WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Citation - WoS: 22Citation - Scopus: 31The 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, PeterDestination 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: 7Citation - Scopus: 8The Effect of Lockdown on Students' Performance: A Comparative Study Between Italy, Sweden and Turkey(Cell Press, 2023-06) Casalone, Giorgia; Michelangeli, Alessandra; Osth, John; Turk, UmutDuring the first months of the COVID-19 outbreak, countries adopted different strategies in order to mitigate the effects of the pandemic, ranging from recommendations to limit individual movement to severe lockdown measures. Regarding higher education, university studies were shifted to digital solutions in most countries. The sudden move to online teaching affected stu-dents differently, depending on the overall mitigation strategies applied. Severe lockdown and closure measures caused a disruption of their academic and social interactions. In contrast, rec-ommendations to limit activities probably did not change students' life to a great extent. The heterogeneity of the policies adopted in three countries (Italy, Sweden and Turkey) gives us an opportunity to assess the effects of lockdown measures due to the COVID-19 pandemic on uni-versity students' performance. We employ a difference-in-differences approach by exploiting the fact that Italy and Turkey experienced national lockdowns, while Sweden never applied nation-wide mandatory restrictive policies. We use administrative data from universities in the three countries to estimate the probability to pass exams after the spread of COVID-19 pandemic (and the shift to distance education), with respect to the previous comparable period. We find that the pass rate decreased with the shift to online teaching. However, lockdown measures, especially if very restrictive as those applied in Italy, helped to compensate such negative effect. A possible explanation is that students took advantage of the huge increase in the time available for their studies, given the impossibility to carry out any activity outside the home.Article Citation - WoS: 9Citation - Scopus: 13Student Performance Under Asynchronous and Synchronous Methods in Distance Education: A Quasi-Field Experiment(Elsevier Sci Ltd, 2022-11) Demirtas, Burak Kagan; Turk, UmutThis 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.Editorial Citation - WoS: 1Citation - Scopus: 2Special Issue on The City 2.0 - Smart People, Places and Planning(Elsevier, 2022-06) Nijkamp, Peter; Kourtit, Karima; Turk, UmutArticle Citation - WoS: 6Citation - Scopus: 8Introducing a Spatially Explicit Gini Measure for Spatial Segregation(Springer Heidelberg, 2023-06-14) Turk, Umut; Osth, JohnThis paper proposes an alternative measure of economic segregation by income that utilizes the Gini index as the basis of measurement. The Gini Index of Spatial Segregation (GSS) is a ratio of two Gini indices that compares the inequality between neighbourhoods to the inequality between individuals at the macro-level where neighbourhoods are nested. Unlike earlier measures of segregation found in the literature, the GSS uses individualized neighbourhoods, which can be defined as an area constituted within a radius or as a population count method around an individual geo-location, depending on the population density and proximity among individuals in the study area. The GSS can measure residential segregation by any continuous variable for both radii and k-nearest neighbours (knn with and without a decay factor) approaches to bespoke neighbourhoods. Therefore, it is sensitive to the spatial configuration of the area, easy to compute and interpret, and suitable for comparative studies of segregation over time and across different contexts. An empirical application of the index is illustrated using data from Sweden that covers the entire population for 1994, 2004, and 2014. We demonstrate how the definition and scale of the neighbourhood influence the measures of economic segregation. Overall, the GSS offers a flexible and robust framework for measuring segregation that can be used to inform policy decisions and research on inequality.Article Citation - WoS: 13Citation - Scopus: 16Inequality 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, PeterLeisure 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: 3Citation - Scopus: 3Inequality in Access to Urban Amenities(Springernature, 2025-07-12) Michelangeli, Alessandra; Osth, John; Toger, Marina; Turk, UmutThis paper provides an overview of urban inequality in the Stockholm Metropolitan Area analyzing the spatial distribution of amenities and their accessibility. Inequality in urban amenities is measured by a multidimensional index at a fine geographical scale and it can be decomposed into the sum of inequality indices computed on the marginal distributions of amenities across locations plus a residual term accounting for their joint distribution. Our research leverages a unique dataset that combines income data for approximately 90,000 geocoded individuals residing in the metropolitan area with information from the OpenStreetMap platform, enabling us to examine the distribution of both natural and urban design-related amenities. Furthermore, we integrate data from online platforms to analyze the housing market. Our findings reveal moderate levels of inequality in amenities within the Stockholm Metropolitan Area, with social segregation emerging as the primary driver of this inequality.Article Citation - WoS: 14Citation - Scopus: 18How Much Does Geography Contribute? Measuring Inequality of Opportunities Using a Bespoke Neighbourhood Approach(Springer Heidelberg, 2019-03-30) Turk, Umut; Osth, JohnTo what extent an individual is successful in a variety of outcomes is the result of multiple factors such as (but not limited to) parental background, level of education, discrimination and business cycles. Factors like these also indicate that the success in life can be attributable to factors that both take individual-level merits into account but also to structural factors such as discrimination and contextual effects. Over the last decades, a growing interest in decomposing and categorising factors that affect the life chances of individuals has led to the formation of inequality of opportunity as a research field. This paper builds upon this growing literature, which amounts to quantify the contribution of factors that lie beyond the control of individuals to the total inequality observed in different spheres of life. Using rich Swedish longitudinal register data, we are able to follow individuals over time and their educational attainment during upbringing and later labour market outcomes. In difference from other inequality of opportunity studies, we make use of an egocentric neighbourhood approach to integrate the socio-economic composition of the parental neighbourhood in an inequality model and illustrate its contribution to the total inequality in both outcomes quantitatively. Using multilevel regression analyses, we show that the parental neighbourhood is highly influential in educational attainment and remains so for market outcomes even years after exposure.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.