Applied Mathematics and Nonlinear Sciences
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Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 2


Published
on

November 4, 2023


Pages


DOI

Article

Optimisation Path of Human Resource Performance Management in Universities Based on Big Data in the Era of Digital Economy

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Authors

Lisheng Hu Affiliation:
Shaoxing University Yuanpei College, Shaoxing, Zhejiang, 312000, China.
and Yuanyuan Zhang Affiliation:
Shaoxing University Yuanpei College, Shaoxing, Zhejiang, 312000, China.


Abstract

This paper aims to create a digital platform that uses big data to manage HR performance. Firstly, the FCM algorithm transforms the dataset according to its affiliation degree and constructs a new database. An objective function is established to optimize the classification of organizational information using the correlation between data. Finally, the AHP algorithm is introduced to set indicator weights and factor sets, making the assessment results more hierarchical. The results show that the management platform system constructed in this paper operates stably, keeping the departure rate of university staff at about 5%, and 92% of students believe that the platform can improve teachers’ teaching quality. This shows that big data technology optimizes human resources management in colleges and universities.


Keywords

Big data, FCM algorithm, Objective function, AHP algorithm, Human resource management, 97D60


Citation

Hu, L. & Zhang, Y. (2023). Optimisation path of human resource performance management in universities based on big data in the era of digital economy. Applied Mathematics and Nonlinear Sciences, 8(2). https://doi.org/10.2478/amns.2023.2.00969
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