Proceedings of the 2020 International Conference on Modern Education Management, Innovation and Entrepreneurship and Social Science (MEMIESS 2020)

Research on the Practice of “Embedded” Intelligent Pension Service -Taking Jinghua Pension Community as an Example

Authors
Qi Zhang
Corresponding Author
Qi Zhang
Available Online 6 February 2021.
DOI
https://doi.org/10.2991/assehr.k.210206.042How to use a DOI?
Keywords
Embedded, wisdom pension, resource embedding, function embedding, embedded communication
Abstract
With the aggravation of the aging population, the pension service has become an issue of great concern to people in society. With the development of science and technology and economy, the smart pension model is becoming more and more mature. Therefore, a new model of “embedded smart pension” has emerged, and some pension communities have begun to try it. However, in the process of deepening the “embedded” smart pension service model in China, there are still some problems, such as the traditional pension concept obstruction, the lack of government impetus, the low quality of embedded social resources, and the insufficient promotion of integrated social forces. This paper discusses the practice of embedded intelligent pension service in Jinghua Pension Community, analyzes the shortcomings of embedded intelligent pension service, and puts forward some feasible suggestions for the future development of embedded intelligent pension service in China.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Cite this article

TY  - CONF
AU  - Qi Zhang
PY  - 2021
DA  - 2021/02/06
TI  - Research on the Practice of “Embedded” Intelligent Pension Service -Taking Jinghua Pension Community as an Example
BT  - Proceedings of the 2020 International Conference on Modern Education Management, Innovation and Entrepreneurship and Social Science (MEMIESS 2020)
PB  - Atlantis Press
SP  - 209
EP  - 214
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.210206.042
DO  - https://doi.org/10.2991/assehr.k.210206.042
ID  - Zhang2021
ER  -