System Dynamics Analysis for Policy Change of Beijing Old-Age Service Industry

DOI

10.2991/aebmr.k.200402.043How to use a DOI?

Keywords

old-age service industry, supply and demand imbalance, system dynamics, policy simulation

Abstract

Under the background of the population aging, taking the pension industry in Beijing as the research object, this paper builds the development model of the pension industry in Beijing by using the system dynamics method and makes comparative simulation analysis. The simulation results show that: (1) The development of the pension industry in Beijing mainly depends on the support of government financial. When the government’s financial investment in the pension services reaches 3‰, it can meet the funds needed for the development of the pension service industry. At the same time, private capital investment should be introduced appropriately in order to reduce financial pressure. (2) The government should improve relevant policies. Elderly people should be encouraged to provide for the aged in different place in order to reduce the pension pressure in Beijing. The medical level should be improved in non-Beijing area, etc. (3) The government and the corresponding pension institutions should work together to improve the quality of the service for the aged, improve the utilization rate of the bed and make rational use of the resources for the aged.

Copyright

© 2020, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yanhong Yang
AU  - Haiqing Cao
AU  - Meiqi Feng
AU  - Cuiyou Yao
PY  - 2020
DA  - 2020/04/06
TI  - System Dynamics Analysis for Policy Change of Beijing Old-Age Service Industry
BT  - Proceedings of the 3rd International Conference on Advances in Management Science and Engineering (IC-AMSE 2020)
PB  - Atlantis Press
SP  - 241
EP  - 249
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.200402.043
DO  - 10.2991/aebmr.k.200402.043
ID  - Yang2020
ER  -