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Choe H.,Korea Research Institute of Chemical Technology | Choe H.,KAIST | Lee D.H.,KAIST | Seo I.W.,KAIST | Kim H.D.,Daegu Digital Industry Promotion Agency
Renewable and Sustainable Energy Reviews | Year: 2013

The goal of this work is to understand the structure and characteristics of technological knowledge flows between countries, institutions, and technology fields in the field of organic photovoltaic cells. This study was conducted in three stages: data collection, network creation, and network analysis. For network analysis, network visualization, network topological analysis, and node centrality analysis were performed in sequence. The network topological analysis revealed that all three citation networks, i.e., countries, institutions, and technology fields, are scale-free networks that follow the power law and display, to a greater or lesser extent, a more efficient knowledge transfer capability than a random network of the same size. The node centrality analysis showed that the United States, Japan, and Germany are the most important citation centers in the country citation network, while Boeing, Konarka Technologies, Eastman Kodak, and Sharp are the most important in the institution citation network, and the U.S. patent classification (USPC) classes of 136, 257, and 428 are the most important in the technology field citation network, each playing critical roles in each the network as core nodes. In this study, we applied various concepts of centrality to the analysis of individual nodes and found that the results from the network topological analysis and the node centrality analysis are not significantly different. The proposed analysis framework in this paper is applicable to different science and technology domains. © 2013 Elsevier Ltd. Source

Lee D.H.,Korea Advanced Institute of Science and Technology | Seo I.W.,Korea Advanced Institute of Science and Technology | Choe H.C.,Korea Research Institute of Chemical Technology | Kim H.D.,Daegu Digital Industry Promotion Agency
Scientometrics | Year: 2012

This study examines the impact of collaborating patterns on the R&D performance of public research institutions (PRIs) in Korea's science and engineering fields. For the construction of R&D collaborating networks based on the co-authorship data of 127 institutions in Scopus, this paper proposes four types of collaborations by categorizing network analyses into two dimensions: structural positions (density, efficiency, and betweeness centrality) and the relational characteristics of individual nodes (eigenvector and closeness centralities). To explore the research performance by collaboration type, we employ a data envelopment analysis window analysis of a panel of 23 PRIs over a 10-year period. Comparing the R&D productivities of each group, we find that the PRIs of higher productivity adhere to a cohesive networking strategy, retaining intensive relations with their existing partners. The empirical results suggest that excessively cohesive alliances might end up in 'lock-in' relations, hindering the exploitation of new opportunities for innovation. These findings are implicit in relation to the Korean Government's R&D policies on collaborating strategies to produce sustained research results with the advent of the convergence research era. © 2012 Akadémiai Kiadó, Budapest, Hungary. Source

Choe H.,Korea Research Institute of Chemical Technology | Lee D.H.,KAIST | Kim H.D.,Daegu Digital Industry Promotion Agency | Seo I.W.,Korea Research Institute of Standards and Science
Renewable and Sustainable Energy Reviews | Year: 2016

This paper identifies the structural properties of a technological knowledge network and the role of major organizations in the network, and analyzes actual contents of technological knowledge flows in terms of organization-technology linkage, by targeting the field of organic solar cells (OSC). Network analysis and matrix analysis methods are used to achieve these purposes. The results show the small-world effect exists in the technological knowledge network of OSCs, and the organizations with high betweenness centrality lead the technological knowledge flows. We also find technological knowledge in classes 136 and 313 flows relatively actively in key organizations network of OSCs. This means that technological knowledge regarding photoelectric batteries and electric lamp and discharge devices is mainly circulated between key organizations and indicates that the electronics or display sector will become a major consumer for early commercialization of OSCs. The target of analysis in this study is a patent citation network in the field of OSCs. Since we did not analyze all scientific publications, we cannot conclude that the results represent the entire flow of technological knowledge in that field. However, given that little attention has been paid to empirical studies of technological knowledge flows at the organizational level, this study makes an academic contribution by directly analyzing technological knowledge flows between organizations and presenting new taxonomic method based on centralities. The analytical process and methodology of this study, which include analysis of the structural properties of technological knowledge networks, matrix analysis and taxonomical grouping, and analysis of technological knowledge flows between key organizations, will be usefully applied to the analysis of technological knowledge networks in other fields. © 2015 Elsevier Ltd. Source

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