Search Results (871)

The adoption of e-Government projects by African governments is increasing, but despite their implementation, high rates of failure and abandonment persist, resulting in significant financial losses and few improvements in the provision of public services. One significant challenge is that such failures are mostly associated with technical/infrastructural factors, which means that other underlying factors in the process of ICT projects’ failure and success remain underexplored, including the interaction between ICT governance and environmental factors. This research focuses on the interaction between ICT governance and the environment and its effects on ICT projects. Using the PRISMA model, the literature review identified 42 of 90 articles and employed thematic analysis for theme categorisation. The findings identify four interdependent dimensions of failure: contextual pressures, structural governance weaknesses, rigid process mechanisms, and relational misalignment. These factors interact in a sequential cascade of Context > Structure > Process > Relational, whereby institutional conditions reconfigure governance into a compliance-based model, resulting in reduced flexibility and coordination. This research builds an ICT governance failure model with multiple dimensions and defines the concept of a Governance–Reality Gap. The results show that achieving better ICT project performance requires the concurrent consideration of ICT governance structures and institutional environments. Full article

Artificial intelligence (AI) may influence economic performance through productivity, innovation, and the diffusion of advanced technologies, but direct country-level measures of AI adoption remain limited for small economies. This study examines the association between AI-related technological capability and economic growth in Cyprus. The descriptive analysis covers 1993–2024, while the econometric analysis uses the common annual sample for 2008–2024 after introducing one-period lags. High-technology exports as a percentage of manufactured exports are treated as an indirect indicator of technological sophistication and absorptive capacity, rather than as a direct measure of AI adoption. A sequential distributed lag ordinary least squares framework introduces current and lagged high-technology exports, merchandise trade, and inflation, with heteroskedasticity-consistent HC3 standard errors. A COVID-19 indicator for 2020–2021 and an observation-exclusion sensitivity analysis are used to assess the influence of exceptional pandemic-era movements. The preferred specification explains a substantial share of annual GDP growth variation, but the small sample requires cautious interpretation. The estimates indicate a positive contemporaneous and a negative lagged association for high-technology exports, a stronger lagged than contemporaneous trade association, and opposite-signed current and lagged inflation coefficients. The COVID-19 indicator is statistically insignificant and does not materially alter the principal coefficient pattern. Complementary DESI, Eurostat enterprise AI use, and ICT employment indicators show that Cyprus has broadly adequate digital inputs while enterprise AI adoption has not yet reached the European Union average, indicating considerable scope for further diffusion. The findings are exploratory statistical associations and do not identify causal effects of AI. The study contributes a country-specific macroeconomic assessment of technological capability, digital readiness, and growth in a small, highly open economy. Full article

Sustainable energy transition is vital for the achievement of economic sustainability, environmental sustainability, and social inclusion. Hence, this paper explores the effect of ICTs, institutions, and per capita GDP on sustainable energy transition in the E7 economies between 2000 and 2024 in favor of causality and cointegration tests appropriate to the characteristics of the dataset. The causality test points out the existence of a one-way Granger causal relation from ICTs, institutions, and per capita GDP to sustainable energy transition. The estimated cointegration coefficients refer to a positive long-term association of ICTs and per capita GDP on sustainable energy transition in most of the E7 countries. Further, institutional quality positively impacts sustainable energy transition in China, India, and Indonesia in the long term, while it negatively impacts sustainable energy transition in Mexico. Our outcomes highlight the significant roles of ICTs, institutions, and per capita income for sustainable energy transition. 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

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

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

This study examines how the strategic integration of digital transformation and national innovation capacity contributes to accelerating sustainable development in Saudi Arabia by focusing on six Sustainable Development Goals (SDGs): SDG 4—Quality Education, SDG 7—Affordable and Clean Energy, SDG 8—Decent Work and Economic Growth, SDG 9—Industry, Innovation and Infrastructure, SDG 12—Responsible Consumption and Production, and SDG 13—Climate Action. Using annual data on ICT use, ICT access, R&D expenditure, and patent applications, the analysis evaluates both the direct and joint relationships between these indicators and SDG performance. Digital transformation is captured through ICT use and ICT access, while national innovation capacity is represented by R&D expenditure and patent applications, reflecting the input and output dimensions of formal innovation activity. The findings indicate that the direct long-run effects of digital transformation and national innovation capacity on the six SDGs are not statistically significant, suggesting that these domains have not yet become standalone drivers of educational advancement, clean-energy adoption, economic performance, industrial upgrading, sustainable resource management, or emissions reduction. In contrast, their interaction produces substantial positive effects on SDG 4, SDG 7, SDG 8, and SDG 9, highlighting improvements in educational quality, renewable energy transition, productivity, and industrial innovation. The interaction also has significant negative effects on SDG 12 and SDG 13, as reflected by reductions in CO₂ intensity and environmental pressures. These results indicate that meaningful progress toward the SDGs emerges when digital capabilities and national innovation capacity evolve jointly, rather than through isolated improvements in ICT infrastructure or innovation inputs. Robustness checks using a composite SDG index confirm the stability of these complementary effects. These findings suggest that Saudi Arabia can accelerate progress toward the SDGs by adopting integrated policies that link ICT expansion with stronger R&D systems, patent commercialization, technological innovation, and sustainability-oriented industrial transformation across education, energy, industry, resource efficiency, and climate action. Full article

Conventional photothermal therapy often relies on high-intensity laser excitation due to the limited photothermal conversion efficiency (PCE) of existing photothermal agents (PTAs), which compromises treatment safety and restricts clinical translation. To address this limitation, we designed and synthesized a series of boron-dipyrromethene (BODIPY)-based derivatives (BDP 1–4) featuring gradient-enhanced donor–acceptor (D-A) push–pull electronic effects for efficient photothermal antitumor therapy. The structure–activity relationships were systematically elucidated through photophysical characterization and in vitro/in vivo photobiological evaluation. From BDP 1 to BDP 4, the progressively strengthened push–pull effect leads to enhanced intramolecular charge transfer (ICT), which, in turn, results in a narrowed HOMO-LUMO gap, redshifted absorption into the near-infrared (NIR) region (up to 843 nm), markedly attenuated fluorescence emission, and a remarkable increase in PCE up to 88.3%. To improve water dispersibility and tumor targeting, these molecules were further encapsulated into nanoparticles using DSPE-PEG₂₀₀₀, and the nanoformulations retained high PCE. Both in vitro and in vivo studies demonstrated that under low-power laser irradiation (0.5 W·cm⁻², 808 nm), the nanoformulation of BDP 4, which exhibited the highest PCE among the series, achieved pronounced photothermal tumor ablation without inducing systemic toxicity. Overall, this study proposes a molecular design strategy that synergistically modulates NIR absorption and photothermal conversion by enhancing the D-A push–pull effect. This strategy provides a design rationale for developing efficient, low-toxicity organic PTAs, and demonstrates potential applicability in low-power PTT modalities. Full article

This study examines motivational and capability barriers to internet non-adoption in Thailand’s near-saturated digital economy. Using the 2025 Q4 ICT Household Survey conducted by Thailand’s National Statistical Office, the analysis focuses on 20,633 adult non-adopters who report either motivational or capability-related barriers. The dependent variable distinguishes capability non-adoption, defined as lack of skill or awareness, from motivational non-adoption, defined as lack of perceived need or privacy/security concerns. Weighted logistic regression with normalised population weights, PSU-clustered robust standard errors, and average marginal effects is used to estimate associations between household ICT access, age, education, employment, smartphone access, and barrier type. Motivational barriers account for 56.2% of the two-category non-adopter population and capability barriers for 43.8%. Although motivational reasons are the more common, household ICT access is positively—if modestly—associated with capability rather than motivational barriers (average marginal effect +1.7 percentage points): capability-constrained non-adopters are concentrated in connected households, the compositional signature predicted by the second-level digital divide. Age does not significantly moderate this association. Among older non-adopters, education, employment, and smartphone access are negatively associated with capability barriers, while household ICT access is not. The findings suggest that in post-access digital economies, household connectivity is insufficient for digital market inclusion; individual-level skills and device access become central to expanding effective digital market reach. Full article

The synergistic transition toward digital transformation and green development has been widely regarded as a core pathway to achieving sustainable development in knowledge production. Using balanced panel data from 39 economies covering 2018–2024, this study employed a two-way fixed-effects model to examine the associations of the energy efficiency of digital infrastructure and the energy structure with carbon intensity (CI). The findings showed that: (1) Reductions in Power Usage Effectiveness (PUE) values were significantly associated with higher macro-level CI (coefficient = −2.1564, p < 0.05), which is consistent with the possibility of a rebound effect in the digital sector. Further, time-series discontinuity tests further suggested that the surge in AI computing power, especially in 2023–2024, may have coincided with a structural shift in this relationship (Chow test, p < 0.05). (2) A Panel Threshold Regression (PTR) identified an optimal renewable energy threshold at 59.82%. Crucially, the carbon rebound effect remained highly significant across both high and low green power regimes, demonstrating that supply-side energy transition alone cannot fully absorb the exponential carbon footprint of digital expansion. Furthermore, Instrumental Variable (IV-2SLS) and Placebo Break Tests confirmed the strict validity of these findings. (3) The emission-reduction benefits related to digital knowledge spillovers appeared to be subject to time lags and a possible energy lock in effect, while current environmental policies and carbon pricing mechanisms appear to impose insufficient constraints. This study provides a crucial quantitative framework for monitoring and evaluating the environmental sustainability of the ICT sector. By highlighting the limitations of pure supply-side greening and the necessity of absolute carbon caps, our findings offer integrated policy approaches to align the exponential growth of Generative AI with global sustainable development goals. Full article

Objective: The purpose of this exploratory study was to examine mean differences, reliability, and agreement between CP and W′ derived from a 3MAT performed after an ICT and values obtained during a standalone 3MAT performed on a separate day. Methods: Ten recreationally trained cyclists and triathletes completed four laboratory visits, including an ICT followed by a 3MAT after 30 min of recovery (same-day condition) and a standalone 3MAT performed on a separate day. CP and W′ were derived from both conditions and compared using paired t-tests and Bland–Altman agreement methods. Results: No systematic differences, but limited individual-level agreement were observed between same-day and separate-day conditions for CP (mean difference: 1.72 ± 36.5 W) or W′ (mean difference: 0.99 ± 5.9 kJ), with trivial to small effect sizes. Peak VO₂ values were also not significantly different across testing conditions (p = 0.483). However, Bland–Altman analysis revealed wide limits of agreement for both CP (−69.8 to 73.3 W) and W′ (−10.7 to 12.7 kJ), indicating substantial variability at the individual level. Conclusions: Although same-day testing does not introduce systematic bias in CP or W′ estimation, the wide limits of agreement suggest that these protocols are not interchangeable for individual monitoring. Same-day testing may be appropriate for group-level assessments but should be used with caution when applied to individual athlete monitoring. Full article

In the digital economy era, computing power, as a novel factor of production, serves as a vital engine for driving high-quality economic development. Building upon China’s traditional 42-sector input–output table, this paper incorporates computing power networks as a new sector to construct a 43-sector dynamic input–output (IO) model. Based on this framework, a Dynamic Stochastic General Equilibrium (DSGE) analysis framework is constructed to systematically reveal the dynamic transmission mechanism of computing power within industrial linkages and capital accumulation. From an energy perspective, energy consumption is implicitly captured through carbon emissions and energy structure, which together reflect the scale, efficiency, and composition of energy use in computing power networks. The findings show that the optimal computing power allocation follows a temporal evolution pattern from the service sector to the manufacturing sector, with ICT manufacturing’s computing power quota reaching 31% by 2030. An investment inflection point occurs in 2026, aligning with the digital infrastructure cycle of China’s 14th Five-Year Plan. The “Eastern Data, Western Computing” strategy reduces unit carbon emissions from computing power by 41%. Policy simulations demonstrate that R&D tax credits generate a 2.9-fold multiplier effect through industrial linkages, boosting GDP by 2.3%. The integrated IO-DSGE framework developed in this study provides a quantitative tool for the full-cycle management of “construction–application–regulation” in computing power networks. It holds significant theoretical value and practical implications for enhancing resource allocation efficiency and promoting green, climate-friendly development. Full article

This study assesses how a country’s digitalization impacts sustainability indicators as measured by unmonitored environmental, social and governance (ESG) risks, which serve as a proxy for the development of financial technology (FinTech). The study employs a cross-country approach using data for up to 163 countries, going beyond the firm-level focus of previous studies. The DiGiX Digitalization Index and the ICT Development Index are used to measure digital maturity, while pillar-level indicators and Sustainalytics ESG country risk scores are used to assess ESG indicators. With evidence of nonlinear, threshold-type effects at higher levels of digital maturity, the regression results suggest a strong negative correlation between digital maturity and ESG risk. Different country typologies are further identified using unsupervised cluster analysis, which reveals a continuous digital and ESG gradient in environmental, social and governance aspects. The analysis proves digital maturity serves as a systemic enabler of ESG risk management by strengthening data availability, governance capacity and policy enforcement. These findings provide policy-related guidance for coordinating digitalization strategies in line with the Sustainable Development Goals. Full article

Environmental degradation has become a critical structural challenge for sustainable development, particularly in regions where economic growth remains closely linked to natural resource exploitation. In Latin America, and specifically within ALADI countries, limited empirical evidence exists on the dynamic interactions among economic growth, trade integration, energy efficiency, and digital transformation in shaping environmental pressures. This study addresses this gap by employing a dynamic panel data approach based on System GMM for the period 2000–2021. The results reveal that economic growth and trade openness have a positive, statistically significant effect on the ecological footprint, confirming the persistence of scale effects and the absence of structural decoupling between economic expansion and environmental degradation. In contrast, energy intensity and ICT service exports, although positively associated with environmental pressure, did not show statistically significant effects, suggesting that their role in driving sustainability transitions remains limited under current structural conditions. These findings highlight that structural economic factors predominantly drive environmental dynamics in the ALADI region, while the estimated effects associated with technological and efficiency-related variables remain comparatively weak and statistically inconclusive under current structural conditions. From a policy perspective, the study underscores the need for deeper structural transformations, including cleaner energy transitions, stronger environmental regulation in trade, and a more effective integration of digitalization into sustainability strategies. The study contributes to the literature by providing robust dynamic evidence on socio-environmental interactions in developing economies and advancing the understanding of sustainability transitions in Latin America. Full article