Credibility-based core knowledge selection with fuzzy information

Managing core knowledge can present considerable challenges for long-term sustainable competitive advantages. The crux among knowledge management is how to effectively select core knowledge from various knowledge-based assets while maintaining tight control over intellectual properties. Owing to linguistic or uncertain concepts frequently represented in decision data, evaluations of real situations should be assumed to be fuzzy numbers. The paper proposes an approach to core knowledge selection with fuzzy information. Using the conceptual framework developed by Lin and Liu (2007), we focus on criteria evaluation and comprehensive procedure that have been previously associated with group decision system. We explore the choice-function which is an aggregating consistency of decision group and provide a fuzzy programming model of seeking core knowledge. Fuzzy constraints are also considered in the model. Credibility measure is applied to solve the proposed model so that it can embody well the group preference level. Results of an example further show that the approach which fits into the general framework can successfully identify core knowledge worthy of attention.