Applying Big Data Analysis to Discuss the Elderly Social Welfare Service Use Condition and the Relevant Factors Cover Image

Applying Big Data Analysis to Discuss the Elderly Social Welfare Service Use Condition and the Relevant Factors
Applying Big Data Analysis to Discuss the Elderly Social Welfare Service Use Condition and the Relevant Factors

Author(s): Zhi-Ping HOU, Zhi-Fei CHEN, Yu-Zhou LUO
Subject(s): Social Sciences, Sociology, Welfare services
Published by: Expert Projects Publishing
Keywords: big data analysis; the elderly; social welfare; service condition; social services;

Summary/Abstract: The advance of medical technology and the change in living environment gradually prolong the life expectancy of humans to constantly increase the elderly population in the world. Relevant demands and problems derived from aging are therefore getting emphasized. To cope with the elderly needs, the government sequentially promotes welfare service. Nevertheless, it is still discovered that the welfare service use rate of the elderly is rather low, not achieving the estimated demand. Aiming at the elderly in Guilin, the data in this study are collected and analyzed from social welfare related open information platforms and the analyses and research, publications, or database of government agencies. The relevant data are integrated, analyzed, discussed, and applied to understand the effects of indicators and further activate the utilization of data. The research results show remarkable correlations between redisposing factors and service use condition, enabling factors and service use condition, and demand factors and service use condition. According to the results, suggestions are proposed, expecting to comprehensively understand the elderly social welfare service use conditions and identify the factors in the elderly service use so as to examine the match of the elderly welfare service with the elderly needs to develop the maximal function of social welfare service.

  • Issue Year: 2020
  • Issue No: 68
  • Page Range: 53-63
  • Page Count: 11
  • Language: English