Navigation behaviour can be considered as one of the most crucial aspects of user behaviour in an electronic commerce environment, which is very good indicator of user's interests either in the process of browsing or purchasing. Revealing user navigation patterns is very helpful in finding out a way for increasing sale, turning the most browsers into buyers, keeping costumer's attention, loyalty, adjusting and improving the interface in order to boost the user experience and interaction with the system. In this regard, this research has identified the most common user navigation patterns across information networks, illustrated through the example of an electronic bookstore. A behavioural-based model that provides profound knowledge about the processes of navigation is proposed, specifically examined for different types of users, automatically identified and clustered into two clusters according to their navigational behaviour. The developed model is based on stochastic modelling using the concept of Generalized Stochastic Petri Nets which complex solution relies on Continuous Time Markov Chain. As a result, calculation of several performance measures is performed, such as: expected time spent in a transient tangible marking, cumulative sojourn time spent in a transient tangible marking, total number of visits in a transient tangible marking etc.