Using big data to measure cultural tourism in Europe
Year: 2024
Type: article
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.
Source: Tourism Economics
Institution: University of Southern Denmark
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W4401997117