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Labor Market Resource Allocation Optimization Based on Principal Component Analysis

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  • Xiaojing Liu

Abstract

As an endogenous mechanism affecting social and economic changes, the allocation of labor affects the overall efficiency and comprehensive level of economic development in a region. Firstly, this paper collects and analyzes the data from 2011 to 2020, then screens out useful data, and predicts the relevant data of the three major industries in 2021 by the grey prediction method and curve fitting method. Secondly, the principal component analysis is used to calculate the weights of indicators such as market share, industrial growth rate, employment contribution rate, and the pulling ability to GDP, and then the strength of each industry is calculated. Finally, the strong industries are determined according to the principle of increasing the intensity of strong industries, so as to provide suggestions for the optimization of the allocation of labor market resources in the three major industries.

Suggested Citation

  • Xiaojing Liu, 2022. "Labor Market Resource Allocation Optimization Based on Principal Component Analysis," Journal of Mathematics, John Wiley & Sons, vol. 2022(1).
    • Handle: RePEc:wly:jjmath:v:2022:y:2022:i:1:n:1478013
    DOI: 10.1155/2022/1478013
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    References listed on IDEAS

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    1. Wang, Jun & Hu, Yong & Zhang, Zhiming, 2021. "Skill-biased technological change and labor market polarization in China," Economic Modelling, Elsevier, vol. 100(C).
    2. Zaohong Liu & Zhangzejun Jiang & Chen Xu & Guanjun Cai & Jian Zhan, 2021. "Assessment of provincial waterlogging risk based on entropy weight TOPSIS–PCA method," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 108(2), pages 1545-1567, September.
    3. WANG, Sophie Xuefei & Yu Benjamin, FU, 2019. "Labor mobility barriers and rural-urban migration in transitional China," China Economic Review, Elsevier, vol. 53(C), pages 211-224.
    4. Weidong Zhao & Qingfeng Zeng & Guangjian Zheng & Liu Yang, 2017. "The resource allocation model for multi-process instances based on particle swarm optimization," Information Systems Frontiers, Springer, vol. 19(5), pages 1057-1066, October.
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    1. Longyue Li & Zhonghui Jia & Bo Cao & Minghui Yan & Ye Tian, 2025. "An Integrated Approach for Screening Multidimensional Indicators in Combat Capability Assessment," Journal of Mathematics, John Wiley & Sons, vol. 2025(1).

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