ارزش اقتصادی خیابان ها: تعامل مکانی فضایی و عملکرد و الگوهای قیمت مسکن

Location factors are vital elements for describing housing price variation. However, limited studies have explicitly illustrated the relationship between urban design and the heterogeneity of housing price patterns. This article specifically evaluates how the interactions between the spatial layouts and land-use system at various scales through street network affect the valuation of the residential properties and the segmentation of housing markets in a network-based Mixed-scale Hedonic Model (MHM) where the submarkets pattern are determined and annotated by the spatially varying estimates on streets. The application of the delivered method in the case of Shanghai City, China, confirms the necessity of using the non-Euclidean distance metric and represent the coexistence between the stationarity and the non-stationarity of the introduced street accessibility variables. The results provide evidence that the impacts of street accessibility measures on the local levels showcase significant spatial variation. It is common for all the places that the properties located on the streets with the higher levels of angular closeness, smaller values of angular betweenness and longer angular distance to the nearby land-uses at the larger scales will be bided higher. It is proven that our delineation of submarket performs better in prediction accuracy than the traditional submarket specifications. The detected submarkets pattern yields that reachable land-use diversity at the pedestrian level is not a preferred factor in the housing submarkets located in the developed city centres. The signs of the price effects of the angular distance to local land-uses distinguish the developing submarkets as two main groups with different degrees of geometrical walkability. It is suggestive that continuously developing pedestrian-oriented neighbours in the walkable areas could contribute to decelerating the growth of house price in Chinese cities. The productions of this study can enrich the understanding of the socioeconomic effects of urban design with greater spatial precision across submarkets.