ORIGINAL RESEARCH
Sustainable Agricultural Development
in China: An Analysis on Spatiotemporal
Evolution and Driving Forces
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School of Statistics and Mathematics, Zhejiang Gongshang University, China
Submission date: 2024-03-18
Final revision date: 2024-05-02
Acceptance date: 2024-05-17
Online publication date: 2024-12-20
Corresponding author
Min Xiao
School of Statistics and Mathematics, Zhejiang Gongshang University, China
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ABSTRACT
Environmental issues worldwide are growing increasingly severe, leading to concerns about
sustainable food systems. Therefore, it is significant to research sustainable agricultural development
(SAD). This study focuses on China as a research area since it is one of the largest agricultural
countries globally. A key objective of this research is the development of a novel evaluation framework
for Sustainable Agricultural Development (SAD), alongside the analysis of the spatiotemporal
differentiation and evolution of China’s SAD levels, and the exploration of the heterogeneity in its
driving factors. The goal is to facilitate relevant departments in formulating differentiated regional
agricultural sustainable development strategies. SAD levels across various Chinese provinces are
evaluated through the development of an index-based assessment system, with a focus on three key
aspects: Resource Conservation, Environmental Friendliness, and Production Efficiency. Additionally,
spatiotemporal differentiation and evolution are analyzed using Kernel Density Estimation and Spatial
Autocorrelation models. We explore the spatiotemporal heterogeneity of driving factors for SAD through
the Geographical and Temporal Weighted Regression (GTWR) model. Findings indicate a steady rise
in SAD levels across China from 2013 to 2021, with notable regional variations. The southeast coastal
region exhibits high SAD levels, while the western inland and northeastern regions show lower levels.
There is a strong positive correlation in SAD levels amongst these selected Chinese provinces, with
increasing agglomeration effects over time. Low-low agglomeration zones are primarily concentrated
in the west, while high-high agglomeration zones are more prevalent in the east. Based on the outcomes,
the factors exhibit spatial and temporal heterogeneity. Economic Development Level, R&D Investment,
and Agricultural Socialized Services positively influence SAD. However, a positive shift to a negative
shift in the impact of Human Capital Education and Openness Level on SAD over time indicates
the areas China’s government should focus on in order to revitalize a path towards great SAD.