An Empirical User Study on Congestion-Aware Route Recommendation

Kun Yi, Xisha Jin (), Zhengyang Bai (), Yuntao Kong and Qiang Ma ()
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Kun Yi: Kyoto University
Xisha Jin: Kyoto University
Zhengyang Bai: RIKEN Center for Computational Science, RIKEN
Yuntao Kong: Japan Advanced Institute of Science and Technology
Qiang Ma: Department of Information Science, Kyoto Institute of Technology

A chapter in Information and Communication Technologies in Tourism 2024, 2024, pp 325-338 from Springer

Abstract: Abstract Overtourism has become a significant concern in many popular travel destinations around the world. As one of considerable approaches to handle the overtourism issues, congestion-aware methods can be effective in mitigating overcrowding at popular attractions by spreading tourists to less-visited areas. However, they may lead to a potential Hawk-Dove game: tourists who share the same preference may have some of them assigned worse routes than others to avoid congestion, which raises a possibility that the tourists who are assigned to relatively unfavorable routes may feel dissatisfaction and unfairness. Most existing research focuses on alleviating congestion from an overall planner perspective through simulation studies, with little emphasis on actual user experience. In this study, we conducted a user survey on congestion-aware route recommendation in Kyoto, Japan, aiming to investigate the evaluation of congestion-aware route recommendation methods from each tourist’s personal perspective and to clarify the development status and future research directions of congestion-aware route recommendation methods. We choose five congestion-aware route recommendation methods that vary in their consideration of congestion and multi-agent interactions. We reveal the strengths and weaknesses of these methods from multiple aspects. We cluster the respondents based on their text responses and explore the differences between these clusters. Furthermore, we investigate the factors affecting tourists’ experience and compare the differences among groups of tourists.

Keywords: User Study; Congestion-aware Route Recommendation; Selfish Tourists; Sustainable Tourism (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-031-58839-6_35

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DOI: 10.1007/978-3-031-58839-6_35

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