再生(生物学)
城市更新
地理
环境规划
环境资源管理
区域科学
业务
环境科学
生物
细胞生物学
作者
Tiantian Shen,Xinyi Yao,Fenghua Wen
出处
期刊:Land Use Policy
[Elsevier]
日期:2021-09-01
卷期号:108: 105571-105571
被引量:35
标识
DOI:10.1016/j.landusepol.2021.105571
摘要
The regeneration of old residential areas in China is facing a complex trap involving all kinds of stakeholders. On the one hand, ambiguous property rights, huge infrastructure investment arrears, and strict urban planning regulations make it challenging for market forces and social capital to enter the field of regeneration of old residential areas. On the other hand, the lack of an effective urban governance and social mobilization system leads to governance failures in the regeneration process. To break out of the above traps theoretically and practically, we construct an analytical framework called the Urban Regeneration Engine Model, in which the city government and the urban regeneration operator act as dual engines of urban regeneration. This dual engine drives the increase in social capital in the regeneration process and promotes the participation of the government, enterprises, residents, social organizations, and financial institutions. The positive feedback that comes from social capital increase further diversifies the fundraising sources, reduces the governance cost, and promotes the sustainable development of the community. Taking the Jinsong Community, one of the earliest residential communities in Beijing after the reform and opening up, as an example, this paper shows that the Urban Regeneration Engine Model provides a feasible and effective model for the regeneration of old residential areas in China and other developing countries facing similar problems. • We construct an analytical framework called Urban Regeneration Engine Model (UREM). • We provide a perspective on social capital as the driving force of sustainable regeneration for old residential areas. • The city government and the urban regeneration operator act as dual engines in the UREM. • UREM promotes the participation of various social stakeholders by increasing social capital in the community.
科研通智能强力驱动
Strongly Powered by AbleSci AI