Applying a Computational Trust and Reputation Model in Comunities of Practice
Applying a Computational Trust and Reputation Model in Comunities of Practice

Summary/Abstract: Knowledge represents a critic asset, the main source of power and competitive advantage in modern organizations. In a global perspective, knowledge is considered a dynamic entity that is processed and analyzed through intelligent networks to serve the knowledge society. Therefore, a new organizational form has emerged that complements existing structures and emphasizes knowledge sharing and learning, called the community of practice. Communities of practice are relying on the existence of trust relationships among their members. Members have to adapt their behavior to the evolution of the common environment. Thus, trust represents an efficient coordinating device by allowing a certain degree of flexibility in members’ behavior. The main objective of this paper is to highlight the importance of trust and reputation in communities of practice and to describe a theoretical framework for the organization of communities of practice in a dynamic perspective. The inter-organizational behavior of communities of practice members has been formalized using agent-based representations. We have proposed an adapted agent-based model to evaluate trust and reputation within communities of practice.

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