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We call knowledge of such a collaborative practice an "internal collaboration script" and regard them as configurations of knowledge components about a collaborative practice.
Thus, internal collaboration scripts need to be understood as highly flexible configurations of knowledge components (plays, scenes, scriptlets, and roles) that have a likely sequencing (if the collaborative practice proceeds as expected) but can be dynamically reconfigured according to changes in the situation or in the activity.
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Each sub-component (sub-element) of a knowledge cluster and innovation network can be displayed as a micro-level sub-configuration of knowledge clusters and innovation networks (see Figure ten of Carayannis and Campbell (2006).
An internal collaboration script is a configuration of knowledge components about a collaborative practice and its parts at different levels of complexity (the so-called internal collaboration script components) that guide the person's understanding of and actions in the collaboration.
An emerging shortage of talent and a recognition of knowledge sources far more spread around the globe have induced firms to re-think their configuration of knowledge-intensive activities, such as R&D.
The paper investigates the impact of the configuration of local knowledge bases on new firm formation dynamics by combining the KSTE framework with the recombinant knowledge approach.
By adjusting the rules, the configuration of the knowledge recommender system could be adapted to different users.
These questions have triggered interest in the existence of "rich" models containing most, if not all, possible configurations of (higher-order) knowledge and beliefs.
In addition to this, we employ prior shape and configuration knowledge of the sub-cortical structures in order to guide the evolution of geometric active surfaces.
It also contributes to recent museum studies literature with its foregrounding of the body and the sensorium in the configuration of the spaces of knowledge at the museum.
We then focus on one of these levels by analyzing monitored data from virtual machines and making decisions on their resource configuration with the help of knowledge management (KM).
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