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Can street segments indexed for accessibility form the basis for housing submarket delineation?

Xiao, Yang, Webster, Christopher and Orford, Scott 2016. Can street segments indexed for accessibility form the basis for housing submarket delineation? Housing Studies 31 (7) , pp. 829-851. 10.1080/02673037.2016.1150433
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Abstract

We test an approach to spatial housing sub-market delineation using street segment as the spatial unit and using finely grained measures of accessibility derived from spatial network analysis. The underlying idea is that street segment connectivity captures fine variations in home-buyers’ preferences for the location. The advantage of the approach is that it is spatially fine grained; it uses the street segment, intuitively the most fundamental spatial unit for spatial housing market analysis; it allows the use of statistical tests to optimize within-sub-market similarities, identifying spatial groups of street segments with the most similar accessibility features; it avoids the predefined arbitrary geographic boundaries usually used in spatial sub-market delineation; it increases the variability of accessibility information in sub-market delineation, accessibility being the principal spatial determinant of housing price; and it allows for normalized measures of accessibility at different spatial scales making it appropriate for comparative analysis across cities. Using a case study of Cardiff, UK, we compare the results with a market segmentation scheme based on prior-knowledge, notably one relying on building type classification. We conclude that street layout can be used to efficiently delineate housing submarkets, and that the estimation is very close to the scheme requiring prior-knowledge. It has advantages, however that make it worthy of further investigation, namely its adaptability, scale-specificity and lower reliance on local knowledge of housing market culture and data.

Item Type: Article
Date Type: Published Online
Status: Published
Schools: Geography and Planning
Wales Institute of Social & Economic Research, Data & Methods (WISERD)
Subjects: G Geography. Anthropology. Recreation > GA Mathematical geography. Cartography
H Social Sciences > HA Statistics
Additional Information: Pdf uploaded in accordance with publisher's policy at http://www.sherpa.ac.uk/romeo/issn/0267-3037/ (accessed 29/03/2016)
Publisher: Routledge
ISSN: 0267-3037
Last Modified: 04 Jun 2017 15:15
URI: http://orca.cf.ac.uk/id/eprint/88260

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