WoS İndeksli Yayınlar Koleksiyonu

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

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Author: search.filters.author.Turk, UmutPublisher: search.filters.publisher.Elsevier Sci Ltd

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Now showing 1 - 7 of 7
  • Article
    Citation - WoS: 22
    Citation - Scopus: 31
    The Path of Least Resistance Explaining Tourist Mobility Patterns in Destination Areas Using AirBNB Data
    (Elsevier Sci Ltd, 2021-06) Turk, Umut; Osth, John; Kourtit, Karima; Nijkamp, Peter
    Destination attractiveness research has become an important research domain in leisure and tourism economics. But the mobility behaviour of visitors in relation to local public transport access in tourist places is not yet well understood. The present paper seeks to fill this research gap by studying the attractiveness profile of 25 major tourist destination places in the world by means of a 'big data' analysis of the drivers of visitors' mobility behaviour and the use of public transport in these tourist places. We introduce the principle of 'the path of least resistance' to explain and model the spatial behaviour of visitors in these 25 global destination cities. We combine a spatial hedonic price model with geoscience techniques to better understand the place-based drivers of mobility patterns of tourists. In our empirical analysis, we use an extensive and rich database combining millions of Airbnb listings originating from the Airbnb platform, and complemented with TripAdvisor platform data and OpenStreetMap data. We first estimate the effect of the quality of the Airbnb listings, the surrounding tourist amenities, and the distance to specific urban amenities on the listed Airbnb prices. In a second step of the multilevel modelling procedure, we estimate the differential impact of accessibility to public transport on the quoted Airbnb prices of the tourist accommodations. The findings confirm the validity of our conceptual framework on 'the path of least resistance' for the spatial behaviour of tourists in destination places.
  • Article
    Citation - WoS: 9
    Citation - Scopus: 13
    Student Performance Under Asynchronous and Synchronous Methods in Distance Education: A Quasi-Field Experiment
    (Elsevier Sci Ltd, 2022-11) Demirtas, Burak Kagan; Turk, Umut
    This study examines student performance under asynchronous and synchronous methods in a microeconomics course during COVID-19 pandemic. We conduct a quasi-field experiment in a state university in Turkey. In the experiment, students were divided into synchronous and asynchronous groups and were taught the same weekly material of microeconomics by the methods respective to their group. At the end of the week, both groups took the same multiple question test. Our results showed that asynchronous group performed significantly better than the synchronous group. While showing the comparative advantage of the asynchronous method, our study also underlines the importance of interaction between instructors and students. We discuss our findings from a socioeconomic perspective, where we argue that the flexibility that the asynchronous method offers might have compensated for the accessibility issues (internet and/or computer) during the COVID-19 outbreak. As a policy recommendation, universities can offer lectures with a recorded option to allow students to interact with the course material multiple times.
  • Article
    Citation - WoS: 2
    Citation - Scopus: 2
    Route Choice to Inform Navigation System Design and Accessibility Analysis for Older Pedestrians: A Scoping Review
    (Elsevier Sci Ltd, 2025-10) Fulman, Nir; Huber, Johannes; Lloyd, Armagan Teke; Foshag, Kathrin; Grinblat, Yulia; Turk, Umut; Zipf, Alexander
    Introduction: Routing systems can support older adults by helping them overcome barriers to walking, promoting independence and well-being. The paths generated by these systems also inform urban accessibility metrics, such as those used in 15-min-city planning. Yet current systems rarely reflect the preferences or constraints of older pedestrians. Empirical studies of route choice can help close this gap by revealing how people trade off different route attributes in real settings. Methods: We conducted a scoping review, following PRISMA-ScR guidelines, of empirical studies analyzing pedestrian route choice among adults. The goal was to identify findings that could inform the design of more age-inclusive routing tools. Results: Eleven studies met the inclusion criteria, eight of which focused exclusively on older adults. Despite varied contexts, three consistent themes emerged: (i) sidewalk quality and manageable gradients; (ii) aesthetic and sensory comfort, including greenery, low noise, and good lighting; and (iii) access to benches, transit, and everyday amenities. However, most studies relied on qualitative methods, limiting direct integration into routing algorithms. Conclusions: Future work should prioritize hybrid qualitative-quantitative designs, large-scale sampling of routes, and fine-grained mapping of micro-barriers. Analyses should account for age, gender, and functional ability, and consider circular leisure walks as a distinct travel pattern. These directions can enhance the usability and equity of routing systems and urban planning frameworks.
  • Article
    Citation - WoS: 13
    Citation - Scopus: 16
    Inequality in Leisure Mobility: An Analysis of Activity Space Segregation Spectra in the Stockholm Conurbation
    (Elsevier Sci Ltd, 2023-07) Toger, Marina; Turk, Umut; Osth, John; Kourtit, Karima; Nijkamp, Peter
    Leisure mobility forms an important part of people's spatial activity and mobility spectrum. This study aims to analyse the inequality dimensions of spatial mobility of individuals who seek to move to recreational and leisure destinations (often 'green' and 'blue') on designated days. The study traces - through the use of spatially dependent multilevel models - the mobility patterns of people from the greater Stockholm area, using individual pseudonymised mobile phone data and other publicly accessible data. We find significant socio-demographic inequalities in the observed residents' spatial leisure choices, where less affluent groups display especially low variation in mobility when comparing between weekdays, weekends, vacation season and work-periods.
  • 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: 10
    Citation - Scopus: 11
    Cities as Drivers of Social Mobility
    (Elsevier Sci Ltd, 2021-01) Michelangeli, Alessandra; Turk, Umut
    The paper studies the role of cities in enhancing intergenerational social mobility. Cities, where children grew up, can provide resources and opportunities able to increase the chance of employment and status attainment. We assess intergenerational mobility in Italy, the most immobile country in Europe together with Greece and Portugal. We use a data survey providing information on the individual-level track of Italian students' life path from high school to occupation. We merge the data survey with city-level information on socio-economic conditions. We distinguish between students who attended university in the same city where they grew up and those who migrated to another city for higher education. Upward mobility turns out to be higher in: (i) larger cities by population size; (ii) more accessible cities; (iii) cities with low income inequality and high education levels. Also social values and cultural traits play a role in enhancing upward mobility. More generally, if we look at the bundle of factors identifying the urban context, we find that the effect of factors with a positive impact on upward mobility prevails in the Northern cities while the opposite occurs in the Southern cities.
  • Article
    Citation - WoS: 35
    Citation - Scopus: 41
    AirBNB and COVID-19: Space-Time Vulnerability Effects in Six World-Cities
    (Elsevier Sci Ltd, 2022-12) Kourtit, Karima; Nijkamp, Peter; Osth, John; Turk, Umut
    This study examines the COVID-19 vulnerability and subsequent market dynamics in the volatile hospitality market worldwide, by focusing in particular on individual Airbnb bookings-data for six world-cities in various continents over the period January 2020-August 2021. This research was done by: (i) looking into factual survival rates of Airbnb accommodations in the period concerned; (ii) examining place-based impacts of intracity location on the economic performance of Airbnb facilities; (iii) estimating the price responses to the pandemic by means of a hedonic price model. In our statistical analyses based on large volumes of time- and space-varying data, multilevel logistic regression models are used to trace `corona survivability footprints' and to estimate a hedonic price-elasticity-of-demand model. The results reveal hardships for the Airbnb market as a whole as well as a high volatility in prices in most cities. Our study highlights the vulnerability and `corona echoeffects' on Airbnb markets for specific accommodation segments in several large cities in the world. It adds to the tourism literature by testing the geographic distributional impacts of the corona pandemic on customers' choices regarding type and intra-urban location of Airbnb accommodations.