Modeling Sustainable City Trips: Integrating CO2e Emissions, Popularity, and Seasonality into Tourism Recommender Systems
<|reference_start|>Modeling Sustainable City Trips: Integrating CO2e Emissions, Popularity, and Seasonality into Tourism Recommender Systems: Tourism affects not only the tourism industry but also society and stakeholders such as the environment, local businesses, and residents. Tourism Recommender Systems (TRS) can be pivotal in promoting sustainable tourism by guiding travelers toward destinations with minimal negative impact. Our paper introduces a composite sustainability indicator for a city trip TRS based on the users' starting point and month of travel. This indicator integrates CO2e emissions for different transportation modes and analyses destination popularity and seasonal demand. We quantify city popularity based on user reviews, points of interest, and search trends from Tripadvisor and Google Trends data. To calculate a seasonal demand index, we leverage data from TourMIS and Airbnb. We conducted a user study to explore the fundamental trade-offs in travel decision-making and determine the weights for our proposed indicator. Finally, we demonstrate the integration of this indicator into a TRS, illustrating its ability to deliver sustainable city trip recommendations. This work lays the foundation for future research by integrating sustainability measures and contributing to responsible recommendations by TRS.<|reference_end|>
@article{banerjee2024modeling,
    title={Modeling Sustainable City Trips: Integrating CO2e Emissions, Popularity,
  and Seasonality into Tourism Recommender Systems},
    author={Ashmi Banerjee, Tunar Mahmudov, Emil Adler, Fitri Nur Aisyah, and
  Wolfgang W"orndl},
    journal={arXiv preprint arXiv:2403.18604},
    year={2024},
    archivePrefix={arXiv},
    eprint={2403.18604},
    primaryClass={cs.IR}
}