Screen LibraryBig 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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| Group Author: | ; ; |
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| Published: |
Emerald Publishing Limited,
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| Publisher Address: | Bingley, UK : |
| Publication Dates: | 2023. |
| Literature type: | Book |
| Language: | English |
| Edition: | First edition. |
| Series: |
Emerald studies in politics and technology
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| Subjects: | |
| Summary: |
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 practitioners. Considering the pervasive impact of big data across a number of issues and domains, clearer insight into its functions and practical application is needed. Through a unique blend of case studies and critical analysis, Big Data and Decision-Making: Applications and Uses in the Public and Private Sector examines how big data influences contemporary societies in decision-making processes, strategy setting and overall performance. Covering topics ranging from data privacy to AI, big data in healthcare, SMEs, tourism and smart cities, contributors offer a critical appraisal of lessons learnt in the process of harnessing the promise inherent in big data. Big Data and Decision-Making: Applications and Uses in the Public and Private Sector breaks down the concept of big data to reveal how it has become integrated into the fabric of both public and private domains, as well as how its value can ultimately be exploited. To this end, its contributors call for the building of bridges between the computer science-driven debate on big data and research taking place in social sciences and management. -- |
| Carrier Form: | xiv, 221 pages : illustrations ; 24 cm. |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: |
9781803825526 1803825529 |
| Index Number: | HD30 |
| CLC: | C934-37 |
| Call Number: | C934-37/B592 |
| Contents: | Chapter 1. Big Data & Decision-Making: How Big Data is Relevant across Fields and Domains; Anna Visvizi, Orlando Troisi, and Mara Grimaldi 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; Anna Visvizi, Orlando Troisi, and Mara Grimaldi Chapter 3. Digital Governance for Addressing Performance Challenges within Inter-Municipalities; Giulia Leoni, Gennaro Maione, and Luca Mazzara Chapter 4. Misuse of Personal Data: Exploring the Privacy Paradox in the Age of Big Data Analytics; Xhimi Hysa, Mario D'Arco, and Joana Kostaqi Chapter 5. NoSQL Security: Can my Data-Driven Decision-Making Be Affected from Outside?; Anastasija Nikiforova, Artjoms Daskevics, and Otmane Azeroual Chapter 6. Big Data, Knowledge Sharing, and the Innovation Process: A Systematic Literature Review; Gianluca Maria Guazzo and Vilma Çekani Part 2. Big Big Data and its Application Across Policy Fields Chapter 7. Transparency in AI Systems for Value Co-Creation in Healthcare; Antonietta Megaro Chapter 8. Big Data and its Impact on Tourism and Entrepreneurship; Antonio Botti and Antonella Monda Chapter 9. Big Data and Digital Technologies for Circular Economy in the Agri-Food Sector; Benedetta Esposito, Ornella Malandrino, Maria Rosaria Sessa, and Daniela Sica Part 3. Business & Policy-making Process Empowered by Big Data Chapter 10. Business Processes Powered By Big Data: Current Issues and New Research Directions; Radosław Malik and Katarzyna Rybkowska Chapter 11. Barriers and Practical Challenges for Data-Driven Decision-Making in Circular Economy SMEs; Anne-Mari Järvenpää, Jari Jussila, and Iivari Kunttu Chapter 12. A Co-Evolutionary Perspective on Data-Driven Organization: Highlights from Smart Cities in the Covid-19 Era; Francesca Loia Chapter 13. What does it take to Build a Smart Sustainable City? -- Modelling an Algorithm of Smart Cities; Olena Sokhatska and Ruslana Lutsiv |