Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/337720 
Year of Publication: 
2022
Citation: 
[Journal:] Annals of Tourism Research Empirical Insights [ISSN:] 2666-9579 [Volume:] 3 [Issue:] 2 [Article No.:] 100061 [Year:] 2022 [Pages:] 1-12
Publisher: 
Elsevier, Amsterdam
Abstract: 
In this paper we aim to classify digital data sources for the measurement of tourist mobility, to establish a set of assessment indicators, and to compare two Big Data sources to gain empirical insights into how we can measure tourism with Big Data. For three holiday destinations in Germany, passive mobile data and passive global positioning systems (GPS) data are compared with reference data from the destinations for twelve weeks in the summer of 2019. Results show that mobile network data are on a plausible level compared to the local reference data and are able to predict the temporal pattern to a very high degree. GPS app-based data also perform well, but are less plausible and precise than mobile network data.
Subjects: 
Big Data
Mobile Network Data
Passive GPS Data
Spatio-temporal behaviour
Tourist classification
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article

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