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• Module overview
• 1. Introduction to knowledge management
  • 1.1 Knowledge management in organisations: Theory and practice
  • 1.2 Information and knowledge
    • 1.2.1 Distinguishing information, data, knowledge and wisdom
    • 1.2.2 Knowledge defined and managed

• 2. Type and structure of knowledge

  • 2.1 Type and structure of knowledge
    • 2.1.1 The structure of purposeful knowledge in an organisation
    • 2.1.2 Explicit and tacit knowledge
  • 2.2 Acquiring knowledge
    • 2.2.1 Sources of knowledge

• 3. Knowledge and learning

  • 3.1 The ability to learn as knowledge
  • 3.2 Types of knowledge and culture, meaning, and learning
  • 3.3. Knowledge management and balanced learning strategies

• 4. A knowledge management cycle

  • 4.1 A Knowledge Management Framework
    • 4.1.1 Stages in KM Cycle
  • 4.2 Dimensions to KM Strategy
    • 4.2.1 Leadership dimension to KM
    • 4.2.2 Governance and policy dimension
    • 4.2.3 Architecture dimension
    • 4.2.4 Absorption dimension
    • 4.2.5 Measurement dimension
  • 4.3 Knowledge as a basis for organising

• 5. Conduct a knowledge audit

  • 5.1 Knowledge audit
    • 5.1.1 Conducting a knowledge audit
    • 5.1.2 The Audit Process

• 6. Organisational Knowledge Capital

  • 6.1 Building an organisational Knowledge Capital framework
    • 6.1.1 IC and KC
    • 6.1.2 The value of knowledge
  • 6.2 Structural capital
  • 6.3 Social capital
  • 6.4 Human Capital defined
    • 6.4.1 Capital resources for organisations
    • 6.4.2 The individual as a capital resource
    • 6.4.3 Ingredients to HCM

• 7. Valuing forms of knowledge

  • 7.1 Valuing forms of knowledge assets
    • 7.1.1 Valuing Intellectual assets
    • 7.1.2 Valuing knowledge as an intangible asset

• 8. Information management systems

  • 8.1 Information management systems
    • 8.1.1 A basic information management framework
    • 8.1.2 Building systems to meet individual and organisational needs
    • 8.1.3 Information guardians versus stakeholders
  • 8.2 Structure and information transfer
    • 8.2.1 Information relevance and timeliness
    • 8.2.2 Information characteristics versus decision types
    • 8.2.3 Storage and retrieval

• 9. Information capture and intelligence gathering

  • 9.1 Information capture and intelligence gathering
    • 9.1.1 Developing a 'wish list'
    • 9.1.2 Finding answers
    • 9.1.3 Integrating intelligence within a knowledge management framework
  • 9.2 Forecasting methods
    • 9.2.1 Issues to consider when forecasting

• 10. IT and E-commerce

  • 10.1 An overview of e-commerce
  • 10.2 The Internet, computer networks and e-commerce
    • 10.2.1 Internet speed, innovation and change
  • 10.3 E-commerce advantages and disadvantages
    • 10.3.1 E-commerce advantages
    • 10.3.2 E-commerce disadvantages and constraints
  • 10.4 The Internet and business
    • 10.4.1 Drivers of e-commerce and Internet growth
  • 10.5 E-commerce and e-business

• 11. IT and supply chain management

  • 11.1 Electronic supply chain management (eSCM)
  • 11.2 E-logistics
    • 11.2.1 Are e-logistics and e-commerce the same thing?
    • 11.2.2 E-logistics blurs older logistic business categories
  • 11.3 E-procurement
  • 11.4 E-fulfilment

1.2 Information and knowledge

It is the interaction between the information and the existing knowledge of the agent that is defining in this case. Data becomes information when the agent receiving it can ascribe meaning to the data; knowledge is generated through the interaction of existing knowledge with the flow of information to the agent. In contrast to information, knowledge cannot be directly observed. Its existence can only be inferred from the action of agents.

(Boisot, 1998:12)

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