Research

My research objective is to advance Business Analytics using Artificial Intelligence approaches (e.g., NLP, computer vision, machine learning, deep learning) thereby creating value from big data in data-intensive platforms (e.g., mobile, social media, advertising) and examining the impacts of AI in business and society.
Refereed Journal Publications (N=10) [Google Scholar] [SSRN] [DBLP] [ORCiD]

Han, Kookyoung, Jin Hyuk Choi, Yunsik Choi, Gene Moo Lee, Andrew B. Whinston (2023) Security Defense against Long-term and Stealthy Cyberattacks, Decision Support Systems, 166: 113912.

[NSF Award] [Best Paper Award at KrAIS 2017]

Kwark, Young, Gene Moo Lee, Paul A. Pavlou, Liangfei Qiu (2021) On the Spillover Effects of Online Product Reviews on Purchases: Evidence from Clickstream Data, Information Systems Research, 32(3): 895-913.

[Data awarded by Wharton Customer Analytics Initiative]

Shin, Donghyuk, Shu He, Gene Moo Lee, Andrew B. Whinston, Suleyman Cetintas, Kuang-Chih Lee (2020) Enhancing Social Media Analysis with Visual Data Analytics: A Deep Learning Approach, MIS Quarterly 44(4): 1459-1492. 

[Literature on visual data analytics] [MISQ curation]

Zhuang, Yunhui, Yunsik Choi, Shu He, Alvin C. M. Leung, Gene Moo Lee, Andrew B. Whinston (2020) Understanding Security Vulnerability Awareness, Firm Incentives, and ICT Development in Pan-Asia, Journal of Management Information Systems 37(3): 668-693.

[Literature on cybersecurity] [NSF Award]

Lee, Gene Moo, Shu He, Joowon Lee, Andrew B. Whinston (2020) Matching Mobile Applications for Cross-Promotion, Information Systems Research 31(3): 865-891.

[Data awarded by IGAWorks]

Song, Reo, Ho Kim, Gene Moo Lee, Sungha Jang (2019) Does Deceptive Marketing Pay? The Evolution of Consumer Sentiment Surrounding a Pseudo-Product-Harm Crisis, Journal of Business Ethics 158(3): 743-761.

[Featured in The Globe and Mail]

Park, Sunyeong, Gene Moo Lee, You-Il Kim, Jinny Seo (2018) Development of Topic Trend Analysis Model for Industrial Intelligence using Public Data, Journal of Technology Innovation 26(4): 199-232.

[Research demo site] 

Lee, Gene Moo, Liangfei Qiu, Andrew B. Whinston (2016) A Friend Like Me: Modeling Network Formation in a Location-Based Social Network, Journal of Management Information Systems 33(4): 1008-1033.

[Best Paper Nomination at HICSS 2016]

He, Shu, Gene Moo Lee, Sukjin Han, Andrew B. Whinston (2016) How Would Information Disclosure Influence Organizations’ Outbound Spam Volume? Evidence from a Field Experiment, Journal of Cybersecurity 2(1): 99-118.

[NSF Award]

Shi, Zhan, Gene Moo Lee, Andrew B. Whinston (2016) Toward a Better Measure of Business Proximity: Topic Modeling for Industry Intelligence, MIS Quarterly 40(4): 1035-1056.

[Research demo site] [MISQ curation]

  • I regularly present papers at IS conferences such as CIST, ICIS, WITS, DS, KrAIS, and HICSS. Before switching to the IS field, I published papers at Computer Science conferences.
  • Project reports, unpublished manuscripts, lecture notes
  • My work was covered in media outlets (e.g., The Globe and Mail, Huffington Post).
Working Papers (N=11) (* equal contribution)
  1. Lee M, Lee GM, Cavusoglu H, Seidel MDL (2022) Strategic Competitive Positioning: An Unstructured Structural Hole-based Firm-specific Measure, Reject and Resubmit, MIS Quarterly. [Last update: Dec 7, 2022]
  2. Zhang X, Zhou M, Lee GM (2022) How Does AI-Generated Voice Affect Online Content Creation? Evidence from TikTok, Reject and Resubmit, Management Science. [Last update: Dec 9, 2022]
  3. Song V, Cavusoglu H, Ma MLZ, Lee GM, (2022) IT Risk and Stock Price Crashes, Major Revision, Information Systems Research. [Decision: Dec 18, 2022]
  4. Yuan L, Lee GM, Xiao H, Ye Q (2023) From Spacing to Scheduling: The Effect of Seller Posting Time Strategies for Short Video Advertising, Under Review. [Submit: Apr 26, 2023]
  5. Park J, Aziz A, Lee GM (2022) Do Incentivized Reviews Poison the Well? Evidence from a Natural Experiment at Amazon.com, CIST 2022. [Last update: Nov 2022]
  6. Schulte-Althoff, M., Lee, G. M., Rothes, H., Kauffman, R., Fürstenau, D. (2022) What Fuels Growth? A Comparative Analysis of the Scaling Intesity of AI Start-ups, WITS 2022. [Latest update: Aug 3, 2022]
  7. Kwon S, Park S, Lee GM, Lee D (2022) Learning Faces to Predict Matching Probability in an Online Dating Market, ICIS 2022. [Last update: Dec 2022]
  8. Park S, Lee GM, Shin D, Han SP (2022) When Does Congruence Matter for Pre-roll Video Ads? The Effect of Multimodal, Ad-Content Congruence on the Ad Completion, Working Paper. [Latest update: June 27, 2022]
  9. Koh Y, Lee GM, Lee GM (2021) Price Competition and Inactive Search, Working Paper. [Latest update: June 16, 2021]
  10. Lee GM*, Naughton J*, Zheng X*, Zhou D* (2020) Predicting Litigation Risk via Machine Learning, Working Paper. [Latest update: Dec 1, 2020]
  11. Schulte-Althoff M, Schewina K., Lee GM, Fürstenau D. (2021) On the Heterogeneity of Startup Tech Stacks, Working Paper [Latest update: May 20, 2021]
Invited Presentations [Full Information]
  • 2023: Yonsei Univ, Dalhousie, Sungkyunkwan, POSTECH, Kyung Hee,
  • 2022 (8): Arizona, George Mason, KAIST, Hanyang, Vancouver KDD, Kyung Hee, McGill, Consulate General of Korea in Vancouver
  • 2021 (11): HKUST, Saarland, Maryland, Korea Univ, American Univ, Kyung Hee, Chung-Ang, NUS, Tennesse Chattanooga, Rochester, KAIST, Yonsei Univ
  • 2020 (5): Rutgers, UBC Commerce Scholars Program, UBC Sauder, Univ of Washington, AKCSE Young Generation Forum
  • 2019 (2): UBC AI Research Centre (CAIDA), Simon Fraser
  • 2018 (4): UBC Information School, Rutgers, Arizona State, Korea Univ, Korea Insurance Research Institute (KIRI)
  • 2017 (4): Univ of North Texas, UT Arlington, Consulate General of Republic of Korea, Korea Institute of Science and Technology Information (KISTI)
  • 2016 (10): UT Arlington, SKKU, Korea Univ, Hanyang, Kyung Hee, Chung-Ang, Yonsei, Seoul National, Kyungpook National, UBC Sauder
  • 2015 (1): KAIST
  • 2014 (7): Notre Dame, Temple, UC Irvine, Indiana, UT Dallas, Minnesota, UT Arlington

Resources