This volume is a step-by-step guide to implementing predictive data analytics in human resource management (HRM). It demonstrates how to apply and predict various HR outcomes which have an organisational impact, to aid in strategising and better decision-making.
The book:
• Presents key concepts and expands on the need and role of HR analytics in business management.
• Utilises popular analytical tools like artificial neural networks (ANNs) and K-nearest neighbour (KNN) to provide practical demonstrations through R scripts for predicting turnover and applicant screening.
• Discusses real-world corporate examples and employee data collected first-hand by the authors.
• Includes individual chapter exercises and case studies for students and teachers.
Comprehensive and accessible, this guide will be useful for students, teachers, and researchers of data analytics, Big Data, human resource management, statistics, and economics. It will also be of interest to readers interested in learning more about statistics or programming.
Cover 1
Half Title 2
Title 4
Copyright 5
Dedication 6
Contents 8
List of illustrations 10
Foreword 12
Foreword 13
Foreword 14
Preface 16
Acknowledgements 18
List of abbreviations 20
1 Analytics in HRM 22
2 Looking for data 54
3 Modelling the business problem 88
4 Predictive analytics tools and techniques 107
5 Evaluation of analytical outcomes 130
6 Predictive HR analytics in recruitment and selection 144
7 Predictive HR analytics in turnover and separation 172
8 Predictive HR analytics in other areas of HRM 197
9 Emerging trends in predictive HR analytics 218
Subject index 234
Company index 237

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SHIVINDER RAJ, SAHIL NIJJER

Psychology Press Ltd

CRC Press

United Kingdom and Ireland, United Kingdom

Abingdon, Oxon, 2021

London, 2021

lg2880254

sources:
9780367903213

producers:
Adobe PDF Library 15.0

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"This volume is a step by step guide to implementing predictive data analytics in human resource management (HRM). It demonstrates how to apply and predict various HR outcomes which have an organizational impact, to aid in strategizing and better decision making. The book: Presents key concepts and expands on the need and role of HR analytics in business management; Utilises popular analytical tools like Artificial Neural Networks (ANN) and K-Nearest Neighbour (KNN) to provide practical demonstrations through R scripts for predicting turnover and applicant screening; Discusses real world corporate examples and employee data collected first-hand by the authors; Includes chapter-wise problem exercises and case studies for students and teachers. Comprehensive and accessible, this guide will be useful for students, teachers and researchers of data analytics, big data, human resource management, statistics, and economics. It will also be of interest to general readers unfamiliar with statistics or programming"-- Provided by publisher

2020-12-10