IDEAS home Printed from https://ideas.repec.org/a/eee/infome/v15y2021i3s1751157721000389.html
   My bibliography  Save this article

A novel approach to measuring science-technology linkage: From the perspective of knowledge network coupling

Author

Listed:
  • Ba, Zhichao
  • Liang, Zhentao

Abstract

Identifying and measuring science-technology linkage is important for understanding interactions between science and technology (S&T). Previous studies have focused mainly on knowledge linkages of knowledge systems between S&T but have ignored their structural linkages. To this end, we propose a novel knowledge network coupling approach to gauge network linkage between S&T by integrating knowledge linkages and structural linkages. Four network construction strategies were first adopted to determine appropriate knowledge networks of S&T, and then their coupling strengths over time were calculated based on similarities of coupling nodes’ degree distribution and similarities of coupling edges’ weight distribution. An experimental study in the field of energy conservation confirms that our approach was indeed successful in revealing interactions between S&T. The proposed approach enriches the current methodology for measuring S&T linkages and provides references for policymakers to conduct policy adjustments, by identifying the lead-lag relationship between S&T.

Suggested Citation

  • Ba, Zhichao & Liang, Zhentao, 2021. "A novel approach to measuring science-technology linkage: From the perspective of knowledge network coupling," Journal of Informetrics, Elsevier, vol. 15(3).
    • Handle: RePEc:eee:infome:v:15:y:2021:i:3:s1751157721000389
    DOI: 10.1016/j.joi.2021.101167
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1751157721000389
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.joi.2021.101167?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. Viklund, Mattias, 2004. "Energy policy options--from the perspective of public attitudes and risk perceptions," Energy Policy, Elsevier, vol. 32(10), pages 1159-1171, July.
    2. Guan, Jiancheng & Liu, Na, 2016. "Exploitative and exploratory innovations in knowledge network and collaboration network: A patent analysis in the technological field of nano-energy," Research Policy, Elsevier, vol. 45(1), pages 97-112.
    3. Li, Kai & Yan, Erjia, 2019. "Are NIH-funded publications fulfilling the proposed research? An examination of concept-matchedness between NIH research grants and their supported publications," Journal of Informetrics, Elsevier, vol. 13(1), pages 226-237.
    4. Perianes-Rodriguez, Antonio & Waltman, Ludo & van Eck, Nees Jan, 2016. "Constructing bibliometric networks: A comparison between full and fractional counting," Journal of Informetrics, Elsevier, vol. 10(4), pages 1178-1195.
    5. Shuo Xu & Dongsheng Zhai & Feifei Wang & Xin An & Hongshen Pang & Yirong Sun, 2019. "A novel method for topic linkages between scientific publications and patents," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 70(9), pages 1026-1042, September.
    6. Wang, Feifei & Jia, Chenran & Wang, Xiaohan & Liu, Junwan & Xu, Shuo & Liu, Yang & Yang, Chenyuyan, 2019. "Exploring all-author tripartite citation networks: A case study of gene editing," Journal of Informetrics, Elsevier, vol. 13(3), pages 856-873.
    7. Chen, Guo & Xiao, Lu, 2016. "Selecting publication keywords for domain analysis in bibliometrics: A comparison of three methods," Journal of Informetrics, Elsevier, vol. 10(1), pages 212-223.
    8. Guijie Zhang & Luning Liu & Fangfang Wei, 2019. "Key nodes mining in the inventor–author knowledge diffusion network," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 721-735, March.
    9. Haunschild, Robin & Leydesdorff, Loet & Bornmann, Lutz & Hellsten, Iina & Marx, Werner, 2019. "Does the public discuss other topics on climate change than researchers? A comparison of explorative networks based on author keywords and hashtags," Journal of Informetrics, Elsevier, vol. 13(2), pages 695-707.
    10. Benjamin F. Jones, 2011. "As Science Evolves, How Can Science Policy?," NBER Chapters, in: Innovation Policy and the Economy, Volume 11, pages 103-131, National Bureau of Economic Research, Inc.
    11. Martin Meyer, 2006. "Are Co-Active Researchers on Top of their Class? An Exploratory Comparison of Inventor-Authors with their Non-Inventing Peers in Nano-Science and Technology," SPRU Working Paper Series 144, SPRU - Science Policy Research Unit, University of Sussex Business School.
    12. Peterman, Andrew & Kourula, Arno & Levitt, Raymond, 2014. "Balancing act: Government roles in an energy conservation network," Research Policy, Elsevier, vol. 43(6), pages 1067-1082.
    13. Kevin W. Boyack & Richard Klavans, 2010. "Co‐citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    14. Murray, Fiona, 2002. "Innovation as co-evolution of scientific and technological networks: exploring tissue engineering," Research Policy, Elsevier, vol. 31(8-9), pages 1389-1403, December.
    15. Hu, Xiaojun & Rousseau, Ronald, 2018. "A new approach to explore the knowledge transition path in the evolution of science & technology: From the biology of restriction enzymes to their application in biotechnology," Journal of Informetrics, Elsevier, vol. 12(3), pages 842-857.
    16. Criscuolo, Paola & Verspagen, Bart, 2008. "Does it matter where patent citations come from? Inventor vs. examiner citations in European patents," Research Policy, Elsevier, vol. 37(10), pages 1892-1908, December.
    17. Erjia Yan & Ying Ding, 2012. "Scholarly network similarities: How bibliographic coupling networks, citation networks, cocitation networks, topical networks, coauthorship networks, and coword networks relate to each other," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(7), pages 1313-1326, July.
    18. Meyer, Martin, 2006. "Are patenting scientists the better scholars?: An exploratory comparison of inventor-authors with their non-inventing peers in nano-science and technology," Research Policy, Elsevier, vol. 35(10), pages 1646-1662, December.
    19. Erjia Yan & Ying Ding, 2012. "Scholarly network similarities: How bibliographic coupling networks, citation networks, cocitation networks, topical networks, coauthorship networks, and coword networks relate to each other," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(7), pages 1313-1326, July.
    20. Verhoeven, Dennis & Bakker, Jurriën & Veugelers, Reinhilde, 2016. "Measuring technological novelty with patent-based indicators," Research Policy, Elsevier, vol. 45(3), pages 707-723.
    21. Xu, Haiyun & Winnink, Jos & Yue, Zenghui & Liu, Ziqiang & Yuan, Guoting, 2020. "Topic-linked innovation paths in science and technology," Journal of Informetrics, Elsevier, vol. 14(2).
    22. Sangyoon Yi & Jinho Choi, 2012. "The organization of scientific knowledge: the structural characteristics of keyword networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(3), pages 1015-1026, March.
    23. Fang Han & Christopher L. Magee, 2018. "Testing the science/technology relationship by analysis of patent citations of scientific papers after decomposition of both science and technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 767-796, August.
    24. Wolfgang Glänzel & Martin Meyer, 2003. "Patents cited in the scientific literature: An exploratory study of 'reverse' citation relations," Scientometrics, Springer;Akadémiai Kiadó, vol. 58(2), pages 415-428, October.
    25. Arnold Verbeek & Koenraad Debackere & Marc Luwel & Petra Andries & Edwin Zimmermann & Filip Deleus, 2002. "Linking science to technology: Using bibliographic references in patents to build linkage schemes," Scientometrics, Springer;Akadémiai Kiadó, vol. 54(3), pages 399-420, July.
    26. Breschi, Stefano & Catalini, Christian, 2010. "Tracing the links between science and technology: An exploratory analysis of scientists' and inventors' networks," Research Policy, Elsevier, vol. 39(1), pages 14-26, February.
    27. Katarina Larsen, 2008. "Knowledge network hubs and measures of research impact, science structure, and publication output in nanostructured solar cell research," Scientometrics, Springer;Akadémiai Kiadó, vol. 74(1), pages 123-142, January.
    28. Kwon, Seokbeom & Liu, Xiaoyu & Porter, Alan L. & Youtie, Jan, 2019. "Research addressing emerging technological ideas has greater scientific impact," Research Policy, Elsevier, vol. 48(9), pages 1-1.
    29. Behrouzi, Saman & Shafaeipour Sarmoor, Zahra & Hajsadeghi, Khosrow & Kavousi, Kaveh, 2020. "Predicting scientific research trends based on link prediction in keyword networks," Journal of Informetrics, Elsevier, vol. 14(4).
    30. Du, Jian & Li, Peixin & Guo, Qianying & Tang, Xiaoli, 2019. "Measuring the knowledge translation and convergence in pharmaceutical innovation by funding-science-technology-innovation linkages analysis," Journal of Informetrics, Elsevier, vol. 13(1), pages 132-148.
    31. Kevin W. Boyack & Richard Klavans, 2010. "Co-citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    32. Noyons, E. C. M. & van Raan, A. F. J. & Grupp, H. & Schmoch, U., 1994. "Exploring the science and technology interface: inventor-author relations in laser medicine research," Research Policy, Elsevier, vol. 23(4), pages 443-457, July.
    33. Ke, Qing, 2020. "An analysis of the evolution of science-technology linkage in biomedicine," Journal of Informetrics, Elsevier, vol. 14(4).
    34. Pei-Chun Lee & Hsin-Ning Su & Te-Yi Chan, 2010. "Assessment of ontology-based knowledge network formation by Vector-Space Model," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(3), pages 689-703, December.
    35. Wolfgang Glänzel & Bart Thijs, 2017. "Using hybrid methods and ‘core documents’ for the representation of clusters and topics: the astronomy dataset," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 1071-1087, May.
    36. Ji-ping Gao & Kun Ding & Li Teng & Jie Pang, 2012. "Hybrid documents co-citation analysis: making sense of the interaction between science and technology in technology diffusion," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(2), pages 459-471, November.
    37. Boyack, Kevin W. & Klavans, Richard, 2008. "Measuring science–technology interaction using rare inventor–author names," Journal of Informetrics, Elsevier, vol. 2(3), pages 173-182.
    38. Bu, Yi & Ni, Shaokang & Huang, Win-bin, 2017. "Combining multiple scholarly relationships with author cocitation analysis: A preliminary exploration on improving knowledge domain mappings," Journal of Informetrics, Elsevier, vol. 11(3), pages 810-822.
    39. Loet Leydesdorff & Martin Meyer, 2007. "The scientometrics of a Triple Helix of university-industry-government relations (Introduction to the topical issue)," Scientometrics, Springer;Akadémiai Kiadó, vol. 70(2), pages 207-222, February.
    40. Huang, Mu-Hsuan & Yang, Hsiao-Wen & Chen, Dar-Zen, 2015. "Increasing science and technology linkage in fuel cells: A cross citation analysis of papers and patents," Journal of Informetrics, Elsevier, vol. 9(2), pages 237-249.
    41. Popp, David, 2017. "From science to technology: The value of knowledge from different energy research institutions," Research Policy, Elsevier, vol. 46(9), pages 1580-1594.
    42. Bruno Cassiman & Patrick Glenisson & Bart Looy, 2007. "Measuring industry-science links through inventor-author relations: A profiling methodology," Scientometrics, Springer;Akadémiai Kiadó, vol. 70(2), pages 379-391, February.
    43. Michael Roach & Wesley M. Cohen, 2013. "Lens or Prism? Patent Citations as a Measure of Knowledge Flows from Public Research," Management Science, INFORMS, vol. 59(2), pages 504-525, October.
    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. Dejian Yu & Zhaoping Yan, 2022. "Combining machine learning and main path analysis to identify research front: from the perspective of science-technology linkage," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 4251-4274, July.
    2. Wang, Chun-Chieh & Lin, Jia-Tian & Chen, Dar-Zen & Lo, Szu-Chia, 2023. "A New Look at National Diversity of Inventor Teams within Organizations," Journal of Informetrics, Elsevier, vol. 17(1).
    3. Xu, Haiyun & Yue, Zenghui & Pang, Hongshen & Elahi, Ehsan & Li, Jing & Wang, Lu, 2022. "Integrative model for discovering linked topics in science and technology," Journal of Informetrics, Elsevier, vol. 16(2).
    4. Chen, Xi & Mao, Jin & Ma, Yaxue & Li, Gang, 2024. "The knowledge linkage between science and technology influences corporate technological innovation: Evidence from scientific publications and patents," Technological Forecasting and Social Change, Elsevier, vol. 198(C).
    5. Shuo Xu & Ling Li & Xin An, 2023. "Do academic inventors have diverse interests?," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(2), pages 1023-1053, February.
    6. Kang, Inje & Yang, Jiseong & Lee, Wonjae & Seo, Eun-Yeong & Lee, Duk Hee, 2023. "Delineating development trends of nanotechnology in the semiconductor industry: Focusing on the relationship between science and technology by employing structural topic model," Technology in Society, Elsevier, vol. 74(C).
    7. Ba, Zhichao & Meng, Kai & Ma, Yaxue & Xia, Yikun, 2024. "Discovering technological opportunities by identifying dynamic structure-coupling patterns and lead-lag distance between science and technology," Technological Forecasting and Social Change, Elsevier, vol. 200(C).

    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. Xu, Haiyun & Yue, Zenghui & Pang, Hongshen & Elahi, Ehsan & Li, Jing & Wang, Lu, 2022. "Integrative model for discovering linked topics in science and technology," Journal of Informetrics, Elsevier, vol. 16(2).
    2. Shuo Xu & Ling Li & Xin An, 2023. "Do academic inventors have diverse interests?," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(2), pages 1023-1053, February.
    3. Xian Li & Dangzhi Zhao & Xiaojun Hu, 2020. "Gatekeepers in knowledge transfer between science and technology: an exploratory study in the area of gene editing," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1261-1277, August.
    4. Mariia Shkolnykova, 2021. "Who shapes plant biotechnology in Germany? Joint analysis of the evolution of co-authors’ and co-inventors’ networks," Review of Evolutionary Political Economy, Springer, vol. 2(1), pages 27-54, April.
    5. Ba, Zhichao & Meng, Kai & Ma, Yaxue & Xia, Yikun, 2024. "Discovering technological opportunities by identifying dynamic structure-coupling patterns and lead-lag distance between science and technology," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    6. Wang, Jean J. & Ye, Fred Y., 2021. "Probing into the interactions between papers and patents of new CRISPR/CAS9 technology: A citation comparison," Journal of Informetrics, Elsevier, vol. 15(4).
    7. Ke, Qing, 2020. "Technological impact of biomedical research: The role of basicness and novelty," Research Policy, Elsevier, vol. 49(7).
    8. Boyack, Kevin W. & Klavans, Richard, 2008. "Measuring science–technology interaction using rare inventor–author names," Journal of Informetrics, Elsevier, vol. 2(3), pages 173-182.
    9. Stéphane Maraut & Catalina Martínez, 2014. "Identifying author–inventors from Spain: methods and a first insight into results," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 445-476, October.
    10. Xu, Haiyun & Winnink, Jos & Yue, Zenghui & Liu, Ziqiang & Yuan, Guoting, 2020. "Topic-linked innovation paths in science and technology," Journal of Informetrics, Elsevier, vol. 14(2).
    11. Wang, Gangbo & Guan, Jiancheng, 2010. "The role of patenting activity for scientific research: A study of academic inventors from China's nanotechnology," Journal of Informetrics, Elsevier, vol. 4(3), pages 338-350.
    12. Shuo Xu & Ling Li & Xin An & Liyuan Hao & Guancan Yang, 2021. "An approach for detecting the commonality and specialty between scientific publications and patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 7445-7475, September.
    13. Dejian Yu & Zhaoping Yan, 2022. "Combining machine learning and main path analysis to identify research front: from the perspective of science-technology linkage," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 4251-4274, July.
    14. Czarnitzki, Dirk & Glänzel, Wolfgang & Hussinger, Katrin, 2009. "Heterogeneity of patenting activity and its implications for scientific research," Research Policy, Elsevier, vol. 38(1), pages 26-34, February.
    15. Alfonso Ávila-Robinson & Shintaro Sengoku, 2017. "Tracing the knowledge-building dynamics in new stem cell technologies through techno-scientific networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1691-1720, September.
    16. Guan-Can Yang & Gang Li & Chun-Ya Li & Yun-Hua Zhao & Jing Zhang & Tong Liu & Dar-Zen Chen & Mu-Hsuan Huang, 2015. "Using the comprehensive patent citation network (CPC) to evaluate patent value," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1319-1346, December.
    17. Yu-Wei Chang & Mu-Hsuan Huang & Chiao-Wen Lin, 2015. "Evolution of research subjects in library and information science based on keyword, bibliographical coupling, and co-citation analyses," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 2071-2087, December.
    18. Yang, Siluo & Han, Ruizhen & Wolfram, Dietmar & Zhao, Yuehua, 2016. "Visualizing the intellectual structure of information science (2006–2015): Introducing author keyword coupling analysis," Journal of Informetrics, Elsevier, vol. 10(1), pages 132-150.
    19. 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.
    20. Dorsa Alipour & Hussein Dia, 2023. "A Systematic Review of the Role of Land Use, Transport, and Energy-Environment Integration in Shaping Sustainable Cities," Sustainability, MDPI, vol. 15(8), pages 1-29, April.

    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:eee:infome:v:15:y:2021:i:3:s1751157721000389. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/joi .

    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.