IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v127y2023ipas0140988323006151.html
   My bibliography  Save this article

Social “win-win” promotion of green housing under the four-subject evolutionary game

Author

Listed:
  • Li, Qianwen
  • Qian, Tingyu
  • Wang, Jiaqi
  • Long, Ruyin
  • Chen, Hong
  • Sun, Chuanwang

Abstract

The development of green housing in China has been primarily driven by the government in a top-down manner. To ensure successful promotion and maximize economic benefits, it is crucial for government departments to accurately understand the payment behavior of residents, the key demand-side participants in China's green housing market. Additionally, realtors stand to benefit from better understanding residents' preferences and employing more accurate marketing strategies, leading to mutually beneficial outcomes for the economy, environment, and society. This study incorporates the main stakeholders of green housing (government, realtors, and residents) into a four-party evolutionary game model, introducing a “virtual game party” (virtual government) under different policy scenarios: no policy, incentive policy, and mandatory policy. The Matlab simulation results indicate that the greater the level of neglect by the government, the more inclined it becomes to adopt incentive or mandatory policies. As the government's penalties become more stringent, real estate developers are more likely to choose to engage in the development and construction of green housing. This, in turn, influences the decisions of the government and residents. Higher government subsidies lead to a greater likelihood of real estate developers choosing to develop green housing, and residents are more inclined to opt for paying for green housing. This also encourages the government to promote green housing initiatives. When the subsidy coefficient offered by real estate developers increases, their likelihood of choosing to develop green housing grows, but at the same time, residents become less likely to opt for paying for green housing. A higher trust coefficient leads to residents being more likely to choose to purchase green housing, which further drives the government and real estate developers to construct and promote green housing. Finally, the study provides corresponding policy recommendations based on the research findings.

Suggested Citation

  • Li, Qianwen & Qian, Tingyu & Wang, Jiaqi & Long, Ruyin & Chen, Hong & Sun, Chuanwang, 2023. "Social “win-win” promotion of green housing under the four-subject evolutionary game," Energy Economics, Elsevier, vol. 127(PA).
  • Handle: RePEc:eee:eneeco:v:127:y:2023:i:pa:s0140988323006151
    DOI: 10.1016/j.eneco.2023.107117
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988323006151
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.eneco.2023.107117?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. De Silva, Muthu & Wang, Pengji & Kuah, Adrian T.H., 2021. "Why wouldn’t green appeal drive purchase intention? Moderation effects of consumption values in the UK and China," Journal of Business Research, Elsevier, vol. 122(C), pages 713-724.
    2. Geng, Jichao & Long, Ruyin & Chen, Hong & Li, Wenbo, 2017. "Exploring the motivation-behavior gap in urban residents’ green travel behavior: A theoretical and empirical study," Resources, Conservation & Recycling, Elsevier, vol. 125(C), pages 282-292.
    3. Tan, Ruipeng & Pan, Lulu & Xu, Mengmeng & He, Xinju, 2022. "Transportation infrastructure, economic agglomeration and non-linearities of green total factor productivity growth in China: Evidence from partially linear functional coefficient model," Transport Policy, Elsevier, vol. 129(C), pages 1-13.
    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. Liwen Chen & Mengjia Zhang & Shiwen Zhao & Junhai Ma, 2021. "Game Analysis of the Multiagent Evolution of Existing Building Green Retrofitting from the Perspective of Green Credit," Discrete Dynamics in Nature and Society, Hindawi, vol. 2021, pages 1-19, June.
    6. Niamh Murtagh & Aeli Roberts & Richard Hind, 2016. "The relationship between motivations of architectural designers and environmentally sustainable construction design," Construction Management and Economics, Taylor & Francis Journals, vol. 34(1), pages 61-75, January.
    7. Tan, Ruipeng & Xu, Mengmeng & Qiao, Gang & Wu, Huaqing, 2023. "FDI, financial market development and nonlinearities of energy and environmental efficiency in China: Evidence from both parametric and nonparametric models," Energy Economics, Elsevier, vol. 119(C).
    8. Qiu, Yueming & Kahn, Matthew E., 2019. "Impact of voluntary green certification on building energy performance," Energy Economics, Elsevier, vol. 80(C), pages 461-475.
    9. Zhang, Yurong & Wang, Yuanfeng, 2013. "Barriers' and policies' analysis of China's building energy efficiency," Energy Policy, Elsevier, vol. 62(C), pages 768-773.
    10. Ye Gao & Renfu Jia & Yi Yao & Jiahui Xu, 2022. "Evolutionary Game Theory and the Simulation of Green Building Development Based on Dynamic Government Subsidies," Sustainability, MDPI, vol. 14(12), pages 1-18, June.
    11. Zhang, Xiaoling, 2015. "Green real estate development in China: State of art and prospect agenda—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 1-13.
    12. Martina Keitsch & Yong Geng & Huijuan Dong & Bing Xue & Jia Fu, 2012. "An Overview of Chinese Green Building Standards," Sustainable Development, John Wiley & Sons, Ltd., vol. 20(3), pages 211-221, May.
    13. Fan, Meiting & Li, Mengxu & Liu, Jianghua & Shao, Shuai, 2022. "Is high natural resource dependence doomed to low carbon emission efficiency? Evidence from 283 cities in China," Energy Economics, Elsevier, vol. 115(C).
    14. Zhang, Li & Wu, Jing & Liu, Hongyu, 2018. "Policies to enhance the drivers of green housing development in China," Energy Policy, Elsevier, vol. 121(C), pages 225-235.
    15. Olubunmi, Olanipekun Ayokunle & Xia, Paul Bo & Skitmore, Martin, 2016. "Green building incentives: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1611-1621.
    16. Hong, Ying & Hu, Jiangting & Chen, Mengyu & Tang, Shoulian, 2023. "Motives and antecedents affecting green purchase intention: Implications for green economic recovery," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 523-538.
    17. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Quangdung Tran & Sajjad Nazir & Tu-Hieu Nguyen & Ngoc-Khoa Ho & Tuan-Hai Dinh & Viet-Phuong Nguyen & Manh-Hung Nguyen & Quoc-Khanh Phan & The-Son Kieu, 2020. "Empirical Examination of Factors Influencing the Adoption of Green Building Technologies: The Perspective of Construction Developers in Developing Economies," Sustainability, MDPI, vol. 12(19), pages 1-28, September.
    2. 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.
    3. Albert Ping Chuen Chan & Amos Darko & Ernest Effah Ameyaw, 2017. "Strategies for Promoting Green Building Technologies Adoption in the Construction Industry—An International Study," Sustainability, MDPI, vol. 9(6), pages 1-18, June.
    4. Rongrong Liu & Dong Chen & Suchang Yang & Yang Chen, 2021. "Evaluation of Green Development Efficiency of the Major Cities in Gansu Province, China," Sustainability, MDPI, vol. 13(6), pages 1-18, March.
    5. Yajing Zhang & Jingfeng Yuan & Lingzhi Li & Hu Cheng, 2019. "Proposing a Value Field Model for Predicting Homebuyers’ Purchasing Behavior of Green Residential Buildings: A Case Study in China," Sustainability, MDPI, vol. 11(23), pages 1-31, December.
    6. Shiwen Zhao & Liwen Chen, 2021. "Exploring Residents’ Purchase Intention of Green Housings in China: An Extended Perspective of Perceived Value," IJERPH, MDPI, vol. 18(8), pages 1-19, April.
    7. Ke Guo & Yongbo Yuan, 2021. "Geographic Distribution and Influencing Factor Analysis of Green Residential Buildings in China," Sustainability, MDPI, vol. 13(21), pages 1-14, November.
    8. Zezhou Wu & Mingyang Jiang & Yuzhu Cai & Hao Wang & Shenghan Li, 2019. "What Hinders the Development of Green Building? An Investigation of China," IJERPH, MDPI, vol. 16(17), pages 1-18, August.
    9. Wei Wang & Shoujian Zhang & Yikun Su & Xinyang Deng, 2018. "Key Factors to Green Building Technologies Adoption in Developing Countries: The Perspective of Chinese Designers," Sustainability, MDPI, vol. 10(11), pages 1-22, November.
    10. Mustaffa, Nur Kamaliah & Kudus, Sakhiah Abdul, 2022. "Challenges and way forward towards best practices of energy efficient building in Malaysia," Energy, Elsevier, vol. 259(C).
    11. Huang, Haiping & Huang, Baolian & Sun, Aijun, 2023. "How do mineral resources influence eco-sustainability in China? Dynamic role of renewable energy and green finance," Resources Policy, Elsevier, vol. 85(PA).
    12. Gang Wang & Qigan Shao & Changchang Jiang & James J. H. Liou, 2022. "Exploring the Driving Factors Influencing Designers to Implement Green Design Practices Based on the DANP Model," Sustainability, MDPI, vol. 14(11), pages 1-15, May.
    13. Yu Cao & Cong Xu & Syahrul Nizam Kamaruzzaman & Nur Mardhiyah Aziz, 2022. "A Systematic Review of Green Building Development in China: Advantages, Challenges and Future Directions," Sustainability, MDPI, vol. 14(19), pages 1-29, September.
    14. Linyan Chen & Xin Gao & Shitao Gong & Zhou Li, 2020. "Regionalization of Green Building Development in China: A Comprehensive Evaluation Model Based on the Catastrophe Progression Method," Sustainability, MDPI, vol. 12(15), pages 1-22, July.
    15. Lei, Mingyu & Cai, Wenjia & Liu, Wenling & Wang, Can, 2022. "The heterogeneity in energy consumption patterns and home appliance purchasing preferences across urban households in China," Energy, Elsevier, vol. 253(C).
    16. Li, Mengxu & Liu, Jianghua & Chen, Yang & Yang, Zhijiu, 2023. "Can sustainable development strategy reduce income inequality in resource-based regions? A natural resource dependence perspective," Resources Policy, Elsevier, vol. 81(C).
    17. Fleckinger, Pierre & Glachant, Matthieu & Tamokoué Kamga, Paul-Hervé, 2019. "Energy Performance Certificates and investments in building energy efficiency: A theoretical analysis," Energy Economics, Elsevier, vol. 84(S1).
    18. Shuguang Liu & Jiayi Wang & Yin Long, 2023. "Research into the Spatiotemporal Characteristics and Influencing Factors of Technological Innovation in China’s Natural Gas Industry from the Perspective of Energy Transition," Sustainability, MDPI, vol. 15(9), pages 1-34, April.
    19. Zhao, Xing & Guo, Yifan & Feng, Tianchu, 2023. "Towards green recovery: Natural resources utilization efficiency under the impact of environmental information disclosure," Resources Policy, Elsevier, vol. 83(C).
    20. Huang, Beijia & Mauerhofer, Volker, 2016. "Low carbon technology assessment and planning—Case analysis of building sector in Chongming, Shanghai," Renewable Energy, Elsevier, vol. 86(C), pages 324-331.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:127:y:2023:i:pa:s0140988323006151. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.