Search Results (2,086)

In the context of tightening sustainability regulations and rising demands for transparent and responsible capital allocation, understanding how digital financial innovations influence market efficiency has become increasingly important. This study examines the impact of Financial Technology (FinTech) solutions and crowdfunding platforms on sustainable market efficiency, volatility dynamics, and risk structures in the United Kingdom. Using weekly data for the Financial Times Stock Exchange 100 (FTSE 100) index from January 2010 to June 2025, the analysis applies the Lo–MacKinlay variance ratio test to assess compliance with the Random Walk Hypothesis as a proxy for informational efficiency. Firm-level proxies for FinTech and crowdfunding activity are constructed using the Nomenclature of Economic Activities (NACE) and Standard Industrial Classification (SIC) systems. The empirical results indicate substantial deviations from random-walk behavior in crowdfunding-related market segments, where persistent positive autocorrelation and elevated volatility reflect liquidity constraints and informational frictions. By contrast, FinTech-dominated segments display milder inefficiencies and faster information absorption, pointing to more stable price-adjustment mechanisms. After controlling for structural distortions through heteroskedasticity-consistent corrections and volatility adjustments, variance ratios converge toward unity, suggesting a restoration of informational efficiency. The results provide relevant insights for investors, regulators, and policymakers seeking to align financial innovation with the objectives of sustainable financial systems. Full article

This study investigates the valuation dynamics of 30 publicly listed fintech firms across six Asian economies from January 2021 to December 2025. It examines how intrinsic firm-level scale (market capitalization) and extrinsic macroeconomic conditions (GDP growth) jointly influence fintech valuation ratios, as reflected in price-to-earnings (P/E), price-to-book (P/B), and price-to-sales (P/S) measures. It also identifies significant structural heterogeneity and distributional asymmetries in valuation outcomes by implementing a multi-method empirical strategy that includes a Panel Autoregressive Distributed Lag (ARDL) framework, two-way fixed-effects models with interaction terms, and quantile regression. The findings reveal a robust, positive long-run relationship between market capitalization and valuation multiples across all ratios, confirming that firm-level scale as reflected in market capitalization is the primary driver of market value. Critically, the analysis identifies a dual-regime landscape in the Asian fintech sector: developed markets (South Korea, Japan, and Singapore) are fundamentally firm-scale driven, where intrinsic scale is the superior predictor of valuation. In contrast, developing markets (China, India, and Indonesia) are primarily macro-growth driven, exhibiting high sensitivity to GDP growth as a macroeconomic indicator of market expansion. The quantile regression results demonstrate a winner-takes-all effect, where the impact of scale on valuation is significantly more pronounced for highly valued firms in the 75th percentile. These results challenge the efficacy of universal valuation models and provide a context-dependent navigational framework for investors, analysts, and policymakers to distinguish between structural scale and cyclical growth in the rapidly evolving Asian fintech ecosystem. Full article

Driven by the national policy of total water resources control and efficiency improvement, the behavior of water resource utilization reduction by firms is widespread, which may have an impact on the value of firms. This study integrates dynamic capability theory and signaling theory to construct a dual-path analytical framework, systematically investigating the impact of water utilization reduction on firm value and its intrinsic mechanisms. Based on data from Chinese A-share listed companies spanning 2012–2023, fixed-effect models, mediation-effect tests, and heterogeneity analysis are employed for empirical verification. The results reveal that water utilization reduction exerts a significant dual-path promoting effect on firm value: it enhances financial performance (ROA) primarily through technological innovation, reflecting the process of resource orchestration and dynamic capability construction; concurrently, it boosts market performance (Tobin’s Q) mainly by improving ESG performance as a signaling channel, mirroring the capital market’s positive pricing of green signals. Further heterogeneity analysis indicates that these effects are more pronounced during the policy deepening stage, in non-water-intensive industries, and in humid/sub-humid regions. This study contributes theoretical support and empirical evidence for firms’ green transformation and the formulation of differentiated water resource policies by the government, highlighting the synergistic development of high-quality economic growth and ecological civilization construction. Full article

This study aimed to develop a credit risk index to classify coffee producers according to socioeconomic, agronomic, and financial performance variables, with the purpose of strengthening financial inclusion. We combined qualitative and quantitative methods to understand credit risk factors among smallholder coffee producers. The study followed a descriptive-analytical approach structured in consecutive methodological phases. The systematic review, conducted following the Kitchenham protocol, identified theoretical factors associated with credit risk, while fieldwork with 300 producers provided the socioeconomic and productive contexts of coffee-growing households. Producer income, cost of living, and farm management expenses were modeled using regression, statistical, and machine learning methods. Subsequently, these variables were integrated to construct a financial risk index, which was normalized using expert scoring. The index was validated using data from 100 additional producers, for whom annual repayment capacity and maximum loan amounts were estimated according to their risk level. The results indicated that incorporating municipal-level economic variables, such as estimated average prices, income, and expenses, enhanced predictive accuracy and improved the rational allocation of loan amounts. The study concludes that credit risk analysis based on variables related to human, productive, and economic capital constitutes an effective strategy for improving access to finance in rural areas. Full article

Financial crises increasingly exhibit complex, interconnected patterns that traditional risk models fail to capture. The 2008 global financial crisis, 2020 pandemic shock, and recent banking sector stress events demonstrate how systemic risks propagate through multiple channels simultaneously—e.g., network contagion, extreme co-movements, and information cascades—creating a multidimensional phenomenon that exceeds the capabilities of conventional actuarial or econometric approaches alone. This paper addresses the fundamental challenge of modeling this multidimensional systemic risk phenomenon by proposing a mathematically formalized three-tier integration framework that achieves 19.2% accuracy improvement over traditional models through the following: (1) dynamic network-copula coupling that captures 35% more tail dependencies than static approaches, (2) semantic-temporal alignment of textual signals with network evolution, and (3) economically optimized threshold calibration reducing false positives by 35% while maintaining 85% crisis detection sensitivity. Empirical validation on historical data (2000–2023) demonstrates significant improvements over traditional models: 19.2% increase in predictive accuracy (R² from 0.68 to 0.87), 2.7 months earlier crisis detection compared to Basel III credit-to-GDP indicators, and 35% reduction in false positive rates while maintaining 85% crisis detection sensitivity. Case studies of the 2008 crisis and 2020 market turbulence illustrate the model’s ability to identify subtle precursor signals through integrated analysis of network structure evolution and semantic changes in regulatory communications. These advances provide financial regulators and institutions with enhanced tools for macroprudential supervision and countercyclical capital buffer calibration, strengthening financial system resilience against multifaceted systemic risks. Full article

The development of energy systems toward a decarbonized economy is increasingly constrained not only by technological challenges, but also by deficiencies in the organization, coordination, and governability of sustainable financing. This study aims to substantiate an integrated conceptual model and a multi-level governance framework for the sustainable financing mechanism of energy system development under decarbonization, ensuring the alignment of financial instruments with transition strategies, performance indicators, and feedback mechanisms. The methodology combines a bibliometric analysis of Scopus-indexed journal publications with an examination of international statistical and analytical data produced by leading global organizations, complemented by systemic, institutional, and comparative analytical approaches. The bibliometric analysis was conducted in 2025 and covered peer-reviewed articles published during 2017–2025, while empirical financial indicators were synthesized for the most recent available period of 2022–2024 using comparable time-series data reported by international institutions. The results indicate that despite global energy investments reaching approximately $3 trillion in 2024—nearly $2 trillion of which was allocated to clean energy technologies—a persistent annual financing gap for climate change mitigation in the energy sector remains. Moreover, to remain consistent with the Net Zero trajectory, investments in clean energy must increase by approximately 1.7 times by 2030. The synthesis of contemporary research and empirical evidence reveals a predominance of studies focused on individual green and transition finance instruments, accompanied by persistent fragmentation between financial flows, governance structures, and measurable decarbonization outcomes. To address this gap, the paper proposes a conceptual model that interprets sustainable finance as a governed system rather than a collection of isolated instruments, together with a multi-level governance framework integrating strategic (policy), sectoral, and project-level decision-making with systems of key performance indicators, monitoring, and feedback. The findings demonstrate that the effectiveness of sustainable financing critically depends on the coherence between financial instruments, governance architectures, and decarbonization objectives, which ultimately determines the capacity to translate mobilized capital into tangible energy infrastructure modernization and measurable emissions reductions. The proposed approach provides a practical foundation for improving energy transition policies and investment strategies at both national and supranational levels. Full article

As a key strategic sector underpinning China’s future development, the artificial intelligence (AI) industry is essential to enhancing national competitiveness and advancing sustainable economic and social development. Based on Chinese provincial panel data from 2012 to 2022, we explore how industrial structure upgrading (ISU) affects the resilience of China’s AI industry chain (RAIIC) and empirically test the underlying transmission mechanism using a mediation effect model. The results indicate that (1) ISU significantly enhances the RAIIC, thereby providing a solid structural foundation for its long-term stability and sustainable evolution; (2) the impact of ISU on the RAIIC can be realized by enhancing regional financial agglomeration and human capital levels; (3) the positive impact of ISU on the RAIIC is significantly stronger in regions with larger population sizes, higher levels of economic development, higher technological sophistication, and more advanced digital inclusive finance. These findings imply that policy design should emphasize regional coordination and dynamic adaptability so as to support the balanced and sustainable nationwide development of the AI industry. According to these findings, we propose corresponding policy recommendations aimed at providing theoretical support and practical guidance for the sustainable and high-quality development of China’s AI industry. Full article

This study investigates the “insurance-like effect” of corporate Environmental, Social, and Governance (ESG) performance amid financial restatement events among Chinese listed firms and examines the moderating role of ESG rating divergence. Employing an event study methodology on a sample of 1552 financial restatement events in China’s A-share market from 2013 to 2023, we measure market reactions using the cumulative abnormal return (CAR) over a [−1, +1] day window. Our findings reveal that strong ESG performance significantly mitigates the negative market reactions triggered by financial restatements. However, this protective effect of ESG is significantly weakened by the inconsistency in ESG assessments among rating agencies, known as ESG rating divergence, particularly when such divergence is persistent. We argue that the underlying mechanism is that rating divergence creates signal conflicts, exacerbates information asymmetry, and erodes the credibility of ESG signals. This, in turn, undermines the stakeholder trust and moral capital that underpin the insurance-like effect. This research sheds light on the complex impact of ESG rating divergence on the value-protective mechanism of ESG and contributes new empirical evidence to the literature on ESG and its insurance-like effect, especially within the context of an emerging market. Full article

This study investigates the interplay between asset quality, financial ratios, and market valuation in Indian commercial banks over a twelve-year period (2014–2025). Using a hybrid approach combining Structural Equation Modeling, correlation analysis, and trend evaluation, the research examines whether Non-Performing Assets (NPAs) influence market capitalization directly or through Return on Equity (ROE) as an intermediary. The findings reveal that NPAs exert a significant negative impact on both ROE and market value, while Net Interest Margin (NIM) emerges as a strong positive determinant of valuation. Conversely, Capital Adequacy Ratio (CAR), though vital for regulatory compliance, shows no direct effect on market prices. Mediation analysis challenges conventional assumptions, indicating that profitability alone does not fully explain valuation dynamics. These insights underscore the need for integrated strategies addressing asset quality and operational efficiency, offering practical implications for policymakers, investors, and bank management in strengthening resilience and optimizing shareholder value. Full article

This paper examines the impact of environmental, social, and governance (ESG) disclosure on the cost of capital for banks as well as financial technology companies in Europe, America, and Asia from 2010 to 2024. The study investigates how sustainability affects financing conditions in the two institutional settings of conventional and digital financial intermediaries. We estimate the average cost of capital using the traditional WACC (weighted average cost of capital) formula, which calculates the cost and proportions of debt and equity capital. Panel regressions with firm and year fixed effects are used, along with an instrumental variable (IV) approach (2SLS), by way of peer-based ESG instruments to correct for endogeneity. The paper also carries out robustness checks such as the Anderson–Rubin weak IV tests and over identification diagnostics. The findings indicate that more ESG disclosure has a significant negative effect on WACC and debt costs and no robust impact on equity cost. Governance disclosure is revealed to be the dominant dimension and it always correlates with lower financing costs. Environmental disclosure is occasionally associated with a higher cost of equity, owing to investors’ expectation of short-term compliance costs. The results shed light on the dynamic relationship between innovation and sustainability in driving banks and financial technology firms financing environment. Full article

Background/Objectives: Digital transformation is increasingly essential for healthcare organizations to improve operational efficiency and service quality. However, in developing countries such as Indonesia, many lower-middle-class hospitals lag due to limited financial, human, and infrastructural resources. This study examines how environmental dynamism—comprising regulatory changes, market pressures, and technological shifts—affects the digital capabilities of these hospitals. Methods: A quantitative, cross-sectional survey was conducted in Class C and D hospitals across Indonesia. Respondents included hospital directors, deputy directors, and IT heads. Data were collected through structured questionnaires measuring environmental dynamism and digital capability using a six-point Likert scale. Reliability testing yielded Cronbach’s alpha values above 0.96 for both constructs. Correlation analysis was performed to examine the relationship between environmental dynamism and digital capability. Results: Findings reveal a weak positive correlation (r = 0.1816) between environmental dynamism and digital capability. Although external factors such as policy regulations and technological competition encourage digital adoption, hospitals with limited internal resources struggle to translate these pressures into sustainable transformation. Key challenges include low ICT budgets, inconsistent staff training, and insufficient infrastructure. Conclusions: The results suggest that environmental change alone cannot drive digital readiness without internal capacity development. To foster resilient digital healthcare ecosystems, policy interventions should integrate regulatory frameworks with practical support programs that strengthen resources, leadership, and human capital in lower-middle-class hospitals. Full article

In response to recent policies on sustainable finance, nature restoration, soil protection, and biodiversity conservation, it is increasingly important for projects to assess their impacts on natural capital to safeguard Ecosystem Services (ES). Nature-Based Solutions (NBSs) are recognized as strategic tools for fostering cost-effective, nature- and people-centered development. Yet, standard economic and financial assessment methods often fall short, as many ES lack market prices. Indirect, ecosystem-based approaches—such as ES monetization and environmental cost accounting—are therefore critical. This study evaluates the feasibility of investing in NBSs by estimating their economic and financial value through indirect ES valuation. An empirical methodology is applied to quantify environmental costs relative to ES delivery, using Willingness to Pay (WTP) as a proxy for the economic relevance of NBSs. The proposed ES-Cost Accounting (ES-CA) framework was implemented across major NBS categories in Europe. Results reveal that the scale of NBS implementation significantly influences both unit environmental costs and ES provision: larger interventions tend to be more cost-efficient and generate broader benefits, whereas smaller solutions are more expensive per unit but provide more localized or specialized services. The findings offer practical guidance for robust cost–benefit analyses and support investment planning in sustainable climate adaptation and mitigation from an ES perspective. Full article

Real estate constitutes a core segment of the global building and built environment industry, absorbing substantial volumes of international institutional investment capital. Unlisted real estate has featured prominently in the portfolios of global institutional investors. In recent years, global real estate markets have been significantly impacted by rising interest rates, posing a real and significant risk to investors. In response, more tactical asset allocation strategies have been adopted. Investment fund managers and institutional investors seek to rebalance through sector selections and sectoral portfolio diversification when tactical asset allocation strategy may be insufficient in phases of heightened rate volatility. By deploying MSCI US unlisted sector-specific real estate quarterly total returns between March 1999 and June 2024, this research assesses portfolio asset allocation strategy for unlisted sector-specific real estate over both rate-easing and rate-tightening phases to investigate how the structural change shapes portfolio asset allocation strategy resulting from the rising interest rates. Overall, the findings show that unlisted sector-specific real estate played a substantial role in the US institutional mixed-asset portfolios during rate-hike phases in the period before the COVID-19 recession. The allocation to unlisted sector-specific real estate was close to the maximum 10% cap, averaging 9.5% during rate-easing phases but decreasing to 7.5% during rate-tightening phases. At a sector level, unlisted office real estate allocations were higher across constrained mixed-asset and real estate portfolios in rate-tightening phases relative to those in rate-easing phases, while portfolio asset allocations to unlisted real estate sectors were lower in rate-easing phases relative to those in rate-tightening phases. These empirical findings provide real estate investment stakeholders with practical and crucial insights into rebalancing portfolios’ tactical asset allocation strategies for unlisted sector-specific real estate responding to interest rate phases and macro-financial markets, albeit static asset allocation strategies being insufficient in phases of heightened rate volatility. The investment implications of empirical outcomes are identified and further discussed. Full article

Agricultural listed companies are key nodes in the agricultural industry chain, providing capital, technology and market access to upstream producers and downstream processors. When these firms face delisting risk, the resilience and sustainability of the industry chain are threatened. Using data from 897 observations of Chinese A-share listed companies in the agriculture, forestry, animal husbandry, and fishery sector over 2010–2021, this study links multidimensional firm vulnerability to subsequent delisting risk. We construct 30 internal and external indicators covering financial performance, innovation input, supply chain concentration, government support and market competitiveness. Clustering method is applied to capture heterogeneity in firms’ multidimensional structural, gradient boosting models are used to predict ST (Special Treatment) status within three years, and SHAP analysis is used to identify the main risk. The results show that a small subset of firms with high leverage, tight liquidity, weak profitability, insufficient innovation, and highly concentrated key customers and suppliers accounts for most ST cases. Strengthening capital buffers, diversifying critical supply-chain relationships, and maintaining stable innovation investment are thus crucial for reducing delisting risk and enhancing the resilience of agricultural listed companies. Full article

Despite growing interest in sustainable supply chains, we still know relatively little about how environmental requirements transmitted from key customers along the supply chain affect firms’ productivity and long-run economic sustainability. To address this gap, we introduce the notion of green supply chain pressure, downstream customers’ explicit green and low-carbon requirements on suppliers, and examine its implications for firm-level productivity and the mechanisms involved. Using a panel of Chinese A-share listed firms over 2014–2024, we construct a novel text-based index of green supply chain pressure by combining supply-chain relationship data with MD&A disclosures of major customers. Firm-level economic sustainability is measured by Levinsohn–Petrin total factor productivity, with Olley–Pakes estimates used for robustness. Fixed-effects regressions with industry–year and city–year controls show that stronger green supply chain pressure is associated with significantly higher productivity. Mediation analysis reveals that this effect operates partly through three resource-intensive adjustment channels: (i) a higher share of green patents in total innovation, (ii) capital deepening via a higher share of digital and intelligent fixed assets in total net fixed assets, and (iii) human capital upgrading through a larger proportion of highly educated employees. Interaction models further indicate that financing constraints critically condition these gains: the productivity effect of green supply chain pressure is stronger for firms with greater financial slack, and for high-tech, green-attribute and larger firms. Overall, the results highlight supply chain-based governance as a powerful complement to formal regulation for promoting long-run economic sustainability at the firm level. Full article