Jae Young Choi

Prof. Jae Young Choi

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Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 June 2019 in Telematics and Informatics
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JLJunghyo Lee
Junghyo Lee
JKJunghun Kim
Junghun Kim
JCJae Young Choi
Jae Young Choi

19 May 2015 in Scientometrics
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SJSeongkyoon Jeong
Seongkyoon Jeong
JKJong-Chan Kim
Jong-Chan Kim
JCJae Young Choi
Jae Young Choi

3 November 2013 in Science and Public Policy
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SJSeongkyoon Jeong
Seongkyoon Jeong
JCJae Young Choi
Jae Young Choi
JKJang-Yun Kim
Jang-Yun Kim
International collaboration in research activities has been highlighted because it offers higher productivity and has a greater impact than non-international collaboration. Given the importance of international collaboration, researchers make strategic decisions on their collaboration modes in the light of their environments and the expected trade-offs, since long-distance research collaboration entails both costs and benefits. By using national data at the project level, this paper examines the possible factors in international collaboration in various research areas, mainly focusing on research activities by universities. Our empirical results suggest that substantial financial and attentional resources, academic excellence, individual motivation, and active informal communication play significant roles in accomplishing international collaboration. Additionally, this paper refines the understanding of the role of communication and policy in ensuring the most effective use of research resources, helping research managers to promote collaboration in an appropriate decision-making context.

6 August 2011 in Scientometrics
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SJSeongkyoon Jeong
Seongkyoon Jeong
JCJae Young Choi
Jae Young Choi
JKJaeyun Kim
Jaeyun Kim

25 August 2015 in Sustainability
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JCJae Young Choi
Jae Young Choi
SJSeongkyoon Jeong
Seongkyoon Jeong
KKKyunam Kim
Kyunam Kim
Technology convergence indicates that technologies of different application areas are converted into a new and common unity of technology. Its range spans from inter-field, whereby technologies are converged between heterogeneous fields in homogeneous sector, to a wider inter-sector, whereby technologies belong to heterogeneous technology sector are converged. This paper determined the definition of technology convergence from previous literature and classified patents into technology category depending on patent information. Furthermore, we empirically measure technology convergence degree based on co-classification analysis and estimate its diffusion trend at the entire technology domain level by using overall 1,476,967 of patents filed to the KIPO (Korean Intellectual Property Office) from 1998 to 2010. As a result, potential size and growth rate of technology convergence are varied by both technology and type of technology convergence, i.e., inter-field and inter-sector technology convergence. Diffusion pattern of inter-sector technology convergence appears as the more various form than that of inter-field technology convergence. In a relationship between potential size and growth rate of technology convergence, growth rate of technology convergence is in inverse proportion to potential size of technology convergence in general. That is, the faster the growth rate of technology convergence, the smaller the potential size of technology convergence. In addition, this paper found that technology convergence of the instrument and chemistry sector is actively progressing in both inter-field and inter-sector convergence, while the technologies related to Information and Communication Technology (ICT) in electrical engineering sector have relatively mature progress of technology convergence, especially in inter-sector technology convergence.

8 July 2016 in Sustainability
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KKKyunam Kim
Kyunam Kim
JJJung-Kyu Jung
Jung-Kyu Jung
JCJae Young Choi
Jae Young Choi
The characteristics of the smart city industry and its effects on the national economy of Korea are investigated using input-output analysis. The definition and industrial classification of a smart city are established using the Delphi technique for experts in various fields, from information and communication technologies (ICT) to governmental policies for urban matters. The results of the analysis, including the production, value added and employment induction effects, show that the smart city industry has intermediate characteristics between ICT and urban construction industries, indicating that acquisition of the competitive edge of both the ICT and construction industries is the key to the success of the smart city industry. The crucial industries related to the smart city industry are identified based on an analysis of the forward and backward linkage effects, the results of which suggest the importance of the relevant service industries. The economic effects on the national economy induced by the governmental program for smart city demonstration are estimated using input-output analysis results. Overall, the results of this study indicate that facilitation of the smart city industry plays a key role not only in the sustainable city, but also in the growth of the national economy.