Social entrepreneurship is construed an innovative activity that addresses or mitigates social issues based on self-sufficiency and financial stability. It offers the potential to shift civil society through innovative social ventures that pursue profit and purpose. It is gaining international attention due to the intent of social entrepreneurs to change and to see the world as it can be, not as it is. These changemakers blend lessons from business with the diversity and complexity of social values and in the process pursue opportunities for change. International Perspectives on Value Creation and Sustainability Through Social Entrepreneurship explores various issues and ideas about social entrepreneurship through the lens of theoretical, practical, and empirical research. It provides an international outlook of social entrepreneurship, focusing primarily on value creation and sustainability. Covering topics such as entrepreneurship education, post-COVID perspectives, and private wealth, this premier reference source is an essential resource for entrepreneurs, business leaders, managers, government officials, policymakers, libraries, students and faculty of higher education, researchers, and academicians.

The success of many companies through the assistance of bitcoin proves that technology continually dominates and transforms how economics operate. However, a deeper, more conceptual understanding of how these technologies work to identify innovation opportunities and how to successfully thrive in an increasingly competitive environment is needed for the entrepreneurs of tomorrow. Transforming Businesses With Bitcoin Mining and Blockchain Applications provides innovative insights into IT infrastructure and emerging trends in the realm of digital business technologies. This publication analyzes and extracts information from Bitcoin networks and provides the necessary steps to designing open blockchain. Highlighting topics that include financial markets, risk management, and smart technologies, the research contained within the title is ideal for entrepreneurs, business professionals, managers, executives, academicians, researchers, and business students.

This book discusses ideas for stakeholders to develop strategies to access and use financial products and services such as deposits, loans, and fund transfer mechanism, insurance, payment services, and intermediaries, distribution channels at economical prices in order to cater to the needs of the poor and underprivileged people. Financial inclusion ensures ease of access, availability, and usage of the financial products and services to all the sections of the society. The book will help in recognizing the role of financial inclusion as one of the main drivers in reducing income inequality and thus supporting sustainable economic growth of the countries, especially of an emerging economy. The book provides conceptual and practical ideas from the practitioners, best practices from the experts, and empirical views from the researchers on the best practices and how to mitigate the challenges and issues plaguing the development of the financial inclusion.

Recent advancements in graph neural networks have expanded their capacities and expressive power. Furthermore, practical applications have begun to emerge in a variety of fields including recommendation systems, fake news detection, traffic prediction, molecular structure in chemistry, antibacterial discovery physics simulations, and more. As a result, a boom of research at the juncture of graph theory and deep learning has revolutionized many areas of research. However, while graph neural networks have drawn a lot of attention, they still face many challenges when it comes to applying them to other domains, from a conceptual understanding of methodologies to scalability and interpretability in a real system. Concepts and Techniques of Graph Neural Networks provides a stepwise discussion, an exhaustive literature review, detailed analysis and discussion, rigorous experimentation results, and application-oriented approaches that are demonstrated with respect to applications of graph neural networks. The book also develops the understanding of concepts and techniques of graph neural networks and establishes the familiarity of different real applications in various domains for graph neural networks. Covering key topics such as graph data, social networks, deep learning, and graph clustering, this premier reference source is ideal for industry professionals, researchers, scholars, academicians, practitioners, instructors, and students.

Advanced Field Effect Transistor: Theory and Applications offers a fresh perspective on the design and analysis of advanced FET devices and its applications. The text emphasizes both fundamental and new paradigms that are essential for upcoming advancement in field of transistors beyond the CMOS. This book used lucid, intuitive language to gradually increase the comprehension of readers about the key concepts of field effect transistor, including their theory and applications. In order to improve readers' learning opportunities, “Advanced Field Effect Transistor: Theory and Applications”, presents a wide range of crucial topics: o Design and Challenges in Tunnel FET o Various modelling approach for FET o Study of organic thin-film transistors o Biosensing application of FET o Implementation of Memory/Logic gates with FET Advent of low Semiconductor Devices and Related Implications for Upcoming Technology Nodes provides valuable insight into low-power devices and their applicability in the wireless, biosensing, and circuit aspects. As a result, researchers are constantly looking for new semiconductor devices to meet consumer demand. The book gives more details about all aspects of the low-power technology, including ongoing and prospective circumstances with fundamentals of FET devices as well as sophisticated low-power applications.

In the era of social connectedness, people are becoming increasingly enthusiastic about interacting, sharing, and collaborating through online collaborative media. However, conducting sentiment analysis on these platforms can be challenging, especially for business professionals who are using them to collect vital data. Sentiment Analysis and Knowledge Discovery in Contemporary Business is an essential reference source that discusses applications of sentiment analysis as well as data mining, machine learning algorithms, and big data streams in business environments. Featuring research on topics such as knowledge retrieval and knowledge updating, this book is ideally designed for business managers, academicians, business professionals, researchers, graduate-level students, and technology developers seeking current research on data collection and management to drive profit.

This book discusses ideas for stakeholders to develop strategies to access and use financial products and services such as deposits, loans, and fund transfer mechanism, insurance, payment services, and intermediaries, distribution channels at economical prices in order to cater to the needs of the poor and underprivileged people. Financial inclusion ensures ease of access, availability, and usage of the financial products and services to all the sections of the society. The book will help in recognizing the role of financial inclusion as one of the main drivers in reducing income inequality and thus supporting sustainable economic growth of the countries, especially of an emerging economy. The book provides conceptual and practical ideas from the practitioners, best practices from the experts, and empirical views from the researchers on the best practices and how to mitigate the challenges and issues plaguing the development of the financial inclusion.

Recent advancements in graph neural networks have expanded their capacities and expressive power. Furthermore, practical applications have begun to emerge in a variety of fields including recommendation systems, fake news detection, traffic prediction, molecular structure in chemistry, antibacterial discovery physics simulations, and more. As a result, a boom of research at the juncture of graph theory and deep learning has revolutionized many areas of research. However, while graph neural networks have drawn a lot of attention, they still face many challenges when it comes to applying them to other domains, from a conceptual understanding of methodologies to scalability and interpretability in a real system. Concepts and Techniques of Graph Neural Networks provides a stepwise discussion, an exhaustive literature review, detailed analysis and discussion, rigorous experimentation results, and application-oriented approaches that are demonstrated with respect to applications of graph neural networks. The book also develops the understanding of concepts and techniques of graph neural networks and establishes the familiarity of different real applications in various domains for graph neural networks. Covering key topics such as graph data, social networks, deep learning, and graph clustering, this premier reference source is ideal for industry professionals, researchers, scholars, academicians, practitioners, instructors, and students.

Social entrepreneurship is construed an innovative activity that addresses or mitigates social issues based on self-sufficiency and financial stability. It offers the potential to shift civil society through innovative social ventures that pursue profit and purpose. It is gaining international attention due to the intent of social entrepreneurs to change and to see the world as it can be, not as it is. These changemakers blend lessons from business with the diversity and complexity of social values and in the process pursue opportunities for change. International Perspectives on Value Creation and Sustainability Through Social Entrepreneurship explores various issues and ideas about social entrepreneurship through the lens of theoretical, practical, and empirical research. It provides an international outlook of social entrepreneurship, focusing primarily on value creation and sustainability. Covering topics such as entrepreneurship education, post-COVID perspectives, and private wealth, this premier reference source is an essential resource for entrepreneurs, business leaders, managers, government officials, policymakers, libraries, students and faculty of higher education, researchers, and academicians.

The success of many companies through the assistance of bitcoin proves that technology continually dominates and transforms how economics operate. However, a deeper, more conceptual understanding of how these technologies work to identify innovation opportunities and how to successfully thrive in an increasingly competitive environment is needed for the entrepreneurs of tomorrow. Transforming Businesses With Bitcoin Mining and Blockchain Applications provides innovative insights into IT infrastructure and emerging trends in the realm of digital business technologies. This publication analyzes and extracts information from Bitcoin networks and provides the necessary steps to designing open blockchain. Highlighting topics that include financial markets, risk management, and smart technologies, the research contained within the title is ideal for entrepreneurs, business professionals, managers, executives, academicians, researchers, and business students.

In the era of social connectedness, people are becoming increasingly enthusiastic about interacting, sharing, and collaborating through online collaborative media. However, conducting sentiment analysis on these platforms can be challenging, especially for business professionals who are using them to collect vital data. Sentiment Analysis and Knowledge Discovery in Contemporary Business is an essential reference source that discusses applications of sentiment analysis as well as data mining, machine learning algorithms, and big data streams in business environments. Featuring research on topics such as knowledge retrieval and knowledge updating, this book is ideally designed for business managers, academicians, business professionals, researchers, graduate-level students, and technology developers seeking current research on data collection and management to drive profit.