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The structure and change of the research collaboration network in Korea (2000–2011): network analysis of joint patents

Author

Listed:
  • Hochull Choe

    (Korea Research Institute of Chemical Technology (KRICT))

  • Duk Hee Lee

    (Korea Advanced Institute of Science and Technology (KAIST))

Abstract

This study is to examine the structure, characteristics, and change of a research collaboration network using co-assignee information of joint patents in Korea. The study was conducted in three stages: data collection, network construction, and network analysis. For network analysis, network topological analysis, node centrality analysis, and block modeling were performed in sequence. The analysis results revealed that the network has small-world properties. The results also showed that while government-sponsored research institutes (GRIs) played a role as a hub and bridge in the network in the early 2000s, universities gradually took their place to play a key role as a hub and bridge in the network. In addition, the block modeling analysis indicated that while, in the early 2000s, GRI-centered network density was shown to be high, the network density became concentrated around universities after 2004, and this tendency intensified after 2008. Bearing in mind a lack of empirical studies on inter-organizational research collaboration networks using patent data, this study made an academic contribution by specifically analyzing the structure and change of research collaboration networks by targeting Korea’s major innovative actors. From the policy perspective, it provides important implications for figuring out the effects of university–industry–GRI (UIG) collaboration policies implemented so far, and can be of assistance for making evidence-based policies to build up a more effective UIG collaboration network or establish a new national science and technology innovation system.

Suggested Citation

  • Hochull Choe & Duk Hee Lee, 2017. "The structure and change of the research collaboration network in Korea (2000–2011): network analysis of joint patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 917-939, May.
    • Handle: RePEc:spr:scient:v:111:y:2017:i:2:d:10.1007_s11192-017-2321-2
    DOI: 10.1007/s11192-017-2321-2
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    References listed on IDEAS

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    6. Essén, Anna & Wennberg, Karl & Krohwinkel, Anna, 2022. "Assessing Whether Mission-Driven Innovation Makes a Difference: Mission Impossible? Developing a Guiding Framework for the Evaluation of Five Mission Driven Environments for Health in Sweden," SSE Working Paper Series in Business Administration 2022:2, Stockholm School of Economics.
    7. Xi Yang & Xiang Yu, 2020. "Preventing Patent Risks in Artificial Intelligence Industry for Sustainable Development: A Multi-Level Network Analysis," Sustainability, MDPI, vol. 12(20), pages 1-21, October.
    8. Yindan Ye & Kevin De Moortel & Thomas Crispeels, 2020. "Network dynamics of Chinese university knowledge transfer," The Journal of Technology Transfer, Springer, vol. 45(4), pages 1228-1254, August.
    9. Wei Yang & Xiang Yu & Dian Wang & Jinrui Yang & Ben Zhang, 2021. "Spatio-temporal evolution of technology flows in China: patent licensing networks 2000–2017," The Journal of Technology Transfer, Springer, vol. 46(5), pages 1674-1703, October.
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    11. Shu-Hao Chang, 2022. "Examining Key Technologies Among Academic Patents Through an Analysis of Standard-Essential Patents," SAGE Open, , vol. 12(3), pages 21582440221, July.

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