IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v98y2014i3d10.1007_s11192-013-1134-1.html
   My bibliography  Save this article

How knowledge diffuses across countries: a case study in the field of management

Author

Listed:
  • Jiancheng Guan

    (University of Chinese Academy of Sciences)

  • Wenjia Zhu

    (Fudan University)

Abstract

This study introduces nation diffusion breadth and nation diffusion intensity by adapting the notions of field diffusion breadth and field diffusion intensity as defined by Liu and Rousseau, and a variation on the total cited influence indicator introduced by Hu et al. Knowledge diffusion across countries in the field of management is then analyzed as a case study. Main countries in the field of management studies are considered as centers in their own ego-centered citation networks. The three indicators mentioned above are then calculated for these ego-centered citation networks. They measure the scientific impact each of these countries has on other nations. A general picture of the knowledge diffusion process is given by the three indicators at the country level over four periods 1992–1996, 1997–2001, 2002–2006, and 2007–2011. The validity of the proposed indicators is verified by the calculated results.

Suggested Citation

  • Jiancheng Guan & Wenjia Zhu, 2014. "How knowledge diffuses across countries: a case study in the field of management," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 2129-2144, March.
    • Handle: RePEc:spr:scient:v:98:y:2014:i:3:d:10.1007_s11192-013-1134-1
    DOI: 10.1007/s11192-013-1134-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-013-1134-1
    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/s11192-013-1134-1?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. Luís M. A. Bettencourt & David I. Kaiser & Jasleen Kaur & Carlos Castillo-Chávez & David E. Wojick, 2008. "Population modeling of the emergence and development of scientific fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 75(3), pages 495-518, June.
    2. Chaomei Chen & Diana Hicks, 2004. "Tracing knowledge diffusion," Scientometrics, Springer;Akadémiai Kiadó, vol. 59(2), pages 199-211, February.
    3. Kiss, Istvan Z. & Broom, Mark & Craze, Paul G. & Rafols, Ismael, 2010. "Can epidemic models describe the diffusion of topics across disciplines?," Journal of Informetrics, Elsevier, vol. 4(1), pages 74-82.
    4. Shelagh K. Genuis, 2006. "Exploring the role of medical and consumer literature in the diffusion of information related to hormone therapy for menopausal women," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(7), pages 974-988, May.
    5. Zhang, Lin & Thijs, Bart & Glänzel, Wolfgang, 2011. "The diffusion of H-related literature," Journal of Informetrics, Elsevier, vol. 5(4), pages 583-593.
    6. Xuan Liu & Siddharth Kaza & Pengzhu Zhang & Hsinchun Chen, 2011. "Determining inventor status and its effect on knowledge diffusion: A study on nanotechnology literature from China, Russia, and India," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(6), pages 1166-1176, June.
    7. Bettencourt, Luís M.A. & Cintrón-Arias, Ariel & Kaiser, David I. & Castillo-Chávez, Carlos, 2006. "The power of a good idea: Quantitative modeling of the spread of ideas from epidemiological models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 364(C), pages 513-536.
    8. Hu, Xiaojun & Rousseau, Ronald & Chen, Jin, 2011. "On the definition of forward and backward citation generations," Journal of Informetrics, Elsevier, vol. 5(1), pages 27-36.
    9. Xia Gao & Jiancheng Guan, 2012. "Network model of knowledge diffusion," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(3), pages 749-762, March.
    10. Xiaojun Hu & Ronald Rousseau & Jin Chen, 2012. "Structural indicators in citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(2), pages 451-460, May.
    11. Bar-Ilan, Judit, 2008. "Informetrics at the beginning of the 21st century—A review," Journal of Informetrics, Elsevier, vol. 2(1), pages 1-52.
    12. Xuan Liu & Siddharth Kaza & Pengzhu Zhang & Hsinchun Chen, 2011. "Determining inventor status and its effect on knowledge diffusion: A study on nanotechnology literature from China, Russia, and India," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(6), pages 1166-1176, June.
    13. Loet Leydesdorff & Ismael Rafols, 2009. "A global map of science based on the ISI subject categories," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(2), pages 348-362, February.
    14. Yuxian Liu & Ronald Rousseau, 2010. "Knowledge diffusion through publications and citations: A case study using ESI-fields as unit of diffusion," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(2), pages 340-351, February.
    15. Lambiotte, R. & Panzarasa, P., 2009. "Communities, knowledge creation, and information diffusion," Journal of Informetrics, Elsevier, vol. 3(3), pages 180-190.
    16. Yuxian Liu & Ronald Rousseau, 2010. "Knowledge diffusion through publications and citations: A case study using ESI‐fields as unit of diffusion," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(2), pages 340-351, February.
    17. Lee Fleming, 2001. "Recombinant Uncertainty in Technological Search," Management Science, INFORMS, vol. 47(1), pages 117-132, January.
    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. Dengsheng Wu & Yongjia Xie & Qianzhi Dai & Jianping Li, 2016. "A Systematic Overview of Operations Research/Management Science Research in Mainland China: Bibliometric Analysis of the Period 2001–2013," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 33(06), pages 1-26, December.
    2. Xuan Liu & Shan Jiang & Hsinchun Chen & Catherine A. Larson & Mihail C. Roco, 2015. "Modeling knowledge diffusion in scientific innovation networks: an institutional comparison between China and US with illustration for nanotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1953-1984, December.

    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. Xuan Liu & Shan Jiang & Hsinchun Chen & Catherine A. Larson & Mihail C. Roco, 2015. "Modeling knowledge diffusion in scientific innovation networks: an institutional comparison between China and US with illustration for nanotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1953-1984, December.
    2. Wang, Haiying & Moore, Jack Murdoch & Wang, Jun & Small, Michael, 2021. "The distinct roles of initial transmission and retransmission in the persistence of knowledge in complex networks," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    3. Xia Gao & Jiancheng Guan, 2012. "Network model of knowledge diffusion," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(3), pages 749-762, March.
    4. Yue, Zenghui & Xu, Haiyun & Yuan, Guoting & Pang, Hongshen, 2019. "Modeling study of knowledge diffusion in scientific collaboration networks based on differential dynamics: A case study in graphene field," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 375-391.
    5. Stephen Carley & Alan L. Porter, 2012. "A forward diversity index," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(2), pages 407-427, February.
    6. Lyu, Haihua & Bu, Yi & Zhao, Zhenyue & Zhang, Jiarong & Li, Jiang, 2022. "Citation bias in measuring knowledge flow: Evidence from the web of science at the discipline level," Journal of Informetrics, Elsevier, vol. 16(4).
    7. Bei Zeng & Haihua Lyu & Zhenyue Zhao & Jiang Li, 2021. "Exploring the direction and diversity of interdisciplinary knowledge diffusion: A case study of professor Zeyuan Liu's scientific publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 6253-6272, July.
    8. Chen, Lixin, 2017. "Do patent citations indicate knowledge linkage? The evidence from text similarities between patents and their citations," Journal of Informetrics, Elsevier, vol. 11(1), pages 63-79.
    9. Kiss, Istvan Z. & Broom, Mark & Craze, Paul G. & Rafols, Ismael, 2010. "Can epidemic models describe the diffusion of topics across disciplines?," Journal of Informetrics, Elsevier, vol. 4(1), pages 74-82.
    10. 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.
    11. Daniel Torres-Salinas & Nicolás Robinson-García & Álvaro Cabezas-Clavijo & Evaristo Jiménez-Contreras, 2014. "Analyzing the citation characteristics of books: edited books, book series and publisher types in the book citation index," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 2113-2127, March.
    12. John McLevey & Alexander V. Graham & Reid McIlroy-Young & Pierson Browne & Kathryn S. Plaisance, 2018. "Interdisciplinarity and insularity in the diffusion of knowledge: an analysis of disciplinary boundaries between philosophy of science and the sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 331-349, October.
    13. Li, Jingjing & Zhang, Yumei & Man, Jiayu & Zhou, Yun & Wu, Xiaojun, 2017. "SISL and SIRL: Two knowledge dissemination models with leader nodes on cooperative learning networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 740-749.
    14. Xiaojun Hu & Ronald Rousseau & Jin Chen, 2012. "Structural indicators in citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(2), pages 451-460, May.
    15. Zhu, He & Ma, Jing, 2018. "Knowledge diffusion in complex networks by considering time-varying information channels," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 225-235.
    16. Rousseau, Ronald & Hu, Xiaojun, 2013. "Two time series, their meaning and some applications," Journal of Informetrics, Elsevier, vol. 7(3), pages 603-610.
    17. M. Laura Frigotto & Massimo Riccaboni, 2011. "A few special cases: scientific creativity and network dynamics in the field of rare diseases," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(1), pages 397-420, October.
    18. Goldman, Alyssa W., 2014. "Conceptualizing the interdisciplinary diffusion and evolution of emerging fields: The case of systems biology," Journal of Informetrics, Elsevier, vol. 8(1), pages 43-58.
    19. Wang, Haiying & Wang, Jun & Small, Michael, 2018. "Knowledge transmission model with differing initial transmission and retransmission process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 478-488.
    20. Wang, Shiyun & Mao, Jin & Lu, Kun & Cao, Yujie & Li, Gang, 2021. "Understanding interdisciplinary knowledge integration through citance analysis: A case study on eHealth," Journal of Informetrics, Elsevier, vol. 15(4).

    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:98:y:2014:i:3:d:10.1007_s11192-013-1134-1. 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.