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How large of a grant size is appropriate? Evidence from the National Natural Science Foundation of China

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  • Peixin Duan

Abstract

Under the current universal trend towards larger grant sizes in research funding systems, we focus on how large of a grant size is appropriate. We study the directional returns to scale (RTS) to assess whether current grant sizes are the most productive. We take the General Program of the National Natural Science Foundation of China (NSFC) as an example and select three samples of physics, geography and management for an empirical study. We find that the optimal input direction and the most productive grant size scale is different for the three disciplines; based on the current grant size, physics should not expand the grant size and team size input, geography should further increase the grant size to improve performance and management should further expand the team size rather than the grant size. In this paper, we demonstrate a new method to calculate the optimal direction, which is the lowest rate of congestion, according to the characteristics of the General Program. Based on these results, we also calculate the most productive scale size. This method has certain value for project management.

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  • Peixin Duan, 2022. "How large of a grant size is appropriate? Evidence from the National Natural Science Foundation of China," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-14, February.
  • Handle: RePEc:plo:pone00:0264070
    DOI: 10.1371/journal.pone.0264070
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    1. William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), 2011. "Handbook on Data Envelopment Analysis," International Series in Operations Research and Management Science, Springer, number 978-1-4419-6151-8, December.
    2. Yang, Guo-liang & Rousseau, Ronald & Yang, Li-ying & Liu, Wen-bin, 2014. "A study on directional returns to scale," Journal of Informetrics, Elsevier, vol. 8(3), pages 628-641.
    3. Banker, Rajiv D. & Thrall, R. M., 1992. "Estimation of returns to scale using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 62(1), pages 74-84, October.
    4. Kristiaan Kerstens & Ignace Van de Woestyne, 2018. "Enumeration algorithms for FDH directional distance functions under different returns to scale assumptions," Annals of Operations Research, Springer, vol. 271(2), pages 1067-1078, December.
    5. Soleimani-damaneh, M. & Jahanshahloo, G.R. & Reshadi, M., 2006. "On the estimation of returns-to-scale in FDH models," European Journal of Operational Research, Elsevier, vol. 174(2), pages 1055-1059, October.
    6. Sarabjeet D. Natesan & Rahul Ratnakar Marathe, 2017. "Evaluation of MGNREGA: data envelopment analysis approach," International Journal of Social Economics, Emerald Group Publishing Limited, vol. 44(2), pages 181-194, February.
    7. Torben Schubert & Guoliang Yang, 2016. "Institutional change and the optimal size of universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(3), pages 1129-1153, September.
    8. Banker, Rajiv D., 1984. "Estimating most productive scale size using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 17(1), pages 35-44, July.
    9. F R Førsund & L Hjalmarsson, 2004. "Calculating scale elasticity in DEA models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(10), pages 1023-1038, October.
    10. Kao, Chiang, 2022. "Measuring efficiency in a general production possibility set allowing for negative data: An extension and a focus on returns to scale," European Journal of Operational Research, Elsevier, vol. 296(1), pages 267-276.
    11. William W. Cooper & Lawrence M. Seiford & Joe Zhu, 2011. "Data Envelopment Analysis: History, Models, and Interpretations," International Series in Operations Research & Management Science, in: William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), Handbook on Data Envelopment Analysis, chapter 0, pages 1-39, Springer.
    12. Sun, Huaping & Edziah, Bless Kofi & Sun, Chuanwang & Kporsu, Anthony Kwaku, 2019. "Institutional quality, green innovation and energy efficiency," Energy Policy, Elsevier, vol. 135(C).
    13. Hu, Albert G.Z., 2020. "Public funding and the ascent of Chinese science: Evidence from the National Natural Science Foundation of China," Research Policy, Elsevier, vol. 49(5).
    14. Victor V. Podinovski & Finn R. Førsund, 2010. "Differential Characteristics of Efficient Frontiers in Data Envelopment Analysis," Operations Research, INFORMS, vol. 58(6), pages 1743-1754, December.
    15. Sueyoshi, Toshiyuki & Sekitani, Kazuyuki, 2007. "Measurement of returns to scale using a non-radial DEA model: A range-adjusted measure approach," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1918-1946, February.
    16. Rajiv D. Banker & William W. Cooper & Lawrence M. Seiford & Joe Zhu, 2011. "Returns to Scale in DEA," International Series in Operations Research & Management Science, in: William W. Cooper & Lawrence M. Seiford & Joe Zhu (ed.), Handbook on Data Envelopment Analysis, chapter 0, pages 41-70, Springer.
    17. Wei, Quanling & Yan, Hong, 2004. "Congestion and returns to scale in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 153(3), pages 641-660, March.
    18. Carter Bloch & Jesper W Schneider & Thomas Sinkjær, 2016. "Size, Accumulation and Performance for Research Grants: Examining the Role of Size for Centres of Excellence," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-17, February.
    19. Chen, Yao, 2003. "A non-radial Malmquist productivity index with an illustrative application to Chinese major industries," International Journal of Production Economics, Elsevier, vol. 83(1), pages 27-35, January.
    20. Henrik Dimke & Maria Theresa Norn & Peter Munk Christiansen & Jeppe Wohlert & Nikolaj Thomas Zinner, 2019. "Most scientists prefer small and mid-sized research grants," Nature Human Behaviour, Nature, vol. 3(8), pages 765-767, August.
    21. Bert Balk & Rolf Färe & Giannis Karagiannis, 2015. "On directional scale elasticities," Journal of Productivity Analysis, Springer, vol. 43(1), pages 99-104, February.
    22. António Osório & Lutz Bornmann, 2021. "On the disruptive power of small-teams research," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 117-133, January.
    23. Dan Rosen & Claire Schaffnit & Joseph Paradi, 1998. "Marginal Rates and Two-dimensional Level Curves in DEA," Journal of Productivity Analysis, Springer, vol. 9(3), pages 205-232, March.
    24. Yue Liu & Aijun Yang & Jijian Zhang & Jingjing Yao, 2020. "An Optimal Stopping Problem of Detecting Entry Points for Trading Modeled by Geometric Brownian Motion," Computational Economics, Springer;Society for Computational Economics, vol. 55(3), pages 827-843, March.
    25. M C A Silva Portela & E Thanassoulis & G Simpson, 2004. "Negative data in DEA: a directional distance approach applied to bank branches," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(10), pages 1111-1121, October.
    26. Lee, Taehwee & Yeo, Gi-Tae & Thai, Vinh V., 2014. "Environmental efficiency analysis of port cities: Slacks-based measure data envelopment analysis approach," Transport Policy, Elsevier, vol. 33(C), pages 82-88.
    27. Abdullah Gök & John Rigby & Philip Shapira, 2016. "The impact of research funding on scientific outputs: Evidence from six smaller European countries," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(3), pages 715-730, March.
    28. Takanori Ida & Naomi Fukuzawa, 2013. "Effects of large-scale research funding programs: a Japanese case study," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 1253-1273, March.
    29. Yue Liu & Lixin Tian & Zhuyun Xie & Zaili Zhen & Huaping Sun, 2021. "Option to survive or surrender: carbon asset management and optimization in thermal power enterprises from China," Papers 2104.04729, arXiv.org.
    30. Banker, Rajiv D. & Chang, Hsihui & Cooper, William W., 1996. "Equivalence and implementation of alternative methods for determining returns to scale in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 89(3), pages 473-481, March.
    31. Taleb, Mushtaq & Khalid, Ruzelan & Ramli, Razamin & Ghasemi, Mohammad Reza & Ignatius, Joshua, 2022. "An integrated bi-objective data envelopment analysis model for measuring returns to scale," European Journal of Operational Research, Elsevier, vol. 296(3), pages 967-979.
    32. Mohammad Khodabakhshi & Farhad Hosseinzadeh Lotfi & Kourosh Aryavash, 2014. "Review of Input Congestion Estimating Methods in DEA," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-9, April.
    33. Krist Vaesen & Joel Katzav, 2017. "How much would each researcher receive if competitive government research funding were distributed equally among researchers?," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-11, September.
    34. Vincent Larivière & Benoit Macaluso & Éric Archambault & Yves Gingras, 2010. "Which scientific elites? On the concentration of research funds, publications and citations," Research Evaluation, Oxford University Press, vol. 19(1), pages 45-53, March.
    35. Zhu, Joe, 2001. "Super-efficiency and DEA sensitivity analysis," European Journal of Operational Research, Elsevier, vol. 129(2), pages 443-455, March.
    36. Fukuyama, Hirofumi, 2003. "Scale characterizations in a DEA directional technology distance function framework," European Journal of Operational Research, Elsevier, vol. 144(1), pages 108-127, January.
    37. Carter Bloch & Mads P. Sørensen, 2015. "The size of research funding: Trends and implications," Science and Public Policy, Oxford University Press, vol. 42(1), pages 30-43.
    38. Siri Brorstad Borlaug, 2016. "Moral hazard and adverse selection in research funding: Centres of excellence in Norway and Sweden," Science and Public Policy, Oxford University Press, vol. 43(3), pages 352-362.
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