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Organisational knowledge in high-risk industries: supplementing model-based learning approaches

Author

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  • Karina Aase
  • Geir Nybo

Abstract

High-risk industries are often facing a dilemma in their approach to creating a more competent and safe industry: they are excluded from some of the most effective learning processes such as trial-and-error learning and learning from failures and errors, due to the potentially catastrophic outcome associated with mistakes. As a consequence, these industries commonly rely on formal models of information gathering and dissemination. In a learning perspective, such approaches have often shown to be ineffective and unreliable, disregarding the social and contextual aspects of organisational knowledge. In a safety perspective, these formal repositories of experience and knowledge are often highly necessary and strictly enforced due to the high-risk environment. Is this a dilemma without solution? Are there alternative learning approaches to collectively develop, make sense of, and disseminate tacit and sticky knowledge in high-risk industries? Examples from studies of different high-risk industries are used to highlight these questions.

Suggested Citation

  • Karina Aase & Geir Nybo, 2005. "Organisational knowledge in high-risk industries: supplementing model-based learning approaches," International Journal of Learning and Intellectual Capital, Inderscience Enterprises Ltd, vol. 2(1), pages 49-65.
  • Handle: RePEc:ids:ijlica:v:2:y:2005:i:1:p:49-65
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