Abstract:
present paper aimed at developing an approach based on Fuzzy Inference System (FIS) for measuring of knowledge sharing in the organization. In recent years there has been increasing interest in the knowledge sharing by experts and managers in the world, according to increasing importance of knowledge as the key source of competitive advantage, organizations have made serious effort to find effective ways to share knowledge among their employees. It is important to invest in knowledge sharing activities and make innovation and enhance organizational performance. To achieve this elite opportunity, organizations need solutions that are able to evaluate the knowledge sharing. The purpose of the research was to provide a solution for evaluating knowledge sharing. Mined in this research using knowledge sharing model of scientific texts and the appropriate model is designed on the basis of summing up the results of the fuzzy inference system. And finally, knowledge sharing will be evaluated in the case study
Machine summary:
, 2 (3), 193- 202, Summer 2012 © IAU A Model for Evaluating Knowledge Sharing Using Fuzzy Inference System (Case Study: Tehran Municipality ICT Organization) 1 M.
Pilevari 1 Department of Information Technology Management, School of Management and Economics, Science and Research Branch, Islamic Azad University (IAU), Tehran, Iran 2 Department of Industrial Management, Shahr-e-Rey Branch, Islamic Azad University (IAU), Tehran, Iran present paper aimed at developing an approach based on Fuzzy Inference System (FIS) for measuring of knowledge sharing in the organization.
Keywords: Knowledge sharing, Fuzzy inference system, Knowledge management, Information and communication technology, Human capital, Organizational capital INTRODUCTION Knowledge management efforts typically focus on organizational objectives such as improved performance, competitive advantage, innovation, the sharing of lessons learned, integration and continuous improvement of the organization.
(2008) Knowledge sharing in Chinese construction project teams and it’s affecting factors: An empirical study Regression analysis Human 4 Azad and Rashidi (2009) Knowledge sharing engineering with the help of knowledge management system Questionnaire Human 5 Lin (2008) The effect of knowledge sharing model Neural network- based nonlinear Human, Organization 6 Sohrabi et al.
For evaluating knowledge sharing three attribute have been used as proposed inference system inputs, but in most steps there are several rules for evaluating so in the last step we need an y j Ai xi y j 1 i 1 m n Ai xi j 1 i 1 The proposed fuzzy model consists of four main rule blocks and nine inputs (TL, MV, PS, ST, SC, CL, CM, CB and SR), three intermediates (human capital, organizational capital and information and communications technology) and the output of the main fuzzy inference system is the knowledge sharing in the case study (Tehran municipality ICT organization) evaluated and the results have been shown in table 5.