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.

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.

Religion is an important part of individual lives, playing a major role in our decision making and puchasing. Understanding the influence of religion on consumer behaviour is therefore an essential practice for business. The COVID-19 pandemic has especially enhanced the influence of consumers' religiosity on their consumption decisions. This book concentrates on understanding the relationship of religiosity with various aspects of consumption and consumer behaviour to improve policy and build on an under represented topic. In this edited collection, expert contributors, academicians and researchers discuss the influence of religion on consumer behaviour in depth including the "dark side" of religion on consumers' consumption behaviour and religious cults. The chapters also explore the ethical issues surrounding consumption and the role of religion on branding and sustainable practices. With a broad perspective, the book draws on examples of practices from Christianity, Islam, Hinduism and Buddhism. This book will be a particularly valuable resource for scholars and upper level students of marketing, consumer behaviour and consumer psychology. The interdisciplinary perspectives will also appeal to those studying sociology and globalization.