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An actor-network theory analysis and modelling of carbon reduction policy coordination in China: A collaborative environmental governance perspective.

Authors :
Chu, Zhaopeng
Li, Xiaoyan
Bian, Chen
Yang, Jun
Source :
Journal of Cleaner Production. Feb2024, Vol. 442, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

In order to probe collaborative environmental governance (CEG) in China's "1 + N" policy framework for carbon peak and carbon neutrality, this paper applies the Actor-network theory (ANT) as an analytical framework to explore carbon reduction policy coordination. We then model ANT's relations with an evolutionary game theory (EGT) model to examine the evolutionarily stable strategies in CO 2 emission reduction by various actors including the central government, local governments, commercial banks, and polluting enterprises. Our objective is to examine policy coordination as the key enabler for governing success via an ANT-based mechanism design in China's institutional context. Combining the strength of ANT with a four-party EGT model, we investigate how to improve policy coordination to mobilize the actor-network for promoting CEG. Simulations are conducted to examine the effectiveness of policy coordination involving multiple policy instruments for controlling carbon emissions. The central government fulfills leadership in translating the interests of other actors and shaping the desired collaborative network. Without proper coordination, environmental policies may counteract each other. Government transfers and subsidies have direct impacts, but in the long run enhanced competitiveness and profitability of enterprises represent the intrinsic key to CEG success. From a methodology perspective, policy simulation in an EGT framework represents a novel addition to the research toolbox that expands ANT. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09596526
Volume :
442
Database :
Academic Search Index
Journal :
Journal of Cleaner Production
Publication Type :
Academic Journal
Accession number :
175453963
Full Text :
https://doi.org/10.1016/j.jclepro.2024.140966