Research on the Spatial Correlation Network and Driving Mechanism of Agricultural Green Development in China
Year: 2025
Type: article
Abstract: Agricultural green development is an essential pathway to achieving comprehensive agricultural and rural modernization and holds significant importance for ensuring national food, resource, and ecological security. Based on panel data from 30 provinces in China during 2004–2022, this study employed the super-efficiency SBM-GML model, the modified gravity model, social network analysis (SNA), and the quadratic assignment procedure (QAP) regression model to systematically analyze the spatial association network characteristics and driving mechanisms of agricultural green development in China. The results showed that (1) the number of spatial linkages in interprovincial agricultural green development had been increasing, with the network exhibiting strong connectivity, stability, and accessibility. (2) Major grain-producing areas and economically developed regions along the eastern coast had become the driving sources of spatial spillovers in agricultural green development. Meanwhile, the central and western regions acted as “brokers” in facilitating the reception and transfer of resources within the overall network, while municipalities such as Tianjin and Shanghai exhibited siphon effects on other regions. (3) Geographical proximity, government fiscal support, rural labor force size, progress in green technologies, and the agricultural economic development level significantly enhanced the spatial spillover effects of agricultural green development. However, regional disparities in agricultural industrial structures served as a key obstacle to realizing these spillover effects.
Source: Agriculture
Authors: Yu He, Guozhu Fang, Chunjie Qi, Yumeng Gu
Institutions: Huazhong Agricultural University, Zhejiang Party School
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $3,137
Awards: G2076906382, G227674655, G774151456
OpenAlex ID: W4408812992
