,  том 14 ,  издание 3 ,  страницы 279-292

Predicting and explaining employee turnover intention

Тип публикации: Journal Article
Дата публикации: 2022-05-23
SCImago Q1
WOS Q3
БС2
SJR: 0.954
CiteScore: 5.5
Impact factor: 2.9
ISSN: 2364415X, 23644168
Computer Science Applications
Computational Theory and Mathematics
Information Systems
Applied Mathematics
Modeling and Simulation
Краткое описание
Turnover intention is an employee’s reported willingness to leave her organization within a given period of time and is often used for studying actual employee turnover. Since employee turnover can have a detrimental impact on business and the labor market at large, it is important to understand the determinants of such a choice. We describe and analyze a unique European-wide survey on employee turnover intention. A few baselines and state-of-the-art classification models are compared as per predictive performances. Logistic regression and LightGBM rank as the top two performing models. We investigate on the importance of the predictive features for these two models, as a means to rank the determinants of turnover intention. Further, we overcome the traditional correlation-based analysis of turnover intention by a novel causality-based approach to support potential policy interventions.
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ГОСТ |
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Lazzari M. et al. Predicting and explaining employee turnover intention // International Journal of Data Science and Analytics. 2022. Vol. 14. No. 3. pp. 279-292.
ГОСТ со всеми авторами (до 50) Скопировать
Lazzari M., Alvarez J. M., Ruggieri S. Predicting and explaining employee turnover intention // International Journal of Data Science and Analytics. 2022. Vol. 14. No. 3. pp. 279-292.
RIS |
Цитировать
TY - JOUR
DO - 10.1007/s41060-022-00329-w
UR - https://doi.org/10.1007/s41060-022-00329-w
TI - Predicting and explaining employee turnover intention
T2 - International Journal of Data Science and Analytics
AU - Lazzari, Matilde
AU - Alvarez, Jose M
AU - Ruggieri, Salvatore
PY - 2022
DA - 2022/05/23
PB - Springer Nature
SP - 279-292
IS - 3
VL - 14
SN - 2364-415X
SN - 2364-4168
ER -
BibTex |
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BibTex (до 50 авторов) Скопировать
@article{2022_Lazzari,
author = {Matilde Lazzari and Jose M Alvarez and Salvatore Ruggieri},
title = {Predicting and explaining employee turnover intention},
journal = {International Journal of Data Science and Analytics},
year = {2022},
volume = {14},
publisher = {Springer Nature},
month = {may},
url = {https://doi.org/10.1007/s41060-022-00329-w},
number = {3},
pages = {279--292},
doi = {10.1007/s41060-022-00329-w}
}
MLA
Цитировать
Lazzari, Matilde, et al. “Predicting and explaining employee turnover intention.” International Journal of Data Science and Analytics, vol. 14, no. 3, May. 2022, pp. 279-292. https://doi.org/10.1007/s41060-022-00329-w.
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