https://doi.org/10.1140/epjds/s13688-022-00354-6
Regular Article
Measuring sustainable tourism with online platform data
1
Trust in Digital Services, Technische Universität Berlin, 10623, Berlin, Germany
2
Oxford Internet Institute, University of Oxford, OX1 3JS, Oxford, UK
3
Datenwissenschaftliche Gesellschaft Berlin, 10117, Berlin, Germany
Received:
7
November
2021
Accepted:
11
June
2022
Published online:
18
July
2022
Sustainability in tourism is a topic of global relevance, finding multiple mentions in the United Nations Sustainable Development Goals. The complex task of balancing tourism’s economic, environmental, and social effects requires detailed and up-to-date data. This paper investigates whether online platform data can be employed as an alternative data source in sustainable tourism statistics. Using a web-scraped dataset from a large online tourism platform, a sustainability label for accommodations can be predicted reasonably well with machine learning techniques. The algorithmic prediction of accommodations’ sustainability using online data can provide a cost-effective and accurate measure that allows to track developments of tourism sustainability across the globe with high spatial and temporal granularity.
Key words: Sustainable tourism / Platform data / TripAdvisor / Nowcasting / Imbalanced classification / Supervised learning
© The Author(s) 2022
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