Insights in a city through the eyes of Airbnb reviews: Sensing urban characteristics from homestay guest experiences

Wang, J.F.; Chow, Yoong Shin; Biljecki, Filip

doi:10.1016/j.cities.2023.104399

Cited by 7 publications

(2 citation statements)

References 43 publications

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“…These insights can be useful for distinguishing visitors' experiences and their levels of satisfaction. Online textual data are sourced from various platforms such as TripAdvisor [32,48,49], Booking [50], Expedia [51], and Airbnb [33]. As stated by Li et al [47], TripAdvisor stands out as one of the largest and the most popular tourism social media sources.…”

Section: Poi Definition With Location-based Datamentioning

confidence: 99%

“…Examining individuals' location choice behavior in real-world settings is critical for identifying actual tourist behavior, focusing on what tourists do rather than what they say they will do in a survey [24,25]. With the emergence of digital technologies, large volumes of data from GPS-enabled devices [26][27][28], data from volunteered geographic information (VGI) platforms, such as location-based social networks (i.e., Flickr and Instagram), and sharing platforms (i.e., Airbnb and Trip Advisor) [29][30][31][32][33][34] have become available and have been employed in studies to explain visitors' actual location choice behaviors in time and space. These studies demonstrate the potential of location-based data in revealing visitors' choice of Points of Interest (POIs), movement patterns between POIs, and their expressions of affective experiences about POIs.…”

Section: Introductionmentioning

confidence: 99%

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Analyzing the Influence of Visitor Types on Location Choices and Revisit Intentions in Urban Heritage Destinations

Karayazi,

Dane,

Arentze

2024

IJGI

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Understanding visitors’ spatial choice behavior is important in developing effective policies to counteract overcrowdedness in attractive urban heritage areas. This research presents a comprehensive analysis of visitor location choice behavior, aiming to address two primary objectives. First, this paper investigates the relationship between visitor segments and the choice of particular Points of Interest (POIs). Second, this paper explores the impacts of visitors’ experiences and visitor segments on their revisit intentions. We used a sample of 320 visitors who had been to Amsterdam within the last five years to collect data about their location choice behavior and intention to revisit after a recent visit to the city. Combining the revealed choices and intentions of pre-defined visitor segments obtained from a stated choice experiment, association rules are extracted to reveal differences in the patterns of behaviors related to the segment. The findings identify associations between various POIs, including museums such as the Rijksmuseum and Madame Tussauds, and visitor classes, which include “cultural attraction seekers”, “selective sightseers”, and “city-life lovers”. Furthermore, binary logistic regression analysis reveals that affective experiences, such as feelings of comfort, happiness, and annoyance, have a significant influence on visitors’ intentions to revisit the destination in the future. This research found that “cultural attraction seekers” and “selective sightseers” display a higher likelihood of considering a return visit to the city.

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