Knowledge Sharing Trust Level Measurement Adoption Model Based On Fuzzy Expert System

Abstract

In this paper, a fuzzy expert system-based Knowledge Sharing Trust Level(KSTL) measurement adoption model is presented. The KSTL was modeled using four input variables, developed from Technology Acceptance Model constructs namely; Perceived Trust Towards Competence, Perceived Trust Towards Benevolence, Perceived Trust Barrier for Sharing, External Cue Towards Trust to determine KSTL. A KSTL-fuzzy algorithm was developed using a trust metric equation at the preprocessing stage and implemented using Matlab 7.6.0 to compute KSTL crisp_value. The results obtained provided a useful understanding about the degree of trust among Community of Practice practicing knowledge-sharing. The proposed work was found to be dynamic, as the computed KSTL fluctuates with changes in the input variables. The simulated results demonstrate the effectiveness of the model in measuring trust level in knowledge-sharing applications.

The impact of knowledge sharing through social media among academia

“…Apart from that, [8] measured the successful rate of knowledge sharing in Tehran Municipality ICT Organization by applying a Fuzzy Logic (FL) understanding. Another research on FL application and its efficiency in solving KM issues was study done by [9]. In his research, FL was used to model the trust level in knowledge sharing application.…”