Research on the Current Situation of Employment Mobility and Retention Rate Predictions of “Double First-Class” University Graduates Based on the Random Forest and BP Neural Network Models

Yilin Zhao, Feng He and Ying Feng
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Yilin Zhao: School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China
Feng He: School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China
Ying Feng: School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China

Sustainability, 2022, vol. 14, issue 14, 1-22

Abstract: The economic development of various regions is influenced by high-quality population mobility. The research object of this article is the employment mobility data of “Double First-Class” university graduates from 2014 to 2019; the subsequent analysis is based on these data. First, this paper summarizes the current state of university graduates’ employment mobility. Second, this paper employs the fixed-effect model and PCA method to conclude that economic factors are the primary factors influencing university graduates’ employment mobility. Finally, based on the nonlinear, small sample, and high-dimensional characteristics of university graduates’ employment mobility data, this paper employs the random forest and BP neural network methods to build a prediction model for university graduates’ employment retention rate. The results show that the BP neural network model outperforms the random forest model in terms of prediction accuracy. The BP neural network model can accurately predict the employment retention rate of “Double First-Class” university graduates, which can guide the reasonable mobility of university graduates and provide a reference for government universities and individuals to make decisions.

Keywords: double first-class; random forest; BP neural network; prediction; graduates; university; employment; mobility (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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