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To improve the effectiveness of urban planning, the effect of rail-transit construction on the value of residential projects along rail-transit lines should be assessed. In studies to date, the focus has been on the effects of various urban development elements on housing prices in rail transit station areas; however, there are few studies of the premium effects and value-capture mechanisms in rail transit station areas. In this study, the average price of a residence in existing residential neighborhoods in Hefei, using data published on the Anjuke website in December 2018, was used in an assessment of the value added of the Hefei Metro Line 1. The data included the name of the community, average price per unit area, location, housing age, floor area ratio, and greenery rate. Baidu POI data from December 2018 were used to determine bus routes and various public service facilities in the district. First, we constructed a housing price fitting model in the station area and analyzed the spatial value-added pattern of housing and the premium effectiveness of each fitting index. From this analysis we extracted the premium characteristics of housing projects in the station area and then determined the value capture mechanism and proposed optimization strategies. The results indicate the following: (1) The impact of Hefei Metro Line 1 on housing prices along the line is significant and decays with increasing distance from the rail transit station. (2) Different index elements have different effects on station-area residential premiums. The location and transportation level indicators contribute the most to the premium, followed by the neighborhood and environment level indicators. In contrast, the building form level indicators contribute the least to housing prices in this model. Specifically, the distance between the residential community and the rail station, as well as the distance between the residential community and the CBD, produce a significant negative price premium that decays with distance. Other indicators―housing age and presence of amenities such as hospitals, shopping malls, and museums―also have significant negative linear premium effect. The number of bus lines, as well as the greenery rate and presence of parks had significant positive linear premium effects. (3) Based on the model score results, quadratic groups were constructed to evaluate the station area, and the premium rule and geographical effect of the station area was established. The systematic connection between the premium effect and the value capture of the rail transit station area can be identified, the distribution characteristics of the housing price of the station area can be accurately identified, and the current differences in the degree of residential premium in the station area can be indicated. Furthermore, based on the case of the Hefei metro area, the interaction between rail transit financing and value capture was analyzed for its applicability to China's public ownership land system. Accordingly, a land use strategy with institutional feasibility is proposed, and different models and implementation mechanisms of premium allocation are suggested, which are of great importance in terms of promoting the return of rail transit premiums to the public, the sharing of land benefits among urban residents, and, ultimately, sustainable social and economic development. |
