2,523 research outputs found

    Mapping knowledge management and organizational learning in support of organizational memory

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    The normative literature within the field of Knowledge Management has concentrated on techniques and methodologies for allowing knowledge to be codified and made available to individuals and groups within organizations. The literature on Organizational Learning however, has tended to focus on aspects of knowledge that are pertinent at the macro-organizational level (i.e. the overall business). The authors attempt in this paper to address a relative void in the literature, aiming to demonstrate the inter-locking factors within an enterprise information system that relate knowledge management and organizational learning, via a model that highlights key factors within such an inter-relationship. This is achieved by extrapolating data from a manufacturing organization using a case study, with these data then modeled using a cognitive mapping technique (Fuzzy Cognitive Mapping, FCM). The empirical enquiry explores an interpretivist view of knowledge, within an Information Systems Evaluation (ISE) process, through the associated classification of structural, interpretive and evaluative knowledge. This is achieved by visualizng inter-relationships within the ISE decision-making approach in the case organization. A number of decision paths within the cognitive map are then identified such that a greater understanding of ISE can be sought. The authors therefore present a model that defines a relationship between Knowledge Management (KM) and Organisational Learning (OL), and highlights factors that can lead a firm to develop itself towards a learning organization

    Reasoning with linguistic preferences using NPN logic

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    Negative-positive-neutral logic provides an alternative framework for fuzzy cognitive maps development and decision analysis. This paper reviews basic notion of NPN logic and NPN relations and proposes adaptive approach to causality weights assessment. It employs linguistic models of causality weights activated by measurement-based fuzzy cognitive maps' concepts values. These models allow for quasi-dynamical adaptation to the change of concepts values, providing deeper understanding of possible side effects. Since in the real-world environments almost every decision has its consequences, presenting very valuable portion of information upon which we also make our decisions, the knowledge about the side effects enables more reliable decision analysis and directs actions of decision maker
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