IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v127y2022i12d10.1007_s11192-022-04557-6.html
   My bibliography  Save this article

Technology convergence among various technical fields: improvement of entropy estimation in patent analysis

Author

Listed:
  • Wenjing Zhu

    (Nanjing University)

  • Bohong Ma

    (Nanjing University)

  • Lele Kang

    (Nanjing University)

Abstract

Recent years have witnessed rapid and widespread technology convergence (TC) in various technical fields. Researchers often focus on developing new methods to identify TC in a specific field without studying the temporal trend of TC and comparing it among different fields. To fill the research gap, this study extends the literature to examine TC in 35 technical fields with 49,687,173 patents from 2000 to 2018. Interestingly, the analysis results show that Shannon, Tsallis, and Renyi entropies, as the indicators of TC, perform differently in describing temporal trends in TC. Further investigation shows that Shannon entropy cannot well depict the incremental trend of TC as single-field patents increased steeply. Thus, Tsallis entropy is used to analyze TC in the study. And we further analyze the complementary (CTC) and substitutability (STC) technology convergence of four representative technical fields. The results show CTC and STC are heterogeneous in the industrial development stage. Industries represent a high level of CTC and a low level of STC in early R&D stage, while STC increases significantly during industrial development. This study contributes to the literature by clarifying the measurements for TC and identifying CTC and STC in various industries.

Suggested Citation

  • Wenjing Zhu & Bohong Ma & Lele Kang, 2022. "Technology convergence among various technical fields: improvement of entropy estimation in patent analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7731-7750, December.
  • Handle: RePEc:spr:scient:v:127:y:2022:i:12:d:10.1007_s11192-022-04557-6
    DOI: 10.1007/s11192-022-04557-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-022-04557-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11192-022-04557-6?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Loet Leydesdorff & Duncan Kushnir & Ismael Rafols, 2014. "Interactive overlay maps for US patent (USPTO) data based on International Patent Classification (IPC)," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1583-1599, March.
    2. Gambardella, Alfonso & Torrisi, Salvatore, 1998. "Does technological convergence imply convergence in markets? Evidence from the electronics industry," Research Policy, Elsevier, vol. 27(5), pages 445-463, September.
    3. Gauch, Stephan & Blind, Knut, 2015. "Technological convergence and the absorptive capacity of standardisation," Technological Forecasting and Social Change, Elsevier, vol. 91(C), pages 236-249.
    4. Lybbert, Travis J. & Zolas, Nikolas J., 2014. "Getting patents and economic data to speak to each other: An ‘Algorithmic Links with Probabilities’ approach for joint analyses of patenting and economic activity," Research Policy, Elsevier, vol. 43(3), pages 530-542.
    5. Matti Karvonen & Matti Lehtovaara & Tuomo Kässi, 2012. "Build-Up Of Understanding Of Technological Convergence: Evidence From Printed Intelligence Industry," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 9(03), pages 1-24.
    6. Joon Hyung Cho & Jungpyo Lee & So Young Sohn, 2021. "Predicting future technological convergence patterns based on machine learning using link prediction," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5413-5429, July.
    7. Andy Stirling, 2007. "A General Framework for Analysing Diversity in Science, Technology and Society," SPRU Working Paper Series 156, SPRU - Science Policy Research Unit, University of Sussex Business School.
    8. Zoltan J. Acs & Luc Anselin & Attila Varga, 2008. "Patents and Innovation Counts as Measures of Regional Production of New Knowledge," Chapters, in: Entrepreneurship, Growth and Public Policy, chapter 11, pages 135-151, Edward Elgar Publishing.
    9. Jun Ruan & Munisamy Gopinath, 2010. "Technological convergence, competitiveness, and welfare: A study of international manufacturing industries," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 19(4), pages 517-551.
    10. Jeeeun Kim & Sungjoo Lee, 2017. "Forecasting and identifying multi-technology convergence based on patent data: the case of IT and BT industries in 2020," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 47-65, April.
    11. Teece, David J, 2018. "Dynamic capabilities as (workable) management systems theory," Journal of Management & Organization, Cambridge University Press, vol. 24(3), pages 359-368, May.
    12. Inyoung Hwang, 2020. "The effect of collaborative innovation on ICT-based technological convergence: A patent-based analysis," PLOS ONE, Public Library of Science, vol. 15(2), pages 1-20, February.
    13. Furman, Jeffrey L. & Porter, Michael E. & Stern, Scott, 2002. "The determinants of national innovative capacity," Research Policy, Elsevier, vol. 31(6), pages 899-933, August.
    14. Jae Young Choi & Seongkyoon Jeong & Kyunam Kim, 2015. "A Study on Diffusion Pattern of Technology Convergence: Patent Analysis for Korea," Sustainability, MDPI, vol. 7(9), pages 1-24, August.
    15. Rosenberg, Nathan, 1963. "Technological Change in the Machine Tool Industry, 1840–1910," The Journal of Economic History, Cambridge University Press, vol. 23(4), pages 414-443, December.
    16. Matti Karvonen & Tuomo Kässi, 2012. "Industry convergence analysis with patent citations in changing value systems," International Journal of Business and Systems Research, Inderscience Enterprises Ltd, vol. 6(2), pages 150-175.
    17. Yueran Duan & Qing Guan, 2021. "Predicting potential knowledge convergence of solar energy: bibliometric analysis based on link prediction model," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 3749-3773, May.
    18. Jaeyong Song & Paul Almeida & Geraldine Wu, 2003. "Learning--by--Hiring: When Is Mobility More Likely to Facilitate Interfirm Knowledge Transfer?," Management Science, INFORMS, vol. 49(4), pages 351-365, April.
    19. Paola Criscuolo, 2006. "The 'home advantage' effect and patent families. A comparison of OECD triadic patents, the USPTO and the EPO," Scientometrics, Springer;Akadémiai Kiadó, vol. 66(1), pages 23-41, January.
    20. Alan L. Porter & Ismael Rafols, 2009. "Is science becoming more interdisciplinary? Measuring and mapping six research fields over time," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(3), pages 719-745, December.
    21. Byunghoon Kim & Gianluca Gazzola & Jaekyung Yang & Jae-Min Lee & Byoung-Youl Coh & Myong K. Jeong & Young-Seon Jeong, 2017. "Two-phase edge outlier detection method for technology opportunity discovery," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 1-16, October.
    22. Sai Yayavaram & Wei-Ru Chen, 2015. "Changes in firm knowledge couplings and firm innovation performance: The moderating role of technological complexity," Strategic Management Journal, Wiley Blackwell, vol. 36(3), pages 377-396, March.
    23. Lissoni, Francesco, 2001. "Knowledge codification and the geography of innovation: the case of Brescia mechanical cluster," Research Policy, Elsevier, vol. 30(9), pages 1479-1500, December.
    Full references (including those not matched with items on IDEAS)

    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. Zhou, Yuan & Dong, Fang & Kong, Dejing & Liu, Yufei, 2019. "Unfolding the convergence process of scientific knowledge for the early identification of emerging technologies," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 205-220.
    2. Dejing Kong & Jianzhong Yang & Lingfeng Li, 2020. "Early identification of technological convergence in numerical control machine tool: a deep learning approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 1983-2009, December.
    3. Seo, Wonchul & Afifuddin, Mokh, 2024. "Developing a supervised learning model for anticipating potential technology convergence between technology topics," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    4. Sick, Nathalie & Preschitschek, Nina & Leker, Jens & Bröring, Stefanie, 2019. "A new framework to assess industry convergence in high technology environments," Technovation, Elsevier, vol. 84, pages 48-58.
    5. Park, Mingyu & Geum, Youngjung, 2022. "Two-stage technology opportunity discovery for firm-level decision making: GCN-based link-prediction approach," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    6. Ying Tang & Xuming Lou & Zifeng Chen & Chengjin Zhang, 2020. "A Study on Dynamic Patterns of Technology Convergence with IPC Co-Occurrence-Based Analysis: The Case of 3D Printing," Sustainability, MDPI, vol. 12(7), pages 1-26, March.
    7. Sick, Nathalie & Bröring, Stefanie, 2022. "Exploring the research landscape of convergence from a TIM perspective: A review and research agenda," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    8. Lee, Hyunmin, 2023. "Converging technology to improve firm innovation competencies and business performance: Evidence from smart manufacturing technologies," Technovation, Elsevier, vol. 123(C).
    9. 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.
    10. Rakas, Marija & Hain, Daniel S., 2019. "The state of innovation system research: What happens beneath the surface?," Research Policy, Elsevier, vol. 48(9), pages 1-1.
    11. Yi Bu & Mengyang Li & Weiye Gu & Win‐bin Huang, 2021. "Topic diversity: A discipline scheme‐free diversity measurement for journals," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(5), pages 523-539, May.
    12. Pan, Maomao & Bai, Min & Ren, Xiaoxiao, 2022. "Does internet convergence improve manufacturing enterprises’ competitive advantage? Empirical research based on the mediation effect model," Technology in Society, Elsevier, vol. 69(C).
    13. Pieter E. Stek, 2021. "Identifying spatial technology clusters from patenting concentrations using heat map kernel density estimation," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 911-930, February.
    14. Sajad Ashouri & Anne-Laure Mention & Kosmas X. Smyrnios, 2021. "Anticipation and analysis of industry convergence using patent-level indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5727-5758, July.
    15. Zhao, Shengchao & Zeng, Deming & Li, Jian & Feng, Ke & Wang, Yao, 2023. "Quantity or quality: The roles of technology and science convergence on firm innovation performance," Technovation, Elsevier, vol. 126(C).
    16. Kim, Yong Jin & Lee, Duk Hee, 2020. "Technology convergence networks for flexible display application: A comparative analysis of latecomers and leaders," Japan and the World Economy, Elsevier, vol. 55(C).
    17. Qian Xu & Hua Cheng, 2021. "Research on the Evolution of Textile Technological Convergence in China," Sustainability, MDPI, vol. 13(5), pages 1-13, February.
    18. Stek, Pieter E. & van Geenhuizen, Marina S., 2016. "The influence of international research interaction on national innovation performance: A bibliometric approach," Technological Forecasting and Social Change, Elsevier, vol. 110(C), pages 61-70.
    19. Kangas, H.L. & Ollikka, K. & Ahola, J. & Kim, Y., 2021. "Digitalisation in wind and solar power technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    20. We Shim & Oh-jin Kwon & Yeong-ho Moon & Keun-hwan Kim, 2016. "Understanding the Dynamic Convergence Phenomenon from the Perspective of Diversity and Persistence: A Cross-Sector Comparative Analysis between the United States and South Korea," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-29, July.

    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:spr:scient:v:127:y:2022:i:12:d:10.1007_s11192-022-04557-6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.