Search Results (81)

In order to study the stability of orthotropic steel box girders and the characteristics of the synergistic stress mechanism of key components, the test method of axial compression using the scale model of steel box girder segments was carried out, and the collaborative working performance of the plate ribs of the U-shaped stiffener plate and the influence mechanism of the diaphragm on the structural stability were systematically studied. The results show that the strain difference between the deckplate and the U rib increases significantly with the increase in load, and the distribution law of the end chamber is larger than the middle, and the bottom plate is larger than the top plate and the web plate. The diaphragm mainly bears the tensile force under axial load, which provides out-of-plane restraint for the stiffener, and its restraint effect is the strongest at the web plate and the weakest at the bottom plate. This paper clarifies the synergistic stress mechanism of U-rib stiffeners under high axial pressure conditions, quantifies the contribution of diaphragms to local stability, and provides a theoretical basis for the structural design of similar bridges. Full article

The tourism and hospitality sector in Saudi Arabia is undergoing rapid sustainability transformation under the strategic direction of Vision 2030. This study examines the maturity of Sustainability Actions (SAs), their key drivers, and implementation barriers, comparing the perceptions of industry practitioners and academic experts. Using a qualitative abductive research design based on 20 in-depth semi-structured interviews with industry and academic experts in Saudi Arabia, followed by thematic analysis using a machine learning Qualcoder 3.7 software, the findings reveal both convergence and divergence between the two groups. While both recognize Vision 2030 as the primary catalyst and acknowledge financial costs and knowledge gaps as major barriers, industry experts emphasize operational efficiency and short-term performance outcomes, whereas academics advocate systemic transformation grounded in circular economy principles and long-term socio-ecological regeneration. The results demonstrate that sustainability adoption in Saudi Arabia is shaped not only by market demand but also by a strong government-led institutional framework that accelerates sectoral change. The findings are structured across environmental, social, and economic sustainability dimensions, offering differentiated implications for industry practitioners and academic stakeholders within emerging tourism economies. The study contributes to sustainability and tourism and hospitality literature by offering a comparative multi-perspective analysis and by conceptualizing sustainability transition as a hybrid model combining policy direction, market incentives, and knowledge collaboration. Managerially, the findings highlight the need for regulatory clarity, targeted financial mechanisms, capacity building, and stronger industry–academia integration to institutionalize sustainability practices in emerging tourism economies. Full article

This study delves into how the literature conceptualizes banking efficiency as a capability shaping sustainability-oriented pathways under conditions of systemic uncertainty, including recurrent economic–financial disruptions and geopolitical shocks. Using records indexed in the Web of Science Core Collection, the study combines bibliometric mapping with conceptual structuring to examine publication dynamics, collaboration networks, and the thematic evolution of research linking bank efficiency, green finance intermediation, sustainable digital innovation, and risk governance. The study reveals a multidimensional knowledge base organized around two converging streams: (i) research on efficiency, stability, and crisis transmission emphasizing intermediation quality, performance under stress, and prudential responses; and (ii) sustainability and innovation scholarship focusing on how financial systems enable eco-innovation diffusion and low-carbon transition through capital allocation, governance mechanisms, and digitally enabled transformation. Across these streams, banking efficiency is increasingly discussed not merely as a performance ratio, but as a strategic capability that becomes particularly salient in crisis environments: it can reduce intermediation frictions when funding conditions tighten, strengthen screening and monitoring of green projects amid elevated uncertainty, and support the continuity and scaling of eco-innovations by improving decision speed and resource allocation through digital tools. Collaboration patterns indicate growing interdisciplinary engagement—especially among European and Asian institutions—where crisis, sustainability, and innovation perspectives are integrated into systems-based approaches to green finance. Building on these insights, the article outlines a research agenda oriented toward innovation outcomes in turbulent contexts, emphasizing (a) measurement strategies that connect efficiency to eco-innovation diffusion and adoption rates during stress periods; (b) comparative analyses of how policy incentives and green market signals interact with bank efficiency across crisis episodes; and (c) hybrid methodological designs combining econometric identification, network analytics, scenario-based stress framing, and AI-enabled analytical tools to capture nonlinear dynamics in efficiency–innovation linkages. Overall, the study clarifies how banking efficiency may condition the capacity of financial institutions to sustain green investment intermediation and advance eco-innovation pathways when uncertainty is systemic rather than episodic. Full article

The rapid pace of digital transformation has increased organizations’ reliance on digital technologies and collaborative systems as key drivers of technological innovation. However, the mechanisms through which digital trust, digital technology, and digital capability shape innovation performance—particularly through knowledge sharing—remain insufficiently explored. This study examined the relationships among these digital enablers and innovation performance, positioning knowledge sharing as a central mediating mechanism grounded in the Knowledge-Based View and Open Innovation Theory. A quantitative research design was adopted, and data were collected through a structured survey of 280 professionals working in IT, software development, telecommunications, and other technology-intensive industries. Convenience sampling was employed, and statistical analyses were conducted using SPSS to assess reliability, validity, and structural relationships. The findings revealed that digital trust, digital technology, and digital capability significantly enhance knowledge-sharing practices, which in turn positively influence innovation performance. Moreover, knowledge sharing was found to play a critical mediating role in translating digital enablers into innovation outcomes. This study contributes to the digital innovation literature by highlighting the importance of digital preparedness and collaborative knowledge practices in fostering technological innovation. The findings also offer practical insights for organizations seeking to strengthen innovation performance by developing digital capabilities, fostering trust, and promoting effective knowledge-sharing cultures in technology-intensive environments. Full article

This article examines the role of Human Resource Management (HRM) in shaping employees’ green behaviour and its contribution to organisational environmental performance through an original bibliometric analysis of the international literature. The analysis is based on 105 scientific publications retrieved from the Scopus database for the period 2009–2025. Bibliometric techniques were applied using Bibliometrix and VOSviewer to map publication trends, co-authorship networks, thematic clusters, and the maturity of research themes. The results indicate a strong increase in research output after 2019, combined with high levels of international collaboration and a geographical concentration of studies in Asian economies. Keyword co-occurrence analysis identifies Green Human Resource Management (GHRM) and organisational environmental performance as the core conceptual pillars of the field, while employees’ green behaviour emerges as a key mediating mechanism linking HR practices to environmental outcomes. Thematic mapping based on centrality and density suggests that the field has entered a phase of theoretical consolidation, with emerging research directions focusing on behavioural, strategic, and social dimensions of sustainability. Overall, the study provides a structured overview of the GHRM research landscape and highlights important gaps related to causal mechanisms, economic performance, and cross-sectoral and cross-country evidence. The findings also indicate that sectoral applications beyond tourism and hospitality, cross-country comparative studies, and the integration of economic performance indicators with GHRM remain underexplored, highlighting specific directions for future research. The study adopts a bibliometric research design and does not aim to provide a systematic review of empirical findings. Full article

The present numerical study simultaneously investigates the aerodynamic performance, shape optimization, and aeroacoustic characteristics of modified leading-edge wavy wings for the NACA 0020 airfoil. Unlike conventional passive flow-control approaches, the present study proposes a collaborative vortex–slot control strategy, where streamwise vortices induced by a wavy leading edge interact constructively with momentum injection from upper-surface slot channels. Flow field is analyzed at a Reynolds number of 290,000 and various angles of attack (AoA) utilizing Computational Fluid Dynamics (CFD). Three leading-edge wavy wing configurations, namely A3L11, A3L40 and A11L40, are examined and further modified by introducing streamwise slots near the leading edge on the upper surface of the wing. Three slot diameters (0.07c, 0.10c, and 0.13c) are examined at a constant draft angle of 7.5°, which represents the inclination of the slot relative to the wing surface. The numerical results are validated against experimental data available in the literature. The findings indicate that the A3L11 configuration with a 0.07c slot diameter, as well as the A11L40 configuration at high angles of attack, outperform the baseline wavy wing. This improvement is attributed to the slotting mechanism, which enhances surface suction and streamwise momentum, thereby improving boundary-layer behavior. An increase in aerodynamic efficiency, quantified by the lift-to-drag ratio, is observed at 20° AoA for all configurations. To further enhance performance, shape optimization is performed by optimizing the slot diameter and the distance between the chord line and the slot center using a Genetic Algorithm (GA), with the A11L40 configuration at 20° AoA identified as the optimal design. The optimized configuration yields an overall aerodynamic performance improvement of approximately 27.76% compared to the smooth wing, while broadband aeroacoustic source modeling indicates a relative reduction in predicted noise-source intensity relative to the baseline modified wing. The results are presented through combined quantitative metrics and qualitative flow analyses, demonstrating the potential applicability of the proposed optimization framework to low-Reynolds-number aerodynamic and aeroacoustic design problems, such as those encountered in small-scale air vehicles, bio-inspired wings, and noise-sensitive systems. Full article

This work presents a novel soft gripper concept featuring integrated force feedback and a compact, resource-efficient geometry. The gripper is designed to provide a low-cost, adaptable, and precise solution for manipulating delicate and irregularly shaped objects. By embedding force feedback directly into the structure, the system reliably detects contact and enables controlled, gentle gripping of fragile items. The design was developed for collaborative and assistive robotic applications, where safety and human–robot interaction are prioritized. The prototype is fabricated using consumer-grade 3D-printed components and employs a simple cable-driven actuation system. The hybrid soft–rigid architecture combines compliant fingers with a rigid, sensorized thumb, preserving the adaptive grasping characteristics of soft robotics while simplifying sensing integration and construction. A motor-based control mechanism synchronizes finger motion through cable traction, ensuring reliable and repeatable performance. Experimental evaluations demonstrate secure, damage-free handling across diverse object types, highlighting the gripper’s potential in assistive robotics, cobot environments, biomedical contexts, and other domains requiring safe and delicate manipulation. Full article

The study aims to develop a conceptual model for immersive chemical hazard response training that explicitly addresses four core operational constraints: time pressure, uncertainty, teamwork, and procedural/psychomotor precision. The model responds to the need for collaborative and mistake-driven training approaches in high-risk contexts. A design-oriented, theory-informed approach is applied, combining the identification of training requirements characteristic of chemical hazard response and the formulation of core operational constraints shaping the training design with the specification of CAVE affordances, a four-dimensional instructional design framework (cognitive, emotional, social, and psychomotor), conceptual alignment of scenario components with selected Sustainable Development Goals (SDGs 3, 4, 11, and 16), and a preliminary expert-based content appraisal. Results are presented as a design-oriented outcome in the form of a conceptual framework, accompanied by an illustrative scenario-based instantiation and an expert-based content appraisal demonstrating internal coherence and practical plausibility (I-CVI = 0.80–1.00; S-CVI/Ave = 0.93). Conclusions indicate that the proposed model serves as a structured instructional and scenario-design reference for immersive chemical hazard response training, positioning CAVEs as pedagogically organised learning spaces rather than as standalone simulation technologies. Further implications relate to the transferability of the model to sustainability-oriented response training across other high-risk domains. Empirical evaluation of learning processes, performance outcomes, and transfer to operational practice is identified as a necessary next step for future research. Full article

Respiratory infections cause substantial morbidity and mortality in older adults and other at-risk adult populations. Despite the availability of effective vaccines, adult vaccination coverage remains suboptimal. This narrative review examines strategies designed to improve vaccine uptake among non-pregnant adults aged ≥18 years and inform future adult vaccination strategies. We conducted a targeted literature search using keywords for vaccination, respiratory diseases, strategy/program/implementation, and adults in PubMed database and CDC, WHO, and ECDC websites, between 2014 and 2024. A snowball search of literature reviews and key references was also performed to identify additional relevant studies. Eligible publications focused on vaccination strategies against influenza, COVID-19, and pneumococcal disease targeting non-pregnant adults (≥18 years). We categorized the strategies by intervention type to describe their influence on vaccination campaigns and vaccine uptake/coverage. We included 45 publications, encompassing strategies focused on individual decision-making, healthcare system functions, and national policy. Educational and awareness interventions (such as healthcare worker/provider recommendations during consultation, phone calls, letters, text messages, and social media outreach) reportedly raised vaccination rates. Access-related factors, including convenient vaccination sites and free or subsidized vaccines, were reported to be important factors in improving coverage in underserved communities. Within healthcare settings, strategies such as continuous vaccine provider training and workflow/process optimization were shown to enhance vaccination delivery. At the local or national policy levels, legislation governing program targets shaped immunization efforts and facilitated collaborations and partnerships to expand campaign reach. The findings may inform policymakers and public health/immunization practitioners in designing context-specific immunization initiatives that effectively reach adult populations. Full article

Geothermal energy is a crucial component of climate adaptation and sustainability transitions, as it provides a dependable, low-carbon source of baseload power that can accelerate sustainable energy transitions and enhance climate resilience. Yet, in East Africa—one of the world’s most promising geothermal regions, with the East African Rift—a unique climate-energy opportunity zone—the harnessing of geothermal power remains slow and uneven. This study examines the contextual conditions that facilitate the successful and sustainable development of geothermal power in the region. Drawing on semi-structured interviews with 17 experienced professionals who have worked extensively on geothermal projects across East Africa, the analysis identifies how technical, institutional, managerial, and relational circumstances interact to shape outcomes. The findings indicate an interdependent configuration of success conditions, with structural, institutional, managerial, and meta-conditions jointly influencing project trajectories rather than operating in isolation. The most frequently emphasised enablers were resource confirmation and technical design, leadership and team competence, long-term stakeholder commitment, professional project management and control, and collaboration across institutions and communities. A co-occurrence analysis reinforces these insights by showing strong patterns of overlap between core domains—particularly between structural and managerial factors and between managerial and meta-conditions, highlighting the mediating role of managerial capability in translating contextual conditions into operational performance. Together, these interrelated circumstances form a system in which structural and institutional foundations create the enabling context, managerial capabilities operationalise this context under uncertainty, and meta-conditions sustain cooperation, learning, and adaptation over time. The study contributes to sustainability research by providing a context-sensitive interpretation of how project success conditions manifest in geothermal development under climate transition pressures, and it offers practical guidance for policymakers and partners working to advance SDG 7 (Affordable and Clean Energy), SDG 9 (Industry, Innovation and Infrastructure), and SDG 13 (Climate Action) in Africa. Full article

Extended Reality (XR) technologies have matured into powerful tools for training in high-stakes domains, from emergency response to search and rescue. Yet current systems often struggle to balance real-time AI-driven personalisation with the need for human oversight and calibrated trust. This article synthesizes the programmatic contributions of a multi-study doctoral project to advance a design-and-evaluation framework for trustworthy adaptive XR training. Across six studies, we explored (i) recommender-driven scenario adaptation based on multimodal performance and physiological signals, (ii) persuasive dashboards for trainers, (iii) architectures for AI-supported XR training in medical mass-casualty contexts, (iv) theoretical and practical integration of Human-in-the-Loop (HITL) supervision, (v) user trust and over-reliance in the face of misleading AI suggestions, and (vi) the role of interaction modality in shaping workload, explainability, and trust in human–robot collaboration. Together, these investigations show how adaptive policies, transparent explanation, and adjustable autonomy can be orchestrated into a single adaptation loop that maintains trainee engagement, improves learning outcomes, and preserves trainer agency. We conclude with design guidelines and a research agenda for extending trustworthy XR training into safety-critical environments. Full article

The shipbuilding industry relies heavily on welding, which accounts for approximately 70% of the overall production process. However, the recent decline in skilled workers, together with rising labor costs, has accelerated the automation of shipbuilding operations. In particular, the welding activities are concentrated in the double-bottom region of ships, where collaborative robots are increasingly introduced to alleviate workforce shortages. Because these robots must directly recognize U-shaped weld joints, this study proposes an image-based classification system capable of automatically identifying and classifying such joints. In double-bottom structures, U-shaped weld joints can be categorized into 176 types according to combinations of collar plate type, slot, watertight feature, and girder. To distinguish these types, deep learning-based image recognition is employed. To construct a large-scale training dataset, 3D Computer-Aided Design (CAD) models were automatically generated using Open Cascade and subsequently rendered to produce synthetic images. Furthermore, to improve classification performance, the input images were split into left, right, upper, and lower regions for both training and inference. The class definitions for each region were simplified based on the presence or absence of key features. Consequently, the classification accuracy was significantly improved compared with an approach using non-split images. Full article

As a neighborhood-scale derivative of the Business Improvement District (BID) model, the Neighborhood Business Improvement District (NBID) represents a collaborative governance framework aimed at fostering spontaneous urban regeneration. Its successful establishment critically depends on building consensus among diverse stakeholders during the preparatory phase. This study addresses a significant gap by investigating the psychological mechanisms that shape stakeholders’ willingness to engage in NBIDs prior to their formation. Employing an exploratory sequential mixed-methods approach, we conducted semi-structured interviews in the Tiyuan North Community (Tianjin) and the Yulin East Road Community (Chengdu). Insights from the qualitative phase informed a subsequent quantitative survey administered to 215 stakeholders in Tianjin. Data were analyzed using regression analysis and Structural Equation Modeling (SEM). The results reveal that stakeholders’ performance expectations and collaborative willingness are significantly influenced by three core confidence factors: “Confidence in Authority Support (AS)” (particularly “Confidence in Council Representation”), “Confidence in Organization Capability (OC)” (especially “Confidence in Coordination Ability”), and “Confidence in Multi-party Collaboration.” Crucially, “Confidence in Enabling collaboration (MC_3)” itself acts as a key mediator, translating institutional trust into performance expectations. This study contributes a novel “Confidence–Expectation” framework to the literature on collective action and offers practical, context-sensitive insights for designing collaborative community governance structures aimed at sustainable urban regeneration in China and beyond. Full article

Although communication quality is widely recognized as a catalyst for workplace innovation, existing research seldom integrates communication quality, trust in leadership, and organizational commitment within a single explanatory framework, particularly in team-based enterprises operating in emerging economies. This study examines how communication quality fosters employee innovation through the sequential mediating roles of trust in leadership and organizational commitment, emphasizing its contribution to sustainable enterprise performance. Rooted in Social Exchange Theory (SET), the study illustrates how transparent, reciprocal, and supportive communication enhances relational trust, strengthens employees’ emotional attachment to their organizations, and creates a climate conducive to creativity and collaborative problem-solving. A quantitative design was employed using data from employees engaged in innovation-driven projects within medium- and large-sized software firms in Turkey’s ICT sector. A total of 339 valid responses were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to test the hypothesized relationships. The findings demonstrate that communication quality directly promotes employee innovation and indirectly strengthens innovation through trust in leadership and organizational commitment as sequential mediators. Additionally, organizational commitment amplifies the influence of communication quality on innovation, indicating that committed employees more effectively translate constructive communication into innovative behaviors. These results underscore the strategic importance of communicative clarity, relational leadership, and commitment-building practices in shaping resilient, innovation-oriented teams. The study advances SET by identifying trust and commitment as key relational mechanisms through which communication quality drives innovation, offering theoretical enrichment and practical guidance for sustainable human resource management and team-based organizational development. Full article

The rapid emergence of generative AI is transforming how employees engage with technology to perform tasks, make decisions, and create value. Despite its transformative potential, empirical findings on AI adoption remain inconsistent, particularly regarding how job characteristics shape employees’ confidence and readiness to use generative AI. Grounded in the Task–Technology Fit framework and self-efficacy theory, this research examines the curvilinear relationship between job complexity and AI self-efficacy and its subsequent effects on AI adoption readiness and behavior. We conducted two survey studies to test the proposed hypotheses using structural equation modeling. Results reveal that employees in both low- and high-complexity roles exhibit a low level of AI self-efficacy and a subsequent lower level of AI adoption behaviors compared to those in moderately complex roles. These findings challenge the assumption that highly skilled roles typically lead AI integration and instead highlight the importance of aligning task structure with AI capabilities. This study advances theory by introducing a non-linear boundary condition to technology adoption and offers practical guidance for organizations to design jobs and training programs that cultivate confidence and foster sustainable human–AI collaboration. Full article