Proposed models of adaptive knowledge aggregator

Abstract

Knowledge is considered as an important and valuable source for organizations. The right knowledge contributes to better decision making and thus, improves competitiveness and organizational performance. Thus, it is essential for organizations to manage their knowledge properly through knowledge management processes as to sustain in the competitive industry. Tacit knowledge, which is stored in employees’ minds and is hard to manage, has been considered as a crucial factor affecting the performance of organisations. Therefore, knowledge management enables the tacit knowledge of employees be converted to explicit knowledge to enable the retrieval of knowledge by other organizational members so that they can use that knowledge to be more innovative. Retrieving the right knowledge is important to enable the employees to perform better in their work; however, it poses a major challenge especially when retrieving knowledge from a large and variety of sources. The traditional knowledge retrieval methods share the explicit knowledge without a proper evaluation of the quality of knowledge (for example, without a proper editing). Thus, the aim of this paper is to develop efficient knowledge management methods that are able to; (1) to retrieve the right explicit knowledge from tacit knowledge based on responsible measurement variables; and (2) to aggregate and formulate the retrieved knowledge effectively for sharing valuable and focused knowledge. These methods will enable the organizational members to share the right explicit knowledge to the right employees at the right time. © 2005 - 2015 JATIT & LLS. All rights reserved.