IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v81y2009i3d10.1007_s11192-008-2224-3.html
   My bibliography  Save this article

Patterns of scientific and technological knowledge flows based on scientific papers and patents

Author

Listed:
  • Hyun Woo Park

    (Korea Institute of Science and Technology Information)

  • Jay Kang

    (San Francisco State University)

Abstract

This paper examines how Korean technological development is linked with scientific activities and spreads to industrial fields through knowledge flows. It empirically assesses the linkages between scientific and technological knowledge flows and technological innovation by determining whether the quantity and quality of scientific papers cited by, and the knowledge being absorbed in, Korean patents filed in USPTO varied over time, and between technology fields. We conducted MANOVA and then canonical discriminate analysis. Our findings are: the patterns of both the absorption of scientific knowledge and the diffusion of technological knowledge differ by period and by field, and the speed of knowledge diffusion differs by technology field. This implies that the time required for Korean investment in basic and applied research to impact her industrial innovation differs by technology field.

Suggested Citation

  • Hyun Woo Park & Jay Kang, 2009. "Patterns of scientific and technological knowledge flows based on scientific papers and patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(3), pages 811-820, December.
    • Handle: RePEc:spr:scient:v:81:y:2009:i:3:d:10.1007_s11192-008-2224-3
    DOI: 10.1007/s11192-008-2224-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-008-2224-3
    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/s11192-008-2224-3?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. Acosta, Manuel & Coronado, Daniel, 2003. "Science-technology flows in Spanish regions: An analysis of scientific citations in patents," Research Policy, Elsevier, vol. 32(10), pages 1783-1803, December.
    2. Stéphane Malo & Aldo Geuna, 2000. "Science-Technology Linkages in an Emerging Research Platform: The Case of Combinatorial Chemistry and Biology," Scientometrics, Springer;Akadémiai Kiadó, vol. 47(2), pages 303-321, February.
    3. Manuel Trajtenberg, 1990. "A Penny for Your Quotes: Patent Citations and the Value of Innovations," RAND Journal of Economics, The RAND Corporation, vol. 21(1), pages 172-187, Spring.
    4. Karki, M. M. S., 1997. "Patent citation analysis: A policy analysis tool," World Patent Information, Elsevier, vol. 19(4), pages 269-272, December.
    5. Pavitt, Keith, 1998. "The social shaping of the national science base," Research Policy, Elsevier, vol. 27(8), pages 793-805, December.
    6. Harhoff, Dietmar & Scherer, Frederic M. & Vopel, Katrin, 2003. "Citations, family size, opposition and the value of patent rights," Research Policy, Elsevier, vol. 32(8), pages 1343-1363, September.
    7. 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.
    8. Sorenson, Olav & Fleming, Lee, 2004. "Science and the diffusion of knowledge," Research Policy, Elsevier, vol. 33(10), pages 1615-1634, December.
    9. Narin, Francis & Noma, Elliot & Perry, Ross, 1987. "Patents as indicators of corporate technological strength," Research Policy, Elsevier, vol. 16(2-4), pages 143-155, August.
    10. Martin Meyer, 2002. "Tracing knowledge flows in innovation systems," Scientometrics, Springer;Akadémiai Kiadó, vol. 54(2), pages 193-212, June.
    11. Narin, Francis & Hamilton, Kimberly S. & Olivastro, Dominic, 1997. "The increasing linkage between U.S. technology and public science," Research Policy, Elsevier, vol. 26(3), pages 317-330, 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. Shu-Hao Chang, 2018. "A pilot study on the connection between scientific fields and patent classification systems," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 951-970, March.
    2. Sung, Hui-Yun & Wang, Chun-Chieh & Huang, Mu-Hsuan & Chen, Dar-Zen, 2015. "Measuring science-based science linkage and non-science-based linkage of patents through non-patent references," Journal of Informetrics, Elsevier, vol. 9(3), pages 488-498.
    3. 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.
    4. Guijie Zhang & Yuqiang Feng & Guang Yu & Luning Liu & Yanqiqi Hao, 2017. "Analyzing the time delay between scientific research and technology patents based on the citation distribution model," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1287-1306, June.
    5. 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.
    6. Zhang, Chengzhi & Liu, Lifan & Wang, Yuzhuo, 2021. "Characterizing references from different disciplines: A perspective of citation content analysis," Journal of Informetrics, Elsevier, vol. 15(2).
    7. Chihmao Hsieh, 2011. "Explicitly searching for useful inventions: dynamic relatedness and the costs of connecting versus synthesizing," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(2), pages 381-404, February.

    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. Lee, Changyong & Cho, Yangrae & Seol, Hyeonju & Park, Yongtae, 2012. "A stochastic patent citation analysis approach to assessing future technological impacts," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 16-29.
    2. Zi-Lin He & Min Deng, 2007. "The evidence of systematic noise in non-patent references: A study of New Zealand companies’ patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 72(1), pages 149-166, July.
    3. Fischer, Timo & Henkel, Joachim, 2012. "Patent trolls on markets for technology – An empirical analysis of NPEs’ patent acquisitions," Research Policy, Elsevier, vol. 41(9), pages 1519-1533.
    4. Eun Han & So Sohn, 2015. "Patent valuation based on text mining and survival analysis," The Journal of Technology Transfer, Springer, vol. 40(5), pages 821-839, October.
    5. 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.
    6. Ugo Rizzo & Nicolò Barbieri & Laura Ramaciotti & Demian Iannantuono, 2020. "The division of labour between academia and industry for the generation of radical inventions," The Journal of Technology Transfer, Springer, vol. 45(2), pages 393-413, April.
    7. Jang, Hyun Jin & Woo, Han-Gyun & Lee, Changyong, 2017. "Hawkes process-based technology impact analysis," Journal of Informetrics, Elsevier, vol. 11(2), pages 511-529.
    8. Jurriën Bakker & Dennis Verhoeven & Lin Zhang & Bart Van Looy, 2016. "Patent citation indicators: One size fits all?," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(1), pages 187-211, January.
    9. Sung, Hui-Yun & Wang, Chun-Chieh & Huang, Mu-Hsuan & Chen, Dar-Zen, 2015. "Measuring science-based science linkage and non-science-based linkage of patents through non-patent references," Journal of Informetrics, Elsevier, vol. 9(3), pages 488-498.
    10. Kwon, Seokbeom & Drev, Matej, 2020. "Defensive Patent Aggregators as Shields against Patent Assertion Entities? Theoretical and Empirical Analysis," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    11. Martin Meyer & Kevin Grant & Piera Morlacchi & Dagmara Weckowska, 2014. "Triple Helix indicators as an emergent area of enquiry: a bibliometric perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(1), pages 151-174, April.
    12. Wang, Fang, 2024. "Does the recombination of distant scientific knowledge generate valuable inventions? An analysis of pharmaceutical patents," Technovation, Elsevier, vol. 130(C).
    13. Haupt, Reinhard & Kloyer, Martin & Lange, Marcus, 2007. "Patent indicators for the technology life cycle development," Research Policy, Elsevier, vol. 36(3), pages 387-398, April.
    14. Acosta, Manuel & Coronado, Daniel & Toribio, Mª Rosario, 2011. "The use of scientific knowledge by Spanish agrifood firms," Food Policy, Elsevier, vol. 36(4), pages 507-516, August.
    15. Dar-Zen Chen & Wen-Yau Cathy Lin & Mu-Hsuan Huang, 2007. "Using Essential Patent Index and Essential Technological Strength to evaluate industrial technological innovation competitiveness," Scientometrics, Springer;Akadémiai Kiadó, vol. 71(1), pages 101-116, April.
    16. Mu-Hsuan Huang & Hui-Yun Sung & Chun-Chieh Wang & Dar-Zen Chen, 2013. "Exploring patent performance and technology interactions of universities, industries, governments and individuals," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(1), pages 11-26, July.
    17. Leten, Bart & Landoni, Paolo & Van Looy, Bart, 2014. "Science or graduates: How do firms benefit from the proximity of universities?," Research Policy, Elsevier, vol. 43(8), pages 1398-1412.
    18. Chang, Ke-Chiun & Chen, Dar-Zen & Huang, Mu-Hsuan, 2012. "The relationships between the patent performance and corporation performance," Journal of Informetrics, Elsevier, vol. 6(1), pages 131-139.
    19. Malwina Mejer, 2012. "The impact of knowledge diversity on inventive performance at European universities," Working Papers TIMES² 2013-004, ULB -- Universite Libre de Bruxelles.
    20. 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.

    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:spr:scient:v:81:y:2009:i:3:d:10.1007_s11192-008-2224-3. 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.