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: 4Using Individualised HDI Measures for Predicting Educational Performance of Young Students-A Swedish Case Study(MDPI, 2021-05-28) Turk, Umut; Osth, John; Toger, Marina; Kourtit, KarimaHDI is a frequently used quantitative index of human potential and welfare, developed as a comprehensive measure for the cross-sectional and temporal comparison of socioeconomic performance. The HDI is a standardised quantitative estimation of welfare comprising indicators of health, knowledge and standard of living, enabling assessment over countries, regions or time periods, in case of limited data access. The index highlights critical conditions for equity and socioeconomic development outside the group of stakeholders and researchers. The HDI provides a learning potential that may be harnessed to enhance insights into the magnitude of human potential at super-local levels. In this paper we design, implement and test the validity of a super-local variant of HDI in the context of pedagogical performance of young pupils. We compare whether HDI is a good predictor for school grades among all ninth-grade students in Sweden during the year 2014. Our results show that a super-local HDI index is performing equal to or better than the one related to standard measures of human potential, while the index can be generated on individual levels using k-nearest neighbour approaches during the index creation process.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.Book Part The Geography of Daily Urban Spatial Mobility During COVID: The Example of Stockholm in 2020 and 2021(Springer Nature Switzerland Ag, 2023) Shuttleworth, Ian; Toger, Marina; Turk, Umut; Osth, JohnArticle 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: 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: 2Citation - Scopus: 2Rural Feet Voting of Leisure Explorers(Wiley, 2025-01) Turk, Umut; Toger, Marina; Osth, John; Kourtit, Karima; Nijkamp, PeterIn the COVID-19 period, spatial leisure behavior, often driven by the desire to escape urban life, reflected health and environmental concerns. This study examines how pandemic-induced spatial motives and changes impacted disparities in leisure mobility, specifically urban-to-rural tourism, in Sweden. Analyzing pre-pandemic, during pandemic, and post-pandemic periods, using anonymized mobile phone and socioeconomic data, the paper explores urban-rural leisure mobility variations. Despite a decline in professional geographical mobility, mainly of people in affluent urban areas, due to remote work, the spatial leisure activities remained rather stable? Our findings, based on a negative binomial regression analysis, reveal also exacerbated socioeconomic segregation in recreational trips. The disruption in mobility accessibility due to COVID-19 appears to amplify existing socioeconomic disparities, notably in urban-to-rural leisure travel. Our research sheds new light on the widening gap in geographical leisure activities, emphasizing the need for equitable access to nonurban destinations.Editorial Modelling Place Attractiveness in the Era of Big and Open Data Introduction(Wiley, 2022-08) Osth, John; Turk, Umut; Huang, JieArticle Citation - WoS: 20Citation - Scopus: 28Leisure Mobility Changes During the COVID-19 Pandemic- An Analysis of Survey and Mobile Phone Data in Sweden(Elsevier, 2023-06) Osth, John; Toger, Marina; Turk, Umut; Kourtit, Karima; Nijkamp, PeterThe COVID-19 pandemic affected travelling in general, and the leisure mobility and the spatial distribution of travellers in particular. In most parts of the world, both domestic and international travel has been replaced by restrictive policies and recommendations on mobility. A modal shift from public transport towards private cars and micro-mobility was also observed. This study seeks to trace the implications of the COVID-19 pandemic for leisure mobility. We use a unique Swedish database containing daily mobility patterns of pseudonymised mobile phone users, combined with a survey on vacation transport behaviour. By contrasting mobility patterns for selected holiday days during the unaffected summer of 2019 with corresponding dates in 2020 and 2021, we are able to model and detect the pandemic effects on tourism and recreational mobility. Moreover, by identifying the general mobility patterns, we analyse whether and how the transport mode has changed. Using data on the spatial distribution of recreational amenities, we identify locations that were favoured during the pandemic. In Sweden, even though the pandemic decreased in spread and severity during the summers, most travel restrictions were still enforced, international vacations uncommon, and larger vacation spots, such as amusement parks and cultural institutions, were closed down. Swedish vacation homes in remote or rural areas were quickly booked. This change in recreational behaviour, where less populated areas, open air and nature recreation were favoured over indoor or crowded urban cultural activities, was more substantial in 2021 than in 2020. This result shows how policies can effectively be developed, so that Swedes respond properly to recommendations and adjust their vacation plans.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: 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.