IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v13y2024i2p219-d1336598.html
   My bibliography  Save this article

Spatial–Temporal Characteristics and Influencing Factors of Eco-Efficiency of Cultivated Land Use in the Yangtze River Delta Region

Author

Listed:
  • Yeting Fan

    (School of Public Administration, Nanjing University of Finance & Economics, 3 Wenyuan Road, Qixia Distinct, Nanjing 210023, China
    The Key Laboratory of Carbon Neutrality and Territory Optimization, Ministry of Natural Resources, Nanjing 210023, China)

  • Wenjing Ning

    (School of Public Administration, Nanjing University of Finance & Economics, 3 Wenyuan Road, Qixia Distinct, Nanjing 210023, China)

  • Xinyuan Liang

    (School of Geography and Ocean Sciences, Nanjing University, Nanjing 210023, China)

  • Lingzhi Wang

    (College of Earth Sciences, Jilin University, Changchun 130061, China)

  • Ligang Lv

    (School of Public Administration, Nanjing University of Finance & Economics, 3 Wenyuan Road, Qixia Distinct, Nanjing 210023, China)

  • Ying Li

    (School of Public Administration, Nanjing University of Finance & Economics, 3 Wenyuan Road, Qixia Distinct, Nanjing 210023, China)

  • Junxiao Wang

    (School of Public Administration, Nanjing University of Finance & Economics, 3 Wenyuan Road, Qixia Distinct, Nanjing 210023, China)

Abstract

The sustainable utilization of regional cultivated land systems in the Yangtze River Delta (YRD) region over the past 40 years has been severely impacted by rapid urbanization processes. Improving the eco-efficiency of cultivated land use (ECLU) plays a significant role in achieving the sustainable utilization of farmland and high-quality development of agriculture and rural areas. In this study, the spatial–temporal features and influencing factors of the ECLU in the YRD are investigated by various methods, such as a super-efficient SBM model, hot spot analysis, Dagum Gini coefficient, and panel tobit model. The findings indicate the following: the ECLU showed an overall high level from 2000 to 2020; the ECLU varied significantly over time and space in the YRD. The ECLU presented obvious spatial agglomeration in the YRD: southern regions exhibited a concentration of cold spots, while hot spots were primarily found in the east and north of the YRD. The trend of regional differences in ECLU during the research period fluctuated upwards in the YRD, and the density difference super-variable was the main source of regional differences. Increases in urbanization level and GDP per capita contributed to ECLU enhancement in the YRD, and agricultural intensity levels and agricultural industrial structures played a negative role in ECLU improvement. Finally, we suggest that different regions should adapt to local conditions, scientifically and reasonably allocate cultivated land production resources, and promote the coordinated improvement of ECLU. This study could provide a reference for policymakers to formulate better decisions on cultivated land utilization and management.

Suggested Citation

  • Yeting Fan & Wenjing Ning & Xinyuan Liang & Lingzhi Wang & Ligang Lv & Ying Li & Junxiao Wang, 2024. "Spatial–Temporal Characteristics and Influencing Factors of Eco-Efficiency of Cultivated Land Use in the Yangtze River Delta Region," Land, MDPI, vol. 13(2), pages 1-20, February.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:2:p:219-:d:1336598
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/13/2/219/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/13/2/219/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dagum, Camilo, 1997. "A New Approach to the Decomposition of the Gini Income Inequality Ratio," Empirical Economics, Springer, vol. 22(4), pages 515-531.
    2. Xiang Luo & Zuo Zhang & Xinhai Lu & Lu Zhang, 2019. "Topographic heterogeneity, rural labour transfer and cultivated land use: An empirical study of plain and low‐hill areas in China," Papers in Regional Science, Wiley Blackwell, vol. 98(5), pages 2157-2178, October.
    3. Xiangzheng Deng & John Gibson, 2020. "Sustainable land use management for improving land eco-efficiency: a case study of Hebei, China," Annals of Operations Research, Springer, vol. 290(1), pages 265-277, July.
    4. Xiao Lu & Yi Qu & Piling Sun & Wei Yu & Wenlong Peng, 2020. "Green Transition of Cultivated Land Use in the Yellow River Basin: A Perspective of Green Utilization Efficiency Evaluation," Land, MDPI, vol. 9(12), pages 1-22, November.
    5. Greene, William H, 1981. "On the Asymptotic Bias of the Ordinary Least Squares Estimator of the Tobit Model," Econometrica, Econometric Society, vol. 49(2), pages 505-513, March.
    6. Du, Juan & Liang, Liang & Zhu, Joe, 2010. "A slacks-based measure of super-efficiency in data envelopment analysis: A comment," European Journal of Operational Research, Elsevier, vol. 204(3), pages 694-697, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xingjia Wang & Dongyan Wang, 2024. "Breaking Spatial Constraints: A Dimensional Perspective-Based Analysis of the Eco-Efficiency of Cultivated Land Use and Its Spatial Association Network," Land, MDPI, vol. 13(12), pages 1-19, December.

    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. Guiying Liu & Mengqi Yang, 2024. "Characteristics of Spatial–Temporal Evolution of Sustainable Intensification of Cultivated Land Use and Analysis of Influencing Factors in China, 2001–2020," Sustainability, MDPI, vol. 16(23), pages 1-22, December.
    2. Ellis Scharfenaker, Markus P.A. Schneider, 2019. "Labor Market Segmentation and the Distribution of Income: New Evidence from Internal Census Bureau Data," Working Paper Series, Department of Economics, University of Utah 2019_08, University of Utah, Department of Economics.
    3. Stéphane Mussard & Kuan Xu, 2006. "Multidimensional Decomposition of the Sen Index: Some Further Thoughts," Cahiers de recherche 06-08, Departement d'économique de l'École de gestion à l'Université de Sherbrooke.
    4. Charles Condevaux & Stéphane Mussard & Téa Ouraga & Guillaume Zambrano, 2020. "Generalized Gini linear and quadratic discriminant analyses," METRON, Springer;Sapienza Università di Roma, vol. 78(2), pages 219-236, August.
    5. Luc Savard & Stéphane Mussard, 2005. "Micro-simulation and Multi-decomposition: A Case Study: Philippines," Cahiers de recherche 05-02, Departement d'économique de l'École de gestion à l'Université de Sherbrooke.
    6. Ruijing Zheng & Yu Cheng & Haimeng Liu & Wei Chen & Xiaodong Chen & Yaping Wang, 2022. "The Spatiotemporal Distribution and Drivers of Urban Carbon Emission Efficiency: The Role of Technological Innovation," IJERPH, MDPI, vol. 19(15), pages 1-22, July.
    7. Maximilian Riedl & Ingo Geishecker, 2014. "Keep it simple: estimation strategies for ordered response models with fixed effects," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(11), pages 2358-2374, November.
    8. Xianpu Xu & Tieshan Zhao, 2024. "Towards Green Development: Exploring the Impact of Housing Price Bubbles on Regional Green Innovation Efficiency Based on Chinese Provincial Panel Data Analysis," Sustainability, MDPI, vol. 16(23), pages 1-23, November.
    9. Lee, Chien-Chiang & Qian, Anqi, 2024. "Regional differences, dynamic evolution, and obstacle factors of cultivated land ecological security in China," Socio-Economic Planning Sciences, Elsevier, vol. 94(C).
    10. Pan Wenjie & Mei Daniel Weiyue, 2022. "Comprehensive Evaluation of China's Green Urbanization Level--Measurement Based on Provincial Panel Data," International Business Research, Canadian Center of Science and Education, vol. 15(9), pages 1-16, September.
    11. Qiangyi Li & Jiexiao Ge & Mingyu Huang & Xiaoyu Wu & Houbao Fan, 2024. "Uncovering the Triple Synergy of New-Type Urbanization, Greening and Digitalization in China," Land, MDPI, vol. 13(7), pages 1-24, July.
    12. Long Qian & Yunjie Zhou & Ying Sun, 2023. "Regional Differences, Distribution Dynamics, and Convergence of the Green Total Factor Productivity of China’s Cities under the Dual Carbon Targets," Sustainability, MDPI, vol. 15(17), pages 1-26, August.
    13. K. -L. Wang & Y. -T. Tseng & C. -C. Weng, 2003. "A study of production efficiencies of integrated securities firms in Taiwan," Applied Financial Economics, Taylor & Francis Journals, vol. 13(3), pages 159-167.
    14. Danijela Tuljak-Suban & Patricija Bajec, 2022. "A Hybrid DEA Approach for the Upgrade of an Existing Bike-Sharing System with Electric Bikes," Energies, MDPI, vol. 15(21), pages 1-23, October.
    15. Allanson, Paul, 2017. "Monitoring income-related health differences between regions in Great Britain: A new measure for ordinal health data," Social Science & Medicine, Elsevier, vol. 175(C), pages 72-80.
    16. Awadh Pratap Singh & Shiv Prasad Yadav & Preeti Tyagi, 2022. "Performance assessment of higher educational institutions in India using data envelopment analysis and re-evaluation of NIRF Rankings," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(2), pages 1024-1035, April.
    17. Nan Li & Beibei Shi & Rong Kang, 2023. "Analysis of the Coupling Effect and Space-Time Difference between China’s Digital Economy Development and Carbon Emissions Reduction," IJERPH, MDPI, vol. 20(1), pages 1-25, January.
    18. Yaoyao Wang & Yuanpei Kuang, 2023. "Evaluation, Regional Disparities and Driving Mechanisms of High-Quality Agricultural Development in China," Sustainability, MDPI, vol. 15(7), pages 1-20, April.
    19. Zhao, Feifei & Hu, Zheng & Yi, Ping & Zhao, Xu, 2024. "Does environmental decentralization improve industrial ecology? Evidence from China's Yangtze River Economic Belt," Economic Analysis and Policy, Elsevier, vol. 82(C), pages 1250-1270.
    20. Richard Mussa, 2013. "Rural--urban differences in parental spending on children's primary education in Malawi," Development Southern Africa, Taylor & Francis Journals, vol. 30(6), pages 789-811, December.

    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:jlands:v:13:y:2024:i:2:p:219-:d:1336598. 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.