Multi-model methods for structural analysis of China’s green economy network based on input-output method

The green economy has been advocated globally as a solution to environmental issues. In China, it is considered a national strategy for future economic development. This study utilizes methods such as Industry Network, Maximum Spanning Tree (MST) method, Leiden Community Clustering (LCC) algorithm, and Weaver-Thomas (WT) model to explore the contribution and position of the green economy and industries in China's economic development. The findings are as follows: (1) The density of China's green industry network has experienced a process of initially tightening and then loosening, ultimately tending towards stability. (2) The trunk structure of China's industrial network remains relatively stable, forming an industrial structure with electricity, heat production and supply as the core. (3) China's industrial and green industry communities continue to improve and become more cohesive, but some green industries are still on the periphery of communities. (4) The ability of green industries to pull other industries is weak, and the subsequent promotion momentum needs to be improved. However, the green industry still has enormous room for growth and potential to unleash its long-term positive multiplier effects. More attention and support need to be given by managers and decision-makers, so that it can make better contributions to society and the economy.

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Publication Details

Journal
PLoS ONE
Published
2024-09-05
DOI
https://doi.org/10.1371/journal.pone.0309916
Citations
1
Primary Topic
Environmental Impact and Sustainability
Type
article
Field-Weighted Citation Impact
0.21

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article

Multi-model methods for structural analysis of China’s green economy network based on input-output method

Jiayao Pan, Shaoling Ding, Jingliang Huai, Meng Yan et al.
1 citations
PLoS ONE
Environmental Impact and Sustainability
0.21
article

Multi-model methods for structural analysis of China’s green economy network based on input-output method

Jiayao Pan, Shaoling Ding, Jingliang Huai, Meng Yan, Yigang Guo
article en
1 citations

Abstract

The green economy has been advocated globally as a solution to environmental issues. In China, it is considered a national strategy for future economic development. This study utilizes methods such as Industry Network, Maximum Spanning Tree (MST) method, Leiden Community Clustering (LCC) algorithm, and Weaver-Thomas (WT) model to explore the contribution and position of the green economy and industries in China's economic development. The findings are as follows: (1) The density of China's green industry network has experienced a process of initially tightening and then loosening, ultimately tending towards stability. (2) The trunk structure of China's industrial network remains relatively stable, forming an industrial structure with electricity, heat production and supply as the core. (3) China's industrial and green industry communities continue to improve and become more cohesive, but some green industries are still on the periphery of communities. (4) The ability of green industries to pull other industries is weak, and the subsequent promotion momentum needs to be improved. However, the green industry still has enormous room for growth and potential to unleash its long-term positive multiplier effects. More attention and support need to be given by managers and decision-makers, so that it can make better contributions to society and the economy.

PLoS ONEVol. 19(9)
Guangxi Normal University (CN), Guilin University of Technology (CN)
National Natural Science Foundation of China, Natural Science Foundation of Guangxi Province
Industry, innovation and infrastructure
Openalex Percentile: Top 51%
Environmental Impact and Sustainability
0.21
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Multi-model methods for structural analysis of China’s green economy network based on input-output method — Jiayao Pan, Shaoling Ding, et al. · PLoS ONE (2024) | TGRS Research Map | TGRS