Operational efficiency evaluation of urban and rural residents' basic pension insurance system by utilizing a picture fuzzy TOPSIS method based on the cumulative prospect theory - Xiong, Yifan (Frontiers in Public Health, 2022)
The population ageing is the most serious challenge facing the pension insurance system in China in the next few decades. Compared with the employees of civil servants and enterprises and institutions, urban and rural residents are unstable vulnerable groups with less income. In order to deal with the pension risks caused by the growing population aging, and solve the security problems of urban and rural residents, our government has carried out a series of constructive work in the pension insurance system: in view of the rural and urban residents, new rural social endowment insurance system and the social endowment insurance system for urban residents have been set up and combined into an unified basic old-age insurance system for urban and rural residents in 2014.With the continuous expansion of the scale of income and expenditure of urban and rural living insurance fund and the size of the insured number, it is of great necessity to evaluate the efficiency of this system. The operational efficiency evaluation of urban and rural residents’ basic pension insurance systems is viewed as the multi-attribute group decision-making (MAGDM). In this paper, we propose an approach by combining the traditional TOPSIS with CPT which can be widely used with vague information. Thus, the main contribution of this study is: (1) the TOPSIS method is extended by PFSs with unknown weight information; (2) entropy method to obtain the original weights of attributes; (3) the PF-CPT-TOPSIS method is used to deal with the MAGDM problems under PFSs; (4) a numerical instance for operational efficiency evaluation of urban and rural residents’ basic pension insurance systems is proposed to testify the effectiveness of new method; (5) some comparative studies are provided to give effect to the rationality of PF-CPT-TOPSIS approach.