'Knowledge Management Foundations' is just what it claims, the first attempt to provide a secure intellectual footing for the myriad of practices called "knowledge management." A breath of fresh air from the usual KM gurus, Fuller openly admits that the advent of KM is a mixed blessing that often amounts to the conduct of traditional management by subtler means. However, Fuller's deep understanding of both the history of management theory and knowledge production more generally enables him to separate the wheat from the chaff of the KM literature. This ground-breaking book will prove of interest to both academics and practitioners of knowledge management. It highlights the ways in which KM has challenged the values associated with knowledge that academics have taken for granted for centuries. At the same time, Fuller resists the conclusion of many KM gurus, that the value of knowledge lies in whatever the market will bear in the short term. He pays special attention to how information technology has not only facilitated knowledge work but also has radically altered its nature. There are chapters devoted to the revolution in intellectual property and an evaluation of peer review as a quality control mechanism. The book culminates in a positive re-evaluation of universities as knowledge producing institutions from which the corporate sector still has much to learn.

In the past, applied artificial intelligence systems were built with particular emphasis on general reasoning methods intended to function efficiently, even when only relatively little domain-specific knowledge was available. In other words, AI technology aimed at the processing of knowledge stored under comparatively general representation schemes. Nowadays, the focus has been redirected to the role played by specific and detailed knowledge, rather than to the reasoning methods themselves. Many new application systems are centered around knowledge bases, i. e. , they are based on large collections offacts, rules, and heuristics that cap ture knowledge about a specific domain of applications. Experience has shown that when used in combination with rich knowledge bases, even simple reasoning methods can be extremely effective in a wide variety of problem domains. Knowledge base construction and management will thus become the key factor in the development of viable knowledge-based ap plications. Knowledge Base Management Systems (KBMSs) are being proposed that provide user-friendly environments for the construction, retrieval, and manipUlation of large shared knowledge bases. In addition to deductive reasoning, KBMSs require operational characteristics such as concurrent access, integrity maintenance, error recovery, security, and perhaps distribution. For the development ofKBMSs, the need to integrate concepts and technologies from different areas, such as Artificial Intel ligence, Databases, and Logic, has been widely recognized. One of the central issues for KBMSs is the framework used for knowledge representation-semantic networks, frames, rules, and logics are proposed by the AI and logic communities.

"This book provides comprehensive coverage of all areas (people, process, and technology) necessary to become a knowledge-based enterprise. It presents several frameworks facilitating the implementation of a KM initiative and its ongoing management so that pertinent knowledge and information are always available to the decision maker, and so the organization may always enjoy a sustainable competitive advantage"--Provided by publisher.

In the past, applied artificial intelligence systems were built with particular emphasis on general reasoning methods intended to function efficiently, even when only relatively little domain-specific knowledge was available. In other words, AI technology aimed at the processing of knowledge stored under comparatively general representation schemes. Nowadays, the focus has been redirected to the role played by specific and detailed knowledge, rather than to the reasoning methods themselves. Many new application systems are centered around knowledge bases, i. e. , they are based on large collections offacts, rules, and heuristics that cap ture knowledge about a specific domain of applications. Experience has shown that when used in combination with rich knowledge bases, even simple reasoning methods can be extremely effective in a wide variety of problem domains. Knowledge base construction and management will thus become the key factor in the development of viable knowledge-based ap plications. Knowledge Base Management Systems (KBMSs) are being proposed that provide user-friendly environments for the construction, retrieval, and manipUlation of large shared knowledge bases. In addition to deductive reasoning, KBMSs require operational characteristics such as concurrent access, integrity maintenance, error recovery, security, and perhaps distribution. For the development ofKBMSs, the need to integrate concepts and technologies from different areas, such as Artificial Intel ligence, Databases, and Logic, has been widely recognized. One of the central issues for KBMSs is the framework used for knowledge representation-semantic networks, frames, rules, and logics are proposed by the AI and logic communities.

Creating Knowledge Based Organizations brings together high quality concepts and techniques closely related to organizational learning, knowledge workers, intellectual capital, and knowledge management. It includes the methodologies, systems and approaches that are needed to create and manage knowledge based organizations.

A new, thoroughly updated edition of a comprehensive overview of knowledge management (KM), covering theoretical foundations, the KM process, tools, and professions. The ability to manage knowledge has become increasingly important in today's knowledge economy. Knowledge is considered a valuable commodity, embedded in products and in the tacit knowledge of highly mobile individual employees. Knowledge management (KM) represents a deliberate and systematic approach to cultivating and sharing an organization's knowledge base. This textbook and professional reference offers a comprehensive overview of the field. Drawing on ideas, tools, and techniques from such disciplines as sociology, cognitive science, organizational behavior, and information science, it describes KM theory and practice at the individual, community, and organizational levels. Chapters cover such topics as tacit and explicit knowledge, theoretical modeling of KM, the KM cycle from knowledge capture to knowledge use, KM tools, KM assessment, and KM professionals. This third edition has been completely revised and updated to reflect advances in the dynamic and emerging field of KM. The specific changes include extended treatment of tacit knowledge; integration of such newer technologies as social media, visualization, mobile technologies, and crowdsourcing; a new chapter on knowledge continuity, with key criteria for identifying knowledge at risk; material on how to identify, document, validate, share, and implement lessons learned and best practices; the addition of new categories of KM jobs; and a new emphasis on the role of KM in innovation. Supplementary materials for instructors are available online.

Knowledge Management has evolved into one of the most important streams of management research, affecting organizations of all types at many different levels. The Encyclopedia of Knowledge Management, Second Edition provides a compendium of terms, definitions and explanations of concepts, processes and acronyms addressing the challenges of knowledge management. This two-volume collection covers all aspects of this critical discipline, which range from knowledge identification and representation, to the impact of Knowledge Management Systems on organizational culture, to the significant integration and cost issues being faced by Human Resources, MIS/IT, and production departments.