Leveraging the knowledge gained from Knowledge Management and from the growing fields of Analytics and Artificial Intelligence (AI), this Research Agenda highlights the research gaps, issues, applications, challenges and opportunities related to Knowledge Management (KM). Exploring synergies between KM and emerging technologies, leading international scholars and practitioners examine KM from a multidisciplinary perspective, demonstrating the ways in which knowledge sharing worldwide can be enhanced in order to better society and improve organisational performance.

This book constitutes the refereed proceedings of the 17th International Conference on Knowledge Management in Organisations, KMO 2023, held in Bangkok, Thailand, during July 24–27, 2023. The 32 full papers included in this book were carefully reviewed and selected from 73 submissions. They were organized in topical sections as follows: Knowledge Transfer & Sharing, Knowledge in Business & Organisation, Digital Transformation and Innovation, Data Analysis and Science, KM and Education, Knowledge Management Process and Model, Information & Knowledge Systems, IT &New Trends in KM, Healthcare.

This edited volume explores the challenges and opportunities of knowledge management (KM) in the post-pandemic world. Intangibles have become dominant resources, and their effective management is key to navigating the complexity of the new business environment. The book is divided into three parts, each focusing on a different aspect of KM: complexity, human factors, and technology. Through 15 chapters by 28 contributors from 18 countries, this collection offers a diverse range of perspectives on the evolution of KM over the past decade and its potential for the future. The contributors analyze topics such as digital transformation, distant reading, knowledge visualization, and advanced KM systems. This volume will be of interest to researchers and practitioners in the field of KM, as well as to anyone interested in the challenges and opportunities facing organizations in the post-pandemic world. This edited volume celebrates the 10th anniversary of the International Association for Knowledge Management, offering an overview of the field's achievements and prospects for innovation and sustainability.

This thoroughly revised fourth edition of the leading knowledge management (KM) textbook offers a comprehensive and accessible overview of the theory and practice of KM. Today’s knowledge-driven economy raises the stakes for organizations and individuals whose success depends on the effective management of information and knowledge. Knowledge is an asset that is not always easily tapped, especially when embedded in products and in the tacit understanding of highly mobile individual employees. Knowledge management (KM) represents a deliberate and systematic approach to cultivating and sharing an organization's knowledge base. This thoroughly revised new edition of the leading knowledge management textbook offers a comprehensive and accessible overview of the theory and practice of KM. Drawing on ideas, tools, and techniques from such disciplines as sociology, cognitive science, organizational behavior, and information science, it serves as an invaluable resource for students and researchers across information sciences, business, education, and communication. Global in scope and updated to reflect the maturing field, this fourth edition emphasizes optimizing KM and measuring its success and impact in meaningful ways. Fourth edition highlights: Comprehensively updated to integrate the latest theories, practices, and technologies in KM Discusses not only how to implement but how to sustain successful KM strategies and systems in the long term Includes new coverage of KM governance and the KM ISO standard introduced in 2018 Features detailed, real-world vignettes and a wealth of instructor resources, including slides and solutions

This innovative Research Agenda uncovers links between different levels of border-making processes, or bordering, from the political to the cognitive, and connects everyday processes and experiences of border-making to the wider social world. It addresses the question of how everyday bordering practices and discourses can be productively linked to different aspects of social relations.

This timely Research Agenda moves beyond classic approaches that consider the relationship between heritage and tourism either as problematic or as a factor for local development, and instead adopts an understanding of heritage and tourism as two reciprocally supported social phenomena that are co-produced.

We have witnessed the growing worldwide trends in moving from digitization to digitalization to digital transformation. In order to survive in today's environment, organizations must embrace digital transformation. In fact, digital transformation transcends all elements of society, whether agriculture, home, business, transportation, and the like. This book focuses on digital transformation and its impact upon society.

The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics technique. Analytics and Knowledge Management examines the role of analytics in knowledge management and the integration of big data theories, methods, and techniques into an organizational knowledge management framework. Its chapters written by researchers and professionals provide insight into theories, models, techniques, and applications with case studies examining the use of analytics in organizations. The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics techniques. Analytics, on the other hand, is the examination, interpretation, and discovery of meaningful patterns, trends, and knowledge from data and textual information. It provides the basis for knowledge discovery and completes the cycle in which knowledge management and knowledge utilization happen. Organizations should develop knowledge focuses on data quality, application domain, selecting analytics techniques, and on how to take actions based on patterns and insights derived from analytics. Case studies in the book explore how to perform analytics on social networking and user-based data to develop knowledge. One case explores analyze data from Twitter feeds. Another examines the analysis of data obtained through user feedback. One chapter introduces the definitions and processes of social media analytics from different perspectives as well as focuses on techniques and tools used for social media analytics. Data visualization has a critical role in the advancement of modern data analytics, particularly in the field of business intelligence and analytics. It can guide managers in understanding market trends and customer purchasing patterns over time. The book illustrates various data visualization tools that can support answering different types of business questions to improve profits and customer relationships. This insightful reference concludes with a chapter on the critical issue of cybersecurity. It examines the process of collecting and organizing data as well as reviewing various tools for text analysis and data analytics and discusses dealing with collections of large datasets and a great deal of diverse data types from legacy system to social networks platforms.

Regulating Hate Speech Created by Generative AI explores the new hybrid space of Human Machine Interaction (HMI) in which hate speech is represented and computed through algorithms and AI generative systems. The book is exploratory because there are still many problem-solving challenges to be faced. It is also innovative because it is not assuming that solutions lie only in technological advancements but on a broader scale. In this sense, large language models can and are being considered from a holistic view (i.e., from the different dimensions and layers of regulatory and legal governance). Highlights of the book include: Generative AI and social engines of hate An introduction to generative Artificial Intelligence application, trends, and ethics The mechanics and validation of generative AI outcomes An evaluation of Generative AI for hate speech detection Best practices and key considerations for AI regulation Using GenAI capabilities for early detection of threats in the digital environment. This book is a hard look at ways to regulate generative AI to reduce online hate and secure justice in a digital environment. Featuring research and offering practical guidelines, the book examines guidelines for regulating generative AI models, so they do not contribute to online hate disinformation and imagery.