A Socially Motivating and Environmentally Friendly Tour Recommendation Framework for Tourist Groups

Kargar, M.; Lin, Z.

Abstract

Traveling in a group brings various social and environmental benefits, yet members might have different (and sometime conflicting) preferences. In this study, a tour recommendation framework is proposed that receives a set of must-visit and preferred points of interest from each tourist and forms multi-day tours that cover all must-visit points. Furthermore, the framework attempts to maximize fairness among group members. This ensures all members are motivated to participate in the group tour. While generating the itinerary, the framework also guarantees that a threshold on the commuted distance, time, and monetary budget is met on each day. The benefits of this approach are the maximization of social wellbeing and minimization of energy consumption. The advantages of the proposed framework are confirmed via a test using a Foursquare dataset of two major cities of New York and Tokyo and a user study.

Citation

Kargar, M., & Lin, Z. (2021). A Socially Motivating and Environmentally Friendly Tour Recommendation Framework for Tourist Groups. Expert Systems with Applications, 180, Article 115083. https://doi.org/10.1016/j.eswa.2021.115083

• Journal Article Type: Article
• Acceptance Date: Apr 17, 2021
• Online Publication Date: Apr 29, 2021
• Publication Date: Oct 15, 2021
• Deposit Date: Apr 19, 2021
• Publicly Available Date: Apr 29, 2023
• Journal: Expert Systems with Applications
• Print ISSN: 0957-4174
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 180
• Article Number: 115083
• DOI: https://doi.org/10.1016/j.eswa.2021.115083
• Public URL: https://durham-repository.worktribe.com/output/1244195