Open AccessOptimization of Bed Demand for Elderly Care Services Based on Leslie Matrix
Author(s) -
Jun Yu,
Jing Yang
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2224/1/012121
Subject(s) - pension , service (business) , investment (military) , analytic hierarchy process , scale (ratio) , population ageing , population , process (computing) , leslie matrix , tertiary sector of the economy , rural area , business , supply and demand , rate of return , actuarial science , operations research , economics , computer science , geography , medicine , finance , microeconomics , marketing , engineering , environmental health , cartography , pathology , politics , political science , law , operating system
With the deepening of the aging process and the weakening of the family’s ability to care for the aged, urban residents will have an increasing demand for elderly care service institutions in the future. Therefore, it is necessary to optimize the prediction of the demand for elderly service beds. In the paper, an optimization method of Leslie matrix is proposed to predict the future trend of the total population and aging by comprehensively considering factors such as birth rate and mortality rate, and analyze and predict the demand scale of elderly service beds according to the distribution of urban and rural areas and economic divisions. Based on the AHP model, the business opportunities for elderly service beds will be transformed into a quantitative evaluation model to analyzing the return rate of pension service investment in different regions. The simulation experiment shows that increasing the total number of elderly care institutions and improving them can effectively solve the insufficient number of elderly service beds.