Exploring the drivers of green agricultural development (GAD) in China: A spatial association network structure approaches

Zhe Chen, Apurbo Sarkar, Airin Rahman, Xiaojing Li and Xianli Xia

Land Use Policy, 2022, vol. 112, issue C

Abstract: Green agricultural development (GAD) becomes one of the major concerns for not only China’s fostering agricultural development but also part and parcel step for mitigating sustainable development (SD) goals set by the United Nations (UN). This notion is also addressed by the Nineteenth National People’s Congress and declared as a national strategy for constructing agro-ecological culture within China. The study provided a robust assessment of the spatial association network of GAD across 31 provinces in China from 2003 to 2018 by employing a modified gravity model and social network analysis method. More specifically, we adopted a combined tactic of entropy weight and linear addition framework. The results indicated that (i) the structure of agricultural green association networks are stable in China and possessed good accessibility, the links between provinces and blocks are relatively close, and the spillover effect between provinces is noticeable. (ii) The geographical network portrayed a “core-edge” spatial variation, whereas the expanding trend has been traced within the core area and shrinking within the border area. The core area gradually extended from southeast coastal provinces to the North-South parts of the country. (iii) The demographic characteristics of network components significantly impact GAD and possess differences among provinces. The differences in industrial structure, economic development, spatial adjacency, urbanization development, and transportation development of different provinces affected the GAD network. On this basis, the paper puts forward the policy suggestions of green coordinated development and governance of China's agriculture.

Keywords: Green development; Spatial association network; Entropy weight method; Social network analysis; Spatial correlation (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (18)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:lauspo:v:112:y:2022:i:c:s0264837721005500

DOI: 10.1016/j.landusepol.2021.105827

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