Supply-demand matching study of the intelligent old-age care services based on the multi-source data
A modular bilateral matching decision method based on multi-source data was proposed to address the problems of uncertainty,fuzziness,and mismatch between the supply and demand in the evaluation of intelligent old-age care services.This method does not require the uniformity of information,which can reduce the loss of information processing.Considering the demand differences among the elderly population,a two-step clustering method was used to classify them.For the heterogeneous evaluation attributes of the intelligent old-age care services,the probability language terms and intuitionistic fuzzy numbers were used to conduct the qualitative evaluation information,while the precise numbers were used to conduct the quantitative evaluation information.The attribute weights were calculated by improving the maximum deviation method.The compromise solution using measurement alternatives and ranking was employed to achieve the bilateral utility satisfaction,and a bilateral matching model was constructed.Finally,the feasibility and rationality of the method were verified through the simulation experiment on the supply and demand matching of intelligent old-age care for the elderly population in Shanghai.The results showed that the proposed method could identify five categories of elderly groups,and it could match different intelligent old-age care services for elderly populations with different characteristics.
NETL
NSTL
万方数据
维普
