Data · dataset · 2022
Spatial Pattern and Influencing Factors of Affordable Housing Land Allocation: Based on the Perspective of Spatial Mismatch among Provinces, Cities and Counties(in Chinese)
Listed in DANS Data Station Social Sciences and Humanities
Exploring the spatial pattern of affordable housing land and understanding the allocation logic of multi-level governments can help promote the optimal land allocation and accelerate the equalization of regional basic public services.
Description
Based on the affordable housing land in China Land Market Network, this paper uses the kernel density and geographic detector model to study the spatial pattern of affordable housing land from the perspectives of the province, city and county levels in China and analyze the influencing factors of its spatial mismatch.
The results show that: 1) The allocation pattern of affordable housing land shows strong spatial differentiation at all levels, and the dense distribution and scattered distribution are obvious. 2) There are spatial mismatches in the affordable housing land among all levels. Excessive and shortage mismatches coexist, and are closely related to land factors. 3) There are differences in the influencing factors of affordable housing land spatial mismatch.
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Affordable housing land basically follows the allocation logic of reducing costs among provinces. However, among cities and counties, it's affected by land constraints and land cost at the same time, showing a strong logic of task completion and cost reduction. Accordingly, suggestions are given: It should reasonably evaluate the demand for affordable housing and accurately allocate land resource, the supervision and assessment system of local governments needs to be optimized to prevent the strategic behavior.
Links
Where it is published
- Dataverse dataset page ssh.datastations.nl/dataset.xhtml?persistentId=doi%3A10.17026%2FDANS-ZY7-2P8X ↗
landing page · from ssh datastations nl
- DOI doi.org/10.17026/dans-zy7-2p8x ↗
DOI / persistent id · from ssh datastations nl
Catalogue records · 1
- Dataverse API ssh.datastations.nl/api/datasets/:persistentId/?persistentId=doi%3A10.17026%2FDANS… ↗
metadata API · from ssh datastations nl
Topics
- Stated by source
- Arts and Humanities
- From keywords
- Humanities · Social Science
- Inferred from text
- Human geography 72%
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DANS Data Station Social Sciences and Humanities | doi:10.17026/DANS-ZY7-2P8X | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:4406 | enrichment · ssh datastations nl | taxonomy-embedding@1.0.0 | title+keywords+description (72%) |
| concepts[field].dataverse_subject:arts-and-humanities | source · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | /subjects |
| concepts[field].local:field:humanities | mapping · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | /subjects |
| concepts[field].local:field:social-science | mapping · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | /subjects |
| created_date | source · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | |
| description | source · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | /description |
| publication_date | source · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | |
| title | source · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | /name |
| updated_date | source · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 | |
| version_label | source · ssh datastations nl | connector:ssh_datastations_nl@1.0.0 |