Predicting Employee Career Development based on Employee Personal Background and Education Status
- Resource Type
- Authors
- Jiamin Liu; Tao Wang; Hao Wang; Erbao Wang; Yingwu Chen; Jiting Li
- Source
- DSIT
- Subject
- Knowledge management
ComputingMilieux_THECOMPUTINGPROFESSION
business.industry
05 social sciences
02 engineering and technology
Competitive advantage
020204 information systems
Human resource management
0502 economics and business
0202 electrical engineering, electronic engineering, information engineering
Statistical analysis
Business
050203 business & management
Career development
- Language
Recruiting and retaining high-potential employees is quite critical for enterprises to maintain competitive advantages in modern knowledge-intensive economy. In this paper, we attempt to identify existing talents who have development potentials based on their personal backgrounds and education statuses through data analysis and a prediction model. Our research is based on data that are collected from a large state-owned enterprise. Statistical analysis method is utilized to discover the correlations between the employee career development and their personal backgrounds and education statuses. Besides, data mining used in the proposed prediction model is to forecast the potential employee career development. From the results, our research provides a reliable and practical way to use personal background and education status features forecast employee career development potential and find out significant factors affecting employee career development.