Performance Evaluation of Online Recruitment Enterprises Based on Intuitionistic Fuzzy Set and TOPSIS

Xiaoyun Chen, Zhe Xue and Wen-Tsao Pan

Mathematical Problems in Engineering, 2022, vol. 2022, 1-10

Abstract: With the advancement of global informatization process, the development of online recruitment enterprises shows a continuous growth trend. Moreover, the growth rate has long been higher than the average level of the information industry. The adjustment and improvement of industrial structure has become an important means for the sustainable development of online recruitment enterprises. In order to further improve the development level of enterprise online recruitment performance, this paper proposes an improved intuitionistic fuzzy analytic hierarchy process and further proposes an intuitionistic fuzzy TOPSIS method optimized by adaptive ant colony algorithm. Select the sample system and finally determine the index system. Finally, the performance of the improved intuitionistic fuzzy set and TOPSIS method is evaluated. The results show that the improved intuitionistic fuzzy set based on adaptive ant colony algorithm and TOPSIS method proposed in this paper is obviously superior to other methods in optimization ability, stability, convergence speed, and running time and can be better applied to practical work. The improvement of the average performance level of online recruitment enterprises in 2022 mainly depends on the improvement of recruitment and appointment level. Enterprises also need to strengthen recruitment and appointment and optimize the company's performance management as a whole.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:8526826

DOI: 10.1155/2022/8526826

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