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Research on the Evaluation Model of the Overall Benefit of the Nonlinear Rural Pension Based on Particle Swarm Optimization Algorithm: From the Perspective of Migrant Workers Returning

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  • Yong Wang
  • Fang Li
  • Jia-Li Dou
  • Naeem Jan

Abstract

In this paper, based on the existing research, the rural talent supply situation is analyzed. Rural talent relative to the existing rural labor force has a higher human capital of the labor force. We also discuss the part of moving workers who can be considered as talents. Financial dimension is mostly through literature collection and statistical data finding and computational calculation, according to the results of communicate indicators, to reflect its performance level. The performance analysis of organizational management dimension and institutional development dimension mainly focuses on qualitative analysis and comparative analysis, and then we summarize and evaluate the performance status of Shanghai basic endowment insurance system for urban and rural residents. Therefore, all countries in the world are constantly exploring and trying to improve the performance management model of their social security institutions. Through the evaluation and analysis of the above four dimensions, it can be found that the overall performance level of urban and rural residential insurance in Shanghai is relatively high, but there are still some problems in the operation process.

Suggested Citation

  • Yong Wang & Fang Li & Jia-Li Dou & Naeem Jan, 2022. "Research on the Evaluation Model of the Overall Benefit of the Nonlinear Rural Pension Based on Particle Swarm Optimization Algorithm: From the Perspective of Migrant Workers Returning," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-8, April.
  • Handle: RePEc:hin:jnlmpe:6554300
    DOI: 10.1155/2022/6554300
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    Cited by:

    1. Liu, Sujiao & Zhu, Mengcheng & Ling, Wenhao, 2023. "Research on the impact of population aging and endowment insurance on household financial asset allocation- Evidence on CFPS data," Finance Research Letters, Elsevier, vol. 54(C).

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