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The role of subjective perceptions and objective measurements of the urban environment in explaining house prices in Greater London: A multi-scale urban morphology analysis using space syntax

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2022_Sijie_Wang
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Attribution: The role of subjective perceptions and objective measurements of the urban environment in explaining house prices in Greater London: A multi-scale urban morphology analysis using space syntax is licensed under CC BY-SA 4.0
    2022_Sijie_Wang
    2022_Sijie_Wang
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    The role of subjective perceptions and objective measurements of the urban environment in explaining house prices in Greater London: A multi-scale urban morphology analysis using space syntax

    House prices have long been considered to be closely related to the built environment of cities. The hedonic house price model is a well-known theoretical model that encompasses four dimensions: house structure attributes, location attributes, neighbourhood attributes and environmental attributes. In recent years, some scholars have used the urban morphology research tool space syntax instead of location attributes to study the built environment's impact on house prices at multiple scales. At the same time, subjective perception analysis of cities using street view images as a database has become a popular research trend in recent years and is considered to impact house prices. This study investigates the impact of subjective urban perceptions on house prices in combination with other objective urban elements at multiple scales of urban morphology. In particular, subjective urban perceptions were assessed through street images, where a perception survey based on 300 street images was conducted among the population, and the results were subsequently used to build a machine learning model to predict street perception scores for areas around house price points across Greater London. The integration and choice values analyse the multi-scale urban morphology in the space syntax, combined with a number of other functional variables, to create the hedonic house price model, which is then placed in the OLS regression model for analysis. The final results indicate that the impact of subjective perception on house prices is second only to location attributes and higher than neighbourhood attributes and house structure attributes. There is considerable differentiation in the impact at multiple scales of urban morphology. In the global analysis, subjective perceptions have a greater impact in the micro-scale urban morphology, which is higher than the location attributes, and a more negligible impact in the macro-scale urban morphology, which is lower than the location attributes, with 'enclosure' and 'sense of comfort' being more important than the other perception variables in influencing house prices. In the analysis of the four local areas, the study reveals that local urban form has a greater impact on house prices in the urban centres than in the city's peripheral areas, while the opposite trend is observed for the subjective perception variables.

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