Influences of the Plot Area and Floor Area Ratio of Residential Quarters on the Housing Vacancy Rate: A Case Study of the Guangzhou Metropolitan Area in China
Autor(en): |
Xiaoli Yue
Yang Wang Hong’ou Zhang |
---|---|
Medium: | Fachartikel |
Sprache(n): | Englisch |
Veröffentlicht in: | Buildings, 31 Juli 2022, n. 8, v. 12 |
Seite(n): | 1197 |
DOI: | 10.3390/buildings12081197 |
Abstrakt: |
Factors affecting the housing vacancy rate (HVR) vary, but few studies have considered the relationships between the HVR and plot area (PA) and floor area ratio (FAR). This study thus considered 212 residential quarters in the Guangzhou metropolitan area as the research object, and we constructed a regression model of the factors impacting housing vacancies. The model includes two explanatory variables, PA and FAR, and the remaining six impact factors as control variables. In this study, the influences of PA and FAR on the HVR was analyzed by combining the traditional ordinary least squares (OLS) and two spatial regression models: the spatial lag model (SLM) and spatial error model (SEM). The results indicate that (1) the HVR in the Guangzhou metropolitan area shows spatial difference characteristics of the low central area and high edge, and there is spatial autocorrelation. (2) The PA of the residential quarters gradually increases from the central to the edge area, but the spatial pattern of FAR is the opposite. (3) The SLM results indicate that the PA and FAR of the residential quarters have significant positive correlations with HVR; that is, the larger the PA and FAR, the larger the HVR of the residential quarters, which is in accordance with the expected direction of the theory; furthermore, basic education convenience, road density, and waterfront accessibility have significant negative effects on HVR. This conclusion provides a reference for government departments to formulate reasonable and effective housing policies aimed at the current housing vacancy problem and should help alleviate urban housing vacancies. |
Copyright: | © 2022 by the authors; licensee MDPI, Basel, Switzerland. |
Lizenz: | Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden. |
Geografische Orte
2.6 MB
- Über diese
Datenseite - Reference-ID
10688533 - Veröffentlicht am:
13.08.2022 - Geändert am:
10.11.2022