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Efficiency evaluation of basic research in China

Author

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  • Wei Meng

    (Institute of Physics, Chinese Academy of Sciences)

  • Zhenhua Hu

    (Business School, Central South University)

  • Wenbin Liu

    (Centre for Anglo-Chinese Business and Management, KBS, University of Kent)

Abstract

Summary Following the increasing investment on basic research in China, the outputs of basic research have been greatly enhanced. In this paper, the relative efficiency of investments in basic research is analyzed by adopting statistical regressions and Data Envelopment Analysis (DEA) method. Preliminary results show that injected investment seems to be the main driving force for the increased basic research outputs in China. It is found that there were significant improvements on overall efficiency from 1991 to 1996, although this trend has noticeably slowed down since 1996. Possible causes of this slow-down are discussed.

Suggested Citation

  • Wei Meng & Zhenhua Hu & Wenbin Liu, 2006. "Efficiency evaluation of basic research in China," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(1), pages 85-101, October.
    • Handle: RePEc:spr:scient:v:69:y:2006:i:1:d:10.1007_s11192-006-0140-y
    DOI: 10.1007/s11192-006-0140-y
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    Cited by:

    1. Du, Yuxin & Teixeira, Aurora A.C., 2012. "A bibliometric account of Chinese economics research through the lens of the China Economic Review," China Economic Review, Elsevier, vol. 23(4), pages 743-762.
    2. Yi Zhang & Mingting Kou & Kaihua Chen & Jiancheng Guan & Yuchen Li, 2016. "Modelling the Basic Research Competitiveness Index (BR-CI) with an application to the biomass energy field," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(3), pages 1221-1241, September.
    3. W. B. Liu & Z. L. Cheng & J. Mingers & L. Qi & W. Meng, 2010. "The 3E methodology for developing performance indicators for public sector organizations," Public Money & Management, Taylor & Francis Journals, vol. 30(5), pages 305-312, September.
    4. Liu, W.B. & Zhang, D.Q. & Meng, W. & Li, X.X. & Xu, F., 2011. "A study of DEA models without explicit inputs," Omega, Elsevier, vol. 39(5), pages 472-480, October.
    5. Lee, Seonghee & Lee, Hakyeon, 2015. "Measuring and comparing the R&D performance of government research institutes: A bottom-up data envelopment analysis approach," Journal of Informetrics, Elsevier, vol. 9(4), pages 942-953.
    6. Zhang, Daqun & Banker, Rajiv D. & Li, Xiaoxuan & Liu, Wenbin, 2011. "Performance impact of research policy at the Chinese Academy of Sciences," Research Policy, Elsevier, vol. 40(6), pages 875-885, July.
    7. Khoshnevis, Pegah & Teirlinck, Peter, 2018. "Performance evaluation of R&D active firms," Socio-Economic Planning Sciences, Elsevier, vol. 61(C), pages 16-28.
    8. Yamin Du & Wonchul Seo, 2022. "A Comparative Study on the Efficiency of R&D Activities of Universities in China by Region Using DEA–Malmquist," Sustainability, MDPI, vol. 14(16), pages 1-13, August.
    9. Liu, John S. & Lu, Wen-Min, 2010. "DEA and ranking with the network-based approach: a case of R&D performance," Omega, Elsevier, vol. 38(6), pages 453-464, December.
    10. Zhu-Mei Sun & Wei-Na Hua, 2015. "A comparative study of Ocean Engineering research between China and the world," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(1), pages 51-63, October.
    11. Cristhian Fabián Ruiz & Ricardo Bonilla & Diego Chavarro & Luis Antonio Orozco & Roberto Zarama & Xavier Polanco, 2010. "Efficiency measurement of research groups using Data Envelopment Analysis and Bayesian networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(3), pages 711-721, June.
    12. Sungmin Park, 2015. "The R&D logic model: Does it really work? An empirical verification using successive binary logistic regression models," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1399-1439, December.
    13. Aoife Hanley & Wan-Hsin Liu & Andrea Vaona, 2015. "Credit depth, government intervention and innovation in China: evidence from the provincial data," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 5(1), pages 73-98, June.
    14. Chiang Kao & Shiang-Tai Liu & Hwei-Lan Pao, 2012. "Assessing improvement in management research in Taiwan," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(1), pages 75-87, July.
    15. W. Liu & W. Meng & X. Li & D. Zhang, 2010. "DEA models with undesirable inputs and outputs," Annals of Operations Research, Springer, vol. 173(1), pages 177-194, January.
    16. Ibrahim Alnafrah, 2021. "Efficiency evaluation of BRICS’s national innovation systems based on bias-corrected network data envelopment analysis," Journal of Innovation and Entrepreneurship, Springer, vol. 10(1), pages 1-28, December.
    17. Meng, Wei & Zhang, Daqun & Qi, Li & Liu, Wenbin, 2008. "Two-level DEA approaches in research evaluation," Omega, Elsevier, vol. 36(6), pages 950-957, December.
    18. Cui Huang & Jun Su & Xiang Xie & Jiang Li, 2014. "Basic research is overshadowed by applied research in China: a policy perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(3), pages 689-694, June.
    19. Stepan Zemtsov & Maxim Kotsemir, 2019. "An assessment of regional innovation system efficiency in Russia: the application of the DEA approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 375-404, August.
    20. Seema Sharma & V. J. Thomas, 2008. "Inter-country R&D efficiency analysis: An application of data envelopment analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 76(3), pages 483-501, September.
    21. Jiancheng Guan & Kaihua Chen, 2010. "Modeling macro-R&D production frontier performance: an application to Chinese province-level R&D," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(1), pages 165-173, January.
    22. Aristovnik, Aleksander, 2014. "Efficiency of the R&D Sector in the EU-27 at the Regional Level: An Application of DEA," MPRA Paper 59081, University Library of Munich, Germany.
    23. J Mingers & W Liu & W Meng, 2009. "Using SSM to structure the identification of inputs and outputs in DEA," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(2), pages 168-179, February.

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