IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0165091.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0165091
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0165091&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0165091?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Si Hyung Joo & Yeonbae Kim, 2010. "Measuring relatedness between technological fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(2), pages 435-454, May.
    2. Tijssen, Robert J. W., 1992. "A quantitative assessment of interdisciplinary structures in science and technology: Co-classification analysis of energy research," Research Policy, Elsevier, vol. 21(1), pages 27-44, February.
    3. Giuditta Prato & Daniel Nepelski, 2014. "Global technological collaboration network: network analysis of international co-inventions," The Journal of Technology Transfer, Springer, vol. 39(3), pages 358-375, June.
    4. Guellec, Dominique & Pottelsberghe de la Potterie, Bruno v., 2000. "Applications, grants and the value of patent," Economics Letters, Elsevier, vol. 69(1), pages 109-114, October.
    5. Jun-Ping Qiu & Ke Dong & Hou-Qiang Yu, 2014. "Comparative study on structure and correlation among author co-occurrence networks in bibliometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1345-1360, November.
    6. Manuel Trajtenberg & Rebecca Henderson & Adam Jaffe, 1997. "University Versus Corporate Patents: A Window On The Basicness Of Invention," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 5(1), pages 19-50.
    7. Cantner, Uwe & Graf, Holger, 2006. "The network of innovators in Jena: An application of social network analysis," Research Policy, Elsevier, vol. 35(4), pages 463-480, May.
    8. Carpenter, Mark P. & Narin, Francis & Woolf, Patricia, 1981. "Citation rates to technologically important patents," World Patent Information, Elsevier, vol. 3(4), pages 160-163, October.
    9. Yonghan Ju & So Young Sohn, 2015. "Identifying patterns in rare earth element patents based on text and data mining," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 389-410, January.
    10. Ernst, Holger, 2003. "Patent information for strategic technology management," World Patent Information, Elsevier, vol. 25(3), pages 233-242, September.
    11. George A. Barnett & Han Woo Park & Ke Jiang & Chuan Tang & Isidro F. Aguillo, 2014. "A multi-level network analysis of web-citations among the world’s universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(1), pages 5-26, April.
    12. Jiancheng Guan & Yuan Shi, 2012. "Transnational citation, technological diversity and small world in global nanotechnology patenting," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(3), pages 609-633, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Enrico Santarelli & Jacopo Staccioli & Marco Vivarelli, 2023. "Automation and related technologies: a mapping of the new knowledge base," The Journal of Technology Transfer, Springer, vol. 48(2), pages 779-813, April.
    2. 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.
    3. Wu, Xuehui & Wu, Zhong & Hu, Jun, 2022. "Global competitiveness analysis of industrial robot technology innovations market layout using visibility graph," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    4. Inchae Park & Byungun Yoon, 2018. "Identifying Promising Research Frontiers of Pattern Recognition through Bibliometric Analysis," Sustainability, MDPI, vol. 10(11), pages 1-32, November.
    5. 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).
    6. 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.
    7. 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).
    8. 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.
    9. 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.
    10. Won Sang Lee & So Young Sohn, 2017. "Identifying Emerging Trends of Financial Business Method Patents," Sustainability, MDPI, vol. 9(9), pages 1-21, September.
    11. Aram Min & Ji-Hyun Lee, 2019. "A Conceptual Framework for the Externalization of Ecological Wisdom: The Case of Traditional Korean Gardens," Sustainability, MDPI, vol. 11(19), pages 1-17, September.
    12. 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.
    13. 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.
    14. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sungho Son & Nam-Wook Cho, 2020. "Technology Fusion Characteristics in the Solar Photovoltaic Industry of South Korea: A Patent Network Analysis Using IPC Co-Occurrence," Sustainability, MDPI, vol. 12(21), pages 1-19, October.
    2. Nils Omland, 2011. "Valuing Patents through Indicators," Chapters, in: Federico Munari & Raffaele Oriani (ed.), The Economic Valuation of Patents, chapter 7, Edward Elgar Publishing.
    3. Sergio Cuellar & Alberto Méndez-Morales & Milton M. Herrera, 2022. "Location Matters: a Novel Methodology for Patent’s National Phase Process," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(3), pages 2138-2163, September.
    4. Verhoeven, Dennis & Bakker, Jurriën & Veugelers, Reinhilde, 2016. "Measuring technological novelty with patent-based indicators," Research Policy, Elsevier, vol. 45(3), pages 707-723.
    5. Seongkyoon Jeong & Jong-Chan Kim & Jae Young Choi, 2015. "Technology convergence: What developmental stage are we in?," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 841-871, September.
    6. Manuel Acosta & Daniel Coronado & Esther Ferrándiz & Manuel Jiménez, 2022. "Effects of knowledge spillovers between competitors on patent quality: what patent citations reveal about a global duopoly," The Journal of Technology Transfer, Springer, vol. 47(5), pages 1451-1487, October.
    7. Altuntas, Serkan & Dereli, Turkay & Kusiak, Andrew, 2015. "Analysis of patent documents with weighted association rules," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 249-262.
    8. Roman Jurowetzki, 2015. "Unpacking Big Systems - Natural Language Processing meets Network Analysis. A Study of Smart Grid Development in Denmark," SPRU Working Paper Series 2015-15, SPRU - Science Policy Research Unit, University of Sussex Business School.
    9. Nicolas van Zeebroeck & Bruno van Pottelsberghe de la Potterie, 2011. "Filing strategies and patent value," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 20(6), pages 539-561, February.
    10. Pereira, Cristiano Gonçalves & Lavoie, Joao Ricardo & Garces, Edwin & Basso, Fernanda & Dabić, Marina & Porto, Geciane Silveira & Daim, Tugrul, 2019. "Forecasting of emerging therapeutic monoclonal antibodies patents based on a decision model," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 185-199.
    11. Nicolas van Zeebroeck, 2011. "The puzzle of patent value indicators," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 20(1), pages 33-62.
    12. Martin Kalthaus, 2020. "Knowledge recombination along the technology life cycle," Journal of Evolutionary Economics, Springer, vol. 30(3), pages 643-704, July.
    13. Euiseok Kim & Yongrae Cho & Wonjoon Kim, 2014. "Dynamic patterns of technological convergence in printed electronics technologies: patent citation network," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 975-998, February.
    14. Antonio Malva & Stijn Kelchtermans & Bart Leten & Reinhilde Veugelers, 2015. "Basic science as a prescription for breakthrough inventions in the pharmaceutical industry," The Journal of Technology Transfer, Springer, vol. 40(4), pages 670-695, August.
    15. Higham, Kyle & de Rassenfosse, Gaétan & Jaffe, Adam B., 2021. "Patent Quality: Towards a Systematic Framework for Analysis and Measurement," Research Policy, Elsevier, vol. 50(4).
    16. Hur, Wonchang & Oh, Junbyoung, 2021. "A man is known by the company he keeps?: A structural relationship between backward citation and forward citation of patents," Research Policy, Elsevier, vol. 50(1).
    17. Yong-Gil Lee, 2008. "Patent licensability and life: A study of U.S. patents registered by South Korean public research institutes," Scientometrics, Springer;Akadémiai Kiadó, vol. 75(3), pages 463-471, June.
    18. Song, Haoyang & Hou, Jianhua & Zhang, Yang, 2023. "The measurements and determinants of patent technological value: Lifetime, strength, breadth, and dispersion from the technology diffusion perspective," Journal of Informetrics, Elsevier, vol. 17(1).
    19. Marina Van Geenhuizen & Pieter Stek, 2015. "Mapping innovation in the global photovoltaic industry: a bibliometric approach to cluster identification and analysis," ERSA conference papers ersa15p697, European Regional Science Association.
    20. Stefano Basilico & Alberto Marzucchi & Sandro Montresor, 2024. "Combining digital and green technologies in regions: how to close the gap with respect to the frontier?," Papers in Evolutionary Economic Geography (PEEG) 2440, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Dec 2024.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0165091. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.