Search Results (498)

Employee turnover remains a critical challenge for organizations, prompting an examination of how leadership approaches influence employees’ intentions to leave. This study investigates the impact of transformational leadership on turnover intention, focusing on emotional exhaustion and creativity as potential mediators. The study employs a quantitative design grounded in leadership and organizational psychology theory and surveys 182 professionals working in the information technology sector across Bosnia and Herzegovina, Croatia, Serbia, and Montenegro. Structural equation modeling reveals that transformational leadership reduces turnover intention by alleviating emotional exhaustion, highlighting the importance of psychological well-being in employee retention. While transformational leadership enhances employee creativity, creativity did not significantly mediate turnover intention in this context. These findings suggest that strategies that foster engagement and reduce burnout in knowledge-intensive industries can strengthen organizational commitment and improve retention. This study contributes to the understanding of behavioral mechanisms linking leadership to employee outcomes and offers actionable insights for modern organizations aiming to address turnover through supportive, empowering leadership practices. Additional mediators and contextual variables should be explored in further research. Full article

Existing research predominantly focuses on the preservation or renewal models of the physical forms of historic cultural districts, with limited exploration of their roles in stimulating tourists’ cognitive, affective resonance, and behavioral interactions. This study addresses historic cultural districts by evaluating the space quality and its impact on tourist experiences through the “cognition-affect-behavior” framework, integrating GIS, street view semantic segmentation, VR eye-tracking, and web crawling technologies. The findings reveal significant multidimensional differences in how space quality influences tourist experiences: the impact intensities of functional diversity, sky visibility, road network accessibility, green visibility, interface openness, and public facility convenience decrease sequentially, with path coefficients of 0.261, 0.206, 0.205, 0.204, 0.201, and 0.155, respectively. Additionally, space quality exerts an indirect effect on tourist experiences through the mediating roles of cognitive, affective, and behavioral dimensions, with a path coefficient of 0.143. This research provides theoretical support and practical insights for empowering cultural heritage space governance with digital technologies in the context of cultural and tourism integration. Full article

The growing need for secure and privacy-preserving identity management in industrial environments has exposed the limitations of traditional, centralized authentication systems. In this context, SIBERIA was developed as a modular solution that empowers users to control their own digital identities, while ensuring robust protection of critical services. The system is designed in alignment with European standards and regulations, including EBSI, eIDAS 2.0, and the GDPR. SIBERIA integrates a Self-Sovereign Identity (SSI) framework with a decentralized blockchain-based infrastructure for the issuance and verification of Verifiable Credentials (VCs). It incorporates multi-factor authentication by combining a voice biometric module, enhanced with spoofing-aware techniques to detect synthetic or replayed audio, and a behavioral biometrics module that provides continuous authentication by monitoring user interaction patterns. The system enables secure and user-centric identity management in industrial contexts, ensuring high resistance to impersonation and credential theft while maintaining regulatory compliance. SIBERIA demonstrates that it is possible to achieve both strong security and user autonomy in digital identity systems by leveraging decentralized technologies and advanced biometric verification methods. Full article

Background/Objectives: BRIGHTLIGHT was the national evaluation of adolescent and young adult (AYA) cancer services in England. BRIGHTLIGHT results were not available when the most recent healthcare policy (NHSE service specifications for AYA Cancer) for AYA was drafted and therefore did not consider BRIGHTLIGHT findings and recommendations. We describe the co-development and delivery of a Policy Lab to expedite the implementation of the new service specification in the context of BRIGHTLIGHT results, examining the roles of multi-stakeholders to ensure service delivery is optimised to benefit AYA patients. We address the key question, “What is the roadmap for empowering different stakeholders to shape how the AYA service specifications are implemented?”. Methods: A 1-day face-to-face policy lab was facilitated, utilising a unique, user-centric engagement approach by bringing diverse AYA stakeholders together to co-design strategies to translate BRIGHTLIGHT evidence into policy and impact. This was accompanied by an online workshop and prioritisation survey, individual interviews, and an AYA patient workshop. Workshop outputs were analysed thematically and survey data quantitatively. Results: Eighteen professionals and five AYAs attended the face-to-face Policy Lab, 16 surveys were completed, 13 attended the online workshop, three professionals were interviewed, and three AYAs attended the patient workshop. The Policy Lab generated eight national and six local recommendations, which were prioritised into three national priorities: 1. Launching the service specification supported by compelling communication; 2. Harnessing the ideas of young people; and 3. Evaluation of AYA patient outcomes/experiences and establishing a national dashboard of AYA cancer network performance. An animation was created by AYAs to inform local hospitals what matters to them most in the service specification. Conclusions: Policy and research evidence are not always aligned, so when emerging evidence does not support current guidance, further exploration is required. We have shown through multi-stakeholder involvement including young people that it was possible to gain a different interpretation based on current knowledge and context. This additional insight enabled practical recommendations to be identified to support the implementation of the service specification. Full article

This study explores the role of community-centered farm-based hospitality in promoting sustainable rural development, with a focus on South Tyrol, Italy. A survey of 461 local residents assessed perceptions of agritourism’s impact on agricultural heritage, environmental sustainability, and community well-being. Factor analysis identified two main constructs—Agroheritage Sustainability and Empowered Eco-Tourism—which together capture the multifaceted benefits of agritourism. Agroheritage Sustainability reflects the preservation of traditional farming practices, cultural landscapes, and intergenerational knowledge, emphasizing the role of tourism in maintaining cultural identity and preventing land abandonment. Empowered Eco-Tourism highlights the socio-economic benefits of sustainable tourism, including community empowerment, environmental stewardship, and the creation of new economic opportunities. The study’s findings indicate that local residents view agritourism as a holistic approach that supports rural livelihoods while preserving cultural heritage and promoting ecological resilience. The analysis further supports the potential of farm-based hospitality as a model for sustainable rural development, aligning closely with EU policies and global best practices. The Roter Hahn initiative in South Tyrol serves as a practical example of this approach, demonstrating the value of certification programs in enhancing transparency, quality, and sustainability. These insights provide valuable guidance for policymakers and tourism developers seeking to promote sustainable rural tourism globally. The contribution of this research lies in its empirical validation of a dual-construct model that links community engagement with agroecological and cultural sustainability, offering a transferable framework for evaluating agritourism as a lever for sustainable rural development in diverse regional contexts. Full article

In the context of industrial digitalization, the Industry 5.0 paradigm introduces digital twins as a cutting-edge solution. This study explores the concept of digital twins and their integration with the Industrial Internet of Things (IIoT), offering insights into how these technologies bring intelligence to industrial settings to drive both process optimization and sustainability. Industrial digitalization connects products and processes, boosting the productivity and efficiency of people, facilities, and equipment. These advancements are expected to yield broad economic and environmental benefits. As connected systems continuously generate data, this information becomes a vital asset, but also introduces new challenges for industrial operations. The work presented in this article aims to demonstrate the possibility of generating advanced tools for process optimization. This, which ultimately impacts the environment and empowers people in the processes, is achieved through data integration and the development of a digital twin using open tools such as NodeRed v4.0.9 and Python 3.13.5 frameworks, among others. The article begins with a conceptual analysis of IIoT and digital twin integration and then presents a case study to demonstrate how these technologies support the principles of the Industry 5.0 framework. Specifically, it examines the requirements for applying the golden batch concept within a biological production environment. The goal is to illustrate how digital twins can facilitate the achievement of quality standards while fostering a more sustainable production process. The results from the case study show that biomaterial concentration was optimized by approximately 10%, reducing excess in an initially overdesigned process. In doing so, this paper highlights the potential of digital twins as key enablers of Industry 5.0—enhancing sustainability, empowering operators, and building resilience throughout the value chain. Full article

This research explores the concept of open building (OB) in the context of low-cost housing, focusing on its historical applications in Egypt during the 1980s. By evaluating past experiences, the study aims to extract key lessons that can inform the design and implementation of contemporary social housing projects. The goal is to foster resilience and diversity in housing typologies to ensure they align with the evolving needs of residents. To achieve these objectives, the research employed a multi-dimensional strategy, beginning with a comprehensive literature review of the open building movement (OB); then, the study traced the evolution of the OB movement in Egypt using a qualitative analysis approach, which involved analyzing its implementation in low-cost housing projects over the past four decades. Through this historical lens, the study identifies design principles and strategies that can enhance social housing projects by applying OB. Considering the life cycle cost, OB enables an incremental process that would align with users’ financial capacities. The research revealed the substantial capacity of open building (OB) to address Egypt’s social housing challenges, primarily by fostering user-driven flexibility in housing unit design and area selection. This empowers occupants to choose spaces perfectly suited to their family’s evolving needs. Moreover, the findings provide a roadmap for revitalizing the OB movement by analyzing and overcoming past implementation difficulties, consequently balancing the initial cost and long-term economics for citizens and significantly reducing the governmental sector’s expenditure. Full article

Image segmentation is a foundation for autonomous driving frameworks that empower vehicles to explore and navigate their surrounding environment. It gives a fundamental setting to the dynamic cycles by dividing the image into significant parts like streets, vehicles, walkers, and traffic signs. Precise segmentation ensures safe navigation and the avoidance of collisions, while following the rules of traffic is very critical for seamless operation in self-driving cars. The most recent deep learning-based image segmentation models have demonstrated impressive performance in structured environments, yet they often fall short when applied to the complex and unpredictable conditions encountered in autonomous driving. This study proposes an Adaptive Ensemble Attention (AEA) mechanism within a Generative Adversarial Network architecture to deal with dynamic and complex driving conditions. The AEA integrates the features of self, spatial, and channel attention adaptively and powerfully changes the amount of each contribution as per input and context-oriented relevance. It does this by allowing the discriminator network in GAN to evaluate the segmentation mask created by the generator. This explains the difference between real and fake masks by considering a concatenated pair of an original image and its mask. The adversarial training will prompt the generator, via the discriminator, to mask out the image in such a way that the output aligns with the expected ground truth and is also very realistic. The exchange of information between the generator and discriminator improves the quality of the segmentation. In order to check the accuracy of the proposed method, the three widely used datasets BDD100K, Cityscapes, and KITTI were selected to calculate average IoU, where the value obtained was 89.46%, 89.02%, and 88.13% respectively. These outcomes emphasize the model’s effectiveness and consistency. Overall, it achieved a remarkable accuracy of 98.94% and AUC of 98.4%, indicating strong enhancements compared to the State-of-the-art (SOTA) models. Full article

Despite progress in inclusive education, students with Special Educational Needs (SEN) often lack valid, tailored tools for career assessment, limiting equitable transitions to adulthood and employment. Closing this gap is crucial for Sustainable Development Goal 4 (SDG 4), which calls for quality and inclusive educational opportunities. This study addresses this need by adapting and validating a 16-item Career Maturity Inventory-Form C (CMI-C) for Chinese post-secondary SEN students (n = 34) in vocational training in higher education. Rasch modeling, supported by exploratory factor analysis, indicated that a two-factor structure—‘career choice readiness’ and ‘intention to seek career consultation’—provided the best fit to the data, rather than the originally hypothesized four-factor model. The results were more consistent with a two-dimensional structure than with prior four-factor frameworks, though both were explored. Two poorly performing items were removed, resulting in a fourteen-item scale with acceptable item fit and reliability indices in this hard-to-reach group. This restructuring suggests constructs such as concern, confidence, and curiosity are closely linked in SEN populations, underscoring the value of context-sensitive assessment. The revised instrument demonstrated satisfactory model fit and internal consistency; however, convergent validity and practical utility should be interpreted cautiously given the modest sample size. While further validation in larger and more diverse samples is warranted, this study offers preliminary evidence for an adapted, inclusive assessment tool that aligns with SDG 4’s aim to promote equity and empower SEN students in educational and career pathways. Full article

This study examines the added value of territorial cooperation within the LEADER approach, a key pillar of the EU’s rural development policy. Both interterritorial and transnational cooperation projects empower Local Action Groups (LAGs) to tackle common challenges through innovative and community-driven strategies. Drawing on over 3000 projects since 1994, LEADER cooperation has proven its ability to deliver tangible results—such as joint publications, pilot projects, and shared digital platforms—alongside intangible benefits like knowledge exchange, improved governance, and stronger social capital. By facilitating experiential learning and inter-organizational collaboration, cooperation enables stakeholders to work across territorial boundaries and build networks that respond to both national and transnational development issues. The interaction among diverse actors often fosters innovative responses to local and regional problems. Using a mixed-methods approach, including case studies of Italian LAGs, this research analyses the dynamics, challenges, and impacts of cooperation, with a focus on learning processes, capacity building, and long-term sustainability. Therefore, this study focuses not only on project outcomes but also on the processes and learning dynamics that generate added value through cooperation. The findings highlight how territorial cooperation promotes inclusivity, fosters cross-border dialogue, and supports the development of context-specific solutions, ultimately enhancing rural resilience and innovation. In conclusion, LEADER cooperation contributes to a more effective, participatory, and sustainable model of rural development, offering valuable insights for the broader EU cohesion policy. Full article

Background/Objectives: The Janus kinase-signal transducer and activator of transcription (JAK-STAT) signaling pathway is a critical mediator of immune regulation, inflammation, and cancer progression. Although implicated in colorectal cancer (CRC) pathogenesis, its molecular heterogeneity and clinical significance remain insufficiently characterized—particularly within early-onset CRC (EOCRC) and across diverse treatment and demographic contexts. We present AI-HOPE-JAK-STAT, a novel conversational artificial intelligence platform built to enable the real-time, natural language-driven exploration of JAK/STAT pathway alterations in CRC. The platform integrates clinical, genomic, and treatment data to support dynamic, hypothesis-generating analyses for precision oncology. Methods: AI-HOPE-JAK-STAT combines large language models (LLMs), a natural language-to-code engine, and harmonized public CRC datasets from cBioPortal. Users define analytical queries in plain English, which are translated into executable code for cohort selection, survival analysis, odds ratio testing, and mutation profiling. To validate the platform, we replicated known associations involving JAK1, JAK3, and STAT3 mutations. Additional exploratory analyses examined age, treatment exposure, tumor stage, and anatomical site. Results: The platform recapitulated established trends, including improved survival among EOCRC patients with JAK/STAT pathway alterations. In FOLFOX-treated CRC cohorts, JAK/STAT-altered tumors were associated with significantly enhanced overall survival (p < 0.0001). Stratification by age revealed survival advantages in younger (age < 50) patients with JAK/STAT mutations (p = 0.0379). STAT5B mutations were enriched in colon adenocarcinoma and correlated with significantly more favorable trends (p = 0.0000). Conversely, JAK1 mutations in microsatellite-stable tumors did not affect survival, emphasizing the value of molecular context. Finally, JAK3-mutated tumors diagnosed at Stage I–III showed superior survival compared to Stage IV cases (p = 0.00001), reinforcing stage as a dominant clinical determinant. Conclusions: AI-HOPE-JAK-STAT establishes a new standard for pathway-level interrogation in CRC by empowering users to generate and test clinically meaningful hypotheses without coding expertise. This system enhances access to precision oncology analyses and supports the scalable, real-time discovery of survival trends, mutational associations, and treatment-response patterns across stratified patient cohorts. Full article

The TOWCHED project explores how arts and heritage-based educational methodologies can support sustainable development by enhancing key transversal competencies in learners, particularly children and youth. In response to the global challenges outlined in the sustainable development goals (SDGs), this project promotes inclusive and participatory approaches to education that foster social cohesion, intercultural understanding, and civic engagement. Partnering with museums, TOWCHED develops cross-curricular pedagogical interventions, such as experiential, blended, and collection-mediated learning, that link cultural heritage with contemporary social and environmental concerns. These approaches aim to strengthen creativity, critical thinking, collaboration, and self-awareness. TOWCHED demonstrates that heritage collection-based education can play a vital role in transforming schools and other learning environments into hubs for sustainable, lifelong learning. By embedding cultural expression and heritage into educational practices, the project offers a compelling model for empowering individuals to navigate and shape a more equitable and interconnected world. This paper has two aims. First, we introduce TOWCHED, an interdisciplinary project recently funded by the Horizon Europe program of the European Union to preserve and promote education for sustainability in the heritage context. Second, we introduce a set of tools related to the project. Full article

This study explores how Black student leaders (BSLs) at public historically white institutions (HWIs) in Florida and Georgia navigate racial battle fatigue (RBF) in the context of anti-DEI legislation. Amid rising political hostility toward diversity, equity, and inclusion (DEI) efforts, this research examines the lived experiences of 11 BSLs as they respond to racialized campus climates that are increasingly ambiguous and unsupportive. Using a critical qualitative approach, data were collected through two in-depth interviews per participant and analyzed using inductive and deductive coding. Four major findings emerged: (1) BSLs experience heightened psychological, physiological, and emotional forms if stress linked to their identity and leadership roles; (2) anti-DEI policies contribute to institutional erasure and confusion; (3) students express emotional withdrawal, hypervigilance, and disillusionment with performative leadership; (4) students employ culturally grounded coping strategies centered on self-care, spirituality, and community. This study underscores that BSLs are both empowered and burdened by their leadership, especially under politically restrictive conditions. The findings call for student affairs educators to prioritize engagement and belonging and offer identity-affirming support. Further, scholars with academic freedom are urged to continue documenting racialized student experiences. These insights are critical to protecting Black student leadership and equity-centered educational transformation. Full article

The rapid spread of artificial intelligence (AI) in education means that students need to master both AI literacy and personal agency. This study situates a sample of 425 Slovenian secondary technical students within a three-tier framework that maps psychological empowerment onto AI literacy outcomes within a cultural–historical activity system. The agency competence assessments yielded four profiles of student agency, ranging from fully empowered to largely disempowered. The cluster membership explained significant additional variance in AI literacy scores, supporting the additive empowerment model in an AI-rich vocational education and training context. The predictive modeling revealed that while self-efficacy, mastery-oriented motivations, and metacognitive self-regulation contributed uniquely—though small—to improving AI literacy, an unexpectedly negative relationship was identified for internal locus of control and for behavioral self-regulation focused narrowly on routines, with no significant impact observed for grit-like perseverance. These findings underscore the importance of fostering reflective, mastery-based, and self-evaluative learning dispositions over inflexible or solely routine-driven strategies in the development of AI literacy. Addressing these nuanced determinants may also be vital in narrowing AI literacy gaps observed between diverse disciplinary cohorts, as supported by recent multi-dimensional literacy frameworks and disciplinary pathway analyses. Embedding autonomy-supportive, mastery-oriented, student-centered projects and explicit metacognitive training into AI curricula could shift control inward and benefit students with low skills, helping to forge an agency-driven pathway to higher levels of AI literacy among high school students. The most striking and unexpected finding of this study is that students with a strong sense of competence—manifested as high self-efficacy—can achieve foundational AI literacy levels equivalent to those possessing broader, more holistic agentic profiles, suggesting that competence alone may be sufficient for acquiring essential AI knowledge. This challenges prevailing models that emphasize a multidimensional approach to agency and has significant implications for designing targeted interventions and curricula to rapidly build AI literacy in diverse learner populations. Full article

Native forest timber supplies are declining, and industry needs to do more with less to meet growing demand for wood products. An Australian-based, vertically integrated timber manufacturing business is commissioning a spindleless lathe to produce engineered wood products from small logs. The literature on innovation in timber manufacturing was found to generally focus on technical innovation, with relatively little use of market-oriented concepts and theory. This was particularly true in the Australian context. Using a market-oriented case study approach, this research assessed innovation in the business. It aimed to inform industry-wide innovation approaches to meet market demand in the face of timber supply challenges. Interviews were conducted with key personnel at the firm. Data and outputs were produced to facilitate comparison to existing research and conceptual frameworks. The business was found to empower key staff and willingly access knowledge, information and data from outside its corporate domain. It was also found to prioritise corporate goals outside of traditional goals of profit and competitive advantage. This was shown to increase willingness to try new things at the mill and increase the chances that new approaches would succeed. Thinking outside of the corporate domain was shown to allow access to resources that the firm could not otherwise count on. It is recommended that wood processing businesses seek to emulate this element of the case study, and that academia and the broader sector examine further the potential benefits of using enterprise and market-oriented lenses to better utilise available resources and maintain progress towards corporate goals. Full article