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Knowledge Management and Sharing

Bee K. Yew, WeiXiong Ho, Marvin D. Troutt

Open publisher page 3 citations

Abstract

The knowledge economy is driven by growth and development of intellectual capital in organizations. Knowledge is defined to be reusable abstractions that can produce new knowledge and modify existing knowledge. Decision making, which includes task solving, is a common feature of the working organization, and it requires good knowledge as input. This chapter provides a review of the knowledge management (KM) concepts and perspectives, with an introduction to the knowledge management Systems (KMS) and its related technologies. The importance of a knowledge base for KM and knowledge sharing (KS) activities is illustrated for Callisma, a consulting firm. Models for knowledge cycle and conversions are covered to provide further theory for KM research. KS, in particular, is an important concern for a knowledge organization as it is believed that effective knowledge sharing or better knowledge utilization can result in increased organizational capabilities as defined by competitiveness, efficiency, competency, and creativity. The inquiring models based on Kant, Hegel, Locke and Liebnitz mental models are presented to provide an analytical framework for knowledge creating and sharing activities.

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The knowledge economy is driven by growth and development of intellectual capital in organizations. Knowledge is defined to be reusable abstractions that can produce new knowledge and modify existing knowledge. Decision making, which includes task solving, is a common feature of the working organization, and it requires good knowledge as input. This chapter provides a review of the knowledge management (KM) concepts and perspectives, with an introduction to the knowledge management Systems (KMS) and its related technologies. The importance of a knowledge base for KM and knowledge sharing (KS) activities is illustrated for Callisma, a consulting firm. Models for knowledge cycle and conversions are covered to provide further theory for KM research. KS, in particular, is an important concern for a knowledge organization as it is believed that effective knowledge sharing or better knowledge utilization can result in increased organizational capabilities as defined by competitiveness, efficiency, competency, and creativity. The inquiring models based on Kant, Hegel, Locke and Liebnitz mental models are presented to provide an analytical framework for knowledge creating and sharing activities.

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Available abstract

The knowledge economy is driven by growth and development of intellectual capital in organizations. Knowledge is defined to be reusable abstractions that can produce new knowledge and modify existing knowledge. Decision making, which includes task solving, is a common feature of the working organization, and it requires good knowledge as input. This chapter provides a review of the knowledge management (KM) concepts and perspectives, with an introduction to the knowledge management Systems (KMS) and its related technologies. The importance of a knowledge base for KM and knowledge sharing (KS) activities is illustrated for Callisma, a consulting firm. Models for knowledge cycle and conversions are covered to provide further theory for KM research. KS, in particular, is an important concern for a knowledge organization as it is believed that effective knowledge sharing or better knowledge utilization can result in increased organizational capabilities as defined by competitiveness, efficiency, competency, and creativity. The inquiring models based on Kant, Hegel, Locke and Liebnitz mental models are presented to provide an analytical framework for knowledge creating and sharing activities.

Key concepts: Knowledge management, Knowledge sharing, Knowledge value chain, Intellectual capital, Personal knowledge management, Knowledge economy, Organizational learning, Procedural knowledge

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