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Analysing spatiotemporal patterns of tourism in Europe at high-resolution with conventional and big data sources

Tourism ManagementPublished 18 March 2018Open access
Filipe Batista e Silva, Mario Alberto Marín Herrera, Konštantín Rosina, Ricardo Barranco, Sérgio Freire, Marcello Schiavina
Citations229
SJR quartileQ1
SJR score4.15
SNIP3.74
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Abstract

Available statistics on tourism from official European sources are limited in terms of both the spatial and temporal resolutions, curbing potential analyses and applications relevant for tourism management and policy. In this study, we produced a novel, complete and consistent dataset describing tourist density at high spatial resolution with monthly breakdown for the whole of the European Union. This is achieved thanks to the integration of data from conventional statistical sources with big data from emerging sources, namely two major online booking services containing the precise location and capacity of tourism accommodation establishments. The produced dataset allowed us to uncover key spatiotemporal patterns of tourism in Europe at unprecedented detail, showcasing the usefulness of complementing official statistical data with emerging big data sources.

Keywords

Social Sciences