The Big Data-Driven Digital Economy: Artificial and Computational Intelligence

The Big Data-Driven Digital Economy: Artificial and Computational Intelligence

Author: Abdalmuttaleb M. A. Musleh Al-Sartawi

Publisher: Springer Nature

Published: 2021-05-28

Total Pages: 472

ISBN-13: 3030730573

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This book shows digital economy has become one of the most sought out solutions to sustainable development and economic growth of nations. This book discusses the implications of both artificial intelligence and computational intelligence in the digital economy providing a holistic view on AI education, economics, finance, sustainability, ethics, governance, cybersecurity, blockchain, and knowledge management. Unlike other books, this book brings together two important areas, intelligence systems and big data in the digital economy, with special attention given to the opportunities, challenges, for education, business growth, and economic progression of nations. The chapters hereby focus on how societies can take advantage and manage data, as well as the limitations they face due to the complexity of resources in the form of digital data and the intelligence which will support economists, financial managers, engineers, ICT specialists, digital managers, data managers, policymakers, regulators, researchers, academics, students, economic development strategies, and the efforts made by the UN towards achieving their sustainability goals.


Digital Economy, Business Analytics, and Big Data Analytics Applications

Digital Economy, Business Analytics, and Big Data Analytics Applications

Author: Saad G. Yaseen

Publisher: Springer Nature

Published: 2022-09-26

Total Pages: 723

ISBN-13: 3031052587

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This book is about turning data into smart decisions, knowledge into wisdom and business into business intelligence and insight. It explores diverse paradigms, methodologies, models, tools and techniques of the emerging knowledge domain of digitalized business analytics applications. The book covers almost every crucial aspect of applied artificial intelligence in business, smart mobile and digital services in business administration, marketing, accounting, logistics, finance and IT management. This book aids researchers, practitioners and decisions makers to gain enough knowledge and insight on how to effectively leverage data into competitive intelligence.


Applications of Computational Intelligence in Data-Driven Trading

Applications of Computational Intelligence in Data-Driven Trading

Author: Cris Doloc

Publisher: John Wiley & Sons

Published: 2019-11-05

Total Pages: 313

ISBN-13: 1119550513

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“Life on earth is filled with many mysteries, but perhaps the most challenging of these is the nature of Intelligence.” – Prof. Terrence J. Sejnowski, Computational Neurobiologist The main objective of this book is to create awareness about both the promises and the formidable challenges that the era of Data-Driven Decision-Making and Machine Learning are confronted with, and especially about how these new developments may influence the future of the financial industry. The subject of Financial Machine Learning has attracted a lot of interest recently, specifically because it represents one of the most challenging problem spaces for the applicability of Machine Learning. The author has used a novel approach to introduce the reader to this topic: The first half of the book is a readable and coherent introduction to two modern topics that are not generally considered together: the data-driven paradigm and Computational Intelligence. The second half of the book illustrates a set of Case Studies that are contemporarily relevant to quantitative trading practitioners who are dealing with problems such as trade execution optimization, price dynamics forecast, portfolio management, market making, derivatives valuation, risk, and compliance. The main purpose of this book is pedagogical in nature, and it is specifically aimed at defining an adequate level of engineering and scientific clarity when it comes to the usage of the term “Artificial Intelligence,” especially as it relates to the financial industry. The message conveyed by this book is one of confidence in the possibilities offered by this new era of Data-Intensive Computation. This message is not grounded on the current hype surrounding the latest technologies, but on a deep analysis of their effectiveness and also on the author’s two decades of professional experience as a technologist, quant and academic.


Data-Driven Business Models for the Digital Economy

Data-Driven Business Models for the Digital Economy

Author: Rado Kotorov

Publisher: Business Expert Press

Published: 2020-04-21

Total Pages: 161

ISBN-13: 195152781X

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Today the fastest growing companies have no physical assets. Instead, they create innovative digital products and new data-driven business models. They capture huge market share fast and their capitalizations skyrocket. The success of these digital giants is pushing all companies to rethink their business models and to start digitizing their products and services. Whether you are a new start-up building a digital product or service, or an employee of an established company that is transitioning to digital, you need to consider how digitization has transformed every aspect of management. Data-driven business models scale not through asset accumulation and product standardization, but through disaggregation of supply and demand. The winners in the new economy master the demand for one and the supply to millions. Throughout the book the author illustrates with examples and use cases how the market competition has changed and how companies adept to the new rules of the game. The economic levers of scale and scope are also different in the digital economy and companies have to learn new tactics how to achieve and sustain their competitive advantage. While data is at the core of all digital business models, the monetization strategies vary across products, services and business models. Our Monetization Matrix is a model that helps managers, marketers, sales professionals, and technical product designers to align the digital product design with the data-driven business model.


Artificial Intelligence, Data And Blockchain In A Digital Economy, First Edition

Artificial Intelligence, Data And Blockchain In A Digital Economy, First Edition

Author: Infocomm Media Development Authority

Publisher: World Scientific

Published: 2020-06-22

Total Pages: 215

ISBN-13: 9811218978

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Digital transformation continues to create new growth opportunities for businesses and improve the lives of citizens. To help businesses seize these opportunities, the Infocomm Media Development Authority (IMDA) launched the Digital Economy Framework for Action in 2018. This living document aims to enhance Singapore's digital competitiveness and become a global node in Asia.As part of Singapore's push for a Digital Economy, IMDA and the Singapore University of Social Sciences have collaborated to jointly publish the Artificial Intelligence, Data and Blockchain in a Digital Economy, First Edition. This book explains how frontier technologies such as blockchain and artificial intelligence can empower Singapore's digital transformation. It also highlights and provides insights on transformative services and how frontier technology can impact the nation's digitalisation journey.


Artificial Intelligence, Internet of Things, and Society 5.0

Artificial Intelligence, Internet of Things, and Society 5.0

Author: Azzam Hannoon

Publisher: Springer Nature

Published: 2023-11-08

Total Pages: 590

ISBN-13: 3031433009

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This book unlike any other previous book provides a platform for scholars and researchers to present the latest insights and findings on the application of artificial intelligence and other sustainable technologies for a human-centric society. It brings together technology with society with special attention given to AI and IoT-related intricacies for a digital economy. It covers a variety of research topics including block ciphers, network marketing for sustainability entrepreneurship and AI, AI and stock trading decisions, digital transformation, knowledge management, chatbot engineering, cybersecurity, and smart metering system. The book is a comprehensive reference work for scholars, academics, policymakers, students, and professionals presenting an overall understanding of AI, its present and future trends, and presents a discourse on important policies and strategies on inclusivity, diversity, bias, accountability, security, metaverse applications of AI, and other technologies such as IoT.


Artificial Intelligence for Sustainable Finance and Sustainable Technology

Artificial Intelligence for Sustainable Finance and Sustainable Technology

Author: Abdalmuttaleb M. A. Musleh Al-Sartawi

Publisher: Springer Nature

Published: 2022-01-01

Total Pages: 637

ISBN-13: 3030934640

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This book shows latest research on artificial intelligence for sustainable technology. ICGER 2021 was organized by the Accounting, Finance and Banking Department at Ahlia University, Bahrain, and was conducted on the 15th and 16th of September. The strategic partners included the University of Jordan, the Bahrain Economists Society, the Association of Chartered Certified Accountants: ACCA, Al-Barka Banking Group and the International Computer Auditing Education Association: ICAEA . The theme of the ICGER 2021 centered around artificial intelligence for sustainable finance and sustainable technology. Accordingly, the papers presented at the conference provided a holistic view of sustainable finance, sustainability, AI, financial technology, cybersecurity, blockchain, CSR, and governance. This book, unlike ever before, brings together intelligence applications of new technologies and the sustainability requirements in the era of the digital economy, with special attention given to the opportunities, challenges, for education, business growth, and economic progression of nations which will help societies (economists, financial managers, engineers, ICT specialists, digital managers, data managers, policymakers, regulators, researchers, academics, and students) to better understand, use, and control AI applications and financial technologies to develop future strategies and to achieve sustainable development goals.