Abstract The article examines how organisational and structural configurations shape the quality of administrative decision-making in European asylum offices. Drawing on fuzzy-set Qualitative Comparative Analysis (fsQCA) of 27 cases across nine countries between 2010 and 2022, it analyses variation in administrative decision-making quality using judicial overturn rates as a proxy. The findings show that variation and fluctuation in decision-making quality is best explained by specific combinations of organisational and structural conditions rather than by single factors such as application pressure or professional capacity alone. Higher quality emerges through a limited number of conjunctural pathways in which greater administrative insulation from political influence or lower application pressure function as enabling conditions. Organisational experience and caseworker competence contribute to quality only when embedded in supportive institutional settings. Overall, the findings indicate that differences in decision-making quality stem from asylum offices’ varying capacity to manage political and workload pressures.
Many cities promote walkability through concepts such as the compact city and 15-minute city to enhance urban livability, yet few methods link spatial walkability features to empirically measured livability and account for temporal dynamics. The method developed for this study uses mobile phone data from the Helsinki Metropolitan Area (Finland) to assess whether commonly used, literature-derived livability indicators (diversity, density, proximity, accessibility) predict observed human activity patterns across different times of day. We constructed two key dimensions of livability: attractiveness and walkability with quantifiable sub-indicators that were selected based on literature. Our analysis shows that walkability, and even more so the combined livability index, correlates with activity patterns, outperforming the pure attractiveness perspective. However, this relationship is temporally unstable, significantly weakening at night and fluctuating daily. Moreover, based on Geographically Weighted Regression analysis, our results reveal significant spatial variation in the relationship between livability and the intensity of human activities. The findings suggest that traditional urban planning goals, such as functional diversity to enhance walkability, contribute to livability but have a limited impact on the 15-minute city's overall sustainable mobility objectives, necessitating a larger-scale perspective and more functionally profiled approaches for urban development.
Abstract Opposition against refugees and migrants is a central topic of the populist far-right’s political agenda. In Italy, the populist far-right has come to lead the national government with the Meloni government. In this scenario, this article identifies what can be defined as the “populist far right paradox”: how to maintain the electoral commitment of rigid closure towards immigrants and refugees, in the presence of interests and pressures that instead require openness. This general question generates three sub-questions. First of all, in which ways, once in government, does the populist far-right try to keep its promises to block immigration? Secondly, how do they manage to navigate between different needs and pressures, which for different reasons require an openness to new entries of people from abroad? Third, how the Meloni government relates with the EU policies?
Abstract This short intervention starts from observing a persistent, if not growing, framing of migration research – in CMS and beyond - through a concept of crisis. We contend that such an unreflexive framing, or what we call ‘crisisology’, is deeply problematic due to the reproduction of a highly skewed and binary understanding of migration. We argue that a more spatially and temporally relational approach is needed in order to dismantle such binarism. In making our argument, we first review existing critical and reflexive research on migration and crisis, while pointing out the ongoing limitations, or blind spots, of this work in moving beyond crisisology. We conclude by briefly outlining what a spatio-temporally relational approach to studying migration and ‘crisis-ness’ would entail thematically, methodologically, and conceptually.
Despite the evident drawbacks, car ownership and usage continue to rise globally, leading to increased pollution and urban sprawl. As alternatives, Active Mobility and Public Transport are promoted for their health, economic, and environmental benefits. However, the efficiency of Public Transport varies widely. Metro systems, in particular, offer a high-capacity, long-distance solution, but they are expensive and only found in a limited number of cities. Trams, on the other hand, may serve as a substitute. This study compares the modal share in European cities, analysing the differences between those that have a metro, a tram, or neither. The analysis draws on a comprehensive dataset from CitiesMoving.com, which compiles and harmonises mobility surveys from around the world according to the ABC framework (A for Active mobility, B for Bus and other forms of Public Transport, and C for Cars). Findings reveal that cities with a metro have a significantly lower share of car journeys than those with only a tram or no rail system.
Understanding how urban systems and traffic dynamics co-evolve is crucial for advancing sustainable and resilient cities. However, their bidirectional causal relationships remain underexplored due to challenges of simultaneously inferring spatial heterogeneity, temporal variation, and feedback mechanisms. To address this gap, we propose a novel spatio-temporal causality framework that bridges correlation and causation by integrating spatio-temporal weighted regression with a newly developed spatio-temporal convergent cross-mapping approach. Characterizing cities through urban structure, form, and function, the framework uncovers bidirectional causal patterns between urban systems and traffic dynamics across 30 cities on six continents. Our findings reveal asymmetric bidirectional causality, with urban systems exerting stronger influences on traffic dynamics than the reverse in most cities. Urban form and function shape mobility more profoundly than structure, even though structure often exhibits higher correlations, as observed in cities such as Singapore, New Delhi, London, Chicago, and Moscow. This does not preclude the reversed causal direction, whereby long-established mobility patterns can also reshape the built environment over time. Finally, we identify three distinct causal archetypes: tightly coupled, pattern-heterogeneous, and workday-attenuated, which map pathways from causal diagnosis to intervention. This typology supports city-to-city learning and lays a foundation for context-sensitive strategies in sustainable urban and transport planning.
Abstract The massive increase in labor migration to the Middle East during the past three decades has rivaled its historical trends bound to the West. This paper assesses how this growing trend of migration may have helped shape the economic structure and performance across the member countries of the Gulf Cooperation Council. Findings from a descriptive and time series regression analysis of the limited cross-country data show that the experience with labor migration and its linkage with other aspects of the economy are varied. The migration trend coinciding with increasing personal remittances attests to the competitive demand for foreign labor. While labor migration shows mixed association with the key aspects of the economy, the stock of migrant population is negatively associated with economic growth. Albeit seemingly contradictory, the insights from this six-country analysis covering the periods since 1990 are useful to understand the complex nature of relationship between labor migration and economic structure and performance in the region.
Jebran Khan, Kashif Ahmad, Senthil Kumar Jagatheesaperumal
et al.
In the modern world, our cities and societies face several technological and societal challenges, such as rapid urbanization, global warming & climate change, the digital divide, and social inequalities, increasing the need for more sustainable cities and societies. Addressing these challenges requires a multifaceted approach involving all the stakeholders, sustainable planning, efficient resource management, innovative solutions, and modern technologies. Like other modern technologies, social media informatics also plays its part in developing more sustainable and resilient cities and societies. Despite its limitations, social media informatics has proven very effective in various sustainable cities and society applications. In this paper, we review and analyze the role of social media informatics in sustainable cities and society by providing a detailed overview of its applications, associated challenges, and potential solutions. This work is expected to provide a baseline for future research in the domain.
Laboni Paul, Rahul Deb Mohalder, Kazi Masudul Alam
The population of the urban areas is increasing daily, and this migration is causing serious environmental pollution. A larger population is creating pressure on the municipality's waste management and the city corporations of developing countries such as Bangladesh, further threatening human health. New generation technologies, such as the Internet of Things (IoT)-based waste management systems, can help improve this serious issue. IoT-enabled smart dustbins and mobile applications-based interactive management can effectively solve this problem. In this article, we combine these two technologies to offer an acceptable solution to this problem. The proposed waste management model enables smart dustbins to communicate with waste collectors or waste control centers whenever it is necessary. Additionally, city dwellers can use mobile applications to report their observations in their neighborhoods. As a result, both sensors and humans are involved directly in the development loop. We have conducted a detailed survey to study the acceptance of such a system in the community and received some encouraging results.
Luiza Lober, Kirstin O. Roster, Francisco A. Rodrigues
Supervised machine learning models and public surveillance data has been employed for infectious disease forecasting in many settings. These models leverage various data sources capturing drivers of disease spread, such as climate conditions or human behavior. However, few models have incorporated the organizational structure of different geographic locations for forecasting. Traveling waves of seasonal outbreaks have been reported for dengue, influenza, and other infectious diseases, and many of the drivers of infectious disease dynamics may be shared across different cities, either due to their geographic or socioeconomic proximity. In this study, we developed a machine learning model to predict case counts of four infectious diseases across Brazilian cities one week ahead by incorporating information from related cities. We compared selecting related cities using both geographic distance and GDP per capita. Incorporating information from geographically proximate cities improved predictive performance for two of the four diseases, specifically COVID-19 and Zika. We also discuss the impact on forecasts in the presence of anomalous contagion patterns and the limitations of the proposed methodology.
The field of Intelligent Transportation Systems (ITS) relies on accurate traffic forecasting to enable various downstream applications. However, developing cities often face challenges in collecting sufficient training traffic data due to limited resources and outdated infrastructure. Recognizing this obstacle, the concept of cross-city few-shot forecasting has emerged as a viable approach. While previous cross-city few-shot forecasting methods ignore the frequency similarity between cities, we have made an observation that the traffic data is more similar in the frequency domain between cities. Based on this fact, we propose a \textbf{F}requency \textbf{E}nhanced \textbf{P}re-training Framework for \textbf{Cross}-city Few-shot Forecasting (\textbf{FEPCross}). FEPCross has a pre-training stage and a fine-tuning stage. In the pre-training stage, we propose a novel Cross-Domain Spatial-Temporal Encoder that incorporates the information of the time and frequency domain and trains it with self-supervised tasks encompassing reconstruction and contrastive objectives. In the fine-tuning stage, we design modules to enrich training samples and maintain a momentum-updated graph structure, thereby mitigating the risk of overfitting to the few-shot training data. Empirical evaluations performed on real-world traffic datasets validate the exceptional efficacy of FEPCross, outperforming existing approaches of diverse categories and demonstrating characteristics that foster the progress of cross-city few-shot forecasting.
For controlling pollution of the marine environment while developing coastal economy, the coastal environmental performance was proposed and measured in static and dynamic methods combined with DEA and efficiency theory in this paper. With the two methods, 16 harbor cities were evaluated. The results showed the index designed in this paper can better reflect the effect to the marine environment for economy of the coastal cities.
In the period of post-communist transition, Central Europe witnessed complex and multifaceted mobility processes; permanent outmigration, of an ethnic or labour-related nature, coexisted with temporary, seasonal, or cross-border movements and an increasing influx of foreigners. To study these complex processes, we have chosen to apply a holistic and comprehensive approach, rather than limit conceptual considerations to one theory of migration determinants. We focus on eleven post-communist countries that joined the European Union (EU-11) and on the period extending from around 1989, covering the EU’s eastward enlargement, to the present. The aim of this study is twofold: first, we propose a general conceptual framework, based on the aspirations/capabilities approach, to present the main determinants of emigration from this part of the European continent. Second, in relation to each determinant, we formulate research questions postulated by selected theories of international migration and present the evidence, based on existing empirical studies, that addresses these questions. The paper contributes to the literature by providing a broad interpretation of post-transition mobility and pointing to commonly overlooked explanatory factors. We highlight the importance of economic factors that have enhanced and directed the outward migration from the EU-11 to selected EU member states and selected economic sectors; in particular, as regards capabilities, these factors include the lifting of labour market restrictions, high demand in the secondary sector of labour markets, and the roles of migration networks and the migration industry. Emphasis is also placed on aspirational factors, such as labour market failures and the substantial aspirational gap resulting from improvements in high educational attainment in the countries of origin. The aspirations/capabilities approach serves well as a general framework of migration determinants, but its explanatory power is enhanced by reference to other, more specific theories of migration. We show that a combination of the complementary approaches provides a more refined and in-depth picture of migration from the region.
* This article belongs to a special issue on “Demographic Developments in Eastern and Western Europe Before and After the Transformation of Socialist Countries”.
Urban groups. The city. Urban sociology, City population. Including children in cities, immigration
Abstract In a comparison of three human service organisations in which the human body plays a key role, we examine how organisations regulate religious body practices. We concentrate on Muslim norms of dressing and undressing as a potential focal point of cultural and religious diversity. Inspired by Ray’s (2019) idea of racialized organizations, we assume that state-run organizations in Germany are characterized by a strong commitment to religious tolerance and non-discrimination but also marked by anti-Muslim sentiment prevalent among the German population. Our study looks for mechanism that explain how Human Service Organizations accommodate Muslim body practices. It draws on qualitative empirical data collected in state-run hospitals, schools and swimming pools in Germany. Our analyses show that the organizations draw on formal and informal rules at the organizational level to accommodate Islam. We identify five general organizational mechanisms that may hinder Muslim accommodation in human service organizations. In particular, we see a risk of decoupling between the expectation of religious tolerance and processes that lead to informal discrimination, driven mainly by the difficulty of controlling group dynamics among users.
Making Smart Cities more sustainable, resilient and democratic is emerging as an endeavor of satisfying hard constraints, for instance meeting net-zero targets. Decentralized multi-agent methods for socio-technical optimization of large-scale complex infrastructures such as energy and transport networks are scalable and more privacy-preserving by design. However, they mainly focus on satisfying soft constraints to remain cost-effective. This paper introduces a new model for decentralized hard constraint satisfaction in discrete-choice combinatorial optimization problems. The model solves the cold start problem of partial information for coordination during initialization that can violate hard constraints. It also preserves a low-cost satisfaction of hard constraints in subsequent coordinated choices during which soft constraints optimization is performed. Strikingly, experimental results in real-world Smart City application scenarios demonstrate the required behavioral shift to preserve optimality when hard constraints are satisfied. These findings are significant for policymakers, system operators, designers and architects to create the missing social capital of running cities in more viable trajectories.
Chieh Hubert Lin, Hsin-Ying Lee, Willi Menapace
et al.
Toward infinite-scale 3D city synthesis, we propose a novel framework, InfiniCity, which constructs and renders an unconstrainedly large and 3D-grounded environment from random noises. InfiniCity decomposes the seemingly impractical task into three feasible modules, taking advantage of both 2D and 3D data. First, an infinite-pixel image synthesis module generates arbitrary-scale 2D maps from the bird's-eye view. Next, an octree-based voxel completion module lifts the generated 2D map to 3D octrees. Finally, a voxel-based neural rendering module texturizes the voxels and renders 2D images. InfiniCity can thus synthesize arbitrary-scale and traversable 3D city environments, and allow flexible and interactive editing from users. We quantitatively and qualitatively demonstrate the efficacy of the proposed framework. Project page: https://hubert0527.github.io/infinicity/
A smart city involves, among other elements, intelligent transportation, crowd monitoring, and digital twins, each of which requires information exchange via wireless communication links and localization of connected devices and passive objects (including people). Although localization and sensing (L&S) are envisioned as core functions of future communication systems, they have inherently different demands in terms of infrastructure compared to communications. Wireless communications generally requires a connection to only a single access point (AP), while L&S demand simultaneous line-of-sight propagation paths to several APs, which serve as location and orientation anchors. Hence, a smart city deployment optimized for communication will be insufficient to meet stringent L&S requirements. In this article, we argue that the emerging technologies of reconfigurable intelligent surfaces (RISs) and sidelink communications constitute the key to providing ubiquitous coverage for L&S in smart cities with low-cost and energy-efficient technical solutions. To this end, we propose and evaluate AP-coordinated and self-coordinated RIS-enabled L&S architectures and detail three groups of application scenarios, relying on low-complexity beacons, cooperative localization, and full-duplex transceivers. A list of practical issues and consequent open research challenges of the proposed L&S systems is also provided.
The ubiquitous use of mobile devices and associated Internet services generates vast volumes of geolocated data, offering valuable insights into human behaviors and their interactions with urban environments. Over the past decade, mobile phone data have proven indispensable in various fields such as demography, geography, transport planning, and epidemiology. They enable researchers to examine human mobility patterns on unprecedented scales and analyze the spatial structure and function of cities. The relationship between mobile phone data and land use has also been extensively explored, particularly in inferring land use patterns from spatiotemporal activity. However, many studies rely on Call Detail Records (CDR) or eXtended Detail Records (XDR), which may not capture specific mobile application usage. This study aims to address this gap by mapping mobile service usage diversity in 20 French cities and investigating its correlation with land use distribution. Utilizing a Shannon diversity index, the study evaluates mobile service usage diversity based on hourly traffic volume data from 17 mobile services. Furthermore, the study compares temporal diversity with land distribution both within and among cities.
Although extensive research investigates the consequences of teenage motherhood, there is still very limited research exploring young mothers’ experiences in their own voices. This gap is particularly evident for those non-Western developing countries in which women’s voices are largely muted. This paper explores women’s perceptions and evaluations of their early motherhood, drawing on their lived experiences and retrospective accounts. This study also investigates how early first birth influences these mother’s subsequent fertility. The study adopts a qualitative method based on interviews with a total of 17 women in several cities in Turkey who had their first birth at a young age (ages 17-22). A qualitative approach is most suitable for this research area, which aims to explore young mothers’ interpretations of their fertility timing and the consequences of this event for their lives in general, including subjective evaluations and subtle meanings. A key finding of this study is that the interviewees describe early childbearing as a negative event in their life course, convey regret for having had an early first birth, and report a feeling of dissatisfaction with being a young mother. A second finding concerns the influence of early first birth on subsequent childbearing. The women’s accounts indicate that subsequent fertility operated as a compensation for the missed feelings of motherhood and served as an opportunity to heal from hurtful experiences. This study points to the importance of social context in determining the consequences of early fertility.
Urban groups. The city. Urban sociology, City population. Including children in cities, immigration