Search Results (546)

The rapidly urbanizing peripheries of the Global South face significant demographic pressures, leading to governance deficits that often neglect the long-term structural safety of new buildings. While regulatory frameworks predominantly emphasize initial construction quality, they frequently overlook the critical “post-occupancy” phase, during which distinct structural risks accumulate. This study introduces a reproducible, open-data risk identification framework designed to trace theoretical “windows of vulnerability” in Çekmeköy, a peripheral district of Istanbul. By triangulating temporal, spatial, and demographic municipal administrative records from 2018 to 2024, we illustrated how low-cost data can serve as proxies for prioritizing structural risk assessments. The findings demonstrate that a 103% population increase between 2008 and 2023, coupled with a 21% reduction in the average household size, has generated urgent housing demand that outpaces supply. We hypothesize that these conditions create high-probability zones for “informality creep,” where demographic pressures induce informal practices, such as unauthorized structural modifications within ostensibly formal high-rise settings. The primary contribution is a transferable algorithmic tool, the Weighted Post-Occupancy Vulnerability Index (POVI). Rather than serving as a deterministic building-level diagnostic, this framework operates much like an epidemiological screening process; it acts as a macroscopic prioritization heuristic that allows resource-constrained municipalities to proactively direct their inspection efforts. By mathematically quantifying the conditions under which post-occupancy risks develop, this framework provides an essential resource for enhancing urban resilience during reactive urbanism planning. Full article

The need for aligned policy responses to coordinate among governmental agencies is challenged by the “administrative silos” prevalent in government bureaucracy. How do collaboration risks influence the abilities of cities to effectively coordinate their efforts to address complex issues such as economic development, climate mitigation, and climate related disaster adaptation? Although coordination problems in the face of administrative silos are widely acknowledged, systematic examination of what accounts for variation in the extent to which local governments are able to successfully coordinate their functions to address complex problems are conspicuously absent from the literature. This research applies functional institutional collective action (ICA) theory to fill this lacuna. Problem uncertainty, actor’s political incentives, and institutions were hypothesized to influence successful coordination. Pooled GLM Probits were estimated with data from 1124 U.S. cities. Uncertainty inherent in specific types of problems, the characteristics of affected actors, and local and regional institutions influenced whether successful coordination among municipal departments was achieved. We conclude by identifying implications for collective action theory and for organizing and standard setting for sustainability policy. Full article

Background: Viral attachment mediated by host cell surface receptors is the first step in viral infection. As a key cell surface receptor, heparan sulfate (HS) mediates the attachment and entry of numerous non-enveloped viruses in livestock, thereby serving as a crucial molecular target for studying virus–host interactions. Methods: Based on the structural scaffold of a nanobody (Nb; PDB: 7TJC), we rationally designed and constructed a mutant Nb targeting HS, designated HS-Mut-Nb1, using molecular docking, site-directed mutagenesis, molecular dynamics (MD) simulations, and experimental characterization. Results: Molecular docking indicated that the active site of wild-type Nb for HS binding was located within the cavity jointly formed by the complementarity-determining region 3 (CDR3) and the framework regions (FRs) of the wild-type Nb. A comprehensive analysis integrating virtual alanine scanning, site-directed mutagenesis, and MD simulations revealed that the combination of three point mutations (Phe47Arg, Asp99Tyr, and Tyr108Pro) significantly enhanced the binding affinity of Mut-Nb1 for HS, with a calculated binding free energy (ΔG) of −83.26 ± 3.06 kcal/mol. Enzyme-linked immunosorbent assay (ELISA) results further confirmed that Mut-Nb1 exhibited high affinity for HS (K_D = 65.87 nM) and specificity (positive/negative ratio, P/N = 3.84; cross-reactivity, CR < 6.60%). Conclusions: This study not only provides novel candidate molecules for elucidating the mechanism of HS–virus interactions and developing related inhibitors but also offers a reference for the rapid construction of mutant Nbs. Full article

This paper examines leadership characteristics within local self-governments in the Republic of Serbia through a comparative analysis of leaders’ self-assessments and associates’ evaluations. Drawing on the Johari Window framework, the study explores differences in the perception of leadership attributes from two complementary perspectives. The sample consisted of 150 participants occupying managerial positions within different municipal administrations. The findings indicate that capability is the dominant leadership attribute across both respondent groups, followed by energy, reliability, intelligence, and responsibility. However, notable discrepancies were identified between self-perception and external evaluation, particularly regarding adaptive and interpersonal characteristics. The results further suggest that leadership perception in transitional institutional environments is strongly influenced by organizational uncertainty and institutional instability. Emotional and relational attributes appear to be less emphasized, whereas functional competencies and managerial effectiveness remain highly valued. The study contributes to contemporary leadership research by highlighting the importance of contextual and relational dimensions in the interpretation of leadership characteristics. In addition, the findings offer practical implications for leadership development within public administration systems. Full article

Inadequate management of municipal solid waste represents a critical challenge for the sustainability of modern cities, characterized by low citizen participation rates due to the lack of direct incentives. Unlike existing approaches that isolate hardware classification or fleet monitoring, this article presents RENOVA as a socio-technical closed-loop system based on the Internet of Things (IoT) and artificial intelligence (AI). This system integrates an IoT-enabled smart bin, a gamified mobile application for citizens, and an administrative web panel for merchant redemption, all interconnected via a REST API. The system employs computer vision through the GPT-4o (OpenAI, San Francisco, CA, USA) multimodal model for the automatic classification of recyclable materials (PET plastic and Aluminum) and integrates a gamified rewards program to incentivize citizen participation. The methodology follows an applied technological development approach under the agile Scrum framework. Prototype validation demonstrated successful real-time communication between the IoT device and the cloud platform, achieving classification accuracy exceeding 95% under controlled conditions. A diagnostic survey applied to a convenience sample of 51 participants revealed that 94.1% accepted the proposed gamification model, while user experience evaluation (n = 74; consisting primarily of university-affiliated individuals aged 15–24) yielded a mean overall satisfaction score of 4.77/5.0 (SD = 0.48), with 79.7% of participants assigning the maximum rating. These findings reflect stated user acceptance and behavioral intention under prototype conditions rather than observed long-term behavioral change, and should not be generalized to broader urban populations without further validation. The proposed solution directly contributes to Sustainable Development Goals 11 (Sustainable Cities) and 12 (Responsible Consumption), suggesting a potentially scalable framework. Full article

This study addresses the fragmented integration of smart technologies into sustainable tourism management, where digital tools are often implemented without sufficient coordination, interoperability, or clear links to sustainability objectives. Such a situation limits the potential of smart solutions to improve destination governance, visitor experience, and the long-term competitiveness of tourism destinations. The aim of the study is to evaluate how the Smart Region concept can be operationalized at the urban level by analysing the city of České Budějovice (Czech Republic)—the primary regional tourism and administrative hub—as a critical case study. The research first analysed relevant municipal and regional strategic documents, then examined secondary data and publicly available digital services and technological solutions, and finally conducted a structured observation of selected tools relevant to tourism management. The findings show that the city has already introduced several elements of smart tourism management, especially in digital information services, transport management, and sustainable mobility. However, the analysis also reveals important shortcomings in data sharing, cross-sector coordination, and the integration of tourism-oriented digital tools. The study concludes that deeper institutional cooperation and more coherent smart governance are necessary to strengthen sustainability, improve efficiency, and support the long-term competitiveness of the destination. Full article

This study presents a hybrid spatio-textual matching approach for integrating historical web-derived address datasets with a municipal reference dataset, using the 2009 administrative delineation of Şişli (Istanbul) as a case study. The proposed approach addresses challenges commonly encountered in data obtained from web archives, such as lexical differences, abbreviations, heterogeneous structures, and missing address information. The methodology consists of three main stages: (i) preprocessing and structuring of web-based address records; (ii) hybrid matching, combining deterministic rules with similarity-based methods; and (iii) post-matching geographic enrichment using an Application Programming Interface (API) to provide supplementary geographic context for matched records. The matching process is conducted exclusively between historical datasets; contemporary geographic information is used only after the completion of the matching process to provide additional contextual information. The methodology integrates token-based, vector-based, and structural similarity measures within a calibrated scoring scheme to improve the matching of ambiguous and inconsistent address records. The results indicate that 65.4% of the records were automatically accepted, 7.3% required manual review, and no suitable candidate was found for 5.4%. Deterministic matching results reveal that strict rule-based approaches are highly sensitive to data integrity and attribute consistency, especially in heterogeneous web-based datasets, highlighting the value of combining multiple similarity measures within a hybrid matching strategy. The API-based enrichment results provide supplementary geographic context regarding the contemporary surroundings of matched records, while historical interpretations remain grounded in the original archival datasets. In this context, the study may contribute to the integration of historical web-based address data with structured municipal datasets under heterogeneous archival data conditions. Full article

How does artificial intelligence (AI) adoption shape administrative efficiency and e-citizen integration in local governments, and what role does professional development play in mediating these relationships? Drawing on a survey of 500 municipal employees across Spanish municipalities, this study employs partial least squares structural equation modelling (PLS-SEM), with formal non-linearity testing via Warp3 algorithms, to test a theoretically grounded model. The conceptual framework integrates Digital Transformation Theory and Public Value Theory as primary explanatory lenses, while drawing on the Technology Acceptance Model (TAM) and Total Factor Productivity (TFP) logic as complementary background perspectives that contextualise rather than directly operationalise the micro-level findings. Structural results reveal that AI adoption exerts a strong direct (and statistically linear) effect on perceived administrative efficiency (β = 1.04, p < 0.001; the standardised coefficient exceeding 1.0 and R² > 1 are a legitimate WarpPLS warp-model fit index rather than evidence of model misspecification: the Warp3 warp functions inflate the variance of predicted efficiency and break the additive identity SST = SSM + SSE, with the high AI–PD collinearity (r ≈ 0.84) as the contributing mechanism (RSCR = 1.000, SSR = 1.000); a comparative re-estimation without the moderation term yields β = 0.87 and R² = 0.76; we adopt this parsimonious specification (β ≈ 0.87, R² = 0.76) as the substantively interpretable estimate, with predictive relevance confirmed by a high Stone–Geisser Q² = 0.685, indicating that the model fits and predicts well rather than overfitting, while simultaneously stimulating professional development (β = 0.84, p < 0.001, R² = 0.70). Professional development positively predicted both efficiency (β = 0.27, p < 0.001) and e-citizen integration (β = 0.26, p < 0.01). Efficiency is the primary driver of e-citizen integration (β = 0.54, p < 0.001, R² = 0.53). The proposed moderation of AI adoption by professional development on efficiency was not supported (β = −0.01, p = 0.44), suggesting additive rather than synergistic effects. Model fit was robust (GoF = 0.701; ARS = 0.749; APC = 0.495); convergent and discriminant validity were confirmed by composite reliability, average variance extracted, Fornell–Larcker, and HTMT criteria; and common method bias diagnostics (Harman’s single-factor test, full-collinearity AFVIF, and marker-variable analysis) indicated that systematic method variance was not a material threat. These findings offer micro-empirical evidence of the mechanisms linking AI adoption to citizen service outcomes via a professional development pathway and provide actionable recommendations for Spanish and European municipalities navigating AI-driven governance reform. Full article

Digital transformation has become a strategic pillar of modernization in public administration; however, evidence from emerging economies shows that technology implementation alone does not guarantee institutional transformation. This study examines the structural relationships among digital competencies, change management, technology adoption, and digital transformation in public administration institutions in Lima, Peru, incorporating Digital Inclusion Practices (DIP) as a moderating variable. A quantitative, non-experimental, cross-sectional design was applied to a sample of 358 public servants working in ministries, national agencies, regional administrative units, and municipal governments located in Lima. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that digital competencies and change management are positively associated with technology adoption, and that change management and technology adoption show significant positive relationships with digital transformation. Technology adoption partially mediates the relationships between digital competencies and digital transformation, and between change management and digital transformation. Additionally, digital competencies show a direct and statistically significant, although weak, relationship with digital transformation. The moderating relationship involving DIP was not statistically significant. These findings suggest that digital governance in emerging public administrations may depend less on individual skills alone and more on structured institutional processes that support effective technology adoption, strategic change management, and institutional modernization. Full article

Artificial intelligence (AI) is becoming increasingly embedded in the digital infrastructure of local government, creating new opportunities to improve public sector productivity while also influencing systemic risk and organisational resilience across interconnected public systems. As municipalities adopt AI to automate, support, and transform administrative processes, organisational performance becomes more dependent on the reliability of algorithms, the quality of data, effective governance, and coordination among public institutions. These growing interconnections create new vulnerabilities that can spread across public service networks, yet evidence on the productivity, risk, and resilience implications of AI adoption remains fragmented and dispersed across different fields of research. This study develops an integrative conceptual framework that examines the relationship between AI adoption, public sector productivity, systemic risk, and organisational resilience within interconnected sociotechnical systems. Drawing on insights from productivity economics, systems theory, and public governance, the framework positions total factor productivity (TFP) within a broader public value and risk governance perspective. Using the PRISMA 2020 methodology, the study systematically reviews 68 peer reviewed empirical studies published between 2015 and 2025, assessing productivity outcomes, methodological quality, effect sizes, and contextual factors relevant to local government and networked public administration. The findings show that productivity gains associated with AI are strongly influenced by organisational readiness, including digital maturity, workforce capabilities, governance quality, and institutional coordination. While AI has the potential to improve operational efficiency and strengthen adaptive capacity, inadequate readiness can increase systemic risks arising from algorithmic opacity, cybersecurity challenges, data dependence, coordination failures, and disruptions that may spread across interconnected administrative systems. The review also highlights that resilience depends on the ability of public organisations to anticipate, absorb, adapt to, and recover from AI-related disruptions while maintaining the continuity and quality of public services. The study contributes to theory by integrating perspectives from productivity economics, public administration, and systemic risk within a sociotechnical systems framework. It contributes empirically through a comprehensive synthesis of evidence on AI and public sector productivity and methodologically through the application of transparent PRISMA 2020 review procedures. From a practical perspective, the study offers a conceptual measurement framework and policy guidance for municipal decision makers seeking to improve productivity while strengthening resilience and reducing systemic risks in increasingly interconnected public governance systems. Full article

The management of European mountain landscapes is increasingly threatened by rural abandonment and escalating environmental risks. This study investigates an innovative Stewardship–Renewable Energy Communities model for the Central Apennines, exploring how post-seismic public reconstruction can serve as a financial engine for territorial maintenance. Utilizing Open Data Sisma administrative records and Photovoltaic Geographical Information System irradiation metrics, this research assesses the solar potential of 18 municipalities within the Sibillini seismic crater. To ensure a reliable baseline, a Building Suitability Coefficient was introduced as a conservative proxy for the public reconstruction sector. Results indicate that the implementation of a distributed network of 6.5 MWp across 325 public nodes, with a specific yield of 1390 kWh/kWp on the entire area, could generate 9 GWh/year. This translates to approximately EUR 1.08 million in annual revenue from energy incentives and sharing. This economic surplus provides a Stewardship Capacity sufficient to fund the active maintenance of 789.77 hectares per year through Nature-Based Solutions, based on a regional rate of 1200 EUR/ha. The novelty of this study lies in bridging post-disaster energy policy with landscape resilience, demonstrating that distributed rooftop solar portfolios represent a non-invasive, self-funding mechanism. By leveraging the reconstructed public stock, mountain territories can transition from passive neglect to active, energy-backed stewardship, offering a reproducible template for high-value cultural landscapes. Full article

The implementation of the circular economy (CE) at the local level remains uneven and strongly dependent on institutional and governance capacities, particularly in metropolitan areas characterised by fragmented administrative structures and differentiated local conditions. This article analyses the determinants shaping CE implementation in municipalities of the Lodz Metropolitan Area (Poland), with particular emphasis on inter-municipal cooperation and multilevel governance mechanisms. The study employs a mixed-methods approach combining semi-structured interviews with municipal representatives, correspondence with municipalities, and the analysis of strategic and institutional documents. The findings indicate that CE implementation in the studied area remains predominantly operational, with activities focused mainly on waste management and educational activities, while more integrated circular practices are underdeveloped. Significant differences were identified between municipalities, resulting from variations in institutional, organisational, and financial capacities, as well as governance capacity. Three types of municipalities were identified according to their level of CE implementation and engagement in supra-local cooperation. The study also reveals that inter-municipal cooperation remains limited, fragmented, and predominantly project-based, while coordination between governance levels is insufficiently institutionalised. In addition, limited cooperation between municipalities and private-sector actors constrains the development of local material loops and more systemic circular solutions. The article contributes to the literature by providing empirical evidence on CE implementation in a metropolitan area in Central and Eastern Europe and by linking circular economy research with multilevel governance and inter-municipal cooperation perspectives. The findings highlight the importance of governance capacity, coordination mechanisms, and supra-local institutional support for strengthening local circular transformation. Full article

Background/Objectives: South Korea became a super-aged society in 2024, and this demographic shift is unfolding alongside the depopulation of rural municipalities across the country. How spatial inequality and community social capital jointly relate to elderly health—and whether those relationships look different for younger versus older elderly—remains an open question. We investigated associations between two dimensions of community social capital (sense of belonging and neighbor communication), subjective perception of capital–provincial inequality, and self-rated health among Korean elderly, with separate analyses for the Young-Old (aged 60–69) and Old-Old (aged 70+). Methods: We used the 2024 Social Integration Survey from the Korea Institute of Public Administration (full sample N = 2588; elderly subsample N = 1020). Random intercept hierarchical linear models accounted for the nesting of individuals within 17 metropolitan cities and provinces. Stepwise models examined social capital antecedents, a healthcare satisfaction indirect association pathway, and the direct association of spatial inequality perception with health. The elderly subsample was stratified into Young-Old (N = 289) and Old-Old (N = 731). A mixed-effects ordered logistic regression with Liang–Zeger cluster-robust standard errors was estimated as a robustness check. Results: Sense of belonging was positively associated with subjective health among the elderly (B = 0.065, p < 0.05) as a net of rurality and socioeconomic controls. Perceived spatial inequality showed a negative association (B = −0.070, p < 0.05). The indirect association pathway through healthcare satisfaction was not supported (Sobel Z = −1.458, p = 0.144). Age-stratified models revealed a striking split: belonging was the dominant predictor for the Young-Old (B = 0.149, p < 0.01), while neighbor communication (B = 0.078, p < 0.05) and spatial inequality perception (B = −0.092, p < 0.01) were significant only among the Old-Old. The ordered logistic robustness check confirmed the negative association of perceived spatial inequality across all specifications. Conclusions: What predicts health in the younger elderly is not what predicts health in the older elderly. Korea’s Integrated Community Care Act, set for nationwide rollout in 2026, should account for this divergence—prioritizing psychological community attachment for the Young-Old and face-to-face social contact combined with regional equity for the Old-Old. Full article

This study analyzes the impact of socio-demographic factors on citizens’ perceptions of the functioning of local-level inclusion mechanisms, focusing on four dimensions: information, participation, transparency, and effectiveness. A mixed-methods approach is employed, combining: (1) a large-scale survey with 885 residents in three municipalities (Patos, Elbasan, and Mat) and (2) in-depth interviews with mayors, municipal councilors, and social service managers. The quantitative analysis was conducted through binary logistic regression models in SPSS version 27, as well as ordered logistic regression, examining the impact of socio-demographic factors such as age, education level, gender, employment status, and area of residence on the four dimensions of the study and the Inclusion Index. The qualitative component analyzes how local officials address citizen inclusion in key social policy areas such as employment, education, housing, social assistance, and social services. The results show that residence is the strongest predictor, with citizens in urban areas reporting higher levels of information, transparency, and effectiveness of participatory processes. Employment status is also associated with more positive perceptions, while gender and educational level show limited and inconsistent effects. Qualitative findings suggest that these differences are mediated by structural and institutional factors, such as infrastructure, administrative capacity and access to information. The study contributes to the literature on democratic innovation and participatory governance by showing that the impact of demographic factors on civic engagement is mediated by institutional and territorial conditions, particularly in developing countries. Full article

Disaster risk reduction and management are essential for sustainable development in territories highly exposed and vulnerable to natural hazards. Recent disasters in the Canary Islands have highlighted the importance of proactive preparedness and systemic approaches to risk management, emphasizing the need to better understand existing barriers to disaster risk reduction (DRR). This study develops an analysis of risk governance within the current planning instruments in the Canary Islands, the island of Tenerife, and the municipality of Candelaria. The research examines the integration of DRR across strategic, territorial, urban, and emergency planning at the regional, insular, and municipal levels. The findings identify key challenges and opportunities for integrating DRR within existing planning frameworks, highlighting both the potential and the limitations of current instruments as cross-cutting tools for building more resilient territories. While Tenerife has a relatively solid administrative and planning structure that could support a more systemic vision of risk, sectoral fragmentation and coordination gaps remain. Overall, the study contributes to the ongoing discussion on advancing risk governance from a systemic perspective at the local level. The challenges identified delineate the boundaries and directions for improvement, offering a valuable contribution to the existing body of knowledge. Full article