Research on Spatial Distribution Characteristics and Influencing Factors of Pension Resources in Shanghai Community-Life Circle
Bibliographic Data
| ID | 22032245 |
|---|---|
| Authors | Xiaoran Huang (0000-0002-8702-2805, North China University of Technology, corresponding author), Pixin Gong (0000-0003-4795-666X, North China University of Technology), Marcus White (0000-0002-2238-9251, Swinburne University of Technology), Bo Zhang (0000-0003-0986-0018, North China University of Technology) |
| Year | 2022 |
| Volume | 11 |
| Issue | 10 |
| Pages | 518 |
| Publication date | 2022-10-16 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | ISPRS International Journal of Geo-Information (JOURNAL) |
| Journal identifiers | ISSN: 2220-9964 • E-ISSN: 2220-9964 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/ijgi11100518 |
| OpenAlex | W4306381984 |
| Language | EN |
| Citations received | 7 |
| References cited | 33 |
With population ageing being a notable demographic phenomenon, aging in place is an efficient model to accommodate the mounting aging needs. Based on the community scale, this study takes the 15-min community-life circle as the basic research unit to investigate the imbalanced distribution of pension resources and its influencing factors in downtown Shanghai. We obtained six types of elderly care facilities data from the Shanghai elderly care service platform and utilized the Gaussian 2-step Floating Catchment Area method to calculate the accessibility of 6-type elderly care facilities. Then, we used the Entropy Weight Method to calculate the comprehensive accessibility of elderly care facilities. The Getis–Ord Gi* method was adopted to analyze the overall distribution, identifying the well-developed and the under-developed areas. To explore the influencing factors of the distribution, this paper obtained multi-source data to construct a total of 17 indicators and established a Random Forest model to identify the feature importance. With the selected eight factors, the Geographically Weighted Regression (GWR) model was applied to study the spatial heterogeneity of influencing factors, and the model showed a good performance with the AdjR2 being 0.8364. The findings of this research reveal the following: (1) The distribution of six types of elderly care facilities is extremely uneven, with obvious spatial aggregation characteristics. Amongst the seven administrative regions, Huangpu District has the best accessibility to pension resources, while the resources in the other six regions are highly inadequate. (2) Essential influencing factors of the comprehensive accessibility of community-based elderly care facilities are accessibility of nursing institutions (positive), hotel density (positive), catering density (negative), education density (positive) and medical density (negative), while “rents”, “plot ratio” and “building density” have little impact on comprehensive accessibility. (3) The results of GWR revealed that the eight indicators are heterogeneous in space, all of which have bidirectional effects on comprehensive accessibility. By investigating the spatial distribution patterns and influencing factors of pension resources in Shanghai, this research could further contribute to establishing a sound community-based elderly care service system that improves older adults’ quality of life and promotes social fairness and justice
Business · Cartography · Downtown · Environmental health · Geography · Pension · Population · Population ageing · Health disparities and outcomes · Mathematics · Medicine · Migration, Aging, and Tourism Studies · Psychology · Urban Transport and Accessibility
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| Unique citing works | 7 |
|---|---|
| Citations per year | 2,33 |
| Citation span | 2023 - 2026 (4) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 7 |