Search Results (66)

Artificial intelligence (AI) is increasingly being integrated into Clinical Decision-Support Systems (CDSSs), shifting attention from algorithmic performance alone to the broader sociotechnical conditions that shape effective human–AI collaboration. In this study, we investigated whether nine displacement-based structured coordination protocols can improve the collective diagnostic decision-making of hybrid human–AI teams (16 board-certified radiologists and a simulated AI model) in a radiological double-reading task for vertebral fracture detection from X-ray images. Among the protocols tested, the Accuracy-Oriented, Confidence-Oriented, and Presumptuous strategies achieved the highest (balanced) accuracy overall, with up to 97% among strong clinicians and 92% among weak ones, significantly outperforming simpler methods like majority voting. Conversely, approaches optimized for a single metric (e.g., sensitivity or specificity) introduced performance trade-offs. Benefits were strongest among less proficient clinicians, which exhibited substantial and consistent improvements, while proficient clinicians showed limited gains and occasional declines. Critically, Kasparov’s Law emerged as a comparative framework for empirically evaluating coordination quality relative to the diagnostic task, clinical objective, and clinician proficiency by identifying situations in which less proficient clinicians supported by superior coordination protocols outperformed more proficient clinicians operating under inferior ones. These findings demonstrate that coordination design is a critical determinant of hybrid human–AI decision-making, highlighting that a well-structured process can be more relevant than individual components’ performance and support process-centered approaches to the development and evaluation of CDSSs. Full article

This study develops and evaluates machine learning models for classifying Korean Baseball Organization (KBO) playoff advancement using pitching metrics from 2015 to 2024 (N = 100 team-seasons), focusing specifically on pitching’s contribution to playoff qualification to address the ERA-FIP paradox at the team level. Five algorithms were compared: Random Forest, Support Vector Machines, Logistic Regression, Neural Networks, and Decision Trees. Independent variables included ten pitching statistics: Earned Run Average (ERA), Walks and Hits per Inning Pitched (WHIP), Fielding Independent Pitching (FIP), Strikeouts per 9 Innings (K/9), Walks per 9 Innings (BB/9), Strikeout-to-Walk Ratio (K/BB), Home Runs per 9 Innings (HR/9), batting average against (BAA), and opponent On-Base Percentage (OBP) and On-Base Plus Slugging (OPS). Logistic Regression achieved the highest classification performance with an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.804 and classification accuracy of 73.0%, followed by Neural Network (AUC = 0.799, CA = 72.0). Feature importance analysis showed ERA and WHIP, both defense-dependent metrics, as the dominant predictors of postseason qualification, collectively accounting for 33.7% of information gain, while FIP ranks fifth, indicating that defense-dependent metrics are more informative for team success than defense-independent measures. The findings highlight the strategic importance of pitching–defense synergy, demonstrate the applicability of machine learning-based playoff classification beyond Major League Baseball, and provide empirical evidence that defense-dependent metrics (ERA, WHIP) exhibit superior discriminatory power compared to defense-independent metrics (FIP) for team playoff qualification. Findings reflect pitching’s contribution to playoff success; comprehensive models integrating hitting, defense, and managerial factors would provide more complete classification frameworks. Full article

(1) Background: Zinc is an essential micronutrient involved in immune regulation, epithelial barrier integrity, and the host response to bacterial infections. However, the clinical benefits of zinc supplementation across different age groups remain uncertain, with heterogeneous findings and variable dosing strategies reported in the literature. (2) Objectives: To map and summarize randomized controlled trials (RCTs) evaluating zinc supplementation (either as treatment or prophylaxis) for bacterial infection outcomes in neonates, children, and adults, and to identify gaps requiring further research, including the use of zinc-based nanoparticles. (3) Eligibility Criteria: We included English-language RCTs that evaluated zinc supplementation and reported clinical outcomes related to bacterial infections. Observational studies, trials without infection-related outcomes, and studies not involving human participants were excluded. (4) Sources of Evidence: A MEDLINE (PubMed) search was conducted from 2000 to 1 November 2025 using predefined keywords related to zinc supplementation, neonates, children, adults, and bacterial infections. Reference lists of eligible articles were screened to identify additional studies. (5) Charting Methods: Data were charted for each included study, including population characteristics, zinc dosing and regimen, type of supplementation (therapeutic or prophylactic), main infection-related outcomes, and key findings. Data charting was performed independently and verified within the research team. (6) Results: A total of 51 RCTs were included: 10 in neonates, 32 in children, and 9 in adults. In neonates, therapeutic zinc supplementation as an adjunct to antibiotics showed heterogeneous results, with some studies reporting reductions in morbidity, inflammatory markers or mortality, while others found no significant differences in clinical outcomes. In children, zinc supplementation consistently reduced the duration and severity of diarrheal episodes and, in several trials, improved the resolution of respiratory infections. In adults, the evidence was limited but suggested potential benefits in selected populations, such as burn patients or those with zinc deficiency or immunologic dysfunction. Variability in zinc dosage, treatment duration, and outcome definitions limits direct comparison across studies. (7) Conclusions: Zinc supplementation appears to provide benefits in neonates and children, whereas evidence in adults remains mixed and inconclusive. Standardized, well-powered RCTs are needed to define optimal dosing strategies, identify populations most likely to benefit, and clarify the mechanisms underlying zinc’s anti-infective effects. Future research should consider the use of zinc oxide nanoparticles (ZnO-NPs) demonstrated broad-spectrum antimicrobial activity and potential synergy with antibiotics, although clinical data remain still limited. Full article

Human–Robot Collaboration (HRC) in construction projects promises enhanced productivity, safety, and quality, yet realizing these benefits requires understanding the multifaceted human and robotic factors that influence team performance. This study develops and validates a multidimensional framework that links key human abilities (operational skill, decision-making ability, and learning ability) and robot capacities (functionality and operability) to HRC team performance, with task complexity considered as contextual influence. A field survey of construction practitioners (n = 548) was analyzed using partial least squares structural equation modeling (PLS-SEM) to test direct effects and human–robot synergies. Results reveal that all five main effects are positive and significant, indicating that both human abilities and robot capacities have significant contribution. Moreover, every hypothesized two-way interaction is supported, evidencing strong interaction effects. Three-way moderation analyses further reveal that task complexity significantly strengthened the interactions of human abilities with robot functionality, whereas its interactions with robot operability were not significant. The study contributes an integrated and theory-driven model of HRC team performance that accounts for human abilities and robot capacities under varying task complexity, and validated constructs that can be used to diagnose and predict performance. The findings offer actionable guidance for project managers by recommending that they prioritize user-friendly robot operability to translate worker expertise into performance across a wide range of tasks, invest in training to strengthen operators’ skills and decision-making, and, for complex tasks, pair highly skilled workers with high-functionality robots to maximize performance gains. Full article

This study evaluates the competency-based performance of Initial Incident Commander (IIC) candidates—fire officers who serve as first-arriving, on-scene incident commanders—in South Korea and identifies sub-competency deficits to inform training improvements. Using evaluation data from 92 candidates tested between 2022 and 2024—of whom 67 achieved certification and 25 did not—we analyzed counts and mean scores for each sub-competency and integrated transcribed radio communications to contextualize deficiencies. Results show that while a majority (72.8%) passed, a significant proportion (27.2%) failed, with recurrent weaknesses in crisis response, progress management, and decision-making. For example, “Responding to Unexpected or Crisis Situations 3-3” recorded 27 unsuccessful cases with a mean score of 68.8. Candidates also struggled with resource allocation, situational awareness and radio communications. The study extends recognition-primed decision-making theory by operationalizing behavioral marker frameworks and underscores the need for predetermined internal alignment, scalability and teamwork synergy. Practical implications recommend incorporating high-fidelity simulation and VR scenarios, competency frameworks and reflective debriefs in training programs. Limitations include the single-country sample, reliance on predetermined scoring rubrics and absence of team-level analysis. Future research is indispensable to adopt multi-jurisdictional longitudinal designs, evaluate varied training interventions, assess skill retention and explore the interplay between physical and cognitive training over time. Full article

This study investigates the influence of cultural dimensions on IT project team effectiveness through a comprehensive multi-method approach designed to connect theoretical cultural knowledge with practical implementation. Using data collected from 127 IT professionals across various cultural backgrounds, we applied regression analysis, factor analysis, cluster analysis, decision trees, and structural equation modeling to examine relationships between cultural factors and project outcomes. The research identified that power distance, individualism, and uncertainty avoidance significantly impact team productivity, management effectiveness, methodology selection, and innovation capabilities. Three distinct clusters of IT professionals emerged with varying attitudes toward cultural diversity, requiring fundamentally different management approaches. Results show that low power distance and high individualism correlate positively with team performance, while high uncertainty avoidance negatively impacts productivity. Based on these findings, we propose the novel CROSS Cycle Framework (Culture Recognition, Role Alignment, Organizational Adaptation, Synergy Building, Sustainability) for improving cross-cultural team management. Teams implementing cluster-appropriate versions of this methodology showed significant performance improvements compared to generic approaches. This research contributes to both theoretical understanding and practical management of multicultural IT teams by providing the first systematic integration of cultural assessment with sustainable, role-specific management adaptations designed specifically for IT project environments. Full article

Background/Objectives: In today’s rapidly evolving healthcare landscape, fostering a culture of innovation and continuous improvement is essential—especially within a nursing association that leads individual and organizational credentialing. Methods: Colleagues from the American Nurses Enterprise (ANE) Innovation Department and the Institute for Nursing Research and Quality Management collaborated to develop the Culture of Innovation and Quality Model^TM. This process involved conducting a literature review, developing a survey instrument, and administering a pilot pre-survey to ANE employees to collect baseline data. Future research will include a comparison with a post-survey after interventions aimed at strengthening the culture of innovation and quality. Results: The results of the pilot pre-survey were high overall and guided the team in identifying areas with the greatest opportunities for improvement. Based on these findings, interventions are being developed that will be implemented at ANE to enhance the practice of and promote the synergy between innovation and quality. Conclusions: Achieving and sustaining high-quality standards of care and advancing the professional development of nurses requires a culture where staff feel safe and have opportunities to create, innovate, improve, and learn. This will help promote an environment where people thrive while ensuring that the nursing profession and practice remain cutting-edge and aligned with emerging technologies and evolving healthcare complexities. The Culture of Innovation and Quality Model^TM may provide a blueprint for organizations who seek to advance innovation and quality knowledge, engagement, and practices and assist their employees in providing better service to colleagues, partners, and customers while adapting to the evolving healthcare environment. Full article

The incentive mechanism functions as a core safeguard to ensure the efficient execution of consortium-based Public–Private Partnership (PPP) projects and the realization of value-added outcomes. The heterogeneity of consortium members, their reciprocal preferences, and the collaborative dynamics of the team collectively contribute to the formation of project alliances characterized by resource synergy, complementary advantages, and risk sharing. However, these same factors also contribute to the multi-layered structure of principal–agent relationships and the inherent complexity of incentive pathways and mechanisms in consortium-based PPP settings. Drawing upon the team collaboration effect and reciprocal preferences among consortium members, this study incorporated the member heterogeneity and developed three incentive models for such projects, such as the Dual-Performance (DP) mode, the Total-Performance (TP) mode, and the Individual-Performance (IP) mode. This study examined the conditions under which these incentive modes were established, the relationship between incentive intensity and optimal effort levels of consortium members, and the influence of reciprocal preferences on incentive effectiveness. Further, the selection criteria and appropriate application scenarios for each of the three incentive models were analyzed according to a comparative analysis, thereby putting forward effective suggestions for improving the effort levels of private investors in consortium-based PPP projects. The study results indicate that team synergy effects play an imperative role in improving the optimal effort levels under all three modes, whereas reciprocity preferences exhibit a negative relationship with effort in the DP and TP modes. When reciprocity remains within a moderate range, the DP mode achieves highest aggregate effort levels, whereas the IP mode induces positive incentive effects only under extreme reciprocity conditions. Thus, the application of dual incentive coefficients can enhance operational adaptability and allocative efficiency and governments should establish a multidimensional collaborative incentive for consortium-based PPP projects to strengthen effectiveness and project quality. This comprehensive evaluation provides crucial insights for policymakers, emphasizing the strategic selection of incentive mechanisms to enhance the sustainability and effectiveness of consortium-based PPP Projects. Full article

With the increasing complexity of grid project systems, it is difficult for an individual project management perspective to meet the macro management needs of the project, unapplicable to overall project layout management. However, the current grid project portfolio management (PPM) configuration lacks systematic methodological support, and the synergistic relationships between projects in terms of resources, strategy, and other aspects have not been effectively utilized, making it difficult to optimize the effectiveness of management and investment schemes. Therefore, in this paper, we propose a method called CNMI-PGPC, which combines complex networks and multidimensional indicators to explore the correlations among grid projects, deeply mines the key grid project clusters and the optimal allocation strategy, and is devoted to improving the comprehensive efficiency of grid projects. The methodology was validated on data derived from the Grid Multi-Category Reserve Project (including grid infrastructure, production technology improvement, and grid digitization). The results show that the proposed method can effectively provide a scientific basis for configuring and managing grid projects, support the preferential decision-making tasks of projects, and optimize the layouts of grid projects. We shift from single-project optimization to global synergy, quantify the comprehensive benefits of the project team in terms of economics, strategy, and other dimensions, bridge the gap between the previous individual project assessment perspectives, and provide a systematic decision-making basis for grid project portfolio planning. Full article

Background: While several test-automation maturity models (e.g., CMMI, TMMi, TAIM) exist, none explicitly integrate ISO 9001-based quality management systems (QMS), leaving a gap for organizations that must align E2E test automation with formal quality assurance. Objective: This study proposes a test-automation maturity model (TAMM) that bridges E2E automation capability with ISO 9001/ISO 9004 self-assessment principles, and evaluates its reliability and practical impact in industry. Methods: TAMM comprises eight maturity dimensions, 39 requirements, and 429 checklist items. Three independent assessors applied the checklist to three software teams; inter-rater reliability was ensured via consensus review (Cohen’s κ = 0.75). Short-term remediation actions based on the checklist were implemented over six months and re-assessed. Synergy with the organization’s ISO 9001 QMS was analyzed using ISO 9004 self-check scores. Results: Within 6 months of remediation, mean TAMM score rose from 2.75 → 2.85. Inter-rater reliability is filled with Cohen’s κ = 0.75. Conclusions: The proposed TAMM delivers measurable, short-term maturity gains and complements ISO 9001-based QMS without introducing conflicting processes. Practitioners can use the checklist to identify actionable gaps, prioritize remediation, and quantify progress, while researchers may extend TAMM to other domains or automate scoring via repository mining. Full article

As organizations become increasingly projectified, safeguarding the resilience of project professionals and teams emerges as a critical organizational challenge. Adopting a systems lens, we investigate how agile mindsets and agile practices function as systemic antecedents of resilience at the individual and team levels. Eleven semi-structured interviews with experienced project managers, product owners, and team members from diverse industries were analyzed through inductive thematic coding and system mapping. The findings show that mindset supplies psychological resources—self-efficacy, openness and a learning orientation—while practices such as team autonomy, iterative delivery and transparent communication provide structural routines; together they trigger five interlocking mechanisms: empowerment, fast responsiveness, holistic team dynamics, stakeholder-ecosystem engagement and continuous learning. These mechanisms reinforce one another in feedback loops that boost a project system’s adaptive capacity under volatility. The synergy of mindset and practices is especially valuable in hybrid or traditionally governed projects, where cognitive agility offsets structural rigidity. This study offers the first multi-level, systems-based explanation of agile antecedents of resilience and delivers actionable levers for executives, transformation leaders, project professionals, and HR specialists aiming to sustain talent performance in turbulent contexts. Full article

In practice, the new generation of knowledge-based employees often exhibits a “lying flat” attitude. This reflects the failure of organizational incentive mechanisms. In order to improve the incentive system and encourage employees to be proactive, the study explores and compares the synergistic effects of different rewards tools on various forms of proactive behavior in the new generation of knowledge employees. After conducting fsQCA and NCA analyses on paired data from 93 leaders and 210 employees based on the ERG theory, the findings indicate that no single reward tool is a necessary condition for triggering high proactive behavior. Instead, different reward tools need to work in synergy to produce effective motivation. Three patterns drive employees to exhibit high individual task proactivity. They are the “Dual-Drive Salary Security and Moderate Labor Dominant” pattern, the “Moderate Labor Dominant” pattern, and the “Salary Security Dominant” pattern. Two patterns drive employees to demonstrate high team member proactivity, namely the “Employee Care Dominant High-Investment” pattern and the “Pay Fairness Dominant High-Investment” pattern. Additionally, good work experience (i.e., colleague relationships) in the workplace has a significant impact on both types of proactive behavior. The research conclusions will provide insights and references for enterprise managers to design more targeted compensation incentive policies and unleash the vitality of the new generation of knowledgeable employees. Full article

Based on a sample of A-share companies listed on the Shanghai Stock Exchange and the Shenzhen Stock Exchange from 2011 to 2022, this paper measures and analyzes the degree of enterprises’ digital–green synergy and further tests the influence mechanism of fintech on enterprises’ digital–green synergistic development. It is found that fintech has a significant positive effect on enterprises’ digitization, enterprises’ greening, and their digital–green synergistic development, and the conclusion still holds after robustness and endogeneity tests. A heterogeneity analysis shows that the heterogeneity of enterprises’ size and the degree of industry emissions affects the promotional effect of fintech on the synergy. Fintech effectively promotes enterprises’ digital–green synergistic development through the three channels of green innovation, efficiency enhancement, and environmental information disclosure, and the heterogeneity of the executive team’s ages and the heterogeneity of their occupational backgrounds have a positive moderating effect on the promotional effect of fintech. The findings provide a conceptual framework and policy formulation guidelines for fintech to support the promotion of enterprises’ digital–green synergy and the improvement of new-quality productivity. Full article

Value management (VM) is a management approach aimed at inspiring individuals, nurturing their talents, and fostering synergy and innovation, all with the objective of enhancing an organization’s overall performance. This methodology seeks to reduce costs while actively engaging a diverse array of stakeholders throughout the project lifecycle. Despite its significance in construction projects, there exists a notable gap in the literature regarding the implementation of value management in public works. This study aims to identify the barriers that hinder the effective implementation of value management, as well as the critical success factors and potential risks associated with its adoption in public projects. Additionally, it assesses Turkey’s readiness for implementation within the construction sector by examining awareness levels, legislative issues, and other pertinent topics. To conduct the study, a quantitative survey was administered to 337 participants from various roles within the Turkish construction sector. The findings revealed that the inherent complexity of construction projects, time constraints, and difficulties in alternative selection are the primary barriers to implementing the value management approach in public works. Regarding the critical success factors for effective VM implementation, the involvement of end users, a collaborative workshop environment, and the multidisciplinary composition of the VM team were identified as the most significant contributors to success. Additionally, the study highlighted potential risks associated with the adoption of VM in public works, including low operating efficiency, a low participation rate in tenders, and cost overruns. The discussion also addressed legislative and process-oriented strategies for the potential adoption of value management. Full article

With increasing air traffic, the workload of air traffic controllers (ATCOs) and their limited number is again a restricting factor for the evolution of airspace management. Currently, possibilities to apply artificial intelligence for improving the support of ATCOs are widely discussed. By introducing a digital ATCO as a team partner for a human ATCO, we can expand capabilities. It can be trained to manage traffic across various airspace sectors without the limitations imposed by required licenses. This way, shortages of human ATCOs may be absorbed, and flexible assignment to sectors is facilitated with a digital ATCO partner. To be effective, the digital ATCO needs an understanding of current and future traffic situations to share the situation awareness of the human ATCO. The goal is to equip the digital ATCO with a comparable understanding—referred as a “mental model”—of the traffic situation and human actions, thereby improving decision-making and build up adequate trust with humans. In this work, decisive factors of traffic and management for the creation of digital situation awareness are identified and examined for their relevance and applicability for digital ATCOs. Within this study, a data-driven process of building up digital situation awareness including the influencing factors are suggested, and the usability of factors like the airspace complexity for indicating digital situation awareness are proposed. Finally, an example is presented and discussed to showcase our approach with focus on the integration of digital and human ATCOs through shared situation awareness. Full article