Research on the supply and demand of elderly care service resources in China

This study aims to assess the current status and spatial distribution differences of elderly care service resources supply and demand in China.

Semi-structured qualitative interviews were utilized to gather participants' insights into the current demands for elderly care services, the status of resource allocation, and related indicators. The entropy weight method was employed to determine indicator weights, yielding objective demand and allocation indices for elderly care service resources. Kernel density estimation was used to illustrate the distribution characteristics of the demand and allocation indices. The coupling coordination degree model was applied to measure the coupling coordination level of China's elderly care service resource supply and demand system in 2020.

The demand index ranks highest in Beijing (0.3291), Shanghai (0.2941), and Tianjin (0.2563), while the lowest are found in Tibet (0.1673), Guangxi (0.1727), and Guizhou (0.1737). Kernel density estimation shows that the demand index is concentrated in the range of 0.1800 to 0.2000. The top three regions for allocation index are Shanghai (184.0007), Qinghai (129.8177), and Beijing (109.5941), with the lowest in Liaoning (34.8558), Hainan (35.3168), and Yunnan (36.6366). Kernel density estimation indicates that the allocation index is concentrated in the range of 25-75. Calculations of coupling coordination degree show that Shanghai has high coordination quality (0.9368), Beijing has good coordination (0.8392), while Hainan and Yunnan experience severe imbalances (0.1990, 0.1831).

There is a significant lack of coordination between the demand for elderly care services and the allocation of resources in Hainan and Yunnan provinces in China. Most provinces, with the exception of Beijing and Shanghai, exhibit some degree of misalignment. The Chinese government should address the varying needs of the elderly population in different regions, pay timely attention to regional disparities, enhance regional cooperation, and dynamically allocate elderly care resources in a rational manner.