A study on performance evaluation model of individual knowledge-sharing

To evaluate the knowledge-sharing performance in the customer collaborative innovation organization based on subtractive clustering and Fuzzy Neural Network (SC-FNN), an knowledge-sharing performance evaluation model was proposed. Firstly, the process of Knowledge-sharing was researched, and the performance affecting factors of knowledge-sharing were analyzed, then the index system of performance evaluation was constructed. Secondly, fuzzy subtractive clustering was used to simplify and reduce the rules of fuzzy neural network. Moreover, particle swarm optimization algorithm and genetic algorithm were utilized to decide the parameters´ values of fuzzy neural network. Based on the model, the synthetic evaluation of Knowledge-sharing was realized.