Against the backdrop of increasingly severe population aging, which presents profound challenges to socioeconomic systems globally, the issue of uneven distribution of elderly care service resources has become critically prominent, particularly in rapidly urbanizing contexts. Conducting an indepth, multidimensional investigation into the configuration rationality of elderly care facilities and the spatial equity of their layout is therefore of paramount importance for effectively safeguarding the fundamental needs of the growing elderly demographic and actively promoting the equitable allocation of finite social public resources.This research is grounded in a comprehensive analysis of 2,057 institutional and community-based home care facilities located within Suzhou, establishing equity and efficiency as the foundational dual pillars of its analytical framework. The investigation leverages the advanced computational and spatial visualization capabilities of Geographic Information Systems (GIS) to conduct a systematic quantification and sophisticated graphical representation of equity manifested in the geographical distribution of these facilities. To ensure a multi-faceted assessment, the evaluation is strategically organized around three pivotal dimensions: the quantitative and qualitative availability of service resources, the geographical accessibility for the elderly population, and the spatial efficiency of service coverage. Methodologically, the research integrates established spatial statistical tools, including the Gini coefficient, a classical measure of inequality, and the more granular Two-Step Floating Catchment Area (2SFCA) method, which calculates service provider-to-population ratios within defined service areas.To further identify the key factors influencing the equity of elderly care facility layout, a structured analytical framework comprising 14 carefully selected indicators was constructed. This framework incorporated both socioeconomic data (such as per capita GDP, average housing prices, and per capita disposable income) and built-environment data (including land use mix, density of medical facilities, and spatial centrality of commercial areas). Subsequently, analytical tools including the Geodetector and the Geographically Weighted Regression (GWR) model were applied to investigate the causes of spatial differentiation in the equity of elderly care facility distribution. The Geodetector was employed to assess the explanatory power of various influencing factors on the spatial variation of layout equity, while the GWR model, which accounts for spatial heterogeneity, facilitated the analysis of how the effects of these factors vary across different geographical regions. The study results reveal three principal findings. First, the overall Gini coefficient of 0.369 7 for the distribution of elderly care facility resources relative to the elderly population in Suzhou indicates a relatively equitable allocation, although significant disparities persist in certain areas. Accessibility to facilities remains comparatively poor in northern river-adjacent regions and southern Wujiang District. While facility coverage in Suzhou’s urban core is generally high, severe service area overlaps are observed in several sub-districts, reflecting inefficient resource distribution. Second, per capita GDP demonstrates a positive correlation with all three evaluated dimensions: service resources, accessibility, and coverage. Conversely, population density exerts a negative influence on the equity of service resource distribution and accessibility. Third,Geographically Weighted Regression (GWR) results confirm that six indicators—per capita GDP, population density, road network density, medical facility density, bus stop density, and land use mix—exhibit spatial heterogeneity in their effects on layout equity. These factors demonstrate bidirectional influences on comprehensive equity, with varying impacts across different geographical contexts. The findings generated by this study possess significant practical applicability as well as substantive theoretical value. From a practical standpoint, the results offer scientifically rigorous references and evidence-based guidance for optimizing the spatial arrangement of elderly care facilities and for informing the development of future-oriented elderly care planning strategies in Suzhou. By identifying specific gaps and inefficiencies in resource distribution, the research empowers decision-makers to implement targeted interventions, thereby enhancing the overall fairness, equity, and operational efficiency of the city’s elderly care service system. On a theoretical level, the well-defined research framework and the comprehensive analytical methodology employed—which systematically integrates GIS technology with a suite of advanced quantitative tools, including the Gini coefficient, the Two-Step Floating Catchment Area (2SFCA) method, the Geodetector, and the Geographically Weighted Regression (GWR) model—provide innovative perspectives and robust methodological benchmarks for conducting equity analyses of other geographical phenomena and spatial distributions. This approach offers fresh conceptual ideas and applicable procedural models for investigating the fairness inherent in the allocation of various public facilities, such as schools, hospitals, and other essential services, thereby significantly enriching the application scope and analytical power of spatial analysis methodologies within the broader field of public service resource allocation research.