IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i16p7189-d1720558.html
   My bibliography  Save this article

Improving Ecosystem Services Production Efficiency by Optimizing Resource Allocation in 130 Cities of the Yangtze River Economic Belt, China

Author

Listed:
  • Wenyue Hou

    (Institute of Modern Agricultural Equipment, Xihua University, Chengdu 610039, China)

  • Xiangyu Zheng

    (College of Environmental Sciences, Sichuan Agricultural University, Chengdu 611130, China)

  • Tao Liang

    (Institute of Modern Agricultural Equipment, Xihua University, Chengdu 610039, China)

  • Xincong Liu

    (School of Architecture and Civil Engineering, Chengdu University, Chengdu 610106, China)

  • Hengyu Pan

    (College of Environmental Sciences, Sichuan Agricultural University, Chengdu 611130, China)

Abstract

China has adopted extensive restoration practices to improve ecosystem function. The efficiency of these restoration efforts remains unclear, which may hinder the supply of ecosystem services (ESs). In this context, this study first employed InVEST models to clarify spatio-temporal changes in five key ESs. The static and dynamic efficiencies of ecosystem service production in 130 cities from 2015 to 2021 in the Yangtze River Economic Belt (YREB) were then measured using the Super-SBM-Malmquist model, with ESs considered as outputs. The results indicated that water conservation (WC), water purification (WP), and soil retention (SR) exhibited overall declining trends, decreasing by 28.32%, 3.22%, and 10.00%, respectively, while carbon storage (CS) and habitat quality (HQ) remained steady. More than 70% of studied cities exhibited static efficiency levels below 50%, which were attributed to inefficient utilization of labor, capital, and technology. Significant spatial heterogeneity was observed, with high-efficiency cities mainly located in mountainous areas and low-efficiency cities concentrated in flat regions. The downward trend in dynamic efficiency has been reversed from a 39.02% decline in 2015–2018 to a 38.31% increase in 2018–2021, despite being adversely affected by technological regression. Finally, several policy implications are proposed, including optimizing resource allocation, introducing advanced technology and setting the intercity cooperation and complementarity mechanisms.

Suggested Citation

  • Wenyue Hou & Xiangyu Zheng & Tao Liang & Xincong Liu & Hengyu Pan, 2025. "Improving Ecosystem Services Production Efficiency by Optimizing Resource Allocation in 130 Cities of the Yangtze River Economic Belt, China," Sustainability, MDPI, vol. 17(16), pages 1-20, August.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:16:p:7189-:d:1720558
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/16/7189/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/16/7189/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Liu, Xiping & Zhang, Xiaoling & Sun, Wen, 2022. "Does the agglomeration of urban producer services promote carbon efficiency of manufacturing industry?," Land Use Policy, Elsevier, vol. 120(C).
    2. Ouyang, Xiao & Tang, Lisha & Wei, Xiao & Li, Yonghui, 2021. "Spatial interaction between urbanization and ecosystem services in Chinese urban agglomerations," Land Use Policy, Elsevier, vol. 109(C).
    3. Jiang, Yanan & Guan, Dongjie & He, Xiujuan & Yin, Boling & Zhou, Lilei & Sun, Lingli & Huang, Danan & Li, Zihui & Zhang, Yanjun, 2022. "Quantification of the coupling relationship between ecological compensation and ecosystem services in the Yangtze River Economic Belt, China," Land Use Policy, Elsevier, vol. 114(C).
    4. Wang, Shuhong & Zhao, Danqing & Chen, Hanxue, 2020. "Government corruption, resource misallocation, and ecological efficiency," Energy Economics, Elsevier, vol. 85(C).
    5. Wang, Yi & Wang, Huiping, 2023. "Spatial spillover effect of urban sprawl on total factor energy ecological efficiency: Evidence from 272 cities in China," Energy, Elsevier, vol. 273(C).
    6. Xu, Xibao & Jiang, Bo & Chen, Minkun & Bai, Yang & Yang, Guishan, 2020. "Strengthening the effectiveness of nature reserves in representing ecosystem services: The Yangtze River Economic Belt in China," Land Use Policy, Elsevier, vol. 96(C).
    7. Yu, Anyu & You, Jianxin & Rudkin, Simon & Zhang, Hao, 2019. "Industrial carbon abatement allocations and regional collaboration: Re-evaluating China through a modified data envelopment analysis," Applied Energy, Elsevier, vol. 233, pages 232-243.
    8. Jiang, Bo & Bai, Yang & Wong, Christina P. & Xu, Xibao & Alatalo, Juha M., 2019. "China’s ecological civilization program–Implementing ecological redline policy," Land Use Policy, Elsevier, vol. 81(C), pages 111-114.
    9. Siyuan Cai & Xu Zhao & Cameron M. Pittelkow & Mingsheng Fan & Xin Zhang & Xiaoyuan Yan, 2023. "Optimal nitrogen rate strategy for sustainable rice production in China," Nature, Nature, vol. 615(7950), pages 73-79, March.
    10. 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.
    11. Susaeta, Andres & Sancewich, Brian & Adams, Damian & Moreno, Paulo C., 2019. "Ecosystem Services Production Efficiency of Longleaf Pine Under Changing Weather Conditions," Ecological Economics, Elsevier, vol. 156(C), pages 24-34.
    12. Susaeta, Andres & Sancewich, Brian & Klizentyte, Kotryna & Soto, Jose & Joshi, Omkar, 2024. "Profit efficiency in the provision of ecosystem services in the Cross Timbers forests," Land Use Policy, Elsevier, vol. 136(C).
    13. Lina Ke & Qingli Jiang & Lei Wang & Yao Lu & Yu Zhao & Quanming Wang, 2025. "Spatiotemporal Evolution of Ecosystem Service Value and Its Tradeoffs and Synergies in the Liaoning Coastal Economic Belt," Sustainability, MDPI, vol. 17(12), pages 1-20, June.
    14. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    15. Yuanjie Deng & Wencong Cai & Mengyang Hou & Xiaolong Zhang & Shiyuan Xu & Nan Yao & Yajun Guo & Hua Li & Shunbo Yao, 2022. "How Eco-Efficiency Is the Forestry Ecological Restoration Program? The Case of the Sloping Land Conversion Program in the Loess Plateau, China," Land, MDPI, vol. 11(5), pages 1-20, May.
    16. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    17. Hui Zhang & Yingqi Sun & Zhaoying Fan & Zhi Long & Shilong Wan & Zilong Zhang & Xingpeng Chen, 2023. "Analysis of County-Scale Eco-Efficiency and Spatiotemporal Characteristics in China," Land, MDPI, vol. 12(2), pages 1-21, February.
    18. Li, Jinghui & Bai, Yang & Alatalo, Juha M., 2020. "Impacts of rural tourism-driven land use change on ecosystems services provision in Erhai Lake Basin, China," Ecosystem Services, Elsevier, vol. 42(C).
    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. Amirteimoori, Alireza & Cezar, Asunur & Zadmirzaei, Majid & Susaeta, Andres, 2024. "Environmental performance evaluation in the forest sector: An extended stochastic data envelopment analysis approach," Socio-Economic Planning Sciences, Elsevier, vol. 94(C).
    2. Loske, Dominic & Klumpp, Matthias, 2021. "Human-AI collaboration in route planning: An empirical efficiency-based analysis in retail logistics," International Journal of Production Economics, Elsevier, vol. 241(C).
    3. Sun, Chuanwang & Xu, Shuai & Xu, Mengjie, 2023. "What causes green efficiency losses in Chinese agriculture? A perspective based on input redundancy," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    4. Wen-Min Lu & Shih-Fang Lo, 2012. "Constructing stratifications for regions in China with sustainable development concerns," Quality & Quantity: International Journal of Methodology, Springer, vol. 46(6), pages 1807-1823, October.
    5. Kai Xu & Lawrence Loh & Qiang Chen, 2020. "Sustainable Innovation Governance: An Analysis of Regional Innovation with a Super Efficiency Slack-Based Measure Model," Sustainability, MDPI, vol. 12(7), pages 1-19, April.
    6. Tianshu Yu & Ling Li & Tao Li, 2025. "Impact of Shrinking Cities on Carbon Emission Efficiency in China," Sustainability, MDPI, vol. 17(8), pages 1-22, April.
    7. Xi Jin & Bin Zou & Chan Wang & Kaifeng Rao & Xiaowen Tang, 2019. "Carbon Emission Allocation in a Chinese Province-Level Region Based on Two-Stage Network Structures," Sustainability, MDPI, vol. 11(5), pages 1-24, March.
    8. Shuai Wang & Cunyi Yang & Zhenghui Li, 2021. "Spatio-Temporal Evolution Characteristics and Spatial Interaction Spillover Effects of New-Urbanization and Green Land Utilization Efficiency," Land, MDPI, vol. 10(10), pages 1-26, October.
    9. Tao Xu & Jianxin You & Yilei Shao, 2020. "Efficiency of China’s Listed Securities Companies: Estimation through a DEA-Based Method," Mathematics, MDPI, vol. 8(4), pages 1-16, April.
    10. Zhuyuan Li & Xiaolong Wang & Run Zheng & Sanggyun Na & Chang Liu, 2022. "Evaluation Analysis of the Operational Efficiency and Total Factor Productivity of Container Terminals in China," Sustainability, MDPI, vol. 14(20), pages 1-12, October.
    11. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    12. W-M Lu & S-F Lo, 2007. "A benchmark-learning roadmap for regional sustainable development in China," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(7), pages 841-849, July.
    13. Yongrong Xin & Kengcheng Zheng & Yujiao Zhou & Yangyang Han & P. R. Tadikamalla & Qin Fan, 2022. "Logistics Efficiency under Carbon Constraints Based on a Super SBM Model with Undesirable Output: Empirical Evidence from China’s Logistics Industry," Sustainability, MDPI, vol. 14(9), pages 1-24, April.
    14. Fang, Tao & Fang, Debin & Yu, Bolin, 2022. "Carbon emission efficiency of thermal power generation in China: Empirical evidence from the micro-perspective of power plants," Energy Policy, Elsevier, vol. 165(C).
    15. Adel Hatami-Marbini & Aliasghar Arabmaldar & John Otu Asu, 2022. "Robust productivity growth and efficiency measurement with undesirable outputs: evidence from the oil industry," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(4), pages 1213-1254, December.
    16. Rafael Benítez & Vicente Coll-Serrano & Vicente J. Bolós, 2021. "deaR-Shiny: An Interactive Web App for Data Envelopment Analysis," Sustainability, MDPI, vol. 13(12), pages 1-19, June.
    17. Fang Zhang & Hong Fang & Junjie Wu & Damian Ward, 2016. "Environmental Efficiency Analysis of Listed Cement Enterprises in China," Sustainability, MDPI, vol. 8(5), pages 1-19, May.
    18. Cabrera-Jiménez, Richard & Mateo-Sanz, Josep M. & Gavaldà, Jordi & Jiménez, Laureano & Pozo, Carlos, 2022. "Comparing biofuels through the lens of sustainability: A data envelopment analysis approach," Applied Energy, Elsevier, vol. 307(C).
    19. Mushtaq Taleb & Ruzelan Khalid & Ali Emrouznejad & Razamin Ramli, 2023. "Environmental efficiency under weak disposability: an improved super efficiency data envelopment analysis model with application for assessment of port operations considering NetZero," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(7), pages 6627-6656, July.
    20. Pooja Bansal & Aparna Mehra, 2018. "Multi-period additive efficiency measurement in data envelopment analysis with non-positive and undesirable data," OPSEARCH, Springer;Operational Research Society of India, vol. 55(3), pages 642-661, November.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:jsusta:v:17:y:2025:i:16:p:7189-:d:1720558. 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.