IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i20p13683-d949469.html
   My bibliography  Save this article

Research on the Efficiency of Green Agricultural Science and Technology Innovation Resource Allocation Based on a Three-Stage DEA Model—A Case Study of Anhui Province, China

Author

Listed:
  • Sheng Yao

    (Institute of Agricultural Economics and Information, Anhui Academy of Agricultural Sciences, Hefei 230031, China)

  • Guosong Wu

    (School of Economics and Management, Huzhou University, Huzhou 313000, China
    Institute of “Two Mountains” Theory, Huzhou University, Huzhou 313000, China)

Abstract

In order to achieve sustainable development of agriculture, people have gradually begun to attach importance to the development of low-carbon agriculture and to regard green agricultural technology innovation and promotion as increasingly more important. Taking the Anhui Province of China as an example, this study analyzed the impact of green agricultural science and technology innovation resource allocation on rural revitalization by constructing an econometric model. We found that the overall efficiency of the overall allocation of agricultural science and technology innovation resources in Anhui Province increased in the sample period, but the scale efficiency level was relatively low. The key path to improving the overall efficiency of allocation was to improve the scale efficiency level. The allocation of agricultural science and technology innovation resources in 16 cities and prefectures performed well in terms of pure technical efficiency, but there were significant differences in scale efficiency, which further affected the overall allocation efficiency of different regions. Among them, the allocation efficiencies of agricultural science and technology innovation resources in Hefei and Fuyang were at the leading level in Anhui Province. Similar to the overall situation of the province, the improvement path of areas with low comprehensive efficiency lay in the improvement of scale efficiency. In view of this, from the policy level, we need to optimize the relationship between the government and the market, speed up the construction of platforms and carriers, attach importance to the construction of the agricultural science and technology talent training system, and improve the open sharing mechanism.

Suggested Citation

  • Sheng Yao & Guosong Wu, 2022. "Research on the Efficiency of Green Agricultural Science and Technology Innovation Resource Allocation Based on a Three-Stage DEA Model—A Case Study of Anhui Province, China," IJERPH, MDPI, vol. 19(20), pages 1-12, October.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:20:p:13683-:d:949469
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/20/13683/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/20/13683/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. H. Fried & C. Lovell & S. Schmidt & S. Yaisawarng, 2002. "Accounting for Environmental Effects and Statistical Noise in Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 17(1), pages 157-174, January.
    2. Matthew Rafferty & Mark Funk, 2004. "Demand shocks and firm-financed R&D expenditures," Applied Economics, Taylor & Francis Journals, vol. 36(14), pages 1529-1536.
    3. Xiangyu Guo & Canhui Deng & Dan Wang & Xu Du & Jiali Li & Bowen Wan, 2021. "International Comparison of the Efficiency of Agricultural Science, Technology, and Innovation: A Case Study of G20 Countries," Sustainability, MDPI, vol. 13(5), pages 1-16, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499.
    2. Jia Li & Yahong Zheng & Bing Liu & Yanyi Chen & Zhihang Zhong & Chenyu Dong & Chaoqun Wang, 2024. "The Synergistic Relationship between Low-Carbon Development of Road Freight Transport and Its Economic Efficiency—A Case Study of Wuhan, China," Sustainability, MDPI, vol. 16(7), pages 1-21, March.
    3. Zhang, Zumeng & Ding, Liping & Wang, Chaofan & Dai, Qiyao & Shi, Yin & Zhao, Yujia & Zhu, Yuxuan, 2022. "Do operation and maintenance contracts help photovoltaic poverty alleviation power stations perform better?," Energy, Elsevier, vol. 259(C).
    4. Jens Kjærsgaard & Niels Vestergaard & Kristiaan Kerstens, 2009. "Ecological Benchmarking to Explore Alternative Fishing Schemes to Protect Endangered Species by Substitution: The Danish Demersal Fishery in the North Sea," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 43(4), pages 573-590, August.
    5. Ren, Siyu & Hao, Yu & Wu, Haitao, 2022. "The role of outward foreign direct investment (OFDI) on green total factor energy efficiency: Does institutional quality matters? Evidence from China," Resources Policy, Elsevier, vol. 76(C).
    6. Nolwenn Roudaut & Anne Vanhems, 2012. "Explaining firms efficiency in the Ivorian manufacturing sector: a robust nonparametric approach," Journal of Productivity Analysis, Springer, vol. 37(2), pages 155-169, April.
    7. Fu, Shuke & Ge, Yingchen & Hao, Yu & Peng, Jiachao & Tian, Jiali, 2024. "Energy supply chain efficiency in the digital era: Evidence from China's listed companies," Energy Economics, Elsevier, vol. 134(C).
    8. Miki Tsutsui & Kaoru Tone, 2007. "Separation of uncontrollable factors and time shift effects from DEA scores," GRIPS Discussion Papers 07-09, National Graduate Institute for Policy Studies.
    9. Yang, Shang-Ho & Burdine, Kenneth H. & Hu, Wu-Yueh, 2016. "An Alternative Approach to Estimate the Economic Loss of Porcine Epidemic Diarrhea (PED) via Data Envelopment Analysis: The Case in Taiwan," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235574, Agricultural and Applied Economics Association.
    10. Pengyu Ren & Zhaoxia Liu, 2021. "Efficiency Evaluation of China’s Public Sports Services: A Three-Stage DEA Model," IJERPH, MDPI, vol. 18(20), pages 1-12, October.
    11. Ke Huang & Martin Dallimer & Lindsay C. Stringer & Anlu Zhang & Ting Zhang, 2021. "Does Economic Agglomeration Lead to Efficient Rural to Urban Land Conversion? An Examination of China’s Metropolitan Area Development Strategy," Sustainability, MDPI, vol. 13(4), pages 1-19, February.
    12. Huayong Niu & Zhishuo Zhang & Yao Xiao & Manting Luo & Yumeng Chen, 2022. "A Study of Carbon Emission Efficiency in Chinese Provinces Based on a Three-Stage SBM-Undesirable Model and an LSTM Model," IJERPH, MDPI, vol. 19(9), pages 1-19, April.
    13. Yu, Ming-Miin, 2010. "Assessment of airport performance using the SBM-NDEA model," Omega, Elsevier, vol. 38(6), pages 440-452, December.
    14. Weixin Yang & Lingguang Li, 2017. "Energy Efficiency, Ownership Structure, and Sustainable Development: Evidence from China," Sustainability, MDPI, vol. 9(6), pages 1-26, June.
    15. Wanke, Peter & Barros, C.P. & Figueiredo, Otávio, 2016. "Efficiency and productive slacks in urban transportation modes: A two-stage SDEA-Beta Regression approach," Utilities Policy, Elsevier, vol. 41(C), pages 31-39.
    16. Brown, Rayna, 2006. "Mismanagement or mismeasurement? Pitfalls and protocols for DEA studies in the financial services sector," European Journal of Operational Research, Elsevier, vol. 174(2), pages 1100-1116, October.
    17. Kozo Harimaya & Kei Tomimura & Nobuyoshi Yamori, 2015. "Efficiencies of Small Financial Cooperatives in Japan: Comparison of Estimation Methods," Discussion Paper Series DP2015-04, Research Institute for Economics & Business Administration, Kobe University.
    18. Antonis Adam & Manthos Delis & Pantelis Kammas, 2011. "Public sector efficiency: leveling the playing field between OECD countries," Public Choice, Springer, vol. 146(1), pages 163-183, January.
    19. Fenfang Xu & Teng Shao & Ruili Hu & Minbo Zhang, 2024. "Research on Energy-Saving Efficiency and Influencing Factors of Green and Low-Carbon Enterprises Based on Three-Stage DEA and Tobit Models," Sustainability, MDPI, vol. 16(17), pages 1-19, August.
    20. Tavana, Madjid & Ebrahimnejad, Ali & Santos-Arteaga, Francisco J. & Mansourzadeh, Seyed Mehdi & Matin, Reza Kazemi, 2018. "A hybrid DEA-MOLP model for public school assessment and closure decision in the City of Philadelphia," Socio-Economic Planning Sciences, Elsevier, vol. 61(C), pages 70-89.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:20:p:13683-:d:949469. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.