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Efficiency analysis of funding resources for rural revitalization in China based on the concept of sustainable development: evidence from parallel DEA with shared inputs/outputs and Tobit models

Author

Listed:
  • Helu Xiao

    (Hunan Normal University)

  • Qing Wang

    (Hunan Normal University)

  • Tiantian Ren

    (Xiangtan University)

  • Zhongbao Zhou

    (Hunan University)

Abstract

Funding support is essential to the comprehensive implementation of China’s rural revitalization strategy. However, no consensus has currently emerged in the academics and industry on how to measure the efficiency of funding to rural revitalization system (FRRS). In this context, it is of great importance to construct workable measures to depict the FRRS performance. According to the content of rural revitalization strategy, this paper first regards rural revitalization as a network system consisting of five parallel subsystems that interact with each other, and the agricultural loans and fiscal allocations as the shared inputs are consumed for the five subsystems. On this basis, we propose a shared input–output parallel process for FRRS. Second, following the proposed input–output process, we construct a parallel data envelopment analysis (DEA) model with shared inputs/outputs to measure the efficiency of FRRS, where the link between the efficiency of FRRS and its subsystems is further discussed. Third, the Tobit panel model is employed to identify the external factors that affect the obtained FRRS efficiency. Finally, we empirically analyze the FRRS performance for a panel database of 31 provinces (regions) in China during 2017–2022. The evidence reveals that: (i) there is certain individual variation in the global efficiency of FRRS and the corresponding five subsystems during the observed period. The period efficiency of FRSS and subsystems in most provinces shows a fluctuating upward trend, but that of some provinces has been decreasing in recent years; (ii) the regional heterogeneity in FRRS efficiency can be found, which ranges from high to low in the northeastern region, eastern region, central region, and western region; (iii) the development of subsystems and FRRS is not all coordinated, and this incoherence exhibits regional heterogeneity; (iv) the FRRS performance is influenced by a variety of external factors, and their influence is different in terms of direction and magnitude.

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  • Helu Xiao & Qing Wang & Tiantian Ren & Zhongbao Zhou, 2025. "Efficiency analysis of funding resources for rural revitalization in China based on the concept of sustainable development: evidence from parallel DEA with shared inputs/outputs and Tobit models," Operational Research, Springer, vol. 25(3), pages 1-44, September.
  • Handle: RePEc:spr:operea:v:25:y:2025:i:3:d:10.1007_s12351-025-00960-y
    DOI: 10.1007/s12351-025-00960-y
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    1. Manogna R. L. & Aswini Kumar Mishra, 2022. "Agricultural production efficiency of Indian states: Evidence from data envelopment analysis," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4244-4255, October.
    2. Ding, Tao & Zhang, Yun & Zhang, Danlu & Li, Feng, 2023. "Performance evaluation of Chinese research universities: A parallel interactive network DEA approach with shared and fixed sum inputs," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    3. Helu Xiao & Na Wang & Shanping Wang, 2023. "Dynamic sustainability assessment of poverty alleviation in China: evidence from both novel non-convex global two-stage DEA and Malmquist productivity index," Operational Research, Springer, vol. 23(2), pages 1-40, June.
    4. Chen, Ya & Pan, Yongbin & Liu, Haoxiang & Wu, Huaqing & Deng, Guangwei, 2023. "Efficiency analysis of Chinese universities with shared inputs: An aggregated two-stage network DEA approach," Socio-Economic Planning Sciences, Elsevier, vol. 90(C).
    5. Xianhua Tan & Sanggyun Na & Lei Guo & Jing Chen & Zhihua Ruan, 2019. "External Financing Efficiency of Rural Revitalization Listed Companies in China—Based on Two-Stage DEA and Grey Relational Analysis," Sustainability, MDPI, vol. 11(16), pages 1-21, August.
    6. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    7. Yang Liu & Jiajun Qiao & Jie Xiao & Dong Han & Tao Pan, 2022. "Evaluation of the Effectiveness of Rural Revitalization and an Improvement Path: A Typical Old Revolutionary Cultural Area as an Example," IJERPH, MDPI, vol. 19(20), pages 1-24, October.
    8. Xiaohong Zhuang & Zhuyuan Li & Run Zheng & Sanggyun Na & Yulin Zhou, 2021. "Research on the Efficiency and Improvement of Rural Development in China: Based on Two-Stage Network SBM Model," Sustainability, MDPI, vol. 13(5), pages 1-21, March.
    9. Kerstens, Kristiaan & Mazza, Paolo & Ren, Tiantian & Van de Woestyne, Ignace, 2022. "Multi-Time and Multi-Moment Nonparametric Frontier-Based Fund Rating: Proposal and Buy-and-Hold Backtesting Strategy," Omega, Elsevier, vol. 113(C).
    10. Chen, Chih Cheng, 2017. "Measuring departmental and overall regional performance: applying the multi-activity DEA model to Taiwan׳s cities/counties," Omega, Elsevier, vol. 67(C), pages 60-80.
    11. Xiyang Lei & Yongjun Li & Qiwei Xie & Liang Liang, 2015. "Measuring Olympics achievements based on a parallel DEA approach," Annals of Operations Research, Springer, vol. 226(1), pages 379-396, March.
    12. Wade Cook & Moez Hababou & Hans Tuenter, 2000. "Multicomponent Efficiency Measurement and Shared Inputs in Data Envelopment Analysis: An Application to Sales and Service Performance in Bank Branches," Journal of Productivity Analysis, Springer, vol. 14(3), pages 209-224, November.
    13. Gao, Yajuan & Zhang, Congqing & Wang, Yilin & Wang, Shuaihao & Zou, Yunjin & Gao, Junhong & Wang, Zeyu, 2023. "Fiscal decentralization and rural resource utilization efficiency: Evidence from quasi-natural experiment in China," Resources Policy, Elsevier, vol. 87(PB).
    14. Wang, Jing, 2023. "Digital inclusive finance and rural revitalization," Finance Research Letters, Elsevier, vol. 57(C).
    15. Kao, Chiang, 2009. "Efficiency measurement for parallel production systems," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1107-1112, August.
    16. Chen, Yao & Du, Juan & David Sherman, H. & Zhu, Joe, 2010. "DEA model with shared resources and efficiency decomposition," European Journal of Operational Research, Elsevier, vol. 207(1), pages 339-349, November.
    17. C Kao, 2012. "Efficiency decomposition for parallel production systems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 63(1), pages 64-71, January.
    18. Li, Nan & Jiang, Yuqing & Mu, Hailin & Yu, Zhixin, 2018. "Efficiency evaluation and improvement potential for the Chinese agricultural sector at the provincial level based on data envelopment analysis (DEA)," Energy, Elsevier, vol. 164(C), pages 1145-1160.
    19. Cook, Wade D. & Hababou, Moez, 2001. "Sales performance measurement in bank branches," Omega, Elsevier, vol. 29(4), pages 299-307, August.
    20. A. Charnes & W. W. Cooper, 1962. "Programming with linear fractional functionals," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 9(3‐4), pages 181-186, September.
    21. Deng, Haiyan & Zheng, Wangyi & Shen, Zhiyang & Štreimikienė, Dalia, 2023. "Does fiscal expenditure promote green agricultural productivity gains: An investigation on corn production," Applied Energy, Elsevier, vol. 334(C).
    22. Li, Qi & Maasoumi, Esfandiar & Racine, Jeffrey S., 2009. "A nonparametric test for equality of distributions with mixed categorical and continuous data," Journal of Econometrics, Elsevier, vol. 148(2), pages 186-200, February.
    23. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    24. Jie Wu & Beibei Xiong & Qingxian An & Jiasen Sun & Huaqing Wu, 2017. "Total-factor energy efficiency evaluation of Chinese industry by using two-stage DEA model with shared inputs," Annals of Operations Research, Springer, vol. 255(1), pages 257-276, August.
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