ORIGINAL RESEARCH
Sustainable Agricultural Development in China: An Analysis on Spatiotemporal Evolution and Driving Forces
Li Yu 1
,
 
 
 
 
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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.
eISSN:2083-5906
ISSN:1230-1485
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