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Measuring regional science networks in China: a comparison of international and domestic bibliographic data sources

Author

Listed:
  • S. Hennemann

    (Justus Liebig University of Giessen)

  • T. Wang

    (Nanjing Normal University)

  • I. Liefner

    (Justus Liebig University of Giessen)

Abstract

Bibliographic databases are frequently used and analysed for the purpose of assessing the capacity and performance of individual researchers or entire research systems. Many of the advantages and disadvantages are the subject of continued discussion in the relevant literature, although only rarely with respect to the regional dimension of scientific publication activity. The importance of the regional dimension of science is reflected in many theoretical concepts, ranging from innovation system theories to territorial cluster concepts and learning regions. This article makes use of the extensive information found in bibliographic data and assesses the reliability of this information as a proxy indicator for the spatial dimension of scientific collaboration in emerging economies. This is undertaken using the example of the emerging field of biotechnology in China from 2000 onwards. Two data sets have been prepared: (1) the frequently used ISI Web of Knowledge database (SCI-Expanded) and (2) the domestic Chinese Chongqing VIP database. Both data sources were analysed using a variety of bibliometric and network scientific methods. The structural and topological similarity of networks, built from co-authorship data, is apparent between the two databases. At an abstract level, general network forces are present, resulting in similar network sizes, clustering, or assortativity. However, introducing additional complexity through regional subdivision reveals many differences between the two data sources that must be accounted for in the analytic design of future scientometric research in dynamic spaces.

Suggested Citation

  • S. Hennemann & T. Wang & I. Liefner, 2011. "Measuring regional science networks in China: a comparison of international and domestic bibliographic data sources," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(2), pages 535-554, August.
    • Handle: RePEc:spr:scient:v:88:y:2011:i:2:d:10.1007_s11192-011-0410-1
    DOI: 10.1007/s11192-011-0410-1
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    Cited by:

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    2. Sheng-qiang Jiang & An-na Shi & Zhi-hang Peng & Xin Li, 2017. "Major factors affecting cross-city R&D collaborations in China: evidence from cross-sectional co-patent data between 224 cities," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1251-1266, June.
    3. Jiang Wu, 2013. "Geographical knowledge diffusion and spatial diversity citation rank," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 181-201, January.
    4. Copiello, Sergio, 2019. "Peer and neighborhood effects: Citation analysis using a spatial autoregressive model and pseudo-spatial data," Journal of Informetrics, Elsevier, vol. 13(1), pages 238-254.
    5. Jiang, Hanchen & Qiang, Maoshan & Fan, Qixiang & Zhang, Mengqing, 2018. "Scientific research driven by large-scale infrastructure projects: A case study of the Three Gorges Project in China," Technological Forecasting and Social Change, Elsevier, vol. 134(C), pages 61-71.
    6. Dandan Li & Yehua Dennis Wei & Changhong Miao & Yangyi Wu & Weiye Xiao, 2019. "Innovation, Network Capabilities, and Sustainable Development of Regional Economies in China," Sustainability, MDPI, vol. 11(17), pages 1-21, September.
    7. David Emanuel Andersson & Saileshsingh Gunessee & Christian Wichmann Matthiessen & Søren Find, 2014. "The Geography of Chinese Science," Environment and Planning A, , vol. 46(12), pages 2950-2971, December.
    8. Fei Shu & Wen Lou & Stefanie Haustein, 2018. "Can Twitter increase the visibility of Chinese publications?," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 505-519, July.
    9. Heindl, Anna-Barbara & Liefner, Ingo, 2019. "The Analytic Hierarchy Process as a methodological contribution to improve regional innovation system research: Explored through comparative research in China," Technology in Society, Elsevier, vol. 59(C).
    10. Zhihui Zhang & Jason E. Rollins & Evangelia Lipitakis, 2018. "China’s emerging centrality in the contemporary international scientific collaboration network," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 1075-1091, August.
    11. Jinyuan Ma & Fan Jiang & Liujian Gu & Xiang Zheng & Xiao Lin & Chuanyi Wang, 2020. "Patterns of the Network of Cross-Border University Research Collaboration in the Guangdong-Hong Kong-Macau Greater Bay Area," Sustainability, MDPI, vol. 12(17), pages 1-17, August.

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    More about this item

    Keywords

    China; Spatial scientometrics; Database comparison; Regional science networks; Biotechnology;
    All these keywords.

    JEL classification:

    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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