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The Matthew effect in China’s science: evidence from academicians of Chinese Academy of Sciences

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Abstract

Utilizing a unique dataset of the Chinese Academy of Sciences academicians (1993–2013), this paper investigates the Matthew effect in China’s science. Three indicators, namely the concentration index, the Matthew index and the coefficient of variation, are adopted to measure the uneven distribution of academicians of the Chinese Academy of Sciences among different regions and disciplines. The empirical analysis demonstrates the existence of the Matthew effect in China’s science for the above two dimensions. Yet, this effect has weakened for all regions with the exception of Beijing. We argue that this uneven distribution of the nation’s brightest minds makes scientifically competitive regions and disciplines even more competitive while putting those less developed regions and research domains at further disadvantage.

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Notes

  1. Currently, China has 28 provinces and autonomous regions, four provincial level municipalities (Beijing, Shanghai, Tianjing and Chongqing), and two special administrative regions (Hong Kong and Macau). Unless specified, the term “region” in this paper refers only to the regions from which CAS academicians were elected.

  2. For further information on CAS and the institutes, see “2014 Guide to CAS” (http://english.cas.cn).

  3. Please note that due to political reasons, prior to 1990, the election of CAS members occurred only three times.

  4. In addition, there were 88 Foreign Members at the end of 2013. In this paper, the Foreign Members were not taken into account.

  5. Each newly assigned CAS academician is assigned to only one region.

  6. The illustration case is appeared in “Appendix”.

  7. The allocation of province is based on the location of affiliation that CAS academicians work when they were elected.

  8. As 564 CAS academicians were elected from 27 provincial level regions over the examined period, the top 20 % regions is calculated by 27 × 20 % which including approximate five regions compared with the rest 22 regions (27 × 80 %). Ranking by descending numerical order of elected CAS academicians within the 20 year period, these top 20 % regions are Beijing (265), Shanghai (67), Jiangsu (37), Hong Kong (22) and Anhui (20) in proper order.

  9. The number refers to the population at the end of 2013. The data source is the official website of National Bureau of Statistics of China (http://www.stats.gov.cn/).

  10. Here, we used the 27 provincial level administrative divisions year-end population data when there were CAS academicians elected from 1993 to 2013.

  11. See annual China Statistical Yearbook compiled by National Bureau of Statistics of China.

  12. There are three types of patents in SIPO: Invention, Utility Model, and Design.

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Acknowledgments

This research was jointly supported by the National Natural Science Foundation of China (Grants #71302133 and #71303147) and the Innovation Team Project funded by the Ministry of Education in Sichuan, China (Grant #13TD0040).

Author information

Authors and Affiliations

  1. School of Business, Sichuan University, Wangjiang Road 29, Chengdu, 610064, China

    Xue Yang, Xin Gu & Yuandi Wang

  2. Jincheng College of Sichuan University, Xiyuan Avenue 1, Chengdu, 611731, China

    Xue Yang

  3. Innovation and Entrepreneurship Research Institute, Sichuan University, Wangjiang Road 29, Chengdu, 610064, China

    Xin Gu

  4. School of Public Economics and Administration, Shanghai University of Finance and Economics, Shanghai, 200433, China

    Guangyuan Hu & Li Tang

Authors
  1. Xue Yang
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  2. Xin Gu
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  3. Yuandi Wang
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  4. Guangyuan Hu
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  5. Li Tang
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Corresponding author

Correspondence to Li Tang.

Appendix

Appendix

See Table 5.

Table 5 The illustration case of calculating Concentration Index I
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Yang, X., Gu, X., Wang, Y. et al. The Matthew effect in China’s science: evidence from academicians of Chinese Academy of Sciences. Scientometrics 102, 2089–2105 (2015). https://doi.org/10.1007/s11192-014-1502-5

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