IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i2p660-d309469.html
   My bibliography  Save this article

The Scientific Cooperation Network of Chinese Scientists and Its Proximity Mechanism

Author

Listed:
  • Wentian Shi

    (Institute for Global Innovation and Development, East China Normal University, Shanghai 200062, China
    School of Urban and Regional Science, East China Normal University, Shanghai 200241, China)

  • Wenlong Yang

    (Institute of World Economy, Shanghai Academy of Social Sciences, Shanghai 200020, China)

  • Debin Du

    (Institute for Global Innovation and Development, East China Normal University, Shanghai 200062, China
    School of Urban and Regional Science, East China Normal University, Shanghai 200241, China)

Abstract

The collaboration of scientists is important for promoting the scientific development and technological progress of a country, and even of the world. Based on the cooperation data of academicians of the Chinese Academy of Sciences (CAS) in the China National Knowledge Infrastructure (CNKI), we portray the scientific cooperation network of Chinese scientists using Pajek, Gephi, ArcGIS, and other software, and the complexity of the scientific cooperation network of Chinese scientists and its proximity mechanism are explored by combining complex network analysis, spatial statistical analysis, and negative binomial regression models. Our main conclusions are as follows: (1) In terms of network structure, the scientific cooperation network of Chinese scientists has a multi-triangular skeleton, with Beijing as its apex. The network has an obvious hierarchical structure. Beijing and Shanghai are located in the core area, and 16 cities are located in the semi-periphery of the network, while other cities are located at the periphery of the network. (2) In terms of spatial distribution, the regional imbalance of the scientific cooperation of Chinese scientists is obvious. Beijing–Tianjin–Hebei, the Yangtze River Delta, and the central-south region of Liaoning are hot spots for the scientific research activities of Chinese scientists. (3) The negative binomial regression model accurately explains the proximity mechanism of the scientific cooperation network of Chinese scientists. The geographical proximity positively affects the scientific cooperation of Chinese scientists under certain conditions. The educational proximity is the primary consideration for scientists to cooperate in scientific research. The closer the educational level of the cities, the greater the cooperation. Economic and social proximity can promote scientific cooperation among scientists, whereas institutional proximity negatively and significantly affects scientific cooperation.

Suggested Citation

  • Wentian Shi & Wenlong Yang & Debin Du, 2020. "The Scientific Cooperation Network of Chinese Scientists and Its Proximity Mechanism," Sustainability, MDPI, vol. 12(2), pages 1-18, January.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:2:p:660-:d:309469
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/2/660/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/2/660/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Leydesdorff, Loet & Wagner, Caroline S., 2008. "International collaboration in science and the formation of a core group," Journal of Informetrics, Elsevier, vol. 2(4), pages 317-325.
    2. Qinchang Gui & Chengliang Liu & DeBin Du, 2019. "The Structure and Dynamic of Scientific Collaboration Network among Countries along the Belt and Road," Sustainability, MDPI, vol. 11(19), pages 1-17, September.
    3. Haitao Ma & Chuanglin Fang & Bo Pang & Guangdong Li, 2014. "The Effect of Geographical Proximity on Scientific Cooperation among Chinese Cities from 1990 to 2010," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-11, November.
    4. Thomas Scherngell & Yuanjia Hu, 2011. "Collaborative Knowledge Production in China: Regional Evidence from a Gravity Model Approach," Regional Studies, Taylor & Francis Journals, vol. 45(6), pages 755-772.
    5. Lorenzo Cassi & Andrea Morrison & Roberta Rabellotti, 2015. "Proximity and Scientific Collaboration: Evidence from the Global Wine Industry," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 106(2), pages 205-219, April.
    6. Chen, Kaihua & Zhang, Yi & Fu, Xiaolan, 2019. "International research collaboration: An emerging domain of innovation studies?," Research Policy, Elsevier, vol. 48(1), pages 149-168.
    7. Jarno Hoekman & Koen Frenken & Frank Oort, 2009. "The geography of collaborative knowledge production in Europe," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 43(3), pages 721-738, September.
    8. Yun Liu & Zhe Yan & Yijie Cheng & Xuanting Ye, 2018. "Exploring the Technological Collaboration Characteristics of the Global Integrated Circuit Manufacturing Industry," Sustainability, MDPI, vol. 10(1), pages 1-23, January.
    9. Qinchang Gui & Chengliang Liu & Debin Du, 2018. "International Knowledge Flows and the Role of Proximity," Growth and Change, Wiley Blackwell, vol. 49(3), pages 532-547, September.
    10. Agrawal, Ajay & Kapur, Devesh & McHale, John, 2008. "How do spatial and social proximity influence knowledge flows? Evidence from patent data," Journal of Urban Economics, Elsevier, vol. 64(2), pages 258-269, September.
    11. Michel Zitt & Elise Bassecoulard & Yoshiko Okubo, 2000. "Shadows of the Past in International Cooperation: Collaboration Profiles of the Top Five Producers of Science," Scientometrics, Springer;Akadémiai Kiadó, vol. 47(3), pages 627-657, March.
    12. Giuditta Prato & Daniel Nepelski, 2014. "Global technological collaboration network: network analysis of international co-inventions," The Journal of Technology Transfer, Springer, vol. 39(3), pages 358-375, June.
    13. Mila Davids & Koen Frenken, 2018. "Proximity, knowledge base and the innovation process: towards an integrated framework," Regional Studies, Taylor & Francis Journals, vol. 52(1), pages 23-34, January.
    14. Nii A. Addy & Laurette Dubé, 2018. "Addressing Complex Societal Problems: Enabling Multiple Dimensions of Proximity to Sustain Partnerships for Collective Impact in Quebec," Sustainability, MDPI, vol. 10(4), pages 1-28, March.
    15. Katz, J. Sylvan & Martin, Ben R., 1997. "What is research collaboration?," Research Policy, Elsevier, vol. 26(1), pages 1-18, March.
    16. Hong, Wei & Su, Yu-Sung, 2013. "The effect of institutional proximity in non-local university–industry collaborations: An analysis based on Chinese patent data," Research Policy, Elsevier, vol. 42(2), pages 454-464.
    17. Ron Boschma, 2005. "Proximity and Innovation: A Critical Assessment," Regional Studies, Taylor & Francis Journals, vol. 39(1), pages 61-74.
    18. Wentian Shi & Debin Du & Wenlong Yang, 2019. "The Flow Network of Chinese Scientists and Its Driving Mechanisms Based on the Spatial Development Path of CAS and CAE Academicians," Sustainability, MDPI, vol. 11(21), pages 1-22, October.
    19. Franz Huber, 2012. "On the Role and Interrelationship of Spatial, Social and Cognitive Proximity: Personal Knowledge Relationships of R&D Workers in the Cambridge Information Technology Cluster," Regional Studies, Taylor & Francis Journals, vol. 46(9), pages 1169-1182, October.
    20. Jonathan Adams, 2013. "The fourth age of research," Nature, Nature, vol. 497(7451), pages 557-560, May.
    21. Jonathan Adams, 2012. "The rise of research networks," Nature, Nature, vol. 490(7420), pages 335-336, October.
    22. Roderik Ponds & Frank Van Oort & Koen Frenken, 2007. "The geographical and institutional proximity of research collaboration," Papers in Regional Science, Wiley Blackwell, vol. 86(3), pages 423-443, August.
    23. Muriithi, Petronilla & Horner, David & Pemberton, Lyn & Wao, Hesborn, 2018. "Factors influencing research collaborations in Kenyan universities," Research Policy, Elsevier, vol. 47(1), pages 88-97.
    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. Xuli Tang & Xin Li & Feicheng Ma, 2022. "Internationalizing AI: evolution and impact of distance factors," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 181-205, January.
    2. Jun Guan & Chunxiu Liu & Guoqiang Liang & Lizhi Xing, 2023. "Framework to Measure the Mobility of Technical Talents: Evidence from China’s Smart Logistics," Sustainability, MDPI, vol. 15(3), pages 1-16, January.
    3. Wentian Shi & Quansheng Fu & Wenlong Yang & Fan Yang & Xiao Lin & Xueying Mu, 2022. "The spatial relationship between the mobility and scientific cooperation of Chinese scientists," Growth and Change, Wiley Blackwell, vol. 53(2), pages 951-971, June.
    4. Yinqi Ma & Qi Xiu & Lingzhi Shao & Hao Yao, 2022. "Promoting the Sustainable Improvement of Educational Empirical Research Quality: What Kinds of Collaborative Production Relationships Make Sense?," Sustainability, MDPI, vol. 14(6), pages 1-23, March.
    5. Lei Luo & Zhenhua Zheng & Jing Luo & Yuqiu Jia & Qi Zhang & Chun Wu & Yifeng Zhang & Jia Sun, 2020. "Spatial Agglomeration of Manufacturing in the Wuhan Metropolitan Area: An Analysis of Sectoral Patterns and Determinants," Sustainability, MDPI, vol. 12(19), pages 1-23, September.

    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. Luigi Aldieri & Gennaro Guida & Maxim Kotsemir & Concetto Paolo Vinci, 2019. "An investigation of impact of research collaboration on academic performance in Italy," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(4), pages 2003-2040, July.
    2. Stanislav Avdeev, 2021. "International collaboration in higher education research: A gravity model approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5569-5588, July.
    3. Vieira, Elizabeth S. & Cerdeira, Jorge & Teixeira, Aurora A.C., 2022. "Which distance dimensions matter in international research collaboration? A cross-country analysis by scientific domain," Journal of Informetrics, Elsevier, vol. 16(2).
    4. Graf, Holger & Kalthaus, Martin, 2018. "International research networks: Determinants of country embeddedness," Research Policy, Elsevier, vol. 47(7), pages 1198-1214.
    5. Jyoti Dua & Hiran H. Lathabai & Vivek Kumar Singh, 2023. "Measuring and characterizing research collaboration in SAARC countries," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(2), pages 1265-1294, February.
    6. Elizabeth S. Vieira, 2022. "International research collaboration in Africa: a bibliometric and thematic analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(5), pages 2747-2772, May.
    7. Tatiana Plotnikova & Bastian Rake, 2014. "Collaboration in pharmaceutical research: exploration of country-level determinants," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 1173-1202, February.
    8. Jorge Cerdeira & João Mesquita & Elizabeth S. Vieira, 2023. "International research collaboration: is Africa different? A cross-country panel data analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(4), pages 2145-2174, April.
    9. Laurent R. Bergé, 2017. "Network proximity in the geography of research collaboration," Papers in Regional Science, Wiley Blackwell, vol. 96(4), pages 785-815, November.
    10. Morescalchi, Andrea & Pammolli, Fabio & Penner, Orion & Petersen, Alexander M. & Riccaboni, Massimo, 2015. "The evolution of networks of innovators within and across borders: Evidence from patent data," Research Policy, Elsevier, vol. 44(3), pages 651-668.
    11. Christian Omobhude & Shih-Hsin Chen, 2019. "The Roles and Measurements of Proximity in Sustained Technology Development: A Literature Review," Sustainability, MDPI, vol. 11(1), pages 1-30, January.
    12. Ana Fernández & Esther Ferrándiz & M. Dolores León, 2021. "Are organizational and economic proximity driving factors of scientific collaboration? Evidence from Spanish universities, 2001–2010," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 579-602, January.
    13. Jyoti Dua & Vivek Kumar Singh & Hiran H. Lathabai, 2023. "Measuring and characterizing international collaboration patterns in Indian scientific research," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(9), pages 5081-5116, September.
    14. A. Fernández & E. Ferrándiz & M. D. León, 2016. "Proximity dimensions and scientific collaboration among academic institutions in Europe: The closer, the better?," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(3), pages 1073-1092, March.
    15. Utku Ali Rıza Alpaydın & Rune Dahl Fitjar, 2021. "Proximity across the distant worlds of university–industry collaborations," Papers in Regional Science, Wiley Blackwell, vol. 100(3), pages 689-711, June.
    16. Chen, Kaihua & Zhang, Yi & Fu, Xiaolan, 2019. "International research collaboration: An emerging domain of innovation studies?," Research Policy, Elsevier, vol. 48(1), pages 149-168.
    17. Dosso, Mafini & Cassi, Lorenzo & Mescheba, Wilfriedo, 2023. "Towards regional scientific integration in Africa? Evidence from co-publications," Research Policy, Elsevier, vol. 52(1).
    18. Candelaria Barrios & Esther Flores & M. Ángeles Martínez & Marta Ruiz-Martínez, 2019. "Is there convergence in international research collaboration? An exploration at the country level in the basic and applied science fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 631-659, August.
    19. Sidonia Proff & Thomas Brenner, 2014. "The dynamics of inter-regional collaboration: an analysis of co-patenting," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 52(1), pages 41-64, January.
    20. Pierre-Alexandre Balland & Ron Boschma & Koen Frenken, 2015. "Proximity and Innovation: From Statics to Dynamics," Regional Studies, Taylor & Francis Journals, vol. 49(6), pages 907-920, June.

    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:gam:jsusta:v:12:y:2020:i:2:p:660-:d:309469. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.