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Spatial characteristics of joint application networks in Japanese patents

Author

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  • Inoue, Hiroyasu
  • Souma, Wataru
  • Tamada, Schumpeter

Abstract

Technological innovation has extensively been studied to make firms sustainable and more competitive. Within this context, the most important recent issue has been the dynamics of collaborative innovation among firms. We therefore investigated a patent network, especially focusing on its spatial characteristics. The results can be summarized as follows. (1) The degree distribution in a patent network follows a power law. A firm can then be connected to many firms via hubs connected to the firm. (2) The neighbors’ average degree has a null correlation, but the clustering coefficient has a negative correlation. The latter means that there is a hierarchical structure and bridging different modules may shorten the paths between the nodes in them. (3) The distance of links not only indicates the regional accumulations of firms, but the importance of time it takes to travel, which plays a key role in creating links. (4) The ratio of internal links in cities indicates that we have to consider the existing links firms have to facilitate the creation of new links.

Suggested Citation

  • Inoue, Hiroyasu & Souma, Wataru & Tamada, Schumpeter, 2007. "Spatial characteristics of joint application networks in Japanese patents," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(1), pages 152-157.
    • Handle: RePEc:eee:phsmap:v:383:y:2007:i:1:p:152-157
    DOI: 10.1016/j.physa.2007.04.096
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    Citations

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    Cited by:

    1. Noriko Yoda & Kenichi Kuwashima, 2020. "Triple Helix of University–Industry–Government Relations in Japan: Transitions of Collaborations and Interactions," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 11(3), pages 1120-1144, September.
    2. Inoue, Hiroyasu & Souma, Wataru & Tamada, Schumpeter, 2010. "Analysis of cooperative research and development networks on Japanese patents," Journal of Informetrics, Elsevier, vol. 4(1), pages 89-96.
    3. Xia Gao & Jiancheng Guan, 2009. "Networks of scientific journals: An exploration of Chinese patent data," Scientometrics, Springer;Akadémiai Kiadó, vol. 80(1), pages 283-302, July.
    4. Weiwei Liu & Yuan Tao & Zhile Yang & Kexin Bi, 2019. "Exploring and Visualizing the Patent Collaboration Network: A Case Study of Smart Grid Field in China," Sustainability, MDPI, vol. 11(2), pages 1-18, January.
    5. Inoue, Hiroyasu, 2014. "A two-layer team-assembly model for invention networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 181-188.
    6. Yilei Pan & Mengying Chang & Shumin Feng & Dongsheng Hao, 2023. "Modeling and Complex Characteristics of Urban Subway Co-Opetition Network: A Case Study of Wuhan," Sustainability, MDPI, vol. 15(1), pages 1-17, January.

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