Flexible spatial multilevel modelling of neighbourhood satisfaction in Beijing

This paper develops an innovative and flexible Bayesian spatial multilevel model to examine the socio-spatial variations in perceived neighbourhood satisfaction, using a large-scale household satisfaction survey in Beijing. In particular, we investigate the impact of a variety of housing tenure types on neighbourhood satisfaction, while controlling for household and individual socio-demographic attributes and geographical contextual effects. The proposed methodology offers a flexible framework for modelling spatially clustered survey data widely used in social science research by explicitly accounting for spatial dependence and heterogeneity effects. The results show that neighbourhood satisfaction is influenced by individual, locational and contextual factors. Homeowners, except those of resettlement housing, tend to be more satisfied with their neighbourhood environment than renters. Moreover, the impacts of housing tenure types on satisfaction vary significantly in different neighbourhood contexts and spatial locations.