Tourism flows in large-scale destination systems

Large-scale destination systems, especially cross-border regions are less studied in literature as their size and transnational nature makes these hard to analyse with traditional methods. Tourism systems like the Danube Region are composed of several local and regional destinations, and even when these are branded together for tourists the integration of these into one system is often compromised by national boundaries and socio-economic differences. This study shows how the Danube region is composed of different clusters of destinations, and how national boundaries have a strong shielding effect in the interregional movements of tourists. A methodology based on network analysis with efficient clustering algorithms applied on large geotagged datasets from User Generated Content is proposed. Flickr data was used to map short time-interval visitor flows along the linear system of the river Danube. 18 regional clusters integrated into 3 strong, but separated destination systems were identified by modularity analysis. The central integrating effect of the large capital cities and the boundary-shielding effect impeding the total integration of this large-scale system were made measurable.