Search Results (7,234)

With the rapid development of the Internet of Things (IOT), 5G, and modern power systems, demand-side loads are becoming increasingly observable and remotely controllable, which enables demand-side flexibility to participate more actively in grid dispatch and emergency support. Under extreme rainstorm conditions, however, component failure risk rises and the availability and dispatchability of demand-side flexibility can change rapidly. This paper proposes a risk-aware emergency regulation framework that translates rainstorm information into actionable multi-load aggregation decisions for urban power systems. First, demand-side resources are quantified using four response attributes, including response speed, response capacity, maximum response duration, and response reliability, to enable a consistent characterization of heterogeneous flexibility. Second, a backpropagation (BP) neural network is trained on long-term real-world meteorological observations and corresponding reliability outcomes to estimate regional- or line-level fault probabilities from four rainstorm drivers: wind speed, rainfall intensity, lightning warning level, and ambient temperature. The inferred probabilities are mapped onto the IEEE 30-bus benchmark to identify high-risk areas or lines and define spatial priorities for emergency response. Third, guided by these risk signals, a two-level coordination model is formulated for a load aggregator (LA) to schedule building air conditioning loads, distributed photovoltaics, and electric vehicles through incentive-based participation, and the resulting optimization problem is solved using an adaptive genetic algorithm. Case studies verify that the proposed strategy can coordinate heterogeneous resources to meet emergency regulation requirements and improve the aggregator–user economic trade-off compared with single-resource participation. The proposed method provides a practical pathway for risk-informed emergency regulation under rainstorm conditions. Full article

This study examines how corporate participation in green technology standard-setting affects two dimensions of green innovation–substantive and symbolic green innovation–through the mediating role of knowledge integration and across different stages of the firm life cycle. Analyzing panel data from Chinese A-share listed firms (2010–2023), we find that standard-setting participation significantly enhances both types of innovation, with a stronger and more enduring effect on substantive innovation. The effects exhibit clear life cycle heterogeneity: substantive green innovation is consistently enhanced across all stages of the firm life cycle, whereas symbolic green innovation is predominantly reinforced during the maturity stage. Grounded in the knowledge-based view and institutional theory, our findings highlight how institutional engagement fosters sustainable innovation by strengthening firms’ capacity for knowledge acquisition and integration. This research advances understanding of the strategic value of standard-setting in sustainability efforts and provides actionable insights for aligning standardization practices with long-term innovation goals. Full article

This research simulates Aswan City’s urban transportation dynamics utilizing the Multi-Agent Transport Simulation (MATSim) framework. As a fast-expanding urban center, Aswan has many transportation difficulties that require extensive modeling toward sustainable mobility solutions. MATSim, recognized for its agent-based methodology, offers a detailed portrayal and analysis of individual travel behaviors and their interactions within the metropolitan transportation system. This study compiled and combined many databases, including demographic data, road infrastructure, public transit plans, and travel demand trends. These data are altered to produce a realistic digital clone of Aswan’s transportation system. Simulated scenarios analyze the consequences of several actions, such as increased public transit scheduling, traffic flow management, and the adoption of alternative transport modes, on minimizing congestion and boosting accessibility. Pilot findings show that MATSim effectively captures the distinct features of Aswan’s transportation network and offers practical insights for decision-makers. The results identified some opportunities to improve mobility and promote sustainable urban growth in developing cities. This study emphasized the importance of agent-based simulations in designing future transportation systems and urban infrastructure. Full article

To maintain power system stability and supply quality when integrating doubly fed induction generator (DFIG)-based wind energy conversion systems (DFIG-WECSs), regulators regularly update grid codes specifying low voltage ride-through (LVRT) requirements. This paper presents a systematic literature review (SLR) on the use of STATCOMs to enhance LVRT capability in DFIG-WECSs. Objectives included a structured literature search, bibliographic analysis, thematic synthesis, trend identification, and proposing future research directions. A PRISMA-based methodology guided the review, utilising PRISMA 2020 for Abstracts in the development of the abstract. The final search was conducted on Scopus (31 March 2025). Eligible studies were primary research in English (2009–2014) where STATCOM was central to LVRT enhancement; exclusions included non-English studies, duplicates, reviews, and studies without a STATCOM focus. Quality was assessed using an adapted Critical Appraisal Skills Programme (CASP) tool. No automation or machine learning tools were used. Thirty-eight studies met the criteria and were synthesised under four themes: operational contexts, STATCOM-based schemes, control strategies, and optimisation techniques. Unlike prior reviews, this study critically evaluates merits, limitations, and practical challenges. Trend analysis shows evolution from hardware-based fault survival strategies to advanced optimisation and coordinated control schemes, emphasising holistic grid stability and renewable integration. Identified gaps include cyber-physical security, techno-economic assessments, and multi-objective optimisation. Actionable research directions are proposed. By combining technical evaluation with systematic trend analysis, this review clarifies the state of STATCOM-assisted LVRT strategies and outlines pathways for future innovation in DFIG-WECS integration. Full article

Existing office buildings in Australia contribute to 24% of the nation’s electricity consumption and 10% of greenhouse gas emissions, with energy use projected to rise by 84%. Meeting the 2050 sustainability target and United Nations (UN) 17 Sustainable Development Goals (SDGs) requires improving sustainability within existing office buildings. This systematic review examines net zero energy and climate resilience strategies in these buildings by analysing 74 studies from scholarly literature, government reports, and industry publications. The literature search was conducted across Scopus, Google Scholar, and Web of Science databases, with the final search in early 2025. Studies were selected based on keywords and research parameters. A narrative synthesis identified key technologies, evaluating the integration of net zero principles with climate resilience to enhance energy efficiency through HVAC modifications. Technologies like heat pumps, energy recovery ventilators, thermal energy storage, and phase change materials (PCMs) have been identified as crucial in reducing HVAC energy usage intensity (EUI). Lighting control and plug load management advancements are examined for reducing electricity demand. This review highlights the gap between academic research and practical applications, emphasising the need for comprehensive field studies to provide long-term performance data. Current regulatory frameworks influencing the net zero transition are discussed, with recommendations for policy actions and future research. This study links net zero performance with climate adaptation objectives for existing office buildings and provides recommendations for future research, retrofit planning, and policy development. Full article

Occupational Health and Safety (OHS) in educational settings is a vital responsibility that is often inconsistently implemented. There is a need for research to bridge the gap between policy and practice. This study employed a cross-sectional mixed-methods design in six schools in the capital city of Indonesia to identify key implementation barriers, strategies, and compliance levels in OHS. Data were collected from 217 teachers using a structured KPAP (Knowledge, Attitudes, Perceptions, Practices) survey and from an additional 38 teachers via Focus Group Discussions (FGDs). Quantitatively, teachers showed highly positive attitudes (99.4% viewing OHS as a professional duty) and generally positive perceptions but implementation practices were sub-optimal (e.g., low participation in drills and PPE usage), showing a gap between awareness and action. Qualitatively, the main barriers identified were a lack of specific OHS regulation or guidance for schools, limited resources/infrastructure, and the perception of OHS as a low priority. Management strategies focused on external collaboration and ongoing in-school initiatives. In conclusion, a significant gap exists between OHS awareness and its integration into school management, highlighting the urgent need for strengthened governance, comprehensive policies, and sustained capacity-building to ensure a proactive, safe, and sustainable school environment for staff and students. Full article

The rapid increase in electric vehicle (EV) ownership necessitates the adaptation of fuel stations to charging infrastructure and the re-evaluation of capacity planning. In the literature, demand forecasting and installation costs are mostly examined; however, station-scale queue analyses supported by field data remain limited. This study aims to examine the integration of EV charging in fuel stations through simulation-based capacity analyses, taking current conditions into account. In this context, a scenario in which one and two dual-hose pumps at a fuel station located on the Turkey–Istanbul E-5 highway side-road is converted into a charging unit has been evaluated using a discrete-event microsimulation model. The analyses were conducted using a discrete event-based microsimulation model. The simulation inputs were derived from field observations and survey data, including the hourly arrival rates of internal combustion engine vehicles (ICEVs), the dwell times at the station, and the charging durations of EVs. In the study, station capacity and service performance were evaluated under scenarios representing EV shares of 5%, 10%, and 20% within the country’s passenger vehicle fleet. Within the scope of the study, the hourly arrival rates and dwell times of ICEVs were determined through field measurements, while EV charging durations were assessed by jointly analyzing field observations and survey data. Simulation results showed that the average number of waiting vehicles increases as the EV share rises; for example, in the 10% EV share scenario, 15.6 (±0.84) EVs were observed waiting within the station, while 34.06 (±1.23) EVs were identified in the 20% scenario. These queues constrict internal circulation within the station, limiting the maneuverability of ICEVs and causing delays in overall service operations. Furthermore, when two dual-hose pumps are replaced with charging units, noticeable increases in waiting times emerge, particularly during the evening peak period. Specifically, 5.88% of ICEVs experienced queuing between 17:00–18:00, rising to 12.33% between 18:00–19:00. In conclusion, this study provides a practical and robust model for short- and medium-term capacity planning and offers data-driven, actionable insights for decision-makers during the transition of fuel stations to EV charging infrastructure. Full article

In post-Soviet Georgia, the renewed visibility of religion in the public sphere has generated ambivalent effects, fostering both social cohesion and identity-based exclusion. This article focuses on the work I Am the Way by Georgian Orthodox thinker Zurab Kiknadze to explore how a non-instrumental, ethics-based conception of public religion can be sociologically conceptualized. Drawing on a qualitative, hermeneutic-narrative method, the analysis identifies two core motifs in Kiknadze’s thought—“spiritual journey” and “silent witness”—and interprets them through the lenses of public religion theory (Casanova), lived religion paradigms (McGuire, Ammerman), and post-secular debates (Habermas). The findings indicate that Kiknadze understands faith not as a marker of dogmatic or ethno-political belonging but as a practice contributing to ethical continuity and the reconstruction of social trust. Within this framework, “silent witness” is defined as a form of faith grounded in consistency, humility, and action-oriented conviction; it is proposed as a transferable sociological mechanism that supports trust, reconciliation, and inclusive citizenship in transitional societies. Centering on the Georgian case, this article offers a conceptual contribution to rethinking the public role of religion in post-authoritarian contexts within an ethical framework. Full article

Households are the major contributor to food waste generation in the European Union according to the recently published data from Eurostat. Promoting food systems sustainability and aspiring to achieve the United Nations SDG 12.3 requires a better insight to the underlying drivers of the household food waste occurrence. The present study presents the combination of a well-established method of acquiring information, the questionnaire surveys, with a state-of-the-art technology for data imputation and interpretation using machine learning (ML). The Food Loss and Waste Prevention Unit (FLWPU) of the municipality of Halandri employed two surveys within the framework of the European funded projects Food Connections and FOODRUS. The first questionnaire was designed for rapid completion, to maximize response rates and minimize respondent burden, ensuring the collection of a consistent core dataset. A total of 154 replies were collected. The second questionnaire, associated with FOODRUS, was more detailed, enabling the participants to provide more in-depth information on their household food waste (HHFW) practices. In total, 43 responses were collected. ML algorithms were applied for data enhancement and data clustering. Specifically, ML and statistical techniques are applied for data imputations. An XGBoost algorithm was trained so as to capture complex relationships between variables. Behavioral intentions and effective strategies for reducing food waste at the community level are identified from the responses of both questionnaires, while a clustering of respondents in five groups emerged by using k-means, thus providing valuable insight into targeted HHFW prevention action plans. Full article

To address the pervasive challenges of resource inefficiency and static management in the hospitality sector, this study proposes a novel management framework that synergistically integrates Model Predictive Control (MPC) with Green Human Resource Management (GHRM). Methodologically, the framework establishes a dynamic closed-loop architecture that cyclically links environmental sensing, predictive optimization, plan execution and organizational learning. The MPC component generates data-driven forecasts and optimal control signals for resource allocation. Crucially, these technical outputs are operationally translated into specific, actionable directives for employees through integrated GHRM practices, including real-time task allocation via management systems, incentives-aligned performance metrics, and structured environmental training. This practical integration ensures that predictive optimization is directly coupled with human behavior. Theoretically, this study redefines hospitality operations as adaptive sociotechnical systems, and advances the hospitality energy-saving management framework by formally incorporating human execution feedback, predictive control theory, and dynamic optimization theory. Empirical validation across a sample of 40 hotels confirms the framework’s effectiveness, demonstrating significant reductions in daily average water consumption by 15.5% and electricity usage by 13.6%. These findings provide a robust, data-driven paradigm for achieving sustainable operational transformations in the hospitality industry. Full article

As sustainability becomes a strategic priority, the Information Technology (IT) sector faces pressure on both reducing its environmental impact and leading in innovation. This study examines how Green Human Resource Management (GHRM) practices influence employees’ Green IT Attitudes (GITA) and beliefs within the IT industry. Guided by the Belief–Action–Outcome (BAO) framework, it explores how HR strategies can foster eco-conscious mindsets that support sustainable behaviour. A quantitative cross-sectional design was used, collecting data through a validated questionnaire. The study was conducted in Australia, focusing on IT professionals employed. Responses from 112 IT professionals, determined through G*Power sample estimation, were analysed using SPSS 28.0.1 with regression techniques to assess the relationship between GHRM practices and environmental attitudes and beliefs. Results indicate that GHRM practices have a modest but significant positive effect on employees’ green IT attitudes and beliefs, supporting the view that structured HR initiatives can shape sustainability-driven mindsets. The findings emphasize the strategic role of HR in embedding sustainability within organizational culture, particularly in technology-driven environments. The study offers practical guidance for IT organizations aiming to integrate sustainability into internal systems by leveraging HRM. Future research should examine moderating variables and long-term behavioural effects, enhancing our understanding of sustainability-focused HRM in the digital era. Full article

Urban resilience has emerged as a critical paradigm for addressing the intertwined challenges of climate change, rapid urbanization, and social inequality, positioning green public spaces as catalysts for social, ecological, and institutional transformation. This article presents a systematic review conducted under the PRISMA 2020 guidelines, examining how collaborative and community participation influenced transformative urban resilience in green public spaces between 2021 and 2025. A total of 6179 records were initially identified across ScienceDirect and MDPI (last search: July 2025), of which 26 empirical studies met the inclusion criteria (peer-reviewed, empirical, published 2021–2025). Methodological rigor was strengthened through the application of the Mixed Methods Appraisal Tool (MMAT, 2018) and confidence in qualitative evidence was assessed using the GRADE-CERQual approach, enhancing transparency and reliability. Data extraction and synthesis followed a theoretical-methodological coding framework, allowing for the comparison of participatory strategies, typologies of green spaces, resilience dimensions, and applied instruments. The results show that multi-actor co-management, co-design, and community self-organization are the most frequent participatory strategies, while urban green infrastructure, pocket parks, and urban gardens constitute the predominant spatial contexts. Socio-ecological and social-participatory resilience emerged as dominant theoretical perspectives, with qualitative and mixed-methods designs prevailing across studies. Evidence synthesis through GRADE-CERQual identified seven key pathways—multi-actor co-management, Nature-based Solutions, community-based actions, social equity, cultural identity, institutional innovation, and planned densification—each contributing differently to resilience dimensions. Overall, the findings highlight that transformative resilience depends on deep, inclusive participatory processes, multi-level governance, and the integration of social, ecological, and cultural dimensions. Despite the heterogeneity of designs and unequal data adequacy, this review confirms that transformative urban resilience is a co-produced process grounded in community action, ecological sustainability, and collaborative governance. Strengthening underexplored areas—technological innovation, cultural resilience, and standardized methodological instruments—is essential for advancing comparative research and practice. Full article

In the hospitality industry, corporate social responsibility practices are getting more recognition as a strategic driver of stakeholders’ sustainable behaviors. This study creates and tests a moderated serial mediation model that connects hotel CSR activities to guests’ pro-environmental behavior (PROE). In addition, moral elevation (ME) and pro-social behaviors of guests (PSO) are posited as affective and behavioral mediating mechanisms, whereas the perceived transparency (TRA) of hotel actions is investigated as a moderator. The survey data were collected from 426 hotel guests who had stayed in hotels in the Turkish Republic of Northern Cyprus (TRNC) and used partial least squares structural equation modeling (PLS-SEM) to analyze it. The findings reveal that CSR does have a positive effect on ME, which sequentially makes ME affect PSO and PROE behavior positively. The research shows that the moderator TRA also amplifies the relationship strength between CSR and ME, which suggests that transparent actions of hotels do have a positive emotional impact on guests. The research contributes to hospitality literature and also sustainability literature by identifying ME as an emotional mechanism and TRA as a moderating condition that alter guests’ behaviors. As managerial implications, the research underlines the value of creating CSR practices that are both transparent and authentic to guests and stakeholders to ultimately maximize the engagement of guests in the context of sustainability. Full article

While the international influence of the Programme for International Student Assessment (PISA) on education policy debates is well recognized, the degree to which PISA findings drive actual policy reforms and classroom practices remain debated. Using PISA as a case, this article examines how educational research is translated into policy responses and practices in German federalism, focusing specifically on immigrant students—a key group within German education reform discourse. It analyzes the reflection of PISA findings from the 2000, 2018, and 2022 assessments on immigrant student performance in the resolutions of the Standing Conference of Ministers of Education and Cultural Affairs, the process of implementation by the federal states (Länder), and the effect on school-level practice. Framed by research knowledge mobilization theory, the article investigates the relationships among research production, mediation, and usage, clarifying the interplay between educational research, policy, and practice in Germany’s federal system. Historical analysis exposes consistent gaps between research-derived recommendations and binding, actionable change at both policy and practice levels, often due to challenges in developing evidence-based and consistently applied policy measures across the Länder. The article concludes with practical recommendations for improving the impact of interdisciplinary, policy-oriented research on policy and practice, considering the complexities of Germany’s federal governance. Full article

The use of ships and boats as sea-state (SS) measurement platforms has the potential to expand ocean observations while providing actionable information for real-time operational decision-making at sea. Within the framework of the Wave Buoy Analogy (WBA), this work develops an inverse approach in which efficient simulations of wave-induced motions of an advancing vessel are used to train a neural network (NN) to predict SS parameters across a broad range of wave climates. We show that a reduced set of novel motion discriminant variables (MDVs)—computed from short time series of heave, roll, and pitch motions measured by an onboard inertial measurement unit (IMU), together with the vessel’s forward speed—provides sufficient and robust information for accurate, near-real-time SS estimation. The methodology targets small, barge-like tugboats whose operations are SS-limited and whose motions can become large and strongly nonlinear near their upper operating limits. To accurately model such responses and generate training data, an efficient nonlinear time-domain seakeeping model is developed that includes nonlinear hydrostatic and viscous damping terms and explicitly accounts for forward-speed effects. The model is experimentally validated using a scaled physical model in laboratory wave-tank tests, demonstrating the necessity of these nonlinear contributions for this class of vessels. The validated model is then used to generate large, high-fidelity datasets for NN training. When applied to independent numerically simulated motion time series, the trained NN predicts SS parameters with errors typically below 5%, with slightly larger errors for SS directionality under relatively high measurement noise. Application to experimentally measured vessel motions yields similarly small errors, confirming the robustness and practical applicability of the proposed framework. In operational settings, the trained NN can be deployed onboard a tugboat and driven by IMU measurements to provide real-time SS estimates. While results are presented for a specific vessel, the methodology is general and readily transferable to other ship geometries given appropriate hydrodynamic coefficients. Full article