Homebuyers’ heterogeneous preferences for urban green–blue spaces: A spatial multilevel autoregressive analysis

Abstract

Integrated urban blue-green spaces (UBGS) represent a new global strategic initiative in the construction of ecologically multifunctional and socially inclusive cities. A common challenge is to integrate social preferences and values into UBGS planning and management. Using a 3-D spatial multilevel autoregressive model, this study attempts to differentiate and decompose the impacts of four UBGS attributes (including river water quality, detectable black-odorous problem, riparian greening, and provision of recreational facilities) on apartment prices in Guangzhou (China), so as to elicit homebuyers’ preferences and associate their preferences with higher hierarchical level (district) socioeconomic characteristics. Our modelling results reveal that homebuyers are insensitive to a relatively good water quality (Grade IV) of UBGS, but strongly dislike UBGS with black-odorous phenomenon. Both riparian greening and recreational facilities could command premiums, showing homebuyers’ significant preferences. At the aggregated level, district average income level plays a moderating role: homebuyers’ positive preferences (for riparian greening) and negative preference (for black-odorous river) become weakened when district income level increases. And district population density plays an enhancing role: homebuyers’ positive preferences (for riparian greening and recreational facilities) and negative preference (for black-odorous UBGS) become stronger when population density increases. These findings help optimizing UBGS design and establishing UBGS restoration priorities differently in divergent urban contexts, so as to improve environmental welfare and social equity.