Search Results (39)

This article explores the role of the European Union (EU) as a normative gender actor promoting women’s participation in STEM (Science, Technology, Engineering, and Mathematics) within the Eastern Partnership (EaP) region. In a context marked by global inequality and overlapping international efforts, this paper assesses the extent to which EU-driven Europeanisation influences national gender policies in non-EU states. Using a postfunctionalist lens, this research draws on a qualitative analysis of EU-funded programmes, strategic documents, and a detailed case study encompassing Armenia, Georgia, Moldova, Ukraine, Belarus, and Azerbaijan. This study highlights both the opportunities created by EU initiatives such as Horizon Europe, Erasmus+, and regional programmes like EU4Digital and the challenges presented by political resistance, institutional inertia, and socio-cultural norms. The findings reveal that although EU interventions have fostered significant progress, structural barriers and limited national commitment hinder the long-term sustainability of gender equality in STEM. Moreover, the withdrawal of other global actors increases pressure on the EU to maintain leadership in this area. This paper concludes that without stronger national alignment and global cooperation, EU gender policies risk becoming symbolic rather than transformative. Full article

This article examines how governance structures and procedural timing influence the effectiveness of Territorial Management Instruments (TMIs) in Portugal. Anchored in a comparative analysis of two key legal reforms (Decree-Law No. 380/1999 and Decree-Law No. 80/2015), the study explores the tensions between democratic legitimacy and regulatory complexity. While the 1999 framework emphasized vertical coordination and participatory rights, it often led to procedural rigidity and institutional inertia. Conversely, the 2015 reform promoted digital tools and streamlined processes but introduced new governance gaps, reduced stakeholder diversity, and compressed consultation timelines. Drawing on a qualitative analysis of legal texts, policy documents, and technical documentation, the article introduces the concept of temporal governance, the idea that planning time is not merely a constraint but a governable resource. Through this lens, planning delays are reframed as either pathological (caused by inefficiency and fragmentation) or productive (used strategically to enhance environmental assessment and stakeholder engagement). A new conceptual framework is proposed to classify types of planning time, differentiate delays, and support temporal calibration in governance design. Findings show that effective planning outcomes hinge not only on legal architecture or participatory norms but also on the institutional ability to balance speed with deliberation and strategic foresight with procedural pragmatism. The paper concludes by calling for adaptive governance models that integrate time as a dynamic dimension of spatial planning, with implications for environmental resilience, democratic value, and, above all, institutional trust. Full article

Smart governance—the integration of digital technologies into urban governance—is increasingly recognized as a transformative approach to addressing complex urban challenges such as rapid urbanization, climate change, social inequality, and resource constraints. As a foundational pillar of the smart city paradigm, it enhances decision-making, service delivery, transparency, and civic participation through data-driven tools, digital platforms, and emerging technologies such as AI, IoT, and blockchain. While often positioned as a pathway toward sustainability and inclusivity, existing research on smart governance remains fragmented, particularly regarding its relationship to urban sustainability. This study addresses that gap through a systematic literature review using the PRISMA methodology, synthesizing theoretical models, empirical findings, and diverse case studies. It identifies key enablers—such as digital infrastructure, data governance, citizen engagement, and institutional capacity—and highlights enduring challenges including digital inequity, data security concerns, and institutional inertia. In response to this, the study proposes a multidimensional framework that integrates governance, technology, and sustainability, offering a holistic lens through which to understand and guide urban transformation. This framework underscores the importance of balancing technological innovation with equity, resilience, and inclusivity, providing actionable insights for policymakers and planners navigating the complexities of smart cities and urban development. By aligning smart governance practices with the United Nations’ sustainable development goals (SDG)—particularly SDG 11 on sustainable cities and communities—the study offers a strategic roadmap for fostering resilient, equitable, and digitally empowered urban futures. Full article

The E-7 nations face significant challenges in harmonizing artificial intelligence (AI) adoption with sustainable economic and environmental goals. While AI holds transformative potential to revolutionize energy structures, modernize infrastructure, broaden financial inclusion, and reduce carbon emissions, its effective integration is frequently hindered by policy inertia, economic limitations, and long-standing institutional barriers. Using the multi-level perspective (MLP), this study employs the method of moments quantile regression (MMQREG) on panel data from 2004 to 2024 to investigate the determinants of artificial intelligence (AI) adoption, focusing on the roles of energy structure (ES), infrastructure (INFRA), financial inclusion (FI), economic growth (GDP), patent activity (Tpatent), population (TP), and carbon emissions (CE) across E-7 nations. The study findings reveal that economic growth and energy structure play a significant role in driving AI adoption, while inadequacies in infrastructure and limited financial inclusion significantly hinder AI progress. Additionally, the analysis reveals a positive relationship between AI adoption and CO₂ emissions, where early stages of technology uptake lead to increased emissions, but sustained integration eventually results in efficiency gains that help to reduce them. These findings underscore the need for E-7 nations to adopt targeted policies that modernize digital and physical infrastructure, broaden financial access, and expedite the transition to sustainable energy systems. This study offers actionable insights for policymakers to align digital innovation with sustainable development goals. Full article

This study examines the policy and technological dynamics shaping China’s road transport sector’s transition to low-carbon sustainability, focusing on battery electric vehicles (BEVs) and hydrogen fuel cell electric vehicles (HFCEVs). As the world’s second-largest carbon emitter, China faces significant challenges in reducing its fossil fuel dependency in road transport, which accounts for diverse emissions and energy security risks. The present work, using a dual tech multi-level perspective (DTMLP) framework integrating multi-level perspective (MLP) and an advocacy coalition framework (ACF), analyzes the interplay of landscape pressures (global carbon constraints), regime dynamics (policy–market interactions), and niche innovations (BEV/FCEV competition). The results reveal BEVs’ dominance in light-duty markets, achieving remarkable operational emission reductions but facing lifecycle carbon lock-ins from battery production and coal-dependent power grids. HFCEVs demonstrate potential for heavy-duty decarbonization but struggle with gray hydrogen reliance and infrastructure gaps. Policy evolution highlights shifting governance from subsidies to market-driven mechanisms, alongside regional disparities in implementation. This study proposes a three-phase roadmap: structural optimization (2025–2030), technological adaptation (2030–2045), and hydrogen–electric system integration (post-2045), emphasizing material innovation, renewable energy alignment, and multi-level governance. Our findings underscore the necessity of coordinated policy–technology synergies, grid decarbonization, and circular economy strategies, to overcome institutional inertia and achieve China’s ‘Dual Carbon’ targets. This work provides actionable insights for global sustainable transport transitions amid competing technological pathways and geopolitical resource constraints. Full article

Background: Personalized cancer medicine (PCM) tailors cancer treatments based on individual genetic profiles, enabling more precise and effective therapies. Despite its potential, integrating PCM into clinical practice remains challenging because of organizational and systemic barriers. This study examined the factors influencing PCM implementation at a major cancer center in Stockholm, Sweden. Methods: We conducted semi-structured interviews with 16 medical professionals and management staff from Karolinska University Hospital and Karolinska Institutet. Content analysis was used to identify key themes related to PCM implementation. This study followed the established Consolidated Criteria for Reporting Qualitative Research guidelines to ensure methodological rigor and transparency. Results: Informants framed PCM as both a technological innovation and a patient-centered approach. However, significant barriers to implementation were identified, including organizational inertia, fragmented funding models, and ethical challenges related to access and equity. Structural silos between academic and healthcare institutions complicate integration. Key facilitators include leadership commitment, cross-sectoral collaboration, and a supportive policy environment. Participants emphasized the need for integrated infrastructure, real-time data-sharing mechanisms, and interdisciplinary training programs to support PCM. Conclusions: Successful PCM implementation requires overcoming entrenched organizational and systemic barriers through a multi-stakeholder approach involving healthcare providers, researchers, policymakers, and patient advocates. The findings underscore the necessity of a “third-form organization” to mediate between academia and clinical care. Addressing these challenges requires adaptive governance models, evidence-based policy reforms, and sustainable funding frameworks. Future research should explore comparative contexts to enhance the scalability and generalizability of PCM integration strategies. Full article

Against the backdrop of global climate change, extreme weather events, such as heavy rainfall, typhoons, tsunamis, and rising sea levels, have become frequent, posing unprecedented challenges to human society. As an important strategy for coastal cities to respond to climate change, climate-induced evacuation is influenced by complex and diverse factors. This study delves into the driving mechanisms of population migration willingness, revealing the dynamic balance of push, pull, and resistance factors and their interaction with individual value orientations affecting migration decisions. By constructing a Logistic Regression Model, this research quantitatively analyzes the significant impacts of personal circumstances, family characteristics, living conditions, risk perception, compensation relocation, and supportive policies on climate-induced migration willingness, using Shanghai as a case study. The findings indicate that age, education level, household size, housing type, risk perception, and compensation policies are key factors. Building upon the multidimensional capital interaction mechanisms and dynamic threshold response patterns identified in the research, this study proposes a three-phase progressive policy framework: initially, establishing an integrated human–material–social capital framework to implement tiered relocation incentive programs, which address decision window constraints through cognitive empowerment and asset replacement strategies; subsequently, creating a dynamic compensation adjustment mechanism by developing policy toolkits aligned with inverted U-shaped utility curves while enhancing synergistic effects between cultural cognition transformation and vocational training; and ultimately, innovating an institutional–cultural co-governance paradigm that rebalances public service dependency and place attachment through spatial equity redistribution. Specific recommendations encompass designing modular risk education curricula, establishing social network transplantation mechanisms, piloting climate citizenship regimes, and constructing cross-border governance knowledge platforms. These multidimensional interventions encompassing capital restructuring, threshold responsiveness, and cultural adaptation offer valuable policy insights for resolving the “development resilience–migration inertia” paradox in coastal cities. Full article

Human resource management (HRM) plays a critical role in shaping public administration by ensuring the efficiency, effectiveness, and adaptability of public institutions. In post-socialist European countries, HRM reforms have been central to broader public sector transformations aimed at increasing transparency, meritocracy, and efficiency. However, these reform processes are often hindered by institutional inertia, political influences, and resistance to change. This study examines how reform requirements and resistance to change influence the transformation of HRM practices in public administration across post-socialist European countries. Using a structured literature review approach, this study systematically analyzes peer-reviewed academic research published in quality journals indexed in the Web of Science database. A purposive and criterion-based sampling strategy was applied to select relevant studies that address HRM reforms, institutional challenges, and governance dynamics within the post-socialist context. Findings indicate that historical legacies, politicization, and institutional resistance remain significant barriers to the successful implementation of HRM reforms. This study also highlights that while legal and procedural adjustments have been made, many public administrations struggle with the practical application of reform policies due to entrenched bureaucratic cultures and limited professionalization of HRM functions. By providing a structured synthesis of existing research, this study contributes to a deeper understanding of HRM transformation in post-socialist public administrations. It also identifies areas wherein further empirical research is needed to explore potential strategies for overcoming barriers to reform. Full article

This paper aims to investigate the sustainability performance trajectories of the Visegrád Group (V4) countries since their accession to the European Union. Given their shared historical, geopolitical, and socio-economic backgrounds, this study explores common evolutionary patterns and convergence within the sustainable development goal framework. This research employs the Kml3D non-parametric clustering algorithm and standard beta and sigma convergence tests. The analysis covers the 2004–2023 data sourced from the European Sustainable Development Report 2023/24 by the Sustainable Development Solutions Network. The findings demonstrate that while each country follows a distinct path, Czechia and Slovakia exhibit notable similarities in the evolution of individual sustainability dimensions. This underscores the influence of path dependence, institutional inertia, and cross-border policy coordination in sustainable development. The results also suggest that although the V4 countries generally converge in socio-economic and infrastructural dimensions of sustainability, divergence persists in education, gender equality, nature preservation, and institutional performance. Full article

During the execution of autonomous tasks within sheltered space environments, unmanned vehicles demand highly precise and seamless continuous positioning capabilities. While the existing visual–inertial-based positioning methods can provide accurate poses over short distances, they are prone to error accumulation. Conversely, radio-based positioning techniques could offer absolute position information, yet they encountered difficulties in sheltered space scenarios. Usually, three or more base stations were required for localization. To address these issues, a binocular vision/inertia/ultra-wideband (UWB) combined positioning method based on factor graph optimization was proposed. This approach incorporated UWB ranging and positioning information into the visual–inertia system. Based on a sliding window, the joint nonlinear optimization of multi-source data, including IMU measurements, visual features, as well as UWB ranging and positioning information, was accomplished. Relying on visual inertial odometry, this methodology enabled autonomous positioning without the prerequisite for prior scene knowledge. When UWB base stations were available in the environment, their distance measurements or positioning information could be employed to institute global pose constraints in combination with visual–inertial odometry data. Through the joint optimization of UWB distance or positioning measurements and visual–inertial odometry data, the proposed method precisely ascertained the vehicle’s position and effectively mitigated accumulated errors. The experimental results indicated that the positioning error of the proposed method was reduced by 51.4% compared to the traditional method, thereby fulfilling the requirements for the precise autonomous navigation of unmanned vehicles in sheltered space. Full article

Ideally, teachers’ classroom assessment literacy can be developed through in-service teacher education or assessment training from institutions. Yet in reality, teachers may not gain sufficient assessment training on the job or from institutionalised training programmes. This contextual disadvantage cannot explain teacher inertia in advancing their professional knowledge and their skills in classroom-based assessment. Instead, teachers are encouraged to proactively rely on themselves to enhance their CAL amid their tried-and-tested assessment practices. The current qualitative case study explores how a university English teacher directed herself to develop CAL in her assessment practices over time. Data were collected through narrative frames, interviews with the teacher and her students, classroom observations, and documents. This study shows that self-directed CAL development may be buttressed by the teacher’s prior assessment experiences. The teacher’s self-agency and reflections further empowered her to acquire the assessment knowledge, skills, and experience in improving assessment effectiveness. The implications for enhancing self-directed professional development in assessment are also discussed. Full article

A modeling technique for a nearshore hybrid wind–wave energy converter system (HWWECS) is presented in this research. The model consists of the buoy, wind system, and generator, allowing simulation of the HWWECS’s behavior in response to varied wave circumstances, such as different wave heights and periods. The HWWECS is made up of two buoy units and a wind system that work together to power a generator. The Wave Analysis at Massachusetts Institute of Technology (WAMIT) software is used to calculate the hydrodynamic forces. A variable inertia hydraulic flywheel is used to bring the system into resonance with incident wave frequencies in order to improve power production. Full article

This document presents a study of thermal inertia in the subsoil adjacent to the Civil Engineering laboratory of the Technological Institute of Sonora (ITSON) in the south of Sonora, Mexico, in service of the development of a solution proposal of a ground-coupled air heat exchanger for the cooling months. The research was divided into three phases: first, the monitoring of temperature in 10 layers of the ground; second, the analysis of thermal ground properties; and last, the design and simulation of a ground-coupled air heat exchanger. The objectives were to determine the variation in the thermal inertia of the soil with depth and over time and to determine the optimum depth for a ground-coupled heat exchanger system. The second objective was to develop a design proposal for a ground-coupled heat exchanger for the university laboratory. We found that the optimum depth is 3.0 m in a soil with high-compressibility clay with 21% humidity and 0.152 W/mK of thermal conductivity. However, the proposed design identified the best depth for the cooling system as 3 m considering a ground-coupled heat exchanger for a volume of 222.2 m³, corresponding to the volume of the classrooms of the building. With this design, the approach was to reduce the temperature by at least 10 °C on the hottest day (41 °C) of the year studied. We concluded that with this kind of system, the climate of the building studied could reduce the thermal load of active AC systems and reduce the energy load by 59%. Full article

The article examines the territorial conditions, actors, and processes that facilitate or hinder the emergence of social innovation in the inner peripheries. It investigates three social innovation initiatives taking place in the Italian Apennine through a discourse analysis of policy documents and a number of semi-structured interviews of project promoters and local actors. The research findings show that social innovation emerges as an act of territorial provocation practiced by a coalition of actors that weave strong ties with the local community. Provocation takes the form of an adaptive response of the local community to the dynamics of territorial marginalization, a reaction to tackle what we called the “wanna be” feeling, namely, a sense of constriction and frustration found in local inhabitants and linked to conditions of physical and social isolation, inertia, and a lack of future perspectives. This reaction has allowed them to shape new socio-institutional networks and structures that have catalyzed local communities’ capacity to mobilize particular resources or specific assets existing in places, improving their living conditions. Full article

Background: Classic locational principles predict a picture of urban intensity decaying from the city center to the periphery under ideal assumptions. However, various exogenous factors can influence the real-world urban intensity and often deviate from the theoretical pattern. The specific mechanisms are worthy of exploration and are of potential theoretical and practical significance. Methods: In this paper, we consider two city districts with typical urban locations, namely, Changping and Chaoyang in Beijing, and construct mechanistic models of the status quo urban intensity (floor area ratio, FAR) utilizing multisource spatiotemporal big data. We further compare these models with the “theoretically ideal” FAR patterns as would be predicted by applied locational theories. Results: We find that the status quo FAR distribution generally conforms to the theoretical predictions but still exhibits regional deviations that can be explained by historical inertia and influence from particular policies. Conclusion: We conclude this paper with discussions on the findings’ methodological and practical implications for urban planning institutions, especially in a transition economy context. Full article