Search Results (764)

The long-term durability and structural integrity of modern buildings, which are inherently reliant on reinforced concrete, are governed by the rate of corrosion of embedded steel reinforcement. Corrosion kinetics, therefore, is not merely an academic exercise, but rather a critical foundation for predicting and extending a structure’s life span, mitigating safety risks, and ensuring the sustainability of the built environment against a host of environmental and chemical degradation factors. The present study conducts a comparative analysis of the short-term corrosion initiation behavior of steel reinforcement embedded in three distinct types of geopolymer binders, a cementitious paste, and a cementitious composite with natural aggregates. Electrochemical techniques, such as Open Circuit Potential (OCP) and linear polarization tests were used to characterize the behavior of the steel reinforcement embedded in the 4 types of samples. Additionally, these samples containing the reinforcement were further characterized using advanced microstructural techniques, specifically porosimetry, Nuclear Magnetic Resonance (NMR), and Scanning Electron Microscopy (SEM). Full article

Procedural approaches have long been used in game development to reduce authoring costs and increase content diversity; however, traditional rule-based systems struggle to scale narrative complexity, whereas recent large language model (LLM)-based methods often produce outputs that are structurally invalid or incompatible with real-time game engines. This gap reflects a fundamental limitation in current practice: generative models lack systematic mechanisms for managing executable game knowledge rather than merely producing free-form narrative texts. To address this issue, we propose a Game Knowledge Management System (G-KMS) that reformulates LLM-based narrative generation as a structured knowledge management process. The proposed framework integrates knowledge grounding, schema-governed generation, normalization-based repair, engine-aligned knowledge admission, and application within a unified pipeline. The system was evaluated on a compact 2D Unity-based RPG benchmark using automated structural and semantic analyses, engine-level playability probes, and a controlled human player study. The experimental results demonstrated high reliability in knowledge admission, stable procedural structures, controlled expressive diversity, and a strong alignment between system-level metrics and player-perceived narrative quality, indicating that LLMs can function as dependable knowledge-construction components when embedded within a governed management pipeline. Beyond the evaluated RPG setting, this study suggests a practical and reproducible approach that may be extended to other executable systems, such as interactive simulations and training environments. Full article

A three-dimensional discrete element method (DEM) framework was developed and applied to investigate the time-domain seismic response of a soil–pier system embedded in stratified dry sand. The numerical model was validated against analytical solutions to determine the ultimate vertical load capacity and internal forces when subjected to a lateral load at the pier head. Simulations were conducted to explore the influence of different excitation frequencies and amplitudes on soil–foundation interaction. Dynamic p–y curves were extracted at multiple elevations along the shaft to examine variations in lateral stiffness with depth. The results show that seismic loading significantly increases lateral displacement, and the residual response is strongly governed by the input motion amplitude. Peak lateral deformation and internal forces were observed when the excitation frequency coincided with the pier’s natural frequency. Both cyclic shear strain and ground settlement reached their maximum near the natural frequency of the soil deposit, and increased substantially with shaking amplitude. Full article

Background: The rapid diffusion of large language models (LLMs) such as Claude, ChatGPT, Gemini, LLaMA, and Mistral is reshaping logistics and supply chain management by embedding generative intelligence into planning, coordination, and governance processes. While prior studies emphasize algorithmic capability, far less is known about how differences in diffusion pathways shape productivity outcomes, managerial cognition, and institutional control. Methods: This study develops and applies an integrative analytical framework—the AI Diffusion Triad—comprising Productivity, Perspective, and Power. Using comparative qualitative analysis of five leading LLM ecosystems, the study examines how technical architecture, access models, and governance structures influence adoption patterns and operational integration in logistics contexts. Results: The analysis shows that diffusion outcomes depend not only on model performance but on socio-technical alignment between AI systems, human workflows, and institutional governance. Proprietary platforms accelerate productivity through centralized integration but create dependency risks, whereas open-weight ecosystems support localized innovation and broader participation. Differences in interpretability and access significantly shape managerial trust, learning, and decision autonomy across supply chain tiers. Conclusions: Sustainable and inclusive AI adoption in logistics requires balancing operational efficiency with interpretability and equitable governance. The study offers design and policy principles for aligning technological deployment with workforce adaptation and ecosystem resilience and proposes a research agenda focused on diffusion governance rather than algorithmic advancement alone. Full article

The rule of law, a foundational value of the European Union as enshrined in Article 2 of the Treaty on European Union, faces challenges in implementation due to historical and political factors that have evolved over the past decade, particularly within Member States in the administrative domain. While institutional backsliding in countries like Hungary and Poland has drawn significant political attention, less emphasis has been placed on the role of public administrations in upholding or undermining the rule of law on a day-to-day basis. This paper argues that the sustainability of the rule of law in the EU requires more than legal compliance mechanisms. These alone do not address the underlying administrative and cultural factors necessary for effective implementation. Instead, it requires closer attention to how rule-of-law principles are embedded in the everyday functioning of public administrations. This argument is informed by the authors’ systematic examination of recent EU monitoring practices and administrative reform instruments. Adopting a mixed conceptual-empirical methodology, the paper draws on primary data from EU Rule of Law Reports (2020–2024), the EU Justice Scoreboard, the Recovery and Resilience Facility (RRF), and the Technical Support Instrument (TSI), complemented by relevant OECD/SIGMA indicators. Several structural obstacles emerge from the analysis. These include symbolic compliance, whereby organisations adopt formal structures without corresponding behavioural change; weak institutional leadership that fails to drive reform momentum; and the absence of integrated performance metrics, which hampers meaningful accountability. Fragmented ownership of reform agendas, in turn, breeds inconsistency in implementation. These challenges point to the limitations of a technocratic or legalistic approach to rule-of-law governance. Strategic leadership and organisational flexibility emerge from the evidence as preconditions—not merely facilitators—of genuine internalisation, though the relationship is context-dependent. Digitalisation can reinforce these dynamics, yet its contribution depends on whether it is embedded within broader integrity-oriented reforms. The paper advocates for a shift from externalized compliance mechanisms to a model that emphasizes administrative ownership through specific strategies such as developing integrity-based leadership programs and embedding governance practices that prioritize transparency and accountability. It proposes concrete institutional reforms, including performance-linked conditionalities that tie funding to measurable outcomes, ethical leadership academies to train future leaders, integrity audits to ensure accountability, and administrative benchmarking to set clear standards, as tools to foster autonomous, value-driven public institutions capable of adapting to evolving governance challenges while maintaining core democratic values. Full article

In the context of global decarbonization and digital transformation, this study investigates whether and how the adoption of artificial intelligence (AI) promotes corporate energy transition, as measured by firms’ total energy consumption, energy intensity, and carbon emission intensity. Drawing on the theories of general-purpose technology (GPT), the resource-based view (RBV), and dynamic capabilities, the paper conceptualizes AI as a production-embedded technological capability that enhances intelligent automation, energy monitoring, and resource coordination within firms. Using panel data on Chinese A-share listed firms from 2012 to 2024, and capturing AI adoption through observable changes in firms’ production-related capital intensity, the analysis employs firm- and year-fixed effects, instrumental variables, and a dynamic event-study design to address endogeneity and temporal dynamics. The results show that AI adoption reduces firms’ energy consumption by approximately 2.0%, energy intensity by 1.8%, and carbon emission intensity by 2.3% within two to three years after adoption. Mechanism tests indicate that green innovation, operational efficiency, and resource allocation efficiency mediate this effect. Heterogeneity analyses reveal more substantial effects among non-state, large-scale, and technology-intensive firms operating in highly marketized regions. The findings broaden understanding of AI as a strategic sustainability technology and provide actionable implications for policymakers to align digital and energy governance to achieve carbon neutrality goals. Full article

This study explores how teachers’ work sustainability is shaped through everyday governance practices within private higher education institutions in China. Using a constructivist grounded theory approach, the analysis draws on long-term fieldwork and in-depth interviews with teachers, administrators, leaders, and students from two private colleges. The findings suggest that teachers’ difficulties do not stem from isolated adverse incidents, but rather from an ongoing organizational process embedded in routine management practices. Evaluation-centered promotion systems, relationship-based governance, and data-driven oversight interact to restructure how teaching work is organized, recognized, and assessed. Professional contributions are frequently treated as negotiable outcomes subject to managerial discretion, while informal alignment practices and selective monitoring gradually narrow teachers’ space for professional judgment and initiative. Despite accumulating dissatisfaction, most teachers remain in their positions. Occupational identity, social expectations, and constrained labor mobility limit realistic exit options, transforming short-term accommodation into prolonged endurance. In this context, teacher retention reflects not organizational stability, but the persistence of governance conditions that challenge the long-term sustainability of teachers’ work. By examining how routine management practices gradually reshape teachers’ work, this study highlights an overlooked dimension of sustainability in higher education: the long-term viability of teachers’ professional lives within existing governance arrangements. Unlike studies that conceptualize teachers’ difficulties through the lens of workplace bullying or interpersonal conflict, this study focuses on how ordinary governance practices shape long-term work sustainability without overt confrontation. Full article

As a critical infrastructure carrier underpinning the cross-regional circulation of data elements within socioeconomic systems, intelligent computing centres (ICCs) confront a pivotal practical challenge amid the transition to a green economy: whether they can synergistically drive digital economy development while facilitating green growth. This question demands empirical verification from the perspective of social science systems practice. Drawing on panel data covering 292 Chinese cities at the prefecture level and above over the period 2010–2023, this study constructs a multidimensional difference-in-differences model with ICC construction as the core explanatory variable. Adopting a systemic analytical framework that integrates urban governance, industrial organization and regional coordination, it explores the impact of ICC deployment on urban environmental performance as well as the operational mechanisms embedded in socioeconomic practices. The findings demonstrate that ICC construction significantly enhances urban environmental performance. This conclusion remains robust after addressing endogeneity concerns and conducting multiple robustness tests. Heterogeneity analysis, grounded in social and regional contextual disparities, indicates that this positive effect is more pronounced in non-resource-based cities, cities with a strong focus on environmental governance and cities located in western China. Mechanism tests further clarify that such effects are achieved through two critical pathways of organizational and systemic transition, fostering green innovation and advancing industrial structure optimization. Moreover, by constructing a Spatial Durbin Model to analyse interregional systemic linkages, this study identifies a significant positive spatial spillover effect of ICC construction. This outcome reflects the cross-regional synergistic value of digital infrastructure within the national green economy system. From the perspective of social science systems practice, this study innovatively reveals the embedded role of digital infrastructure in the green economy system. It provides empirical support for optimizing the spatial layout of ICCs and offers targeted policy references for promoting the coordinated development of the digital economy and ecological environmental protection. Full article

The Jeju Olle Trail has evolved from a grassroots initiative into a contested space where post-pandemic growth intersects with environmental limits and fragmented governance. Moving beyond environment-centric models, this study examines the trail as a transcultural walking tourism system. The authors triangulated 900 user-generated content (UGC) narratives from major travel platforms (Korean, Chinese, and English) with semi-structured interviews from three key institutional informants (NTO, RTO, and NPO). The analysis explores how sustainable experiences are negotiated in practice. Findings suggest that Self-Determination Theory (SDT) constructs like autonomy are not universal constants but are culturally mediated through Western “digital detox,” Korean “collective healing,” and Chinese chūxīn (original heart) narratives. Institutional and narrative data indicate that these experiences appear linked to managing governance tensions between national mandates and localized stewardship. The study concludes that experiential sustainability involves navigating trade-offs regarding narratively signaled environmental impacts and community capacity. By framing walking tourism as a governance-dependent practice, this research demonstrates how culturally embedded mechanisms shape destination viability. Full article

In the coordinated management of air pollutants and carbon emissions, governments impose differentiated regulatory requirements on gases, while mitigation technologies have heterogeneous abatement potential. However, existing studies on emission quota management, an important mitigation instrument, focus on single gases and neglect integrating multigas policy preferences and heterogeneous abatement potentials, weakening policy responsiveness and scheme feasibility. This study develops a two-stage allocation framework. First, policy preference weights are introduced to evaluate multigas synergistic emission reduction potential and determine maximum quota reduction constraints for each gas. Second, policy preference weights and a non-radial directional distance function (NDDF) are embedded in a zero-sum gains data envelopment analysis (ZSG-DEA) model to capture multigas heterogeneity in policy preferences and reduction constraints, improving applicability and feasibility. Applied to the coal-fired power sector, the results show that, relative to the equal weight scenario, CO₂ incentive intensity rises by 22% under a carbon priority scenario and SO₂ incentive intensity increases by 13% under a pollution priority scenario, while the maximum quota reduction ratios of CO₂ and SO₂ are constrained from 41.75% to 9.18% and from 78.57% to 37.28%, respectively, ensuring alignment with policy preferences and keeping abatement within feasible ranges to support carbon neutrality and pollution control targets, thereby contributing to sustainable development. Full article

Instant messaging services are the main modern means of communication because they allow the exchange of messages between people anywhere and through many types of devices. Smishing involves sending text messages spoofing banks, government institutions, or companies in order to deceive. These messages often include malicious links that redirect users to fraudulent websites designed to steal personal information and commit financial fraud, identity theft, and extortion, among other crimes. Detecting smishing requires techniques to prevent access to dynamic links generated by cybercriminals to take control of devices or to consult blacklists of malicious links. Optical Character Recognition (OCR) recognizes text embedded in images without accessing links. This paper presents a conceptual model that uses OCR to extract text from messages suspected of smishing from a screenshot of a mobile device so that further processing can analyze whether it is smishing. Full article

This paper conducts a PRISMA-guided systematic review of the empirical literature on environmental, social, and governance (ESG) risk integration in European banking. Using evidence systematically retrieved from Scopus, ScienceDirect, IDEAS/RePEc, and SSRN, the review synthesizes 51 peer-reviewed and working studies published between 2020 and 2025, reflecting the recent and rapidly evolving nature of this research field. The analysis classifies the literature into three domains—pricing and allocation, monitoring and stress testing, and governance and management control systems—and evaluates whether ESG variables operate as first-order drivers within production credit-risk models. The results indicate that while ESG signals are increasingly incorporated into pricing decisions, stress-testing exercises, and governance frameworks, no study provides verifiable evidence of full model-level integration within Probability of Default (PD) or Loss Given Default (LGD) models. The contribution of this review lies in systematically identifying the structural, data-related, and supervisory constraints that sustain this integration gap and in proposing a roadmap that distinguishes incremental ESG sensitivity from genuine prudential model embedding. Overall, the findings clarify that ESG responsiveness in European banking is substantial, yet integration into core risk models remains limited. Full article

Rapid urbanization and industrialization have significantly reshaped rural landscapes in metropolitan fringe areas, resulting in “hybridized” characteristics. This study establishes an analytical framework to systematically characterize hybrid rural landscapes, diagnose specific local issues, reveal their spatial differentiation patterns and driving mechanisms, and propose targeted governance strategies. Taking 124 rural units in Baoshan District, Shanghai as a case, multi-source data from the latest available years (2020–2023) were compiled as a cross-sectional snapshot, and a comprehensive indicator system integrating landscape pattern (P), social function (F), and spatial vitality (V) was developed. Utilizing multi-source geospatial data—including land-use maps, points of interest, and mobile signaling data—Gaussian Mixture Models were applied to classify typical hybrid landscape types. Spatial evolution processes and underlying driving forces were further interpreted through remote sensing imagery analysis, field investigations, and policy document reviews. Eleven distinctive hybrid rural landscape types (HTs) were characterized, forming a spatial gradient from urban to rural, encompassing “high-density urbanized” → “ecologically embedded” → “production–living integrated” → “traditional rural landscapes”. Additionally, five representative evolutionary patterns—“urban restructuring”, “ecological orientation”, “industrial-driven transition”, “transitional hybridization”, and “traditional preservation”—were identified, shaped by spatial configuration, planning policies, industrial investments, and demographic dynamics. The framework enhances understanding of the complexity and evolutionary dynamics of rural landscapes, providing theoretical insights and practical guidance for effective typological governance and targeted policy interventions. Full article

This article examines how everyday architecture can advance spatial justice in post-active conflict cities through ethnographic and participatory design. Drawing on a decade of work by the StreetSpace studio in Belfast (2015–2025), the paper explores how architecture students and community participants co-design spatial strategies that enhance mixed-use mid-density living, inclusive mobility, and street-level accessibility. In a context where car dominance, segregation, and privatisation of public space continue to fragment urban life, the everyday street becomes a testbed for envisioning an equitable and community-centred city. The studio’s methodology is grounded in ethnographic engagement, informed by an embedded anthropologist, and includes stakeholder mapping, walking workshops, and collaborative drawing. These practices reveal lived experiences and shape community-driven briefs for housing, schools, public spaces, and multifunctional infrastructure. Anchored in spatial justice discourse and feminist theory (Jane Jacobs, David Harvey, Roberto Rocco, Phil Hubbard, Leslie Kern, and Caroline Criado Perez), the work positions the everyday as a site of architectural agency and proposes a contemporary vernacular that is socially embedded and climate-resilient. This work unfolds through complex and often contested processes that require sustained, iterative engagement with people and places. Meaningful collaboration is neither linear nor inherently caring; it frequently involves conflict, disagreement, and competing priorities that must be navigated over time. Through long-term relationships with government departments, local authorities, and NGOs, StreetSpace demonstrates how architectural pedagogy can nonetheless contribute to policy formation and more inclusive urban redevelopment by engaging in compromise, critical negotiation, and moments of care alongside friction and resistance. Through a series of collaborations and public events the project has contributed to the transformation of Botanic Avenue, informed studies of the East Belfast Greenways through contributions to Groundswell and participated in embedded public processes in collaboration with PPR, culminating in an exhibition at the MAC in Belfast in 2025. Full article

This study examines the performance implications of CEO duality from a configurational governance perspective, with particular attention given to its relevance within an ESG-oriented framework. While prior research on CEO duality has produced inconsistent findings, much of the literature relies on variable-centered approaches that overlook the systemic and context-dependent nature of governance mechanisms. Drawing on agency theory, stewardship theory, and resource dependence theory, we analyze 59 publicly listed South Korean firms between 2018 and 2022 using fuzzy-set qualitative comparative analysis (fsQCA). Five governance-related conditions—CEO duality, ownership concentration, CEO tenure, institutional ownership, and environmental dynamism—are calibrated into fuzzy sets to identify causal configurations associated with high firm performance, defined as membership in the top 30% of return on assets (ROA). The results reveal six equifinal pathways to high performance, two of which exhibit particularly strong consistency and coverage. These dominant configurations show that CEO duality contributes positively to performance when embedded in either strong internal governance alignment or robust external monitoring under dynamic conditions. By demonstrating that the effectiveness of CEO duality is contingent upon its governance configuration, this study challenges one-size-fits-all prescriptions and contributes to the ESG literature by highlighting the conditional role of leadership structure in sustainable value creation. Full article