Employee turnover prediction model, a case study of hi-tech R&D-team.
| Autor: | Chia-Hsun Cheng, 鄭嘉勳 |
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| Rok vydání: | 2018 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 106 Base on the approach of machine learning, we built an employee turnover prediction model faster and more visualization by utilizing Decision tree on human resource management (HRM) data. These advantages allow it be more useful in practice and reflect the condition of labor force in firm timely. In this thesis, we refer to many factors of predicting turnover behavior from literatures, and collect these factors from EHRMs of the firm. We find out some significant changes of those who left or stayed within five years. Then, we build a turnover prediction model by these changes. We totally get 889 records of 237 employees from the firm. The result of the model is : (1) Those who took leaves more than 43 times, 95% of them leave (2) Those who took leaves less than or equal to 43 times and had more than 48 months’ seniority, 0.2% of them leave. (3) Those who took leaves between 18 to 43 times and had less than or equal to 48 months’ seniority, 69% of them leave. (4) Those who took leaves less than or equal to 18 times and had between 27 to 48 months’ seniority, 5.3% of them leave. (5) Those who took leaves less than or equal to 18 times and had between 3 to 27 months’ seniority, 33% of them leave. (6) Those who Those who took leaves less than or equal to 18 times and had less than or equal to 3 months’ seniority, 64.2% of them leave. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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