A Framework for Analyzing Physical Form Outcomes of Value Capture Paths of Regeneration Projects in Residential Historic Areas


  • Zhiyu PANG Southeast University


value capture, physical form, residential historic area, regeneration project, analytical framework




As “progressive and small scale” has become the mainstream regeneration method for residential historic areas in China, the physical form of these areas is directly affected by the uncertainties in the implementation process of the regeneration projects under the control of planning (Ministry of Housing and Urban-Rural Development, 2021). The implementation of regeneration projects needs to be realized through specific paths of value capture, including the four paths of increasing intensity, changing use, improving quality, and changing property rights (ZHAO et al., 2021).

However, existing literatures have not been able to explain the mechanism of value capture on physical form, in other words, they can only explain whether the project is realized, but not the how the physical form is changed. Although there have been studies that have attempted to bridge the knowledge gap between the two fields of study, such efforts have remained limited to the district/street scale and above (Tennekes et al., 2015), and there is still a lack of attention to the plot/building scale (PANG et al., 2023).

This study intends to build a framework to analyze how the value capture path of residential historic area regeneration projects affects the physical form outcomes. The independent variables of the framework include four parameters: adjusting property rights, changing use, increasing intensity, and improving quality, and the dependent variables of the framework include five parameters: plot form (Bobkova et al., 2021), building type, number of building floors, building density, and setback distance, and the interpretive capability of the framework is verified with the example of the XIAOXIHU historic area in Nanjing, China.

The findings suggest that even the same planning control conditions can produce different physical spatial form outcomes, which can be explained largely by value capture paths. The analytical framework shows promise for probabilistic prediction of spatial form outcomes through a combination of current spatial conditions, planning control requirements, and value capture paths.