RETRACTED ARTICLE: Optimizing the spatial allocation of pension resources in downtown Shanghai: a dynamically updated...

Area of Science:

• Urban Planning
• Gerontology
• Spatial Analysis

Background:

• Existing research on resource allocation often overlooks community-level assets.
• Literature frequently focuses on street or town levels, neglecting embedded community resources.

Purpose of the Study:

• To investigate the spatial allocation of pension resources across multiple administrative and community levels.
• To identify underserved areas for pension facilities within Shanghai's urban landscape.
• To optimize the placement of pension facilities to meet the needs of the ageing population.

Main Methods:

• Utilized spatial analysis techniques including buffer analysis, grouping analysis, and the genetic algorithm.
• Integrated data across district, street, and housing estate levels, incorporating community-based beds.
• Employed ArcGIS 10.8 for data management and spatial analysis.

Main Results:

• Identified a significant spatial mismatch between pension resources and the ageing population in downtown Shanghai (2020).
• Established a 15-minute community life circle to pinpoint areas lacking adequate pension resource coverage.
• Demonstrated spatial disparities in resource distribution impacting the elderly.

Conclusions:

• A dynamically updated genetic algorithm proved most effective for optimizing pension facility site selection.
• This advanced algorithm achieved full coverage of the 15-minute community life circle with minimal new facility requirements.
• The findings offer crucial insights for Shanghai's urban planning and pension resource distribution strategies.