Search Results (1,147)

Power-quality resilience is an important component of sustainable industrial electricity use, as voltage sag events can cause production interruptions, equipment damage, and inefficient allocation of mitigation costs and benefits among stakeholders. However, high initial investment costs and the lack of a viable commercial operation scheme have hindered the large-scale deployment of mitigation devices. To support sustainable power-quality governance, this study proposes an integrated framework that connects the technical compensation performance of the mitigation device with the economic foundation of a tripartite commercial operation model. First, an adaptive switching compensation strategy dynamically shifts between different modes based on the real-time voltage sag depth, establishing a mapping relationship with avoided-loss benefits. Then, a bi-level Nash bargaining model is constructed to allocate costs and benefits among the government, the enterprise, and the user, deriving closed-form analytical solutions for both the upper- and lower-level games. Through pilot operations at a large public service facility, economic losses of 480,000 CNY caused by a single voltage sag can be effectively avoided. Meanwhile, under the proposed scheme, all three parties achieve positive net present values. Compared to the user self-funding mode, the user’s NPV increases by 21.9%. Furthermore, unlike bilateral or equal-sharing alternatives, the Nash bargaining solution ensures all parties remain within the strong feasible region. The government and enterprise recover their costs within 4.14 and 6.20 years, respectively. These results indicate that the proposed framework can enhance the economic sustainability of power-sensitive users, encourage shared public–private investment in power-quality improvement, and support more resilient and efficient industrial electricity use. Full article

We re-conceptualize corporate debt default risk (EDF) as an emergent state variable of a coupled financial system and ask how capital-market opening reshapes its equilibrium. Extending the structural credit-risk framework with three interacting subsystem channels—external financing, investment efficiency, and information disclosure—we derive a closed-form result showing that an exogenous increase in liberalization strictly reduces the system-level corporate debt default probability through three complementary channels. We then exploit the staggered roll-out of China’s Shanghai–Hong Kong and Shenzhen–Hong Kong Stock Connect (HSGT) programs as a quasi-natural experiment on a panel of 21,351 firm-year observations over 2011–2023. A difference-in-differences (DID) estimator confirms a significant stabilizing effect on the firm’s market-implied default probability that is robust to an extensive battery of identification and specification checks; mechanism regressions confirm all three model-implied channels. The stabilizing effect is further amplified in firms facing greater environmental uncertainty and greater customer concentration—precisely the regimes in which our model predicts the underlying subsystem coupling to be most fragile. Our findings recast capital-market opening as a system-level intervention that simultaneously re-balances financing, investment, and information subsystems of the financial system, with implications for financial-stability policy in emerging economies. Full article

This study empirically analyses the influence of energy consumption, economic growth, and foreign direct investment (FDI) on carbon emission in India. The Autoregressive Distributed Lag (ARDL) bounds-testing approach is applied on time series data from 1990 to 2022 to determine the cointegration between series variables. The findings show that all variables are cointegrated. The Granger Causality test confirms unidirectional causality running from economic growth to carbon emissions, from carbon emissions to energy consumption, from energy consumption to foreign direct investment, and from foreign direct investment to renewable energy consumption. Also, the results presented a bidirectional causal relationship between foreign direct investment and carbon emission. Thus, the level of carbon emissions is significantly connected with economic growth and energy consumption. The rising energy demand further supports investment in the energy sector. Based on our findings, this study suggests the creation of policies towards mitigation of environmental pollution and promotion of investment in clean energy sources. Full article

Understanding how landscape patterns affect habitat quality in fragile karst regions is critical for biodiversity conservation, yet the driving mechanisms remain poorly understood, particularly regarding karst geomorphic heterogeneity. Taking Guizhou Province, a typical karst area of southwestern China, this study integrated land-use and natural geographic data (DEM, karst landforms, soil types, slope, soil thickness, vegetation cover, bedrock exposure, and rocky desertification) from 2000 to 2020. We quantified landscape pattern indices and habitat quality using Fragstats and InVEST, then explored spatial relationships via bivariate spatial autocorrelation and geographically weighted regression (GWR). Results show that land-use intensity increased and landscape structure stabilized, while fragmentation slightly decreased, but connectivity weakened. Habitat quality declined 4.4% over two decades. Globally, habitat quality was positively correlated with aggregation, cohesion, contagion, and largest patch index, and negatively correlated with shape complexity, patch density, diversity, and splitting indices. Locally, six karst zones exhibited distinct clustering patterns, revealing nonlinear interactions between natural vulnerability (e.g., bedrock exposure, thin soil) and human activities. After 2010, the dominant driver shifted from natural conditions to human–land interactions, with human activities contributing approximately 60% of habitat quality degradation. These findings provide a quantitative, spatially explicit basis for ecological zoning and differentiated policy making in Guizhou and similar fragile regions. Full article

The rapid growth in vessel size associated with global maritime trade is placing increasing pressure on port infrastructure worldwide. In Brazil, many existing ports face structural limitations due to insufficient navigational depth and limited opportunities for spatial expansion, often constrained by urban encroachment. In this context, identifying suitable coastal locations for deep-draft port development has become a key strategic challenge for long-term planning. This study develops a GIS-based spatial suitability model to identify segments of the Brazilian coastline with favourable conditions for deep-draft port infrastructure capable of accommodating large vessels, including post-Panamax ships. The approach considers physical constraints, environmental restrictions and basic logistical connectivity within a multi-criteria spatial framework implemented through map algebra. The model is conceived as a strategic screening tool to support early-stage decision-making rather than a detailed feasibility assessment. The results identify nine coastal locations with the highest suitability scores, indicating that highly favourable conditions for deep-draft port development are spatially limited. Notably, one of these candidate locations partially overlaps with an existing port-related cluster, suggesting consistency between the model outputs and real-world port development patterns. In contrast, large portions of the southeastern coastline (particularly in São Paulo and Paraná) exhibit lower suitability due to a combination of urban pressure, environmental constraints and limited depth conditions. Overall, the findings reveal a spatial mismatch between Brazil’s main economic core and the coastal areas with more favourable natural conditions for new port infrastructure. The proposed framework contributes a transparent and transferable spatial decision-support tool that can assist policymakers in identifying priority areas for future port development and in balancing investments between the expansion of existing ports and the development of new locations. Full article

Wastewater treatment plants (WWTPs) face increasing climate-change-induced flooding, yet flood resilience is seldom integrated into design, operation, or investment decisions. This study presents a multidimensional framework to support climate-resilient, circular, and bankable wastewater infrastructure planning. The methodology combines spatial flood exposure mapping using QGIS and Aqueduct flood layers for 2030, 2050, and 2080 with a 142-indicator Circular Economy (CE) scoring framework. Applied to five WWTPs in Türkiye, we develop the Index for Climate Risk and Circularity (ICRC), linking facility-level circularity performance with physical flood exposure. The results show that some technically advanced facilities achieve relatively high CE scores while remaining exposed to partial or near-complete inundation under future 1000-year flood scenarios, particularly in coastal areas. By connecting flood exposure, circularity, and operational cost reduction potential, the framework translates technical sustainability improvements into investment-relevant metrics for utilities, engineers, and financiers. It shows that circularity investments (e.g., renewable energy, resource efficiency) strengthen bankability only when combined with physical climate adaptation. Robustness checks, including alternative weighting assumptions and a cross-facility comparison, suggest that the main investment-prioritization logic remains broadly stable. The framework provides a replicable decision-support tool for prioritizing investments that enhance circularity, climate resilience, and long-term financial viability, while supporting the Sustainable Development Goals (SDGs) 6, 9, 11, and 13. Full article

Do enterprises with high tax contributions exhibit green transformation inertia due to the alignment of government and enterprise interests? Using data from the Chinese A-share market, this paper finds that high tax contributions significantly inhibit corporate green transformation. The mechanism lies in the fact that local governments implement inclusive regulation for high-tax-contribution enterprises, reducing their environmental compliance pressure and cutting environmental protection investment; at the same time, the halo effect of tax contributions provides a cover for enterprises’ low-quality environmental information disclosure. Exclusion analysis shows that financing constraints are not a limiting factor. Heterogeneity analysis indicates that the above effects are more prominent in samples with close government–enterprise connections, fierce industry competition, and loose local environmental regulations. Economic consequences show that insufficient green transformation caused by high tax contributions ultimately damages enterprises’ environmental performance and long-term sustainable development capabilities, and significantly increases stock price crash risk. Optimizing internal management and external supervision within enterprises can help mitigate this negative effect. This paper reveals the hidden obstacles to corporate green transformation under the symbiosis of government and enterprise interests, providing a new perspective for understanding the complexity of environmental governance. Full article

With increasing residential electricity demand, hybrid energy systems capable of simultaneously improving affordability, reliability, and environmental performance have become increasingly important. This paper develops an integrated techno-economic and environmental assessment framework for grid-connected residential energy systems under unreliable grid conditions and applies it to a real-world residential case study in Fayoum, Egypt. In the proposed framework, the utility grid is treated as the primary electricity source, while PV, diesel generation, and battery storage are evaluated as backup/support options. Six grid-connected hybrid configurations, namely Grid/Diesel, Grid/PV/Diesel, Grid/PV/Diesel/Battery, Grid/Diesel/Battery, Grid/PV/Battery, and Grid/Battery, were evaluated under identical load, solar resource, and economic conditions to identify the minimum net present cost (NPC)configuration capable of satisfying a specified service level, expressed in terms of the maximum allowable unmet load ratio. The optimization problem was formulated as a single-objective model that minimizes NPC, subject to technical constraints and a service level constraint represented by a zero unmet load requirement in this study. Additional indicators, including levelized cost of energy (LCOE), renewable fraction, CO₂ emissions, and electricity purchased from the grid, were used for comparative performance evaluation. The candidate systems were simulated and optimized under frequent grid outage conditions using HOMER Pro. The results identify the Grid/PV/Battery configuration as the preferred base case backup/support configuration among the evaluated alternatives, achieving the lowest NPC of USD 8949, the lowest LCOE of USD 0.135/kWh, the highest renewable fraction of 55.1%, and the lowest annual CO₂ emissions of 2333 kg/yr, while satisfying the zero unmet load requirement. Compared with the base Grid/Diesel system, the optimal configuration reduces annual operating cost from USD 1204/yr to USD 648.19/yr and lowers emissions by approximately 50%, despite requiring a higher initial capital investment. Sensitivity analysis shows that the preferred solution remains robust across most of the examined financing parameter space. The PV derating factor analysis further indicates that the Grid/PV/Battery configuration remains optimal at higher PV derating levels of 70–80%, whereas the preferred solution shifts toward Grid/Diesel at lower derating levels of 50–60%. Overall, the results demonstrate that combining service-level-constrained NPC minimization with comparative techno-economic and environmental evaluation provides a robust basis for identifying suitable backup-supported grid-connected residential energy solutions under unreliable grid conditions. Full article

Using a dataset covering January 1975 to March 2026 and six agricultural commodities, wheat, corn, soybeans, oats, sugar, and coffee, this paper explores the role of geopolitical risk (acts and threats) in shaping cross-market connectedness. It proposes a multilayer methodology based on the time-varying parameter vector autoregressive (TVP-VAR), the exponential GARCH with exogenous variables (EGARCH-X), and the wavelet quantile correlation (WQC) frameworks. This methodology captures cross-market volatility spillovers, assesses the effects of geopolitical risk and its components on the strength and instability of connectedness, and incorporates nonlinearity and asymmetry across investment horizons and market conditions. The results show a time-varying pattern in agricultural cross-market connectedness. Corn and soybeans transmit volatility shocks, while the other commodities are net receivers. These commodities have a central position in the connectivity network, whereas sugar and coffee are in the peripheral zone. The EGARCH-X results show that geopolitical acts and threats do not significantly alter the overall level of connectedness but intensify its volatility, suggesting that geopolitical tensions primarily influence stability rather than the intensity of connectedness. Economic policy uncertainty and oil price volatility have similar effects. In line with these results, the WQC analysis uncovers significant nonlinearity and state-dependent linkages, underscoring that the effect of geopolitical acts and threats becomes prominent over medium- and long-term horizons and during periods of market stress. These findings contribute to the literature by differentiating the effects of geopolitical incidents on agricultural market connectedness versus volatility. From an operational standpoint, these results imply that policymakers and market operators should enhance their risk-monitoring and hedging strategies during periods of high geopolitical stress, as such events can amplify instability across agricultural commodity markets. Full article

Green fintech operates at the intersection of sustainable finance, digital innovation, and financial-sector risk governance. It promises to improve the allocation of capital toward environmentally sustainable activities by lowering information costs, scaling disclosure tools, automating environmental verification, and widening access to green investment products. Yet the same digital features that make green fintech attractive—speed, scalability, data intensity, platform intermediation, cross-border distribution, and algorithmic decision-making—can also transform apparently local regulatory weaknesses into broader financial-stability concerns. This article examines how regulatory risk associated with green fintech may evolve into systemic risk under conditions of market concentration, weak data governance, regulatory fragmentation, greenwashing amplification, and financial interconnectedness. It develops a mechanism-based conceptual framework rather than an econometric test. The framework connects three regulatory dimensions—regulatory clarity and scope, supervisory consistency, and innovation facilitation—with five systemic-risk transmission channels: market concentration, data and model risk, regulatory arbitrage, greenwashing amplification, and financial interconnectedness. The article draws on sustainable-finance regulation, the financial-stability literature, fintech scholarship, and official supervisory documents, including the EU Sustainable Finance Disclosure Regulation, the EU Taxonomy Regulation, the Digital Operational Resilience Act, and the ESG Ratings Regulation. The central argument is cautious but policy-relevant: green fintech does not automatically create systemic risk, but regulatory uncertainty and supervisory gaps may become systemic when they are embedded in digital infrastructures that scale quickly and are relied upon by multiple financial institutions. The article contributes to risk scholarship by shifting the analysis from compliance-level regulatory risk to transmission mechanisms through which green-finance innovation may affect market integrity and financial stability. Full article

Digital infrastructure may improve firm productivity, yet its economic value depends on whether firms can absorb external connectivity and embed it in production, management, and investment decisions. Using the staggered implementation of the “Broadband China” pilot policy as a quasi-natural experiment, this study examines the effect of city-level broadband infrastructure on the revenue-based labor productivity of Chinese A-share listed firms from 2009 to 2023. A multi-period difference-in-differences model shows that the pilot policy is associated with an increase in revenue per employee. The baseline estimate implies an economically meaningful increase of approximately 4.1%, and the result remains robust to alternative productivity measures, sample restrictions, stricter fixed effects, placebo tests, PSM-DID, and IPW-DID. CSDID estimates are positive but not statistically significant at conventional levels and are therefore interpreted as directionally consistent rather than independently confirmatory. Evidence based on total factor productivity, management expense intensity, and investment adjustment is consistent with production efficiency, management coordination, and organizational adjustment channels. Heterogeneity tests show stronger effects among non-state-owned, eastern region, and non-manufacturing firms. The findings suggest that broadband infrastructure generates productivity benefits when firms have the organizational absorptive capacity to convert external digital connectivity into internal operational efficiency. Full article

Even though the literature extensively examines aspects of the efficiency, waterway infrastructure, and competitiveness of inland waterway transport (IWT), a systemic composite index that integrates navigational, operational, and digital factors of IWT infrastructure into a single comparable evaluation system at the level of port hinterlands has not been identified. This study proposes a multi-criteria inland waterway transport infrastructure index (IWTI) designed to assess complex infrastructure conditions. The IWTI measures infrastructural readiness, physical navigational, operational, and digital prerequisites that enable the realisation of IWT potential. The index is calculated using the multi-criteria decision-making method TOPSIS, with criterion weights determined based on expert evaluation (n = 7) data. Rank stability was tested via Spearman’s rank correlation sensitivity analysis under three alternative weighting scenarios. The methodology was applied to assess seven ports in the Baltic Sea region using data from 2023. The IWTI ranges from 0.00 (Tallinn does not have an IWT connection) to 0.80 (Szczecin). The study revealed significant regional differences: the hinterland of the HaminaKotka port is characterised by a mature Saimaa canal and lake system; the hinterlands of Szczecin and Klaipėda demonstrate strong potential for the Oder/Odra and Nemunas corridors; the port of Gdańsk was identified as a medium-potential case with clearly defined priorities for infrastructure improvements. The ports of Gdynia and Riga lack functional inland waterway connections, but the infrastructural potential scenario indicates significant IWTI growth opportunities upon the implementation of planned investments. Sensitivity analysis confirmed high stability of the rank (Spearman ρ ≥ 0.964 in all scenarios). The proposed index provides a structured methodological basis for evaluating IWT potential and can serve as a decision-making tool for infrastructure planning and transport policy development, contributing to sustainable cargo carriage and the decarbonisation goals of the transport sector. Full article

The Iberian Peninsula hosts one of the world’s most endemic fish faunas. Its extensive evolutionary, palaeogeographic, and geological history has produced a distinctive freshwater fish fauna. Many of these species have very limited distributions, making them especially vulnerable to habitat disturbance. Past monitoring of this biodiversity has revealed alarming results, indicating that most native Spanish species are at risk. The causes of this serious situation are varied and reflect the ongoing deterioration of freshwater ecosystems. The main pressures faced by populations include pollution, loss of river connectivity caused by hydraulic infrastructure, regulation of watercourses, water extraction, fishing, and the presence of invasive species. Additionally, the effects of climate change worsen the risk of extinction for these populations, particularly through the increased frequency and intensity of droughts and heatwaves. It is evident that current planning models and investments are inadequate to conserve freshwater fish. To prevent the extinction of many populations in Spain, especially Iberian endemics, it is crucial to change the management of aquatic ecosystems and adopt integrated solutions that halt population declines and promote the sustainable use of aquatic resources. The IUCN Red Lists of Threatened Species are vital indicators of biodiversity health and are widely used to guide and structure conservation efforts. These lists, published in the Red Books, result from a thorough evaluation process that employs specific categories and criteria to assess the extinction risk of species, both globally and regionally. This report presents preliminary findings from a monitoring study on the current state of freshwater fish in Spain. The monitoring results reveal that, based on IUCN assessment criteria, two species are classified as extinct (EX), four as critically endangered (CR), eighteen as endangered (EN), and twenty-one as vulnerable (VU). Of fifty-seven species documented, 79% are considered threatened. The project’s final outcome is the development of the Atlas and Red Book of Freshwater Fish of Spain. This resource includes the main native and invasive freshwater and diadromous fish species, offers detailed information on their biological and ecological traits, and provides an up-to-date inventory of records along with an assessment of their conservation status. Full article

Exploring the interaction relationship among multiple ecosystem services is vital for maintaining ecosystem function. However, traditional approaches are limited in their ability to: (i) characterize complex interactions and (ii) visualize the spatial connectivity of various ecosystem services delivered by social–ecological systems. To address these challenges, a framework for constructing spatial networks of multiple ecosystem services was proposed. The framework is implemented by: (i) estimating the spatial distribution of multiple ecosystem services using the InVEST model, and (ii) generating network nodes and edges with geographical attributes based on the minimum cumulative resistance model and a multiresolution segmentation method. We conducted a case study in the Guangdong–Hong Kong–Macao Greater Bay Area and examined the topological features of the spatial networks using complex network indicators. For each network, winding and multiple edges connected adjacent nodes and formed continuous linkages across the entire study area, indicating that the proposed framework is feasible for capturing the spatial connectivity of multiple ecosystem services. The different ecosystem service networks exhibited conspicuous spatial heterogeneity and generally maintained relatively high connectivity, as evidenced by their tree-like structure with winding pathways and the distribution of multi-edge nodes, indicating that each ES was predominantly connected with multiple other ecosystem services. Meanwhile, nodes with high values of degree centrality and clustering coefficient were mainly concentrated in coastal and mountainous regions. This study advances the representation of complex interactions among multiple ecosystem services from a spatial perspective, thereby facilitating a deeper understanding of the interaction mechanisms underlying ecosystem functioning. Full article

The Behavioral Finance (BF) has undergone significant developments due to the transformative influence of Environmental, Social and Governance (ESG) practices. BF and Sustainable Investment (SI) are closely intertwined domains, both of which bring into line with the broader framework of ESG. Integrating BF into the field of SI expands the understanding of how psychological biases, emotional factors, and cognitive constraints influence investors decisions connected to sustainability focused assets. Despite their growing relevance, the existing literature lacks a comprehensive review that provides holistic reviewing of research integrating into these areas. To address this gap, we provide an overview of BF and SI research in Socially Responsible Investments (SRI). Using both co-citation and bibliometric-coupling analysis, we infer the thematic structure of key words of BF and SI for a period of 20 years starting from 2004 to September 2025. Additionally using performance analysis and co-occurrence analysis, we highlighted trends and research directions regarding BF and SI. Further, seven thematic clusters and coupling networks were also identified which are offering to the researchers a structured foundation to explore emerging trends and consolidate knowledge within the BF and SI field. This Bibliometric study aids in recognizing the emerging topics for research in the domain of BF and SI. Full article