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Carbon Emission Efficiency Network: Evolutionary Game and Sensitivity Analysis between Differentiated Efficiency Groups and Local Governments

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  • Renjie Zhang

    (China Aerospace Academy of Systems Science and Engineering, Beijing 100089, China)

  • Hsingwei Tai

    (School of Civil and Architectural Engineering, Shandong University of Technology, Zibo 255000, China)

  • Kuotai Cheng

    (Department of Environmental and Cultural Resources, National Tsing Hua University, Hsinchu 300044, Taiwan)

  • Huizhong Dong

    (School of Management, Shandong University of Technology, Zibo 255000, China)

  • Wenhui Liu

    (School of Academy of Fine Arts, Shandong University of Technology, Zibo 255000, China)

  • Junjie Hou

    (China Aerospace Academy of Systems Science and Engineering, Beijing 100089, China)

Abstract

With its proposal of the “double carbon” (peak carbon dioxide emissions and carbon neutralization) goal, China has entered a new stage in creating an ecological civilization and achieving sustainable development. Based on the formation and evolution mechanism of the carbon emission efficiency network, in this study, a trilateral evolutionary game model—including efficiency groups (high- and low-efficiency groups) and local governments—was constructed, in an attempt to discuss the conditions needed for different players and trilateral interconnected systems to implement balanced and stable strategies. Furthermore, the sensitivity of the participants’ evolutionary trajectories toward factors such as the initial strategy ratio, transition cost, and network capital were tested via a system simulation. The main conclusions were as follows: (1) Efficiency groups form a virtuous circle when the initial proportion of the participants’ strategies reaches a certain threshold, and converge into a stable “win–win” state. Under these circumstances, high-efficiency groups tend to give full play to their efficiency advantages in terms of carbon emission reduction and green development, while low-efficiency groups tend to choose green transformation and accept the spillover effect from high-efficiency groups. (2) When efficiency groups achieve a “win–win” state or form good self-management, local governments move from active supervision to a passive supervision strategy in order to reduce supervision costs. (3) While different initial strategy proportions do not affect the stable convergence point of the evolutionary system, they have a differentiated impact on the convergence speed of the players. Under the condition of a low initial strategy ratio, transformation costs can reduce the green transformation enthusiasm of inefficient groups, while network capital can enhance the green transformation willingness of inefficient groups.

Suggested Citation

  • Renjie Zhang & Hsingwei Tai & Kuotai Cheng & Huizhong Dong & Wenhui Liu & Junjie Hou, 2022. "Carbon Emission Efficiency Network: Evolutionary Game and Sensitivity Analysis between Differentiated Efficiency Groups and Local Governments," Sustainability, MDPI, vol. 14(4), pages 1-19, February.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:4:p:2191-:d:749677
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    References listed on IDEAS

    as
    1. Liu, Weihua & Long, Shangsong & Xie, Dong & Liang, Yanjie & Wang, Jinkun, 2021. "How to govern the big data discriminatory pricing behavior in the platform service supply chain?An examination with a three-party evolutionary game model," International Journal of Production Economics, Elsevier, vol. 231(C).
    2. Ying, Zhou & Xin-gang, Zhao, 2021. "The impact of Renewable Portfolio Standards on carbon emission trading under the background of China’s electricity marketization reform," Energy, Elsevier, vol. 226(C).
    3. Jiang, Qichuan & Ma, Xuejiao, 2021. "Spillovers of environmental regulation on carbon emissions network," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    4. Chen, Xing & Lin, Boqiang, 2021. "Towards carbon neutrality by implementing carbon emissions trading scheme: Policy evaluation in China," Energy Policy, Elsevier, vol. 157(C).
    5. Wu, Dong & Geng, Yong & Pan, Hengyu, 2021. "Whether natural gas consumption bring double dividends of economic growth and carbon dioxide emissions reduction in China?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    6. Yu, Yantuan & Zhang, Ning, 2021. "Low-carbon city pilot and carbon emission efficiency: Quasi-experimental evidence from China," Energy Economics, Elsevier, vol. 96(C).
    7. Zhao, Dan & Ji, Shou-feng & Wang, He-ping & Jiang, Li-wen, 2021. "How do government subsidies promote new energy vehicle diffusion in the complex network context? A three-stage evolutionary game model," Energy, Elsevier, vol. 230(C).
    8. Wang, Guofeng & Deng, Xiangzheng & Wang, Jingyu & Zhang, Fan & Liang, Shiqi, 2019. "Carbon emission efficiency in China: A spatial panel data analysis," China Economic Review, Elsevier, vol. 56(C), pages 1-1.
    9. Wen, Wen & Feng, Cuiyang & Zhou, Hao & Zhang, Li & Wu, Xiaohui & Qi, Jianchuan & Yang, Xuechun & Liang, Yuhan, 2021. "Critical provincial transmission sectors for carbon dioxide emissions in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    10. Mahapatra, Bamadev & Irfan, Mohd, 2021. "Asymmetric impacts of energy efficiency on carbon emissions: A comparative analysis between developed and developing economies," Energy, Elsevier, vol. 227(C).
    11. He, Yong & Fu, Feifei & Liao, Nuo, 2021. "Exploring the path of carbon emissions reduction in China’s industrial sector through energy efficiency enhancement induced by R&D investment," Energy, Elsevier, vol. 225(C).
    12. Guo, Li-Yang & Feng, Chao, 2021. "Are there spillovers among China's pilots for carbon emission allowances trading?," Energy Economics, Elsevier, vol. 103(C).
    13. Shi, Yingying & Wei, Zixiang & Shahbaz, Muhammad & Zeng, Yongchao, 2021. "Exploring the dynamics of low-carbon technology diffusion among enterprises: An evolutionary game model on a two-level heterogeneous social network," Energy Economics, Elsevier, vol. 101(C).
    14. Sadawi, Alia Al & Madani, Batool & Saboor, Sara & Ndiaye, Malick & Abu-Lebdeh, Ghassan, 2021. "A comprehensive hierarchical blockchain system for carbon emission trading utilizing blockchain of things and smart contract," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
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    Cited by:

    1. Tao Li & Lei Ma & Zheng Liu & Chaonan Yi & Kaitong Liang, 2023. "Dual Carbon Goal-Based Quadrilateral Evolutionary Game: Study on the New Energy Vehicle Industry in China," IJERPH, MDPI, vol. 20(4), pages 1-16, February.
    2. Hongtao Jiang & Jian Yin & Yuanhong Qiu & Bin Zhang & Yi Ding & Ruici Xia, 2022. "Industrial Carbon Emission Efficiency of Cities in the Pearl River Basin: Spatiotemporal Dynamics and Driving Forces," Land, MDPI, vol. 11(8), pages 1-22, July.

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