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Patent Network Analysis and Quadratic Assignment Procedures to Identify the Convergence of Robot Technologies

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  • Woo Jin Lee
  • Won Kyung Lee
  • So Young Sohn

Abstract

Because of the remarkable developments in robotics in recent years, technological convergence has been active in this area. We focused on finding patterns of convergence within robot technology using network analysis of patents in both the USPTO and KIPO. To identify the variables that affect convergence, we used quadratic assignment procedures (QAP). From our analysis, we observed the patent network ecology related to convergence and found technologies that have great potential to converge with other robotics technologies. The results of our study are expected to contribute to setting up convergence based R&D policies for robotics, which can lead new innovation.

Suggested Citation

  • Woo Jin Lee & Won Kyung Lee & So Young Sohn, 2016. "Patent Network Analysis and Quadratic Assignment Procedures to Identify the Convergence of Robot Technologies," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-16, October.
    • Handle: RePEc:plo:pone00:0165091
    DOI: 10.1371/journal.pone.0165091
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    3. Ben Zhang & Xin Liu, 2024. "Technology Proximity Mechanism and Collaborative Innovation Orientation: How to Coordinate Multiple Subsidiaries’ Innovation Strategies?," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 706-731, March.
    4. Bo Kyeong Lee & So Young Sohn, 2017. "Exploring the effect of dual use on the value of military technology patents based on the renewal decision," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1203-1227, September.
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    6. Zhenfu Li & Yixuan Wang & Zhao Deng, 2022. "Research on Evolution Characteristics and Factors of Nordic Green Patent Citation Network," Sustainability, MDPI, vol. 14(13), pages 1-21, June.
    7. Kose, Toshihiro & Sakata, Ichiro, 2019. "Identifying technology convergence in the field of robotics research," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 751-766.
    8. Suh, Jung Woo & Sohn, So Young & Lee, Bo Kyeong, 2020. "Patent clustering and network analyses to explore nuclear waste management technologies," Energy Policy, Elsevier, vol. 146(C).
    9. Kim, Tae San & Sohn, So Young, 2020. "Machine-learning-based deep semantic analysis approach for forecasting new technology convergence," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    10. Koopo Kwon & Sungchan Jun & Yong-Jae Lee & Sanghei Choi & Chulung Lee, 2022. "Logistics Technology Forecasting Framework Using Patent Analysis for Technology Roadmap," Sustainability, MDPI, vol. 14(9), pages 1-30, April.
    11. Won Sang Lee & So Young Sohn, 2017. "Identifying Emerging Trends of Financial Business Method Patents," Sustainability, MDPI, vol. 9(9), pages 1-21, September.
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    13. Yaya Li & Yongtao Peng & Jianqiang Luo & Yihan Cheng & Eleonora Veglianti, 2019. "Spatial-temporal variation characteristics and evolution of the global industrial robot trade: A complex network analysis," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-14, September.
    14. Arho Suominen & Ozgur Dedehayir, 2017. "Pathways To A Drug: A Mixed Methods Analysis Of Emergence," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 21(08), pages 1-17, December.

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