02177nam a2200169   4500999001700000020001800017082002200035245009200057260004900149300001400198520155000212650002501762700002801787700003301815942001201848952014701860  c39240d39240  a9781800888548  aRR.005.7407bHAN-  aHandbook of Big Data Research Methods/cedited by Shahriar Akter and Samuel Fosso Wamba  aLondon:bEdward Elgar Publishing Ltd,c2023.  axi, 322p.  aThis 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.  aResearch Methodology  aAkter, Shahriareeditor  aWamba, Samuel Fosso eeditor  2ddccBK  001040708HBMaNASSDOCbNASSDOCd2024-03-21g12464.01i20-03-2024l0oRR.005.7407 HAN-p54342r2024-05-20 00:00:00v19175.40w2024-05-20yRB