|
|
|
|
| LEADER |
04895nmm a2200289 u 4500 |
| 001 |
EB002168257 |
| 003 |
EBX01000000000000001305589 |
| 005 |
00000000000000.0 |
| 007 |
cr||||||||||||||||||||| |
| 008 |
230705 ||| eng |
| 020 |
|
|
|a 9781800888555
|
| 050 |
|
4 |
|a QA76.9.B45
|
| 100 |
1 |
|
|a Akter, Shahriar
|e [editor]
|
| 245 |
0 |
0 |
|a Handbook of big data research methods
|h Elektronische Ressource
|c edited by Shahriar Akter (Faculty of Business and Law, University of Wollongong, Australia) and Samuel Fosso Wamba (Department of Information, Operations and Management Sciences, Toulouse Business School, France)
|
| 260 |
|
|
|a Cheltenham, UK
|b Edward Elgar Publishing Limited
|c 2023, 2023
|
| 300 |
|
|
|a 334 pages
|
| 505 |
0 |
|
|a 16. Does personal data protection matter in data protection law? A transformational model to fit in the digital era / Gowri Harinath -- 17. The future of ai-based crm / Khadija Alnofeli, Shahriar Akter and Venkata Yanamandram -- 18. Descriptive analytics methods in big data: A systematic literature review / Nilupulee Liyanagamage and Mario Fernando -- Index
|
| 505 |
0 |
|
|a Includes bibliographical references and index
|
| 505 |
0 |
|
|a 9. Gaussian process classification for psychophysical detection tasks in multiple populations (wide big data) using transfer learning / Hossana Twinomurinzi and Hermanus C. Myburgh -- 10. Predictive analytics for machine learning and deep learning / Tahajjat Begum -- 11. Building a successful data science ecosystem using public cloud / Mohammad Mahmudul Haque -- 12. How hr analytics can leverage big data to minimise employees' exploitation and promote their welfare for sustainable competitive advantage / Kumar Biswas, Sneh Bhardwaj and Sawlat Zaman -- 13. Embracing data-driven analytics (dda) in human resource management to measure the organization performance / P.S. Varsha and S. Nithya Shree -- 14. A process framework for big data research: Social network analysis using design science / Denis Dennehy, Samrat Gupta and John Oredo -- 15. Notre-dame de paris cathedral is burning: Let's turn to twitter / Serge Nyawa, Dieudonné Tchuente and Samuel Fosso Wamba --
|
| 505 |
0 |
|
|a Contents: 1. Introduction to the handbook of big data research methods / Shahriar Akter, Samuel Fosso Wamba, Shahriar Sajib and Sahadat Hossain -- 2. Big data research methods in financial prediction / Md Lutfur Rahman and Shah Miah -- 3. Big data, data analytics and artificial intelligence in accounting: An overview / Sudipta Bose, Sajal Kumar Dey and Swadip Bhattacharjee -- 4. The benefits of marketing analytics and challenges / Madiha Farooqui -- 5. How big data analytics will transform the future of fashion retailing / Niloofar Ahmadzadeh Kandi -- 6. Descriptive analytics and data visualization in e-commerce / P.S. Varsha and Anjan Karan -- 7. Application of big data bayesian interrupted time-series modeling for intervention analysis / Neha Chaudhuri and Kevin Carillo -- 8. How predictive analytics can empower your decision making / Nadia Nazir Awan --
|
| 653 |
|
|
|a Big data / Research
|
| 700 |
1 |
|
|a Fosso Wamba, Samuel
|e [editor]
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
|
|b ZDB-1-EEM
|a Edward Elgar eBooks Collection Business & Economics
|
| 856 |
4 |
0 |
|u https://www.elgaronline.com/view/book/9781800888555/9781800888555.xml
|x Verlag
|3 Volltext
|
| 082 |
0 |
|
|a 510
|
| 520 |
|
|
|a 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
|