Green Building Design and Sustainable Development Optimization Strategy Based on Evolutionary Game Theory Model
This study introduces an evolutionary game model to investigate the strategic interaction among government regulatory agencies, shopping center investors, and tenants in the global energy-saving renovation market. The focus is on three innovative aspects. Firstly, the model reveals that positive tenant behavior can stimulate investors’ participation in energy-saving renovation projects by triggering potential market demand, thereby establishing a dynamic balance between supply and demand. This viewpoint has been previously overlooked in energy renovation research. Secondly, the model demonstrates the dynamic transformation of government regulatory strategies. In the early stages of market development, direct intervention through subsidies and penalties is crucial, and investors’ decisions are constrained by both returns and costs. When returns exceed the cost premium, investors actively participate, and policy incentives lower early cost barriers to promote market expansion. As the market matures, a transition toward policy guidance optimizes sustainable outcomes. Thirdly, extensive numerical simulations have confirmed the existence of multiple stable equilibrium states under different incentive and cost conditions, providing new evidence for the stability and adaptability of the energy-saving renovation market. These findings significantly advance the theoretical understanding of multi-stakeholder interactions in green building transformation and provide practical guidance for developing adaptive and effective policy frameworks.
Authors
- Yi Yang (ORCID: https://orcid.org/0000-0001-5161-991X)
- Yujing Si (ORCID: https://orcid.org/0000-0003-3669-1301)
- Ze Shao
Institutions
- Zhejiang University (CN)
- Taiyuan University of Technology (CN)
Publication Details
- Journal
- Sustainability
- Published
- 2025-03-17
- DOI
- https://doi.org/10.3390/su17062649
- Citations
- 3
- Primary Topic
- Sustainable Building Design and Assessment
- Type
- article
- Field-Weighted Citation Impact
- 3.02