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 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.
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.
With the COVID-19 pandemic, we have seen universities worldwide having to 'pivot' quickly to transform their education delivery to an online environment, as well as having to conduct their business operations virtually/remotely. For those universities who embraced digital transformation, they were able to adapt quickly to this new learning environment. Many others were not as successful. Part of the formula for success is for universities and other higher education institutions apply digital transformation technologies, processes, and leadership in this 'new normal'. This book will highlight what is needed in terms of digital transformation for the universities of the future in terms of technologies, processes, culture, and leadership considerations.The book will be part of the new World Scientific book series, Digital Transformation: Accelerating Organizational Intelligence.Related Link(s)
The world is witnessing the growth of a global movement facilitated by technology and social media. Fueled by information, this movement contains enormous potential to create more accountable, efficient, responsive, and effective governments and businesses, as well as spurring economic growth. Big Data Governance and Perspectives in Knowledge Management is a collection of innovative research on the methods and applications of applying robust processes around data, and aligning organizations and skillsets around those processes. Highlighting a range of topics including data analytics, prediction analysis, and software development, this book is ideally designed for academicians, researchers, information science professionals, software developers, computer engineers, graduate-level computer science students, policymakers, and managers seeking current research on the convergence of big data and information governance as two major trends in information management.
This innovative Research Agenda critically reflects on the state of the art and offers inspiration for future higher education research across a variety of geographical, disciplinary and theoretical perspectives. It explores the impact of Covid-19, and the need to re-engage with the Global South and reconsider conventional paradigms and assumptions. Leading international contributors address a set of salient issues, ranging from research on macro-level themes to meso and micro-level phenomena.
This book develops and examines the concepts and strategies for rural empowerment through the formation of a community-driven social knowledge management (SKM) framework aided by social technology. The framework is aimed at mobilizing knowledge resources to bridge the rural–urban knowledge divide while securing rural empowerment using digital connections and social collaborations built on strategies of self-sustenance and self-development. With key empirical findings supplemented by relevant theoretical structures, case studies, illustrative figures and a lucid style, the book combines social technologies and social development to derive a social knowledge management platform. It shows how the proposed SKM framework can enhance knowledge capabilities of rural actors by facilitating connection among rural–urban entities through formation of purposive virtual communities, which allow social agents to create, modify and share content collaboratively. The volume brings forward diverse issues such as conceptual foundations; bridging the rural–urban knowledge and information divide; issues of information and knowledge asymmetry; a knowledge-theoretic perspective of rural empowerment; knowledge capability, freedom of choice and wellbeing, to provide a comprehensive outlook on building a knowledge society through digital empowerment. This book will be useful to scholars and researchers of development studies, rural sociology, management studies, IT/IS, knowledge management and ICT for development, public policy, sociology, political economy and development economics. It will benefit professionals and policymakers, government and nongovernment bodies and international agencies involved with policy decisions related to application of technologies for rural development, social workers and those in the development sector.
The evolution of knowledge management theory and the special emphasis on human and social capital sets new challenges for knowledge-driven and technology-enabled innovation. Emerging technologies including big data and analytics have significant implications for sustainability, policy making, and competitiveness. This edited volume promotes scientific research into the potential contributions knowledge management can make to the new era of innovation and social inclusive economic growth. We are grateful to all the contributors of this edition for their intellectual work. The organization of the relevant debate is aligned around three pillars: SECTION A. DATA, KNOWLEDGE, HUMAN AND SOCIAL CAPITAL FOR INNOVATION We elaborate on the new era of knowledge types and the emerging forms of social capital and their impact on technology-driven innovation. Topics include: · Social Networks · Smart Education · Social Capital · Corporate Innovation · Disruptive Innovation · Knowledge integration · Enhanced Decision-Making. SECTION B. KNOWLEDGE MANAGEMENT & BIG DATA ENABLED INNOVATION In this section, knowledge management and big data applications and systems are presented. Selective topic include: · Crowdsourcing Analysis · Natural Language Processing · Data Governance · Knowledge Extraction · Ontology Design Semantic Modeling SECTION C. SUSTAINABLE DEVELOPMENT In the section, the debate on the impact of knowledge management and big data research to sustainability is promoted with integrative discussion of complementary social and technological factors including: · Big Social Networks on Sustainable Economic Development · Business Intelligence
