WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Citation - WoS: 2Citation - Scopus: 2Slow Motion in Corona Times: Modeling Cyclists' Spatial Choice Behavior Using Real-Time Probe Data(Univ Minnesota, Center Transportation Studies, 2024-11-11) Kourtit, Karima; Osth, John; Nijkamp, Peter; Turk, UmutThe recent COVID-19 pandemic has provided a renewed impetus for empirical research on slow and active modes of transportation, specifically bicycling and walking. Changes in modal choice appear to be sensitive to the actual quality of the environment, the attractive land use and built environment conditions, and the ultimate destination choice. This study examines and models the influence of cyclists' health concerns during the pandemic on their spatial destination and route choices. Using a large real-time dataset on the individual daily mobility of cyclists in the province of Utrecht, the Netherlands, collected through GPS-linked sensors on bikes (VGI, or volunteered geographical information), the analysis employs spatial regression models, Shapley decomposition techniques, and spatial autocorrelation methods to unveil the backgrounds of changes in spatial behavior. The results reveal that the perceived wellbeing benefits of bicycling in green areas during the pandemic have significantly influenced cyclists' choice behavior, in particular route and destination choice.Article Citation - WoS: 1Citation - Scopus: 2Is Artificial Intelligence a Trustworthy Route Navigation System for Smart Urban Planning(Univ Alexandru Ioan Cuza, Centrul Studii Europene, 2024) Kourtit, Karima; Nijkamp, Peter; Osth, John; Turk, UmutIn the age of smart or intelligent cities, the use of Artificial Intelligence (AI) presents a spectrum of new opportunities and challenges for both the research and policy community. The present study explores the intricate interplay between AI-generated content and actual choice spectra in urban planning. It focuses on the concept of 'city intelligence' and related AI concepts, underscoring the pivotal role of AI in addressing and understanding the quality of life in contemporary urban environments. As AI continues its transformative impact on communication and information systems in the realm of urban planning, this study brings to the forefront key insights into the challenges of validating AI-based information. Given the inherently subjective nature of AIgenerated content, and its influential role in shaping user-perceived value, AI will most likely be a game changer catalyzing enhancements in the urban quality of life and inducing favorable urban developments. Additionally, the study also addresses the significance of the so-called 'Garbage-in Garbage-out' (GiGo) principle and 'Bullshitin Bullshit out' (BiBo) principle in validating AI-generated content, and seeks to enhance our understanding of the spatial information landscape in urban planning by introducing the notion of an urban X'XQ' performance production function.Article Citation - WoS: 5Citation - Scopus: 6Hedonic 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, PeterThe 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: 1Citation - Scopus: 3Effects of External Shocks on the AirBNB Market - Modeling Business Survival Using Geocoded Open Data(Routledge Journals, Taylor & Francis Ltd, 2024-12-11) Turk, Umut; Osth, John; Kourtit, Karima; Nijkamp, PeterThis paper seeks to trace the determinants of business survival in the Airbnb market during the latest pandemic. The paper starts with an examination of the key factors determining survival rates of accommodation listings in the Airbnb market during the early shock phase of the pandemic. The analysis is carried out for 10 metropolitan cities all over the world in both 2019 and 2020, so as to investigate the differences in survival probabilities between the pre- and early-pandemic period. We also study the dynamics of the Airbnb market in the late pandemic period using a multinomial logistic regression model. The results show similar patterns as the pre- and early-pandemic periods, indicating a tendency to return to a pre-pandemic state. In particular, in the pandemic time analyses, distance to nature appeared to be positively associated with firm survival, suggesting the importance of a healthy environment for attracting guests during this period. The findings contribute to our understanding of the effects of the pandemic on short-term rental and highlight the role of various critical background factors.Article Citation - WoS: 5Citation - Scopus: 5A Digital 'Smiley Analysis of the Appreciation for Tourist Amenities by Visitors to London(Springer, 2025-03-28) Kourtit, Karima; Nijkamp, Peter; Osth, John; Turk, UmutDigital 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.