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http://dx.doi.org/10.14400/JDC.2022.20.4.093

An analysis of operation status depending on the characteristics of R&D projects in Sciences and Engineering universities  

Lee, Sang-Soog (Department of Public Administration, Korea University)
Yoo, Inhyeok (AI solution team, Future Innovation Center, Hanwah Systems/ICT)
Kim, Jinhee (Center for University Innovation Support, Yonsei University)
Publication Information
Journal of Digital Convergence / v.20, no.4, 2022 , pp. 93-100 More about this Journal
Abstract
This study aimed to understand the current status of science and engineering university(SEU) R&D operations depending on the research project characteristics(e.g., stages and characteristics), then provide implications for future university R&D support systems and related policies. Hence, an online survey targeting SEU R&D recipients was conducted between October 4th to November 5th, 2021. Analyzing 445 valid data using the Apriori algorithm, 16 association rules for R&D operation according to the research project characteristics show that regardless of research characteristics, SEU's R&D projects, particularly in applied research, were funded or operated under the leadership of government or public institutions. For basic research, individual researchers had a higher level of autonomy in determining research topics; yet, they had a short duration (3 years) and a unit of evaluation period of more than 3 years. These findings can be empirical evidence for revealing the relationship among various variables in operating SEUs' R&D.
Keywords
Science and engineering research project; science and engineering research and development; science and engineering research operation; Apriori algorithms; association rules analysis;
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