CoMIS-KMS: An Elaborated Process Model for Transitioning MIS to KMS

CoMIS-KMS: An Elaborated Process Model for Transitioning MIS to KMS

Ricardo Anderson (The University of the West Indies – Mona, Jamaica) and Gunjan Mansingh (The University of the West Indies – Mona, Jamaica)
Copyright: © 2019 |Pages: 22
DOI: 10.4018/978-1-5225-5427-1.ch009
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Modern information system environments generally contain complex computing infrastructure often mapping business processes to people and data. Data manipulation to summarize and report meaningful information is commonplace, although some of these systems and techniques have not been extensively exploited within developing countries. Even in developed economies, where resources and experience are abundant and accessible, the process for moving from information management to knowledge management is not well understood and therefore remains a challenge. In this study, a comprehensive process model that guides the transitioning of an existing information system to a knowledge management system is developed and evaluated. The results indicate that the model sufficiently represents and organizes the activities to be carried out to meet the desired outcome of converting an existing information system into a knowledge management system.
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Knowledge Elicitation, Codification, And Management

Leonard and Sensipar (1998) define knowledge as relevant, actionable information based partially on experience. O’Dell et al (1998) suggest that knowledge is what members of an organization know about their customers, products, successes and mistakes. The authors adopt for the purpose of this study that knowledge is a ’fluid mix of framed experience, values, contextual information and expert insight that provide a framework for evaluation and incorporating new experiences and information (Davenport & Prusak, 2000). This differs significantly from information and data which are lower according to the data-information-knowledge-wisdom (DIKW) hierarchy (Rowley, 2007). Data is a collection of facts and figures, while information is organized data that provides meaning. Context, experiences, and expert insights can then be added to information to produce knowledge.

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