WoS İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394

Browse

Filters

20252

Settings

Has files: NoSubject: search.filters.subject.Airbnb

Search Results

Now showing 1 - 2 of 2
  • Article
    Citation - WoS: 5
    Citation - Scopus: 6
    Hedonic Price Models, Social Media Data and AI - An Application to the AirBNB Sector in US Cities
    (Elsevier Sci Ltd, 2025-09) Osth, John; Turk, Umut; Kourtit, Karima; Nijkamp, Peter
    The Airbnb sector has experienced exponential growth over the past decade and has led to extensive research in fields such as hospitality sciences, urban geography, tourism economics, and information management. This paper contributes to quantitative research in the Airbnb sector by focusing on the integration of digital platform data at the neighborhood level. It explores innovative methodologies for analyzing urban attractiveness by combining insights from hedonic pricing models with large-scale digital data sourced through AI-based approaches. This novel framework compares user-based valuations of accommodations derived from hedonic pricing with subjective, AI-generated neighborhood descriptions, offering new perspectives on data quality and reliability in information systems. The study also critically examines the challenges of integrating AI-generated content in information science, referencing also 'Garbage-in Garbage-out' and 'Bullshit-in Bullshit-out' concepts. Employing a multi-scalar modeling approach, the research examines Airbnb pricing dynamics across several U.S. cities, starting with Manhattan (USA) as an illustrative case. A subsequent large-scale application to additional metropolitan areas utilizes a combination of hedonic price modeling, social media data, and AI-generated urban descriptions, including a Shapley decomposition analysis. This interdisciplinary integration provides actionable insights into neighborhood attractiveness and pricing mechanisms, while highlighting methodological and empirical contributions to the broader field of information management. By employing the relationship between AI-driven textual data and quantitative modeling, this research provides added value in analyzing urban information systems and their application to digital platforms.
  • Article
    Citation - WoS: 5
    Citation - Scopus: 5
    A Digital 'Smiley Analysis of the Appreciation for Tourist Amenities by Visitors to London
    (Springer, 2025-03-28) Kourtit, Karima; Nijkamp, Peter; Osth, John; Turk, Umut
    Digital wellbeing research is on a rising edge. It is also increasingly applied in the hospitality sector to measure the satisfaction of visitors (metaphorically called here 'smileys'); understanding and enhancing visitor satisfaction are pivotal for the success of tourism destinations. This study seeks to identify critical factors influencing the visitors' appreciation for London, a city renowned for its allure, by harnessing available user data from Airbnb listings and hotels, using online reviews, with a particular view to the spatial pattern of visitors' choices in corona times. Advanced statistical techniques, including sentiment analysis, digital text analysis, multilevel analysis, and geographically weighted regression, are employed to discover geographical patterns as well as statistical correlations between land use, density, geographic location, and visitor contentment. The findings reveal that proximity to parks, accessibility to public transportation, and the presence of natural amenities exert substantial influence on visitor satisfaction in London. Especially, the proximity to a park enhances visitor satisfaction, predominantly in western London. Efficient access to public transportation in central areas of the city positively impacts visitor contentment levels as well. Furthermore, the availability of and accessibility to natural attractions in the southern and southwest areas of London appear to elevate visitor satisfaction. These novel insights empower destination managers, policymakers, and tourism stakeholders to make informed decisions, formulate targeted strategies, and enhance visitor experiences in specific London locales. The research highlights the importance of considering location-specific factors and customizing approaches to optimize the visitor appreciations for a city. By understanding the complex dynamics between land use, density, location, and visitor satisfaction, stakeholders can foster sustainable tourism growth and create a more appealing environment for visitors.