Search Results (1,805)

As a new engine of economic development, the digital economy is profoundly reshaping the governance structure and production models of modern agriculture and has increasingly become a significant force driving the high-quality development of agricultural export trade. Based on provincial panel data from 30 Chinese provinces spanning from 2014 to 2023, this paper employs a two-way fixed effects model to systematically examine the statistical association between the digital economy and agricultural export competitiveness. Furthermore, a mediation effects model is adopted to explore the underlying transmission pathways, and a threshold effects model is applied to reveal the nonlinear characteristics of this association, thereby providing a multidimensional analysis of the underlying mechanisms. The empirical results indicate that: (1) there is a significant positive statistical association between the digital economy and agricultural export competitiveness, and this finding remains robust across a series of robustness checks; (2) upgrading of agricultural industrial structure, agricultural technological innovation, and agricultural labor transfer serve as three important transmission pathways through which the digital economy is associated with enhanced export competitiveness; (3) this positive association exhibits regional heterogeneity, with stronger effects observed in central regions and major grain-producing areas; and (4) there is a nonlinear relationship between the digital economy and agricultural export competitiveness. Finally, based on these empirical findings, several policy implications are proposed, including strengthening digital infrastructure construction, enhancing trade openness, cultivating agricultural digital talents, optimizing factor allocation structures, and improving the digital economy governance system, so as to fully unlock the potential space of the positive association between the digital economy and agricultural export competitiveness. Full article

This study investigates the impact of real effective exchange rate (REER) volatility on foreign direct investment (FDI) inflows in three major Central and Eastern European (CEE) economies—Hungary, Poland, and Romania—using quarterly data spanning from 2007-Q1 to 2024-Q4. The exchange rate volatility is modeled using a Generalized Autoregressive Conditional Heteroskedasticity (GARCH) framework, and country-specific relationships are estimated through Autoregressive Distributed Lag (ARDL) bounds testing and Toda–Yamamoto causality analysis. Our research indicates that a uniform relationship does not exist across the region. In Hungary, the utilization of directional FDI data excluding Special Purpose Entities (SPEs), in conjunction with structural breaks and quarterly seasonal controls, reveals a statistically significant nonlinear (inverted U-shaped) relationship between long-run exchange rate volatility and FDI inflows. In addition, domestic financial development exerts a substantial buffering effect on the transmission of volatility in Hungary by bypassing SPE flows that previously obscured this effect. In Poland and Romania, a stronger currency consistently discourages investment by reducing cost competitiveness. Romania shows a distinct pattern: volatility initially attracts FDI, and while deeper financial markets meaningfully dampen this effect, the net relationship remains positive, unlike Hungary, where sufficiently deep credit markets fully reverse it. These results suggest that policymakers should look beyond short-term exchange rate stabilization and instead prioritize structural reforms, competitive exchange rate levels, transparent FDI reporting standards, and deeper domestic financial markets to sustain FDI inflows. Full article

The hydrogen economy has emerged as a promising pathway to address climate change and ensure long-term global energy security, with water electrolysis powered by renewable energy as a key enabler of sustainable hydrogen production. Recent advances in various electrolyser technologies have enhanced their suitability for industrial applications, creating new opportunities for deploying green hydrogen. To address the gap in integrated, multi-dimensional assessment tools for groundwater-based hydrogen systems in water-scarce developing countries, this study develops and presents a Structured Assessment Framework for Green Hydrogen Production from Groundwater in South Africa—the first framework to simultaneously integrate hydrogeological sustainability screening, electrolyser technology selection under groundwater quality constraints, disaggregated levelised cost of hydrogen (LCOH) analysis including water treatment costs, comparative life cycle assessment (LCA) of green, blue, and grey hydrogen pathways, and policy and governance alignment within a single operationalised architecture. This included integrating five thematic dimensions: groundwater resource assessment, electrolyser technology integration, economic viability, environmental sustainability, and policy and governance considerations. This systematic review was conducted in accordance with the PRISMA 2020 guidelines, drawing on 130 studies retrieved from Scopus and Web of Science (2015–2025). The analysis examines groundwater quality and suitability, the technical feasibility of electrolyser systems, and the comparative implications of grey, blue, and green hydrogen pathways on cost and environmental performance. The framework also provides strategic guidance for deploying renewable-energy-powered hydrogen systems, emphasising life-cycle impacts, regulatory alignment, and the potential for decentralised hydrogen hubs. Findings highlight the significance of strengths, weaknesses, opportunities, and threats (SWOT) for green hydrogen production using groundwater in South Africa, including export potential and strong linkages to the circular economy. The study offers actionable insights for policymakers, planners, and industry stakeholders seeking to advance a sustainable and economically competitive hydrogen landscape. Full article

Against a backdrop of rising macroeconomic uncertainty, the digital economy has become a key driver of regional economic resilience. However, research on this relationship still requires further refinement for the Yellow River Basin, a special region characterized by ecological redline constraints and a dense concentration of resource-based cities. Using panel data from 78 prefecture-level cities over the period 2008–2019 and treating the global financial crisis as an exogenous shock, this study employs two-way fixed effects, mediation, and spatial Durbin models to examine the mechanisms and spatial patterns of the digital economy’s impact on economic resilience, while also incorporating heterogeneity analyses with regional characteristics of the Yellow River Basin for further investigation. The results show the following: (1) The digital economy expanded rapidly while resilience declined, with significant spatial divergence in both. (2) The digital economy positively affects resilience and is robust to various checks. (3) Industrial upgrading, innovation, and entrepreneurship serve as mediating channels. (4) The digital economy exerts spatial spillover effects on economic resilience at the basin-wide level. (5) The impact of the digital economy on resilience is moderated by ecological redline policies and resource dependence—western and resource-based cities gain the most, while eastern cities show negative spillovers from intensified factor competition. This study provides empirical evidence and policy insights for formulating differentiated digital transformation strategies in the Yellow River Basin. Full article

The inefficient management of agro-industrial residues, particularly cocoa pod husk and mucilage, represents a critical environmental and economic challenge in Santander and Norte de Santander, Colombia, where over 55,000 tons of biomass waste are generated annually from a regional production exceeding 23,500 tons of cocoa beans. Furthermore, these residues, which constitute approximately 70% to 75% of the fruit’s total weight, are currently underutilized, generating severe localized pollution through uncontrolled decomposition and causing substantial economic losses by wasting compounds with high valorization potential. This article proposes the design and systematic experimental calibration and internal cross-validation of an empirical model based on artificial intelligence capable of predicting quantities of valuable compounds, including bioethanol, essential oils, paraffins, antioxidants, and pectins, obtained from cocoa residues. The model integrates critical variables such as cocoa variety, extraction methods, and process conditions, incorporating advanced machine learning techniques trained on a 100% empirical database of eighty-four (84) laboratory trials, combined with a post-inference sensitivity analysis via the Monte Carlo method with 10,000 simulations. Preliminary results demonstrate significant varietal differences; for instance, the CCN-51 variety achieves a mean bioethanol yield of 79.30 ± 4.96 mL/kg with a 95% confidence interval of (69.44–88.93) mL/kg, while the Criollo variety reaches 43.55 ± 2.72 mL/kg (38.14–48.84 mL/kg), exhibiting highly synchronized coefficients of variation of 6.255% and 6.246%, respectively. Furthermore, the integration of a cascading extraction sequence combined with neural networks may potentially contribute to maximizing by-product yields, with theoretical mass balance estimations suggesting a possible reduction of up to 40% in final residue generation compared to conventional isolated extraction pathways, as detailed in the proposed framework. This tool could potentially support the circular economy and alignment with Sustainable Development Goals 7, 9, and 12, while offering a possible pathway to contribute to the competitiveness of the Colombian cocoa industry through data-driven decision-making and sustainable technology adoption. Full article

The tourism industries of the Chinese Mainland, Hong Kong SAR, Macao SAR, and the Taiwan region are globally competitive yet diverse, but persistent developmental disparities have hindered robust inbound tourism cooperation. This study assesses the synergistic potential and driving factors of the joint inbound tourism market among the Mainland, Hong Kong, Macao and Taiwan. Using panel data from 16 source countries (2000–2021), we construct a coupling framework for the inbound tourism relationship circle. We develop an inbound tourism relationship index and employ text analysis alongside ArcGIS Pro3.4.1-based spatiotemporal mapping to reveal the dynamic evolution of coupling coordination. A panel model is then applied to examine six influencing factors: economic, geographic, population, cultural, visa, and institutional. The results indicate that the coupling coordination degree remains generally high, though with stage-specific variations. Population, visa, and institutional factors exert significant positive effects, while economic and geographic factors show significant negative effects—economic because smaller-economy source countries are more likely to treat the four regions as a combined destination, facilitating inter-regional synergy, and geographic because greater distance raises travel costs and reduces visitor flows, thereby weakening coordination. Cultural factors are insignificant. Future efforts should prioritize visa facilitation and institutional building, providing a reference for market promotion, national integration, and sustainable regional cooperation. Full article

This study aims to examine the innovation efforts approach through long-term panel data and its impact on innovation outputs, in contrast to the majority of innovation studies that rely on short-term panel data with limited samples. It also addresses the debate and disparity in previous studies concerning the effects of R&D on innovation output. The data source is the Technological Innovation Panel (PITEC) of Spain’s Ministry of Economy and Competitiveness. The results show that internal and external innovation efforts in all of Spain and the other regions of Spain had the most positive effect on innovation output among the regions, while Cataluña, Madrid, and Andalucía exhibited the lowest positive effects. The study recommends establishing coordination between research and training centers with an emphasis on the participation of the national and regional levels, to formulate innovation policies adapted to a business environment. Full article

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

Here, changes in sustainability are assessed using statistical data for all countries between 1990 and 2015, with a focus on the fifteen most populous countries. The indicators used cover GDP for the economy; poverty, education, and health for human capabilities; as well as environmental impacts on water, climate, air, and bioresources. An authoritative model is used to describe the environmental impacts, resulting from pressures driven by population and affluence; and responses, through decreasing resource intensity, measured by the resource use per GDP, and improving environmental efficiency, defined as emissions per resource use. Resource intensity decreases in most countries. Environmental efficiency improves for wastewater and NOx, hardly changes for CO₂, and increases in nature protection areas, but this rarely compensates for deforestation. The combination of pressures and responses reduced water pollution and air pollution, and mitigated climate change in high-income countries, but did not reduce the degradation of biodiversity. While the pressures, responses, and environmental impacts of economic growth vary across all countries, twenty-five growing economies have reduced those environmental impacts. Changes toward sustainability are discussed with regard to the growing share of services in economies in the ‘EKC hypothesis’, innovation for achieving higher value at lower impact in the ‘green growth’ idea, and regulations that lead to profitable environmental investments in the ‘Porter hypothesis’. Combined, they only partially explain the changes because they ignore the low prices of natural resources and high shareholder consumption. Additionally, regulations are needed that increase the price of environmental impacts relative to the price of man-made resources and enforce high-quality performance standards. Full article

This article examines how intensifying geoeconomic rivalry reshapes European Union (EU) economic governance through the lens of economic security. In response to the fragmentation of the global economy and the politicisation of interdependence, the EU seeks to balance openness with the need to reduce strategic vulnerabilities. The study employs a concept-driven qualitative policy analysis based on the systematic examination of EU strategic and regulatory documents, complemented by interpretative analysis and analytically oriented comparison. Applying an original analytical framework, the study links systemic geoeconomic pressures, EU policy instruments and internal political-economy dynamics to explain the emergence of EU economic security as a hybrid governance model. The findings show that EU economic security does not emerge as a coherent doctrine but as a hybrid governance model combining the promotion of competitiveness, the protection of strategic assets and the development of partnerships. This model is shaped not only by external pressures but also by distributive effects, Member State preferences and institutional constraints. The analysis further identifies key trade-offs between efficiency and resilience, openness and control, and integration and fragmentation. The article concludes that EU economic security represents a structurally conditioned balancing process reflecting the adaptation of an open economic model to the conditions of increasing geoeconomic competition. In doing so, the article also contributes to debates on sustainable economic governance by showing how the EU’s pursuit of economic security affects long-term resilience, social cohesion and the normative foundations of its open economic model. Full article

Hungarian legislation—TÉKA 280/2024 and ÉKM 9/2023, effective January 2025—requires hospitality properties to install operational EV charging infrastructure. This study develops a techno-economic scenario model assessing DC Fast Charging (DCFC) powered by formic acid (HCOOH)-based proton-exchange membrane (PEM) fuel cell microgrids as an alternative to conventional grid-tied AC charging in energy-constrained rural tourism destinations. Three containerized HCOOH-PEM configurations (100 kW, 500 kW, 1 MW) are modelled using published technical parameters and secondary market benchmarks, and results are interpreted through Porter’s competitive advantage theory and Ritchie and Crouch’s destination competitiveness framework. All reported values are simulation outputs derived from predefined assumptions rather than empirically validated findings. Under these assumptions, the DC-HCOOH configuration projects annual EBITDA of €72,946 per unit (284% above the modelled AC baseline) with a comparable simple payback period, while ancillary guest spending during DCFC dwell-time (‘Charge and Spend’) is projected at roughly 5.3 times the AC level. Sensitivity scenarios show that payback estimates are highly responsive to CAPEX scope and ancillary-margin assumptions. Findings offer a conceptual basis for destination managers, investors, and policymakers, while underscoring the need for empirical validation with primary operational data. Full article

Against the backdrop of deepening global digital economic integration and intensifying geopolitical competition, cross-border data flow regulation has become a core institutional arrangement for coordinating development and security. Based on panel data from 31 Chinese provinces from 2015 to 2025, this study proposes an adapted provincial DFRI and a comprehensive resilience index, which together provide an operational foundation for examining the relationship between data regulation and industrial chain resilience across Chinese regions. It empirically examines the effects, transmission mechanisms, and configurational pathways through which regulation influences industrial chain resilience. The results show that cross-border data flow regulation significantly enhances the resilience of the core industrial chains of the digital economy. The balance between efficiency and security plays a key mediating role in the process through which regulation affects industrial chain resilience. Moreover, the regulatory effect exhibits significant heterogeneity in the level of digital economic development. The coefficient of REG is higher in provinces whose digital economy development index exceeds the sample mean than in provinces at or below the sample mean. Further, fuzzy-set qualitative comparative analysis (fsQCA) identifies four equivalent pathways through which regulatory improvement, infrastructure development, innovation investment, digital trade, and industrial compatibility jointly drive high resilience. The findings provide empirical evidence and policy implications for constructing regionally differentiated data governance systems and enhancing the resilience of China’s core digital economy industrial chains. Full article

Throughout primary and secondary education in the United States, science, technology, engineering, art, and mathematics (STEAM) education has become increasingly important as it promotes critical thinking skills and drives competition in the global economy. While some literature exists on teaching science to Deaf and hard of hearing (DHH) students, to date, few studies focus on teaching Deaf students with disabilities (DWD), particularly in STEAM subjects. In this study, we used a collaborative autoethnographic approach to document, reflect on, and modify the instructional approaches and assessment strategies we developed while working with DWD learners in our postsecondary science courses. We analyzed each strategy and categorized them into three areas: (1) facilitating environmental and physical access; (2) facilitating linguistic and cognitive access; and (3) facilitating formative and summative assessment access. We further categorized each strategy as to their potential applications to other science courses, STEAM courses, and/or more broadly. We present our findings as a description of each strategy, explaining how it was implemented and our observations of its outcomes for access, teaching and learning. We recognize that while our autoethnographic approach provides a rich accounting of these strategies, the efficacy of this study is limited by our individual and collective memory and the lack of consistent, formalized student feedback to further validate these findings. Therefore, we call for additional research to evaluate the efficacy and applicability of these and other instructional strategies across STEAM educational settings. Full article

This study demonstrates the rapid microwave-assisted upcycling of diverse bio-wastes—including aloe vera industrial leaf waste (av), corn cob agricultural residues (cc), and soft slaughterhouse (sh) by-products (pork liver, lung, and heart) into high-surface-area activated carbons for efficient hexavalent chromium removal via ZnCl₂-activated microwave pyrolysis. To process the challenging high-moisture animal organs, a hybrid approach combining microwave-assisted hydrothermal pre-treatment with subsequent ZnCl₂-activated microwave pyrolysis was developed to promote chemical dehydration and aromatic network development. Structural characterization by N₂ porosimetry, FT-IR, Raman, and XRD confirmed the formation of stable, amorphous porous networks, with surface development strongly dependent on both precursor type and pyrolysis temperature. The materials exhibited high specific surface areas (BET) of 1442, 1120, and 775 m²/g for cc, av, and sh, respectively, and they also demonstrated high water dispersibility. Cr(VI) adsorption data were best described by the Langmuir isotherm model, while thermodynamic analysis confirmed the spontaneous and endothermic adsorption process. The maximum adsorption capacities (qmax) at pH 3 were 157, 112, and 71 mg/g for the activated carbons derived from cc, av, and sh, respectively. Agricultural-derived carbons exhibited superior adsorption performance, whereas all materials remained competitive, demonstrating a potential sustainable circular-economy strategy for waste valorization. Full article

This study examines how non-interest income diversification affects bank performance and risk in selected emerging Asian economies. Drawing on panel data from 44 banks across China (36) and Thailand (8) over 2022–2025, the analysis employs fixed-effects regressions, mediation analysis, and subsample testing to unpack the performance implications of revenue diversification. The non-interest income ratio (NII) serves as the proxy for income diversification, capturing the strategic shift away from traditional net-interest margins toward fee-based and digitally facilitated activities in markets where mobile payment ecosystems and virtual banking frameworks have reshaped competitive dynamics. Results indicate that NII exerts a statistically significant positive effect on bank profitability (ROA and ROE), with no corresponding increase in risk exposure as measured by Z-score. The relationship is markedly stronger among large banks, consistent with scale advantages in technology infrastructure, network effects, and regulatory compliance cost amortization. Cost efficiency does not mediate the NII-performance nexus, suggesting that revenue-side mechanisms dominate in this context. Cross-country exploratory patterns reveal stable but modest effects in China’s mature diversification ecosystem against larger but statistically imprecise coefficients in Thailand’s early-stage transition. These findings offer a qualified complement to the Western-centric complexity-risk narrative and highlight institutional boundary conditions governing bank diversification outcomes in emerging markets. Full article