Job satisfaction and turnover decision of employees in the Internet sector in the US

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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.

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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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