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Supporting Knowledge Evaluation to Increase Quality in Electronic Knowledge Repositories

Supporting Knowledge Evaluation to Increase Quality in Electronic Knowledge Repositories

Lena Aggestam, Per Backlund, Anne Persson
Copyright: © 2010 |Volume: 6 |Issue: 1 |Pages: 21
ISSN: 1548-0666|EISSN: 1548-0658|ISSN: 1548-0666|EISBN13: 9781616929251|EISSN: 1548-0658|DOI: 10.4018/jkm.2010103002
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MLA

Aggestam, Lena, et al. "Supporting Knowledge Evaluation to Increase Quality in Electronic Knowledge Repositories." IJKM vol.6, no.1 2010: pp.23-43. http://doi.org/10.4018/jkm.2010103002

APA

Aggestam, L., Backlund, P., & Persson, A. (2010). Supporting Knowledge Evaluation to Increase Quality in Electronic Knowledge Repositories. International Journal of Knowledge Management (IJKM), 6(1), 23-43. http://doi.org/10.4018/jkm.2010103002

Chicago

Aggestam, Lena, Per Backlund, and Anne Persson. "Supporting Knowledge Evaluation to Increase Quality in Electronic Knowledge Repositories," International Journal of Knowledge Management (IJKM) 6, no.1: 23-43. http://doi.org/10.4018/jkm.2010103002

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Abstract

Knowledge forms an important asset in modern organizations. In order to gain and sustain competitive advantage knowledge has to be managed. One aspect of this is to use Electronic Knowledge Repositories (EKR) to enhance knowledge sharing, reuse and learning. The success of an EKR is dependent on the quality of its content. For knowledge to be stored in an EKR, it has to be captured. One crucial part of the capture process is to evaluate whether the identified knowledge should be incorporated in the EKR or not. Therefore, to increase quality in an EKR, the evaluation stage of the capture process must be successfully carried out. Based on an interpretive field study and an extensive literature review, this paper identifies and characterizes Critical Success Factors (CSF) in the evaluation stage and presents guidance aiming to support implementation of the evaluation stage with the purpose to increase the quality of an EKR. In particular, the guidance supports the decision whether identified knowledge should be stored or not and it highlights the importance of performing evaluation addressing correctness, relevance, protection and redundancy. The characterization of the capture process contributes mainly to KM theory, and the guidance to KM practice.

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