Search Results (337)

Foreign direct investment (FDI) has often been cast as a straightforward engine of growth, yet its record across Central and Eastern Europe tells a more tangled story where outcomes hinge on the interplay of education, governance, and the timing of external shocks. This study embeds fixed effects panel econometrics within a systems framework, treating FDI as a subsystem of socio-economic dynamics. Using a long-run panel of eleven economies from 2000 to 2023, the analysis models path dependence and regime shifts through interaction terms and period-specific dummies set against a systems-thinking backdrop. The analysis shows that for the average CEE economy, FDI’s contribution has waxed and waned: it dragged on growth during the early transition years (2000–2007), settled into a neutral role after the global financial crisis, and proved unpredictable in the pandemic era. Romania stands out, however, with a marked “FDI premium” quantified as approximately 0.7 pp of growth per pp of FDI that seems to stem from reinforcing loops between rising tertiary enrolment and productivity spillovers. Mapping these feedbacks brings to light virtuous circles where human capital and resilience make or break the benefits of foreign capital. The policy message is plain: nurture the positive loops through investment in skills and firm linkages, keep institutions nimble enough to adapt, and watch for early warning signs of systemic strain. Full article

The application of Generative Artificial Intelligence (GenAI)—defined as a class of AI systems capable of autonomously generating new content such as images, texts, and design solutions based on learned data patterns—has become increasingly widespread in creative design. By supporting ideation, rapid trial-and-error, and data-driven decision-making, GenAI enables designers to explore design alternatives more efficiently and enhances human–computer interaction experiences. In design practice, GenAI functions not only as a productivity-enhancing tool but also as a collaborative partner that assists users in visual exploration, concept refinement, and iterative development. However, users still face a certain learning curve before effectively adopting these technologies. Within the framework of human-centered artificial intelligence, contemporary design practices place greater emphasis on inclusivity across diverse user groups and on enabling intuitive “what-you-think-is-what-you-get” interaction experiences. From a sustainable design perspective, GenAI’s capabilities in digital simulation, rapid iteration, and automated feedback contribute to more efficient design workflows, reduced collaboration costs, and broader access to creative participation for users with varying levels of expertise. These characteristics play a crucial role in enhancing the accessibility of design resources and supporting the long-term sustainability of creative processes. Focusing on the context of China’s digital design industry, this study investigates the application of GenAI in design workflows through an empirical case study of Zhitu AI, a generative design tool developed by Beijing Didi Infinity Technology Development Co., Ltd. The study conducts a literature review to outline the role of GenAI in visual design processes and employs observation-based experiments and semi-structured interviews with users of varying levels of design expertise. The findings reveal key pain points across stages such as prompt formulation, secondary editing, and asset generation. Drawing on the Kano model, the study further identifies potential design opportunities and discusses their value in improving efficiency, supporting non-expert users, and promoting more sustainable and inclusive design practices. Full article

This study introduces an Impact Thinking Approach (ITA) as a strategic framework to strengthen traceability implementation in the fashion and textile industry. The research examines how ESG impact dimensions shape sustainable strategy definition and how traceability can act as a strategic enabler rather than a mere compliance tool. A mixed-method design combining a narrative literature review, content analysis of 69 sustainability sources, and a two-round Delphi study with 19 experts was employed to identify, evaluate, and prioritize impact drivers related to traceability adoption. The resulting ITA framework connects regulatory requirements, impact materiality, and traceability demands into a unified structure that clarifies the strategic relevance of environmental, social, and governance dimensions. Findings reveal that governance-related factors—particularly data transparency, stakeholder engagement, innovation capacity, and cross-sector partnerships—are the strongest enablers for activating effective traceability schemes. The framework provides practitioners with structured guidance for integrating traceability into sustainable business strategies and for developing impact-aligned KPIs and decision-making mechanisms. The study contributes theoretical insights into the ESG–traceability nexus and offers a practical model to support regulatory alignment, organizational readiness, and long-term strategic planning. Full article

This study reviews the current applications of generative artificial intelligence (GenAI) in architectural design education using the PRISMA framework. It compares these applications across the different design stages, namely the pre-design, concept generation, design development, and design production, to identify the current state of evidence and conceptual discussions reported in the literature. The study also discusses the associated opportunities and challenges in this regard. The findings indicate that there is a growing interest in integrating GenAI into architectural design education, especially in the early design stages. However, one of the most significant gaps in this regard lies in the lack of empirical evidence on the long-term impacts of GenAI on students’ critical thinking and problem-solving skills. Future research is needed to explore the integration of GenAI throughout the entire design process, including design development and refinement. There is also a need to incorporate the relevant ethical guidelines for AI-generated content into academic quality assurance systems and to strengthen institutional preparedness through targeted training and policy development. Full article

The COVID-19 pandemic highlighted critical issues in health services and public policy, particularly in long-term care facilities across Canada. Failures in these facilities revolving around chronic underfunding, staffing shortages, inadequate infection control, and inconsistent regulatory oversight, underscore the need to rethink health service interventions, especially considering varying implementation contexts among provinces. The Ontario Long-Term Care COVID-19 Commission Final Report pointed to long-standing systemic issues as the primary causes of the sector’s failures. To explore this issue, a narrative review was conducted with findings indicating that the long-term care crisis in Canada cannot be solved by more privatization, regulation or efficiency measures, as these have contributed to the problem’s root causes. Ontario’s long-term care crisis stems from systemic misalignments in policy, structure and stakeholder dynamics, requiring a shift toward systems thinking and resident-centered care to build an equitable and sustainable long-term care sector. Ultimately, governments must lead a policy redesign that reflects shared responsibility, stakeholder interdependence, and public involvement, offering a model for broader healthcare reform. Full article

This review examines the implementation of computer science (CS) unplugged activities in K–12 education, focusing on their impact on educational outcomes, student motivation, and teacher perceptions. A total of 32 relevant studies published between 2009 and 2025 were analysed, including journal articles, conference reports, and book chapters. The findings suggest that CS unplugged generally improves computational thinking (CT) skills, particularly among younger learners and those who have not yet experienced programming concepts. Students often report greater engagement and less anxiety about coding, while teachers appreciate the cost-effective and flexible nature of unplugged lessons. However, inconsistencies are evident in the long-term retention of concepts and the degree of transfer to more advanced or “plug-in” programming tasks. The effective integration of CS unplugged activities often depends on sound teacher training and alignment with broader curriculum objectives. These findings highlight the potential of CS unplugged to improve early computer education, but also highlight the need for longitudinal studies, standardised assessments and systematic transitions from unplugged to digital practice. Given the substantial heterogeneity of study designs and outcomes—and, critically, the inconsistent operationalisation of CT alongside non-standardised testing metrics across studies—we did not aggregate effect sizes; consequently, a formal meta-analysis was not methodologically feasible. Full article

Urban resilience has emerged as a crucial objective for achieving sustainable urban development. However, its practical integration into planning remains limited. This study evaluates the extent to which resilience thinking is integrated into Chengdu’s urban planning system by combining policy-theoretical analysis with empirical evidence. Drawing on a framework of nine resilience attributes, we conduct content analysis of Chengdu’s three types of statutory plan documents (Socioeconomic Development Plan, Urban and Rural Plan, and Land Use Plan) and a questionnaire survey of 70 expert planners. The results reveal that resilience is reflected implicitly in the plans through engineering-oriented attributes such as robustness, efficiency, and connectivity. In contrast, social and ecological attributes like inclusion, redundancy, and innovation are largely absent. Planners demonstrate moderate awareness of resilience, yet associate it predominantly with rapid response and infrastructure robustness rather than long-term adaptation or community capacity-building. These findings indicate the dominant top-down, growth-centric planning logic that constrains the adoption of broader socio-ecological resilience concepts. This paper concludes with policy recommendations for institutionalizing resilience in Chinese urban planning through legal mandates; multi-sectoral coordination; and participatory, adaptive planning frameworks. Full article

Thought processes in the brain occur as it continually modifies its use of energy. This review integrates research findings from molecular neurology, vascular physiology and non-equilibrium thermodynamics to create a comprehensive perspective on thinking as a coordinated energy process. Data shows that there is a relationship between the processing of information and metabolism throughout all scales, from the mitochondria’s electron transport chain to the rhythmic changes in the microvasculature. Through the cellular level of organization, mitochondrial networks, calcium (Ca²⁺) signals from astrocytes and the adaptive control of capillaries work together to maintain a state of balance between order and dissipation that maintains function while also maintaining the ability to be flexible. The longer-term regulatory mechanisms including redox plasticity, epigenetic programs and organelle remodeling may convert short-lived states of metabolism into long-lasting physiological “memory”. As well, data indicates that the cortical networks of the brain appear to be operating close to their critical regimes, which will allow them to respond to stimuli but prevent the brain from reaching an unstable energetic state. It is suggested that cognition occurs as the result of the brain’s ability to coordinate energy supply with neural activity over both time and space. Providing a perspective of the functional aspects of neurons as a continuous thermodynamic process creates a framework for making predictive statements that will guide future studies to measure coherence as a key link between energy flow, perception, memory and cognition. Full article

Background/Objectives. Self-harm is a heterogeneous behaviour with a lifetime prevalence of around 20% in young people aged 16–25 years old. Recent neurocognitive evidence suggests that, for some individuals, self-harm is associated with motivational processes similar to addiction, including maladaptive mental imagery, reward anticipation, and goal pursuit. However, our knowledge of young people’s subjective experiences of rewards and goals in relation to self-harm behaviour remains limited. Our study aimed to investigate how young people who self-harm experience enjoying and wanting rewards and pursuing goals in daily life and whether this experience changes during periods of self-harm. We also explored their use of mental imagery as a key cognitive process to support motivation. Methods. We conducted two parallel focus groups online (total of N = 12) with young people (mean age = 12.2, SD = 3; nine women, two men, and one non-binary) with a past-year history of self-harm behaviour. Qualitative data was analysed using inductive thematic analysis. Two young people with lived experience of self-harm informed the topic guide and data interpretation. Examples of questions were “Do you think your experiences of enjoying and/or looking forward to pleasant things are related in any way to self-harm, or not?” and “Do you visualise things you enjoy or may look forward to? If you do, how is that experience?”. Results. There were six themes: rewards need deserving, high self-standards, keeping control, trapped into long-term goals, unhelpful mental imagery, and self-harm alters the experience and anticipation of rewards and goal attainment. Most young people reported enjoying conditional rewards and working towards long-term goals that tend to be unattainable and beyond their control. Imagining these goals was experienced as unhelpful by most. For all young people, periods of self-harm thwarted enjoyment and goal achievement, shifted the preference to short-term immediate gratification, including from self-harm behaviour, and devalued long-term goals. However, our data cannot determine if these experiences are specific to young people who self-harm. Conclusions. Our findings indicate that the reciprocal relationship between motivational processes and self-harm behaviour in young people warrants further investigation. Helping individuals develop more adaptive rewards and goals, including appreciation of short-term goals and use of motivational mental imagery, could represent valued support for young people with self-harm. Full article

Despite growing attention to corporate environmental responsibility, there is limited understanding of the psychological and social mechanisms linking corporate environmental responsibility to employees’ coworker-focused pro-environmental behaviors in the workplace, such as advocacy directed at peers. This study examined the influence of corporate environmental responsibility on employees’ coworker pro-environmental advocacy in the Chinese energy sector, with a sample of 1528 employees. Focusing on the mediating roles of long-term orientation, meaningful work, and sense of community, the research integrates insights from Social Exchange Theory, Self-determination Theory, and Affective Events Theory. The data were analyzed using structural equation modeling (SEM) to test the hypothesized relationships. The findings revealed that corporate environmental responsibility positively impacted employees’ advocacy for eco-friendly behaviors among coworkers through forward-thinking attitudes, intrinsic motivation, and strengthened social bonds. The study offers theoretical contributions by unpacking the interplay of individual and organizational factors and provides practical recommendations for cultivating an environmentally conscious culture through value alignment, meaningful work initiatives, and fostering a strong sense of community. Full article

The widespread application of Generative Artificial Intelligence (Gen-AI) is transforming educational practices and driving pedagogical innovation. While cultivating higher-order thinking (HOT) represents a central educational goal, its achievement remains an ongoing challenge. Current evidence regarding the impact of Gen-AI on HOT is relatively fragmented, lacking systematic integration, particularly in the analysis of moderating variables. To address this gap, a meta-analysis approach was employed, integrating data from 29 experimental and quasi-experimental studies to quantitatively assess the overall impact of Gen-AI on learners’ HOT and to examine potential moderating factors. The analysis revealed that Gen-AI exerts a moderate positive effect on HOT, with the most significant improvement observed in problem-solving abilities, followed by critical thinking, while its effect on creativity is relatively limited. Moderation analyses further indicated that the impact of Gen-AI is significantly influenced by experimental duration and learners’ self-regulated learning (SRL) abilities: effects were strongest when interventions lasted 8–16 weeks, and learners with higher SRL capacities benefited more substantially. Based on the research findings, this study proposed that Gen-AI should be systematically integrated as a targeted instructional tool to foster HOT. Medium- to long-term interventions (8–16 weeks) are recommended to enhance learners’ problem-solving and critical thinking abilities. At the same time, effective approaches should also be explored to promote creative thinking through Gen-AI within existing pedagogical frameworks. Furthermore, individual learner differences should be accounted for by adopting dynamic and personalized scaffolding strategies to foster SRL, thereby maximizing the educational potential of Gen-AI in cultivating innovative talents. Full article

Artificial Intelligence (AI) and Virtual Reality (VR) are increasingly integrated into education, yet their combined psychological effects remain underexplored. This paper investigates the potential benefits and risks of AI-powered learning assistants within immersive VR environments. The study builds on insights from a previous pilot involving a virtual tour guide for Athens and proposes a case study with 52 high school students. In groups of three, students would use Oculus headsets with an AI assistant (pre-programmed and AI-generated modes), explore content for a week, and complete questionnaires on usability, trust, and psychological impact. The analysis is expected to support a balance of positive outcomes including greater engagement, motivation and autonomy but also negative ones such as over-reliance, diminished critical thinking, and social isolation. The paper also identifies key psychological dynamics, including the critical role of social influence and teacher-led adoption, and the nuanced nature of student trust in AI-generated information. Ethical implications, such as data privacy and the digital divide, are also discussed. The study concludes by proposing that AI-VR can enrich learning, especially in cultural contexts, but requires safeguards for trust, ethics, and accessibility, with further research on long-term effects, psychological impact and cross-cultural and linguistic nuances. Full article

This study proposes a novel structure-preserving algorithm for the Ginzburg–Landau equation (GLE) by combining the Fourier pseudospectral method with the Exponential Average Vector Field (EAVF) scheme. The proposed numerical framework strictly preserves the energy dissipation property of GLE systems, as validated through theoretical analysis and numerical experiments on solitary wave dynamics. Compared to conventional methods such as the average vector field approach, the EAVF-based scheme demonstrates superior computational efficiency, including faster convergence and enhanced stability under larger time steps, enabling accurate long-term simulation of strongly nonlinear GLE systems. Furthermore, this research incorporates a pedagogical innovation through its implementation within an undergraduate innovation project. By adopting a “problem decomposition–code verification–modular development” training model, students engage in the full cycle of algorithm design, implementation, and validation. This practice-oriented approach significantly enhances students’ competencies in scientific programming, complex problem-solving, and research-oriented thinking, providing an effective paradigm for synergizing advanced computational research with talent cultivation in STEM education. Full article

As environmental sustainability pressures intensify and AI technologies rapidly evolve, the integration of AI into green marketing strategies has become increasingly prominent. This systematic review examines the application of artificial intelligence (AI) in green marketing, with a focus on studies published between 2020 and 2024. This review addresses two key research questions: the effectiveness of different types of artificial intelligence in green marketing applications, and the role of AI in supporting enterprise development in this context. A comprehensive search of SpringerLink, Web of Science, and Google Scholar initially identified 200 records. After duplicate removal and multi-stage screening, 47 articles were deemed to meet the inclusion criteria. Only peer-reviewed journal articles in English were included. Study quality was appraised using established evaluation criteria to ensure methodological rigor. Among these, Thinking AI, Mechanical AI and Feeling AI appeared in 45 studies, 23 studies and 15 studies, respectively. The selected studies span 34 journals and 28 countries, reflecting both the rising academic interest and the interdisciplinary character of this emerging field. However, this review also identifies notable deficiencies in the current body of work. This review integrates these AI types with the 4Ps framework to form a concise conceptual mapping of their respective functions. Although AI has been positioned as a powerful driver of green marketing, research remains fragmented, with limited assessment of AI’s sustainability, weak data and ethical safeguards, and insufficient long-term and global perspectives. This underscores the need for a deeper and more systematic understanding of AI to better achieve the goals of green marketing and improve its practices. Full article

This article explores the crucial role of media education and media literacy as effective tools in combating disinformation. In the context of the growing influence of digital media and the increasing spread of fake news, propaganda, and manipulative content, the authors examine the level of awareness among young people regarding key media-related concepts such as media literacy, fake news, propaganda, and disinformation. A sociological survey was conducted among students from two Ukrainian higher education institutions—Ivan Franko National University of Lviv and Lviv Polytechnic National University—involving 277 respondents. The research aimed to evaluate the depth of understanding and preparedness of youth to critically assess media content and recognize signs of manipulative information. The findings indicate a clear trend: media awareness and critical thinking skills improve progressively from secondary school students to university students. This article emphasizes the importance of integrating media literacy into formal education systems as a long-term strategy to build a more informed and resilient society. The authors highlight the need for systematic educational initiatives and practical training in media literacy to empower young audiences in navigating the complex media environment and resisting the impact of disinformation. Full article