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

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  • 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
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    References listed on IDEAS

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    1. Chaomei Chen & Diana Hicks, 2004. "Tracing knowledge diffusion," Scientometrics, Springer;Akadémiai Kiadó, vol. 59(2), pages 199-211, February.
    2. 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.
    3. Zhang, Lin & Thijs, Bart & Glänzel, Wolfgang, 2011. "The diffusion of H-related literature," Journal of Informetrics, Elsevier, vol. 5(4), pages 583-593.
    4. 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.
    5. 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.
    6. Xia Gao & Jiancheng Guan, 2012. "Network model of knowledge diffusion," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(3), pages 749-762, March.
    7. Xiaojun Hu & Ronald Rousseau & Jin Chen, 2012. "Structural indicators in citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(2), pages 451-460, May.
    8. Bar-Ilan, Judit, 2008. "Informetrics at the beginning of the 21st century—A review," Journal of Informetrics, Elsevier, vol. 2(1), pages 1-52.
    9. 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.
    10. 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.
    11. Lambiotte, R. & Panzarasa, P., 2009. "Communities, knowledge creation, and information diffusion," Journal of Informetrics, Elsevier, vol. 3(3), pages 180-190.
    12. Lee Fleming, 2001. "Recombinant Uncertainty in Technological Search," Management Science, INFORMS, vol. 47(1), pages 117-132, January.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
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    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.

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