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Cited by 9Recommender Systems and TechniquesDiverse Aspects of Tourism ResearchEthics and Social Impacts of AI

Understanding User Perspectives on Sustainability and Fairness in Tourism Recommender Systems

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Banik, Paromita, Banerjee, Ashmi, Wörndl, Wolfgang·2023·Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization
DOI 10.1145/3563359.3597442
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Abstract

Recommender Systems (RS) are widely used in various domains, including travel and tourism, to provide personalized recommendations for accommodations, activities, and destinations. However, the evaluation of RS has traditionally focused on satisfying the needs of end users, item providers, or the recommendation platform itself without considering the impact on society. Sustainable tourism practices are becoming increasingly important, and a Tourism Recommendation System (TRS) can play a crucial role in promoting sustainability by suggesting sustainable activities and less popular destinations to users.

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Cited by

Sorted by citations

Authors
Banik, P., Banerjee, A., & Wörndl, W.
Affiliations
Technical University of Munich (DE)
ORCID
Venue
Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization
Publisher
ACM
Published
2023-06-16
Pages
241-248
DOI
10.1145/3563359.3597442
OpenAlex
W4380880026
Cited by
9
References
1
Citations by year
2026: 3 · 2025: 3 · 2024: 3
FWCI
2.32
Type
conference paper
Language
en
Open access
Licence
www.acm.org/publications/policies/copyright_policy#Background (vor)
Locations
ACM Conference on User Modeling, Adaptation and Personalization (UMAP) (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Recommender Systems and Techniques
  • Social Sciences › Sociology and Political Science › Diverse Aspects of Tourism Research
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
Keywords
tourism recommender systems, sustainable tourism, fairness, user perspective, recommendation evaluation

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