The application of big data analytics in all fields of research is a critical driver for the competitiveness of all countries in the modern world. Currently, governments and industry generate large amounts of data driven by record keeping, compliance, regulations, data privacy, and dynamic requirements, and thus there is a need to create better mechanisms to analyse data, and hence support organizational development, as well as providing aid to policymakers' decision-making processes. In this context, there are emerging disruptive opportunities because of Big Data: new business models, and vertical industry segments will emerge through shared relationships with all the stakeholders, and big data analytics is a major asset to support these dynamic relationships. This book was developed with the objective of analysing some of those challenges while at the same time providing a perspective of the potential of big data analytics, and the importance that analytics have for managers and for policymakers, to help define new strategies and new public policies, respectively. The book is focused on different sectors of activity (i.e. the Health sector, Public Administration, the Education sector, among others), and on different economic dimensions (i.e. Entrepreneurship, and Innovation) and links big data analytics to different fields of research, such as artificial intelligence and other emergent technologies; which are challenging organisations, governments, and societies, with the need to face the new imperative of being prepared for the very uncertain and tremendously complex future - in which big data analytics will play a very decisive and active role.
Author(s): Maria José Sousa, Manuel Au-yong Oliveira
Series: Research Methodology and Data Analysis
Publisher: Nova Science Publishers
Year: 2020
Language: English
Pages: 214
City: New York
Contents
Preface
Chapter 1
Potential of Big Data for Healthcare and Pharmaceutical Professionals Skills Development
Abstract
Introduction
Research Approach and Methodology
Systematic Review Approach and Search Terms
Search Strategy
Data Sources
Search Terms and Selection Criteria
Inclusion, Exclusion and Eligibility
Snowballing
Results from Systematic Review
Findings and Contributions
Conclusion
References
Chapter 2
Knowledge Transfer on Innovation Policies from EU to BRICS: The Power of Big Data Analytics
Abstract
Introduction
Theoretical Framework
Knowledge Conceptualization
Innovation Policies Framework
Big Data Analytics
Empirical Research Approach
Methodology
Lessons from the Field on Knowledge Transfer of Innovation Policies from EU to BRICS
1st Dimension Knowledge Transfer Actors
2nd Dimension Knowledge Transfer Activities
3rd Dimension Integration of Knowledge
4th Dimension - Obstacles and Facilitators
Recommendations for BRICS Policies from the EU Lessons
Conclusion
References
Chapter 3
Big Data Analytics: A New Competitive Advantage
Abstract
1. Introduction and Background
2. Methodology
3. Findings of the Thematic Analysis
3.1. Big Data and Competitive Advantages through Added Business Value
3.2. Big Data and Competitive Advantages through Enhanced Operations
3.3. Big Data and Competitive Advantages through Improved Organizational Knowledge
3.4. Big Data and Competitive Advantages through New Product Development
Conclusion
Acknowledgments
Annex I. Overview of Document Citations Period ≤ 2005 to 2020
Annex II. Overview of Document Self-Citation Period ≤ 2005 to 2020
References
Chapter 4
Integrative Review: Relationship between Big Data and Educational Content Repository
Abstract
Introduction
Theoretical Contribution
Big Data
Repositories of Educational Content
Methods - Integrative Literature Review
Research, Analysis and Discussion of Articles
Relationships between Big Data and Educational Content Repository
Conclusion
References
Chapter 5
The New Challenges of Artificial Intelligence, Profiling and Bigdata Analysis by Tax Administrations: Will the Right to Meet These New Challenges be Shown?
Abstract
Introduction
The New Centrality of Bigdata and Artificial Intelligence
The Dangers of Artificial Intelligence and Bigdata Analysis in Tax Administrations
Conclusion
References
Chapter 6
Big Data Analytics: Emergence, Growth, Issues and Potential
Abstract
Introduction
Literature Review
Emergence and Growth of Big Data Analytics
Issues Associated with Big Data Analytics
Future Prospects of Big Data Analytics
Conclusion
References
Chapter 7
Big Data Analytics to Support Digital Government Public Policies
Abstract
1. Introduction
2. Theoretical Framework
2.1. Concepts and Theories
2.2. Linkages between e-Gov and Big Data Analytics
2.3. Portuguese e-Gov Development Policies in the Context of the European Union
3. Methodological Approach
3.1. Methodology, Observation Context and Consulted Data, to Retrieve the Results
3.2. Digital Transformation Support, in Portugal, as a Case Study in Digital Government
3.3. Results of the Analysis
3.4. Discussion
Conclusion
References
Chapter 8
Big Data Linkages to SDG and Entrepreneurship: A Case Study Approach
Abstract
1. Introduction
2. Big Data, SDG and Entrepreneurship Concepts and Linkages
3. SDG Theoretical Framework
4. Methodological Approach
4.1. Case Studies
4.1.1. Case Study 1 – Dress for Sucess
4.1.1.1. Organization Context
4.1.1.2. UN SDG Implemented by the Organization
4.1.1.3. Contributions for the Wellbeing of the Workers and Citizens
4.1.1.4. Bigdata
4.1.2. Case Study 2 - Sigues
4.1.2.1. Organization Context
4.1.2.2. UN SDG Implemented by the Organization
4.1.2.3. Contributions for the Wellbeing of the Workers and Citizens
4.1.2.4. Big Data
4.1.3. Case Study 3 – Cfisio
4.1.3.1. Organization Context
4.1.3.2. UN SDG Implemented by the Organization
4.1.3.3. Contributions for the Wellbeing of the Workers and Citizens
4.1.3.4. Big Data
Conclusions, Limitations and Future Research
Conclusion
Limitation
Future Lines of Research
Annex I –Questionnaire
Marketing Strategy vs Sustainable Development Objective
Marketing Strategy
Relationship with Customers and Suppliers
Sustainable Development Goals (UN)
References
About the Editors
About the Authors
Index
