Dr. Professor Sang-Joon Lee is a faculty member at the School of Business Administration, Chonnam National University in Gwangju, South Korea, where he has served since February 24, 2007. His research interests include customer segmentation, machine learning, ESG analysis, and industrial control systems. He is a co-author of the journal article “Tailoring Customer Segmentation Strategies for Luxury Brands in the NFT Market – The Case of SUPERGUCCI” published in the Journal of Retailing and Consumer Services (2025), along with Qiuying Chen and Beom-Jin Choi. He also co-authored the conference paper “Predicting ESG Ratings by Machine Learning and Analyzing Influencing Factors by XAI” (2024) with Jeong-Cheol Choi and Qiuying Chen. In 2023, he contributed to the article “GRU-based Buzzer Ensemble for Abnormal Detection in Industrial Control Systems” in Computers, Materials & Continua, with Hyo-Seok Kim, Chang-Gyoon Lim, and Yong-Min Kim. Further information on his academic work is available at his ORCID profile: https://orcid.org/0000-0002-0526-3614.
Dr. Professor Sang-Joon Lee is a faculty member at the School of Business Administration, Chonnam National University in Gwangju, South Korea, where he has served since February 24, 2007. His research interests include customer segmentation, machine learning, ESG analysis, and industrial control systems. He is a co-author of the journal article “Tailoring Customer Segmentation Strategies for Luxury Brands in the NFT Market – The Case of SUPERGUCCI” published in the Journal of Retailing and Consumer Services (2025), along with Qiuying Chen and Beom-Jin Choi. He also co-authored the conference paper “Predicting ESG Ratings by Machine Learning and Analyzing Influencing Factors by XAI” (2024) with Jeong-Cheol Choi and Qiuying Chen. In 2023, he contributed to the article “GRU-based Buzzer Ensemble for Abnormal Detection in Industrial Control Systems” in Computers, Materials & Continua, with Hyo-Seok Kim, Chang-Gyoon Lim, and Yong-Min Kim. Further information on his academic work is available at his ORCID profile: https://orcid.org/0000-0002-0526-3614.