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Network structure of innovation: can brokerage or closure predict patent quality?

Author

Listed:
  • Jyun-Cheng Wang

    (National Tsing Hua University)

  • Cheng-hsin Chiang

    (National Tsing Hua University)

  • Shu-Wei Lin

    (I-PAT)

Abstract

Patents are important intellectual assets for companies to defend or to claim their technological rights. To control R&D cost, companies should carefully examine their patents by patent quality. Approaches to evaluating patent quality are mostly a posteriori uses of factual information of patent quality. This paper examined whether patent quality can be predicted a priori, i.e., during the early years after a patent is granted, by analyzing information embedded in a network of patent citations. Social network analysis was applied to analyze two network positions occupied by a patent, brokerage and closure to determine whether either position is a good predictor of patent quality. Patent renewal decisions and forward citations were adopted as surrogates of patent quality. The analytical results showed that forward citations can be positively predicted by the brokerage position and negatively predicted by the closure position in the early and mature stages. Renewal decisions can be negatively predicted by the brokerage position in the early stage, and the closure position influences the renewal decision in a different way in the early and mature stages. These analytical results imply that a company should focus on developing patents that bridge different technologies as its technological developments reach maturity.

Suggested Citation

  • Jyun-Cheng Wang & Cheng-hsin Chiang & Shu-Wei Lin, 2010. "Network structure of innovation: can brokerage or closure predict patent quality?," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(3), pages 735-748, September.
  • Handle: RePEc:spr:scient:v:84:y:2010:i:3:d:10.1007_s11192-010-0211-y
    DOI: 10.1007/s11192-010-0211-y
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    6. Kuang-Cheng Chai & Yang Yang & Zhiyong Sui & Ke-Chiun Chang, 2020. "Determinants of highly-cited green patents: The perspective of network characteristics," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-13, October.
    7. Jiang, Hongxun & Fan, Shaokun & Zhang, Nan & Zhu, Bin, 2023. "Deep learning for predicting patent application outcome: The fusion of text and network embeddings," Journal of Informetrics, Elsevier, vol. 17(2).
    8. Way-Ren Huang & Chia-Jen Hsieh & Ke-Chiun Chang & Yen-Jo Kiang & Chien-Chung Yuan & Woei-Chyn Chu, 2017. "Network characteristics and patent value—Evidence from the Light-Emitting Diode industry," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-14, August.
    9. De Paulo, A.F. & Porto, G.S., 2023. "Unveiling the cooperation dynamics in the photovoltaic technologies’ development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
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    12. Xuan Liu & Shan Jiang & Hsinchun Chen & Catherine A. Larson & Mihail C. Roco, 2015. "Modeling knowledge diffusion in scientific innovation networks: an institutional comparison between China and US with illustration for nanotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1953-1984, December.
    13. Beaudry, Catherine & Schiffauerova, Andrea, 2011. "Impacts of collaboration and network indicators on patent quality: The case of Canadian nanotechnology innovation," European Management Journal, Elsevier, vol. 29(5), pages 362-376.
    14. Gohar Feroz Khan, 2013. "Social media-based systems: an emerging area of information systems research and practice," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(1), pages 159-180, April.
    15. Hsu, David W.L. & Yuan, Benjamin J.C., 2013. "Knowledge creation and diffusion of Taiwan's universities: Knowledge trajectory from patent data," Technology in Society, Elsevier, vol. 35(3), pages 172-181.
    16. Chih-cheng Lo & Hsin-Chuan Cho & Pin-Wei Wang, 2020. "Global R&D Collaboration in the Development of Nanotechnology: The Impact of R&D Collaboration Patterns on Patent Quality," Sustainability, MDPI, vol. 12(15), pages 1-12, July.
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    18. Tai Quan Peng & Zhen-Zhen Wang, 2013. "Network closure, brokerage, and structural influence of journals: a longitudinal study of journal citation network in Internet research (2000–2010)," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(3), pages 675-693, December.

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