Using big data to measure cultural tourism in Europe

Karol Borowiecki, Maja U Pedersen and Sara Beth Mitchell

Tourism Economics, 2025, vol. 31, issue 3, 477-503

Abstract: International tourism statistics are notorious for being overly aggregated, lacking in detailed tourist information, not timely, and often provided only on an annual basis. We suggest a unique, complementary data-driven approach relying on big data collected from Tripadvisor. We obtain a systematic, consistent, and reliable approximation for tourism flows, with high precision, frequency, and depth of information. The approach provides also a list of all tourist attractions in a country. We validate the approach pursued and present one application of the data by illuminating the patterns and changes in travel flows in selected European destinations during and after the COVID-19 pandemic. This project opens a range of new research questions and possibilities for tourism economics and cultural economics.

Keywords: big data; COVID-19; cultural heritage; tourism; J60; L83; O1; Z11; Z3 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:sae:toueco:v:31:y:2025:i:3:p:477-503

DOI: 10.1177/13548166241273604

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