Socioeconomic development has drawn increasing attention in academia, industries, and governments. The relationship between big data and its technologies and socioeconomic development has drawn certain attention in academia. Socioeconomic development depends not only on big data, but also on big data technologies. However, the relationship between big data and socioeconomic development is not adequately covered in current research. Driving Socioeconomic Development With Big Data: Theories, Technologies, and Applications provides an original and innovative understanding of and insight into how the proposed theories, technologies, and methodologies of big data can improve socioeconomic development and sustainable development in terms of business and services, healthcare, the internet of everything, sharing economy, and more. Covering topics such as corporate social responsibility, management applications, and process mining, this premier reference source is an excellent resource for data scientists, business leaders and executives, IT professionals, government officials, economists, sociologists, librarians, students, researchers, and academicians.

Many fundamental technological and managerial issues surrounding the development and implementation of intelligent analytics within multi-industry applications remain unsolved. There are still questions surrounding the foundation of intelligent analytics, the elements, the big characteristics, and the effects on business, management, technology, and society. Research is devoted to answering these questions and understanding how intelligent analytics can improve healthcare, mobile commerce, web services, cloud services, blockchain, 5G development, digital transformation, and more. Intelligent Analytics With Advanced Multi-Industry Applications is a critical reference source that explores cutting-edge theories, technologies, and methodologies of intelligent analytics with multi-industry applications and emphasizes the integration of artificial intelligence, business intelligence, big data, and analytics from a perspective of computing, service, and management. This book also provides real-world applications of the proposed concept of intelligent analytics to e-SMACS (electronic, social, mobile, analytics, cloud, and service) commerce and services, healthcare, the internet of things, the sharing economy, cloud computing, blockchain, and Industry 4.0. This book is ideal for scientists, engineers, educators, university students, service and management professionals, policymakers, decision makers, practitioners, stakeholders, researchers, and others who have an interest in how intelligent analytics are being implemented and utilized in diverse industries.

In the current technological world, Web services play an integral role in service computing and social networking services. This is also the case in the traditional FREG (foods, resources, energy, and goods) services because almost all traditional services are replaced fully or partially by Web services. Handbook of Research on Demand-Driven Web Services: Theory, Technologies, and Applications presents comprehensive and in-depth studies that reveal the cutting-edge theories, technologies, methodologies, and applications of demand-driven Web, mobile, and e-business services. This book provides critical perspectives for researchers and practitioners, lecturers and undergraduate/graduate students, and professionals in the fields of computing, business, service, management, and government, as well as a variety of readers from all the social strata.

Intelligent business analytics is an emerging technology that has become a mainstream market adopted broadly across industries, organizations, and geographic regions. Intelligent business analytics is a current focus for research and development across academia and industries and must be examined and considered thoroughly so businesses can apply the technology appropriately. The Handbook of Research on Foundations and Applications of Intelligent Business Analytics examines the technologies and applications of intelligent business analytics and discusses the foundations of intelligent analytics such as intelligent mining, intelligent statistical modeling, and machine learning. Covering topics such as augmented analytics and artificial intelligence systems, this major reference work is ideal for scholars, engineers, professors, practitioners, researchers, industry professionals, academicians, and students.

E-commerce has passed through a number of stages in the minds of most readers of the daily press. Initially it was the province of the specialist and considered almost irrelevant to the needs and activities of everyday life - companies looking for venture capital in this area had little if any chance of obtaining sufficient funds from the rather conservative investors who provided the only source of start-up capital. Then came the dot. com boom -and suddenly e-commerce was the most exciting topic possible Venture capital was available from every possible source and almost any company with a . com in its name could be assured of instant funding on request. This boom was, inevitably, followed by the dot. com bust and the press wamed that the days of e-commerce were gone, perhaps never to return. This apparently confusing 'stages of growth' model is in reality nothing ofthe sort. E-commerce is simply the logical outcome of combining computers with tele communications networks. The astonishing changes which a global economy has brought with it are reflected in the changes to the way we do business which are increasingly synonymous with e-commerce. Indeed, the term e-commerce itself is coming to mean only the transaction-based component of e-business-'any process that a business organisation conducts over a computer-mediated network' as Thomas Mesenbourg ofthe U. S. Census Bureau said in 1999."

Big data, analytics, and artificial intelligence are revolutionizing work, management, and lifestyles and are becoming disruptive technologies for healthcare, e-commerce, and web services. However, many fundamental, technological, and managerial issues for developing and applying intelligent big data analytics in these fields have yet to be addressed. Managerial Perspectives on Intelligent Big Data Analytics is a collection of innovative research that discusses the integration and application of artificial intelligence, business intelligence, digital transformation, and intelligent big data analytics from a perspective of computing, service, and management. While highlighting topics including e-commerce, machine learning, and fuzzy logic, this book is ideally designed for students, government officials, data scientists, managers, consultants, analysts, IT specialists, academicians, researchers, and industry professionals in fields that include big data, artificial intelligence, computing, and commerce.

E-commerce has passed through a number of stages in the minds of most readers of the daily press. Initially it was the province of the specialist and considered almost irrelevant to the needs and activities of everyday life - companies looking for venture capital in this area had little if any chance of obtaining sufficient funds from the rather conservative investors who provided the only source of start-up capital. Then came the dot. com boom -and suddenly e-commerce was the most exciting topic possible Venture capital was available from every possible source and almost any company with a . com in its name could be assured of instant funding on request. This boom was, inevitably, followed by the dot. com bust and the press wamed that the days of e-commerce were gone, perhaps never to return. This apparently confusing 'stages of growth' model is in reality nothing ofthe sort. E-commerce is simply the logical outcome of combining computers with tele communications networks. The astonishing changes which a global economy has brought with it are reflected in the changes to the way we do business which are increasingly synonymous with e-commerce. Indeed, the term e-commerce itself is coming to mean only the transaction-based component of e-business-'any process that a business organisation conducts over a computer-mediated network' as Thomas Mesenbourg ofthe U. S. Census Bureau said in 1999."

Many fundamental technological and managerial issues surrounding the development and implementation of intelligent analytics within multi-industry applications remain unsolved. There are still questions surrounding the foundation of intelligent analytics, the elements, the big characteristics, and the effects on business, management, technology, and society. Research is devoted to answering these questions and understanding how intelligent analytics can improve healthcare, mobile commerce, web services, cloud services, blockchain, 5G development, digital transformation, and more. Intelligent Analytics With Advanced Multi-Industry Applications is a critical reference source that explores cutting-edge theories, technologies, and methodologies of intelligent analytics with multi-industry applications and emphasizes the integration of artificial intelligence, business intelligence, big data, and analytics from a perspective of computing, service, and management. This book also provides real-world applications of the proposed concept of intelligent analytics to e-SMACS (electronic, social, mobile, analytics, cloud, and service) commerce and services, healthcare, the internet of things, the sharing economy, cloud computing, blockchain, and Industry 4.0. This book is ideal for scientists, engineers, educators, university students, service and management professionals, policymakers, decision makers, practitioners, stakeholders, researchers, and others who have an interest in how intelligent analytics are being implemented and utilized in diverse industries.

Big data, analytics, and artificial intelligence are revolutionizing work, management, and lifestyles and are becoming disruptive technologies for healthcare, e-commerce, and web services. However, many fundamental, technological, and managerial issues for developing and applying intelligent big data analytics in these fields have yet to be addressed. Managerial Perspectives on Intelligent Big Data Analytics is a collection of innovative research that discusses the integration and application of artificial intelligence, business intelligence, digital transformation, and intelligent big data analytics from a perspective of computing, service, and management. While highlighting topics including e-commerce, machine learning, and fuzzy logic, this book is ideally designed for students, government officials, data scientists, managers, consultants, analysts, IT specialists, academicians, researchers, and industry professionals in fields that include big data, artificial intelligence, computing, and commerce.