The relationships within the carbon emissions game are diverse and intricate, encompassing both horizontal games between regions and vertical games involving governments, enterprises, and the public. To explore the complex game relationships among carbon emission entities, this study integrated horizontal and vertical games and applied the system dynamics method to construct a multilevel and multiagent cross-game model, analyzing the changing trends of strategies among different regional governments, enterprises, and the public. The research reveals that there is free-riding behavior in the governance of carbon emissions among regions. However, this free-riding behavior can lead to a virtuous cycle. The attitude of the government plays a crucial role in determining whether businesses engage in carbon emission management. Increasing government regulatory efficiency does not alter the outcome of the game, but it can reduce the time required to reach Nash equilibrium. The study enhances the simulation of carbon emission game theory and provides a reliable reference for government regulation and low-carbon development in businesses.
JiaoLYangRChenB, et al.Variation, determinants and prediction of carbon emissions in Guizhou, a new economic growth pole in southwest China. J Cleaner Prod2023; 417: 138049.
2.
JiangHYinJZhangB, et al.Industrial carbon emission distribution and regional joint emission reduction: a case study of cities in the pearl river Basin, China. Chinese Geographical Science2024; 34: 210–229.
3.
CainMLynchJAllenMR, et al.Improved calculation of warming-equivalent emissions for short-lived climate pollutants. npj Climate and Atmospheric Science2019; 2: 29.
4.
WeiDYinJXiaR, et al.Study on the coordinated development of urban competitiveness and energy-carbon emission reduction in China. Environ Res2024; 251: 118689.
5.
JiangHYinJQiuY, et al.Industrial carbon emission efficiency of cities in the Pearl River Basin: spatiotemporal dynamics and driving forces. Land (Basel)2022; 11: 1129.
6.
XiaRWeiDJiangH, et al.Study on the coupling coordination development of China’s multidimensional digital economy and industrial carbon emission efficiency. Environmental Science and Pollution Research2023; 30: 114201–114221.
7.
ZhangBYinJJiangH, et al.Spatial-temporal pattern evolution and influencing factors of coupled coordination between carbon emission and economic development along the Pearl River Basin in China. Environmental Science and Pollution Research2022; 30: 6875–6890.
8.
ZhangBYinJJiangH, et al.Multi-source data assessment and multi-factor analysis of urban carbon emissions: a case study of the Pearl River Basin, China. Urban Climate2023; 51: 101653.
9.
WeiJWangC. Improving interaction mechanism of carbon reduction technology innovation between supply chain enterprises and government by means of differential game. J Cleaner Prod2021; 296: 126578.
10.
LiuJMengWHuangB, et al.Factors influencing intergovernmental cooperation on emission reduction in Chengdu-Chongqing urban agglomeration: an evolutionary game theory perspective. Int J Environ Res Public Health2022; 19: 14848.
11.
NiePWangCWenH. Optimal tax selection under monopoly: emission tax vs carbon tax. Environ Sci Pollut Res2021; 29: 12157–12163.
12.
SuQYangWLiuY. Optimization of carbon emission considering production planning at enterprise level. J Cleaner Prod2017; 162: 635–645.
13.
WenWZhouPZhangF. Carbon emissions abatement: emissions trading vs consumer awareness. Energy Econ2018; 76: 34–47.
14.
ZhangYMohsenG. Game theory for wireless communications and networking. CRC press, 2011. http://doi.org/10.1201/b10975
15.
WangCWangWHuangR. Supply chain enterprise operations and government carbon tax decisions considering carbon emissions. J Cleaner Prod2017; 152: 271–280.
16.
LeeCHussainJ. Optimal behavior of environmental regulations to reduce carbon emissions: a simulation-based dual green gaming model. Environ Sci Pollut Res2022; 29: 56037–56054.
17.
LuZLiuMLuW, et al.Shared-constraint approach for multi-leader multi-follower game between generation companies and independent system operator with carbon emission trading mechanism. J Cleaner Prod2022; 350: 131424.
18.
ZengYCaiXFengH. Cost and emission allocation for joint replenishment systems subject to carbon constraints. Comput Ind Eng2022; 168: 108074.
19.
HuZWangS. An evolutionary game model between governments and manufacturers considering carbon taxes, subsidies, and consumers’ low-carbon preference. Dyn Games Appl2021; 12: 513–551.
20.
YuanXZhengC. Evolutionary game and simulation analysis of low-carbon technology innovation with multi-agent participation. IEEE Access2022; 10: 11284–11295.
21.
XiaRWeiDJiangH, et al.Research on the coordinated development and convergence characteristics of China’s urban competitiveness and green total factor productivity. Ecol Indic2024; 161: 111954.
22.
LiuLZhangZWangZ. Two-sided matching and game on investing in carbon emission reduction technology under a cap-and-trade system. J Cleaner Prod2020; 282: 124436.
23.
WeiS. A sequential game analysis on carbon tax policy choices in open economies: from the perspective of carbon emission responsibilities. J Cleaner Prod2020; 283: 124588.
24.
MaJYangWLouW. Research on bifurcation and chaos in a dynamic mixed game system with oligopolies under carbon emission constraint. Int J Bifurcation Chaos2017; 27: 1750158.
25.
YuNChenJChengL. Evolutionary game analysis of carbon emission reduction between government and enterprises under carbon quota trading policy. Int J Environ Res Public Health2022; 19: 8565.
26.
RatliffLJBurdenSASastrySS. On the characterization of local Nash equilibria in continuous games. IEEE Trans Autom Control2016; 61: 2301–2307.
27.
RenyPJ. Nash equilibrium in discontinuous games. Annu Rev Econom2020; 12: 439–470.
28.
LuCYangCYenH. Stackelberg game approach for sustainable production-inventory model with collaborative investment in technology for reducing carbon emissions. J Cleaner Prod2020; 270: 121963.
29.
CuiBShuiZYangS, et al.Evolutionary game analysis of green technology innovation under the carbon emission trading mechanism. Frontiers in Environmental Science2022; 10: 997724.
30.
WangYZengX. Governance mechanisms of industrial carbon emissions in heavy industrial zones under environmental justice based on evolutionary game perspective. J Appl Ecol2022; 33: 3195–3204.
31.
XuBLiQ. Research on supervision mechanism of big data discriminatory pricing on the asymmetric service platform—based on SD evolutionary game model. J Theor Appl Electron Commer Res2022; 17: 1243–1263.
32.
WangXDuQLuC, et al.Exploration in carbon emission reduction effect of low-carbon practices in prefabricated building supply chain. J Cleaner Prod2022; 368: 133153.
33.
BaturİBayramISKocM. Impact assessment of supply-side and demand-side policies on energy consumption and CO2 emissions from urban passenger transportation: the case of Istanbul. J Cleaner Prod2019; 219: 391–410.
34.
JiangQMaX. Spillovers of environmental regulation on carbon emissions network. Technol Forecast Soc Change2021; 169: 120825.
35.
ZhuBZhangT. The impact of cross-region industrial structure optimization on economy, carbon emissions and energy consumption: a case of the Yangtze River Delta. Sci Total Environ2021; 778: 146089.
36.
DingYYinJJiangH, et al.A dual-core system dynamics approach for carbon emission spillover effects analysis and cross-regional policy simulation. J Environ Manag2023; 348: 119374.
37.
WeiZWeiKLiuJ, et al.The relationship between agricultural and animal husbandry economic development and carbon emissions in Henan Province, the analysis of factors affecting carbon emissions, and carbon emissions prediction. Mar Pollut Bull2023; 193: 115134.
38.
LiGChenXYouX-Y. System dynamics prediction and development path optimization of regional carbon emissions: a case study of Tianjin. Renewable Sustainable Energy Rev2023; 184: 113579.
39.
RavihariKKasunHHirushieK, et al.Long-term feasibility of carbon capturing in community energy systems: a system dynamics-based evaluation. J Cleaner Prod2022; 377: 134460.
40.
WangGFengY. Assessment and prediction of net carbon emission from fishery in Liaoning Province based on eco-economic system simulation. J Cleaner Prod2023; 419: 138080.
41.
DongZYuXChangC-T, et al.How does feed-in tariff and renewable portfolio standard evolve synergistically? An integrated approach of tripartite evolutionary game and system dynamics. Renewable Energy2022; 186: 864–877.
42.
YuanLHeWDegefuDM, et al.Transboundary water sharing problem; a theoretical analysis using evolutionary game and system dynamics. J Hydrol2020; 582: 124521.
43.
HeRXiongYLinZ. Carbon emissions in a dual channel closed loop supply chain: the impact of consumer free riding behavior. J Cleaner Prod2016; 134: 384–394.
44.
SykesMAxsenJ. No free ride to zero-emissions: simulating a region's need to implement its own zero-emissions vehicle (ZEV) mandate to achieve 2050 GHG targets. Energy Policy2017; 110: 447–460.
45.
YanNZhangYXuX, et al.Online finance with dual channels and bidirectional free-riding effect. Int J Prod Econ2021; 231: 107834.
