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.
CITATION STYLE
Chang, V., Mou, Y., Xu, Q. A., & Xu, Y. (2023). Job satisfaction and turnover decision of employees in the Internet sector in the US. Enterprise Information Systems, 17(8). https://doi.org/10.1080/17517575.2022.2130013
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