Search Results (469)

While deepening regional connectivity, the Belt and Road Initiative (BRI) poses formidable challenges to conservation of biodiversity in ecologically sensitive areas along its routes. It makes stronger international cooperation on biodiversity conservation imperative for participating countries. However, the existing literature predominantly focuses on single-country institutional analyses or project-level ecological impact assessments, leaving a gap in the integrated governance framework that bridges “internal institutional supply” and “external international cooperation”. The study finds that recent practices along BRI routes show concentrated progress in several key areas: refining targeted legislation in key sectors, integrating local ecosystem characteristics into conservation approaches, and safeguarding the rights and interests of local communities through diverse channels. By systematically classifying the practices of six representative case studies—including the Mombasa–Nairobi Railway and the Karot Hydropower Plant—the evolving trends for biodiversity conservation under the BRI have been revealed: diversification of conservation subjects and digitalization of conservation methods. To balance the supply and demand of the system, the institutional innovation of China’s biodiversity conservation could be realized through dual-dimensional optimization (internal institutional design + external international cooperation). The specific proposals are as follows: (1) Strengthening domestic institutional rigidity: At the top-level design stage, this entails advancing sui generis legislation for biodiversity conservation, encouraging joint rulemaking by local governments and line ministries, and leveraging the supplementary and constraining effects of treaty-based and contractual standards. At the implementation stage, introducing the community co-management model requires improving public participation mechanisms, such as diversified communication channels. (2) Activating the flexibility of international cooperation, establishing BRI Ecological Cloud digital platforms for data sharing and dynamic monitoring, and joint conservation efforts should be conducted through cross-border projects with BRI partner countries, harnessing project resources to achieve mutual benefits in global biodiversity governance to promote the transnational legal process of biodiversity conservation and global ecological civilization construction. Full article

Digital transformation is now one of the key engines of entrepreneurial behavior and company development, but there is still a lack of empirical evidence on the creation of digital ecosystems, especially in the Middle East and North African (MENA) region. This paper examines how digital capabilities affect the sustainable development of entrepreneurial ventures and how the relationship changes depending on the three emerging digital ecosystems of Lebanon, Iraq, and Egypt. Data were collected through a structured online questionnaire developed using Google Forms and distributed via email, WhatsApp, and the Prolific research platform to owners, managers, and key decision-makers of small and medium-sized enterprises (SMEs). A total of 250 questionnaires were distributed, yielding 131 responses, of which 22 were excluded after screening for completeness and eligibility. The final analytical sample comprised 109 valid firm-level responses from Egypt (n = 51), Lebanon (n = 34), and Iraq (n = 24). The study quantitatively assesses digital capabilities on several dimensions, including digital infrastructure adoption, data and analytics capabilities, digital product development, and digital revenue integration, and attributes those capabilities to sustainable business growth indicators (the revenue stability, scalability, profitability, and long-term resilience). The results showed that more robust digital capabilities have more significant impacts on sustainable business growth outcomes, whereas basic digitalization has no significant effect. Further, the analysis found no statistically significant moderating effect of ecosystem contextual factors, including institutional quality and digital maturity, on the relationship between digital capabilities and sustainable business growth across Lebanon, Iraq, and Egypt. This study contributes to the body of knowledge of entrepreneurship and sustainability in emerging markets by integrating Resource-Based View, Dynamic Capabilities Theory, and Digital Ecosystem Theory. The findings have practical implications for entrepreneurs and policymakers who aim to use digital transformation to attain sustainable entrepreneurship in the vulnerable and dynamic digital ecosystems. Full article

Digital innovation platform ecosystems can scale rapidly without becoming durable because broad participation does not ensure sustained value circulation. Existing models homogenize complementors, obscuring horizontal coopetition among distinct groups and its interaction with vertical governance. We examine how vertical and horizontal relations shape value-flow architecture and sustainability. Drawing on ecological symbiosis theory, we distinguish a platform orchestrator, technology-extending complementors, and service-integrating complementors. We construct an extended three-actor Lotka–Volterra model and use the Global Value-Flow Symmetry (GV) index and the continuous directional indicator ${\delta }_c$ to assess symmetry and direction. Designed for theory building rather than empirical calibration or testing, the analysis uses no empirical data and compares 35 vertical–horizontal configurations through deterministic simulation and sensitivity analysis. Results show the following: (1) Greater symmetry is associated with higher aggregate maintained output, but vertical backflow direction shapes its distribution; $\mathrm{G}\mathrm{V}$ must therefore be interpreted with ${\delta }_c$. (2) Under complementor-favoring vertical parasitism, horizontal mutualism expands complementor output but intensifies negative vertical backflow, simultaneously increasing aggregate output and reducing platform equilibrium—a cooperation paradox. (3) The same horizontal mutualism yields three focal outcomes across the examined vertical structures: Negative complementor-to-platform effects produce the cooperation paradox, absent effects produce value decoupling, and mutually positive vertical exchange produces systemic resonance. Thus, horizontal cooperation does not necessarily enhance sustainability; its effect depends on whether complementor gains feed back to support platform capability. This study advances platform-ecosystem sustainability research and offers theoretical guidance for optimizing value backflow and cooperative governance. Full article

Thai Buddhist funeral services constitute a substantial multi-actor service ecosystem that remains largely dependent on conventional, fragmented coordination among bereaved families, temples, service providers, and administrative actors, with limited digital integration. This study reports a pre-deployment acceptance evaluation of a conceptually specified GenAI-assisted funeral-coordination service and proposes an Evidence-to-Design Translation Framework (EDTF) for translating acceptance evidence into initial design and governance requirements. Using non-probability convenience sampling through online recruitment, 342 screened adults with prior funeral-arrangement experience in the Bangkok Metropolitan Area evaluated a standardized vignette and representative interface mockups rather than an operational platform. PLS-SEM was used to examine prospective acceptance under five predefined safeguards: traceability, auditability, contestability and redress, verification, and risk-based human review. Perceived usefulness was the strongest predictor of intention to use, while attitude toward use provided a secondary pathway. The EDTF maps empirically supported user-evaluation signals to candidate workflow features, accountability controls, required records, monitoring indicators, and escalation rules. The findings provide bounded pre-deployment evidence for subsequent prototyping and pilot validation; they do not demonstrate actual adoption, live-system effectiveness, safeguard causality, or realized industry transformation. Full article

The rapid integration of digital technologies including cloud infrastructures, Internet of Things ecosystems, artificial intelligence, and large-scale enterprise platforms has reshaped the operational and architectural foundations of contemporary organizations. Although these technologies enhance flexibility, scalability, and analytics-driven decision processes, they simultaneously increase system complexity, broaden attack surfaces, and intensify governance requirements. This manuscript adopts an engineering-oriented viewpoint on digital governance and enterprise cybersecurity, focusing on secure system architectures, policy-driven control mechanisms, and resilience-focused operational strategies. An integrated framework that unifies governance structures, quantitative risk assessment, compliance automation, cybersecurity engineering is introduced to enable secure-sustainable digital transformation across enterprise environments. Full article

Background: Cholangiocarcinoma (CCA) is a highly heterogeneous malignancy with limited therapeutic options and poor prognosis. The increasing complexity of molecular stratification and treatment selection has stimulated interest in computational and biological modeling approaches for precision oncology. Objective. This narrative review aims to provide a comprehensive overview of digital twins (DTs), DT-enabling computational models, and biological twins (BTs) in CCA, discussing their applications, limitations, and potential integration within hybrid precision medicine frameworks. Methods: A narrative literature review was conducted. To inform the twin-focused sections, a structured PubMed search was performed using predefined keywords related to CCA and twin-related technologies, including organoids, xenografts, organ-on-chip systems. Particular attention was devoted to recent studies addressing computational modeling, patient-derived experimental systems, and translational applications. Results: DT development in CCA is supported by an ecosystem of DT-enabling technologies, including radiomics, artificial intelligence, multi-omics integration, and simulation-based models. However, fully realized medical DTs remain unavailable. BTs, including patient-derived organoids, xenografts, and microfluidic platforms, enable functional validation of therapeutic hypotheses but face challenges related to scalability, standardization, and clinical feasibility. Emerging hybrid DT-BT frameworks seek to combine computational prediction with biological validation through iterative feedback loops, potentially improving patient stratification and treatment personalization. Conclusions: DTs and BTs represent complementary components of an evolving precision oncology ecosystem in CCA. Although technical, biological, regulatory, and implementation challenges remain, the convergence of computational models, longitudinal molecular monitoring, and patient-derived systems may facilitate clinically actionable hybrid twin frameworks. Successful translation will require both technological innovation and healthcare-system improvements to precision medicine access. Full article

Digital technologies have significantly advanced documentation, management, and dissemination of Cultural Heritage (CH) through reality capture, Heritage Building Information Modelling (HBIM), and Extended Reality (XR). However, the digitisation of large and historically stratified heritage sites still relies on fragmented workflows that compromise interoperability and interrupt the continuity of geometric and semantic information throughout the heritage lifecycle. This paper proposes and validates a platform-independent, ecosystem-based methodology integrating multi-scale reality capture, hybrid Scan-to-HBIM modelling, semantic information management, interoperability, and XR within a continuous digital workflow. The methodology was validated through the large-scale digitisation of the Certosa di Pavia, where more than 1500 terrestrial laser scans, over 200,000 photographs, and approximately 50 billion points were acquired across a monumental complex covering nearly 331,000 m². The proposed framework reconstructs irregular architectural geometries with millimetre-scale accuracy (σ = 0.005 m) while preserving geometric reliability, semantic consistency, and information traceability across point-cloud processing, HBIM environments, Common Data Environments (CDEs), and XR applications. The results demonstrate that the effective digitisation of complex CH depends not only on the accuracy of individual technologies but also on their coordinated integration within interoperable digital ecosystems. The proposed methodology provides a transferable framework for preserving knowledge continuity throughout the heritage lifecycle, enabling HBIM to evolve from a geometric representation into a dynamic knowledge environment supporting conservation, management, research, education, and public dissemination. Full article

Digital wellness policies in universities often rely on uniform daily screen time caps, yet platform-specific risks may shape student outcomes as strongly as total time online. This paper presents a methodological proof of concept: it demonstrates an analytical pipeline that converts multi-platform outcome data into a graduated, affordance-informed policy typology, rather than offering validated platform-risk classifications or ready-to-implement policy. Using a publicly available student dataset covering twelve social networks, we aggregate four harm-aligned outcomes—addictive use, poorer mental health, shorter sleep duration, and interpersonal conflict—to the platform level and apply hierarchical clustering to derive a four-tier risk typology. We stress that the clustering and the subsequent principal component analysis operate on only twelve platform-level observations, not on the 705 individual students. We then project the tiers onto a two-dimensional risk map and simulate three illustrative policy regimes: a uniform daily cap, a tier-calibrated cap, and an affordance-targeted short-video cap. In this illustrative dataset, the tier-calibrated cap reproduces roughly seventy percent of the harm reduction in a blanket cap while directly affecting about three-quarters of students, and the three regimes deliver near-equivalent harm reduction per percent of students affected. Because the source data show characteristics consistent with synthetic or semi-synthetic simulation and lack established provenance, all quantitative results are presented as demonstrations of the pipeline. We describe the sensitivity of the typology to clustering choices, the ethical risks of tiered classification, and the replication required before any tier could inform practice. Full article

The rapid digital transformation of education has increased the demand for intelligent assessment systems and architecture capable of evaluating institutional readiness for technology-enhanced teaching, learning, and workforce development. As educational organizations adopt digital platforms, cloud-based learning environments, and globally connected instructional models, there is a growing need for systematic frameworks that can assess human, technological, and organizational capabilities required for successful implementation. This study proposes a digital capability assessment framework for technology-enhanced educational systems that integrates instructional competency evaluation, technology readiness analysis, infrastructure assessment, and institutional support monitoring within a unified analytics-driven model. The proposed framework consists of multiple assessment components, including digital literacy measurement, technology integration capability analysis, instructional innovation indicators, collaborative learning readiness metrics, and institutional resource evaluation mechanisms. These components are designed to support continuous monitoring of digital transformation initiatives and provide evidence-based decision support for educational planning, resource allocation, and technology adoption strategies. The framework further incorporates analytics and reporting functions that enable stakeholders to identify capability gaps, evaluate implementation risks, and prioritize system improvement initiatives. To demonstrate the applicability of the framework, a pilot assessment was conducted using competency and readiness data collected from instructional personnel within a technology-enhanced educational environment. Analytical results revealed strong capability levels across digital instructional practices, technology-supported curriculum development, online learning delivery, and collaborative knowledge-sharing activities. The assessment also identified infrastructure and support-related constraints that may affect the scalability and sustainability of advanced digital learning initiatives. The proposed framework contributes a scalable architecture for institutional readiness assessment and digital capability analytics within technology-enhanced educational systems. By integrating human capability indicators, infrastructure readiness measures, and organizational support metrics into a unified evaluation model, the framework provides a foundation for intelligent decision-support systems, digital transformation monitoring platforms, and technology governance mechanisms in modern educational ecosystems. Full article

With the rapid development of digital technologies, hardware products in two-sided platforms are continuously upgraded, creating challenges for the economic and operational sustainability of platform ecosystems. Platforms must address not only consumers’ strategic waiting behavior but also horizontal seller competition when making pricing decisions. To stimulate consumption and promote product upgrading, governments have introduced subsidy programs for end consumers. This paper develops a two-period dynamic game model involving the government, a monopolistic two-sided platform, buyers, and sellers to examine the effects of three subsidy schemes—no subsidy, consumption subsidy, and trade-in subsidy—on platform pricing, market equilibrium, and social welfare. The results show that: Consumption subsidies intensify buyers’ strategic waiting behavior, reduce current demand for original products, and exacerbate seller competition; as seller competition weakens, platforms reduce product prices and increase seller commissions under all subsidy schemes; and the trade-in subsidy effectively promotes product upgrading and avoids demand cannibalization while maximizing social welfare and generating the highest platform profit and seller surplus, thereby aligning the government’s welfare objective with stakeholder participation incentives and supporting the sustainable operation of the platform. This study enriches the literature on revenue management and two-sided markets. The findings provide theoretical support for platforms’ intertemporal pricing decisions and offer policy implications for designing economically sustainable government subsidy programs for hardware products in two-sided platforms. Full article

This study examines whether the diffusion of financial technology expands or constrains private-sector credit across OECD economies, and whether regulatory quality conditions that relationship. Fintech diffusion is operationalized through a composite index of general digital-infrastructure indicators (internet use, mobile subscriptions, and ICT-service exports); this index proxies the broader digitalization environment rather than measuring payment-platform use, embedded credit, or digital lending directly. It conceptualizes digital payment ecosystems as complex financial systems in which technological diffusion, regulatory capacity, and credit dynamics co-evolve through feedback mechanisms. The policy discourse often assumes that digital financial inclusion automatically enhances resilience, yet evidence on credit expansion and systemic exposure remains contested. Using an unbalanced panel of 37 OECD economies from 2015 to 2024, comprising 356 observations, the analysis employs Driscoll–Kraay standard errors to address cross-sectional dependence within a common-slope two-way fixed-effects framework, along with panel quantile regression at the 10th, 50th, and 90th percentiles and Dumitrescu–Hurlin causality testing. Fintech diffusion is positively and statistically significantly associated with private-sector credit exposure, and this association is robust to a two-way fixed-effects specification. The quantile estimates show that the association is present at these selected points of the conditional distribution and strongest at its lower and upper tails, a pattern consistent with complex-adaptive-system dynamics in which effects vary across system states. Contrary to the negative-feedback expectation, the interaction between fintech diffusion and regulatory quality is positive, consistent with high-quality institutions enabling rather than restraining the translation of fintech into credit, though the observational design identifies this interaction rather than the mechanism producing it. The findings therefore shift the discussion from fintech as a stand-alone inclusion tool to fintech as a system-shaping force with implications for institutional resilience, macroprudential supervision, and systemic credit exposure. Because domestic credit to the private sector aggregates household and corporate lending, the policy implication below is framed at this aggregate level: digital payment infrastructure should be governed jointly with consumer protection, credit reporting, and financial-resilience mechanisms rather than promoted as a neutral technological upgrade. Full article

Sexually transmitted infections (STIs) remain a major global public health challenge, while stigma, privacy concerns, and barriers to healthcare access continue to delay diagnosis and treatment. This narrative review summarizes the current evidence on the use of artificial intelligence (AI) to support STI self-assessment and digital sexual healthcare while critically discussing its current applications, challenges, and limitations, based on a PubMed literature search. Existing studies demonstrate the potential of machine-learning algorithms for individualized HIV/STI risk prediction, symptom-based assessment, automated evaluation of genital lesions, and differentiation of sexually transmitted from non-sexually transmitted conditions, with reported diagnostic performance ranging from AUCs of approximately 0.75–0.95 for symptom assessment models up to 0.893 for multimodal image-based lesion classification and validation accuracies of 94.4% for real-world image analysis platforms. Advances in computer vision and radiomics further highlight the ability of image-based AI systems to identify diagnostically relevant lesion characteristics while improving model interpretability. In parallel, generative AI chatbots are increasingly being explored as tools for sexual health education, personalized risk assessment, behavioural support, triage, and linkage to care. These technologies also influence psychological aspects of sexual health by providing private and accessible support, facilitating risk appraisal, and addressing anxiety associated with STI concerns. However, insufficient demographic diversity and the reliance on retrospective training datasets, privacy and data security concerns, limited prospective validation, and uncertainty regarding real-world clinical effectiveness remain important barriers to the widespread adoption of these technologies. To address some of these limitations, future developments are expected to focus on multimodal and explainable AI systems integrated within digital sexual health ecosystems, with clinicians remaining central to the validation, interpretation, and contextualization of AI-generated assessments and the delivery of patient-centred care. Full article

The embedded finance paradigm is fundamentally restructuring digital economies by seamlessly integrating financial services into non-financial digital infrastructures. This study dynamically evaluates the productivity frontiers of Sea Limited’s embedded fintech operations (SeaMoney) across six core geographic markets (Indonesia, Thailand, Vietnam, the Philippines, Malaysia, and Brazil) over the 2023–2026 temporal horizon. Employing a rigorous Panel Data Envelopment Analysis (DEA) Malmquist Productivity Index framework, the research measures systemic performance by analyzing Sales & Marketing (S & M) Expenses and the undesirable Non-Performing Loan (NPL) rate as inputs, against Gross Loan Outstanding as the primary credit output. Before model execution, robust isotonicity was empirically validated using Pearson correlation matrices. The empirical findings reveal profoundly robust systemic performance across the global ecosystem, driven primarily by overarching algorithmic innovations captured by the Technical Change (TC) index. However, this technological boundary exhibits a stabilizing deceleration over time, indicative of a maturing ecosystem transitioning from explosive, frontier-shifting innovation to optimized refinement. Furthermore, localized managerial optimization, measured by the Efficiency Change (EC) index, displays significant regional heterogeneity. While markets like Brazil demonstrated aggressive late-stage efficiency spikes, and core Southeast Asian markets (such as Vietnam and the Philippines) maintained highly stable, competitive trajectories, other regions, such as Thailand, experienced notable managerial regression. This regression signals severe internal frictions in optimizing local marketing budgets against rising credit defaults. Managerial Implications: These findings provide critical strategic insights for orchestrators of the multinational e-commerce ecosystem. The empirical evidence suggests that relying exclusively on centralized technological scaling, such as unified platform infrastructure and global AI architectures, is insufficient for sustained operational growth. To maintain a competitive advantage, operations executives must deploy hyper-localized resource-allocation and customer-acquisition frameworks tailored to specific regional market dynamics and consumer behavior. Sustainable scaling in cross-border digital commerce requires a precise dynamic equilibrium: leveraging robust global technological infrastructure while executing highly adaptive, market-specific operational and marketing optimizations to maximize customer lifetime value (CLV), eliminate customer acquisition waste, and streamline localized transaction and engagement cycles. Full article

The increasing adoption of digital learning environments has generated large volumes of learner-generated data that can be leveraged to support instructional quality monitoring, educational performance assessment, and evidence-based decision-making. As educational institutions seek scalable mechanisms for evaluating teaching effectiveness within technology-enabled learning ecosystems, there is a growing need for analytics-driven systems capable of transforming learner feedback into actionable performance intelligence. This study proposes an Instructional Quality Analytics System (IQAS) designed to collect, process, analyze, and visualize instructional effectiveness indicators within digital learning environments. The proposed system architecture consists of four integrated components: feedback acquisition, instructional quality analytics, performance monitoring, and decision-support reporting. The framework utilizes structured learner-generated evaluation data to model instructional effectiveness across multiple dimensions, including content quality, instructional delivery, learning environment support, and instructional management practices. Through quantitative analytics mechanisms, the system generates performance indicators, identifies instructional strengths and improvement opportunities, and supports continuous quality assurance processes. To demonstrate the feasibility of the proposed architecture, a pilot implementation was conducted using evaluation data collected from higher education learners within a technology-supported educational environment. Analytical results indicated consistently positive instructional performance across all assessment dimensions, with content-related indicators exhibiting the strongest performance characteristics. The evaluation further demonstrated stable instructional quality profiles across learner groups, suggesting the suitability of the framework for institution-wide monitoring and benchmarking applications. The proposed Instructional Quality Analytics System contributes a scalable architecture for educational performance monitoring and instructional effectiveness assessment within digital learning ecosystems. By integrating feedback analytics, performance intelligence generation, and decision-support capabilities, the framework provides a foundation for next-generation educational monitoring platforms, quality assurance systems, and intelligent learning analytics environments. The study offers practical implications for the development of data-driven educational governance mechanisms that support continuous improvement, resource optimization, and evidence-based instructional decision-making. Full article

Building Information Modeling (BIM) has become a central paradigm in the architecture, engineering, and construction industry, enabling integrated management of design and construction data. Accessibility standards are essential to ensure inclusive and usable built environments, yet manual verification of ISO 21542:2021 criteria in BIM models is time-consuming and error-prone. Following the formal standardization of the Information Delivery Specification (IDS) in 2024, this study investigates its potential for systematic accessibility validation. Using the Design Science Research methodology, ISO 21542 door requirements were translated into IDS format and applied to the Urla Summer Villa case. The workflow integrated IDS Maker for XML rule definition, ArchiCAD for BIM, and BIMvision with the IDS Checker plugin for automated validation. The evaluation revealed an overall compliance rate of 50%, with non-compliances in door width, height, threshold, and handle parameters. Results indicate that IDS can detect accessibility inconsistencies early, provide transparent reporting, and strengthen quality assurance in BIM-based design processes. This study contributes to expanding the limited corpus of accessibility-focused IDS applications and highlights IDS as a practical tool for advancing inclusive design practices within digital construction workflows. The study is limited to a single case and door elements only, within a specific software ecosystem. Future research should extend IDS-based accessibility validation to ramps, stairs, elevators, and diverse BIM platforms to strengthen generalizability. Full article