Collaborative Networks - Premises for Exploitation of Inter-Organizational Knowledge Management

Marinela Mircea ()

Informatica Economica, 2015, vol. 19, issue 2, 57-65

Abstract: Inter-organization knowledge management in the context of collaborative networks is a critical activity for business success. During the evolution of collaborative network specific technologies, increasingly performant instruments were created to exploit this knowledge. As a development cycle, inter-organizational knowledge is built on the foundation of information and data owned by the participants in the collaborative networks. One of the most widely used instruments to exploit this data and knowledge, with the purpose of creating new knowledge, is Data Mining. In the context of this paper, data mining is the process of discovering patterns and hidden relations in very large data collections, stored in data banks or data bases. Because only in extremely rare cases reading data tables record by record leads to the discovery of useful patterns, the information must be processed automatically, process known as Knowledge Discovery. Knowledge Discovery is a component that combines the power of computers with a human operator that has the ability to find the visual patterns revealed by the system. Using an automated data mining system, the computer finds the existing informational patterns and the human factor (the analyst) evaluates those patterns and picks the ones that are really relevant for the current analysis. Considering the current technological context, where storage devices are more and more accessible and performant, the storage capacity is no longer a barrier preventing storage of all required data. Exploitation of inter-organizational knowledge in collaborative networks leads the research to the field of business intelligence applied even on social environment. This approach belongs in literature to the general branch of social business intelligence.

Keywords: Collaborative Networks; Information Technology; Inter-Organizational Knowledge; Knowledge Management; Knowledge Discovery; Data Mining (search for similar items in EconPapers)
Date: 2015
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