Framework for simulating random clickstream data

Improving e-store productivity requires well designed algorithms that are efficient in modelling the online behaviour of customers. However, due to competitive pressures and privacy concerns, e-commerce data is often not readily available to researchers. As a result, the pace of innovation for e-store design and applications is restricted. As a solution, this research develops a framework for generating random clickstream data representing online behaviour of visitors to an e-store. The framework is implemented into a discrete-event simulator that models a hypothetical e-store. Key outcomes from the research are the development of the simulator, the structure of the e-store, the parameterisation used to model the e-store and visitors, and the implementation of automated sales agents. The generated clickstream data was verified to represent what one expects from a real e-store.