"Agent-based modelling and artificial intelligence to optimize digital visitor guidance (working title)"

The cumulative doctoral project will investigate the extent to which agent-based modeling can be used to predict visitor flows and how this modeling can be specifically optimized through the use of artificial intelligence.
The first publication will include a systematic literature review on the current state of research on agent-based modeling in tourism and its use for visitor guidance.

In the second paper, the technical status of agent-based modeling will be discussed in order to show how artificial intelligence can be used to improve this modeling. This could include aspects such as data preparation prior to modeling, optimizing the process to save computing capacity or applying algorithms to improve the model results.

The third publication will be dedicated to the practical application of the modeling, taking into account the findings from the second paper. The focus here is on evaluating the added value of this method for tourism research and practice. One possible application example could be the 2029 Federal Garden Show in the Upper Middle Rhine Valley, as it has a special geographical location that requires targeted visitor guidance.

Through this three-part structure, the doctoral project is intended to make a comprehensive contribution to the understanding of agent-based modeling in the context of digital visitor management and at the same time illustrate the benefits of artificial intelligence for optimizing these models. The findings from this research should help to improve the efficiency and effectiveness of visitor guidance strategies to ensure an optimal visitor experience in different tourist environments.

The doctoral project is being carried out at the Europa Universität Flensburg under the first supervision of Prof. Dr. Bernd Eisenstein and the second supervision of Prof. Dr. Julian Reif.