Quantifying the benefits of accessibility on property prices is important for supporting infrastructure planning and guiding land use development. However, disparities between its effects on house prices and rents remain largely underexplored, which is essential to investigate the similarities and differences between owners and renters in residential location choices. This study is conducted in Fuzhou, China, with the open data, such as house listing information from Lianjia.com , and points of interest from Amap. This study adopts a supply-side perspective to investigate how sellers and landlords capitalize property characteristics into list prices and rents. Econometric analyses, including spatial lag, spatial error, and quantile spatial regression models, revealed consistent variable influences on both house prices and rents—positively for number of bedrooms and negatively for property age and distance to the central business district. However, distinctions arose for variables like south-facing orientation. Notably, homeowners prioritized neighborhood facilities over proximity. Two-stage quantile spatial regression can estimate varying, heterogeneous relationships across the entire conditional distribution, which confirmed that the preferences are different for submarkets. For example, owners of high-priced houses are more influenced by life and education factors, while those of low-priced ones prioritize work and transport. These insights inform governmental housing market regulation and investment strategies.
Jiang et al. (Tue,) studied this question.