Big data and decision-making : applications and uses in the public and private sector

Big data and its accompanying technological ecosystems have had a dramatic impact on business, politics and society. At the same time, the very nature of big data, a term that originates from computer science discourse, often remains opaque to research communities in other disciplines as well as to...

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Bibliographic Details
Other Authors: Visvizi, Anna, 1976- (Editor) 
Troisi, Orlando (Editor) 
Grimaldi, Mara (Editor)
Corporate Author: Emerald Insight (online služba) (Distributor) 
Format: eBook
Language:English
Published: Bingley, U.K. : Emerald Publishing Limited, 2023
Series:Emerald studies in politics and technology
Genre/form:sborníky
elektronické knihy
ISBN:978-1-80382-553-3
978-1-80382-551-9
978-1-80382-552-6
Subjects:
Online Access:Plný text
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Table of Contents:
  • Chapter 1. Big data & decision-making: How big data is relevant across fields and domains
  • Part 1: Conceptualizing big data, its value added and relevance in the modern world
  • Chapter 2. Mapping and conceptualizing big data and its value across issues and domains
  • Chapter 3. Digital governance for addressing performance challenges within inter-municipalities
  • Chapter 4. Misuse of personal data: Exploring the privacy paradox in the age of big data analytics
  • Chapter 5. Nosql security: Can my data-driven decision-making be affected from outside?
  • Chapter 6. Big data, knowledge sharing, and the innovation process: A systematic literature review
  • Part 2: Big big data and its application across policy fields
  • Chapter 7. Transparency in AI systems for value co-creation in healthcare
  • Chapter 8. Big data and its impact on tourism and entrepreneurship
  • Chapter 9. Big data and digital technologies for circular economy in the agri-food sector
  • Part 3: Business & policy-making process empowered by big data
  • Chapter 10. Business processes powered by big data: Current issues and new research directions
  • Chapter 11. Barriers and practical challenges for data-driven decision-making in circular economy SMEs
  • Chapter 12. A co-evolutionary perspective on data-driven organization: Highlights from smart cities in the covid-19 era
  • Chapter 13. What Does It Take to Build a Smart Sustainable City? – Modeling an Algorithm of Smart Cities