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Job satisfaction and turnover decision of employees in the Internet sector in the US.
- Source :
- Enterprise Information Systems; Aug2023, Vol. 17 Issue 8, p1-33, 33p
- Publication Year :
- 2023
-
Abstract
- This paper proposes that high value on the work-life balance, compensation, career opportunity and fitness of culture and management style would improve job satisfaction. A turnover risk prediction model based on the random forest is constructed to understand the turnover risk feature and identify risk. Using a sample of 17,724 online reviews of employees from Glassdoor, the positive effect of antecedents, the job satisfaction variable as a mediator, and the unemployment rate variable as a moderator is verified. Finally, job satisfaction is identified as the most important feature for predicting turnover based on the random forest algorithm. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 17517575
- Volume :
- 17
- Issue :
- 8
- Database :
- Complementary Index
- Journal :
- Enterprise Information Systems
- Publication Type :
- Academic Journal
- Accession number :
- 164705119
- Full Text :
- https://doi.org/10.1080/17517575.2022.2130013