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Impact of Land-Use Intensification on the Development of Sustainable Agricultural Green Innovation Technology

Author

Listed:
  • Tao Luo

    (Guizhou University)

  • Zilin Cheng

    (Guizhou Vocational College of Sports)

  • Hongmei Ma

    (Guizhou University)

Abstract

Green technology aims to follow the ecological principles and ecological economic laws, save resources and energy, and avoid, eliminate, or reduce the pollution and destruction of the ecological environment. Agricultural green innovation technology provides a new impetus and opportunity to promote the coordinated development of economy, society, and ecological resources. This study investigates the relationship between land-use intensification and agricultural green development and explores the moderating effect of agricultural technological progress on this relationship. Using panel data from 30 Chinese provinces spanning 2011 to 2020, land-use intensification was quantified using indices of agricultural capital, labor, and energy intensities, and agricultural green development was assessed using a comprehensive index system. The entropy method, non-linear models, and group regression analyses were employed. Our findings reveal a complex, non-linear relationship between land-use intensification and green agricultural development. Specifically, we identified an inverted U-shaped relationship between capital and energy factor intensification and agricultural green development. This was positively moderated by agricultural technological progress. Conversely, a U-shaped relationship is observed with labor factors, with agricultural technological progress diminishing its positive impact. This study suggests that when a high degree of factor intensification has a crowding-out and substitution effect on agricultural green development, land-use intensification needs to be controlled within an optimal range. This research bolsters the theory of land-use intensification and sustainable agricultural green innovation technology. Furthermore, it advocates a balance between productivity and environmental protection and may guide government strategies to optimize land-use policies and promote green technologies for sustainable agriculture.

Suggested Citation

  • Tao Luo & Zilin Cheng & Hongmei Ma, 2024. "Impact of Land-Use Intensification on the Development of Sustainable Agricultural Green Innovation Technology," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(4), pages 20595-20629, December.
    • Handle: RePEc:spr:jknowl:v:15:y:2024:i:4:d:10.1007_s13132-024-01944-7
    DOI: 10.1007/s13132-024-01944-7
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    1. Changhong Chen & Huijie Zhang, 2023. "Evaluation of Green Development Level of Mianyang Agriculture, Based on the Entropy Weight Method," Sustainability, MDPI, vol. 15(9), pages 1-22, May.
    2. Binlei Gong, 2020. "New Growth Accounting," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(2), pages 641-661, March.
    3. Lijun Zuo & Zengxiang Zhang & Kimberly M. Carlson & Graham K. MacDonald & Kate A. Brauman & Yingchun Liu & Wen Zhang & Huayong Zhang & Wenbin Wu & Xiaoli Zhao & Xiao Wang & Bin Liu & Ling Yi & Qingke , 2018. "Progress towards sustainable intensification in China challenged by land-use change," Nature Sustainability, Nature, vol. 1(6), pages 304-313, June.
    4. David H. Autor, 2015. "Why Are There Still So Many Jobs? The History and Future of Workplace Automation," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 3-30, Summer.
    5. Feng, Sanying & He, Wenqi & Li, Feng, 2020. "Model detection and estimation for varying coefficient panel data models with fixed effects," Computational Statistics & Data Analysis, Elsevier, vol. 152(C).
    6. Erb, Karl-Heinz & Haberl, Helmut & Jepsen, Martin Rudbeck & Kuemmerle, Tobias & Lindner, Marcus & Müller, Daniel & Verburg, Peter H & Reenberg, Anette, 2013. "A conceptual framework for analysing and measuring land-use intensity," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 5(5), pages 464-470.
    7. Haiqian Ke & Bo Yang & Shangze Dai, 2022. "Does Intensive Land Use Contribute to Energy Efficiency?—Evidence Based on a Spatial Durbin Model," IJERPH, MDPI, vol. 19(9), pages 1-17, April.
    8. Eanes, Francis R. & Singh, Ajay S. & Bulla, Brian R. & Ranjan, Pranay & Fales, Mary & Wickerham, Benjamin & Doran, Patrick J. & Prokopy, Linda S., 2019. "Crop advisers as conservation intermediaries: Perceptions and policy implications for relying on nontraditional partners to increase U.S. farmers’ adoption of soil and water conservation practices," Land Use Policy, Elsevier, vol. 81(C), pages 360-370.
    9. Min Wan & Haibo Kuang & Yanbo Yang & Bi He & Sue Zhao & Ying Wang & Jingyi Huo, 2023. "Evaluation of Agricultural Green Development Based on Gini Coefficient and Hesitation Fuzzy Multi-Attribute Decision-Making: The Case of China," Agriculture, MDPI, vol. 13(3), pages 1-15, March.
    10. Brzeska, Joanna & Fan, Shenggen & Halsema, Alex & Keyzer, Michiel, 2013. "From subsistence to profit: Transforming smallholder farms," Food policy reports 26, International Food Policy Research Institute (IFPRI).
    11. Tang, Liwei & He, Gang, 2021. "How to improve total factor energy efficiency? An empirical analysis of the Yangtze River economic belt of China," Energy, Elsevier, vol. 235(C).
    12. Jingyi Wang & Kaisi Sun & Jiupai Ni & Deti Xie, 2020. "Evaluation and Factor Analysis of the Intensive Use of Urban Land Based on Technical Efficiency Measurement—A Case Study of 38 Districts and Counties in Chongqing, China," Sustainability, MDPI, vol. 12(20), pages 1-19, October.
    13. Hua Guo & Fan Gu & Yanling Peng & Xin Deng & Lili Guo, 2022. "Does Digital Inclusive Finance Effectively Promote Agricultural Green Development?—A Case Study of China," IJERPH, MDPI, vol. 19(12), pages 1-17, June.
    14. Bonaccorsi, Andrea & Apreda, Riccardo & Fantoni, Gualtiero, 2020. "Expert biases in technology foresight. Why they are a problem and how to mitigate them," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    15. Oliver T. Coomes & Bradford L. Barham & Graham K. MacDonald & Navin Ramankutty & Jean-Paul Chavas, 2019. "Leveraging total factor productivity growth for sustainable and resilient farming," Nature Sustainability, Nature, vol. 2(1), pages 22-28, January.
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