An Analytics Approach for Proactively Combating Voluntary Attrition of Employees

By Moninder Singh, Kush R. Varshney, Jun Wang, Aleksandra Mojsilovic, Alisia R. Gill, Patricia I. Faur, Raphael Ezry. 2012

28 citations recorded by the source corpus.

Subfields: Industrial and Manufacturing Engineering, Management Science and Operations Research, Strategy and Management

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Industrial and Manufacturing Engineering

1. Vijay Arya
2. Karthikeyan Shanmugam
3. Dennis Wei

In Management Science and Operations Research

1. Q. Liao
2. Pin-Yu Chen
3. Ronny Luss
4. Prasanna Sattigeri
5. Kush R. Varshney

In Strategy and Management

1. Kush R. Varshney
2. Dennis Wei

Citations in the corpus

• On the Safety of Machine Learning: Cyber-Physical Systems, Decision Sciences, and Data Products (2016, background): “1) Predicting Voluntary Resignation: We recently studied a Type A problem of predicting which IBM employees will voluntarily resign from the company in the next six months based on human resources and compensation data, which required us to develop a classification algorithm to be place d within a l”
• Data Science of the People , for the People , by the People : A Viewpoint on an Emerging Dichotomy (2015, background): “We recently studied a Type A problem of predicting which IBM employees will voluntarily resign from the company, which required us to develop a classification algorithm to be placed within a larger decision-making system involving human decision makers [47].”
• One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques (2019, background): “Consider the use case of determining which employees should be targeted with a retention action to dissuade them from leaving the company [53].”
• Robust binary hypothesis testing under contaminated likelihoods (2014, background): “For example, decision maker s may want to use human resources data to predict whether or not an employee will voluntarily resign within th e next 12 months [1], or decision makers may want to determine whether an employee from another division is a s uit ble candidate to fill an open position on a t”