Model Based Fuzzy Expert System for Measuring Organization Knowledge Management - Houshang Taghizadeh; Gholamreza Soltani Fesghandis (Iranian Journal of Information Processing & Management, 2012)
This paper presents a model based on fuzzy set theory for determining the score of knowledge management in organization. The introduced model has five stages. In the first stage, input and output variable of model are characterized by available theories. Inputs are as follows: knowledge acquisition, knowledge storage, knowledge creation, knowledge sharing and knowledge transfer. The output is as follow score of knowledge management in organization. In the second stage, the input and output are converted into fuzzy numbers after classification. Inference rules are explained in the third stage. In the fourth stage, defuzzification is performed, and in the fifth stage, the devised system is tested. The test result shows that the presented model has high validity. Ultimately, by using the designed model, the score of knowledge management for Tabriz Kar machinery industry was calculated. The statistical population consists of 50 members of this organization. All the population has been studied. A questionnaire was devised, and its validity and reliability were confirmed. The result indicated that the score of knowledge management in Tabriz Kar machinery industry with the membership rank of 0.924 was at an average level and with the membership rank of 0.076 was at a high