Measuring sustainable tourism with online platform data
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
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
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