Handbook of big data research methods / edited by Shahriar Akter, Samuel Fosso Wamba.

Format:

Book

Contributor:

Akter, Shahriar, editor.

Fosso Wamba, Samuel, editor.

Series:

Research handbooks in information systems series.

Language:

English

Subjects (All):

Big data--Research.

Big data.

Physical Description:

1 online resource (xi, 322 pages) illustrations

Edition:

1st ed.

Place of Publication:

Cheltenham, UK : Edward Elgar Publishing Limited, 2023.

Summary:

This state-of-the-art Handbook provides an overview of the role of big data analytics in various areas of business and commerce, including accounting, finance, marketing, human resources, operations management, fashion retailing, information systems, and social media. It provides innovative ways of overcoming the challenges of big data research and proposes new directions for further research using descriptive, diagnostic, predictive, and prescriptive analytics. With contributions from leading academics and practitioners, the Handbook analyses how big data analytics can be used in different sectors, including detecting credit fraud in the financial sector, identifying potential diseases in health care, and increasing customer loyalty in the telecommunication sector. Chapters explore the use of artificial intelligence in accounting, the construction of successful data science ecosystems using the public cloud, and transformational models of personal data protection in the digital era. The Handbook also discusses the difficulties of adopting a data science platform and how the public cloud can aid companies in overcoming these challenges. Exploring how industries rely on predictive analytics to improve their decision-making, this Handbook will be essential reading for students and scholars in business analytics, economics, information systems, innovation and technology, and research methods. It will also benefit data analysts, economists, human resource managers, marketers, neuroscientists, and social science researchers.

Contents:

Front Matter

Copyright

Contents

Contributors

1. Introduction to the Handbook of Big Data Research Methods

2. Big data research methods in financial prediction

3. Big data, data analytics and artificial intelligence in accounting: an overview

4. The benefits of marketing analytics and challenges

5. How big data analytics will transform the future of fashion retailing

6. Descriptive analytics and data visualization in e-commerce

7. Application of big data Bayesian interrupted time-series modeling for intervention analysis

8. How predictive analytics can empower your decision making

9. Gaussian process classification for psychophysical detection tasks in multiple populations (wide big data) using transfer learning

10. Predictive analytics for machine learning and deep learning

11. Building a successful data science ecosystem using public cloud

12. How HR analytics can leverage big data to minimise employees' exploitation and promote their welfare for sustainable competitive advantage

13. Embracing Data-Driven Analytics (DDA) in human resource management to measure the organization performance

14. A process framework for big data research: social network analysis using design science

15. Notre-Dame de Paris cathedral is burning: let's turn to Twitter

16. Does personal data protection matter in data protection law? A transformational model to fit in the digital era

17. Understanding the Future trends and innovations of AI-based CRM systems

18. Descriptive analytics methods in big data: a systematic literature review

Index.

Notes:

Includes bibliographical references and index.

Description based on publisher supplied metadata and other sources.

ISBN:

9781800888555

OCLC:

1385455885