NDLI: Testing for Invariance of Employee Turnover Intention Model: Multi-Group Comparison Between Knowledge Workers and Traditional Staff

Content Provider	IEEE Xplore Digital Library
Author	Wu Yang Yu Xiaomin Xu Congwei
Copyright Year	2008
Description	Author affiliation: Sch. of Econ. & Manage., Beihang Univ., Beijing (Wu Yang; Yu Xiaomin)
Abstract	Employee turnover is one of the most durable issues in both organizational behavior research and human resource management practice. Although a great deal of employee turnover models has been well established, much of these researches have not considered the differences between occupation groups. In an effort to fill this theoretical gap, the present study attempted to provide an examination of a turnover intention model and some of the predictors across two groups: knowledge workers and traditional staff, and then distinguished their different influencing mechanisms on employee turnover intention. This study used multi-group structural equation modeling techniques as a cross-validation procedure to investigate whether the proposed model remained stable across two samples. The empirical examination was also conducted. The results based on 606 employees' responses from two occupational categories indicate that four antecedents are significantly associated with employee turnover intention mediated by job satisfaction and organizational commitment. This study finds the model with an adequate level of configural invariance across two groups. However, the corresponding regression weights are significantly different. The findings suggest that both researchers and practitioners should take into consideration not only the organizational factors, but also the occupational type while exploring the process of employee turnover.
Starting Page	1
Ending Page	4
File Size	110179
Page Count	4
File Format	PDF
ISBN	9781424421077
DOI	10.1109/WiCom.2008.1708
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-12
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Technology management Medical services Predictive models Economic forecasting Knowledge management Resource management Human resource management Research and development management Equations Testing
Content Type	Text
Resource Type	Article

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