Search Results (1,832)

(1) Background: Pre-service teachers enter university with extensive digital experience, yet this familiarity does not guarantee pedagogically grounded ICT integration. (2) Objective: This study examines the sociodemographic profile, digital trajectory, ICT perceptions, and methodological orientation of 295 students in the Primary Education Degree and the Secondary Education Teacher Training Master’s program at CES Don Bosco, a Spanish university. (3) Method: A quantitative, descriptive-correlational, cross-sectional design was used, combining non-parametric statistics with cluster analysis and multiple regression. (4) Results: Teaching specialization was significantly associated with age profile (χ²(1) = 67.46, p < 0.001, φ = V = 0.478). Daily ICT exposure showed a weak, negligible association with tool familiarity (ρ = 0.155, p = 0.008), and no asymmetry emerged between the technological and methodological repertoires once expressed proportionally (Wilcoxon Z = 1.32, p = 0.186, r = 0.08). Cluster analysis identified two digital profiles differing not in tool familiarity but in how experience was acquired. Regression showed specific ICT training, not daily exposure, modestly predicted methodological orientation (R² = 0.055). (5) Conclusions: Findings do not support a large technology–pedagogy gap; deliberate training, not passive exposure, predicts methodological orientation. As a single-institution case study, results should not be generalized beyond this context. Full article

The rapid expansion of information and communication technology (ICT) alongside sustained economic growth poses a critical policy challenge for hydrocarbon-based economies seeking to reconcile digital development with environmental sustainability. This study examines both the short- and long-term relationships between per capita CO₂ emissions, GDP per capita, and the adoption of ICT in Saudi Arabia, using annual time-series data for 1995–2024. Methodologically, we employ the ARDL bounds test, an error correction model (ECM), and Granger causality analysis to test the EKC hypothesis. Additionally, we use the Zivot–Andrews test to detect structural breaks, accounting for these through dummy variables. Long-run cointegration among the three variables is validated by the bounds test results. GDP is the dominant long-run driver of internet-based ICT adoption, while CO₂ emissions and GDP are strongly cointegrated through the 2010 structural break and the EKC mechanism. No direct causal link is found between ICT and CO₂ emissions in either direction. The long-run validity of the EKC hypothesis is confirmed, with an estimated income turning point of approximately USD 26,021 per capita, a level reached during the latter part of the sample period. These findings suggest that Saudi Arabia’s internet adoption has yet to generate an independent decarbonization dividend, underscoring the need for policies that couple ICT investment with clean energy deployment under Vision 2030. Full article

Disaster risk reduction, both natural and man-made, is a global priority and is in line with the goals of the 2030 Agenda, defined on the basis of what happened at the beginning of the millennium, starting with the disaster in human lives caused by Katrina in New Orleans. However, there is a scientific gap between the level of risk and the planned risk mitigation measures, with the related training and exercise actions implemented before real-life emergencies happen. In the context of Transport Risk Analysis (TRA), the size of exposure (E), in particular its reduction through evacuation, has been little studied, unlike the dimensions of occurrence (O) and vulnerability (V). This study aims to provide a framework of the scientific literature on the risk exposure component (graphical abstract) in urban transport systems, focusing on four macro areas: planning process; training and exercises; advanced Transport System Models (TSM); and use of emerging ICT (e-ICT). The study has been carried out using forward snowball techniques on a selected sample of the literature. The final set of references comprises 165 publications: 149 retrieved from Scopus (including records assessed at abstract level) and 16 retrieved via Google Scholar and forward-citation snowballing. The publications are distributed across the four macro-areas as follows: 68 concern the planning process, 24 training and exercises, 61 advanced Transport System Models, and 12 the use of e-ICT. The four macro-areas were examined both individually and in their mutual intersections, since several publications address more than one area simultaneously. Each work was classified under its predominant area for tabulation purposes. The analysis shows that the literature examined provides unequal coverage of the four broad areas. Whilst contributions relating to the planning process and modeling are relatively well-established, the integration of ICT with advanced transport system models in the context of transport risk analysis remains extremely limited. Approaches based on forecasts for outdoor evacuation are largely absent, and research into training and drill activities lags behind that on planning models. The framework developed in this work is useful to researchers, policy makers and public sector technicians involved in emergency management, as it offers a clear framework to guide future work in both research and operational action. Full article

Digital technologies are an integral part of young children’s everyday lives, yet their pedagogical integration in early childhood education and care (ECEC) remains limited and highly variable across ECEC centers. Drawing on the extended Structure–Process (SP-E) framework, this study examines how structural characteristics of ECEC centers, particularly the range of available ICT equipment, and educators’ ICT-related professional competencies, especially beliefs and motivational orientations, predict ICT implementation in pedagogical practice. Data from the DIGIPaed project comprised 266 educators across 97 German ECEC centers. Hierarchical regression models with cluster-adjusted standard errors were estimated for two outcomes: ICT use with children and pedagogical ICT activities. Results revealed distinct predictor patterns for the two outcomes. The range of available ICT equipment was positively associated with pedagogical ICT activities but not with ICT use with children. ICT-related self-efficacy was the only professional competence variable to predict both outcomes, explaining additional variance beyond structural conditions and beliefs. Centers with higher proportions of children with a migration background showed lower levels of ICT use with children. These findings suggest that ICT implementation in ECEC is not a unitary construct and that different dimensions of implementation may depend on different conditions. Self-efficacy emerged as a particularly promising target for professional development aimed at supporting meaningful ICT integration in ECEC centers. Full article

Digital transformation is increasingly recognized as an important enabler of sustainable development and competitiveness in small- and medium-sized enterprises (SMEs). However, evidence on how different dimensions of digital transformation relate to the achievement of Sustainable Development Goals (SDGs) remains limited. This study explores the relationship between digital transformation and selected Sustainable Development Goals (SDGs) using an explanatory sequential mixed-methods design, in which quantitative findings informed the subsequent qualitative exploration and interpretation of managerial perspectives. The quantitative phase combined data from Eurostat’s ICT Usage Survey (2020–2024), including 60 sustainability-related indicators, with an analysis of the relationship between the Digital Economy and Society Index (DESI) and selected SDG indicators across 27 EU member states using Spearman’s rank correlation. The quantitative analysis suggests that Slovenia performs close to the EU average in overall digitalization, while significant associations were identified between digitalization and SDG 9. The qualitative phase consisted of semi-structured interviews with managers from ten Slovenian SMEs from different sectors. The findings indicate that managers perceive digital technologies, process digitalization, data-driven decision-making, and employee digital competencies as important contributors to sustainability-related outcomes, particularly in relation to SDG 8, SDG 9, SDG 12, and SDG 13. The study contributes to the literature on sustainability-oriented digital transformation in SMEs by integrating quantitative benchmarking with managerial perspectives. The findings highlight the importance of organizational capabilities, digital competencies, and strategic alignment in translating digital transformation initiatives into sustainability-related outcomes. The results provide practical implications for SMEs and policymakers seeking to support sustainable and digitally enabled business development. Full article

Background: Generative artificial intelligence (GenAI) is diffusing among consumers at exceptional speed, yet little is known about how its adoption relates to households’ prior engagement with digital financial services, or about the barriers associated with non-adoption. Methods: Using individual microdata from the 2025 Spanish Survey on ICT Equipment and Use in Households (INE; 14,642 internet users aged 16 and older), we estimate survey-weighted logistic regressions of GenAI adoption on financial digital engagement, digital skills and sociodemographics, with autonomous community fixed effects and cluster-robust standard errors, complemented by average marginal effects, alternative variance estimators, and an analysis of all stated reasons for non-use. Results: GenAI adoption is 37.3% among internet users. Online banking users have 73% higher adjusted odds of adopting GenAI (OR = 1.73; 95% CI 1.53–1.97), and adoption rises monotonically from 18% to 79% across a 0–4 financial digital engagement index, although this gradient is driven mainly by the online banking (extensive) margin. A steep age gradient is present, but the financial digital advantage does not significantly widen with age. Among non-adopters, the most frequently stated reason for non-use is a lack of perceived need (67%); privacy or security concerns are also prominent (43%) and are cited disproportionately by online banking users, women, and older individuals. Conclusions: Prior financial digital engagement is a strong correlate, rather than a demonstrated cause, of consumer GenAI adoption, consistent with experience and facilitating condition constructs in UTAUT2. Among capable non-adopters, for whom access and skills are not the obstacle, privacy- and security-related concerns, rather than a broader deficit of trust in AI, emerge as the most salient barriers to adoption, underscoring these concerns as priorities for consumer-facing AI in financial services. Full article

Background: Several strategies such as premedication or allergologic work-up have been used to facilitate safe iodinated contrast media (ICM) application. The aim of this study was to assess the negative predictive value of skin tests and complete allergologic work-up with iodinated contrast media in real-life settings. Methods: We retrospectively enrolled 210 patients with a history of immediate hypersensitivity reactions to ICMs. The stepwise protocol of selecting safe ICMs included skin prick tests (SPTs), intracutaneous tests (ICTs), and intravenous drug provocation tests (DPTs). The tests were performed with one or more of the following medications: iohexol, iodixanol, iomeprol, iopromide, and ioversol. At least 6 months after selecting safe ICMs, a telephone follow-up was scheduled. Based on this data, negative predictive values of skin tests and the whole work-up were calculated. Results: Overall, we obtained the following rates of positive tests: SPT—12% (55/441); ICT—10% (40/383); and DPT—5% (10/195). The highest rates of positive work-ups were found in patients tested within 1 year after the reaction and patients with a history of urticaria/angioedema after ICMs. The skin tests and DPTs determined a safe ICM in 184/210 (87%) patients. The negative predictive value of skin tests in reference to DPTs in hospital settings was 95%. Finally, a telephone follow-up demonstrated that 75/184 participants (41%) had been given the recommended ICM, including 68 cases (37%) with no subsequent hypersensitivity reaction and 7 (4%) with a reaction. The negative predictive value of allergologic work-up consisting of SPTs, ICTs and DPTs in real-life settings was 90%. Conclusions: Skin tests and intravenous drug provocation tests with ICMs are characterised by high negative predictive value, and enable the determination of safe ICMs for most patients. Full article

This paper examines the relationship between learning environments and changes in Information and Communication Technologies (ICT)-related career aspirations across education systems in the context of ongoing digital transformation. The analysis uses country-level data from the Programme for International Student Assessment (PISA) 2018 and 2022, combining indicators of student autonomy, digital skills and teacher support. Digital readiness is operationalized as a latent country-level construct combining digital skills, student autonomy and perceived teacher support. The study uses regression analysis as the primary associational approach, complemented by clustering and latent-representation techniques used for exploratory profiling and visualization. Unlike prior research that treats learning loss, digital skills and career expectations separately, our analysis integrates them within a comparative longitudinal framework. It shifts the focus from short-term post-pandemic effects toward the broader capacity of education systems to support digital preparedness and future-oriented career expectations. Digital skills were consistently associated with ICT aspiration growth across education systems, while teacher support played a complementary contextual role. Autonomy shows weaker, context-dependent effects. The findings support interpreting digital readiness as a multidimensional construct reflecting combinations of digital skills, autonomy and teacher support. Full article

Industry 4.0 is widely recognized as a strategic enabler of productivity, flexibility, and competitiveness in manufacturing systems. However, in emerging economies, declared preparedness for digital transformation often exceeds reported implementation. This study examines the readiness–adoption gap of Industry 4.0 in surveyed large manufacturing companies in Valle del Cauca, Colombia. An empirical cross-sectional study was conducted through a structured survey administered to large manufacturing companies in the region. The instrument was grounded in the Technology Acceptance Model and informed by a sociotechnical understanding of Industry 4.0 adoption. It captured perceptions of ICT infrastructure, workforce capabilities, expected benefits, implementation challenges, ease of use, and the reported implementation status of 20 Industry 4.0 technologies. Data from 59 valid responses were analyzed using descriptive statistical techniques, cross-technology comparisons, and an aggregate descriptive synthesis of readiness and adoption indicators. The findings suggest that adoption remains concentrated in foundational technologies such as cybersecurity, cloud computing, and data analytics, while advanced technologies, including artificial intelligence, cyber–physical systems, digital twins, and immersive technologies, show limited implementation despite favorable readiness perceptions. The aggregate synthesis points to a medium-to-high readiness proxy and a substantially lower average adoption level, suggesting the presence of a readiness–adoption gap. The study contributes empirical evidence from large manufacturing companies and derives two practical outputs: a readiness–adoption matrix and a staged roadmap for capability building and technology prioritization. These outputs are presented as context-specific exploratory tools rather than universally validated models. Full article

Background: As Information and Communication Technology (ICT) advances, the healthcare market is shifting toward a consumer-centered paradigm. This study analyzes the structural relationships between medical information quality, medical service quality, and Technology Acceptance Model (TAM) variables to determine their impact on patient satisfaction and revisit intentions in a general hospital context. Methods: An online survey was conducted with 376 consumers who had experience using general hospitals in South Korea between June and December 2024. Data were analyzed using structural equation modeling (SEM) with SPSS 29.0 and AMOS 29.0. Ethical measures, including informed consent and anonymity, were strictly followed. Results: Findings indicate that among medical information quality factors, accuracy significantly enhanced perceived usefulness, while timeliness positively influenced perceived ease of use. Regarding medical service quality, both accessibility and responsiveness significantly improved both usefulness and ease of use, with responsiveness being the most powerful predictor of ease of use (β = 0.655). While both TAM variables significantly increased patient satisfaction, only perceived ease of use and satisfaction directly drove revisit intentions; perceived usefulness influenced revisit intention only through the mediation of satisfaction. Conclusions: Patient satisfaction is a paramount factor directly influencing loyalty. Healthcare administrators should prioritize the accuracy and timeliness of digital health information while improving service responsiveness to enhance long-term hospital competitiveness in the proactive consumer era. Full article

This study investigates the possibilities for recently listed Romanian Information and Communications Technology (ICT) firms to select optimal sets of financial strategies under adverse macroeconomic conditions, with high and persistent inflation, high volatility, high cost of financing and liquidity constraints that influence investment decisions and financial resilience. Using a stochastic investment model with the Tobin’s Q factor in a dynamic framework equipped with a generalized Wiener process, this study offers an intuitive approach for simultaneously assessing corporate market value under financial constraints and formulating optimal decisions based on liquidity management. In this research, the numerical simulations in Python for a set of 16 scenarios resulting from combining technological and macroeconomic variables were performed, with a series of parameters held constant. The results highlight the decisive role of financial restrictions and macroeconomic volatility in shaping the investment behavior, as well as the importance of adjusting the timing of investments together with liquidity mechanisms capable of improving financial resilience. The main contribution of this study is the simplicity with which one can assess the impact of the risk-free rate and volatility on the main parameters of the set of strategies (earnings dynamics, liquidity risk, cost of capital, liquidation value, opportunity cost associated with holding cash) and to assess the integrated perspective on financial resilience. This procedure is simple and scalable and can also represent a practical tool to support management and investment decisions in volatile and turbulent conditions. Full article

This study investigates the relationship between educational leadership, ICT-related factors, and students’ reading performance using the PISA 2022 dataset for Türkiye. Drawing data from 7250 students and 196 school principals, we employed multilevel structural equation modeling and Bayesian estimation. At the student level, between-school actions to sustain learning (SCHSUST) were significantly related to reading achievement. All student-level ICT variables—self-efficacy in digital competencies, practices regarding online information, and subject-related ICT use—significantly predicted reading achievement. Bayesian mediation analysis confirmed significant indirect relationships at student level, indicating that SCHSUST is associated with reading achievement primarily through ICT variables. Students’ economic, social and cultural status predicted reading achievement, indicating socioeconomic inequalities. At the school level, educational leadership (EDULEAD) has been found to be positively associated with preparedness for digital learning and school preparation for remote instruction. However, EDULEAD was negatively related to reading achievement. At the school level, all indirect relationships were insignificant. Furthermore, “economic, social and cultural status” and “academic school selectivity” emerged as the strongest predictors of reading achievement at their respective levels, indicating that the majority of reading inequality is due to substantial between-school inequality, in addition to the socioeconomic basis of digital inequality. Overall, the study highlights that meaningful ICT integration, rather than mere infrastructure provision, is associated with improved reading achievement. Full article

Digital infrastructure expansion in Europe raises a spatial planning problem: early-stage screening needs to compare regional conditions while also checking whether rankings remain stable when decision priorities change. This study evaluates 24 European Nomenclature of Territorial Units for Statistics level 2 (NUTS-2) regions for geo-distributed data center development. The 2022 decision matrix uses five Eurostat criteria: information and communications technology (ICT) specialists’ share in employment, average hourly labor cost, renewable electricity share, non-household electricity price and population density. Four criteria are national intensive proxies assigned to the selected NUTS-2 regions, while population density is directly observed at the NUTS-2 level. After a log₁₀ transformation of population density and min–max normalization, we compare the weighted sum model (WSM), TOPSIS and VIKOR across four weighting scenarios. We then apply a random-weighting audit based on Stochastic Multicriteria Acceptability Analysis (SMAA) principles, using 10,000 Dirichlet weight draws, followed by a local Dirichlet sensitivity analysis around the Balanced profile. Results show that the most stable high-performing profiles are not limited to the established FLAP-D market reference. Latvija (LV00), Stockholm (SE11), Helsinki-Uusimaa (FI1B), Eesti (EE00) and Área Metropolitana de Lisboa (PT17) form the main high-performing set across stochastic rank metrics, while several mature Western metropolitan regions remain more sensitive to cost and territorial-pressure criteria. The study provides a reproducible spatial decision support framework for macro-regional screening rather than micro-siting. Full article

The COVID-19 pandemic generated unprecedented disruptions to the global tourism industry, severely affecting tourism-dependent economies and related employment. India, as one of the world’s major tourist destinations, experienced substantial declines in tourist arrivals during the pandemic period. This study investigates the effects of COVID-19-induced fear on tourism demand and economic performance in India using the COVID-19 Fear Index, which captures behavioural responses to pandemic-related uncertainty beyond conventional indicators such as infection rates, mortality, and lockdown restrictions. The COVID-19 Fear Index is constructed using reported COVID-19 cases and mortality data sourced from the European Centre for Disease Prevention and Control and the Johns Hopkins Coronavirus Resource Centre. Monthly data from January 2020 to October 2023 are analysed using autoregressive distributed lag (ARDL) and nonlinear autoregressive distributed lag (NARDL) models to examine both tourism demand dynamics and the asymmetric tourism–growth relationship. The results confirm a stable long-run cointegration relationship among tourism demand, the COVID-19 Fear Index, exchange rate, and ICT development. Pandemic-induced fear significantly reduces tourism demand in the long run ($-0.152$, $p=0.021$) and short run ($-0.084$, $p=0.000$), indicating that heightened uncertainty suppresses tourist arrivals. Exchange rate depreciation also negatively affects tourism demand ($-0.267$, $p=0.000$), whereas ICT development positively enhances tourism resilience ($0.463$, $p=0.000$). The error correction term ($-0.436$, $p=0.000$) confirms rapid adjustment toward long-run equilibrium. Furthermore, the nonlinear analysis reveals asymmetric effects, where positive tourism shocks increase economic growth by $0.088\%$ ($p=0.003$), while negative shocks exert a stronger contractionary effect ($0.409$, $p=0.000$). These findings highlight the vulnerability of tourism-dependent economies to uncertainty shocks and emphasise the importance of ICT-driven resilience strategies, adaptive tourism policies, and crisis-responsive economic planning. Full article

Purpose: This study was conducted to assess retinal responses in myopic and non-myopic participants after exposure to repeated low-level red-light therapy (RLRT) of 3 min and 1 min duration to see if response differs with exposure time and refractive status using global flash multifocal electroretinogram (gf-mfERG). Methods: This was a prospective exploratory pilot study with a convenient sample of 20 participants of mean age of 25.5 years (18 to 39 years) who underwent 3 min therapy, followed by, 1 week after, 1 min therapy in each participant between February to May 2025. However, four participants who did not appear in 1 min therapy for measurements were excluded from the between-group comparison analysis. We measured retinal responses using gf-mfERG ring-wise implicit time (DCT, ICT) and amplitude (DCA, ICA), baseline, post-first and post-second RLRT. Data analysis included descriptives, repeated measures ANOVA, post hoc test, Bonferroni adjusted correction, and correlation with axial length (AL) and choroidal thickness (CT) in each group. The study was conducted at CEORLab, University of Minho, Portugal, and adhered to Ethical Committee approval and the tenets of the Declaration of Helsinki. Results: In 3 min RLRT exposure, no significant within-subject changes were observed across direct (DC) and induced (IC) gf-mfERG components across all rings (p > 0.05). Statistically significant between-group differences in DC implicit time were noted in Ring 2 (p = 0.029) and Ring 3 (p = 0.012). IC amplitude showed significant within-subject changes in myopes (Ring 1: p = 0.030; Ring 4: p = 0.035) and non-myopes (Ring 1: p = 0.042; Ring 3: p = 0.001; Ring 4: p < 0.001; Ring 5: p = 0.034), with no significant between-group differences (p > 0.05). In contrast, 1 min RLRT showed no significant changes in DC, IC time or amplitudes ICA, DCA (all p > 0.05). Correlation analysis after 3 min RLRT showed that in myopes, DCT positively correlated with AL in Ring 3 (r = 0.591, p = 0.006) and Ring 4 (r = 0.615, p = 0.004), ICT positively correlated with CT in Ring 2 (r = 0.601, p = 0.005) and Ring 3 (r = 0.573, p = 0.008), and ICA negatively correlated with AL in Rings 3–5 (all p < 0.01). Non-myopes demonstrated limited correlations, including a negative association between ICT and axial length in Ring 4 (r = −0.619, p = 0.004). Similar but weaker patterns were observed following 1 min RLRT. Conclusions: 3-min RLRT induces localized inner retinal functional changes without significantly altering outer retinal responses, while 1-min exposure shows no measurable effect. Retinal ERG responses are primarily influenced by axial length, particularly in myopic eyes, highlighting a structure–function relationship rather than a robust short-term therapeutic effect of RLRT. Full article