Decision Support Systems, 44 (2), 2007 – interesting articles

[German title: Decision Support Systems, 44 (2), 2007 – interessante Artikel (Translate text to: Deutsch)]

Decision Support Systems
Volume 44, Issue 2, Pages 369-564 (January 2008)

Transactive memory systems in organizations: Implications for knowledge directories 409-424
Paul Jackson and Jane Klobas

Abstract: This article describes a detailed case study in which the authors observed organizational Transactive Memory Systems (TMS). The concept of TMS was originally used to describe sets of directories that are used to locate, allocate and retrieve knowledge in pairs and small groups. Our case study of head office and distributed knowledge workers revealed that the basic TMS processes and directories appear to be present at an organizational level as well. The results imply that an organization can indeed be seen as a TMS and suggest that information systems which are intended to support TMS should be approached as a component within a complex and multi-dimensional information retrieval ecology.

Keywords: Transactive memory systems; Knowledge management; Virtual work; Global organizations

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Collaborative relevance assessment for task-based knowledge support 524-543
Duen-Ren Liu and I-Chin Wu

Abstract: The operations and management activities of enterprises are mainly task-based and knowledge intensive. Accordingly, an important issue in deploying knowledge management systems is the provision of task-relevant information (codified knowledge) to meet the information needs of knowledge workers during the execution of a task. Codified knowledge extracted from previously executed tasks can provide valuable knowledge about conducting the task-at-hand (current task), and is a valuable information source for constructing a task profile that models a worker’s task needs, i.e., information needs for the current task. In this paper, we propose a novel task-relevance assessment approach that evaluates the relevance of previous tasks in order to construct a task profile for the current task. The approach helps knowledge workers assess the relevance of previous tasks through linguistic evaluation and the collaboration of knowledge workers. In addition, applying relevance assessment to a large number of tasks may create an excessive burden for workers. Thus, we propose a novel two-phase relevance assessment method to help workers conduct relevance assessment effectively. Furthermore, a modified relevance feedback technique, which is integrated with the task-relevance assessment method, is employed to derive the task profile for the task-at-hand. Consequently, task-based knowledge support can be enabled to provide knowledge workers with task-relevant information based on task profiles. Empirical experiments demonstrate that the proposed approach models workers’ task-needs effectively and helps provide task-relevant knowledge.

Keywords: Information retrieval; Knowledge management; Relevance assessment; Task-based knowledge support; Task profile

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Copyright © 2007 Elsevier B.V. All rights reserved

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