2 resultados para explicit knowledge

em WestminsterResearch - UK


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The study of knowledge transfer (KT) has been proceeding in parallel but independently in health services and in business, presenting an opportunity for synergy and sharing. This paper uses a survey of 32 empirical KT studies with their 96 uniquely named determinants of KT success to identify ten unique determinants for horizontal knowledge transfer success. These determinants, the outcome measure of Knowledge Use, and separate explicit and tacit transfer flows constitute the KT Framework, extending the work of previous KT framework authors. Our Framework was validated through a case study of the transfer of clinical practice guideline knowledge between the cardiac teams of selected Ontario hospitals, using a survey of senders and receivers developed from the KT literature. The study findings were: 8 of 10 determinants were supported by the Successful Transfer Hospitals; and 4 of 10 determinants were found to a higher degree in the Successful than non-Successful transfer hospitals. Taken together, the results show substantive support for the KT Framework determinants, indicating aggregate support of 9 of these determinants, but not the 10th - Knowledge Complexity. The transfer of tacit knowledge was found to be related to the transfer of the explicit knowledge and expressed as the transfer or recreation of resource profile and internal process tacit knowledge, where this tacit transfer did not require interactions between Sender and Receiver. This study provides managers with the building blocks to assess and improve the success rates of their knowledge transfers.

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Revenue and production output of the United Kingdom’s Aerospace Industry (AI) is growing year on year and the need to develop new products and innovative enhancements to existing ranges is creating a critical need for the increased utilisation and sharing of employee knowledge. The capture of employee knowledge within the UK’s AI is vital if it is to retain its pre-eminent position in the global marketplace. Crowdsourcing, as a collaborative problem solving activity, allows employees to capture explicit knowledge from colleagues and teams and also offers the potential to extract previously unknown tacit knowledge in a less formal virtual environment. By using micro-blogging as a mechanism, a conceptual framework is proposed to illustrate how companies operating in the AI may improve the capture of employee knowledge to address production-related problems through the use of crowdsourcing. Subsequently, the framework has been set against the background of the product development process proposed by Maylor in 1996 and illustrates how micro-blogging may be used to crowdsource ideas and solutions during product development. Initial validation of the proposed framework is reported, using a focus group of 10 key actors from the collaborating organisation, identifying the perceived advantages, disadvantages and concerns of the framework; results indicate that the activity of micro-blogging for crowdsourcing knowledge relating to product development issues would be most beneficial during product conceptualisation due to the requirement for successful innovation.