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Authors
Park, Jungryeol
Choi, Saesol
Feng, Yituo
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Funding
Funding for this research was provided by:
Electronics and Telecommunications Research Institute (24YF1110, 24YF1110)
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Article History
Received: 14 April 2024
Accepted: 26 August 2024
First Online: 3 September 2024
Declarations
:
: Not applicable.
: The publisher has the author’s permission to publish this paper.
: The authors declare no competing interests.
: JRP<sup>1</sup> is a researcher at the Electronics and Telecommunications Research Institute (ETRI), Technology Strategy Research Division. He received his Ph.D., M.S., and B.S. degrees in Management Information Systems (MIS) from Chungbuk National University. He has published papers related to machine learning and deep learning in several journals, including the Journal of Big Data, Scientific Reports, and PLOS ONE. His main areas of interest are machine learning, deep learning-based business prediction, and technology growth prediction. SSC<sup>2</sup> is a principal researcher in the Technology Strategy Research Division of the Electronics and Telecommunications Research Institute, Republic of Korea. He received his B.S. and M.S. degrees from KAIST. He has published papers in such journals as Online Information Review, Journal of Organizational and End User Computing, International Telecommunications Policy Review, and Korean Journal of Information Technology Applications and Management, and has presented at several IEEE-sponsored international conferences. His research interests include technology management, data driven policy, and IT user behavior. YTF<sup>3*</sup> earned both his Master’s and Doctorate degrees in Management Information Systems (MIS) from the Graduate School of Business at Chungbuk National University, South Korea. He currently works at Yunnan Minzu University in Information Management and Information Systems. Dr. Feng has made significant contributions to the academic community with his works published in esteemed SSCI and SCI journals. Additionally, he has served as a reviewer for various SSCI and SCI journals. His research encompasses machine learning, deep learning, data analytics, Structural Equation Modeling, personnel management, business forecasting, and link prediction.
