Knowledge Sharing

Knowledge sharing is central to knowledge management in organizations. The more tacit the knowledge, the harder it is to share. However, successful knowledge sharing means looking not just at the content of the knowledge, and the people and technology concerned in the sharing, but the context in which that sharing takes place. This chapter discusses relevant theories from knowledge management and other fields. It goes on to present a model covering the time, place and context of the knowledge sharing activity, developed using theories about decision support systems. This forms the final part of a three-stage approach intended to help managers (and others) make decisions about how to support knowledge sharing activities in organizations. Each stage takes the form of a question to be answered, as follows: 1) What are the business processes concerned? 2) What is the knowledge to be shared related to - knowledge creation, knowledge acquisition, knowledge refinement, knowledge storage, or knowledge use? 3) What does this mean for the time, place and context of the knowledge sharing?

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Knowledge Sharing

Information Diffusion Management and Knowledge Sharing ◽

10.4018/978-1-7998-0417-8.ch017 ◽

2020 ◽

pp. 344-357

Author(s):

John S. Edwards

Keyword(s):

Knowledge Management ◽

Decision Support ◽

Knowledge Acquisition ◽

Knowledge Sharing ◽

Decision Support Systems ◽

Knowledge Creation ◽

Business Processes ◽

Support Systems ◽

Knowledge Use ◽

The People

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Decision Support Systems Based on Knowledge Management

Advances in Intelligent Systems and Computing - Recent Advances in Information Systems and Technologies ◽

10.1007/978-3-319-56535-4_24 ◽

2017 ◽

pp. 236-250

Author(s):

Márcia Baptista ◽

José Braga Vasconcelos ◽

Álvaro Rocha

Keyword(s):

Knowledge Management ◽

Decision Support ◽

Decision Support Systems ◽

Support Systems

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Business Intelligence and Data Mining

Research and Development in E-Business through Service-Oriented Solutions - Advances in E-Business Research ◽

10.4018/978-1-4666-4181-5.ch003 ◽

2013 ◽

pp. 57-70

Author(s):

Zsolt T. Kardkovács

Keyword(s):

Data Mining ◽

Decision Support ◽

Strategic Planning ◽

Decision Support Systems ◽

Business Intelligence ◽

Business Processes ◽

Support Systems ◽

Decision Makers ◽

Key Factors ◽

Short Introduction

Whenever decision makers find out that they want to know more about how the business works and progresses, or why customers do what they do, then data miners are summoned, and business intelligence is to be built or altered. Data mining aims at retrieving valid, interesting, explicable connection between key factors for either operative reporting or supporting strategic planning. While data mining discovers static connections between factors, business intelligence visualizes relevant data for decision makers in order to make them identify fast changes and analyze precisely business states. In this chapter, the authors give a short introduction for data oriented decision support systems with data mining and business intelligence in it. While these techniques are widely used in business processes, there are much more bad practices than good ones. We try to make an attempt to demystify and clear the myths about these technologies, and determine who should and how (not) to use them.

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