Measuring sustainable tourism with online platform data.

Imbalanced classification Nowcasting Platform data Supervised learning Sustainable tourism TripAdvisor

Journal

EPJ data science
ISSN: 2193-1127
Titre abrégé: EPJ Data Sci
Pays: Germany
ID NLM: 101686785

Informations de publication

Date de publication:
2022
Historique:
received: 07 11 2021
accepted: 11 06 2022
entrez: 25 7 2022
pubmed: 26 7 2022
medline: 26 7 2022
Statut: ppublish

Résumé

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. The online version contains supplementary material available at 10.1140/epjds/s13688-022-00354-6.

Identifiants

pubmed: 35873664
doi: 10.1140/epjds/s13688-022-00354-6
pii: 354
pmc: PMC9289659
doi:

Types de publication

Journal Article

Langues

eng

Pagination

41

Informations de copyright

© The Author(s) 2022.

Déclaration de conflit d'intérêts

Competing interestsThe authors declare that they have no competing interests.

Références

Euro Surveill. 2010 Jul 29;15(30):
pubmed: 20684815
Science. 2014 Mar 14;343(6176):1203-5
pubmed: 24626916
J R Soc Interface. 2017 Feb;14(127):
pubmed: 28148765
J Big Data. 2021;8(1):105
pubmed: 34367876

Auteurs

Felix J Hoffmann (FJ)

Trust in Digital Services, Technische Universität Berlin, 10623 Berlin, Germany.

Fabian Braesemann (F)

Oxford Internet Institute, University of Oxford, OX1 3JS Oxford, UK.
Datenwissenschaftliche Gesellschaft Berlin, 10117 Berlin, Germany.

Timm Teubner (T)

Trust in Digital Services, Technische Universität Berlin, 10623 Berlin, Germany.

Classifications MeSH