Chang, Victor, Mou, Yeqing, Xu, Qianwen Ariel and Xu, Yue (2022). Job satisfaction and turnover decision of employees in the Internet sector in the US. Enterprise Information Systems ,
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.
Publication DOI: | https://doi.org/10.1080/17517575.2022.2130013 |
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Divisions: | College of Business and Social Sciences > Aston Business School College of Business and Social Sciences > Aston Business School > Operations & Information Management |
Additional Information: | © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) |
Uncontrolled Keywords: | Information Systems and Management,Computer Science Applications |
Publication ISSN: | 1751-7583 |
Last Modified: | 07 Oct 2024 07:39 |
Date Deposited: | 17 Oct 2022 10:53 |
Full Text Link: | |
Related URLs: |
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(Publisher URL) http://www.scop ... tnerID=8YFLogxK (Scopus URL) |
PURE Output Type: | Article |
Published Date: | 2022-10-07 |
Published Online Date: | 2022-10-07 |
Accepted Date: | 2022-09-26 |
Authors: |
Chang, Victor
(
0000-0002-8012-5852)
Mou, Yeqing Xu, Qianwen Ariel Xu, Yue |