The internet represents a rapidly evolving set of technologies which is central to the development of a modern economy. Internet Economics: Models, Mechanisms and Management integrates knowledge about internet service design with economic modelling principles (pricing, cost and service models). Chapters highlight specific applications of the internet such as service provisioning, cloud computing, commerce, business security, network externalities, social media and more recent developments such as the Internet of Things (IoT), the industrial internet, data analytics and the use of big data to bring value to commercial ventures. Therefore, readers will have a conceptual and practical framework for understanding the economics of internet infrastructure and service delivery.

This monograph focuses on exploring game theoretic modeling and mechanism design for problem solving in Internet and network economics. For the first time, the main theoretical issues and applications of mechanism design are bound together in a single text.

Explores the impact of the internet on the future directions of the 'New Economy'.

In the digital age, consumers have morphed from passive receivers of marketing messages to active suppliers of information about product through various digital media, creating a need for businesses to effectively manage a more diverse and creative range of consumers. Managing Diversity, Innovation, and Infrastructure in Digital Business is a collection of innovative research on new avenues in overall digital infrastructures, digital modern business infrastructures, business automation, and financial aspects of modern businesses. Featuring research on topics such as electronic word-of-mouth strategies, social media marketing, and digital communication, this book is ideally designed for business professionals, managers, and undergraduate and postgraduate business students seeking current research on business in the digital environment.

This book presents the proceedings of the International Conference on Managing Business through Web Analytics (ICMBWA 2021). The conference provides a global forum for sharing knowledge and results in theory, methodology, and applications of Web Analytics and their role in the formulation and the orientation of businesses’ strategies. The aim of the conference is to provide a platform for researchers and practitioners from both academia and industry to meet and share their works in the field. Is an excellent resource for scholars, experts and industrial in the fields represented, as well as Ph.D. students seeking an entryway into current research in data analytics, Web analytics, machine learning algorithms, and their various applications within businesses.

The different facets of the sharing economy offer numerous opportunities for businesses ? particularly those that can be distinguished by their creative ideas and their ability to easily connect buyers and senders of goods and services via digital platforms. At the beginning of the growth of this economy, the advanced digital technologies generated billions of bytes of data that constitute what we call Big Data. This book underlines the facilitating role of Big Data analytics, explaining why and how data analysis algorithms can be integrated operationally, in order to extract value and to improve the practices of the sharing economy. It examines the reasons why these new techniques are necessary for businesses of this economy and proposes a series of useful applications that illustrate the use of data in the sharing ecosystem.

Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians.

The human mind is endowed with a remarkable capacity for creative synthesis between intuition and reason; this mental alchemy is the source of genius. A new synergy is emerging between human ingenuity and the computational capacity of generative AI models. Automated Data Analytics focuses on this fruitful collaboration between the two to unlock the full potential of data analysis. Together, human ethics and algorithmic productivity have created an alloy stronger than the sum of its parts. The future belongs to this symbiosis between heart and mind, human and machine. If we succeed in harmoniously combining our strengths, it will only be a matter of time before we discover new analytical horizons. This book sets out the foundations of this promising partnership, in which everyone makes their contribution to a common work of considerable scope. History is being forged before our very eyes. It is our responsibility to write it wisely, and to collectively pursue the ideal of augmented intelligence progress.

In a resolutely practical and data-driven project universe, the digital age changed the way data is collected, stored, analyzed, visualized and protected, transforming business opportunities and strategies. It is important for today’s organizations and entrepreneurs to implement a robust data strategy and industrialize a set of “data-driven” solutions to utilize big data analytics to its fullest potential. Big Data Analytics for Entrepreneurial Success provides emerging perspectives on the theoretical and practical aspects of data analysis tools and techniques within business applications. Featuring coverage on a broad range of topics such as algorithms, data collection, and machine learning, this publication provides concrete examples and case studies of successful uses of data-driven projects as well as the challenges and opportunities of generating value from data using analytics. It is ideally designed for entrepreneurs, researchers, business owners, managers, graduate students, academicians, software developers, and IT professionals seeking current research on the essential tools and technologies for organizing, analyzing, and benefiting from big data.

The main purpose of this book is to investigate, explore and describe approaches and methods to facilitate data understanding through analytics solutions based on its principles, concepts and applications. But analyzing data is also about involving the use of software. For this, and in order to cover some aspect of data analytics, this book uses software (Excel, SPSS, Python, etc) which can help readers to better understand the analytics process in simple terms and supporting useful methods in its application.