Knowledge Management Innovation And Big Data
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| Author | : Patricia Ordóñez de Pablos |
| Publisher | : MDPI |
| Total Pages | : 416 |
| Release | : 2019-12-31 |
| Genre | : Social Science |
| ISBN | : 3039280082 |
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
| Author | : Gyamfi, Albert |
| Publisher | : IGI Global |
| Total Pages | : 275 |
| Release | : 2021-06-18 |
| Genre | : Business & Economics |
| ISBN | : 1799867943 |
Knowledge management has always been about the process of creating, sharing, using, and applying knowledge within and between organizations. Before the advent of information systems, knowledge management processes were manual or offline. However, the emergence and eventual evolution of information systems created the possibility for the gradual but slow automation of knowledge management processes. These digital technologies enable data capture, data storage, data mining, data analytics, and data visualization. The value provided by such technologies is enhanced and distributed to organizations as well as customers using the digital technologies that enable interconnectivity. Today, the fine line between the technologies enabling the technology-driven external pressures and data-driven internal organizational pressures is blurred. Therefore, how technologies are combined to facilitate knowledge management processes is becoming less standardized. This results in the question of how the current advancement in digital technologies affects knowledge management processes both within and outside organizations. Digital Technology Advancements in Knowledge Management addresses how various new and emerging digital technologies can support knowledge management processes within organizations or outside organizations. Case studies and practical tips based on research on the emerging possibilities for knowledge management using these technologies is discussed within the chapters of this book. It both builds on the available literature in the field of knowledge management while providing for further research opportunities in this dynamic field. This book highlights topics such as human-robot interaction, big data analytics, software development, keyword extraction, and artificial intelligence and is ideal for technology developers, academics, researchers, managers, practitioners, stakeholders, and students who are interested in the adoption and implementation of new digital technologies for knowledge creation, sharing, aggregation, and storage.
| Author | : Jennex, Murray Eugene |
| Publisher | : IGI Global |
| Total Pages | : 463 |
| Release | : 2020-03-27 |
| Genre | : Business & Economics |
| ISBN | : 1799823571 |
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.
| Author | : Joe Tidd |
| Publisher | : World Scientific |
| Total Pages | : 551 |
| Release | : 2021-05-05 |
| Genre | : Business & Economics |
| ISBN | : 1800610327 |
Knowledge Management focuses on identifying, sharing, storing, and exploiting internal knowledge, whereas Open Innovation is more concerned with sources of external knowledge. However, this simple dichotomy between open and closed approaches is unhelpful and not realistic. Instead, it is the interaction between internal and external knowledge that creates dynamic capabilities and the ability to innovate. In particular, we need to better understand the interactions between internal and external knowledge, and how these influence innovation outcomes under different conditions. This edited volume, Managing Knowledge, Absorptive Capacity, and Innovation, provides an opportunity to combine contemporary interests in Open Innovation with the classic notion of absorptive capacity, to better understand how organisations can manage the absorption and exploitation of inbound external sources of knowledge in order to innovate.
| Author | : Strydom, Moses |
| Publisher | : IGI Global |
| Total Pages | : 427 |
| Release | : 2019-09-27 |
| Genre | : Computers |
| ISBN | : 1522596895 |
Big data and artificial intelligence (AI) are at the forefront of technological advances that represent a potential transformational mega-trend—a new multipolar and innovative disruption. These technologies, and their associated management paradigm, are already rapidly impacting many industries and occupations, but in some sectors, the change is just beginning. Innovating ahead of emerging technologies is the new imperative for any organization that aspires to succeed in the next decade. Faced with the power of this AI movement, it is imperative to understand the dynamics and new codes required by the disruption and to adapt accordingly. AI and Big Data’s Potential for Disruptive Innovation provides emerging research exploring the theoretical and practical aspects of successfully implementing new and innovative technologies in a variety of sectors including business, transportation, and healthcare. Featuring coverage on a broad range of topics such as semantic mapping, ethics in AI, and big data governance, this book is ideally designed for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research on the production of new and innovative mechanization and its disruptions.
| Author | : Babu George |
| Publisher | : Springer Nature |
| Total Pages | : 306 |
| Release | : 2019-10-04 |
| Genre | : Business & Economics |
| ISBN | : 3030082776 |
The digital traces that people leave behind as they conduct their daily lives provide a powerful resource for businesses to better understand the dynamics of an otherwise chaotic society. Digital technologies have become omnipresent in our lives and we still do not fully know how to make the best use of the data these technologies could harness. Businesses leveraging big data appropriately could definitely gain a sustainable competitive advantage. With a balanced mix of texts and cases, this book discusses a variety of digital technologies and how they transform people and organizations. It offers a debate on the societal consequences of the yet unfolding technological revolution and proposes alternatives for harnessing disruptive technologies for the greater benefit of all. This book will have wide appeal to academics in technology management, strategy, marketing, and human resource management.
| Author | : Jin Chen |
| Publisher | : Routledge |
| Total Pages | : 459 |
| Release | : 2022-05-22 |
| Genre | : Business & Economics |
| ISBN | : 1000585662 |
Knowledge when properly leveraged and harnessed contributes to effective organizational performance. How much an organization benefits from knowledge would depend on how well knowledge has been managed. There have been challenges to implementing knowledge management in today’s dramatically different world from before. This comprehensive reference work is a timely guide to understanding knowledge management. The book covers key themes of knowledge management which includes the basic framework of knowledge management and helps readers to understand the state of art of knowledge management both from the aspects of theory and practice, from the perspectives of strategy, organization, resources, as well as institution and organizational culture. This reference work reflects the increasingly important role of both philosophy and digital technologies in knowledge management research and practice. This handbook will be an essential resource for knowledge management scholars, researchers and graduate students.
| Author | : Valentina Janev |
| Publisher | : Springer Nature |
| Total Pages | : 212 |
| Release | : 2020-07-15 |
| Genre | : Computers |
| ISBN | : 3030531996 |
This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.
| Author | : Bernard Marr |
| Publisher | : John Wiley & Sons |
| Total Pages | : 256 |
| Release | : 2015-01-09 |
| Genre | : Business & Economics |
| ISBN | : 1118965787 |
Convert the promise of big data into real world results There is so much buzz around big data. We all need to know what it is and how it works - that much is obvious. But is a basic understanding of the theory enough to hold your own in strategy meetings? Probably. But what will set you apart from the rest is actually knowing how to USE big data to get solid, real-world business results - and putting that in place to improve performance. Big Data will give you a clear understanding, blueprint, and step-by-step approach to building your own big data strategy. This is a well-needed practical introduction to actually putting the topic into practice. Illustrated with numerous real-world examples from a cross section of companies and organisations, Big Data will take you through the five steps of the SMART model: Start with Strategy, Measure Metrics and Data, Apply Analytics, Report Results, Transform. Discusses how companies need to clearly define what it is they need to know Outlines how companies can collect relevant data and measure the metrics that will help them answer their most important business questions Addresses how the results of big data analytics can be visualised and communicated to ensure key decisions-makers understand them Includes many high-profile case studies from the author's work with some of the world's best known brands
| Author | : Suliman Hawamdeh |
| Publisher | : CRC Press |
| Total Pages | : 312 |
| Release | : 2018-08-06 |
| Genre | : Computers |
| ISBN | : 1351806998 |
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.
