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Funding allocation, inequality, and scientific research output: an empirical study based on the life science sector of Natural Science Foundation of China

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  • Qiang Zhi

    (Central University of Finance and Economics)

  • Tianguang Meng

    (Tsinghua University)

Abstract

Scientific research activity produces the “Matthew Effect” on resource allocation. Based on a data set in the life sciences field from the National Natural Science Foundation of China (NSFC) during the 11th Five-Year-Plan (2006–2010), this paper makes an empirical study on how the Matthew Effect of funding allocation at the institutional level and city level impact scientific research activity output. With Gini coefficient evaluation, descriptive statistic analysis, and the Poisson regression model, we found that there has been a rapid increase in the concentration degree of funding allocation among institutions and cities. Within a period of 5 years, the Gini coefficients of total funding of institutions and cities as the units of measurement have increased from 0.61 and 0.74 to 0.67 and 0.79 respectively. However, this concentration in funding allocation did not result in significant additional benefits. Institutions awarded with more funding did not produce the expected positive spillover effect on their scientific research activity output. Instead, an “inverted U-shape” pattern of decreasing returns to scale was discovered, under which there was a negative effect on internal scientific research activity in the majority of institutions with concentrated funding allocation. Meanwhile, the result shows that Young Scholars projects under the NFSC produced high-level output. We conclude the study by discussing the possible reasons of the inverted U-shape pattern and its policy implications.

Suggested Citation

  • Qiang Zhi & Tianguang Meng, 2016. "Funding allocation, inequality, and scientific research output: an empirical study based on the life science sector of Natural Science Foundation of China," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(2), pages 603-628, February.
    • Handle: RePEc:spr:scient:v:106:y:2016:i:2:d:10.1007_s11192-015-1773-5
    DOI: 10.1007/s11192-015-1773-5
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    Cited by:

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    2. Yin, Zhifeng & Liang, Zheng & Zhi, Qiang, 2018. "Does the concentration of scientific research funding in institutions promote knowledge output?," Journal of Informetrics, Elsevier, vol. 12(4), pages 1146-1159.
    3. Joonha Jeon & So Young Kim, 2018. "Is the gap widening among universities? On research output inequality and its measurement in the Korean higher education system," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(2), pages 589-606, March.
    4. Osterloh, Margit & Frey, Bruno S., 2020. "How to avoid borrowed plumes in academia," Research Policy, Elsevier, vol. 49(1).
    5. Pan, Wenhui & Zhao, Pengwei & Qin, Chunxiu & Ding, Xianfeng, 2020. "How do new members affect the relationship between principal investigator’s network position and academic output of granted funds?," Evaluation and Program Planning, Elsevier, vol. 78(C).
    6. Kazuki Nakajima & Kazuyuki Shudo & Naoki Masuda, 2023. "Higher-order rich-club phenomenon in collaborative research grant networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(4), pages 2429-2446, April.
    7. Wu, Dengsheng & Yuan, Lili & Li, Ruoyun & Li, Jianping, 2018. "Decomposing inequality in research funding by university-institute sub-group: A three-stage nested Theil index," Journal of Informetrics, Elsevier, vol. 12(4), pages 1312-1326.
    8. Zhou Mo & Zhang Yujie & Lei Jiasu & Tan Xiaowen, 2022. "Early firm engagement, government research funding, and the privatization of public knowledge," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(8), pages 4797-4826, August.
    9. Jianping Li & Yongjia Xie & Dengsheng Wu & Yuanping Chen, 2017. "Underestimating or overestimating the distribution inequality of research funding? The influence of funding sources and subdivision," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 55-74, July.
    10. Huang, Ding-wei, 2018. "Optimal distribution of science funding," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 613-618.

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