Sustaining a competitive edge in today’s business world requires innovative approaches to product, service, and management systems design and performance. Advances in computing technologies have presented managers with additional challenges as well as further opportunities to enhance their business models. Advances in Data Communications and Networking for Digital Business Transformation is a critical scholarly resource that examines transformative technologies from the perspective of data communication and networking and research challenges faced by the industry and research and development laboratories. Featuring coverage on a broad range of topics such as routing protocols, network visualization, and corporate social responsibility, this book is geared towards executives, managers, academicians, researchers, and students.

In today’s world of global change, it has never been more critical for businesses to adapt their strategies, management styles, and policies to match that of the surrounding environment. Consumers are increasingly becoming more aware of the impact that businesses and product consumption have on environmental health. Thus, businesses have had to alter their production workflows to better suit a more environmentally conscious customer base. As society faces numerous issues related to the environment, health, poverty, and social justice, the need for socially responsible businesses is crucial to develop and improve the overall landscape of the business field. The Research Anthology on Developing Socially Responsible Businesses discusses the best practices, challenges, opportunities, and benefits of creating socially responsible businesses and provides a context of why these business models are needed. This essential text also considers how society has changed over time and how businesses must adjust their ideals and practices in order to survive in a changing world. Covering a range of topics such as accountability, environmental issues, and human rights, this major reference work is ideal for business owners, managers, policymakers, academicians, researchers, scholars, practitioners, instructors, and students.

The key parameter that needs to be considered when planning the management of resources in futuristic wireless networks is a balanced approach to resource distribution. A balanced approach is necessary to provide an unbiased working environment for the distribution, sharing, allocation, and supply of resources among the devices of the wireless network. Equal resource distribution also maintains balance and stability between the operations of communication systems and thus improves the performance of wireless networks. Managing Resources for Futuristic Wireless Networks is a pivotal reference source that presents research related to the control and management of key parameters of bandwidth, spectrum sensing, channel selection, resource sharing, and task scheduling, which is necessary to ensure the efficient operation of wireless networks. Featuring topics that include vehicular ad-hoc networks, resource management, and the internet of things, this publication is ideal for professionals and researchers working in the field of networking, information and knowledge management, and communication sciences. Moreover, the book will provide insights and support executives concerned with the management of expertise, knowledge, information, and organizational development in different types of work communities and environments.

It is now more important than ever to implement approaches and methods that can be effective in extracting meaningful information from large data sets. Although data sets may be available for different aspects of society, we may not assess the intrinsic characteristics of their behavior effectively. Additionally, frameworks are needed that can store, process, and represent the data in such a manner that can be of practical significance. Interdisciplinary Approaches to Information Systems and Software Engineering is an essential reference publication that assesses the significance of robust information systems in characterizing events of varying nature and dimensions. Additionally, the book includes studies on the development and application of decision-making and prediction modeling frameworks using different approaches such as agent-based modeling, spatial decision support systems, and spatial data mining. Covering topics such as management information systems, knowledge discovery, and mathematical analysis, this book is ideal for professionals, researchers, and academicians in various disciplines including computer science, information technology, geographical information systems, remote sensing, and earth system sciences.

The increase in connected devices in the internet of things (IoT) is leading to an exponential increase in the data that an organization is required to manage. To successfully utilize IoT in businesses, big data analytics are necessary in order to efficiently sort through the increased data. The combination of big data and IoT can thus enable new monitoring services and powerful processing of sensory data streams. The Handbook of Research on Big Data and the IoT is a pivotal reference source that provides vital research on emerging trends and recent innovative applications of big data and IoT, challenges facing organizations and the implications of these technologies on society, and best practices for their implementation. While highlighting topics such as bootstrapping, data fusion, and graph mining, this publication is ideally designed for IT specialists, managers, policymakers, analysts, software engineers, academicians, and researchers.

Various technologies and applications such as cognitive computing, artificial intelligence, and learning analytics have received increased attention in recent years. The growing demand behind their adoption and exploitation in different application contexts has captured the attention of learning technology specialists, computer engineers, and business researchers who are attempting to decipher the phenomenon of personalized e-learning, its relation to already conducted research, and its implications for new research opportunities that effect innovations in teaching. Cognitive Computing in Technology-Enhanced Learning is a critical resource publication that aims to demonstrate state-of-the-art approaches of advanced data mining systems in e-learning, such as MOOCs and other innovative technologies, to improve learning analytics, as well as to show how new and advanced user interaction designs, educational models, and adoptive strategies can expand sustainability in applied learning technologies. Highlighting a range of topics such as augmented reality, ethics, and online learning environments, this book is ideal for educators, instructional designers, higher education faculty, school administrators, academicians, researchers, and students.