Search Results (491)

Construction projects are increasingly complex, fragmented, and data-intensive, making cross-organizational collaboration routine while leaving teams “information-rich but knowledge-poor”; that is, large volumes of drawings, BIM models, meeting records, site reports, and sensor data are produced, but they are not always transformed into reusable, context-sensitive knowledge for future decisions. To consolidate dispersed evidence and capture the shift from digital to intelligent knowledge sharing (KS), this study conducts a PRISMA-guided systematic literature review of KS in construction project management from 2015 to 2025. Through quantitative and qualitative analyses of 163 core articles, this paper identifies five central themes: organizational and behavioral mechanisms, performance–innovation–sustainable value, digital technology empowerment, knowledge mechanisms and organizational learning, and risk–supply chain–governance and security. The study also synthesizes key challenges in knowledge sharing and outlines future research directions. These findings provide guidance for researchers, practitioners, and policymakers seeking efficient, credible, and sustainable systems to enhance project management effectiveness. Full article

Background/Objective: Research has indicated that providing care during the COVID-19 pandemic negatively impacted healthcare providers’ wellbeing and burnout. Much of the literature has focused on emergency department (ED) physicians and nurses, including the distinct challenges they faced caring for persons experiencing homelessness (PEH), including addressing unmet basic needs, limited discharge options, and disruptions to community-based health and social services during the pandemic. Comparatively little research has examined the experiences of other multidisciplinary team members caring for PEH. This study explored the shared experiences of multidisciplinary ED staff caring for PEH during the COVID-19 pandemic to inform workforce planning and future pandemic preparedness. Methods: Using inductive qualitative analysis, we examined self-reported experience, mental health impacts and solutions for workforce planning and pandemic preparedness of multidisciplinary ED staff caring for PEH. Three virtual focus group discussions involving 12 multidisciplinary ED staff (registered nurses, clerical staff, security staff, community support workers, and a clinical assistant) were conducted during the first two years of the COVID-19 pandemic, a period characterized by evolving public health restrictions, uncertainty, and disruptions to health and social services. Results: Inductive qualitative analysis identified four key themes: (1) emotional experiences of care provision (including gratitude, compassion fatigue, and moral distress), (2) hospital- and community-led adaptations to support care delivery, (3) strategies for wellness and resilience building among staff, and (4) recommendations for future workforce planning and pandemic preparedness. Conclusions: Caring for PEH during the intense pandemic period intensified staff distress by exposing them to unmet social needs and system-level resource gaps, while also fostering interprofessional collaboration and resilience. Staff collaborated to facilitate organizational adaptations that enabled continuity-of-care. Future pandemic preparedness should include targeted mental health supports for staff, flexible institutional contingency planning, and formalized hospital–community partnerships to sustain care for PEH and other socially vulnerable populations. Full article

Conventional hazard and operability (HAZOP) studies remain central to process safety management, but their periodic, document-centered implementation and dependence on expert judgment limit their ability to track dynamic operational risk across the full plant lifecycle. This critical literature review, drawing on 113 sources, examines how digital twin (DT) and artificial intelligence (AI) technologies may augment HAZOP practice, advancing an augmentation principle: DT–AI should strengthen expert-led hazard analysis as a decision-support layer, not replace human judgment. The review maps conventional HAZOP limitations to four complementary technology pathways: AI-assisted knowledge capture and deviation reasoning; DT-based hazard monitoring and early warning; hybrid physics–data modeling for predictive safety; and explainable AI for operator trust and regulatory acceptance. Four representative industrial case studies illustrate current practice, and a structured barrier analysis identifies why many pilots stall before reaching sustained deployment. These pathways offer strong potential to improve HAZOP coverage, traceability, operational relevance, and lifecycle learning, but a study-level evidence assessment finds that no reviewed study demonstrates long-term, multi-site validation of an integrated DT–AI–HAZOP system; most implementations remain at conceptual, prototype, or limited pilot levels. Key failure modes, including model drift, sensor faults, large language model hallucination, and automation complacency, are examined alongside a thirteen-item implementation risk register spanning technical, organizational, economic, security, and scalability concerns. The review proposes a phased industrial implementation roadmap, a lifecycle-oriented safety-management framework, and a three-horizon research agenda for advancing toward reliable, validated HAZOP-informed digital twin systems. Full article

Collaborative cyber threat intelligence sharing is becoming a crucial part of contemporary security practices but is still limited by privacy risks and the need to retain confidence within and between organizations due to the heterogeneous nature of the information. NeuralFortress-XFL attempts to alleviate these issues by using a federated and explainable learning architecture that is capable of detecting threats with high fidelity, without revealing raw data or model explanations. The structure incorporates a Dynamic Privacy-Efficient Mechanism (DPEM), which dynamically adapts differential privacy budgets based on local data sensitivity and a lightweight explanation-embedding component that preserves both interpretability and privacy. An experiment conducted using CTI-Sharing-2024 dataset, which contains 15 organizations consisting of financial and healthcare industries, indicates that NeuralFortress-XFL provides the same level of detection as the centralized training accommodations, with significantly lower communication overhead. NeuralFortress-XFL maintains robust performance against up to 40% independent malicious participants (87.4% accuracy with label flipping, 84.3% backdoor detection rate). Against coordinated collusion, robustness degrades proportionally with coalition size: coalitions of five or more clients (33% of 15 organizations) achieve 67.3% attack success, a limitation that is explicitly addressed in the paper, and a trust-weighted aggregation process maintains global model consistency despite adversarial client updates. The framework is also able to offer consistent and sound explanations, which can support real-world analyst workflows. As a whole, NeuralFortress-XFL is a solid security solution for sharing privacy-sensitive cyber threat intelligence in a deployable and balanced way that satisfies all of the following criteria: it is accurate, it is interpretable, it communicates well, and it exhibits adversarial resilience in a multi-organizational real-world setting. Full article

The increasing integration of artificial intelligence (AI) into organizational processes has accelerated the adoption of algorithmic management, reshaping work structures across labor-intensive service organizations. However, empirical evidence remains limited regarding the simultaneous control-oriented and developmental dimensions of AI-enabled management systems. This study examines how algorithmic control and AI-supported skill development influence perceived autonomy and career security among employees in hospitality organizations. Data were collected from 441 employees working in hotel organizations in Bavaria, Germany. The data were analyzed using exploratory factor analysis (EFA), confirmatory factor analysis (CFA), structural equation modeling (SEM), bootstrapped mediation analysis, and hierarchical regression. The results suggest that control-oriented and developmental dimensions of AI are associated with different aspects of employees’ work experiences. Algorithmic control was negatively associated with perceived autonomy, whereas AI-supported skill development was positively associated with both perceived autonomy and career security. Perceived autonomy did not mediate the relationships between AI-related workplace conditions and career security, and digital literacy did not moderate the relationship between algorithmic control and perceived autonomy. The study contributes to research on algorithmic management and AI-enabled workplaces by highlighting the importance of analytically distinguishing between the control-oriented and developmental dimensions of AI when examining the organizational implications of AI-enabled management. Full article

Background: Awake craniotomy is well established in adult neurosurgery for lesions near eloquent cortical areas, but its use in children remains uncommon and presents substantial anesthetic, psychological, and organizational challenges. We report the anesthesiologic management of awake craniotomy in a child with constitutional mismatch repair deficiency (CMMRD). Case Presentation: A 10-year-old boy with CMMRD underwent resection of a recurrent left frontal IDH-mutant astrocytoma, WHO grade 3, located adjacent to eloquent language cortex. Because of the high risk of postoperative language impairment, a structured multidisciplinary pathway was implemented, including neurosurgical, neuropsychological, and anesthesiologic evaluation, preoperative familiarization, and intraoperative language testing. An asleep–awake–asleep strategy was used. After induction with propofol, fentanyl, and rocuronium, the airway was secured with a supraglottic airway device (air-Q) followed by fiberoptic-guided tracheal intubation. During the awake phase, propofol was discontinued, remifentanil reduced, and low-dose dexmedetomidine introduced to preserve cooperation. The patient completed intraoperative language mapping, enabling identification of functional language boundaries and safe resection. No major intraoperative adverse events, airway complications, or seizures occurred. Postoperative pain scores remained below 4 on an age-appropriate Numeric Rating Scale, and the patient showed no new neurological deficits. At 1-month follow-up he remained symptom-free. Conclusions: This case adds to the still limited pediatric experience with awake craniotomy and suggests that, in carefully selected children managed within a structured multidisciplinary perioperative pathway and with a tailored anesthetic strategy, the procedure can be performed safely; confirmation in larger series is nonetheless required. Full article

Large language models (LLMs) are increasingly discussed in digital government research, but existing studies remain fragmented across application opportunities, technical performance, and governance risks, with limited synthesis of how they support service provision within digital government service processes. Using the concept of interpretive support, this study examines: (1) what forms of interpretive support LLMs provide; (2) what task- and service-level effects are reported; and (3) what governance conditions shape responsible integration. Drawing on a socio-technical systems perspective, the study conducts a PRISMA-informed systematic review and thematic synthesis of 60 studies from the Web of Science Core Collection and Scopus. The findings show a shift from stand-alone question answering to broader forms of interpretive support, including rule explanation, service navigation, complaint interpretation, issue routing, and back-office knowledge structuring. The strongest evidence concerns efficiency, responsiveness, and accessibility, whereas claims about trust, accountability, and wider public value remain less well supported. The review concludes that public value is conditional rather than automatic, depending on reliability, legal boundaries, responsibility allocation, data security and privacy, and organizational capacity. Future research should examine whether these service-level gains persist in routine service environments and how governance mechanisms affect service quality, equity, and accountability. Full article

Inter-organizational construction projects depend on intensive information exchange, interface coordination, and joint action among multiple organizations. However, their temporary, fragmented, and multi-actor nature often creates information asymmetry, unclear responsibility attribution, and weak trust foundations, thereby increasing collaboration costs and reducing governance efficiency. Although blockchain technology is often considered capable of addressing these problems through tamper-resistant records, transparent sharing, and smart contract execution, existing studies remain largely focused on technical functions or application scenarios. Less attention has been paid to how blockchain influences trust formation and inter-organizational collaboration through informational governance mechanisms. To address this gap, this study adopts a conceptual theory-building research design and develops a governance-oriented framework explaining how blockchain-enabled informational attributes affect trust and collaboration in construction projects. The study conceptualizes the blockchain’s governance role as an informational governance mechanism rather than a mere technical deployment, focusing on four informational attributes embedded in project transaction records: security, fidelity/authenticity, transparency, and procedural consistency. It further distinguishes interpersonal trust from inter-organizational trust, arguing that blockchain informational attributes may shape both interaction-based trust among boundary spanners and organization-level collaboration expectations. Interpersonal trust may also inform broader trust judgments toward partner organizations. At the collaboration level, the study conceptualizes inter-organizational collaboration as a process structure consisting of coordination and cooperation, with coordination creating conditions for deeper cooperation. The resulting framework links blockchain informational attributes, dual-level trust, coordination, and cooperation, and develops hypotheses for future empirical testing. This study contributes by shifting construction blockchain research from technology adoption and functional description toward informational governance explanation, extending dual-level trust logic into blockchain-enabled construction project governance, and applying the coordination–cooperation process logic to unpack how blockchain-enabled informational governance may influence inter-organizational collaboration. Full article

Public sector organizations are under increasing pressure to modernize service delivery while preserving transparency, interoperability, accountability, and citizen trust. Blockchain technology offers relevant capabilities for these objectives, particularly through shared ledgers, cryptographic verification, and programmable rules. However, its adoption in public sector contexts remains constrained by the lack of architectural guidance tailored to inter-organizational services. This study proposes BRA-PS, a Blockchain Reference Architecture for Public Sector Citizen-Centric Applications, developed from a real-world digitalization project in Quebec, Canada. The architecture organizes components into six layers (presentation, business, communication, smart contract, blockchain, and data) with cross-cutting concerns addressing governance, access control, security, and monitoring. A key design principle is the public–private workflow separation, which enables inter-organizational collaboration while preserving each organization’s operational autonomy and data confidentiality. We validated the architecture through a case study involving a vehicle registration process between two public agencies, supported by a proof-of-concept implementation using Hyperledger Fabric. An Architecture Trade-off Analysis Method (ATAM) evaluation, conducted with a panel of five domain experts, identified six architectural risks, including InterPlanetary File System (IPFS) confidentiality exposure and smart contract inflexibility, six non-risks, six sensitivity points, and six trade-offs across three key quality attributes: autonomy, collaboration, and functional suitability. The results show that BRA-PS can support implementation decisions, clarify stakeholder responsibilities, and expose relevant architectural trade-offs. The recommendations derived from the evaluation provide practical guidance for the adoption of blockchain in citizen-centric public sector services. Full article

The behavior of employees in the hospitality industry has gained strategic significance as it has become a competitive service industry where the level of customer satisfaction is highly dependent on the discretionary contributions made by employees. This study examined whether Employee Engagement mediates the relationship between Transactional Leadership and Organizational Citizenship Behavior and whether the Perceived Organizational Support moderates the relationship of Transactional Leadership and Employee Engagement among the employees working in a fine dining restaurant in Beirut, Lebanon. The study based its moderation mediation analysis on two theoretical frameworks—Social Exchange Theory and Organizational Support Theory. The study employed a quantitative, cross-sectional design and distributed 500 electronic questionnaires via Google Forms to staff working in upscale hospitality and fine dining restaurants after securing managerial approval. A total of 441 questionnaires were received. Following data screening procedures, 428 valid questionnaires were retained for analysis. The analysis was performed using the following applications: AMOS 24, SPSS 27, and the PROCESS Macro 4.2 through 5000 bootstrap resamples. Results showed that Transactional Leadership was positively associated with OCB. Employee Engagement significantly mediated the relationship between Transactional Leadership and Organizational Citizenship Behavior. POS was found to strengthen the relationship between Transactional Leadership and Employee Engagement, and the conditional indirect effect of Transactional Leadership on Organizational Citizenship Behavior through Employee Engagement was stronger when POS was high. Originality/value: This study addresses an important gap in the conditional process leadership literature by combining the concepts of Transactional Leadership, Employee Engagement, POS, and Organizational Citizenship Behavior into one empirical model tested in a hospitality setting plagued by a crisis. The results provide viable solutions for hospitality managers interested in developing improved Employee Engagement, discretionary behavior, and service quality in an operationally constrained environment. Full article

Against the backdrop of geopolitical restructuring and rapid digital transformation, foreign investment security reviews in host countries have become an increasingly important institutional constraint on cross-border business activities. From a broader organizational perspective, such regulatory mechanisms shape the external environment in which emerging market multinational enterprises (EMNEs) make international investment decisions and conduct cross-border acquisitions. This paper explores the moderating effects of EMNE network and internal agency problems on the duration of reverse cross-border M&A (CBMA) under host country security reviews. Utilizing a Negative Binomial regression model, we empirically analyze 503 reverse CBMAs undertaken by Chinese firms in developed economies from 2003 to 2022. The findings reveal that host country security reviews significantly prolong M&A duration. Notably, business group affiliation weakens this positive relationship, whereas political networking strengthens it. Regarding internal governance factors, Type I agency problems reinforce the delaying effect of foreign investment security reviews, while Type II agency problems weaken it. This study provides practical implications for managers and policymakers seeking to improve firms’ responses to increasingly complex regulatory environments. Full article

The security of new energy vehicle (NEV) industry chains has become a strategic issue for industrial competitiveness, the energy transition, and economic security. This study examines how digital economy capabilities jointly support NEV industry chain security across 30 provincial-level administrative regions in China. Drawing on Organizational Information Processing Theory and Dynamic Capability Theory, we conceptualize artificial intelligence capability (AIC), big data analytics capability (BDA), cloud computing infrastructure (CCI), and blockchain application level (BCL) as complementary information-processing and reconfiguration capabilities. We combine Necessary Condition Analysis (NCA), fuzzy-set Qualitative Comparative Analysis (fsQCA), and Random Forest/SHAP analysis. The revised results show that AIC is a practically necessary condition for supply chain resilience, BDA is a necessary condition for achieving a high cybersecurity level, and BCL is a dimension-specific necessary condition for data security. Four sufficient configurational paths—technology-driven, data-driven, infrastructure-driven, and security-synergistic—lead to high comprehensive NEV industry chain security. Robustness checks using alternative calibration anchors and consistency thresholds show that the core configurations are stable. A revised machine learning specification using only digital economy predictors confirms the high relative importance of AIC. It also shows that the marginal contribution of AIC tends to flatten beyond the upper-middle range. The findings provide a configurational and regionally differentiated perspective on digital economy empowerment while avoiding overgeneralization beyond the Chinese provincial context. Full article

This paper proposes, implements and tests a resilient and decentralized system based on blockchain and quantum-secure communication for cyber, scientific, and strategic diplomacy. By introducing a dynamic post-quantum cryptographic binding layer, the proposed architecture significantly amplifies organizational resilience against sovereign-state data disruption and harvesting attempts within highly adversarial environments. The system guarantees end-to-end transparency and confidentiality in the sharing of resources, and it can be used in resilient organizations and for cyber, scientific, and strategic diplomacy. It integrates the following technologies and modules: blockchain technology with a semantic distribution of quantum keys, a frontend interface built exclusively with React, a backend module implemented in Python Flask 3.1.2 and served via Gunicorn 25.0.3, and a set of modular components dedicated to blockchain, quantum simulation, and distributed storage. Moving past theoretical bounds, this work presents structural Threat Models, real-world deployment parameters for Eastern European research infrastructures, and multi-variable empirical performance evaluations under authentic institutional workloads. Moreover, the proposed architecture offers an extensible foundation for the development of future resilient ecosystems supported by blockchain and quantum technologies. Full article

Background/Objectives: Health systems across Europe are increasingly challenged by population ageing, multimorbidity, and persistent inequities in access to care. Community Nursing has emerged as a promising approach to strengthening preventive, community-based services, yet evidence on stakeholder-perceived needs during early implementation remains limited. This study aimed to explore how different types of needs are perceived and articulated during the early implementation of Community Nursing in Austria. Methods: An interpretive descriptive qualitative study was conducted as part of an Austrian Community Nursing pilot project. Semi-structured interviews were carried out with eleven stakeholders, including informal caregivers, network partners (e.g., local healthcare providers), and local political decision-makers. Data were analyzed using qualitative content analysis, guided deductively by Bradshaw’s Taxonomy of Needs and complemented by inductive sub-category development. Interviews were conducted via telephone or video call (Zoom) and ranged from approximately 30 min to an hour. Results: Normative needs reflected expectations for preventive services, continuity of care, advocacy, and sustainable organizational structures. Felt needs centered on trust, emotional security, and relational continuity. Expressed needs became visible through active use of Community Nursing services, including preventive programs, transitional care support, and administrative navigation. Comparative needs highlighted geographic inequities and differences between municipalities with and without access to Community Nursing. Across stakeholder groups, concerns regarding long-term financing and sustainability were prominent. Conclusions: The findings suggest that Community Nursing addresses multiple stakeholder-perceived needs simultaneously, particularly by providing relational, accessible, and preventive support. However, sustained impact depends on stable funding and systemic integration beyond pilot phases. These results offer transferable insights for the development and scaling of community-based nursing models in ageing societies. Full article

The rapid digitalization of transportation systems has expanded the cyberattack surface of critical infrastructure while exposing significant shortages in transportation-specific cybersecurity workforce capacity. Existing workforce studies rarely integrate transportation-sector workforce development, organizational preparedness, operational technology (OT) challenges, and interdisciplinary collaboration within a unified analytical framework. In response to this gap, this study employs a mixed-methods approach that integrates Term Frequency–Inverse Document Frequency (TF-IDF) text analysis of publicly available workforce development documents, qualitative interviews with academics, policymakers, and transportation cybersecurity professionals, and organizational survey analysis to examine workforce development challenges across transportation subsectors. The findings reveal persistent information technology (IT) and operational technology (OT) competency gaps, curriculum–industry misalignment, organizational staffing shortages, disparities in cybersecurity preparedness, and the critical importance of experiential learning and dedicated cybersecurity staffing. The study further emphasizes the need for interdisciplinary education, organizational capacity building, and sustained collaboration among academia, government, and industry to strengthen the transportation cybersecurity workforce’s readiness and resilience. Collectively, the findings position transportation cybersecurity workforce development as a systems-coordination challenge that requires long-term strategic investment, cross-sector collaboration, and workforce innovation to enhance the security, resilience, and operational continuity of transportation systems. Full article