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Purpose This paper aims to provide a network study of the structural and dynamical characteristics of tourism flows in Europe from 1995 to 2012. Design/methodology/approach Travels in Europe were studied by following the network science research paradigm and by focusing on the whole network of intra-European tourism destinations. Network analysis was used to map and reveal the pattern of connections between states as shaped by bilateral tourism flows. Data were provided by the United Nations World Tourism Organization, and the data were integrated with tourism data available from national statistical offices of the individual countries, when necessary. Findings For 2012, results obtained from the UNWTO record-based network were compared to geo-located Twitter data as a proxy of human mobility patterns. The present analysis provides evidence of a shift towards an increased homogeneity in the travelling preferences of European tourists, an acquired attitude of visitors to travel shorter distances and a tendency of mobility patterns to merge. Finally, the comparison between UNWTO and Twitter data shows a different spatial distribution of visitors. These results provide a useful insight for policymakers involved in tourism planning. Originality/value The contribution of this study is threefold. First, to the best of the authors’ knowledge, this is the only study that focuses on the bilateral tourism flows between all countries falling, geographically or politically, under the definition of Europe. Second, evidence is provided of a shift towards a greater homogeneity in the travelling preferences of European tourists. Lastly, for the first time, this study provides a comparison between topological structure and bilateral mobility patterns of tourism flows, based on two different data-recording methods.

This study explores the correlation between human migration and that part of tourism due to people visiting \ud friends and relatives in a foreign country. We first compared the network structure of migration stocks and tourism flows between the 28 member countries of the European Union over the period 2000–2012. Then, we performed several econometric analyses to study the main tourism determinants and the correlations between migration to tourism. The paper derives from the discussion of the results an estimate of the contribution to the overall tourism phenomenon due to visiting friends and relatives. Complex network analysis and gravity models were the investigation methods preferred

This study explores the nexus between tourism and migration on an intra-European scale over the period 2000–2015. Complex-network analysis and gravity models were the investigation methods preferred. For each year under study, we built two country-to-country networks to map and reveal the connections between states as shaped by migration stocks and tourism flows, respectively. Then, the main determinants of the correlation patterns between the two networks were investigated by several econometric analysis. Results point to a quite similar topological structure for the tourism and migration networks as well as to a significant and reciprocal direct influence between tourism and migration movements inside the European Union. No relevant indirect causal relationship is present in the tourism–migration nexus instead.

This study provides an initial analysis of the key determinants of tourism in Sicily. In doing so, it responds to the general lack of a scientific approach in the study and management of tourism in Sicily. By mixing a gravity approach and system dynamics methodology, the attractiveness of Sicily is examined, taking into account both structural and promotional aspects that might affect tourism demand. The results strongly suggest that the island's natural and cultural resources, the road infrastructure and the urban environment are important determinants of tourism demand in Sicily. The findings may be useful for local authorities involved in the development of tourism, and represent a starting point for further research dealing with future trends.