Predicting and explaining employee turnover intention

被引:0
|
作者
Matilde Lazzari
Jose M. Alvarez
Salvatore Ruggieri
机构
[1] Effectory Global,
[2] Scuola Normale Superiore,undefined
[3] University of Pisa,undefined
关键词
Employee turnover; Predictive models; EXplainable AI (XAI); Structural causal models;
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中图分类号
学科分类号
摘要
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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页码:279 / 292
页数:13
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