Search Results (612)

This narrative review examines how big data analytics supports geospatial decision-making in smart cities through the combined roles of spatial data foundations, GeoAI methods, and urban digital twins. Methodologically, the article follows a structured narrative and critical review design rather than a PRISMA-based systematic review, bibliometric analysis, or meta-analysis. The paper responds to fragmentation across GIScience, smart-city studies, urban analytics, geospatial data engineering, and digital twin research, where related contributions often remain technically rich but weakly integrated from a decision-oriented perspective. Rather than treating geospatial decision-making as an extension of GIS or as a general expression of data-driven governance, the review frames it as a layered socio-technical process through which heterogeneous urban data are transformed into decision-relevant knowledge. The analysis first clarifies the conceptual evolution from GIS to spatial decision support and urban governance, and then examines the spatial data sources, integration problems, and representational limits that shape smart-city evidence. It also reviews GeoAI and geospatial analytics methods, including spatial statistics, machine learning, spatiotemporal forecasting, graph-based modeling, optimization, and explainable GeoAI. Urban digital twins are then analyzed as decision infrastructures that connect sensing, data integration, synchronization, semantic modeling, simulation, visualization, user interaction, and feedback into planning or operations. The review further maps these capabilities across mobility, land use, utilities, risk management, environmental resilience, public health, and cross-domain decision contexts. Overall, the paper argues that the value of smart-city geoinformation systems depends not on data abundance or model sophistication alone, but on their capacity to support interpretable, accountable, and context-sensitive urban decisions. Full article

The digital transformation of agrifood systems demands an integrated infrastructure to ensure traceability, trust, and intelligent decision-making across complex and heterogeneous value chains. METROFOOD-IT, a large-scale national research infrastructure in food metrology aligned with the ESFRI METROFOOD-RI, addresses these challenges by combining advanced experimental facilities with a comprehensive digital ecosystem. This paper focuses on the IT kernel of METROFOOD-IT and presents an integrated architectural model that brings together four key technological paradigms: data acquisition through Internet of Things (IoT) and laboratory infrastructures, an Open Data Platform for interoperability and sharing, blockchain-based notarization for integrity and provenance, and Artificial Intelligence (AI) for knowledge extraction and decision support. Rather than describing these components in isolation, the paper abstracts from their implementation within the Italian National Recovery and Resilience Plan (NRRP) project METROFOOD-IT to distill a coherent and reusable architectural pattern in which data management, trust enforcement, and intelligent analytics are tightly coupled. Five explicit design principles are identified and articulated: federated data with centralized metadata, selective on-chain anchoring, user-unobtrusive trust infrastructure, explainability as a first-class architectural concern, and machine learning as the backbone of decision-making. Two empirical case studies—one centered on explainable AI for hyperspectral crop nitrogen assessment and the other on IoT-driven sustainable agriculture monitoring secured by distributed ledger technology—serve a dual role: they motivate and shape the architectural pattern, and they exemplify the operational regimes the resulting design supports. A reference deployment on the Ethereum Sepolia public test network, grounded on an IBM Power E1050 and IBM Storage Scale enterprise substrate, provides quantitative evidence for the proposed hybrid on-chain/off-chain pattern with streaming hash-only notarization. The architecture illustrates how research infrastructures can evolve into integrated digital platforms that enable transparent, verifiable, and scalable agrifood systems, and offers a foundation for generalizable design principles in data-intensive and trust-sensitive settings. Full article

This study examines how digitalization discourse is mobilized in public carbon reporting under institutional complexity and how it varies across different carbon-accountability structures in an emerging-market context within the Global South. A longitudinal comparative discourse analysis was conducted on 70 annual and sustainability reports (2015–2024) from seven Vietnamese listed firms, contrasting firms with internal carbon accountability against those with supply-chain-mediated accountability. The 2015–2024 timeframe was deliberately selected to capture a critical decade of regulatory evolution, marked by the aftermath of the Paris Agreement and the escalating enforcement of net-zero and environmental, social, and governance (ESG) disclosure mandates. Findings reveal that digitalization functions as an ambivalent rhetorical resource rather than a uniformly substantive sustainability enabler. Firms with operationally visible emissions utilize digitalization for “temporal buffering,” deferring immediate physical abatement by framing technology as a future transition pathway. Conversely, firms with supply-chain-mediated emissions employ “boundary displacement,” framing accountability as contingent on fragmented supplier data. These patterned responses constitute “digital institutional camouflage”. We conclude that digital reporting sophistication should not be conflated with substantive decarbonization; effective oversight requires cross-validating digital infrastructures with concrete emission-reduction measures. Ultimately, this study empirically specifies institutional decoupling theory by demonstrating how emissions visibility and organizational control shape distinct pathways of discursive decoupling. Full article

Saudi Arabia currently lacks a nationally representative, multi-day National Household Travel Survey comparable to the US, UK, or New Zealand programmes; existing official data products focus on aggregate road-transport indicators or general household statistics rather than detailed day-to-day travel diaries. This study develops a benchmark-driven framework for NHTS–KSA by comparing Saudi demographic, geographic, infrastructure, climate, and mobility indicators with those of the United States, United Kingdom, and New Zealand, and by systematically assessing 15 survey-design indicators across their national household travel surveys. Context benchmarking identifies the United States as the closest for highway-oriented interurban structure and motorisation level, New Zealand for geography and demographic structure (in particular, near-identical physiological density on limited arable land), and the United Kingdom as the most aspirationally aligned benchmark for the multimodal mobility patterns Saudi Arabia aims to develop under Vision 2030. Design benchmarking shows that the three surveys are closely matched in aggregate similarity but lead on distinct elements: New Zealand on diary length and integrated passive tracking, the US on digital tools and emerging-behaviour modules, and the UK on interviewer-led recruitment and multimodal analysis, a pattern that proves robust to plausible variation in individual scores. The resulting NHTS–KSA blueprint specifies a statistically justified, stratified multistage annual household sample, a two-day diary with rolling 12-month fieldwork, interviewer-assisted recruitment, a digital-first diary with optional GPS tracking, and modules on long-distance travel, telework, e-commerce, gendered mobility, accessibility, safety, and environmental attitudes. While preserving international comparability, the framework provides the data foundation required to steer public-transport investment, demand-management measures, and land-use policies in line with Saudi Arabia’s Vision 2030 objectives for sustainable, inclusive, and smart mobility. Full article

Against the coordinated advancement of building a maritime power, high-quality development of marine tourism and ecological civilization construction, realizing positive interaction between marine resource conservation and tourism industrial development has emerged as a pivotal issue for high-quality growth in coastal regions. Taking 11 coastal provincial-level administrative regions in China spanning 2008 to 2024 as the research sample, this paper first establishes an evaluation indicator system covering marine resources and the tourism industry. It further adopts an integrated empirical framework encompassing the coupling coordination degree model, spatial Markov chain model, obstacle degree model, fixed-effect model and geographically and temporally weighted regression (GTWR) model to systematically unpack the spatiotemporal differentiation characteristics, internal restrictive obstacle factors and external driving determinants of the two-system coupling coordination. On this basis, a marine resource compensation mechanism for tourist destinations is formulated. Empirical results demonstrate four core findings: (1) In terms of temporal evolution, the overall coupling coordination level keeps rising and goes through three phases: initial development, rapid improvement and post-shock recovery. After a short-term decline triggered by the pandemic, the index rebounds markedly after 2023, showing that the two systems can recover and stabilize. (2) In terms of spatial layout, a persistent stratified spatial pattern featuring “higher coordination in southern coast versus lower coordination in northern coast with three-tier hierarchical differentiation” is identified; high-level neighboring regions exert prominent positive spatial spillover effects, whereas low-level adjacent areas are prone to fall into development lock-in traps. (3) For internal constraint obstacles, the marine resource subsystem is persistently restricted by resource exploitation limits and coastal spatial scarcity, while the dominant bottleneck of the tourism industrial subsystem shifts from insufficient market scale to inadequate human capital supply. (4) Regarding external driving forces, the proportion of tertiary industry and the digital infrastructure constitute core driving contributors, whereas marketization progress and opening-up degree act as primary restrictive factors, with pronounced spatial heterogeneity existing across all driving indicators. Finally, in line with the quasi-public-good attribute and ecological externality of marine resources, this study constructs a differentiated and synergistic marine resource compensation mechanism from three dimensions: stakeholder identification, compensation implementation pathways and institutional guarantee systems. The proposed framework provides theoretical references and practical policy options to facilitate high-level coupling and coordinated development between marine resource preservation and the coastal tourism industry. The marginal contribution of this research lies in integrating coupling coordination measurement, obstacle factor diagnosis, driving mechanism identification and compensation mechanism design into an integrated analytical framework, which delivers theoretical foundations and operable policy solutions for coastal marine resource protection, tourism industrial upgrading and differentiated compensation system construction. Full article

Public trust is essential for the effectiveness and long-term sustainability of open government data (OGD) initiatives, particularly in small island developing states (SIDS), where digital governance systems often operate under infrastructural and institutional constraints. Despite growing global research on OGD trust, limited research has examined how the quality dimensions of information systems’ success models shape citizens’ trust in OGD platforms within Caribbean SIDS. This study examines the hypothesised relationships between service quality, system quality, information quality, data quality, and public trust in OGD using an extended information systems success model (ISSM). Data were collected through an online survey of 904 respondents across Caribbean SIDS and analysed using partial least squares structural equation modelling (PLS-SEM). The findings indicate that all proposed relationships were statistically significant. Data quality showed the strongest statistical association with public trust, followed by system quality. Service quality was also significantly associated with system, information, and data quality. In addition, system, information, and data quality showed significant indirect statistical relationships in the association between service quality and public trust in OGD. This study extends the ISSM framework by conceptualising data quality as a distinct construct within OGD environments. The findings provide practical insights for governments seeking to strengthen transparency, citizen engagement, and sustainable digital governance through higher-quality OGD systems and datasets. The results further highlight the role of open government platforms in improving public service delivery by providing citizens with complete, accurate, and accessible data, interactive feedback mechanisms, and effective data visualisation tools that support informed decision-making and public participation. Full article

This article examines the utilization of WhatsApp as an alternative communication tool for disseminating visual content among social activists during protests. While WhatsApp is typically conceptualized as an interpersonal or group messaging platform, research on its role as an infrastructure for alternative media and citizen journalism remains limited. The study focuses on the “Tikva” group, established at the onset of the public struggle against the 2023 judicial reform in Israel, which evolved into a nine-month mass protest movement described as one of the largest in the country’s history. Through qualitative thematic content analysis of videos distributed within the group, the article explores how WhatsApp functions simultaneously as a channel for digital activism and as a site of bottom-up, democratic, non-institutional news production. The findings indicate two primary trends: functionally, WhatsApp operates as a mechanism for resource mobilization, calls to action in physical and digital spaces, and the cultivation of belonging and solidarity among activists facing institutional power; in terms of content and production, the videos articulate an anti-hegemonic discourse and challenge mainstream media conventions. The analysis shows how these videos dismantle delegitimizing frames and construct a counter-narrative depicting protesters as citizens defending democracy, thereby sustaining the protest movement’s momentum. Full article

As the Kingdom of Saudi Arabia (KSA) accelerates its transition toward smart mobility under Vision 2030, establishing a robust digital infrastructure is paramount for the safe deployment of autonomous vehicles (AVs). High-definition (HD) maps serve as a critical foundation for this infrastructure, yet their deployment is severely bottlenecked by extreme operational costs, massive data processing payloads, and rapid environmental variations across vast highway networks. To address these challenges, this paper proposes a comprehensive, localized national strategy structured around three key tasks. First, it establishes a unified national HD map standard to guarantee seamless interoperability and data sharing among competing AV manufacturers and government transport authorities. Second, it implements an AI-powered baseline workflow using Mobile Mapping Systems (MMS) for high-fidelity static map construction, anchored and validated within designated pilot zones, including the King Abdulaziz University campus and key sectors in the Kingdom. Third, it deploys a decentralized, vision-based crowdsourcing system that leverages active public and commercial vehicle fleets for real-time map maintenance. By integrating a sovereign edge-cloud AI infrastructure that respects local Personal Data Protection Law (PDPL), this framework bridges the gap between high-accuracy baseline mapping and long-term economic sustainability, offering an actionable technical roadmap for scaling a resilient digital transport layer across the Kingdom. Full article

Utilizing the progressive rollout of public data open platforms as a quasi-natural experiment, this study applies a staggered difference-in-differences (DID) method to investigate the effect of public data openness on regional carbon emissions. The empirical analysis demonstrates a significant decarbonization effect induced by public data openness, and this conclusion survives a battery of robustness tests. Mechanism analyses confirm that the decarbonization effect of public data openness is driven by enhanced industrial upgrading, green technological innovation, green financial development, and environmental regulation. Heterogeneity analyses reveal that the decarbonization effect is statistically significant mainly in Central China, and in provinces characterized by high marketization and advanced digital infrastructure. Furthermore, public data openness demonstrates a substantial capacity for abating environmental pollutants such as sulfur dioxide and dust, thereby validating a synergistic governance effect. Overall, this study demonstrates the positive role of public data openness in reducing regional carbon emissions, thereby theoretically broadening the literature on its environmental consequences while expanding practical pathways for decarbonization. Full article

This bibliometric study maps olive (Olea europaea L.) yield prediction research as a coherent scientific domain for the first time. A Scopus query (27 February 2026) yielded 84 peer-reviewed articles (2002–2025), from which co-authorship network analysis, Bradford’s and Lotka’s Laws, Latent Dirichlet Allocation topic modelling (LDA), and OLS regression on citation counts were applied. Publication output increased nearly fourfold across three periods: 1.7 articles yr⁻¹ (2002–2014), 4.4 yr⁻¹ (2015–2019), and 6.7 yr⁻¹ (2020–2025). The 84 articles involve 382 authors, 61 journals, and 1551 citations (H-index = 22). Network analysis reveals a concentrated Spanish–Italian co-authorship axis. OLS regression (adj. R² = 0.267) identifies article age and abstract length as the only significant citation predictors, consistent with cumulative exposure time and study scope as structural drivers. Term-frequency screening against 18 a priori concepts finds that transfer learning, federated learning, hyperspectral imaging, digital twins, and SHAP-based explainability are absent or marginal. The field is producing more papers than ever on a narrowing methodological base geographically concentrated in the Mediterranean basin. Priority gaps—explainable AI, multi-region datasets, sensor-fusion pipelines, and federated data infrastructure—align directly with European Farm to Fork and Horizon Europe objectives. Full article

As countries accelerate their transition toward low-carbon economies, understanding the drivers of green finance is essential for shaping effective sustainability policies. This study investigates how FinTech development, digitalization, financial access, and structural factors influence public renewable energy investment—a measurable dimension of green finance—across 29 European countries over 2000–2022, using the Method of Moments Quantile Regression (MMQR). Results reveal strong distributional heterogeneity: FinTech consistently promotes green investment across all quantiles, digital infrastructure amplifies this effect in advanced regimes, and financial access is most binding at lower quantiles. Natural resource dependence exerts a persistent resource curse constraint that intensifies at higher quantiles. Three robustness strategies—2SLS-IV and quantile fixed effects QFE confirm a causal positive FinTech effect. Quantile-specific policy implications are derived: early-stage green investors should prioritize financial access and digital infrastructure, while advanced economies should deepen FinTech adoption and address resource-dependence constraints. Full article

This study examines the association between digitalization-enabled green human resource management (GHRM) practices and employee green behavior (EGB) within a South African metropolitan municipality. Anchored in an extended Ability–Motivation–Opportunity (AMO) framework, a convergent mixed-methods design was employed. Quantitative data were collected from 66 HR employees (from a target population of 80) and analyzed using Spearman’s correlation and hierarchical regression, while qualitative data from seven HR managers were analyzed thematically. Results indicate statistically significant positive associations between digital green training (ρ = 0.524, p < 0.01) and EGB, and between digital performance management (ρ = 0.463, p < 0.01) and EGB. However, regression estimates suggest moderate explanatory power within this context-specific public-sector setting. Qualitative findings identify automation, paperless systems, and e-HRM tools as key digital enablers, alongside infrastructural constraints, skills deficits, and institutional barriers that limit implementation. By integrating quantitative associations with qualitative evidence of implementation gaps, the study proposes a Digitalization-Integrated GHRM–EGB framework and demonstrates that digital HR systems are associated with pro-environmental workplace behaviors, contingent on organizational readiness in resource-constrained municipal environments. Full article

South Africa’s public hospital system faces mounting pressure from ageing infrastructure, rising patient demand, and constrained maintenance budgets. While significant investment has been directed toward the construction of new healthcare facilities, the diffusion and adoption of advanced technologies within operations and maintenance (O&M) remain uneven and underdeveloped. This misalignment limits the long-term performance, safety, and sustainability of hospital assets. This study investigates technological diffusion within the O&M environment of a newly commissioned 500-bed regional hospital in Durban, KwaZulu-Natal. A qualitative single-case study approach was adopted, drawing on semi-structured interviews with 14 stakeholders across project delivery and facility management functions. Data were analysed thematically to identify systemic patterns and operational constraints. Findings reveal a persistent reliance on manual, reactive maintenance practices, with minimal integration of digital tools, including building management systems, predictive maintenance technologies, and real-time monitoring platforms. Key barriers include unclear institutional roles, inadequate handover processes, limited technical capacity, and the absence of strategic leadership to drive innovation. A critical disconnect was also identified between managerial expectations and operational realities. The study argues that technological adoption in hospital O&M is not merely a technical challenge but an institutional one. It recommends targeted capacity development, structured transition frameworks, and stronger governance mechanisms to enable sustainable digital integration. Full article

Information infrastructure is essential for digital transformation and AI-enabled services, but its operation also involves high electricity consumption and carbon emissions. This study develops a tripartite evolutionary game model involving the government, information-infrastructure operators and the public, and integrates it with system dynamics to examine how regulatory mechanisms influence operators’ net-zero behaviours. The model focuses on operational-stage information infrastructure. Initial parameters are calibrated using the 2023 China Statistical Yearbook on Resources and Environment and expert consultation, with key variables measured by operational revenue, net-zero costs, regulatory costs, incentives, penalties, public scrutiny costs and environmental losses. The results show that operators’ net-zero behaviours may fluctuate under weak or static regulation. Government incentives, penalties and public scrutiny can promote net-zero operations, while dynamic reward–penalty mechanisms are more effective in stabilising behavioural evolution. This study extends evolutionary game theory and system dynamics to the net-zero governance of information infrastructure and provides an adaptive regulatory framework for coordinating government regulation, operator behaviour and public participation. Full article

Diagnostic imaging is central to clinical decision-making across many care pathways, yet the expertise needed to use these images well is unevenly distributed across health systems, with workforce limitations identified as a major barrier to equitable access, particularly in low- and middle-income countries. Digital education has emerged as one response to this gap, offering scalability, asynchronous and just-in-time access, and the cost-efficiency required for global deployment. This paper examines the digital education portfolio of the International Atomic Energy Agency’s Nuclear Medicine and Diagnostic Imaging Section, hosted mainly on the open-access Human Health Campus, which in 2025 recorded approximately 45,800 active users and 150,000 views across 159 countries. The portfolio combines structured e-learning courses, interactive webinars, virtual conference access through the Livestream programme, and a broader repository of publications, teaching cases, and reference resources, supported by an internal e-learning framework and learning management system infrastructure. Partnerships with international scientific societies further extend the reach of expert knowledge and professional exchange. The paper argues that these initiatives are best understood not as content delivery alone but as a coordinated strategy to support diagnostic quality at the level of the practising physician, extending access to expertise and strengthening the conditions for better practice, while remaining a complement to, rather than a substitute for, supervised clinical training. Full article