Search in Publications
Found 6289 publications
Preface II
Publication Name: World Sustainability Series
Publication Date: 2026-01-01
Volume: Part F1269
Issue: Unknown
Page Range: ix
Description:
No description provided
Open Access: Yes
DOI: DOI not available
INFLUENCE OF MEMORY EFFECTS ON HEAT AND MASS TRANSFER IN FRACTIONAL CASSON–BRINKMAN ELECTRICALLY CONDUCTING FLOW WITH RAMPED BOUNDARIES
Publication Name: Fractals
Publication Date: 2026-01-01
Volume: Unknown
Issue: Unknown
Page Range: Unknown
Description:
This work presents an analytical study of unsteady, one-dimensional magnetohydrodynamic flow of a Casson–Brinkman fluid over an infinite vertical plate, incorporating heat and mass transfer, internal heat generation, and a first-order chemical reaction. The plate velocity, temperature, and concentration are time-dependent, with ramped boundary conditions, and the governing equations account for a transverse magnetic field. Using Buckingham’s π-theorem, the model is nondimensionalized, introducing key parameters including the Grashof numbers, Hartmann number, Prandtl number, Schmidt number, Casson parameter, and Brinkman parameter. The classical Fourier and Fick laws are extended using the Caputo fractional derivative to capture memory effects, yielding a time-fractional model. The coupled fractional partial differential equations are solved analytically via Laplace transforms, and the effects of the fractional order and the physical parameters on the velocity, temperature, and concentration profiles are graphically analyzed. Results reveal that the fractional parameter significantly varies the heat and mass transfer profiles.
Open Access: Yes
Estimating agricultural sustainability: a multidimensional approach to a farm-level assessment tool
Publication Name: Frontiers in Environmental Science
Publication Date: 2026-01-01
Volume: 13
Issue: Unknown
Page Range: Unknown
Description:
Introduction: In response to the growing demand for practical and robust sustainability assessment tools, this study introduces a new method for evaluating agricultural sustainability at the farm level. The tool relies on indicators covering environmental, economic, and mixed dimensions of sustainability. The mixed dimension integrates environmental, economic, and social indicators. Methods: Indicators were selected based on the literature and empirical data from Hungarian farms. From 61 initial indicators, three groups were formed through factor analysis and clustering. Results: The analysis revealed that environmental and economic factors contribute almost equally to sustainability scores, whereas the mixed dimension has a comparatively smaller impact. This suggests that immediate sustainability improvements might need to prioritize environmental and economic factors. The assessment tool allows the calculation of a complex agricultural sustainability index, which has been validated through case studies on Hungarian farms. Discussion: This study is presented as a methodological pilot project to develop and test a farm-level sustainability assessment tool for agricultural enterprises. The results highlight the practical applicability of the tool for farmers and policymakers, as it offers a transparent, easy-to-use method for identifying sustainability strengths and weaknesses at the enterprise level. Limitations include a small, region-specific sample, which may restrict broader applicability. Additionally, there are challenges in integrating multidimensional indicators. Future research should focus on expanding the dataset, refining indicator weighting, and testing the tool’s applicability in a broader agricultural context. This enhances the robustness and guides stakeholders in sustainable agricultural development.
Open Access: Yes
Evolution of smart farming for the European Green Deal: A review of IoT, artificial intelligence and robotics in sustainable precision agriculture
Publication Name: Progress in Agricultural Engineering Sciences
Publication Date: 2026-01-01
Volume: Unknown
Issue: Unknown
Page Range: Unknown
Description:
Smart farming is constitutes a means of facilitating the European Green Deal and the Farm to Fork strategy. However, credible sustainability results require measurable and validatable indicators, verifiable data and automation that is reliable even under field conditions. This overview study presents developments in IoT-based sensing, artificial intelligence-based analysis and autonomous robotics, and links them to EU target areas. The peer-reviewed studies (2000–2025) were retrieved from the Scopus, Web of Science, and Google Scholar databases and supplemented with key EU legal and strategic documents. The article proposes a policy-driven digital agroecological management (PDAM) framework that establishes adaptable indicators based on past trends in EU targets (pesticides, nutrients, soil, biodiversity and climate) and then develops a system of perception-analysis-implementation based on these indicators. The most effective tools support GNSS-based machine control, variable rate application, and remote sensing, while AI-based decision support tools, autonomous weed control, and digital twin field validation are still weaker. Interoperability, data governance, cybersecurity and safety regulation emerge as critical scaling constraints for auditable smart farming systems.
Open Access: Yes
Operculate land snails (Gastropoda, Caenogastropoda, Cyclophoroidea) from Padang Bindu Karst, South Sumatra, Indonesia with the description of a new species, Chamalycaeus dayangmerindu
Publication Name: Zookeys
Publication Date: 2026-01-01
Volume: Unknown
Issue: 1272
Page Range: 1-31
Description:
The study on Cyclophoroidea from Padang Bindu Karst, South Sumatra, was conducted to document the species diversity of the superfamily in the area. The samples, including leaf litter and soil samples, were collected in May–June 2021 and followed by the determination and examination on 2023 to 2024 in the Museum Zoologicum Bogoriense. In total 3,780 specimens from the superfamily Cyclophoroidea were examined. Measurements of the shell and operculum were performed using L.A.S V4. 13.0 and IMAGE J. The research revealed 11 species from three families (Cyclophoridae, Diplomatinidae, Pupinidae) and four subfamilies. Plectostoma kitteli is the most abundant species followed by Stomacosmethis cf. jagori (19.84%) and Diplommatina liwaensis (6.67%). A new species, Chamalycaeus dayangmerindu Aulia & Nurinsiyah, sp. nov. is described. The study also discovered four species endemics to Sumatra with one species among them so far only recorded from Padang Bindu karst area. These findings emphasize the region’s unique biodiversity.
Open Access: Yes
Does generative AI affect firm sustainability and market performance? Implications for information systems practitioners
Publication Name: Journal of Enterprise Information Management
Publication Date: 2026-01-01
Volume: Unknown
Issue: Unknown
Page Range: Unknown
Description:
Purpose – The present study aims to examine how organisations adopt Generative AI and what are the key capabilities that influence the adoption of this technology. The study also investigates how Generative AI adoption influence market performance and sustainability performance. It additionally examines the moderating effect of regulatory support and organizational culture in influencing the association between Generative AI and firm performance. Design/methodology/approach – The study uses a mixed-methods design involving qualitative and quantitative data collection and analysis. The first stage begins with qualitative interviews followed by thematic analysis to establish leading capabilities behind Gen AI adoption, in the second stage, the data were collected from 385 respondents from different organizations which was then analysed using PLS-SEM structural equation modelling. Findings – The results observed that a firm’s digital transformation, innovation and marketing capabilities (MC) significantly enhance its Generative AI Adoption, which further influences firm performance. In addition, regulatory support emerges as a key moderator in driving DTC. Research limitations/implications – The findings emphasize that the firm should enhancing digital transformation capabilities, innovation capabilities and MC which can further strengthen the adoption of Generative AI and affect the firm market and sustainability performance. Whereas strengthening regulatory support can enhance the positive impact of DTC and Gen AI on firm sustainability performance. Originality/value – The study contributes to the literature on Generative AI by shaping an understanding of how the adoption of GenAI relates with the capability of firms in impacting sustainability performance. The research reports a critical gap in the literature by moving beyond the GenAI enthusiasm and assesses whether the advantages of adopting GenAI are durable as the technology diffuses across industries. The study contributes to literature by highlighting the role of regulatory support and determines that how environmental and firm-level factors jointly shape the effective and responsible capitalization of Generative AI for value creation over time.
Open Access: Yes
ELECTRICITY PRICE SHOCKS, RENEWABLE ENERGY PENETRATION, AND MACROECONOMIC STABILITY IN EUROPEAN COUNTRIES: EVIDENCE FROM THE 2022 ENERGY CRISIS
Publication Name: Economics and Sociology
Publication Date: 2026-01-01
Volume: 19
Issue: 1
Page Range: 250-275
Description:
The 2022 European energy crisis exposed the macroeconomic vulnerability of EU economies to electricity price shocks and raised urgent questions about the stabilising role of renewable energy penetration. This study examines in how far changes in electricity price components affect macroeconomic stability in Europe and whether renewable energy penetration has buffered these effects during the crisis period. Using a balanced panel of 29 European countries over 2019–2024, the analysis estimates the impact of log changes in electricity prices on a composite Macroeconomic Stability Index (MSI) using two-way fixed-effects models with crisis-year heterogeneous slopes, interaction terms, and two-way clustered standard errors. The results show that increases in non-household electricity prices are associated with statistically significant declines in macroeconomic stability, particularly in 2023 (β = −0.084, p < 0.01) and 2024 (β = −0.333, p < 0.05). A 10% rise in business electricity prices reduced the MSI by approximately 0.009–0.010 points in 2023 (around 4% of one standard deviation) and by about 0.029 points in 2024 (around 13% of one standard deviation). In 2022, the adverse effect was significant in low-renewables countries (ME = −0.056) but statistically insignificant in high-renewables countries, indicating short-run buffering. Joint tests confirm that crisis-period slope shifts (χ² = 30.576, p < 0.001) and renewable moderation effects (χ² = 8.603, p = 0.035) are statistically significant.
Open Access: Yes
Intuitionistic Fuzzy Best-Worst Method for Multi-Criteria Decision Making with Application in Health Care Resource Allocation
Publication Name: International Journal of Analysis and Applications
Publication Date: 2026-01-01
Volume: 24
Issue: Unknown
Page Range: Unknown
Description:
In the health care industry, decision-making is critical for determining the most efficient use of limited resources. Multi-criteria decision-making is a significant area that has been used to solve complex problems. To construct an accurate, adaptable, and sustainable framework for decision-making, an intuitionistic fuzzy best-worst method for multi-criteria decision-making in healthcare resource allocation is being developed. To understand the resource allocation mechanisms in different hospitals, the proposed methods employ a pairwise comparison of seven main criteria: infrastructure, consultancy time, paramedics, hospital stay, healthcare resource allocation, healthcare professionals’ satisfaction, and improvements in resource allocation. The weights calculated from the intuitionistic fuzzy best-worst method indicate that health professional satisfaction is the best criterion, whereas the consultancy time is the worst. The goal of this approach is to effectively handle the inherent ambiguity, complexity, and uncertainty that define problems with healthcare resource allocation. This methodology has a wide range of applications, including: hospital resource management, prioritizing patient care during peak times or emergencies such as pandemics, budgeting and financial planning, evaluating the cost-effectiveness of new treatments or technologies, public health planning, planning and executing community health interventions, strategic planning, and policy making.
Open Access: Yes
Risk Management for Road Projects in Mountainous Terrain: A Case Study of Learnings from the Himalayan Belt
Publication Name: World Sustainability Series
Publication Date: 2026-01-01
Volume: Part F1959
Issue: Unknown
Page Range: 473-497
Description:
Infrastructure projects, especially in emerging market countries, are critical to the economic and social development of the countries. The identification of key risk factors and their efficient management are critical to the success of such projects. The risk factors are often special in nature in a mountainous terrain. To investigate the same, we have studied the road highway projects in the Indian state of Himachal Pradesh, which is contiguous to the Himalayan mountains. This is a strategically as well as ecologically sensitive area, where the highway infrastructure needs to be developed with a sense of balance and appropriate risk management measures. Our in-depth study, using primary and qualitative research methods, has brought out several key risk factors, including those specific to mountainous terrain. We have used a comprehensive set of data sources including interviews of stakeholders, documents relating to the projects, and project images at the sites. We believe that our study on the road projects in the Himalayan belt is amongst the few major study focussed on the intersection of the risks in a large mountainous terrain and the demands of a fast-developing economy like India. Using our findings, we have made several specific and actionable recommendations to improve the risk management and bankability of the highway projects, especially in the large mountainous terrain and in emerging economies. Our study will inform policymakers, stakeholders, and investors, enhancing risk management and outcomes.
Open Access: Yes
