Evolutionary Game Theory and the Simulation of Green Building Development Based on Dynamic Government Subsidies
Ye Gao,
Renfu Jia,
Yi Yao and
Jiahui Xu
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Ye Gao: College of Civil Science and Engineering, Yangzhou University, Yangzhou 225127, China
Renfu Jia: College of Civil Science and Engineering, Yangzhou University, Yangzhou 225127, China
Yi Yao: College of Civil Science and Engineering, Yangzhou University, Yangzhou 225127, China
Jiahui Xu: College of Civil Science and Engineering, Yangzhou University, Yangzhou 225127, China
Sustainability, 2022, vol. 14, issue 12, 1-18
Abstract:
The carbon emissions of the construction industry pose a significant challenge to implementing China’s carbon peaking and carbon neutrality goals. This study considered how to promote stable green building (GB) development. First, evolutionary game theory (EGT) was applied to examine the interaction mechanism of complex behaviors between governments and developers, constructing two scenarios of static and dynamic subsidies. Second, we proposed the ideal state where the government does not give funding subsidies and developers take the initiative to build GBs. On this basis, the simulation method was used to verify the game models and primary conclusions. Finally, a detailed sensitivity analysis of selected parameters was undertaken. The results demonstrated that subsidy policy phase-outs could help in the development of GBs; the probability of an ideal state was positively correlated with government supervision and punishment, and it was negatively correlated with government funding subsidies. The research results can be used as a reference for the government to improve incentive measures and decision support for stakeholders to adjust their strategies.
Keywords: green building; evolutionary game theory; Matlab; dynamic subsidies (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (3)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:12:p:7294-:d:838741
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