This book constitutes revised selected papers from the 19th Workshop on e-Business, WeB 2020, which took place virtually on December 12, 2020. The purpose of WeB is to provide a forum for researchers and practitioners to discuss findings, novel ideas, and lessons learned to address major challenges and map out the future directions for e-Business. The WeB 2020 theme was “The Role of e-Business during the Time of Grand Challenges.” The 12 papers included in this volume were carefully reviewed and selected from a total of 24 submissions. The contributions are organized in topical sections as follows: Cybersecurity and COVID-19 challenges; digital platforms; and managing human factors in e-business.

This book is based on a selection of thoroughly revised and extended best papers from the 8th Workshop on E-Business (WEB 2009) held in Phoenix, AZ, USA, on December 15th, 2009. The 29 papers, which were selected from 70 presentations at the workshop, highlight the enormous developments and potential of e-business at a time when new technologies like cloud computing, collective intelligence, and multi-sided platforms are burgeoning. Among the topics covered are Web-based information systems, RFID and supply chain management, process modeling and standardization, security and privacy issues, social networking and mobility, e-services and market mechanisms, IT portfolio management, and other special topics in e-business such as electronic invoicing.

This book constitutes revised selected papers from the 20th Workshop on e-Business, WeB 2021, which took place virtually on December 11, 2021. The purpose of WeB is to provide a forum for researchers and practitioners to discuss findings, novel ideas, and lessons learned to address major challenges and map out the future directions for e-Business. The WeB 2021 theme was “From Grand Challenges to Great Solutions: Digital Transformation in the Age of COVID-19.” The 8 papers included in this volume were carefully reviewed and selected from a total of 24 submissions. The contributions are organized in topical sections as follows: digital innovation and transformation, and e-commerce and social media.

This essential Research Handbook provides an in-depth analysis of the link between corporate governance and ethics. By bringing together internationally renowned scholars, it reflects upon pertinent trends and challenges within the field. Significantly, it illuminates the ethical foundations of corporate governance.

This book reports on the proceedings at the STELLAR Alpine Rendez-Vous 2013, presenting strategies in handling challenges that arise when using technology-enhanced learning (TEL). With insightful contributions from leading teachers, practitioners, researchers and policy makers, this volume will inspire everyone interested in TEL in their future projects. This book continues the influential work of the STELLAR network which was funded by the European Commission to structure the research area of technology-enhanced learning and continues to the work on the previously developed research vision. It has potential to become influential in Europe, North America and Asia.

This book presents a key piece of the vision and strategy developed in STELLAR. It sets out a new mid-term agenda by defining Grand Challenges for research and development in technology-enhanced learning. Other than mere technology prizes, STELLAR Grand Challenges deal with problems at the interface of social and technical sciences. They pose problems that can be solved only in interdisciplinary collaboration. The descriptions of the Grand Challenge Problems were sent out to a number of stakeholders from industry, academia, and policy-making who responded with insightful, creative and critical comments bringing in their specific perspectives. This book will inspire everyone interested in TEL and its neighboring disciplines in their future projects. All of the listed problems, first hints with respect to the approach, measurable success indicators and funding sources are outlined. The challenges focus on what noted experts regard as important upcoming, pending, and innovative fields of research, the solution of which is within reach in a timeframe of a mere 2 to 15 years of work.

This book offers a selection of the best papers presented at the annual international scientific conference “Digital Transformation in Industry: Trends, Management, Strategies,” which was held by the Institute of Economics of the Ural Branch of the Russian Academy of Sciences (Ekaterinburg, Russia) on October 28, 2022. The book focuses on concepts for initiating digitalization processes and identifying successful digital transformation strategies in all sectors of industry. Key topics include the sustainability of digital transformation in uncertain dynamics; conditions of uncertainty and barriers; industrial logistics in the new reality; best practices for implementing digital solutions to ensure sustainable, barrier-free and flexible supply chains; the achievement of sustainability in the process of digital transition; the adaptation of enterprises to the ESG concept through digital solutions; assessing the impact of industrial digital transformation on society and the environment; and clarifying how ESG aspects affect the economy. The experiences of various countries, regions and types of enterprise implementing IT and other technological innovations are also included, making the book a valuable asset for researchers and managers alike.

Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and methods for mining patterns, knowledge, and models from various kinds of data for diverse applications. Specifically, it delves into the processes for uncovering patterns and knowledge from massive collections of data, known as knowledge discovery from data, or KDD. It focuses on the feasibility, usefulness, effectiveness, and scalability of data mining techniques for large data sets. After an introduction to the concept of data mining, the authors explain the methods for preprocessing, characterizing, and warehousing data. They then partition the data mining methods into several major tasks, introducing concepts and methods for mining frequent patterns, associations, and correlations for large data sets; data classificcation and model construction; cluster analysis; and outlier detection. Concepts and methods for deep learning are systematically introduced as one chapter. Finally, the book covers the trends, applications, and research frontiers in data mining. - Presents a comprehensive new chapter on deep learning, including improving training of deep learning models, convolutional neural networks, recurrent neural networks, and graph neural networks - Addresses advanced topics in one dedicated chapter: data mining trends and research frontiers, including mining rich data types (text, spatiotemporal data, and graph/networks), data mining applications (such as sentiment analysis, truth discovery, and information propagattion), data mining methodologie and systems, and data mining and society - Provides a comprehensive, practical look at the concepts and techniques needed to get the most out of your data - Visit the author-hosted companion site, https://hanj.cs.illinois.edu/bk4/ for downloadable lecture slides and errata