Our research group is focusing 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.
Economic and Societal Impacts of AI and IT
Cui, Victor, Gene Moo Lee, Myunghwan Lee (2023) Go beyond the Local Search: Understanding the Impact of AI Capabilities on Exploratory Innovation, Research-in-Progress.
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, Research-in-Progress.
Zhang, Xiaoke, Mi Zhou, Gene Moo Lee (2022) How Does AI-Generated Voice Affect Online Content Creation? Evidence from TikTok, Under Review. [Submitted: Dec 9, 2022]
[DS 2022, WITS 2022, ISMS MKSC 2023] [API by Ensemble Data]
Park, Jaecheol, Myunghwan Lee, Gene Moo Lee (2023) Mobile Resilience: The Effect of Mobile Device Management on Firm Performance during the COVID-19 Pandemic, Work-in-Progress.
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, Research-in-Progress.
[WITS 2020, KrAIS 2020, DS 2022, BIGS 2022]
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, Working Paper. [Last update: Aug 3, 2022]
[HICSS 2021, WITS 2022]
Data Analytics Methods and Frameworks
Lee, Myunghwan, Gene Moo Lee, Hasan Cavusoglu, Marc-David Seidel (2022) Strategic Competitive Positioning: An Unsupervised Structural Hole-based Firm-specific Measure, Under Review. [Submitted: Dec 7, 2022]
[CIST 2019, DS 2021, KrAIS 2021, INFORMS 2022] [Interactive viz]
Kwon, Soonjae, Sunghyuk Park, Gene Moo Lee, Dongwon Lee (2022) Learning Faces to Predict Matching Probability in an Online Dating Market, In Proceedings of International Conference on Information Systems (ICIS) 2022.
[DS 2021, WITS 2021, ICIS 2022]
Cao, Rui, Gene Moo Lee, Hasan Cavusoglu (2021) Corporate Social Network Analysis: A Deep Learning Approach, Research-in-Progress.
[WITS 2020, DS 2021] [Research demo site]
Empirical Analysis of Data-intensive Platforms
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, Working Paper. [Last update: Jan 29, 2023]
[INFORMS 2020, AIMLBA 2020, WITS 2020]
Park, Jaecheol, Arslan Aziz, Gene Moo Lee (2022) Do Incentivized Reviews Poison the Well? Evidence from a Natural Experiment at Amazon.com, Working Paper.
[WISE 2021, PACIS 2022, SCECR 2022, BU 2022, CIST 2022, BIGS 2022]
Schulte-Althoff, Matthias, Kai Schewina, Gene Moo Lee, Daniel Fürstenau (2021) On the Heterogeneity of Startup Tech Stacks, Working Paper [Latest version: May 20, 2021]
Koh, Yumi, Gea M. Lee, Gene Moo Lee (2021) Price Competition and Inactive Search, Working Paper [Latest version: June 16, 2021]
IT Security and Risk
Song, Victor, Hasan Cavusoglu, Li Zhi Ma, Gene Moo Lee (2022) IT Risk and Stock Price Crashes, Major Revision, Information Systems Research. [Decision: Dec 18, 2022]
Lee, Gene Moo, James Naughton, Xin Zheng, Dexin Zhou (2020) Predicting Litigation Risk via Machine Learning, Working Paper. [Latest version: Dec 1, 2020]
[CFMA 2019] [Litigation risk score data 1996-2015]
Disclaimer: Some of the images on the page are generated by DALL-E 2.