CYMLJul 5, 2017

Employee turnover prediction and retention policies design: a case study

arXiv:1707.01377v118 citations
Originality Synthesis-oriented
AI Analysis

This addresses employee retention for organizations, but it is incremental as it applies known customer churn methods to a new domain.

The paper tackled employee turnover prediction by developing a model using classical machine learning techniques, and used the model outputs to design and test retention policies, with the retention discussion highlighted as innovative.

This paper illustrates the similarities between the problems of customer churn and employee turnover. An example of employee turnover prediction model leveraging classical machine learning techniques is developed. Model outputs are then discussed to design \& test employee retention policies. This type of retention discussion is, to our knowledge, innovative and constitutes the main value of this paper.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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