Matches in SemOpenAlex for { <https://semopenalex.org/work/W4313478272> ?p ?o ?g. }
- W4313478272 endingPage "100723" @default.
- W4313478272 startingPage "100723" @default.
- W4313478272 abstract "For buyers, investors and urban policy, understanding drivers of community-level house prices across space and across time, are important for urban management and economic planning. In this study, we interrogated two housing market datasets, one from 2015, the other from 2019, for Wuhan, China, in order to uncover diversities and similarities in the spatial relationships between house price and contextual data; and in the context of increasingly volatile markets. A non-stationary approach was adopted with basic geographically weighted regression (GWR) and multiscale GWR (MGWR), where only the latter enables relationships to vary at their own spatial scale. In terms of model fit, both MGWR (adj. R2: 0.94 and 0.97, for 2015 and 2019, respectively) and GWR (adj. R2: 0.87 and 0.81) represented an improvement over the usual linear regression (adj. R2: 0.11 and 0.09) and the spatial lag mode (adj. R2: 0.21 and 0.27). Similarly marked improvements for GWR and for MGWR were found using corrected Akaike Information Criterion (AICc) based fit diagnostics. However, of more importance and via MGWR, the spatially varying drivers of house price were found to operate at a range of spatial scales, that in turn changed in strength and significance between the two study years. Such insights allow for spatially- and temporally-aware decision- and policy-making for housing price control and urban planning, given China’s housing markets can be increasing prone to strong growth coupled with severe depressions." @default.
- W4313478272 created "2023-01-06" @default.
- W4313478272 creator A5016701351 @default.
- W4313478272 creator A5023127879 @default.
- W4313478272 creator A5024399084 @default.
- W4313478272 creator A5027113543 @default.
- W4313478272 creator A5055094180 @default.
- W4313478272 date "2023-03-01" @default.
- W4313478272 modified "2023-09-30" @default.
- W4313478272 title "Uncovering drivers of community-level house price dynamics through multiscale geographically weighted regression: A case study of Wuhan, China" @default.
- W4313478272 cites W1980398988 @default.
- W4313478272 cites W1984535158 @default.
- W4313478272 cites W1987247048 @default.
- W4313478272 cites W2021325233 @default.
- W4313478272 cites W2025797685 @default.
- W4313478272 cites W2030068896 @default.
- W4313478272 cites W2035395222 @default.
- W4313478272 cites W2047120335 @default.
- W4313478272 cites W2049221328 @default.
- W4313478272 cites W2053506197 @default.
- W4313478272 cites W2059757885 @default.
- W4313478272 cites W2063143131 @default.
- W4313478272 cites W2071038954 @default.
- W4313478272 cites W2083336903 @default.
- W4313478272 cites W2085994609 @default.
- W4313478272 cites W2089543568 @default.
- W4313478272 cites W2090685952 @default.
- W4313478272 cites W2101677938 @default.
- W4313478272 cites W2102763668 @default.
- W4313478272 cites W2115512906 @default.
- W4313478272 cites W2117292285 @default.
- W4313478272 cites W2117920735 @default.
- W4313478272 cites W2120515048 @default.
- W4313478272 cites W2124452065 @default.
- W4313478272 cites W2136211475 @default.
- W4313478272 cites W2147279463 @default.
- W4313478272 cites W2156127902 @default.
- W4313478272 cites W2156378058 @default.
- W4313478272 cites W2157520488 @default.
- W4313478272 cites W2261195128 @default.
- W4313478272 cites W2332041801 @default.
- W4313478272 cites W2559688945 @default.
- W4313478272 cites W2563925603 @default.
- W4313478272 cites W2591878014 @default.
- W4313478272 cites W2599875474 @default.
- W4313478272 cites W2605147858 @default.
- W4313478272 cites W2618940483 @default.
- W4313478272 cites W2796128890 @default.
- W4313478272 cites W2803271468 @default.
- W4313478272 cites W2877017441 @default.
- W4313478272 cites W2902003317 @default.
- W4313478272 cites W2904737368 @default.
- W4313478272 cites W2917454241 @default.
- W4313478272 cites W2921548915 @default.
- W4313478272 cites W3045435521 @default.
- W4313478272 cites W3096441729 @default.
- W4313478272 cites W3111581215 @default.
- W4313478272 cites W3111825624 @default.
- W4313478272 cites W3119224280 @default.
- W4313478272 cites W3126064935 @default.
- W4313478272 cites W3163541942 @default.
- W4313478272 cites W3184045607 @default.
- W4313478272 doi "https://doi.org/10.1016/j.spasta.2022.100723" @default.
- W4313478272 hasPublicationYear "2023" @default.
- W4313478272 type Work @default.
- W4313478272 citedByCount "0" @default.
- W4313478272 crossrefType "journal-article" @default.
- W4313478272 hasAuthorship W4313478272A5016701351 @default.
- W4313478272 hasAuthorship W4313478272A5023127879 @default.
- W4313478272 hasAuthorship W4313478272A5024399084 @default.
- W4313478272 hasAuthorship W4313478272A5027113543 @default.
- W4313478272 hasAuthorship W4313478272A5055094180 @default.
- W4313478272 hasBestOaLocation W43134782721 @default.
- W4313478272 hasConcept C10138342 @default.
- W4313478272 hasConcept C105795698 @default.
- W4313478272 hasConcept C126674687 @default.
- W4313478272 hasConcept C127413603 @default.
- W4313478272 hasConcept C146978453 @default.
- W4313478272 hasConcept C149782125 @default.
- W4313478272 hasConcept C158709400 @default.
- W4313478272 hasConcept C162324750 @default.
- W4313478272 hasConcept C166957645 @default.
- W4313478272 hasConcept C182306322 @default.
- W4313478272 hasConcept C18903297 @default.
- W4313478272 hasConcept C191935318 @default.
- W4313478272 hasConcept C204323151 @default.
- W4313478272 hasConcept C205649164 @default.
- W4313478272 hasConcept C2779343474 @default.
- W4313478272 hasConcept C2910321205 @default.
- W4313478272 hasConcept C2992949716 @default.
- W4313478272 hasConcept C31258907 @default.
- W4313478272 hasConcept C33923547 @default.
- W4313478272 hasConcept C41008148 @default.
- W4313478272 hasConcept C48921125 @default.
- W4313478272 hasConcept C75778745 @default.
- W4313478272 hasConcept C86803240 @default.
- W4313478272 hasConceptScore W4313478272C10138342 @default.
- W4313478272 hasConceptScore W4313478272C105795698 @default.