Knowledge Management

Knowledge Management

Manjunath Ramachandra (MSR School of Advanced Studies, Philips, India)
DOI: 10.4018/978-1-60566-888-8.ch018
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The data in its raw form can make some meaning as information after being subjected to a variety of processes. With the available information, it is possible further to extract the contextual meaning by translating the same in to knowledge. In this chapter, the paradigm of knowledge management is introduced. The acquired knowledge is useful as a tool for the players of the supply chain. Internet plays a crucial role in sharing the knowledge. The different web based techniques for knowledge management are provided here.
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One of the drawbacks with the conventional knowledge management models is that, it is defined in terms of the abstract parameters such as the data, information technology, best practices, etc. They fail to capture the dynamics accurately because these parameters themselves depend up on the variables such as attention, motivation, commitment, creativity, and innovation, that is required to be included in the model. The input of the model needs to capture the dynamics of the organization.

The capability of human beings to interpolate, extrapolate, generalize and learn the patterns enable them to infer the knowledge from the templates not being exposed previously (Brown, J. S. & Duguid P, 2000). As a result, the inference turns out to be personalized depending up on the context, time and relevance (Belbin, R.M, 2000). With this being the situation, storing the individual knowledge in static or standard templates in the databases will not be of much use (Brown, J. S. & Duguid P, 2002).

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