Search Results (15,718)

This study presents and evaluates three sampling strategies to characterize electricity demand in regions of Colombia with limited metering infrastructure. These areas lack Advanced Metering Infrastructure (AMI), relying instead on traditional monthly consumption records. The objective of the research is to obtain user samples that are representative of the original population and logistically efficient, in order to support energy planning and decision-making. The analysis draws on five years of historical data from 2020 to 2024. It includes monthly energy consumption, geographic coordinates, customer classification, and population type, covering over 500,000 users across four subregions of operation determined by the region grid operator: North, South, Center, and East. The proposed methodologies are based on Shannon entropy, consumption-based probabilistic sampling, and Kullback–Leibler divergence minimization. Each method is assessed for its ability to capture demand variability, ensure representativeness, and optimize field deployment. Representativeness is evaluated by comparing the differences in class proportions between the sample and the original population, complemented by the Pearson correlation coefficient between their distributions. Results indicate that entropy-based sampling excels in logistical simplicity and preserves categorical diversity, while KL divergence offers the best statistical fit to population characteristics. The findings demonstrate how combining information theory and statistical optimization enables flexible, scalable sampling solutions for demand characterization in under-instrumented electricity grids. Full article

This study investigates the factors influencing green purchase behavior in emerging economies, focusing on Indonesian consumers’ preferences for organic food products. While sustainability awareness is growing globally, limited research has examined how environmental knowledge and trust interact with marketing efforts to shape green purchasing decisions in developing market contexts like Indonesia. The research model incorporates five constructs: environmental knowledge (awareness of ecological issues), green trust (confidence in environmental claims), green marketing mix (eco-oriented strategies for product, price, place, and promotion), green purchase intention (likelihood of buying eco-friendly products), and green purchase behavior (actual sustainable buying decisions). Data from 211 valid respondents were analyzed using structural equation modeling. The results indicate that environmental knowledge directly influences green trust and the green marketing mix but not green purchase intention or behavior. Instead, it affects behavior indirectly through trust and intention. Contrary to expectations, green trust does not influence the green marketing mix, suggesting it may operate independently of marketing strategies. Similarly, the green marketing mix does not significantly influence green purchase intention or behavior, suggesting that marketing strategies alone may be insufficient in driving sustainable consumer choices. These findings highlight the important role of environmental knowledge in fostering consumer trust and indirectly guiding green purchasing behavior in emerging markets. By promoting sustainable consumption through knowledge and trust, this study offers insights into consumer behavior as a pathway to advancing planetary health. This study advances the Theory of Planned Behavior by integrating green trust and the green marketing mix to explain how trust and economic factors shape green purchasing behavior. Practical implications suggest that businesses should adopt targeted green marketing strategies, such as educational campaigns, eco-labeling, or certifications, to enhance environmental awareness, build consumer trust, and encourage sustainable purchasing decisions. This study contributes to the literature by examining how environmental knowledge indirectly influences green purchase behavior through the mediation of trust and intention within the context of an emerging market. Full article

The aim of this study was to analyse the relationship between sustainability and customer lifetime value (CLV) through the mediation–moderation effect of search engine optimization (SEO) metrics of websites. We obtained a data sample of 296 European sustainable firms from both industrial and technological industries. Based on the theory of source credibility, the firm’s official website, where SEO techniques are applied, is more credible regarding its sustainability activities than other sources such as social media, paid advertising, etc. As a result, we show that sustainability is a precursor of financial performance over time in sustainable firms, represented by CLV. Furthermore, we found that the value of the moderating variable, website traffic, alters the indirect effects produced by the mediating variable called website relevance (domain authority), thereby demonstrating a moderated mediation effect. The contribution of this research to the body of literature is twofold. First, it deepens the understanding of how sustainability predicts marketing outcomes based on both digital and customer metrics over time. Second, we rely on recent literature on prediction-oriented modelling (PLS-SEM) to support that it is not suitable for estimation by reflective measurement models due to the woozle effect. Full article

When a flying wing comes within close proximity to the ground, a phenomenon called ground effect occurs where the lift is increased and the induced drag is decreased. This research seeks to determine the optimal dihedral distribution predicted by lifting-line theory that minimizes induced drag in ground effect. Despite some limitations, using lifting-line theory for this study allows for quick results across a large range of design variables, which would be infeasible for high-fidelity methods. The SLSQP optimization method is used along with a numerical lifting-line code to find the dihedral distribution that minimizes induced drag. Results are presented showing how the wing height, taper ratio, lift coefficient, and aspect ratio impact the induced drag and optimal dihedral distributions. For a given geometry, lifting-line theory predicts that there is a certain height above ground where the optimal solutions for a wing below this height result in bell-shaped wings with large section dihedral angles corresponding to a significant induced-drag reduction. For example, a wing with $R_A=8$ and height of $h/b=0.25$ can benefit from a reduction in induced drag of nearly 50% by employing an optimal dihedral distribution compared to a wing with no dihedral distribution. Full article

As new technologies shape education, helping students develop historical consciousness remains a challenge. Building on Nordic curricula that emphasize students as both “history-made” and “history-making” citizens, this paper proposes an approach that integrates artificial intelligence (AI) with implicit digital game-based learning (DGBL) to learn and develop historical consciousness in education. We outline how traditional, lecture-driven history teaching often fails to convey the abstract principles of historicity (the idea that individual identity, social institutions, values, and ways of thinking are historically conditioned) and the interpretation of the past, understanding of the present, and perspective on the future. Building on Jeismann’s definition of historical consciousness, we identify a gap between the theory-rich notions of historical consciousness and classroom practice, where many educators either do not recognize it or interpret it intuitively from the curriculum’s limited wording, leaving the concept generally absent from the classroom. We then examine three theory-based methods of enriching teaching and learning. Game-based learning provides an interactive environment in which students assume roles, make decisions, and observe consequences, experiencing historical consciousness instead of only reading about it. AI contributes personalized, adaptive content: branching narratives evolve based on individual choices, non-player characters respond dynamically, and analytics guide scaffolding. Implicit learning theory suggests that embedding core principles directly into gameplay allows students to internalize complex ideas without interrupting immersion; they learn by doing, not by explicit instruction. Finally, we propose a model in which these elements combine: (1) game mechanics and narrative embed principles of historical consciousness; (2) AI dynamically adjusts challenges, generates novel scenarios, and delivers feedback; (3) key concepts are embedded into the game narrative so that students absorb them implicitly; and (4) follow-up reflection activities transform tacit understanding into explicit knowledge. We conclude by outlining a research agenda that includes prototyping interactive environments, conducting longitudinal studies to assess students’ learning outcomes, and exploring transferability to other abstract concepts. By situating students within scenarios that explore historicity and temporal interplay, this approach seeks to transform history education into an immersive, reflective practice where students see themselves as history-made and history-making and view the world through a historical lens. Full article

This study examines the transformation of communities within Christian churches in late-modern and postmodern social contexts. As a theoretical foundation, it presents changes in the concept of community, with a particular focus on the role of religious communities. Emphasis is placed on community as a social and spiritual resource and on the possibilities for reorganising churches. Three national case studies—an urban Reformed congregation, a small-town Catholic parish, and an ecumenical pilgrimage community—will be used to illustrate the functioning, challenges, and responses of church communities. This research uses both qualitative and quantitative methods, and the results highlight the power of community retention, the importance of personal relationships, and spiritual depth. This study also highlights the theory that the key to church renewal lies in rethinking and consciously building community forms. Digital space, personal networks, and spiritual needs are calling for new models for the church. Full article

The challenges of climate change require in-depth attention and targeted strategies for specific sectors, such as energy and mining. Within the mining sector, climate change imposes constraints on the sustainable extraction of minerals, thereby heightening the importance of several minerals in addressing these challenges. Chile emerges as a pivotal nation due to its substantial reserves of copper, lithium, cobalt, nickel, and graphite, which are essential for energy transition and decarbonization processes. Consequently, Chile must foster gradual processes to establish competitive advantages based on technological and innovative capabilities, thus projecting a competitive and sustainable mining industry. This endeavor should be accompanied by enhancements in policies and instruments to guide development, expanding local value creation. This study examines the global challenges faced by the mining sector in the context of the energy transition and evaluates Chile’s response through an assessment of public policies for mining development. It provides an analysis of the scope of various public policy instruments to establish the link between international agreements and development opportunities, subsequently proposing a series of indicators to assess policy progress. To this end, the Environmental Observatory of Mining Projects is developing indicators to evaluate compliance with these policies. In addressing the nation’s challenges related to green and sustainable mining, 20 indicators have been developed in collaboration with civil society and public and private stakeholders through a design thinking process. These indicators enable the evaluation of aspects such as air quality, water quality, and the surface area affected by tailings, among others. The initial section of the document outlines the global challenges in achieving the carbon neutrality goals set by the IPCC. The subsequent section elaborates on the theoretical framework of the research, addressing theories of economic development and sustainability, public policy approaches considered in recent years, as well as the governance of mining development, with an emphasis on its capacity to articulate industrial policies, promote environmental sustainability, and foster technological innovation. The third section details the research methodology and framework of the study. This study examines how Chile’s mining policies align with the global energy transition. Amid growing demand for critical minerals, climate change, and decarbonization, Chile faces both opportunities and socio-environmental risks. Addressing these challenges requires integrated sustainability strategies and an active state role to ensure inclusive, environmentally responsible, and innovation-driven mining development. Full article

This paper explores the complexities of measuring impact from placemaking in the context of public and community housing (sometimes known as social or subsidised housing) in Aotearoa New Zealand. Placemaking refers to a range of practices and interventions—including the provision or facilitation of access to community infrastructure—that seek to cultivate a positive sense of place through everyday experiences, spaces, relationships, and rituals. Drawing on interviews with four community housing providers (CHPs), analysis of their documentation, and tenant survey and interview data from two of those CHPs, this research examines providers’ change theories about placemaking in relation to tenants’ experiences of safety, belonging and connectedness, including access to local amenities, ease of getting around, and a sense of neighbourhood and community affiliation. Based on the importance of these variables to wellbeing outcomes, the study highlights the potential of placemaking to support tenant wellbeing, while also recognising that providers must navigate trade-offs and co-benefits, limited resources, and varying levels of tenant engagement. While placemaking can help to foster feelings of connection, belonging and safety, its impact depends on providers’ capacity to initiate and sustain such efforts amidst competing demands and constraints. The study offers indicative findings and recommendations for future research. Although the impacts of placemaking and community infrastructure provision are difficult to quantify, research findings are synthesised into a prototype framework to support housing providers in their decision-making and housing development processes. The framework, which should be adapted and evaluated in situ, potentially also informs other actors in the built environment—including architects, landscape architects, urban designers, planners, developers and government agencies. In Aotearoa New Zealand, where housing provision occurs within a colonial context, government agencies have obligations under Te Tiriti o Waitangi to actively protect Māori rights and to work in partnership with Māori in housing policy and delivery. This underscores the importance of placemaking practices and interventions that are culturally and contextually responsive. Full article

Secure care is used for the most vulnerable and high-risk children in society; however, there is insufficient research examining the way intervention methods are used in this context. This study uses a qualitative approach to examine the use of intervention methods with children in secure care. Data is obtained from 21 meetings with 81 professionals who are involved with children in secure care. The findings suggest that considerable variation exists in the way intervention methods are discussed by professionals. Of the 21 meetings, each regarding a different child, professionals discuss at least one method of intervention with 13 of the children. However, there is often a level of vagueness surrounding what is happening to a child as well as an absence of intervention methods for some children. This problem reflects a disconnect between assessment and intervention methods. We believe that applying ideas from Foucauldian discourse theory to secure care settings shows that the (over-)assessment of some children cannot be understood solely as a supportive element of practice, but instead it operates as a discursive and disciplinary mechanism that reinforces institutional controls and norms while marginalising intervention methods and concealing neglect. Full article

Subject to magnetic saturation, temperature rise, and other factors, the electrical parameters of permanent magnet synchronous motors (PMSMs) in marine electric propulsion systems exhibit time-varying characteristics. Existing parameter identification algorithms fail to fully satisfy the requirements of high-performance PMSM control systems in terms of accuracy, response speed, and robustness. To address these limitations, this paper introduces multi-innovation theory and proposes a novel multi-innovation extended Kalman filter (MIEKF) for the identification of key electrical parameters of PMSMs, including stator resistance, d-axis inductance, q-axis inductance, and permanent magnet flux linkage. Firstly, the extended Kalman filter (EKF) algorithm is applied to linearize the nonlinear system, enhancing the EKF’s applicability for parameter identification in highly nonlinear PMSM systems. Subsequently, multi-innovation theory is incorporated into the EKF framework to construct the MIEKF algorithm, which utilizes historical state data through iterative updates to improve the identification accuracy and dynamic response speed. An MIEKF-based PMSM parameter identification model is then established to achieve online multi-parameter identification. Finally, a StarSim RCP MT1050-based experimental platform for online PMSM parameter identification is implemented to validate the effectiveness and superiority of the proposed MIEKF algorithm under three operational conditions: no-load, speed variation, and load variation. Experimental results demonstrate that (1) across three distinct operating conditions, compared to forget factor recursive least squares (FFRLS) and the EKF, the MIEKF exhibits smaller fluctuation amplitudes, shorter fluctuation durations, mean values closest to calibrated references, and minimal deviation rates and root mean square errors in identification results; (2) under the load increase condition, the EKF shows significantly increased deviation rates while the MIEKF maintains high identification accuracy and demonstrates enhanced anti-interference ability. This research has achieved a comprehensive improvement in parameter identification accuracy, dynamic response speed, convergence effect, and anti-interference performance, providing an electrical parameter identification method characterized by high accuracy, rapid dynamic response, and strong robustness for high-performance control of PMSMs in marine electric propulsion systems. Full article

Resource bricolage, centered on breaking through resource constraints, emphasizes providing innovation momentum for new ventures by creatively reorganizing existing resources at hand. Existing studies have confirmed that resource bricolage exerts an impact on corporate innovation, yet explorations into this approach’s mechanism of action remain insufficient. Based on resource bricolage theory and organizational ambidexterity theory, this study constructs a theoretical framework of “resource bricolage–ambidextrous learning–micro-innovation”. Using 319 new ventures as samples, hierarchical regression analysis is adopted to empirically test the mediating effect of ambidextrous learning and the moderating effects of government support and customer participation. The results show that resource bricolage has a significant positive impact on micro-innovation, with ambidextrous learning playing a partial mediating role. The research conclusions indicate that under resource-constrained contexts, new ventures can activate idle resources and improve resource efficiency through resource bricolage, thereby reducing reliance on new resource inputs. Under this method, new ventures can also rely on ambidextrous learning to accumulate knowledge and capabilities, laying the foundation for the continuous improvement of micro-innovation and further leverage government support to stabilize resource supply and absorb customer participation to align with market demand. This mechanism ultimately enables the achievement of micro-innovation while enhancing its sustainability. This study enriches resource bricolage theory by unpacking the “resource–learning–innovation” mechanism and provides practical guidance for new ventures to leverage resource bricolage and external support for micro-innovation under resource constraints, which is of reference value for sustainable entrepreneurial practices. Full article

This study examines the evolution of willingness to accept the monkeypox (Mpox) vaccine in Romania between 2022 and 2025. It explores key sociodemographic and behavioral predictors of vaccine acceptance and investigates how public perceptions—particularly concerning disease severity and conspiracy beliefs—have shifted across two independent cross-sectional samples. Two nationally distributed surveys were conducted in July 2022 (n = 820) and January–February 2025 (n = 1029), targeting Romanian residents aged 18 and above. Data were analyzed using descriptive statistics, Chi-square tests, Kolmogorov–Smirnov tests, and a Random Forest classification model to assess the relative importance of predictors of vaccine acceptance. Between 2022 and 2025, vaccine acceptance increased modestly, particularly among individuals aged 36–65 and those with prior experience of voluntary or COVID-19 vaccination. Random Forest analysis identified behavioral factors as the strongest predictors of acceptance in both years, while the influence of education and gender varied over time. Belief in conspiracy theories slightly declined and lost predictive relevance by 2025. Perceptions of pandemic potential and fear of infection also decreased, suggesting reduced risk salience and possible pandemic fatigue. Despite a slight upward trend, overall Mpox vaccine acceptance in Romania remains among the lowest in Europe. These findings highlight the need for targeted public health communication, particularly toward skeptical or demographically vulnerable groups. Prior vaccination behavior emerged as a key driver of acceptance, indicating that trust-building strategies should capitalize on existing pro-vaccination habits. Future research should adopt qualitative and longitudinal approaches to better capture the evolving psychosocial dynamics of vaccine hesitancy. Full article

This paper proposes a new accelerated fixed-point algorithm based on a double-inertial extrapolation technique for solving structured variational inclusion and convex bilevel optimization problems. The underlying framework leverages fixed-point theory and operator splitting methods to address inclusion problems of the form $0\in (A+B)\left(x\right)$, where A is a cocoercive operator and B is a maximally monotone operator defined on a real Hilbert space. The algorithm incorporates two inertial terms and a relaxation step via a contractive mapping, resulting in improved convergence properties and numerical stability. Under mild conditions of step sizes and inertial parameters, we establish strong convergence of the proposed algorithm to a point in the solution set that satisfies a variational inequality with respect to a contractive mapping. Beyond theoretical development, we demonstrate the practical effectiveness of the proposed algorithm by applying it to data classification tasks using Deep Extreme Learning Machines (DELMs). In particular, the training processes of Two-Hidden-Layer ELM (TELM) models is reformulated as convex regularized optimization problems, enabling robust learning without requiring direct matrix inversions. Experimental results on benchmark and real-world medical datasets, including breast cancer and hypertension prediction, confirm the superior performance of our approach in terms of evaluation metrics and convergence. This work unifies and extends existing inertial-type forward–backward schemes, offering a versatile and theoretically grounded optimization tool for both fundamental research and practical applications in machine learning and data science. Full article

Core mathematics courses are fundamental to the academic success of engineering students in higher education. These courses equip students with skills and knowledge applicable to their specialized fields. However, first-year engineering students often face significant challenges in mathematics due to a range of factors, including insufficient preparation, mathematics anxiety, and difficulty connecting theoretical concepts to real-life applications. The transition from secondary to tertiary mathematics remains a key area of educational research, with ongoing discussions about effective pedagogical approaches for teaching engineering mathematics. This study utilized a belief survey to gain general insights into the attitudes of first-year mathematics students towards the subject. In addition, it employed the activity theory framework to conduct a deeper exploration of the experiences of first-year engineering students, aiming to identify contradictions, or “tensions,” encountered within a flipped-classroom learning environment. Quantitative data were collected using surveys that assessed students’ self-reported confidence, competence, and knowledge development. Results from Friedman’s and Wilcoxon’s Signed-Rank Tests, conducted with a sample of 20 participants in 10 flipped-classroom sessions, statistically showed significant improvements in all three areas. All of Friedman’s test statistics were above 50, with p-values below 0.05, indicating meaningful progress. Similarly, Wilcoxon’s Signed-Rank Test results supported these findings, with p values under 0.05, leading to the rejection of the null hypothesis. The qualitative data, derived from student questionnaire comments and one-to-one interviews, elucidated critical aspects of flipped-classroom delivery. The analysis revealed emerging contradictions (“tensions”) that trigger “expansive learning”. These tensions encompassed the following: student expectation–curriculum structure; traditional versus novel delivery systems; self-regulation and accountability; group learning pace versus interactive learning; and the interplay between motivation and anxiety. These tensions are vital for academic staff and stakeholders to consider when designing and delivering a first-year mathematics course. Understanding these dynamics can lead to more effective, responsive teaching practices and support student success during this crucial transition phase. Full article

Despite high expectations for Fintech growth, its real-world expansion has fallen short due to its inherent complexity. Although Fintech is innovative, its multidimensional nature has made it difficult for companies to develop effective, tailored solutions for its diverse user groups. To foster the development of effective and practical Fintech solutions that can expand the user base, a novel and integrative approach is required. Therefore, this study aims to explore specific solutions to enhance Fintech use by holistically combining and intertwining various attributes. Based on the diffusion of innovation theory and the information systems success model, we propose a conceptual Fintech model consisting of three dimensions: innovation, financial service, and information technology. To investigate this model, we adopt fuzzy-set qualitative comparative analysis (fsQCA), a set-theoretic method suited to identifying combinations of Fintech attributes that lead to specific outcomes. The results reveal that the configurations of Fintech attributes leading to high Fintech use differ across four user groups: Infrequent users, Lurkers, Task-driven users, and Power users. The findings also show that information technology plays multifaceted roles depending on its combination with other Fintech attributes. This study explains the interdependencies among Fintech attributes and their combined effects on Fintech use, offering deeper insights into Fintech research through a configurational lens. Full article