Title: Analysing spatiotemporal patterns of tourism in Europe at high-resolution with conventional and big data sources
Authors: BATISTA E SILVA FILIPEMARÍN HERRERA MARIO ALBERTOROSINA KONSTANTINRIBEIRO BARRANCO RICARDOCARNEIRO FREIRE SERGIO MANUELSCHIAVINA MARCELLO
Citation: TOURISM MANAGEMENT vol. 68 p. 101-115
Publisher: ELSEVIER SCI LTD
Publication Year: 2018
JRC N°: JRC108661
ISSN: 0261-5177
URI: https://www.sciencedirect.com/science/article/pii/S026151771830044X
http://publications.jrc.ec.europa.eu/repository/handle/JRC108661
DOI: 10.1016/j.tourman.2018.02.020
Type: Articles in periodicals and books
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.
JRC Directorate:Growth and Innovation

Files in This Item:
There are no files associated with this item.


Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.