A decision model for benchmarking knowledge management practice

Deng, H 2006, 'A decision model for benchmarking knowledge management practice', in M. Mohammadian (ed.) A decision model for benchmarking knowledge management practice, Sydney, Australia, 28 November - 1 December 2006, pp. 233-233.

Document type: Conference Paper
Collection: Conference Papers

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Title A decision model for benchmarking knowledge management practice
Author(s) Deng, H
Year 2006
Conference name International Conference on Computational Intelligence for Modelling, Control and Automation (CIMCA 2006)
Conference location Sydney, Australia
Conference dates 28 November - 1 December 2006
Proceedings title A decision model for benchmarking knowledge management practice
Editor(s) M. Mohammadian
Publisher IEEE
Place of publication Piscataway, USA
Start page 233
End page 233
Total pages 1
Abstract This paper presents a decision model for benchmarking and evaluating organizational knowledge management (KM) practices. Linguistic variables approximated by fuzzy numbers are used for adequately handling the subjectiveness and imprecision of the evaluation process. Pairwise comparison is adopted in the evaluation process for greatly reducing the cognitive burden of the decision maker. A fuzzy multicriteria analysis algorithm is developed for generating an overall ranking of all the organizations regarding their KM practices. As a result, the relative performance of organizations in managing their knowledge can be properly assessed, and effective decisions can be made for further improving their KM practices. An empirical study in evaluating the KM practices at Victorian local governments in Australia is presented for demonstrating the applicability of the proposed decision model in real situations.
Subjects Information Systems not elsewhere classified
DOI - identifier 10.1109/CIMCA.2006.3
Copyright notice © 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
ISBN 0-7695-2731-0
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