Handbook of Big Data Research Methods
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Handbook of Big Data Research Methods: (Research Handbooks in Information Systems)

Handbook of Big Data Research Methods: (Research Handbooks in Information Systems)


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About the Book

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.

Table of Contents:
Contents: 1 Introduction to the Handbook of Big Data Research Methods 1 Shahriar Akter, Samuel Fosso Wamba, Shahriar Sajib and Sahadat Hossain 2 Big data research methods in financial prediction 11 Md Lutfur Rahman and Shah Miah 3 Big data, data analytics and artificial intelligence in accounting: an overview 32 Sudipta Bose, Sajal Kumar Dey and Swadip Bhattacharjee 4 The benefits of marketing analytics and challenges 52 Madiha Farooqui 5 How big data analytics will transform the future of fashion retailing 72 Niloofar Ahmadzadeh Kandi 6 Descriptive analytics and data visualization in e-commerce 86 P.S. Varsha and Anjan Karan 7 Application of big data Bayesian interrupted time-series modeling for intervention analysis 105 Neha Chaudhuri and Kevin Carillo 8 How predictive analytics can empower your decision making 117 Nadia Nazir Awan 9 Gaussian process classification for psychophysical detection tasks in multiple populations (wide big data) using transfer learning 128 Hossana Twinomurinzi and Hermanus C. Myburgh 10 Predictive analytics for machine learning and deep learning 148 Tahajjat Begum 11 Building a successful data science ecosystem using public cloud 165 Mohammad Mahmudul Haque 12 How HR analytics can leverage big data to minimise employees’ exploitation and promote their welfare for sustainable competitive advantage 179 Kumar Biswas, Sneh Bhardwaj and Sawlat Zaman 13 Embracing Data-Driven Analytics (DDA) in human resource management to measure the organization performance 195 P.S. Varsha and S. Nithya Shree 14 A process framework for big data research: social network analysis using design science 214 Denis Dennehy, Samrat Gupta and John Oredo 15 Notre-Dame de Paris cathedral is burning: let’s turn to Twitter 233 Serge Nyawa, Dieudonné Tchuente and Samuel Fosso Wamba 16 Does personal data protection matter in data protection law? A transformational model to fit in the digital era 266 Gowri Harinath 17 The future of AI-based CRM 278 Khadija Alnofeli, Shahriar Akter and Venkata Yanamandram 18 Descriptive analytics methods in big data: a systematic literature review 294 Nilupulee Liyanagamage and Mario Fernando Index

About the Author :
Edited by Shahriar Akter, Faculty of Business and Law, University of Wollongong, Australia and Samuel Fosso Wamba, Department of Information, Operations and Management Sciences, TBS Business School, France

Review :
‘Big data research methods have gained dramatic momentum in the world. Researchers and practitioners extend this line of research constantly by producing journals, posts, news articles and podcasts. However, there is a paucity of a book that covers descriptive, diagnostic, predictive and prescriptive method-based research papers under one umbrella. This is one of those books which will immerse a reader in the past, present and future of big data analytics methods. It is an exceptional book that is grounded in evidence and meaningful to practice.’


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Product Details
  • ISBN-13: 9781800888548
  • Publisher: Edward Elgar Publishing Ltd
  • Publisher Imprint: Edward Elgar Publishing Ltd
  • Height: 244 mm
  • No of Pages: 334
  • Width: 169 mm
  • ISBN-10: 1800888546
  • Publisher Date: 23 Jun 2023
  • Binding: Hardback
  • Language: English
  • Series Title: Research Handbooks in Information Systems


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