How to promote local governments collaboration? evidence from carbon reduction in the Yangtze River Delta

China’s central government has proposed a “dual carbon” goal to promote carbon peaking in every province. Collaboration on carbon reduction among local governments is considered an efficient approach to address the carbon emission issues in China. In response, the YRD region implemented the collabor...

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Main Authors: Yue Liu, Yaodong Cang
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-08-01
Series:Frontiers in Environmental Science
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fenvs.2025.1620195/full
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author Yue Liu
Yaodong Cang
author_facet Yue Liu
Yaodong Cang
author_sort Yue Liu
collection DOAJ
description China’s central government has proposed a “dual carbon” goal to promote carbon peaking in every province. Collaboration on carbon reduction among local governments is considered an efficient approach to address the carbon emission issues in China. In response, the YRD region implemented the collaborative mechanism and achieved success in carbon reduction. However, there are still some factors that limit the effectiveness of collaboration, such as inconsistencies in priority sectors and goals for carbon reduction. Therefore, comprehensively identifying the factors that influence collaboration would contribute to understanding the reasons for inefficient collaboration, and exploring the relationships among these factors could provide guidance on promoting collaboration. This study presents a structural model and an impact mechanism model for collaboration through grounded theory, cluster analysis and variation coefficient analysis. The results suggest that there are five factors that influence collaboration: Equitable allocation and pressure from monitoring are pressure factors, governance cost and collaborative benefit are state factors, and governance responsibility is the individual factor. The pressure factors could affect collaboration by affecting state factors, while individual factor plays a moderating role between state factors and collaboration. The research findings provide new insights for promoting collaboration on carbon reduction.
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publisher Frontiers Media S.A.
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spelling doaj-art-8575cd57c5704a5d8fe762e6f19b79f92025-08-20T03:59:45ZengFrontiers Media S.A.Frontiers in Environmental Science2296-665X2025-08-011310.3389/fenvs.2025.16201951620195How to promote local governments collaboration? evidence from carbon reduction in the Yangtze River DeltaYue Liu0Yaodong Cang1College of Economics and Management, Nanjing Forestry University, Nanjing, ChinaSchool of Economics and Management, Dalian University of Technology, Dalian, ChinaChina’s central government has proposed a “dual carbon” goal to promote carbon peaking in every province. Collaboration on carbon reduction among local governments is considered an efficient approach to address the carbon emission issues in China. In response, the YRD region implemented the collaborative mechanism and achieved success in carbon reduction. However, there are still some factors that limit the effectiveness of collaboration, such as inconsistencies in priority sectors and goals for carbon reduction. Therefore, comprehensively identifying the factors that influence collaboration would contribute to understanding the reasons for inefficient collaboration, and exploring the relationships among these factors could provide guidance on promoting collaboration. This study presents a structural model and an impact mechanism model for collaboration through grounded theory, cluster analysis and variation coefficient analysis. The results suggest that there are five factors that influence collaboration: Equitable allocation and pressure from monitoring are pressure factors, governance cost and collaborative benefit are state factors, and governance responsibility is the individual factor. The pressure factors could affect collaboration by affecting state factors, while individual factor plays a moderating role between state factors and collaboration. The research findings provide new insights for promoting collaboration on carbon reduction.https://www.frontiersin.org/articles/10.3389/fenvs.2025.1620195/fullcollaboration on carbon reductionlocal governmentsgrounded theoryK-means clustervariation coefficient analysis
spellingShingle Yue Liu
Yaodong Cang
How to promote local governments collaboration? evidence from carbon reduction in the Yangtze River Delta
Frontiers in Environmental Science
collaboration on carbon reduction
local governments
grounded theory
K-means cluster
variation coefficient analysis
title How to promote local governments collaboration? evidence from carbon reduction in the Yangtze River Delta
title_full How to promote local governments collaboration? evidence from carbon reduction in the Yangtze River Delta
title_fullStr How to promote local governments collaboration? evidence from carbon reduction in the Yangtze River Delta
title_full_unstemmed How to promote local governments collaboration? evidence from carbon reduction in the Yangtze River Delta
title_short How to promote local governments collaboration? evidence from carbon reduction in the Yangtze River Delta
title_sort how to promote local governments collaboration evidence from carbon reduction in the yangtze river delta
topic collaboration on carbon reduction
local governments
grounded theory
K-means cluster
variation coefficient analysis
url https://www.frontiersin.org/articles/10.3389/fenvs.2025.1620195/full
work_keys_str_mv AT yueliu howtopromotelocalgovernmentscollaborationevidencefromcarbonreductionintheyangtzeriverdelta
AT yaodongcang howtopromotelocalgovernmentscollaborationevidencefromcarbonreductionintheyangtzeriverdelta