Knowledge Management Innovation And Big Data

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.

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

This book addresses the usefulness of knowledge discovery through data mining. With this aim, contributors from different fields propose concrete problems and applications showing how data mining and discovering embedded knowledge from raw data can be beneficial to social organizations, domestic spheres, and ICT markets. Data mining or knowledge discovery in databases (KDD) has received increasing interest due to its focus on transforming large amounts of data into novel, valid, useful, and structured knowledge by detecting concealed patterns and relationships. The concept of knowledge is broad and speculative and has promoted epistemological debates in western philosophies. The intensified interest in knowledge management and data mining stems from the difficulty in identifying computational models able to approximate human behaviors and abilities in resolving organizational, social, and physical problems. Current ICT interfaces are not yet adequately advanced to support and simulate the abilities of physicians, teachers, assistants or housekeepers in domestic spheres. And unlike in industrial contexts where abilities are routinely applied, the domestic world is continuously changing and unpredictable. There are challenging questions in this field: Can knowledge locked in conventions, rules of conduct, common sense, ethics, emotions, laws, cultures, and experiences be mined from data? Is it acceptable for automatic systems displaying emotional behaviors to govern complex interactions based solely on the mining of large volumes of data? Discussing multidisciplinary themes, the book proposes computational models able to approximate, to a certain degree, human behaviors and abilities in resolving organizational, social, and physical problems. The innovations presented are of primary importance for: a. The academic research community b. The ICT market c. Ph.D. students and early stage researchers d. Schools, hospitals, rehabilitation and assisted-living centers e. Representatives from multimedia industries and standardization bodies

In today’s world of business, gaining an advantage of competitors is a focal point for organizations and a driving force in the economy. New practices are being studied and implemented constantly by rivaling companies. Many industries have begun putting emphasis on intensive knowledge practices, with the belief that implementing cutting-edge learning practices will fuel research and innovation within the company. Understanding this dynamic method of management is critical for managers and executives who wish to propel the success of their organizations. Knowledge Management, Innovation, and Entrepreneurship in a Changing World is a collection of pioneering research on the methods of gaining organizational advantages based on knowledge innovation and management. While highlighting topics including human-robot teaming, organizational learning, and e-collaboration, this book will explore the sustainable links between knowledge management influences and organizational capability. This book is ideally designed for managers, strategists, economists, policymakers, entrepreneurs, business professionals, researchers, students, and academics seeking research on recent trends in innovative economics and business technologies.

The proceedings from the eighth KMO conference represent the findings of this international meeting which brought together researchers and developers from industry and the academic world to report on the latest scientific and technical advances on knowledge management in organizations. This conference provided an international forum for authors to present and discuss research focused on the role of knowledge management for innovative services in industries, to shed light on recent advances in social and big data computing for KM as well as to identify future directions for researching the role of knowledge management in service innovation and how cloud computing can be used to address many of the issues currently facing KM in academia and industrial sectors.

Adhering to the combination of theoretical introduction and practical case introduction, this book summarizes the basic concepts and methods in management and big data analysis at home and abroad and introduces a large number of relevant practical cases, especially new cases in the Internet era, to help readers integrate theoretical knowledge into practical applications. The chapters of this book are interrelated and independent of each other, making it easy for the reader to study in pieces or to delve deeper into a particular topic of interest. Covering an array of theories about management and big data at home and abroad, this book lays a solid foundation for being an authentic manager. It is organized into sections on decision-making, organization, leadership, control, innovation, and big data to fully dissect and summarize the basic concepts of these characters in management and to show the basic methods that managers can use to solve problems. Each section contains a large number of examples to demonstrate how entrepreneurs successfully manage their large companies and overcome the difficulties in the business, utilizing the corresponding management functions or big data technology. Further, in order to adapt to the development of the Internet era, this book also absorbs a lot of practice cases of management innovation and big data which have emerged in recent years based on advanced network platform and big data analysis. This book puts great emphasis on the innovative function of management, adding more comprehensive methods and more updated cases related to the Internet.

To navigate the complex ecosystem of societal challenges, the International Conference on Knowledge Management Conference (ICKM 2017) focused on big data and data analytics as part of the relationship to the wider concept of knowledge management processes and practices. This book includes top papers presenting the major, and diverse, topics discussed at the conference. The papers covered various aspects of big data ranging from enhancing access to the big data to facilitating its wide applications in healthcare, social media, library and information centers, governments, and corporations.

No matter the industry, the development of information technologies has transformed how information is distributed and used to predict trends. Collecting and identifying the most vital information, however, requires constant management and manipulation. Current Issues and Trends in Knowledge Management, Discovery, and Transfer is an essential reference source that discusses crucial practices for collaborating and distributing work as well as validating accrued knowledge from real-time data. Featuring research on topics such as dynamic knowledge, management systems, and sharing behavior, this book is ideally designed for academics, researchers, librarians, managing professionals, and students seeking coverage on knowledge acquisition and implementation across systems.