4.7 Article

Evaluating knowledge management capability of organizations: a fuzzy linguistic method

Journal

EXPERT SYSTEMS WITH APPLICATIONS
Volume 36, Issue 2, Pages 3346-3354

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2008.01.052

Keywords

Knowledge management (KM); Knowledge management capability (KMC); Linguistic assessment information; Judgment matrix model; 2-Tuple; Fuzzy linguistic approach

Funding

  1. National Science Fund for Distinguished Young Scholars of China [70525002]
  2. National Science Fund for Excellent Innovation Research Group of China [70721001]
  3. Key Laboratory of Integrated Automation of Process Industry (Northeastern University)
  4. Ministry of Education, China [JCLL-01-05]

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Knowledge management capability (KMC) is the source for organizations to gain the sustainable competitive advantage. KMC evaluation is a required work with strategic significance. However it still has not been addressed in the existing literatures. So the objective of this study is to investigate a fuzzy multiple attributes decision-making method (FMADM) for evaluating KMC. In this paper, a framework for evaluating KMC is presented, which includes two parts, one is an evaluation hierarchy with attributes, the other a judgment matrix model with two dimensions to identify the evaluation results of KMC. Then, a fuzzy linguistic approach is proposed to evaluate the KMC of organizations. The evaluation results of KMC obtained through the proposed approach are objective and unbiased due to two reasons. Firstly, the results are generated by a group of experts in the presence of motile attributes. Secondly, the fuzzy linguistic approach employed in this paper has more advantage to reduce distortion and losing of information than other fuzzy linguistic approaches. Through evaluation result of KMC managers could judge the necessity to improve the KMC and determine which dimension of KMC is the most needed direction to improve. Additionally, an example is used to illustrate the availability of the proposed method. (C) 2008 Elsevier Ltd. All rights reserved.

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