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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
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.
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