Research on the Influence of National Education on the Development of Pension Industry Based on Binary Logistic Regression Model
- DOI
- 10.2991/978-94-6463-040-4_111How to use a DOI?
- Keywords
- National condition education; Pension industry; Sustainable development
- Abstract
Population aging is a basic national condition that runs through the 21st century in China. Actively dealing with population aging is a long-term strategic task of the country. Through a questionnaire survey, statistical analysis and other methods, this paper discusses the public's understanding of China's aging and national education, and divides national education into three small parts to explore its impact on the sustainable development of the elderly care industry, thus putting forward three hypotheses. The results show that the hypotheses are valid, so national education has a positive impact on the sustainable development of the pension industry. Therefore, we should expand the publicity channels of national education to increase the popularity of national education on aging, and put forward some suggestions for promoting the sustainable development of China's pension industry.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Shu Yu AU - Xiaomeng Qu PY - 2022 DA - 2022/12/27 TI - Research on the Influence of National Education on the Development of Pension Industry Based on Binary Logistic Regression Model BT - Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022) PB - Atlantis Press SP - 730 EP - 736 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-040-4_111 DO - 10.2991/978-94-6463-040-4_111 ID - Yu2022 ER -