ’23, KrAIS ’23, WeB ’23, BIGS ’23, AOM ’24] #mobile #resilience #productivity


Park, Jaecheol, Myunghwan Lee, J. Frank Li, Gene Moo Lee (2024) Unpacking the AI Transformation: The Impact of AI Strategies on Firm Performance from the Dynamic Capabilities Perspective. Preparing for Journal Submission.

[CIST ’24, INFORMS ’24, KrAIS ’24] #ai #strategy #product #process #value


Kwon, Soonjae, Gene Moo Lee, Dongwon Lee, Sunghyuk Park (2024) Seeing the Unseen: The Effects of Implicit Representation in an Online Dating Platform.

[DS ’21, WITS ’21, ICIS ’22, WITS ’24] #genAI #matching #onlinedating


Lee, Myunghwan, Gene Moo Lee, Donghyuk Shin, Sang-Pil Han (2022) Robots Serve Humans? Understanding the Economic and Societal Impacts of AI Robots in the Service Industry.

[WITS ’20, KrAIS ’20, DS ’22, BIGS ’22] #AI #servicerobots #restaurants


Song, Victor, Hasan Cavusoglu, Li Zhi Ma, Gene Moo Lee (2023) IT Risk and Stock Price Crashes.

[HICSS ’20]

 


Inactive working papers


Lee, Myunghwan, Victor Cui, Gene Moo Lee (2023) Disrupt with AI: The Impact of Deep Learning Capabilities on Exploratory Innovation. [AOM ’23, CIST ’23]

Lee, Myunghwan, Gene Moo Lee (2022) Ideas are Easy but Execution is Everything: Measuring the Impact of Stated AI Strategies and Capability on Firm Innovation Performance. [DS ’22]

Schulte-Althoff, Matthais, Daniel Fürstenau, Gene Moo Lee, Hannes Rothes, Robert Kauffman (2022) What Fuels Growth? A Comparative Analysis of the Scaling Intesity of AI Start-ups [HICSS ’21, WITS ’22]

Cao, Rui, Gene Moo Lee, Hasan Cavusoglu (2021) Corporate Social Network Analysis: A Deep Learning Approach. [WITS ’20, DS ’21] [Research demo site]

Park, Sungho, Gene Moo Lee, Donghyuk Shin, Sang-Pil Han (2022) When Does Congruence Matter for Pre-roll Video Ads? The Effect of Multimodal, Ad-Content Congruence on the Ad Completion. [INFORMS ’20, AIMLBA ’20, WITS ’20]

Schulte-Althoff, Matthias, Kai Schewina, Gene Moo Lee, Daniel Fürstenau (2021) On the Heterogeneity of Startup Tech Stacks. [HICSS ’21]

Koh, Yumi, Gea M. Lee, Gene Moo Lee (2023) Price Competition and Active or Inactive Consumer Search. [APIOC ’19, EARIE ’23]

Bera, Debalina, Gene Moo Lee, Dan J. Kim (2024) Anatomy of Phishing Tactics and Susceptibility: An Investigation of the Dynamics of Phishing Tactics and Contextual Traits in Susceptibility.

Lee, Gene Moo, James Naughton, Xin Zheng, Dexin Zhou (2020) Predicting Litigation Risk via Machine Learning. [CFMA ’19] [Litigation risk score data 1996-2015]


Disclaimer: Some of the images on the page are generated by DALL-E 2.