Principles Of Knowledge Management
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Introduction to Knowledge Management
Knowledge Management (KM) is a hybrid discipline, containing elements of social sciences, technology and business. KM focuses on creating and sharing knowledge. The discipline is a holistic system for management of intellectual capital, organization change, knowledge creation and sharing, for continuous improvement and innovation, and organizational learning, resulting in increased value creation. This symbioses of disciplines takes place within the organizations' vision, purpose and strategy. Introduction to Knowledge Management provides a strategic roadmap for knowledge management and teaches how to implement KM in a company, step by step.
Principles of Knowledge Management
This text provides a comprehensive introduction to the new field of knowledge management. It approaches the subject from a management rather than a highly technical point of view, and provides students with a state-of-the-art survey of KM and its implementation in diverse organizations. The text covers the nature of knowledge (tacit and explicit), the origins and units of organizational knowledge, and the evolution of knowledge management in contemporary society. It explores the implementation and utilization of knowledge management systems, and how to measure their impact, outputs, and benefits. The book includes a variety of original case studies that illustrate specific situations in which the absence or existence of knowledge management systems has been crucial to the organization's actions. Charts and figures throughout help clarify more complex phenomena and classifications, and each chapter includes review questions and a comprehensive index.
Enablers of Organisational Learning, Knowledge Management, and Innovation
This book establishes constructivist, interpretivist, and linguistic approaches based on conventions about the nature of qualitative and text data, the author’s influence on text interpretation, and the validity checks used to justify text interpretations. Vast quantities of text and qualitative data in organizations often go unexplored. Text analytics outlined in this book allow readers to understand the process of converting unstructured text data into meaningful data for analysis in order to measure employee opinions, feedback, and reviews through sentiment analysis to support fact-based decision making. The methods involve using NVivo and RapidMiner software to perform lexical analysis, categorization, clustering, pattern recognition, tagging, annotation, memo creation, information extraction, association analysis, and visualization. The methodological approach in the book uses innovation theory as a sensitizing concept to lay the foundation for the analysis of research data, suggesting approaches for empirical exploration of organizational learning, knowledge management, and innovation practices amongst geographically dispersed individuals and team members. Based on data obtained from a private educational organization that has offices dispersed across Asia through focus group discussions and interviews on these topics, the author highlights the need for integrating organizational learning, knowledge management, and innovation to improve organizational performance, exploring perspectives on collective relationships and networks, organizational characteristics and structures, and tacit and overt values which influence such innovation initiatives. In the process, the author puts forward a new theory which is built on three themes: relationship and networks, knowledge sharing mechanisms, and the role of social cognitive schema that facilitate emergent learning, knowledge management, and innovation.