Search Results (35,883)

This paper explores whether the adoption of renewable energy has accelerated income catch-up in Central and Eastern Europe. The analysis is based on the conditional beta convergence theory, which posits that, after controlling for steady-state differences among countries, economies with lower initial incomes are expected to grow faster. This study uses balanced annual panel data from 11 Central and Eastern European countries between 2000 and 2024. The study distinguishes between two measures of renewable energy transition: renewable electricity production (REL) and renewable energy consumption (REN). The empirical study is conducted in three phases. First, descriptive statistics and convergence indicators are used to document the adoption of renewable energy. Second, income growth equations are estimated using pooled OLS models, fixed-effects models, and random-effects models. Finally, model selection and residual diagnostic tests are applied, including the F-test between pooled OLS and fixed-effects models, the Breusch–Pagan LM test, the Hausman test, and robustness tests based on cluster standard error and Driscoll–Kraay standard error. Other tests include panel unit root tests, substitution lag structure tests, outlier diagnostics, and a pre-specified two-year lag model. The results provide qualified support for conditional income convergence. In fixed-effects models, the coefficient for initial income is typically negative, indicating that lower-income countries tend to grow faster after accounting for structural differences. However, this finding weakens under the more demanding Driscoll–Kraay inferences, particularly in the REN model. In contrast, neither the renewable energy variables nor their interaction with initial income provide strong evidence that they have an independent impact on faster income catch-up. Overall, the renewable energy transition appears to be an accompanying rather than independent driver of income convergence. Full article

Digital transformation in international physical distribution is often constrained by fragmented customer, documentary, operational, fleet, cost, and financial information in transport firms operating in emerging economies. Although ERP and CRM systems have been widely studied, their integration is rarely operationalized as a measurable decision-support capability for Lean–Agile logistics. This article addresses this gap by proposing a KPI-based ERP–CRM framework structured around process-fragmentation diagnosis, ERP–CRM functional architecture, KPI operationalization, scenario-based comparison of digital integration configurations, and sensitivity analysis. The framework is evaluated through a case-based design science research approach using aggregated and anonymized company records from January to December 2025. KPIs cover commercial, documentary, operational, fleet, cost, financial, and documentation-related dimensions, and scenarios range from S0 baseline to S5 ERP–CRM with alerts. Under the defined scenario assumptions, the global performance index increases from 100.0 to 132.9, quotation cycle time decreases from 18.50 to 12.76 h, and operating cost decreases from USD 3.05 to 2.35 million. ERP-focused configurations improve documentary control, fleet coordination, and cost visibility, while CRM-focused configurations strengthen quotation management and customer responsiveness. Overall, integrated ERP–CRM coordination produces a more balanced KPI performance pattern and strengthens logistics–financial visibility, while green implications remain limited to documentation-related process outcomes. Full article

Water scarcity remains a major constraint to agricultural sustainability in Saudi Arabia, creating an urgent need to improve agricultural water productivity. This study examines long-run and short-run associations among national information and communication technology (ICT) infrastructure, national renewable-energy share, climatic conditions, and agricultural water productivity during 1995–2024. ICT infrastructure is represented by internet users, mobile cellular subscriptions, and fixed broadband subscriptions, while renewable energy consumption is examined both as an associated covariate and as a moderator of the ICT–water productivity relationship. Temperature and precipitation are incorporated as control variables. The analysis employs the ARDL approach to estimate long-run equilibrium relationships and short-run adjustment dynamics. The results show positive associations of the three ICT indicators, renewable energy consumption, and rainfall with agricultural water productivity, whereas temperature is negatively associated. The interaction analysis indicates that renewable energy is positively associated with the relationship between ICT infrastructure and agricultural water productivity. These results suggest that digital technologies and renewable energy are jointly associated with higher irrigation performance, improved water-use efficiency, and more sustainable agricultural development. The findings offer policy-relevant evidence for promoting digital infrastructure and renewable energy in Saudi Arabia and other water-scarce economies. Full article

The growing pressure of municipal waste generation and its associated environmental consequences has turned household participation into a central challenge for sustainable waste governance and circular-economy transition. This study adopts Cultural Additivity Theory and employs Bayesian Mindsponge Framework (BMF) analytics to examine how interactions between environmental–cultural and governance value bundles shape household willingness to pay (WTP) for improved urban waste management services, using survey data from 352 households in Hai Phong City, Vietnam. The results show that both the perceived importance of Commune Authorities and Women’s Unions are positively associated with WTP. More importantly, environmental perception and behavior further strengthen these governance–WTP associations, indicating that household financial support for improved waste management is greater when governance values interact with stronger environmental–cultural values. In contrast, higher environmental service satisfaction tends to weaken the positive association between governance importance and WTP. These findings suggest that household WTP is better understood as a relational outcome of interacting value bundles rather than as the product of isolated determinants operating independently. This study makes three contributions. First, it extends Cultural Additivity Theory into the field of urban environmental governance by demonstrating how interactions among value bundles shape household environmental decision-making. Second, it advances the waste-management literature by showing that environmental perception and environmental behavior become more influential when embedded within supportive governance and community structures. Third, it provides empirical evidence for developing community-based urban waste-management policies that integrate environmental communication, source-separation initiatives, local governance, and women-led community engagement to strengthen public participation and support sustainable urban waste-management systems. Full article

Rwanda’s sustainable green economy agenda has placed irrigation and input-support schemes at the centre of efforts to raise tropical fruit productivity in the Mugesera region, yet the econometric analysis presented, in a Cobb–Douglas production function estimated by panel OLS and a Nerlove partial-adjustment model of agricultural supply response required the analyst to pre-specify a log-linear, constant-elasticity functional form. This paper asks whether machine learning methods that learn input–output relationships directly from data can cross-check those findings, and presents a documented Python version 3.10.12 pipeline for doing so. Using a synthetic panel dataset (six regions, 2009–2018, N = 346 farm-year observations) calibrated to match the elasticity magnitudes reported in the original Cobb–Douglas estimation, three models—multiple linear regression, random forest, and gradient boosting—are trained on land, fertilizer, seed, lagged price, and lagged output features, and are evaluated on held-out data. All three models explain a substantial share of variation in output (R² between 0.72 and 0.75 under a random split; for results under panel-aware validation), with tuned gradient boosting achieving the best accuracy under the random split (R² = 0.751, RMSE = 0.268). Permutation feature importance recovers the same relative ranking of input variables as the original regression—fertilizer, then seeds, then land area—without the model being given the Cobb–Douglas functional form in advance. Because the synthetic data were explicitly generated to reproduce these elasticities, this recovery demonstrates that the modelling pipeline behaves as intended; it is a calibrated methodological demonstration and not an independent empirical validation of the original findings. The results are consistent with lagged price and output operating mainly through farmers’ input decisions rather than as direct predictors of output once input quantities are known, although we present this as a hypothesis for future testing rather than a demonstrated finding. Re-running the identical pipeline on real Mugesera farm-level survey microdata is the necessary next step before these results can be treated as genuine empirical findings; this caveat applies to every quantitative result reported below, not only to the conclusion. Full article

This paper examines the relationship between perceived event quality and visitor loyalty in the context of a river-based sport tourism event. This study examines visitors at the Danube Regatta in Negotin, a small-scale sport-tourism event integrated into the international Danube International Regatta. Drawing on event quality and experience economy frameworks, the study analyses the effects of four dimensions of perceived quality-organizational arrangements, program and atmosphere, environmental care, and infrastructure on visitors’ loyalty, operationalized through revisit intention and recommendation. The authors collected data through an on-site survey of 217 event visitors during the 2025 edition of the event. The analysis employed descriptive statistics, Spearman’s correlation, multiple linear regression, and cluster analysis (K-means). The results show that program and atmosphere represent the strongest predictors of visitor loyalty (β = 0.734, p < 0.001), confirming the dominant role of experiential elements. Organizational arrangements (β = 0.196, p < 0.01) and infrastructure (β = 0.203, p < 0.01) also exert statistically significant positive effects, suggesting their role as supporting conditions rather than primary drivers of loyalty. In contrast, perceived environmental care has a statistically significant negative effect (β = −0.240, p < 0.01), indicating a potentially complex sustainability-related relationship whereby perceived shortcomings in environmental practices reduce loyalty intentions. Cluster analysis identified four distinct visitor segments, highlighting heterogeneous visitor behavior motives and behavioral patterns among event participants. The findings add to the existing literature by providing empirical support for a multidimensional event quality–visitor loyalty framework in the context of small-scale river-based sport events. The study highlights the primacy of experiential components while emphasizing the need for more visible and effective environmental management practices in nature-based events. Full article

With the rapid expansion of the low-altitude economy, detecting micro unmanned aerial vehicles (UAVs) in complex urban environments faces severe challenges. In optical surveillance, micro-UAVs typically appear as weak and small targets lacking distinct spatial semantics, rendering conventional appearance-based feature extraction highly ineffective. Furthermore, extreme lighting conditions and complex backgrounds easily submerge these subtle textures into noise. While event cameras can uniquely capture the high-frequency rotational characteristics of UAV rotors thanks to their microsecond temporal resolution, their sparse asynchronous outputs are highly susceptible to environmental clutter. To address this, we propose EGDNet, an event-guided frequency-aware dual-modal detection network optimized for robust UAV sensing. First, we developed a custom co-axial beam-splitting hardware platform to construct a strictly pixel-aligned dual-modal dataset of 43,090 frames, eliminating inter-modal parallax at the physical level. Second, our framework introduces a novel frequency-domain deconstruction pipeline utilizing a Temporal Fast Fourier Transform (T-FFT) to isolate the high-frequency mechanical rotor vibrations from low-frequency background clutter. Additionally, a Cross-Modal Synergistic Enhancement Module (CMSEM) and a Cross-Scale Adaptive Fusion Pyramid Network (CSAFPN) are designed to leverage event-derived high-frequency details for RGB feature restoration and to preserve sub-pixel target signatures during deep downsampling. Experimental results demonstrate that EGDNet achieves a mean average precision of 74.63% (AP@0.5) and an F1 score of 78.57%, significantly outperforming state-of-the-art fusion architectures. This work provides a robust visual perception solution for intelligent low-altitude surveillance. Full article

This study investigates the feasibility of utilizing stone dust waste, an industrial by-product generated during ornamental-stone quarrying processing, as a raw material for 3D-printing mortar. This approach reduces waste disposal and promotes a circular economy. Several high-strength cementitious mixtures were screened and optimized by varying raw materials as a function of slump flow evolution over time, which served as indirect assessment of open time and extrudability. Following the identification of the most suitable mixture for 3D printing, one of the raw materials (an ultrafine limestone filler) was subsequently replaced on a 1:1 mass basis with stone waste, selected due to its comparable particle-size distribution, to assess its feasibility as an alternative filler. Fresh-state properties were evaluated based on flowability, with slump values ranging from 16 cm to 13 cm over time, and extrusion tests on a screw pump, used to validate extrusion stability and shape retention. Hardened-state properties were determined at different curing ages. The incorporation of Apricena stone waste resulted in similar fresh-state and extrusion behaviour of mortar, without additional changes to the mix design, and the intended 30 min qualitative extrusion window was met. At 28 days, the mixture incorporating stone dust waste achieved flexural and compressive strength of 12.51 MPa and 79.72 MPa. The incorporation of stone dust waste resulted in an extrudable mixture for 3D printing, with the intended open time and fresh-state behaviour, as well as mechanical properties complying with high-strength applications. However, the full replacement of one of the limestone fillers led to an 8% reduction in 28-day compressive strength. Overall, the findings demonstrate that the recovery of stone dust slurry as viable supplementary cementitious material for 3D-printed concrete is viable. The data support the use of this stone waste as a raw material for 3D printing, and specific mortar development and mix optimization for different applications are recommended, including the quantitative assessment of buildability, printed mechanical properties, durability, and leaching and life-cycle assessment. Full article

Population aging in Asia is arriving before the institutions to support it. Assessments of social protection usually treat sustainability, adequacy and fairness separately, obscuring how they trade off within one system. This study introduces NTA-SAFE, five indicators derived from the National Transfer Accounts lifecycle identity, applied to Japan, South Korea, Thailand, the Philippines and Indonesia. Base-year per capita profiles are combined with UN World Population Prospects 2024 populations through 2050, so all movement reflects age structure alone; results are reported across all five WPP series as a demographic sensitivity range. An explicit two-part rule classifies each economy by who provides net transfers to its elderly and by demographic stage. Japan and South Korea are state-led; the Philippines and Indonesia are family-asset-led, retaining the fiscal headroom of young populations. Thailand is transitional and the substantive case, carrying the demographic and fiscal exposure of a state-led system while families supply 78% of net transfer support to its elderly. Thai elderly consumption sits near working-age parity: the exposure lies not in current living standards but in the institutional basis on which they rest. Direction of change is robust in 24 of 25 country-indicator combinations. Higher benefit generosity is consistently associated with a narrower fiscal base, as a budget constraint implies, though five cases cannot establish universality. Whether family-mediated support reproduces life-course inequality into old age is a hypothesis the framework can pose but not test, the accounts carrying no distributional data. Indonesia’s classification is provisional, its profile predating the 2014 health insurance reform. NTA-SAFE is replicable wherever National Transfer Accounts exist. Full article

Reducing ordinary Portland cement (OPC) content through waste-derived binders can improve the resource efficiency of mortar and concrete. This study explores the effect of single and combined replacement of ordinary Portland cement (OPC) with ceramic waste powder (CWP) and calcium carbide residue (CCR), with the original contribution being the systematic mixture-design evaluation of a ternary OPC–CWP–CCR binder using mixture design and an integrated assessment of mechanical and durability-related performance. Ten mixes with varying mixture proportions were designed using the mixture design of experiments (DoE). Fresh and hardened properties were evaluated, including flowability, compressive strength, bulk resistivity, and water absorption tests up to 56 days, while chemical durability was assessed by exposure to 5% sulfuric acid. OPC replacement with CCR and CWP reduced early-age strength due to dilution; however, CWP-dominant blends exhibited late-age strength gain. The mixture containing 26.7% CWP and 6.7% CCR reached 44.7 MPa at 90 days and 406.7 Ω·m at 56 days and exhibited the lowest relative strength loss after sulfuric acid exposure (12.8%, versus 16.0% for the control). High CCR contents adversely affected workability, water absorption, strength, and acid resistance. CWP-dominant blends provided the best overall balance of performance and OPC reduction. Full article

Background: The transition from conventional waste management to circular economy systems has generated more interest in how artificial intelligence (AI) can enhance waste prevention, sorting and recycling, optimization, and resource recovery. Owing to the growing complexity and data-driven nature of waste systems, AI has been used to aid operational and strategic decisions throughout the waste management chain. Methods: This study is a systematic review of the literature between 2016 and 2026 on AI in waste management in the circular economy, conducted according to the PRISMA 2020 guidelines based on three directions: AI application, optimization techniques, and recovery routes of resources. In this systematic review, 52 studies were included through systematic database searches, eligibility screening, clear inclusion criteria, and thematic synthesis of the literature to identify the key research areas of AI techniques, optimization strategies, and resource recovery pathways in the circular economy and waste management. Results: The review shows that optimization is the key to implementing the principles of the circular economy in waste management decision-making, and that AI is no longer seen as a taboo topic in the literature but as a functional application. System-level integration and the integration of systems in a holistic circular economy are not yet fully consolidated. To overcome the limitations of single-application studies, an Integrative AI–Circular Waste Value Chain (AI-CWVC) framework is proposed. Conclusions: This review highlights the importance of AI in supporting circular waste management and points to the need for further research that is more integrated, evidence-based, and policy-aligned. Full article

The rapid digitalization of public administration has transformed auditing environments, especially in emerging economies expanding their electronic governance (e-governance) frameworks. This study identifies and prioritizes the key drivers influencing electronic auditing (e-auditing) development in Iraq over the next decade. Using a mixed-methods design, the research first identifies potential drivers through qualitative interviews and open-ended questionnaires. These drivers were then evaluated and prioritized via a two-round Delphi survey involving a purposive panel of 20 experts, including senior auditors, accounting academics, and IT-audit specialists with over 15 years of professional experience. The analysis identified 19 significant drivers categorized into four clusters: (1) emerging audit technologies, (2) information security and data quality, (3) e-governance and transparency, and (4) professional capabilities. Results highlight that technological innovations, specifically real-time monitoring and machine learning, are the most influential drivers. Furthermore, cybersecurity and transparent governance mechanisms are identified as essential pillars for digital auditing in the Iraqi context. By providing a foresight perspective in a post-conflict, emerging economy, this study offers a unique conceptual framework that integrates e-governance maturity with auditing evolution. The findings provide actionable insights for policymakers and regulatory bodies to modernize auditing practices in high-uncertainty environments. Full article

This article examines the cartographic design of nano-scale productive systems led by women nano-entrepreneurs, understood as family-based productive arrangements embedded in everyday domestic spaces. In rural contexts, many women-led ventures operate at a nano-scale and are organized around household dynamics, where entrepreneurial leadership, family labor, and productive activities intersect. Drawing on a qualitative territorial research approach, the study combines semi-structured interviews, fieldwork, and cartographic design to identify productive actions and the spaces in which they take place. The findings show that these nano-scale productive systems function through the articulation of multiple actions rather than formal organizational structures, and that women exercise entrepreneurial leadership by coordinating family-based activities within and beyond the home. As a result, everyday spaces, particularly the household, are resignified as workshops, points of sale, and centers of management, giving rise to locally embedded family-based enterprises in emerging rural economies. Using cartographic design as an analytical tool, the article contributes to research on family entrepreneurship and leadership by highlighting how women-led nanoenterprises reshape spatial organization, and productive practices within emerging family firms. Full article

Fish is a food of high nutritional value, being an important source of proteins, fat, vitamins, and essential minerals. Atlantic horse mackerel is also rich in omega-3 polyunsaturated fatty acids (n3-PUFAs), recognized for their benefits to cardiovascular and neurological health. However, this composition also makes it highly susceptible to lipid oxidation, reducing its shelf life. Oxidation is accelerated by high water activity and near-neutral pH, conditions common in fish and processed products such as fish burgers. This work aimed to develop fish burgers incorporated with bioactive extracts (protein hydrolysates from cod fish processing by-product—PH, or green tea extract—GTE) and study their shelf life. The PH was recovered from cod frames using subcritical water extraction, and GTE with hydro-alcoholic extraction. The fish burgers were prepared using minced fish meat incorporated with 1% (w/w) of extracts, in four formulations: (i) 1% (w/w) of PH; (ii) 1% (w/w) of GTE; (iii) a combination of both extracts at 0.5% (w/w) each; and (iv) control without extracts. Physical–chemical, antioxidant and microbiological analysis of the burgers was performed to evaluate their preservation over 6 days of refrigerated storage. Compared to the control, samples with only GTE or the combined GTE + PH presented a delay in oxidation (50% less in TBARS) and microbiological deterioration (reduction of 0.5–1.8 Log CFU/g in total psychrotropic microorganisms). No significant changes were observed in the fish burgers incorporated with only PH. The results demonstrate that the incorporation of bioactive extracts has potential in reducing oxidative degradation and improving microbiological stability in fish-based products; however, superior doses must be used. Moreover, the use of natural extracts aligns with current consumer demand for clean-label and functional foods. Full article

Carbon balance capacity (CBC) and urban–rural integration (URI) represent two interconnected systems involving ecological sustainability and socioeconomic development. Understanding their interactions is essential for advancing low-carbon development, yet the spatial heterogeneity and directional relationships between these systems remain insufficiently explored. Using panel data for 30 Chinese provinces from 2005 to 2024, this study measures CBC by assessing the relative capacity of regional carbon absorption to balance carbon emissions and constructs URI as a composite index based on a five-dimensional indicator system covering population, economy, space, society, and ecology. Exploratory spatial data analysis (ESDA) and the Dumitrescu–Hurlin panel Granger causality test are then applied to examine the spatiotemporal dynamics and directional relationships between CBC and URI. The results show that carbon emissions exhibit an increasingly pronounced “high East–low West” pattern, whereas carbon absorption maintains a relatively stable “high West–low East” distribution. Accordingly, CBC shows a contraction of high-value regions and increasing concentration of carbon balance advantages in ecologically endowed provinces. Meanwhile, URI has improved continuously, with spatial, ecological, and social dimensions becoming increasingly important, while economic integration remains relatively limited. Granger causality analysis reveals substantial heterogeneity in CBC–URI interactions, with decoupling as the dominant pattern, while some regions exhibit development-related pressures or ecological constraints during urban–rural transformation. Positive interaction pathways, where urban–rural integration contributes to improvements in carbon balance capacity, are identified only in a limited number of regions, indicating diverse evolutionary pathways between urban–rural transformation and carbon balance capacity. This study further develops a typological framework and identifies differentiated development pathways toward more coordinated CBC–URI interactions, providing empirical evidence and policy insights for place-based low-carbon urban–rural transformation. Full article