Search Results (1,975)

The top management team (TMT) plays a key role in shaping corporate strategy. However, how and when TMT faultlines influence corporate digital transformation remains unclear. Drawing on the categorization–elaboration model, this study examines the nonlinear relationship between TMT faultlines and corporate digital transformation and the moderating role of board governance. Using panel data from Chinese A-share-listed manufacturing firms, the results suggest an inverted U-shaped relationship between TMT faultlines and corporate digital transformation. Board monitoring and board networking are associated with a steeper inverted U-shaped curve, whereas board advising is associated with a flatter curve. Heterogeneity analysis shows that the inverted U-shaped relationship is mainly observed in non-state-owned enterprises, younger firms, and firms with high ownership concentration. These findings extend research on faultlines, strategic leadership, and corporate governance and offer practical implications for configuring TMTs and designing board governance mechanisms to support corporate digital transformation. Full article

Decisions made at the early stage of the design process have a substantial influence on the environmental, socio-economic, and technical performance of a building throughout its life cycle. Although an early-stage sustainability assessment is essential to achieving climate-neutral and nearly zero-energy buildings, its implementation remains challenging due to the need to integrate and evaluate large volumes of heterogeneous data originating from multiple sources and disciplines. In view of this challenge, this study presents a hybrid multi-level approach in which data fusion is combined with Building Information Modeling (BIM), web-based technologies, and multi-criteria decision-making (MCDM) methods to support the assessment of sustainable alternative design solutions for buildings. The proposed approach is implemented in the BIM4NZEB-DS web-based decision-support system and validated through a case study. In the data fusion model, BIM-derived information is combined with data from external sources within a unified environment, enabling designers to define sustainability indicators, assign relative level of importance, and evaluate design alternatives across key sustainability dimensions. Automated multi-criteria analysis enables the ranking and comparison of design solutions. The results of the case study demonstrate the capability of the proposed approach in terms of efficiently combining heterogeneous datasets and automating and facilitating systematic comparison of early-stage design alternatives. The findings indicate that a combination of BIM-based information management, web-enabled data fusion, and automated MCDM analysis enhances the transparency, consistency, and robustness of sustainability-oriented decision making. The approach described here contributes to the advancement of digital decision-support systems for sustainable building design and represents a practical tool for supporting climate-neutral building development during the most influential stages of the design process. Full article

Background/Objectives: Digital pathology is transforming diagnostic workflows through whole-slide imaging (WSI), digital archiving, artificial intelligence (AI)-assisted analysis, and remote consultation. The existing literature only partly addresses patient access to pathology records and cross-institutional sharing within a holistic governance framework. This study proposes a Self-Sovereign Identity (SSI)-based conceptual governance model that treats digital pathology archives as components of long-term clinical memory. Here, clinical memory refers to a pathology-specific information layer that preserves record context, provenance, integrity, and longitudinal links across time and institutions while supporting governed reuse and legally bounded patient-managed access. Methods: Eighty publicly available complaints from the Şikayetvar platform were examined using codebook-based thematic content analysis. Aggregated National Health Service (NHS) Written Complaints data were used to provide an illustrative external governance context. These data were not used for cross-country prevalence comparison or corroboration. Results: The main complaint themes were absent or inaccessible pathology results (66.3%) and records that remained unavailable despite notifications that the results were ready (55.0%). Complaint themes, the literature, regulatory sources, technical standards, and internal clinical review were synthesized while preserving different analytical functions, and 11 governance requirements were identified. Conclusions: Developed through Design Science Research, the model integrates verifiable credentials (VCs), a patient digital wallet, purpose- and time-limited authorization, dynamic consent and access revocation, secure off-chain storage, and blockchain-based integrity and auditing. The model was examined through an internal requirement-coverage assessment and a supplementary post hoc benchmark-oriented assessment. These analyses indicate conceptual consistency rather than independent validation. Real-world technical, clinical, usability, security, and equity validation remains necessary. Full article

Cultural heritage faces escalating pressures from mass tourism, environmental degradation, and physical decay, yet existing scholarship predominantly examines Artificial Intelligence(AI) and Virtual Reality(VR) as separate tools rather than as an integrated systemic mechanism. This exploratory study investigates how their convergence can be conceptualized as a mechanism for sustainable heritage management. A qualitative multi-case design was employed, integrating system-structural analysis, comparative case analysis, and conceptual modeling across six cases: comprising four analytical AI-VR convergence cases (Digital Dunhuang, European Time Machine, Vryokastro, and Wat Sri Suphan Ubosot) and two standalone VR reference cases (Rome Reborn and Khiva). The analysis suggests a functional division: Virtual Reality constructs the immersive spatial foundation of experience, while Artificial Intelligence orchestrates adaptive narrative delivery and semantic structuring. Their convergence may generate value across educational, preservation, and economic dimensions. A conceptual model is proposed, formalising this mechanism through four transformation processes: immersive spatialisation, adaptive storytelling, temporal structuring, and interactive co-creation, with the latter two presented as testable propositions requiring further empirical investigation. The model is linked to SDG 4 (Quality Education), SDG 11 (Sustainable Cities and Communities), and SDG 12 (Responsible Consumption and Production), and offers heritage practitioners a strategic thinking framework for considering digital approaches to cultural heritage management. Full article

Digital transformation has become essential for organizations seeking long-term sustainability, innovation, and resilience. However, empirical evidence from developing countries remains limited, particularly in oil-dependent economies where modernization and diversification are often constrained by weak institutions and governance challenges. To address this gap, this study examines the relationship between digital leadership (DL) on the innovation process (IP) in Libyan organizations, with technological readiness (TR) and organizational sustainability (OS) as mediating mechanisms. Using a quantitative research design, data were collected through a structured questionnaire from 423 employees and managers working in medium and large organizations across key sectors, including energy, banking/finance, telecommunications, and other service industries. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were used to validate the measurement model, followed by Structural Equation Modeling (SEM) to test the hypothesized relationships. The results show that DL is significantly associated with TR and OS, but does not have a significant direct association with IP. Instead, significant indirect associations between DL and IP were observed through TR and OS, suggesting that the relationship between DL and innovation is linked with technological readiness and sustainability-oriented organizational capabilities. The study contributes to the literature by showing that DL functions as an enabling strategic capability rather than merely as a managerial approach to technology adoption. Its association with IP was observed primarily through the indirect relationships involving TR and OS, suggesting that transferable digital leadership practices may support broader organizational transformation by strengthening the capabilities through which innovation is generated and implemented. Full article

Digital health commodity networks process billions of transactions annually, yet European health systems exhibit diagnostic lags of 30–180 days between anomalous events and institutional detection. Existing governance architectures are retrospective by design, and no existing framework combines pre-emptive predictive control with a principled human–AI cognitive-boundary taxonomy for this setting. This study introduces Deep Business Analytics (DBA), a pre-emptive management control system extending Simons’ four levers of control with a fifth—Predictive Feedforward Control—implemented via Long Short-Term Memory (LSTM) neural networks integrated with a Balanced Scorecard KPI layer. DBA is governed by Artificial Complementary Intelligence (ACI), a four-domain cognitive boundary taxonomy specifying where algorithmic governance is appropriate and where human clinical judgment must retain sovereignty, operationalised within a four-layer Predictive Governance Architecture (PGA). Empirical grounding draws on two deployments: a longitudinal case study at Royal Liverpool Hospital NHS Trust conducted over 28 consecutive days in 2023 (>10 million timestep records; RMSE = 0.00436) and a practitioner case study of 15 million GKV prescriptions processed in 2023 (VisionXY7; approximately 95% anomaly detection accuracy; Governance Velocity Improvement Ratio≈180:1). The ACI boundary taxonomy identifies two governance domains structurally unsuitable for autonomous AI decision-making. DBA and ACI together constitute an integrated, EU AI Act Annex III-compliant architecture that transforms health network AI governance from retrospective detection to pre-emptive control with principled human–AI boundaries. Full article

The rising number and the complexity of crises in Europe, including the COVID-19 pandemic, migration, and cybersecurity threats, have accelerated the adoption of digital transformation and artificial intelligence (AI) in public administration. This paper is a systematic literature review (SLR) of 58 academic sources examining the effect of digital transformation and AI on crisis response outcomes in European public administration. Records were identified in Scopus and Web of Science, complemented by supplementary sources, and critically appraised through a two-step procedure based on the Mixed Methods Appraisal Tool. The review integrates major themes such as the evolution of digital governance, AI-enabled decision-making, performance in crisis management, and institutional resilience. Gains in efficiency, coordination, and responsiveness are widely reported, but the appraisal shows that they rest on a thin evidential base—one quasi-experimental study, no longitudinal designs, and twenty non-empirical records—while governance, accountability, ethical, and institutional-capacity problems persist. The article reveals significant gaps in research and suggests a broad research agenda in the future with emphasis on theoretical, methodological, and policy aspects. The paper contributes to the emerging digital-era governance literature and offers recommendations for policymakers and researchers. Full article

This study takes a demand-side perspective on sustainable digital government, examining how citizens perceive and value the sustainability of public digital services. The transition to a digital and circular economy places public institutions, no less than firms, under pressure to deliver digital transformation in ways that are technologically robust, socially inclusive, and environmentally responsible; whether citizens register those efforts, as well as in what order, is an open question. Framed by the human-centric logic of Industry 5.0, this study examines how three perceived sustainability dimensions of public digital services (technological, social, and environmental) shape the value citizens derive from e-government services and how that perceived value converts into satisfaction. Using a quantitative design, we surveyed 412 Lithuanian citizens who actively use e-government platforms and tested the model through correlation, multiple regression, and mediation analysis. Perceived technological sustainability showed the strongest association with perceived value and satisfaction, followed by perceived social sustainability and then perceived environmental sustainability, whose contribution is the smallest of the three and materializes chiefly where citizens recognize tangible benefits. Each dimension was measured as a single reflective composite of three self-reported items; the attribute labels used in the separate ranking exercise are not identical to these constructs and the two sets of results should not be read interchangeably. Perceived value emerges as the critical link between perceived sustainability and citizen satisfaction, and citizens rank usability, security, and reliability as their top priorities. The findings indicate a clear hierarchy in citizens’ priorities: value is generated first where systems are perceived as reliable and secure, and only then where inclusiveness and ecological benefits are visible to users. Because all constructs are perceptual, the results describe how citizens rank the sustainability attributes of public digital services, not the fiscal returns of any particular spending decision; linking these perceptions to budgetary data remains a task for future research. Full article

In the context of educational digital transformation, automated grading of paper-based examinations faces two challenges: data privacy concerns and data heterogeneity across educational institutions. Existing Optical Mark Recognition systems are predominantly designed under centralized learning paradigms, requiring examination data to be collected and processed at a central server, which may expose sensitive student information. To address this limitation, this paper proposes a federated OMR framework for automated examination paper digitization and assessment in distributed environments. The proposed system consists of five stages, employing YOLO26 for answer-region localization, ORB-based image registration for geometric alignment, and EfficientNet-B0 for answer-state classification, automated grading, and result aggregation. Federated Averaging is utilized to train a global model across five clients representing heterogeneous data domains with different answer-sheet layouts, ink characteristics, and marking styles, without sharing raw data. Experimental results demonstrate that the federated model achieves an ROI-level accuracy of $99.42\%$ and a Macro F1-score of $95.82\%$. Furthermore, the proposed system attains a Sheet-level accuracy of $84.62\%$, outperforming local training approaches while achieving performance comparable to centralized learning. These findings suggest the feasibility of Federated Learning for developing privacy-preserving and highly generalizable OMR systems for large-scale educational assessment. Full article

Against the backdrop of sustainable education and the digital transformation of higher education, AI assistants on online learning platforms have become important tools for facilitating students’ access to learning resources, providing immediate feedback, and supporting self-directed learning, thereby creating new opportunities for more effective and sustainable learning experiences. However, the psychological mechanisms linking AI assistant intelligence to students’ innovative behavior remain unclear. Based on Social Cognitive Theory (SCT), this study examines how AI assistant intelligence on online learning platforms relates to higher education students’ innovative behavior through academic self-efficacy and academic procrastination and further explores the moderating role of AI literacy. Using a two-phase time-lagged design, the study collected data through online questionnaires from students at Chinese universities, yielding a final matched sample of 503 students. The findings show that AI assistant intelligence is positively associated with both academic self-efficacy and academic procrastination, but it has no significant direct effect on innovative behavior. Importantly, these two mediators operate in opposing directions: academic self-efficacy transmits a positive indirect effect, whereas academic procrastination transmits a negative indirect effect on innovative behavior. In addition, AI literacy strengthens the positive relationship between AI assistant intelligence and academic self-efficacy while weakening its positive relationship with academic procrastination. These findings reveal the dual psychological pathways through which AI assistant intelligence shapes students’ innovative behavior, extend Social Cognitive Theory in intelligent learning environments, and offer practical implications for leveraging AI-assisted learning to foster students’ innovative capacity and inform the sustainable integration of AI in higher education. Full article

Background: Stage II/IIIA colorectal cancer (CRC) patients have a relatively high 5-year overall survival rate after surgical resection alone, but more than 50% of patients receive adjuvant chemotherapy. This study investigates a technology that applies artificial intelligence (AI) to conventional histopathology images to identify patients at risk of recurrence. Methods: HistoNav, a novel AI deep-learning algorithm based on Vision Transformer, Graph Neural Networks and Convolutional Neural Networks was designed to analyse H&E-stained formalin-fixed paraffin-embedded (FFPE) samples (n = 2095) to stratify Stage II/IIIA CRC patients into low-, intermediate-, and high-risk groups. Results: Data analysis revealed a 5-year disease-specific survival (DSS) of 93.2%, 84.3%, and 69.3% for low-, intermediate-, and high-risk groups, respectively. The hazard ratio for the high versus low-risk group (HR = 4.611, 95% CI: 2.776–7.662; p < 0.000001) was statistically significant, demonstrating HistoNav’s potential to stratify patients based on recurrence risk. Conclusions: HistoNav can effectively identify CRC patients with good prognosis using the digital images of H&E-stained resection samples and will support clinical decisions around the use of adjuvant chemotherapy. Full article

The growing deployment of distributed renewable generation, storage, electric vehicles, heat pumps, smart buildings, and controllable demand is expanding the flexibility available to local energy systems. Energy communities provide the governance context for collective participation and value creation, while community virtual power plants provide the operational mechanism for aggregating distributed resources and connecting them to local optimisation, flexibility markets, grid services, and resilience functions. This PRISMA-ScR-informed framework development study synthesises the literature from Scopus, Web of Science, and IEEE Xplore to examine how artificial intelligence supports community VPP operation, where agentic AI adds capabilities beyond established optimisation, reinforcement learning, and multi-agent systems, and which design requirements follow governed orchestration. The synthesis shows that current evidence is strongest for component-level forecasting, scheduling, bidding, adaptive control, distributed coordination, and digital-twin validation, whereas integrated agentic orchestration remains an emerging direction. Classical multi-agent systems already provide decentralised representation, communication, negotiation, and coordinated control; the additional role proposed for agentic AI is therefore narrower and concerns context-aware multi-step workflow orchestration, governed tool use, exception handling, grounded explanation, and bounded delegation across existing analytical and control services. The study introduces operational flexibility intelligence as the capability to transform potential distributed flexibility into deployable, authorised, market-, grid-, resilience-, and community-compatible action. It further develops a conceptual layered reference architecture in which agentic orchestration operates through governed tools and interfaces rather than bypassing validated resource controllers. Fairness, comfort, privacy, cybersecurity, resilience, auditability, and human-in-command authority are treated as cross-cutting operational constraints. The architecture defines a design and validation agenda rather than an empirically validated implementation. Full article

Technological advancements have transformed the ways in which individuals interact with digital platforms, giving rise to data-driven ecosystems in which interface design plays a central role. Within these environments, dark patterns and manipulative and deceptive design techniques shape user behaviour in ways that undermine privacy, autonomy, and informed consent. This paper develops a harm-based analytical framework for privacy dark patterns by deriving a typology of privacy-relevant design mechanisms through a structured consolidation of four independently produced taxonomies. It then constructs a harm typology by combining an injury-based framework with the harm categories developed by regulatory authorities and maps each design mechanism to the harms it is structurally apt to produce. Finally, it identifies the provisions of EU law that each mechanism engages, across the GDPR, consumer protection law, the Digital Services Act, the Digital Markets Act, the Data Act and the AI Act. The analysis finds that the GDPR engages every mechanism identified, that coverage by post-GDPR instruments is uneven, and that one mechanism—the exploitation of relational and third-party data—engages no post-GDPR instrument squarely. The deficiency in the EU framework therefore lies not in the substance of its prohibitions but in the coordination of enforcement and in the evidentiary architecture through which non-material harm must be established. Full article

Against the backdrop of the synergistic development of digitalization and green transformation, supply chain digitalization (SCD) plays a significant role in supporting companies’ green development; however, it remains unclear how it affects greenwashing. This study uses supply chain innovation and application pilots as a quasi-experimental design and employs panel data from Chinese A-share listed companies (2009–2024) and the difference-in-differences (DID) method to conduct theoretical analysis and empirical testing. The results indicate that SCD significantly curbs corporate greenwashing; this conclusion holds even after robustness tests such as parallel trends tests, propensity score matching, and placebo tests. Mechanism analysis indicates that SCD curbs corporate greenwashing through two channels: (1) enhancing corporate green technological innovation capability and (2) alleviating information asymmetry. Heterogeneity analysis indicates that SCD’s inhibitory effect on corporate greenwashing is more pronounced among firms with higher debt financing costs, greater institutional investor ownership, and greater media coverage. From the perspective of SCD, this study offers insights for promoting corporate green transitions and enhancing ESG transparency, while providing practical guidance for government regulators to combat greenwashing. Full article

The rapid advancement of digital technologies has reshaped tourism practices worldwide, positioning smart tourism as a key approach for enhancing user experience. Previous studies have either focused on conceptual discussions of smart tourism principles or examined isolated technological applications; limited research has systematically linked theoretical experiential dimensions with the actual tools and systems implemented in heritage contexts. In response to this gap, a structured review of Scopus-indexed studies published between 2015 and the present was conducted to examine smart tourism applications in historical urban areas, identifying the evolution of the term smart tourism, recurring trends, technological interventions, and operational strategies applied in historical urban destinations. Using an inductive comparative qualitative approach, a selected sample of archival studies was analyzed, classifying studies into two distinct yet potentially complementary research families: a philosophical stream and a practical implementation stream. The selected studies are analyzed through a dual lens: (1) Theoretical dimensions and themes discussed in conceptual literature, and (2) Practical tools and techniques applied in empirical case studies. The core contribution of this research is the critical perspective of these efforts and the bridging of these two domains through the Integrated Smart Tourism Transformation Framework (ISTTF). The findings contribute to both theory and practice by offering a framework for policymakers, designers, and heritage managers seeking to implement smart tourism solutions that enhance user experience while preserving cultural integrity. Full article