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Study on the Behavior Strategy of the Subject of Low-Carbon Retrofit of Residential Buildings Based on Tripartite Evolutionary Game

Author

Listed:
  • Zihan Zhang

    (College of Architectural and Civil Engineering, Xinjiang University, Urumqi 830017, China)

  • Junkang Song

    (College of Architectural and Civil Engineering, Xinjiang University, Urumqi 830017, China)

  • Wanjiang Wang

    (College of Architectural and Civil Engineering, Xinjiang University, Urumqi 830017, China)

Abstract

Under carbon peaking and neutrality constraints, low-carbon retrofitting of residential buildings (LRRB) has become a strategic need for most countries worldwide. However, the development of China’s LRRB market still relies on government guidance without moving towards the goal of autonomous orientation. This area is still a concern for academics. Moreover, many stakeholders are involved in the LRRB, and the secondary stakeholders’ behavioral strategies do not substantially impact the LRRB. So, this paper adopts Mitchell’s score-based approach to identify the core stakeholders, followed by a tripartite evolutionary game model of government, ESCOs, and owners. Based on the system dynamics (SD) model, the evolution rules of the three parties’ behavior strategies and evolution stabilization strategies are analyzed, and the key factors influencing the equilibrium are found. The results of the study show that under the condition that the government adopts the same level of subsidy for ESCOs and owners, ESCOs are more sensitive to the subsidy; with the introduction of penalties under the premise of subsidy, ESCOs can reach evolutionary equilibrium faster; and when the benefits of owners accepting LRRB outweigh the losses, owners will eventually choose to accept retrofit regardless of whether the government subsidizes owners or not. Finally, the paper ends with suggestions for developing an LRRB market. The game model proposed in this paper can provide a scientific reference for stakeholders’ carbon reduction decisions.

Suggested Citation

  • Zihan Zhang & Junkang Song & Wanjiang Wang, 2023. "Study on the Behavior Strategy of the Subject of Low-Carbon Retrofit of Residential Buildings Based on Tripartite Evolutionary Game," Sustainability, MDPI, vol. 15(9), pages 1-25, May.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:9:p:7629-:d:1140719
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    References listed on IDEAS

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    1. Xin Liang & Geoffrey Qiping Shen & Li Guo, 2015. "Improving Management of Green Retrofits from a Stakeholder Perspective: A Case Study in China," IJERPH, MDPI, vol. 12(11), pages 1-20, October.
    2. Daniel Friedman, 1998. "On economic applications of evolutionary game theory," Journal of Evolutionary Economics, Springer, vol. 8(1), pages 15-43.
    3. Ritzberger, Klaus & Weibull, Jorgen W, 1995. "Evolutionary Selection in Normal-Form Games," Econometrica, Econometric Society, vol. 63(6), pages 1371-1399, November.
    4. Sheng-Yuan Wang & Kyung-Tae Lee & Ju-Hyung Kim, 2022. "Green Retrofitting Simulation for Sustainable Commercial Buildings in China Using a Proposed Multi-Agent Evolutionary Game," Sustainability, MDPI, vol. 14(13), pages 1-32, June.
    5. Lu, Chao & Liu, Hu-Chen & Tao, Jie & Rong, Ke & Hsieh, Ying-Che, 2017. "A key stakeholder-based financial subsidy stimulation for Chinese EV industrialization: A system dynamics simulation," Technological Forecasting and Social Change, Elsevier, vol. 118(C), pages 1-14.
    6. Cai, Gangshu & Kock, Ned, 2009. "An evolutionary game theoretic perspective on e-collaboration: The collaboration effort and media relativeness," European Journal of Operational Research, Elsevier, vol. 194(3), pages 821-833, May.
    7. Liang, Xin & Yu, Tao & Hong, Jingke & Shen, Geoffrey Qiping, 2019. "Making incentive policies more effective: An agent-based model for energy-efficiency retrofit in China," Energy Policy, Elsevier, vol. 126(C), pages 177-189.
    8. Xin Liang & Tao Yu & Li Guo, 2017. "Understanding Stakeholders’ Influence on Project Success with a New SNA Method: A Case Study of the Green Retrofit in China," Sustainability, MDPI, vol. 9(10), pages 1-19, October.
    9. Xin, Liu & Yan, Ding & Yujia, Tong & Neng, Zhu & Zhe, Tian, 2014. "Research on the evaluation system for heat metering and existing residential building retrofits in northern regions of China for the 12th five-year period," Energy, Elsevier, vol. 77(C), pages 898-908.
    10. Ming-Qiang Huang & Rui-Juan Lin, 2022. "Evolutionary Game Analysis of Energy-Saving Renovations of Existing Rural Residential Buildings from the Perspective of Stakeholders," Sustainability, MDPI, vol. 14(9), pages 1-20, May.
    11. Chong Jia & Ruixue Zhang & Dan Wang & Daniele Salvati, 2021. "Evolutionary Game Analysis of BIM Adoption among Stakeholders in PPP Projects," Complexity, Hindawi, vol. 2021, pages 1-14, August.
    12. Yuebin Zhang & Xin Yi & Hui Qiu & Jingchuan Chen & Fazal M. Mahomed, 2022. "An Evolutionary Game Analysis of Contractor’s Green Construction Behavior with Government Supervision and WeMedia’s Influence," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-12, May.
    13. Xiaojuan Li & Chen Wang & Mukhtar A. Kassem & Yishu Liu & Kherun Nita Ali, 2022. "Study on Green Building Promotion Incentive Strategy Based on Evolutionary Game between Government and Construction Unit," Sustainability, MDPI, vol. 14(16), pages 1-15, August.
    14. Xiangjun Li & Lianhui Li, 2022. "Evolutionary Game Analysis of Green Building Development Dynamic System under Government Regulation: From the Perspective of the Contractor," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-12, October.
    15. Bobrova, Yekatherina & Papachristos, George & Cooper, Adam, 2022. "Process perspective on homeowner energy retrofits: A qualitative metasynthesis," Energy Policy, Elsevier, vol. 160(C).
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