Search Results (2,864)

This study proposes an integrated model examining the relationship between teacher educators’ digital proficiency and the frequency of their pedagogical use of digital tools. By promoting long-term capacity-building in digital competence, the model contributes to sustainable development goals in education, particularly in ensuring inclusive, equitable, and high-quality learning environments. The study involved 156 faculty members from five teacher-training colleges in Israel. Digital proficiency was measured using a validated self-assessment questionnaire adapted from the SELFIE framework (Self-Reflection on Effective Learning by Fostering the Use of Innovative Educational Technologies). The questionnaire assessed perceived competence across three dimensions: (1) filtering and enhancing digital resources, (2) assessment, feedback, communication, and active learning, and (3) adaptive and creative learning. A second questionnaire examined how frequently educators used specific digital tools across four categories: collaboration, diversity and special needs, active and creative learning, and distance and hybrid learning. Data were analyzed using Item Response Theory (IRT) to generate proficiency scores and Structural Equation Modeling (SEM) to test associations. Results indicated moderate overall digital proficiency, with stronger competence in collaboration and communication and lower use of tools related to personalization and creativity. Significant positive associations were found between digital proficiency and all categories of tool use, especially creative and student-centered learning. Use also varied by gender, seniority, and professional role. The study underscores the importance of pedagogically informed professional development to support meaningful and inclusive digital integration. Full article

Building Information Modelling (BIM) has digitized construction, yet automated cost estimation still suffers from fragmented data and deterministic forecasts that ignore uncertainty. To address this gap, this study introduces a novel framework integrating agentic artificial intelligence (AI) with large language models (LLMs) to enable probabilistic cost estimation from disparate BIM data. The system employs four specialized collaborative agents operating via a shared memory module centered on an LLM with natural language understanding, code generation, and chain-of-thought reasoning. A prototype using GPT-4 Turbo, AutoGen, and Monte Carlo simulation was tested on three real-world structures. Compared to three baselines, the framework reduced processing time (4.2 vs. 18.5–68.0 min), manual interventions (0.8 vs. 9–14), and improved entity resolution accuracy (86.5% vs. 46–62%) with well-calibrated probabilistic forecasts, achieving 86.0% empirical coverage for nominal 90% prediction intervals (Prediction Interval Coverage Probability [PICP] = 86.0%, Prediction Interval Width [PIW] = 0.28; p < 0.01). Qualitative analysis confirmed effective semantic conflict resolution and actionable risk visualization via tornado diagrams. The framework tackles long-standing BIM estimation challenges by delivering probabilistic, transparent outputs. Future work includes digital twin integration, open-source LLM deployment, and during-construction forecasting. Full article

Enhancing urban carbon productivity (UCP) is crucial for achieving the dual carbon goals in China. This study investigates the spatiotemporal patterns and underlying drivers of UCP in the Yangtze River Economic Belt (YREB) from 2010 and 2020. Utilizing a comprehensive dataset of 110 cities, we employ kernel density estimation, spatial autocorrelation analysis, and the Spatial Durbin Model (SDM). The results reveal a significant overall improvement in UCP alongside intensified internal disparities and a fundamental spatial restructuring—from a monocentric eastern-led pattern to a multipolar network driven by the Yangtze River Delta, middle Yangtze, and Chengdu-Chongqing agglomerations. The SDM decomposition reveals a shift in core drivers towards green technological innovation and advanced industrial structure, while energy consumption remains the primary constraint. Crucially, complex spatial spillover effects are identified: factors like advanced industrial structure and digital governance are associated with positive synergistic spillovers, whereas government intervention (government public budget expenditure) and urban sprawl exhibit negative competitive spillovers, collectively corresponding to the polarized regional pattern. Furthermore, urban form shows strong spatial externalities: urban compactness is linked to a “local-neighborhood” double dividend, while urban sprawl is associated with a “local-neighborhood” double curse. The influence of digital factors appears to evolve from early widespread spillovers to later localized deepening. The findings suggest the necessity of implementing spatially differentiated policies, strengthening regional collaborative governance to manage spatial externalities, and promoting compact regional spatial planning to foster synergistic and equitable low-carbon transitions across the YREB. Full article

Promoting the coordinated development of digitalization and greening has become an important pathway for firms to achieve high-quality growth. Using panel data for A-share listed firms in China’s Yangtze River Basin from 2010 to 2022, this study examines the effect of supply chain innovation policy on firms’ digital–green development. We measure the synergy between digitalization and greening using a composite system synergy approach and identify the policy effect through a quasi-natural experiment based on the supply chain innovation policy, combined with a synthetic difference-in-differences model. The results show that the policy significantly improves the coordinated development of firm digitalization and greening, and the findings remain robust across a series of tests. Mechanism analysis indicates that this effect operates through three channels: easing financing constraints, increasing supply chain diversification, and promoting industrial chain modernization. Moderating effect tests further show that supply chain efficiency, supply chain resilience, and entrepreneurship strengthen the policy’s positive effect on digital–green development. Heterogeneity analysis suggests that the policy effect varies systematically with firm size, market competitiveness, and information asymmetry. This study provides micro-level evidence on how supply chain innovation policy can promote firms’ digital–green transformation and offers useful implications for policies aimed at improving firm competitiveness and supporting sustainable development. Full article

Against the backdrop of substantial transformations in the education system, including digitalization and increasing societal pluralization, there is growing attention paid to teachers’ digital competencies and their role within broader school well-being processes in digitally transforming educational environments. This paper adopts digital competencies as a novel domain-specific personal resource within the Job Demands-Resources (JD-R) framework to examine how both individual and organizational resources shape teachers’ professional motivation and organizational commitment. The analysis draws on data from the ‘Deisel’ project, comprising 550 teachers in Germany. Within this empirical context, this study reveals considerable variation in both teachers’ digital competencies and the organizational conditions of schools. In particular, differences in leadership support and collegial collaboration influence whether digital transformation is experienced as an additional burden or as a meaningful resource for professional development. The findings indicate a small but statistically significant indirect association between digital competencies and organizational commitment, operating primarily through reduced psychological strain rather than increased motivation. Prior evidence emphasizing the relevance of school management support and self-efficacy was replicated. These results demonstrate that digital competencies function as a personal resource within the JD-R framework, reducing perceived strain and indirectly strengthening organizational commitment. This study contributes to JD-R research by showing that digital competencies appear to function less as direct motivational drivers and more as domain-specific personal resources that may mitigate the strain associated with technology-related demands in digitally transforming schools. Full article

In an era where artificial intelligence is rapidly expanding into creative domains, the challenge of modeling human-like cognition and emotion in generative processes becomes increasingly central. The present study was made in connection with the exhibition of Munch’s works held in Rome from February to June 2025. Indeed, the paper introduces the concept of a Cognitive Digital Twin grounded in the Super Time-Cognitive Neural Network (STCNN) framework and applies it to the case of Edvard Munch, the iconic Norwegian expressionist. The proposed system—Munch Digital Twin—goes beyond static generative models by integrating temporal, emotional, and cognitive dimensions through a complex-valued time representation t = a + i·b, where a denotes chronological time and b encodes imagination, memory, and creativity. We define Edge Knowledge as an output-stage re-ranking criterion that admits a generated response only where corpus evidence, knowledge-graph constraints and the LLM surface jointly agree (the boundary, or ‘edge’, between documented identity and machine inference). STCNN allows this twin to process real inputs (text, visual prompts, emotional cues) and generate outputs that reflect both the rational and expressive styles of Munch. The imaginary components of the network enable speculative and affective expansions of known artworks—such as reinterpreting The Scream under new emotional or social contexts. This paper presents the theoretical underpinnings of cognitive digital twins, the architecture of the STCNN-based model, and a prototype implementation trained on Munch’s paintings, letters, and critical essays. The system—comprising a GPT-4-Turbo cloud profile and a 4-bit LLaMA-2-13B edge profile for language, Stable Diffusion 1.5 + LoRA for image generation, a Neo4j knowledge graph, and FAISS retrieval—is trained on approximately 600 letters, 100 artworks, and Munch’s diaries and criticism, and evaluated across 100 interactive sessions with 14 students and expert raters. Headline results against an unconditioned baseline include CLIPScore +13.8%, FID −25.5% (small-sample, indicative), and emotion-cosine similarity +44.9%. Ethical implications surrounding posthumous digital emulation, authorship, and emotional manipulation are also discussed. The Munch Digital Twin represents a new paradigm in AI-driven art, where machines do not merely replicate, but collaborate across time with human legacies, enabling an anticipatory and emotionally intelligent form of computational creativity. This work is primarily a conceptual and architectural contribution, supported by a proof-of-concept prototype and a preliminary, non-controlled user study; the quantitative results are indicative and not yet confirmatory. Full article

With the rapid development in generative artificial intelligence (GenAI) technologies, their application in STEAM education offers new possibilities for promoting interdisciplinary integration of technology and the arts. This study employs a systematic literature review method. Six databases—Google Scholar, Web of Science, PubMed, Taylor & Francis, Springer Link, and Scopus—were searched for publications from January 2021 to January 2026. After independent screening and review by two reviewers, 21 empirical studies out of 424 initial records were included. A comprehensive analysis was conducted using a combination of open and axial coding. The findings indicate that GenAI’s support for artistic creativity in STEAM education is primarily manifested in four dimensions: lowering the threshold for creation to enhance the accessibility of artistic creativity, stimulating interdisciplinary associations to strengthen subject integration, supporting critical artistic recreation to deepen cultural engagement, and building a human–GenAI collaborative creation ecosystem to foster reflexivity. Based on this, the study constructs a GCD (Guiding questioning–Co-refining–Deepening reflection) cyclic instructional framework, providing teachers with an actionable pedagogical pathway for using GenAI to cultivate students’ interdisciplinary artistic creativity across different educational stages. Furthermore, the study systematically analyzes ethical challenges such as technological dependency, cultural homogenization, educational equity, and originality, and proposes corresponding pedagogical strategies to address them. It should be noted that the current body of relevant empirical research is limited in quantity and exhibits substantial heterogeneity, and the GCD framework still requires further classroom-based practical validation. Future research could strengthen empirical longitudinal tracking of longterm effects, deepen the construction of support systems for teachers’ digital literacy, and continue to advance the exploration of ethical, equity, and cultural diversity issues in GenAI-based artistic creativity education. Full article

The transition towards sustainable, resilient and digitally integrated port ecosystems has increased the need for collaborative innovation approaches capable of supporting broader sustainability transitions. In this context, open and sustainable innovation (OSI) offers a strategic mechanism for integrating economic, environmental and social objectives within complex maritime ecosystems. Although previous studies have explored technological innovation and isolated sustainability initiatives in ports, limited empirical attention has been given to how stakeholders perceive OSI and how its implementation is operationalised across a national port system. This study addresses this gap by investigating the central research question: how do key stakeholders perceive and implement OSI practices within the Portuguese port system? Specifically, it analyses organisational culture, governance structures, stakeholder engagement mechanisms, institutional barriers and sustainability-oriented innovation practices. The research adopts a qualitative approach based on ten semi-structured interviews with representatives of five Portuguese port authorities occupying senior management and strategic positions. The findings show that OSI is widely recognised as important for competitiveness, sustainability performance and alignment with transition agendas, but its implementation remains uneven across ports. Organisational resistance, fragmented governance, regulatory complexity and limited monitoring mechanisms constrain the institutionalisation of OSI practices. Nevertheless, collaborative initiatives involving universities, innovation networks, public–private partnerships and digital platforms indicate a gradual shift towards more integrated and participatory governance models. The study concludes that OSI can support sustainability transitions in port ecosystems when enabled by coordinated governance, stakeholder collaboration and organisational capabilities. Full article

With the development of ecotourism, national park recreation research has evolved from a marginal branch of tourism studies into a vibrant interdisciplinary field. Although scholarly attention has grown, a systematic, holistic overview of its global development trajectory and knowledge structure remains lacking. To address this gap, this study presents a bibliometric analysis of national park recreation research published from 1994 to 2024, based on the Web of Science Core Collection. Using CiteSpace for scientometric visualization, we examine the field’s evolutionary phases, collaboration networks, thematic distributions, and emerging trends. Our results show that national park recreation research has progressed through three distinct stages: initial emergence, steady development, and rapid growth. Collaboration among individual researchers and institutions remains generally limited. Dominant research themes include spatial planning and zoning, ecological conservation, stakeholder engagement, cultural ecosystem services, and tourists’ pro-environmental behaviors. Building on these findings, we synthesize a comprehensive knowledge structure of this field and outline key future research priorities. This overview enables researchers to quickly grasp the field’s global research panorama and identify targeted thematic directions. We call for greater attention to understudied areas, including visitor social psychology, community participation, digital technology applications, and adaptive management in future studies. Full article

The rapid advancement of internet technology has transformed the tourism industry from traditional offline services to digital networked, and intelligent platforms. WebGIS has become critical infrastructure for tourism information retrieval and spatial decision-making. However, the growing volume and heterogeneity of multi-source tourism data expose fundamental limitations in conventional relational database architectures, particularly in handling complex spatial semantic queries. To address this, the present study proposes a WebGIS design methodology that integrates knowledge graphs with relational databases through a dual-database collaborative architecture. Using tourist attraction data from China’s Xinjiang Uyghur Autonomous Region as a case study, a prototype Xinjiang Smart Tourism WebGIS system was constructed, which consists of an asynchronous synchronization mechanism based on Change Data Capture (CDC) to ensure data consistency across heterogeneous databases. Subsequently, tourism semantic queries of varying depths were constructed and comprehensively tested across different data scales. The experimental results indicate that the proposed methodology effectively decouples business transactions and supports complex relationship computations, achieving shorter cross-domain semantic query times and higher latency stability. These findings offer practical guidance for designing high-performance regional tourism information services. Full article

Under carbon peaking and neutrality goals, building integrated with photovoltaics and energy storage system clusters (BIPECs) enable efficient on-site renewable energy use and can act as dispatch units for the public grid. However, BIPECs face significant uncertainties and are still under development. This study proposes a decentralized cooperative power dispatch model coupling a multi-agent proximal policy optimization (MAPPO) algorithm and offline digital twin (ODT) technology to optimize the photovoltaic (PV) power consumption of clusters despite limited data availability. An integrated BIPEC energy system model is established, and by leveraging the multi-agent system model of the BIPEC, the decentralized dispatch problem is converted into a fully cooperative multi-agent reinforcement learning (MARL) problem. A simulation-assisted ODT framework constructs a digital environment for MAPPO to augment data, conduct MAPPO training, and optimize the reward function, thereby obtaining power dispatch strategies. The results show that the proposed optimization model can obtain dispatch strategies that reflect a high degree of collaboration, reducing the cumulative power supply from the public grid by 0.55–2.56% per month compared to the non-cooperative self-generating and self-using strategy. This study presents the application of MARL in BIPECs by introducing a decentralized collaborative power dispatch methodology for building clusters, enhancing building energy efficiency and facilitating flexible collaborative power dispatch. Full article

The Engineering-Procurement-Construction (EPC) general contracting model has emerged as the dominant delivery method for large-scale infrastructure and industrial projects in China. However, contemporary EPC project cost control remains plagued by critical industry challenges, including fragmented cross-stage coordination, pervasive data silos, and the shallow integration of digital technologies into core management processes. This study considers three key stakeholders—government regulators, project owners, and EPC general contractors—and develops a tripartite evolutionary game model to analyze the strategic interactions underlying intelligent cost control in EPC projects. We examine the evolutionary stability of each stakeholder’s strategy selection, explore how various factors influence tripartite strategic choices, and further investigate the stability of equilibrium points in the game system. The key findings are summarized as follows: (1) Strengthening government incentives and penalties simultaneously promotes owners’ investment in intelligent cost control systems and general contractors’ active collaborative cost management. However, excessive incentive intensity undermines the government’s regulatory effectiveness. (2) Establishing a revenue-sharing mechanism for excess cost savings fully stimulates the spontaneous cooperation willingness of owners and general contractors, serving as the cornerstone for market-oriented operation of intelligent cost control. (3) Reducing owners’ intelligent construction investment costs and general contractors’ collaborative control costs effectively addresses practical implementation barriers and accelerates the digital upgrading of engineering cost management. Finally, numerical simulations are performed using MATLAB R2020b to validate theoretical findings. Full article

As hybrid work arrangements become more established in organisations, the need for effective design and implementation strategies has grown significantly. Evidence indicates that employee wellbeing and engagement in hybrid work environments are declining and this presents a critical challenge for human resource management (HRM) professionals. This presents HRM professionals with a critical imperative of improving wellbeing, while maintaining engagement and productivity at work. This aligns closely with the United Nations’ 17 Sustainable Development Goals, particularly those that promote wellbeing and decent work. Through a systematic synthesis of 78 studies, this research investigates the key determinants of employee engagement and wellbeing in hybrid work contexts. The conceptual framework for this study is grounded in existing theoretical perspectives from the Job Demands–Resources model, Saks Frameworks and wellbeing perspective presented by Guest. The analysis identifies five critical factors that influence engagement and wellbeing outcomes in hybrid work, accompanied by evidence-based propositions for practice. These recommendations encompass: establishing well-equipped workspaces with appropriate flexibility in both location and time; developing organisational culture and leadership through enhanced communication and collaboration mechanisms; strategically allocating jobs and tasks whilst fostering effective networks and collaboration tools and implementing targeted training interventions to mitigate technostress and burnout associated with digital workloads. We advocate for future research to develop comprehensive models, frameworks and wellbeing interventions to guide HRM professionals in addressing these challenges at both the local and global levels. Full article

The open sharing of data as a factor of production is an important institutional mechanism for promoting sustainable innovation in the digital economy. Using Chinese A-share listed firms as the research sample and exploiting the staggered rollout of government open data (GOD) platforms across prefecture-level cities as a quasi-natural experiment, this paper constructs a staggered difference-in-differences (DID) model to examine the effect of GOD on green collaborative innovation (GCI) and its underlying mechanisms. The results show that GOD significantly promotes GCI, indicating that open government data can help firms strengthen collaboration in green innovation and contribute to more sustainable development. Mechanism analysis shows that GOD promotes GCI through four channels: increasing government subsidies, reducing information asymmetry, raising public environmental awareness, and advancing corporate digital transformation. Heterogeneity analysis reveals that the innovation-promoting effect of GOD is more pronounced in large cities, non-resource-based cities, and southern cities, and is more salient among state-owned enterprises, capital-intensive firms, and mature firms. This paper provides empirical evidence on the microeconomic effects of market-oriented data allocation and highlights the role of GOD in supporting GCI, corporate sustainable transformation, and the sustainable development of the digital economy. Full article

Conventional defect inspection for warp-knitted lace relies on manual work and negative-sample-based training, resulting in low efficiency, frequent false detections and poor adaptability. This study presents a novel AI visual inspection system centered on positive-sample learning, which is built upon a five-layer 5G + Industrial Internet distributed architecture. Supported by modified looms, high-precision imaging devices and an optimized YOLOv5s model, the system accomplishes intelligent defect detection. A positive-sample self-learning paradigm and dual-model collaboration mechanism are proposed to reduce the demand for negative samples and cut labeling expenses. The integration of CBAM, FPN + PAN structure, self-supervised learning and hybrid loss further strengthens the recognition performance for subtle defects under complex patterns. Industrial tests show that the system reaches a grid-level classification accuracy of 95% and a frame-level detection rate over 98%, with a detection speed of 30 m/min. It reduces labor costs and product reject rates by 40% and 30% correspondingly while running stably in real production. This method breaks the constraints of traditional training modes, provides a scalable intelligent solution for the digital upgrading of the warp-knitted lace industry, and promotes the high-quality development of textile manufacturing. Full article