Search Results (105,170)

This paper examines the nonlinear relationship between economic diversification and economic growth in Saudi Arabia and estimates a diversification threshold associated with higher growth performance. Using annual data from 1995 to 2024, the analysis situates economic diversification within the context of two major reform periods: the structural transformation policies of the early 2000s and the Vision 2030 program initiated in 2016, both of which aimed to reduce oil dependence and expand the non-oil economy. The empirical findings reveal a nonlinear relationship between diversification and growth, where diversification is associated with higher growth outcomes above an estimated threshold. Overall, the results suggest that higher levels of diversification are associated with greater economic resilience and stability in Saudi Arabia, while highlighting the importance of continued structural reforms to deepen sectoral diversification and support sustainable long-term economic performance. Based on the obtained results, policy implications are discussed. Full article

Accelerating green collaborative innovation is crucial to achieving environmental sustainability. Using panel data from Chinese A-share listed firms, this study theoretically and empirically investigates the causal association between digital and real technological integration and corporate green collaborative innovation. We reveal that digital and real technological integration significantly promotes corporate green collaborative innovation. Mechanism analysis indicates that digital and real technological integration promotes corporate green collaborative innovation by mitigating asset specificity, reducing green agency costs and broadening green knowledge breadth. Furthermore, heterogeneity analysis shows that this positive effect of digital and real technological integration on corporate green collaborative innovation is more pronounced among firms with higher internal control quality, operating in high-tech industries, and located in eastern regions. This study not only deepens our understanding of the economic consequences of digital and real technological integration, but also provides crucial insights and evidence for exploring the antecedents of corporate green collaborative innovation. Full article

Background/Objectives: Adverse childhood experiences (ACEs) are associated with child socio-emotional difficulties, but when using parents’ reports, it remains unclear which scoring approaches are most informative about younger children. This study evaluated a Portuguese caregiver-report ACE assessment derived from the Finkelhor/Turner framework in a community sample of children aged 2–10 years. Methods: Caregivers provided reports on ACE exposure and socio-emotional adjustment for 341 children. Three ACE scores were compared: an approximate original ACE score, a full ACE pool score, and an adapted reduced caregiver-report score. Associations with socio-emotional adjustment were examined using correlations, adjusted regressions, ROC analyses, domain models, and latent class analysis. Results: Higher ACE exposure was associated with greater difficulties and lower prosocial behavior. The nine-item approximate original ACE score, which did not include emotional neglect, showed the strongest overall predictive and discriminative performance for caregiver-reported SDQ outcomes in this Portuguese sample. This finding should therefore be interpreted as evidence regarding the available approximation of conventional ACE indicators rather than the complete original ACE inventory. Among the two expanded ACE scoring approaches, however, the adapted reduced score consistently outperformed the full ACE pool, supporting a more parsimonious approach. ROC analyses indicated acceptable discrimination for elevated total difficulties, with the approximate original score showing the highest area under the curve (AUC); however, positive predictive values were low across all three scores, indicating limited stand-alone screening utility at the individual level. Domain analyses highlighted economic stressors, maltreatment, and family disorder as salient predictors. Latent class analysis identified low adversity, moderate family/economic adversity, and high polyadversity profiles. Both adversity-exposed classes showed poorer socio-emotional adjustment than the low-adversity class. Conclusions: Findings support the relevance of caregiver-report ACE assessment for understanding socio-emotional adjustment in young children, while also highlighting the need for developmentally sensitive, culturally adapted, and outcome-validated scoring approaches. More extensive ACE pools were not necessarily more informative than shorter empirically or theoretically grounded scores. Full article

This study investigates the relationship between SME loans and economic growth in Kazakhstan using quarterly data covering the period 2010Q1–2025Q3. While the finance–growth nexus has been extensively studied, empirical evidence focusing specifically on SME credit remains limited, particularly for transition economies. To address this gap, the study employs the ARDL bounds testing approach to examine both short- and long-run dynamics, while FMOLS is used as a robustness check. Structural breaks are incorporated into the model based on Bai–Perron multiple breakpoint tests. The empirical findings reveal a positive and statistically significant long-run relationship between SME loans and economic growth. In contrast, short-run results indicate that the effect of SME loans is not statistically significant, suggesting that the growth impact of SME financing materializes over time rather than immediately. Among control variables, exports are found to have a strong and consistent positive effect on growth, reflecting the export-oriented structure of the Kazakh economy. Conversely, foreign direct investment exhibits a negative and relatively weak relationship with growth. Overall, the results highlight the importance of SME financing in supporting long-term economic growth while emphasizing the role of structural and external factors in shaping growth dynamics. This study contributes to the literature by providing country-specific evidence and offers policy-relevant insights for strengthening SME financing mechanisms. Full article

Optimising urban growth patterns (UGPs) and enhancing production-living-ecological (PLE) functions are crucial for achieving sustainable urbanisation. However, systematic comparisons remain limited regarding how PLE functions vary with population size under different urban growth patterns and how their relative performance differs. This gap constrains a comprehensive understanding of urban expansion quality and hinders the place-based optimisation of spatial governance strategies. This study analyses 348,817 newly added built-up patches in mainland China, identifies expansion patterns using the landscape expansion index (LEI), and evaluates their functional performance with urban scaling law and the Scale-Adjusted Metropolitan Indicator (SAMI). The findings can be summarized as follows. (1) Edge expansion dominated China’s urban growth over the past decade (64.88%), while infill accounted for the smallest share (14.17%). (2) Infill expansion achieves the highest efficiencies in production (β = 0.662) and living (β = 0.032) functions but suppresses ecological function (β = −0.003), making it more suitable for areas under strong economic development pressure. Outlying expansion shows the opposite pattern, with a slight positive scaling effect on ecological function (β = 0.009) but the lowest efficiencies in production (β = 0.485) and living (β = 0.019) functions, thus fitting regions with strong environmental constraints. Edge expansion lies between the two, with a neutral ecological effect (β = 0.000), and is suited to areas with moderate development needs that also require ecological stability. (3) The SAMI further confirms that infill expansion performed significantly better than expected in production functions, whereas outlying expansion and edge expansion showed clear advantages in ecological functions. These findings reveal differences across urban growth patterns in the scaling and relative performance of PLE functions, providing empirical evidence for selecting growth patterns according to regional functional needs. Full article

Chromium coatings with excellent corrosion resistance and strong Zr interfacial bonding are economical candidates for accident-tolerant fuel claddings. Irradiation-triggered elemental interdiffusion and interfacial voids severely degrade their service reliability. Ni alloying was introduced into the Cr matrix to obtain composite coatings with improved mechanical properties and irradiation resistance. CrNi coatings with different Ni contents were deposited using magnetron sputtering, whose microstructural features, phase composition, mechanical properties and irradiation behavior were comprehensively characterized by XRD, SEM, TEM and mechanical measurements. The pristine CrNi coatings display compact and uniform microstructural morphologies. Increasing Ni concentration significantly refines the columnar grain architecture and diminishes grain dimensions. Post-irradiation microstructural characterization reveals distinct structural evolution features of CrNi coatings with different Ni contents. Pure Cr and low-Ni coatings present enhanced XRD diffraction intensities and contain high-density irradiation-induced dislocation loops. The 27 at.% Ni coating after irradiation is indicative of irradiation-triggered local recrystallization and defect annihilation. Mechanical tests confirm that moderate Ni alloying (~17 at.%) achieves improved resistance to irradiation-induced hardening through solute–defect interaction effects, whereas excessive Ni (~27 at.%) degrades mechanical properties owing to aggravated lattice disorder, increased free volume, and soft Ni-phase dilution effects. Full article

This paper asks whether the digital economy is becoming the new economy: not because traditional economic functions disappear, but because they are increasingly reorganised through digital infrastructure, digital finance and algorithmic capability. We introduce an open-data Digital Architecture framework and build a fully reproducible panel of 38 OECD economies for 2010 to 2024 from World Bank sources. The framework constructs transparent composite indices for digital infrastructure, FinTech, AI/ML capability, the traditional economy, and a clean new economy. Using two-way fixed-effects panels, we provide a descriptive answer: in OECD economies, the digital economy coincides with the new economy mainly through digital infrastructure. First, digital infrastructure is the load-bearing pillar of the digital economy’s association with the new economy: it accounts for about 24 per cent of within-country variation in new-economy outcomes, although its coefficient is imprecise under country-clustered errors. Second, the Digital Architecture Index is useful as a benchmarking construct, but it does not improve the within-country fit because the digital pillars are collinear and infrastructure carries most of the signal. Third, the evidence does not support a robust three-way configuration effect among digital infrastructure, FinTech and AI/ML capability; the association is sensitive to error structure, dynamics, outcome definition and true survey-year estimation. A future-dated placebo loads for the infrastructure block as well, so even the descriptive associations cannot be cleanly separated from slow-moving common trends. The paper therefore contributes a reusable open-data measurement framework and a clear empirical benchmark: in OECD economies, the digital economy aligns with the new economy primarily through digital infrastructure, the pillar that carries the strongest within-country association with productivity and entrepreneurship. The AI/ML capability proxy is externally validated against Eurostat enterprise-AI adoption data, with a cross-country correlation of 0.80. Full article

Digital capitalism is often described either as a clean break with the past or as a continuation of older markets. This article takes a third position: digital capitalism is a reorganisation of capitalist accumulation around platforms, data, attention and digital labour, not a departure from capitalism’s basic logic. The study uses a critical narrative review approach, drawing on Marxian value theory and recent work on platforms, datafication and surveillance. It is anchored by a curated set of publicly reported indicators from institutional and market sources, used as context rather than as a causal test. These show a platform environment that reaches most of humanity, highly concentrated advertising and cloud markets, platform labour as a global phenomenon, and a supposedly weightless economy resting on dense physical infrastructure. The article traces four contradictions: the commodification of unpaid user activity, the material basis of immaterial production, the concentration of market power, and the gap between participation and algorithmic control. The contribution is conceptual. It shows that media business models usually treated as separate, including advertising, subscriptions, creator monetisation, in-game spending and platform commissions, share one logic: user activity is captured as attention, measured as data and converted into revenue. New media therefore function as economic infrastructures for value extraction. Full article

The cultivated peanut (Arachis hypogaea L.) is an important oilseed and economic crop worldwide, with seed protein content being a key target for quality improvement. The Sugars Will Eventually be Exported Transporter (SWEET) gene family encodes sugar transporters that play crucial roles in plant growth and development, stress tolerance, pathogen interactions, and seed filling. In this study, 43 AhSWEET genes were identified in the cultivated peanut genome and classified into four phylogenetic clades. Members within the same clade generally show similar exon-intron structures and conserved motif compositions, suggesting evolutionary conservation within subgroups. Promoter cis-regulatory elements analysis indicated that AhSWEET genes contain multiple elements associated with light response, hormone signaling, stress response, and growth and development, implying their potential involvement in diverse biological processes. Subcellular localization predictions indicated that most AhSWEET proteins are likely localized to the plasma membrane, consistent with their putative roles in transmembrane sugar transport. This was further supported by transient expression analysis of selected AhSWEET-eGFP fusion proteins in Nicotiana benthamiana leaves. Comparative phylogenetic and synteny analyses reveal that AhSWEET5, AhSWEET21, AhSWEET27, and AhSWEET43 are closely related to soybean GmSWEET10a and GmSWEET10b, which are known to regulate seed size and storage-compound accumulation. Transcriptome data and quantitative reverse transcriptase PCR analysis showed that these candidate genes are preferentially expressed in seed-related tissues, particularly the testa and embryo, suggesting possible sugar allocation during peanut seed development. Overall, this study provides a systematic characterization of the AhSWEET gene family and identifies several candidate genes for future functional studies aimed at improving peanut seed quality, including protein accumulation. Full article

The rapid growth of the photovoltaic (PV) market in Poland has increased the importance of data-driven sales management and strategic resource allocation in renewable energy companies. Despite dynamic market expansion, significant regional differences in PV adoption indicate the existence of underutilized sales opportunities. This study aims to develop a decision-support framework for identifying company-specific regional gaps between actual and model-predicted photovoltaic contract volumes. The analysis is based on more than 15,000 real contracts obtained from a large PV installation company and enriched with regional demographic, economic, energy-related, housing, and regulatory data. Several machine learning models were evaluated, including Random Forest, XGBoost (XGB), HistGradientBoosting, and CatBoost. To improve transparency, explainable artificial intelligence (XAI) techniques based on SHapley Additive exPlanations (SHAP) were applied. Additionally, a model-based Untapped Potential Index (UPI) was developed as an operational indicator of the company-specific gap between actual and expected regional sales performance. The results indicate that CatBoost achieved the highest predictive accuracy and enabled the identification of regions with the largest positive company-specific sales gaps. The proposed UPI supports the optimization of marketing activities, sales resource allocation, and regional expansion strategies within the analyzed company. The broader methodological framework may be extended to regional market assessment through recalibration and external validation using independent market data. Full article

The growing implementation of the United Nations Sustainable Development Goals (SDGs) has increased the importance of sustainable transformation in higher education institutions. Universities are increasingly expected to integrate environmental management, digital technologies, governance, education, and community engagement into unified sustainability frameworks. However, integrated sustainability management models for technical universities in emerging economies remain insufficiently explored. This study analyzes the long-term transformation of the EKTU Green Campus project at D. Serikbayev East Kazakhstan Technical University (Kazakhstan) during 2018–2025. The research is based on methodological triangulation combining institutional statistical data, official UI GreenMetric methodologies and indicators, university sustainability reports, and verified ranking results. The study examines the interaction between Smart Campus technologies, digital governance, sustainability-oriented education, environmental management, and campus infrastructure modernization. The results indicate substantial progress across multiple dimensions of institutional sustainability, including energy efficiency, digital sustainability governance, renewable energy implementation, sustainable transportation, circular economy practices, and education and research indicators. The findings suggest that Smart Campus technologies and digital monitoring systems can function as core instruments of institutional sustainability management rather than solely as technical infrastructure solutions. The EKTU Green Campus experience provides a practical reference for sustainability transformation in technical universities in Central Asia and other developing regions, while acknowledging that its applicability may depend on local institutional and socio-economic contexts. The study is limited by its single-case design and its reliance on institutional and ranking data, which may affect the generalizability of the findings. Full article

Disaster risk perception in informal urban settlements remains insufficiently understood despite its importance for climate adaptation and urban resilience policies. This study evaluated disaster risk perception among residents of nine informal settlements in Greater Santo Domingo, Dominican Republic, focusing on the relationship between the subjective risk of disaster, poverty, and socio-environmental vulnerability. A mixed-methods approach was applied using the RISKPERCEP algorithm and a structured survey composed of 98 questions grouped into key perception variables. A total of 198 surveys were conducted across four municipalities, supported by expert consultation, probabilistic sample-size calculation, and statistical analyses including chi-square tests and Cramér’s V coefficients. The results revealed a generalized moderate underestimation of climate-related risks, mainly associated with limited understanding of hazards, weak institutional trust, low personal involvement, poor memory of past disasters, and reduced concern about consequences. Socioeconomic deprivation, particularly among women, retirees, and low-income groups, was strongly associated with higher perceived vulnerability. Statistical analyses demonstrated a dense and multidimensional network of interdependent social, economic, and spatial variables shaping vulnerability. The study concludes that low disaster risk perception constitutes a major barrier to climate adaptation in informal settlements and highlights the need for integrated public policies combining social protection, climate education, urban resilience, and community-based adaptation strategies. The implications of this study point to the use of a disaster risk perception inquiry method at the community level, structured around specific variables that allow the identification of underlying causes of the widespread underestimation of disaster risk. This approach enables the design of adaptive policies—both structural and non-structural—that explicitly incorporate these aspects when formulating resilience measures. Future research should aim to generalize the study to other communities across the country, preceded by addressing the limitations identified. Full article

The formation of asphalt–resin–paraffin deposits (ARPDs) and gas hydrate deposits (GHDs) in oil wells equipped with electric submersible pumps (ESPs) remains a significant challenge in the oil and gas industry. This study aims to develop an inhibitory technology to prevent these deposits by utilizing the synergistic effect of chemical reagents combined with the optimization of ESP operating parameters. Based on previously published mathematical modeling and laboratory studies by the authors, this work presents the technological implementation of the inhibition system and its economic assessment. Specifically, optimal reagent dosages were calculated considering their synergistic interactions, a periodic injection regime was established, and the impact on the well’s mean time between failures (MTBF) was evaluated. Results demonstrate that optimizing ESP parameters shifts the onset depth of GHD formation by 119.4 m (25%) and ARPD formation by 72.6 m (6%). The application of the selected ARPD inhibitor at 0.055 wt.% reduced the thermodynamic hydrate inhibitor (methanol) dosage by 12.17% and enabled a transition from continuous to periodic methanol injection. Consequently, the predicted MTBF increased from 277 to 419 days (+50%). An eight-year economic analysis showed a positive net present value with a payback period of 14 months. Thus, the proposed technology is recommended for field testing in high-paraffin, low-resin oil fields operating under permafrost conditions. Full article

Short-form video (SFV) marketing generates structured consumer ratings and unstructured feedback that can be analyzed for e-commerce decision support. This study examines associations between five content- and creator-related perceptions, Creating Shared Value (CSV), and purchase intention among 409 respondents in Bulgaria. From a business intelligence (BI) perspective, this study combines descriptive profiling, clustering, sentiment analysis, formative partial least squares (PLS) path modeling, group-difference testing, and machine-learning prediction to produce descriptive profiles, explanatory associations, consumer segments, text-analytic findings, and predictive results. CSV is specified as a formative composite of eight noninterchangeable product/economic, community/social, and relational indicators associated with short-form video creators. Clarity (β = 0.260), willingness to use (β = 0.226), similarity (β = 0.205), likability (β = 0.177), and empathy (β = 0.130) are positively associated with CSV; CSV is positively associated with purchase intention (β = 0.567). The model explains 69.1% of CSV variance and 32.2% of purchase-intention variance. Six formative weights are significant, all absolute loadings exceed 0.72, and indicator VIFs remain below 5. The group-difference hypothesis is partially supported by 18 omnibus ANOVAs with Holm correction for multiple testing. Significant differences in both CSV and purchase-intention means are found across age groups and categories based on the number of influencers followed. Significant differences in purchase-intention means are also found across social-media use-frequency and daily SFV-viewing-time categories. Clustering, sentiment-analysis, and machine-learning results are interpreted as complementary BI outputs rather than evidence of causal effects or validated campaign effectiveness. Full article

Spring viremia of carp virus (SVCV) poses a major threat to aquaculture industry, triggering severe economic losses and substantial damage to fish health. Effective antiviral therapeutic approaches are currently insufficient in aquaculture, highlighting an urgent demand for viable intervention strategies. This study assessed the antiviral and immunomodulatory potential of Houttuynia cordata against SVCV in common carp. Combined cellular and in vivo fish experiments demonstrated that Houttuynia cordata markedly suppresses SVCV replication, reduces viral titer, and enhances disease resistance of carp. The extract appears to suppress RARα-A, upregulate IFN-1/CXCL11, and recruit T lymphocytes via CXCL11, thereby enhancing innate and adaptive immunity against SVCV. Experimental results indicate that Houttuynia cordata alleviates hemorrhagic symptoms induced by SVCV infection. Dietary supplementation with this herb realizes dual functions of viral suppression and immune regulation for carp aquaculture. The findings provide a practical prevention and control strategy against SVCV infection and offer novel insights for research on green antiviral agents. Furthermore, this study verifies the potential value of Houttuynia cordata in improving biological safety and facilitating sustainable development of aquaculture, laying a solid foundation for the development of eco-friendly antiviral preparations. Full article