Search Results (1,042)

As the global energy transition accelerates, the integration of solar power and artificial intelligence (AI) technologies offers new pathways for sustainable local development. This study examines four Serbian municipalities—Šabac, Sombor, Pirot, and Čačak—to assess how AI-enabled solar power systems can enhance energy resilience, reduce emissions, and support community-level sustainability goals. Using a mixed-method approach combining spatial analysis, predictive modeling, and stakeholder interviews, this research study evaluates the performance and institutional readiness of local governments in terms of implementing intelligent solar infrastructure. Key AI applications included solar potential mapping, demand-side management, and predictive maintenance of photovoltaic (PV) systems. Quantitative results show an improvement >60% in forecasting accuracy, a 64% reduction in system downtime, and a 9.7% increase in energy cost savings. These technical gains were accompanied by positive trends in SDG-aligned indicators, such as improved electricity access and local job creation in the green economy. Despite challenges related to data infrastructure, regulatory gaps, and limited AI literacy, this study finds that institutional coordination and leadership commitment are decisive for successful implementation. The proposed AI–Solar Integration for Local Sustainability (AISILS) framework offers a replicable model for emerging economies. Policy recommendations include investing in foundational digital infrastructure, promoting low-code AI platforms, and aligning AI–solar projects with SDG targets to attract EU and national funding. This study contributes new empirical evidence on the digital–renewable energy nexus in Southeast Europe and underscores the strategic role of AI in accelerating inclusive, data-driven energy transitions at the municipal level. Full article

The water sector is facing a convergence of systemic challenges generated by climate change, increasing demand, and increasingly stringent regulations, which threaten its operational and strategic sustainability. In this context, the article examines how ESG (environmental, social, governance) principles are integrated into the governance, financing, and management of water resources, with a comparative focus on Romania and the European Union. It aims to assess the extent to which ESG practices contribute to the sustainable transformation of the water sector in the face of growing environmental and socio-economic challenges. The methodology is based on a systematic analysis of policy documents, regulatory frameworks, and ESG standards applicable to the water sector at both national (Romania) and EU levels. This study also investigates investment strategies and their alignment with the EU Taxonomy for Sustainable Activities, enabling a comparative perspective on implementation, gaps and strengths. Findings reveal that while ESG principles are increasingly recognized across Europe, their implementation remains uneven (particularly in Romania) due to unclear standards, limited funding mechanisms, and fragmented policy coordination. ESG integration shows clear potential to foster innovation, improve governance transparency, and support long-term resilience in the water sector. These results underline the need for coherent, integrated policies and stronger institutional coordination to ensure consistent ESG adoption across Member States. Policymakers should prioritize the development of clear guidelines and supportive funding instruments to accelerate sustainable outcomes. The originality of our study lies in its comparative approach, offering an in-depth analysis of ESG integration in the water sector across different governance contexts. It provides valuable insights for advancing policy coherence, investment alignment, and sustainable water resource management at both national and European levels. Full article

Urban areas are responsible for most of Europe’s energy demand and emissions and urgently require building retrofits to meet climate neutrality goals. This study evaluates the energy efficiency potential of three public school buildings in western Macedonia, Greece—a cold-climate region with high heating needs. The buildings, constructed between 1986 and 2003, exhibited poor insulation, outdated electromechanical systems, and inefficient lighting, resulting in high oil consumption and low energy ratings. A robust methodology is applied, combining detailed on-site energy audits, thermophysical diagnostics based on U-value calculations, and a techno-economic assessment utilizing Net Present Value (NPV), Internal Rate of Return (IRR), and SWOT analysis. The study evaluates a series of retrofit measures, including ceiling insulation, high-efficiency lighting replacements, and boiler modernization, against both technical performance criteria and financial viability. Results indicate that ceiling insulation and lighting system upgrades yield positive economic returns, while wall and floor insulation measures remain financially unattractive without external subsidies. The findings are further validated through sensitivity analysis and policy scenario modeling, revealing how targeted investments, especially when supported by public funding schemes, can maximize energy savings and emissions reductions. The study concludes that selective implementation of cost-effective measures, supported by public grants, can achieve energy targets, improve indoor environments, and serve as a replicable model of targeted retrofits across the region, though reliance on external funding and high upfront costs pose challenges. Full article

Unbalanced accelerations occurring during tram travel have a significant impact on passenger comfort and safety, as well as on the rate of wear and tear on infrastructure and rolling stock. Ideally, these dynamic forces should be monitored continuously in real-time; however, traditional systems require high-precision accelerometers and proprietary software—investments often beyond the reach of municipally funded tram operators. To this end, as part of the research project “Accelerometer Measurements in Rail Passenger Transport Vehicles”, pilot measurement campaigns were conducted in Poland on tram lines in Gdańsk, Toruń, Bydgoszcz, and Olsztyn. Off-the-shelf smartphones equipped with MEMS accelerometers and GPS modules, running the Physics Toolbox Sensor Suite Pro app, were used. Although the research employs widely known methods, this paper addresses part of the gap in affordable real-time monitoring by demonstrating that, in the future, equipment equipped solely with consumer-grade MEMS accelerometers can deliver sufficiently accurate data in applications where high precision is not critical. This paper presents an analysis of a subset of results from the Gdańsk tram network. Lateral (x) and vertical (z) accelerations were recorded at three fixed points inside two tram models (Pesa 128NG Jazz Duo and Düwag N8C), while longitudinal accelerations were deliberately omitted at this stage due to their strong dependence on driver behavior. Raw data were exported as CSV files, processed and analyzed in R version 4.2.2, and then mapped spatially using ArcGIS cartograms. Vehicle speed was calculated both via the haversine formula—accounting for Earth’s curvature—and via a Cartesian approximation. Over the ~7 km route, both methods yielded virtually identical results, validating the simpler approach for short distances. Acceleration histograms approximated Gaussian distributions, with most values between 0.05 and 0.15 m/s², and extreme values approaching 1 m/s². The results demonstrate that low-cost mobile devices, after future calibration against certified accelerometers, can provide sufficiently rich data for ride-comfort assessment and show promise for cost-effective condition monitoring of both track and rolling stock. Future work will focus on optimizing the app’s data collection pipeline, refining standard-based analysis algorithms, and validating smartphone measurements against benchmark sensors. Full article

The scientific investment decision of Park-level Integrated Energy System (PIES) projects is of great significance to energy enterprises for improving the efficient utilization of funds, promoting green and low-carbon transformation, and achieving the goal of carbon neutrality. This paper proposed a two-stage investment framework that integrates a multi-objective 0–1 programming model with a multi-criteria decision-making (MCDM) technique to determine the optimal PIES project investment portfolios under the constraint of quota investment. First, a multi-objective (MO) 0–1 programming model was constructed for typical PIES projects in Stage-I, which considers economic and environmental benefits to obtain Pareto frontier solutions, i.e., PIES project portfolios. Second, an evaluation index system from multiple dimensions was established, and a hybrid MCDM technique was adopted to comprehensively evaluate the Pareto frontier solutions in Stage-II. Finally, the proposed model was applied to an empirical case, and the simulation results show that the decision framework can achieve the best overall benefit of PIES project portfolios with maximal economic benefit and minimum carbon emissions. In addition, the robustness analysis was performed by changing the indicator weights to verify the stability of the proposed framework. This research work could provide a theoretical tool for investment decisions regarding PIES projects for energy enterprises. Full article

This study conducts a comprehensive systematic review of the economic impact of Digital Twin (DT) technology within the Architecture, Engineering, and Construction (AEC) industry, following the PRISMA methodology. While DT adoption has been accelerated by advancements in Building Information Modelling (BIM), the Internet of Things (IoT), and data analytics, significant challenges persist—most notably, high initial investment costs and integration complexities. Synthesising the literature from 2016 onwards, this review identifies sector-specific barriers, regulatory burdens, and a lack of standardisation as key factors constituting DT implementation costs. Despite these hurdles, DTs demonstrate strong potential for enhancing construction productivity, optimising lifecycle asset management, and enabling predictive maintenance, ultimately reducing operational expenditures and improving long-term financial performance. Case studies reveal cost efficiencies achieved through DTs in modular construction, energy optimisation, and infrastructure management. However, limited financial resources and digital skills continue to constrain the uptake across the sector, with various extents of impact. This paper calls for the development of unified standards, innovative public–private funding mechanisms, and strategic collaborations to unlock and utilise DTs’ full economic value. It also recommends that future research explore theoretical frameworks addressing governance, data infrastructure, and digital equity—particularly through conceptualising DT-related data as public assets or collective goods in the context of smart cities and networked infrastructure systems. Full article

The future of marine sustainability depends on public understanding and trust in the policy recommendations that emerge from scientific research. For common pool marine resource decisions made by the people who depend on these resources for their food, employment, and economic future, understanding the current status of these marine systems and change is essential to ensure these resources will persist into the future. As such, the informal learning infrastructure is essential to increasing marine science literacy in a changing world. This mixed-methods research study analyzed the distribution and accessibility of marine science education and research across Alaska’s five geographic regions. Using the PRISMA framework, we synthesized data from 198 institutions and analyzed peer-reviewed literature on marine ecosystems to identify geographic and thematic gaps in access to informal science learning and research focus. In parallel, we undertook geospatial analysis and resource availability to describe the distribution of resources, types of informal learning infrastructure present across the state, regional presence, and resources to support informal marine science learning opportunities. Findings from this multifactor research revealed a concentration of resources in urban hubs and a lack of consistent access to learning resources for rural and Indigenous communities. The configurative literature review of 9549 publications identified topical underrepresentation of the Bering Sea and Aleutian Islands, as well as a lack of research on seabirds across all regions. Considered together, these results recommend targeted investments in rural engagement with marine science programming, culturally grounded partnerships, and research diversification. This review concludes that disparities in learning resource support and government-funded priorities in marine wildlife research have created conditions that undermine the local people’s participation in the sustainability of sensitive resources and are likely exacerbating declines driven by rapid change in Arctic and sub-Arctic waters. Full article

The UI GreenMetric World University Ranking has become a widely adopted instrument for benchmarking institutional sustainability performance; nevertheless, empirically grounded evidence from universities in diverse regional contexts remains scarce. This study undertakes a rigorous appraisal of the extent to which Mahasarakham University (MSU) has institutionalized the United Nations Sustainable Development Goals (SDGs) within its pedagogical offerings, research portfolio, community outreach, and governance arrangements during the 2021–2024 strategic cycle. Employing a mixed-methods design and guided by the 2024 UI GreenMetric Education and Research indicators, this investigation analyzed institutional datasets pertaining to curriculum provision, ring-fenced research funding, 574 peer-reviewed sustainability publications, student-led community initiatives, and supporting governance mechanisms; the analysis was interpreted through a Plan–Do–Check–Act management lens. The number of sustainability-oriented academic programs expanded from 49 to 58. Student participation in community service activities strongly recovered following the COVID-19 pandemic, and MSU’s GreenMetric score increased from 7575 to 8475, thereby elevating the institution to the 100th position globally. These gains were facilitated by strategic SDG-aligned investment, cross-sector collaboration, and the consolidation of international partnerships anchored in Thailand’s Isaan region. The MSU case provides a transferable model for universities—particularly those operating in resource-constrained contexts—endeavoring to align institutional development with the SDGs and internationally recognized quality benchmarks. The findings substantiate the capacity of transformative education and applied research to engender enduring societal and environmental benefits. Full article

Objectives: This study evaluates the economic impact of digital health interventions (DHIs) developed under the HosmartAI EU-funded program, focusing on obstetrics, cardiology, and gastroenterology. Methods: A Cost Consequence Analysis (CCA) was chosen in order to be able to examine the costs and consequences of AI technologies in early diagnosis of preterm births, echocardiography, coronary computed tomography angiography (CCTA), and capsule endoscopy (CE). Results: The results show that in obstetrics and CCTA, the AI technologies are cost-saving, with the AI-based preterm birth detection leading to savings of 99,840 EUR due to reduced severity of prematurity. In the echocardiography scenario, the new AI technology slightly increased costs (9409 vs. 2116 EUR), but offered benefits in diagnostic accuracy and shorter interpretation duration, particularly for less experienced physicians. Similarly, the capsule endoscopy AI technology raised annual costs by 6626 EUR but improved productivity, accuracy, and user satisfaction. Conclusions: The findings emphasize the need for standardized frameworks to guide economic evaluations of DHIs, ensuring informed healthcare investment and reimbursement decisions in the future. Full article

Debt financing is important for financing major investments in the biopharmaceutical industry. Debt financing allows companies to raise funds without giving up ownership or control through indenture and covenants of the company. In this study, I analyze the effects of debt financing decisions on profitability in the biopharmaceutical industry. I find that short-term debt, long-term debt, and total debt negatively impact the return on assets (ROA) as a firm’s profitability measure. A comparison is made between American and European biopharmaceutical firms, and the result shows the negative effects of short-term and long-term debt on profitability persist more for US biopharmaceutical firms than European firms. Short-term and long-term debt both impact profitability negatively with 10-year lagged R&D intensity and financial distress. Short-term debt’s negative impact is stronger post-COVID-19, indicating increased financial strain. Long-term debt consistently affects profitability negatively, with relatively stable effects during the pre- and post-COVID-19 pandemic. Full article

Background/Objectives: Reducing waiting times for elective surgeries remains a critical global healthcare challenge that negatively impacts patient outcomes and economic productivity. This study develops an adaptable cost-utility modeling framework for assessing the cost-effectiveness (CE) of reducing waiting time for elective surgeries in data-limited environments. Methods: We evaluated the economic and health impacts of Egypt’s recent initiative aimed at decreasing surgical waiting lists. The study conducts a CE analysis of the initiative by estimating incremental costs (expressed in Egyptian Pounds—EGP) and outcomes (expressed in quality-adjusted life years—QALYs) before and after its implementation, performs a benefit–cost analysis to quantify the initiative’s return on investment, and employs a budget share method to evaluate catastrophic health expenditure (CHE). The analysis included five elective surgical interventions: open-heart surgery, cardiac catheterization, cochlear implantation, ophthalmic surgery, and orthopedic (joint replacement) surgery. Results: The main research outcomes of the study are as follows. The initiative resulted in incremental cost-effectiveness ratios of EGP 46,795 (societal perspective) and EGP 56,094 (payer perspective) per QALY, both within acceptable CE thresholds. Most of the evaluated interventions demonstrated substantial returns on the investment. Without public funding, more than 90% of patients faced CHE, indicating considerable financial barriers to elective surgeries. Conclusions: Egypt’s initiative to reduce waiting times was deemed cost-effective. Our adaptable modeling framework could be practical for similar evaluations in low/middle-income countries, especially where data is limited. Scaling up the initiative to include additional curative and preventive services and integrating it with broader health system reforms in Egypt is strongly recommended. Full article

Determining the optimal portfolio is important in the investment process because it includes the selection of appropriate fund allocation to manage financial risk effectively. Although risk cannot be entirely eliminated, it is managed through strategic allocation based on investor preferences. Therefore, this research aimed to use mathematical models, including the power utility function, the natural logarithm utility function, and a combination of both, to capture varying degrees of risk aversion. The optimal allocation was obtained by analytically maximizing the expected end-of-period wealth utility under each specification, where the investor level of risk aversion was derived by determining the constant. The utility function that failed to produce closed-form solutions was solved through the use of a numerical method to approximate the optimal portfolio weight. Furthermore, numerical simulations were performed using data from two stocks in the e-commerce sector to prove the impact of parameter changes on investment decisions. The result showed explicit analytical values for each utility function, providing investors with a structured framework for determining optimal portfolio weights consistent with their risk profile. Full article

Specialized and special new “little giant” enterprises are characterized by specialization, refinement, uniqueness, and innovation. They have relatively strong innovation capabilities and enterprise vitality. However, they also face problems such as high innovation costs, long investment recovery cycles, and high risks of investment returns, which lead to information asymmetry and financing difficulties. Government venture capital is a policy fund provided by the government and established with the participation of local governments, financial institutions, and private capital. They can utilize fiscal policies to attract market funds and support the development of key industries. Therefore, in this study, the first through sixth batches of specialized and special new “little giant” enterprises listed on the A-share and New Third Board from 2013 to 2023 were taken as samples, and their investment behavior and investment effects were empirically studied using the multiple linear regression method. The investment behavior of government venture capital tends to target strategic emerging industries. The intervention of government venture capital can enhance the innovation of “little giant” enterprises and has an impact through the intermediary mechanism of R&D investment. This paper draws conclusions and puts forward relevant policy suggestions for supporting the development of “little giant” enterprises. Full article

The 83rd session of the IMO Maritime Environment Protection Committee (MEPC 83) approved a global pricing mechanism for the shipping industry, with formal adoption scheduled for October 2025. Proposed mechanisms include the International Maritime Sustainable Fuels and Fund (IMSF&F) and a combined approach integrating GHG Fuel Standards with Universal GHG Contributions (GFS&UGC). This study developed a model based on the marginal abatement cost curve (MACC) methodology to assess the cost-effectiveness of alternative fuels under both mechanisms. Sensitivity analyses evaluated the impacts of fuel prices, carbon prices, and the GHG Fuel Intensity (GFI) indicator on MAC. Results indicate that implementing the GFS&UGC mechanism yields higher net present values (NPVs) and lower MACs compared to IMSF&F. Introducing universal GHG contributions promotes a comparatively fairer transition to sustainable shipping fuels. Investments in zero- or near-zero-fueled (ZNZ) ships are unlikely to be recouped by 2050 unless carbon prices rise sufficiently to boost revenues. Bio-Methanol and bio-diesel emerged as the most cost-competitive ZNZ options in the long term, while e-Methanol’s poor competitiveness stems from its extremely high price. Both pooling costs and universal GHG levies significantly reduce LNG’s economic viability over the study period. MACs demonstrated greater sensitivity to fuel prices (P_fuel) than to carbon prices (P_carbon) or GFI within this study’s parameterization scope, particularly under GFS&UGC. Ratios of P_carbon%/P_fuel% in equivalent sensitivity scenarios were quantified to determine relative price importance. This work provides insights into fuel selection for shipping companies and supports policymakers in designing effective GHG pricing mechanisms. Full article

Wetlands, as critical ecological systems, face increasing threats from anthropogenic pressures and climate change. This study investigates dynamic water allocation strategies for the restoration of Lake Marmara, a nationally important wetland within the Gediz River Basin of Türkiye, which has experienced complete desiccation in recent years. Within the scope of the PRIMA-funded “Mara-Mediterra” project, an integrated modeling approach was employed to evaluate multiple restoration scenarios using the WEAP (Water Evaluation and Planning) platform. Scenarios varied based on the initial storage capacity of Gördes Dam, irrigation demands, environmental flow priorities, and a potential water diversion investment from the Tabaklı reach. Results indicate that under current conditions, Lake Marmara’s ecological water needs can be sustained without the Tabaklı investment. However, under 2050 climate projections, scenarios lacking the Tabaklı investment or deprioritizing ecological needs consistently failed to meet the lake’s minimum water thresholds. Conversely, scenarios combining moderate dam storage levels, environmental prioritization, and Tabaklı inflow succeeded in restoring lake volumes by over 90%. These findings highlight the need for adaptive water planning that aligns with projected hydro-climatic shifts to ensure long-term wetland sustainability. Full article