Academic Journal of Humanities & Social Sciences, 2026, 9(3); doi: 10.25236/AJHSS.2026.090304.
Lingjie Deng1
1School of Economics and Management, South China Agricultural University, Guangzhou, Guangdong, China
Against the backdrop of an aging population and the national strategy of active aging, volunteer services for the elderly are becoming increasingly important, making the exploration of influencing factors increasingly important. This study takes Guangzhou, a pioneering city in mutual-aid elderly care, as an example, examining key factors influencing the continued participation of older adults in volunteer services from the perspectives of organizers and elderly volunteers. The study employed partial least squares structural equation modeling (PLS-SEM) for data analysis and conducted reliability and validity analyses. The results show that institutional capacity, participation experience, and external motivation all have significant positive impacts on volunteer service participation, with institutional capacity having the most significant effect. In contrast, self-identity did not significantly predict volunteer service participation. Therefore, volunteer organizations should focus on improving their organizational operational capabilities, optimizing service content, enhancing the participation experience of elderly volunteers, and strengthening external incentives to promote elderly volunteer service participation.
Volunteer service; Elderly volunteers; Influencing factors; Community
Lingjie Deng. A Study on the Current Status and Influencing Factors of Volunteer Service Participation among the Elderly in China: An Analysis Based on the Mutual Assistance Elderly Care Model in Guangzhou. Academic Journal of Humanities & Social Sciences (2026), Vol. 9, Issue 3: 25-31. https://doi.org/10.25236/AJHSS.2026.090304.
[1] Bodoff, D., & Ho, S. Y. (2016). Partial least squares structural equation modeling approach for analyzing a model with a binary indicator as an endogenous variable. Communications of the Association for Information Systems, 38(1), 23.
[2] Buffel, T., De Donder, L., Phillipson, C., Dury, S., De Witte, N., & Verté, D. (2014). Social participation among older adults living in medium-sized cities in Belgium: the role of neighbourhood perceptions. Health promotion international, 29(4), 655-668.
[3] Cao, Y., Wang, J. (2015). The Influence of Participation in Public Welfare Activities on the Life Satisfaction of Retired Elderly-Based on the Survey in Xicheng District of Beijing. Population and Development, 21(04), 103-112.
[4] Du, P., Xie, L., Li, Y. (2015). How to Expand the Elderly Volunteer Service?-An Empirical Study Based on Chaowai Street in Beijing. Population and Development, 21(01), 89-95.
[5] Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European business review, 31(1), 2-24.
[6] Kisvetrová, H., Mandysová, P., Tomanová, J., & Steven, A. (2022). Dignity and attitudes to aging: A cross-sectional study of older adults. Nursing ethics, 29(2), 413-424.
[7] Le, G. H., & Aartsen, M. (2024). Understanding volunteering intensity in older volunteers. Ageing and Society, 44(8), 1898–1916. doi:10.1017/S0144686X22001106
[8] Li, Y. (2019). Analysis of the Characteristics and Influencing Factors of Elderly Volunteer Service Participation in China. Inner Mongolia Social Sciences, 40(04), 164-171.
[9] Li, Z., Li, W., Gao, G. (2011). Analysis of the Influencing Factors of Urban Elderly Community Participation. Shandong Social Sciences, (03), 112-117.
[10] Liu, Y., Xia, J., Li, G. (2017). The Agglomeration of Productive Service Industry and the Upgrading of Manufacturing Industry. China Industrial Economics, (07), 24-42.
[11] Sarstedt, M., Hair, J. F., Pick, M., Liengaard, B. D., Radomir, L., & Ringle, C. M. (2022). Progress in partial least squares structural equation modeling use in marketing research in the last decade. Psychology & Marketing, 39(5), 1035-1064.
[12] Xie, L. (2017). Research on the Current Status and Influencing Factors of Volunteer Service Participation in Urban Elderly Communities in China. Population and Development, 23(01), 55-65+73.
[13] Xie, L., & Chen, M. (2020). Influencing Factors of Urban Elderly's Participation in Community Governance from the Perspective of Individual-environment Match-Based on the Survey in Beijing. Population Research, 44(03), 71-84.