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Background <p>China’s elderly care service industry (ECSI) plays a critical role in addressing the needs of an aging population. However, the industry faces both resource shortages and waste, particularly of fixed assets, while capacity utilization (CU), which reflects fixed asset efficiency, has received limited attention.</p> Methods <p>This study develops a CU measurement model based on the data envelopment analysis framework to evaluate the CU of ECSI across 30 provinces in China from 2010 to 2022. In addition, the Dagum Gini ratio and Moran’s I are employed to analyze the spatial disparities and correlations.</p> Findings <p>The CU of China’s ECSI showed a downward trend with fluctuations, declining from 0.7426 in 2010 to 0.5889 in 2022. Central China generally exhibit higher CU than eastern and western China. Western China had the lowest CU and the most pronounced fluctuations. The Dagum Gini ratio indicated that the difference between subregions was the primary driver of the total difference (43%), followed by the difference within subregions (28%). Moran’s I analysis showed that CU in China’s ECSI exhibited increasing spatial agglomeration, with weak but significant spatial correlation. Economically developed provinces, such as Jiangsu, Zhejiang, and Hubei, formed High-High clusters. In contrast, underdeveloped western provinces, including Gansu and Xinjiang, formed Low-Low clusters.</p> Conclusions <p>China’s ECSI faces declining CU and pronounced regional imbalances. The increasing spatial agglomeration and distinct clustering patterns highlight the need for targeted policies to reduce regional disparities and improve resource allocation.</p>

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Capacity utilization of China’s elderly care service industry during 2010–2022

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月28日

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  • Xiuquan Huang,
  • Tao Zhang,
  • Xi Wang,
  • Hanxiang Gong,
  • Wenshuo Zhang

摘要

Background

China’s elderly care service industry (ECSI) plays a critical role in addressing the needs of an aging population. However, the industry faces both resource shortages and waste, particularly of fixed assets, while capacity utilization (CU), which reflects fixed asset efficiency, has received limited attention.

Methods

This study develops a CU measurement model based on the data envelopment analysis framework to evaluate the CU of ECSI across 30 provinces in China from 2010 to 2022. In addition, the Dagum Gini ratio and Moran’s I are employed to analyze the spatial disparities and correlations.

Findings

The CU of China’s ECSI showed a downward trend with fluctuations, declining from 0.7426 in 2010 to 0.5889 in 2022. Central China generally exhibit higher CU than eastern and western China. Western China had the lowest CU and the most pronounced fluctuations. The Dagum Gini ratio indicated that the difference between subregions was the primary driver of the total difference (43%), followed by the difference within subregions (28%). Moran’s I analysis showed that CU in China’s ECSI exhibited increasing spatial agglomeration, with weak but significant spatial correlation. Economically developed provinces, such as Jiangsu, Zhejiang, and Hubei, formed High-High clusters. In contrast, underdeveloped western provinces, including Gansu and Xinjiang, formed Low-Low clusters.

Conclusions

China’s ECSI faces declining CU and pronounced regional imbalances. The increasing spatial agglomeration and distinct clustering patterns highlight the need for targeted policies to reduce regional disparities and improve resource allocation.