Search Results (2,373)

This study examines the dynamic relationship between financial development and total energy production in emerging market economies (EMEs) using a balanced panel of 20 countries over the period 2000–2020. Unlike much of the existing literature that focuses on energy consumption or specific energy types, this paper conceptualises total energy production as an aggregate supply-capacity indicator that captures infrastructure investment, capital intensity, and long-run energy system expansion. Employing a panel autoregressive distributed lag model with the Pooled Mean Group (ARDL–PMG) estimator, the analysis distinguishes between long-run equilibrium relationships and heterogeneous short-run adjustment dynamics. The results reveal a stable long-run reciprocal relationship between financial development and total energy production, suggesting that deeper financial systems are associated with higher energy production capacity over time, while expansion in energy production is also linked to financial deepening. Short-run dynamics, however, are asymmetric, indicating the presence of adjustment frictions and investment lags in capital-intensive energy sectors. Robustness checks using a two-step System GMM estimator confirm the qualitative consistency of the main findings after accounting for potential endogeneity and simultaneity. Overall, the results highlight the importance of financial system development in supporting aggregate energy supply expansion in EMEs, while underscoring the need to account for transitional constraints and differing adjustment speeds across sectors and countries. The findings offer policy-relevant insights for aligning financial development with energy infrastructure investment during periods of structural transformation. Full article

In bank-dominated financial systems, the accumulation of non-performing loans is a recognised source of systemic vulnerability, as correlated corporate defaults can erode bank capital, impair liquidity, and propagate stress across interconnected portfolios. Firm-level default detection thus constitutes a microprudential foundation of macroprudential stability: the reliable early identification of risky borrowers reduces both individual credit losses and the aggregate exposures that drive system-level fragility. Yet the use of structured data-mining pipelines for this task remains underexplored in Central and Eastern Europe. This study applies the CRISP-DM methodology to predict corporate loan default using data on 302 Slovak corporate borrowers, combining financial ratios from publicly available financial statements with selected company and loan-related information from internal bank records. Seven individual classifiers were developed and compared: decision trees (CART, CHAID, C5.0), logistic regression, discriminant analysis, and neural networks (MLP, RBF), together with a stacked ensemble based on their outputs. Model performance was evaluated using sensitivity, overall classification accuracy, and area under the ROC curve (AUC), with sensitivity treated as the primary criterion because of the asymmetric costs of misclassification in credit risk assessment. The results confirm that historical firm-level information provides a reliable basis for default prediction, with tree-based models consistently outperforming statistical and neural network approaches. The stacked ensemble achieved the strongest overall performance, whereas C5.0 and CHAID showed that interpretable classifiers can also deliver competitive predictive accuracy. A champion–challenger deployment architecture is proposed, in which the ensemble serves as the performance-oriented champion and interpretable models act as challengers; this arrangement contributes to the operational resilience of the credit-risk assessment process and aligns with macroprudential expectations of model governance, auditability, and explainability. The study offers a replicable methodological framework for integrating data-driven decision support into credit evaluation in comparable banking settings. Full article

The financial early warning mechanism of listed companies has an important strategic value for maintaining the stability of the capital market and preventing systemic financial risks. This study proposes a hybrid model (EBWO-BP) based on the improved beluga optimisation algorithm (EBWO) and BP neural network for financial early warning research. Innovative T-SNE nonlinear dimensionality reduction technique is applied to the multidimensional evaluation system constructed by 23 financial and two non-financial indicators. The empirical evidence based on the data of A-share listed companies in 2022–2024 shows that the accuracy of the EBWO-BP test set reaches 86.51% (AUC = 0.83), which demonstrates a significant prediction advantage compared with the optimisation algorithm models such as GA-BP and PSO-BP, as well as the CNN and LSTM deep learning models; when the sample size is increased to 700 groups, the accuracy is improved to 89.05%, verifying the model robustness. The method achieves significant improvement of financial risk prediction through algorithm fusion innovation, and provides methodological innovation and practical reference for intelligent financial risk monitoring. Full article

Rural household energy-saving behavior is central to low-carbon development in ecologically fragile plateau regions. This study explores whether climate risk perception promotes household energy-saving behavior, through which livelihood capital mechanisms this effect operates, and which livelihood capital configurations support high levels of such behavior. Drawing on survey data from 315 rural households in Xining, China, a sustainable livelihood framework is integrated with the pressure–state–response model, and PLS-SEM, an ANN, and fsQCA are applied. The integrated framework regards climate risk perception as external pressure, livelihood capital as the household livelihood state, and energy-saving behavior as the behavioral response. The sustainable livelihood framework identifies the multidimensional resource conditions of rural households, whereas the pressure–state–response model specifies the causal sequence through which perceived climate pressure affects livelihood states and induces behavioral responses. The results show that climate risk perception significantly promotes energy-saving behavior. Physical, human, and social capital exert positive effects, whereas natural and financial capital exert negative effects. Moreover, natural, financial, and social capital significantly mediate the link between climate risk perception and energy-saving behavior. Multi-group analysis shows that physical capital matters more for agriculture-dominated households than non-farm households. The ANN results identify social and human capital as the strongest predictors, and the fsQCA results show that high levels of energy-saving behavior arise not from any single condition but from multiple capital configurations, in which social capital is consistently central. Energy conservation under climate risk is therefore best understood as a multidimensional, nonlinear adaptation process embedded in household livelihood structures rather than a response to any single factor. These findings extend rural energy-saving research by linking climate pressure, livelihood conditions, and configurational decision logic in a plateau socio-ecological context. Policy interventions should combine energy-efficient infrastructure, targeted financial incentives, community-based diffusion, and livelihood-sensitive support for rural households. Full article

This study examines the impact of ESG disclosure, leverage, and profitability on firm value, measured by Tobin’s Q, among 67 non-financial Tadawul-listed companies in Saudi Arabia over the period 2015–2024. ESG disclosure is captured through a manual content-analysis index that scores the proportion of expected environmental, social, and governance items reported by each firm. The study further investigates whether board independence moderates these relationships while controlling for liquidity, firm size, current ratio, capital expenditure, and board size. Methodologically, the study employs the two-step system generalized method of moments (system GMM) estimator, which addresses dynamic persistence, endogeneity, and unobserved heterogeneity. The findings reveal that ESG disclosure has a positive and significant effect on firm value, indicating that the Saudi market increasingly rewards firms that provide broader sustainability-related information. Profitability also exerts a positive influence on Tobin’s Q, while leverage has a negative and significant effect, suggesting that higher debt weakens market valuation. Among the moderating effects, board independence significantly reduces the negative impact of leverage on firm value, although it does not significantly strengthen the positive ESG disclosure–firm value relationship. The results also show that liquidity, firm size, capital expenditure, and board size positively influence firm value. The study’s novelty lies in being the first, to our knowledge, to integrate ESG disclosure, financial structure, profitability, and board independence within a single dynamic firm-value framework over a decade-long panel that brackets the Saudi Exchange’s 2021 ESG disclosure guideline. In doing so, it advances emerging-market ESG research by showing that, under Saudi Arabia’s largely voluntary disclosure regime and concentrated-ownership structure, board independence operates primarily as a risk-monitoring mechanism rather than as an amplifier of disclosure value. The findings imply that regulators should strengthen and progressively mandate ESG reporting frameworks, that investors should treat ESG transparency as value-relevant information, and that firms should view ESG transparency and prudent governance as strategic tools for enhancing market value in line with Vision 2030. Full article

With the global rise in sustainable investment concepts, environmental, social, and governance (ESG) factors have increasingly become important criteria influencing investment decisions. Although institutional investors are paying greater attention to corporate ESG performance, limited evidence exists regarding its impact within the Chinese A-share market. Using panel data from Chinese listed firms during the period 2010–2023, this study employs fixed-effects models with clustered standard errors as the baseline estimation method. To improve the robustness of the findings, Tobit regression, Logit regression, lagged-variable models, heterogeneity analysis, and Hausman tests are further conducted. The empirical findings indicate that the overall ESG score and the individual environmental (E), social (S), and governance (G) dimensions do not exhibit statistically significant effects on institutional ownership in the baseline fixed-effects regressions. The results suggest that ESG performance has not yet become a dominant determinant of institutional investment decisions in China’s capital market. However, the robustness tests based on Tobit and Logit models provide limited evidence that ESG performance may still influence institutional investor behavior under alternative empirical specifications. Furthermore, the heterogeneity analysis reveals that the relationship between ESG dimensions and institutional ownership differs across environmentally related and non-environmentally related firms, although the effects are generally weak and statistically limited. The study contributes to the ESG and institutional investment literature in three important ways. First, it provides updated evidence from the Chinese A-share market over the 2010–2023 period, reflecting the evolving stage of ESG development in emerging economies. Second, it comparatively examines the differentiated roles of environmental, social, and governance dimensions rather than relying solely on aggregated ESG indicators. Third, it highlights the limited and transitional nature of ESG integration among institutional investors in China, where traditional financial indicators continue to play a more important role in investment decisions. The findings provide important implications for policymakers, listed firms, and institutional investors seeking to promote sustainable finance development and improve the effectiveness of ESG disclosure practices in emerging markets. Full article

This paper shifts the research perspective from “Buddhist monasteries” to “monastic Buddhism,” using Nālandā Mahāvihāra as a micro-level case to illuminate the broader support mechanism of Indian Buddhist monasteries, with particular focus on the concept of “non-exhaustible endowment”. Drawing on epigraphic evidence, Vinaya texts, and Chinese pilgrims’ records, it finds that major donors supported monasteries through religious rituals, land grants, and cash investments, primarily in the form of landed property and gold and silver currency, which were designated as non-exhaustible endowments. Monasteries then engaged in agriculture, handicrafts, building industry, commerce, and lending, transforming static assets into a non-exhaustible cycle of capital that benefited both monastics and laity. Systems such as Yizhi (robe funds) and Gongfu zhi Zhuang (robe-providing estates) reveal mature financial services that not only liberated monks from economic constraints but also stimulated the cotton textile trade between India and China. The wealth possessed by monasteries was not static but perpetually engaged in a dynamic cycle of capital. Major Buddhist monasteries thus emerged as regional economic engines, which became the core value for continuous royal patronage, as well as the key incentive for their violent destruction by Turkic Muslims. However, the transformation of the religious landscape and economic network in late medieval Bihār was not a simplistic process. Faced with a changing political and religious environment over time, Sufi saints, Jain followers, Shaiva ascetics and other religious communities, each grounded in their own faiths, landholdings, commercial networks and educational systems, gradually displaced, restructured and undermined the Buddhist monastery-centered endowment mechanism, causing Buddhism to progressively lose its regional dominance as an institutionalized religion. 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

With the digital economy advancing at a fast pace, digital transformation plays a pivotal role in reinforcing firms’ innovation capability and promoting high-quality development. This study analyzes Chinese non-financial publicly listed firms on the A-share market over the period 2009–2023. Based on text mining of annual reports, this study constructs an index capturing digital transformation and empirically evaluate its impact on innovation output with firm and year fixed effects. The estimates suggest that digital transformation meaningfully increases firms’ innovation output; the inference is unchanged when applying instrumental-variable approaches and conducting extensive robustness checks. Mechanism analysis reveals two parallel channels: (1) the R&D investment mechanism, characterized by improvements in R&D intensity, capitalization rate, per capita efficiency, and investment growth; (2) the governance environment mechanism, reflected in enhanced internal control, improved information disclosure quality, and strengthened audit supervision. Once firms are stratified by characteristics, the estimated positive effect of digital transformation is most pronounced for firms with low financial constraints, large size, eastern locations, and state ownership. This study identifies both direct and indirect mechanisms linking digital transformation to innovation and highlights how firm- and region-specific features condition the magnitude of this effect, thereby offering empirical implications for corporate digitalization strategies and policy design. Full article

Whether information consumption guides firms back to their core businesses or instead exacerbates corporate financialization remains empirically underexplored. We use panel data of Chinese A-share listed firms from 2009 to 2024. We take China’s Information Consumption Pilot policy as a quasi-natural experiment and employ a staggered difference-in-differences approach to examine the impact of information consumption on corporate financialization. The findings show that information consumption significantly promotes corporate financialization, with the precautionary motive driving financialization more strongly than the profit-seeking motive. Mechanism tests reveal that information consumption drives corporate financialization by easing financing constraints and improving investment efficiency, while internal corporate governance and external economic policy uncertainty play significant moderating roles. Heterogeneity analysis indicates that the exacerbating effect of information consumption on corporate financialization is more pronounced in non-state-owned enterprises, small-scale firms, non-high-tech industries, and regions with a low level of financial development. Further analysis shows that information consumption not only exacerbates excessive corporate financialization but also triggers peer effects in financialization. Moreover, the financialization induced by information consumption suppresses long-term corporate performance growth. These findings uncover the micro-mechanisms through which information consumption reshapes corporate capital allocation decisions, offering practical implications for refining information consumption policies and channeling financial resources back to the real economy. Full article

During the stage of high-quality economic development, the synergy between advancing county industrial structure and employment growth has become a key issue in county governance. Although existing studies confirm that industrial structure has both creation and substitution effects on employment, few have adopted a configurational perspective to reveal how combinations of multiple factors can jointly promote both advanced county industrial structure and employment growth, thereby achieving industry-employment synergy. From the perspective of inclusive growth, this study incorporates six factors-economic level, financial level, innovation level, human capital, fiscal expenditure, and agricultural resources-into a unified analytical framework under the dimensions of efficiency and equity. Using a mixed method that combines dynamic QCA and regression analysis, and taking 1128 Chinese counties as the sample, this study explores configurational pathways that can simultaneously achieve advanced county industrial structure and inclusive employment growth. The findings are as follows: (1) Four configurational pathways lead to advanced county industrial structure: market-driven with efficiency priority (C1), endowment-substituted with factor concentration (C2), endowment-dependent with efficiency-equity coordination (C3), and talent–innovation dual-driven with government assistance (C4). (2) These four pathways differ in their effectiveness in promoting industry–employment synergy. Configurations C1, C2, and C3 achieve coordinated development of county industry and employment, whereas configuration C4 promotes advanced county industrial structure but inhibits employment growth. The conclusions reveal multiple equivalent pathways for synergistically enhancing county industry and employment, providing a basis for local governments to formulate context-specific industry–employment coordination policies. Full article

Corporate sustainability and the reliability of ESG reporting have gained relevance in the evaluation of listed companies, particularly in emerging capital markets, where reporting practices are still in their early stages of development. The purpose of this study is to analyze the relationship between the quality of ESG reporting, the risk of greenwashing estimated using a proxy derived from reported information, and the market value of companies listed on the Bucharest Stock Exchange. The research employs a mixed-methods design, involving content analysis of annual reports, sustainability reports, and sustainability statements for 25 companies over the 2020–2024 period. The scores corresponding to the Environmental, Social, and Governance dimensions, as well as the proxy for greenwashing risk, were developed using an ordinal scoring grid, which was validated through inter-rater assessment. During the course of the study, the empirical relationships were tested using pooled OLS specifications on short panel data, incorporating the natural logarithm of market capitalization, financial controls, year effects, and sector dummy variables. The results highlight the presence of an association between the quality of ESG reporting and market value, particularly for environmental and social dimensions, while the greenwashing risk proxy exhibits a limited statistical influence. The study contributes to the literature on ESG reporting in emerging markets and highlights the need for a cautious interpretation of indicators constructed based on corporate disclosures. Full article

Accounting harmonization enables the comparison of financial reporting and enhances its usefulness. The IFRS was developed to achieve such harmonization in a globalized world. This study focuses on the impact of transitioning from IAS 17 to IFRS 16 within the European airline industry. We conducted a quantitative analysis using non-parametric statistical tests to evaluate the impact on financial and economic ratios and compare the periods before and after the change, covering the period from 2018 to 2024. Our results show that both financial ratios and economic ratios were significantly affected by IFRS 16 adoption; namely, in contrast to prior studies, we show that ROE is significantly and positively affected, an important contribution of this study. Additionally, the size and type of airline company (low-cost, full-service, and flag airline companies) maintain these impacts, representing an innovative approach to this study compared to previous research. Overall, by recognizing both assets and liabilities in financial statements, IFRS 16 allows stakeholders to gain an accurate understanding of a firm’s capital structure and performance. This study contributes empirical evidence to the prior literature about the benefits of the new lease accounting standard and to improving the scientific knowledge on this topic. Full article

Cordyceps militaris is a high-value medicinal mushroom with growing demand in functional-food and nutraceutical markets, yet practical frameworks for small-scale, family-operated cultivation remain limited. This study presents an integrated technical and economic feasibility analysis of small-scale Cordyceps production under two scenarios: a one-room setup (Scenario 1) and a two-room configuration with a shared processing area and staggered scheduling (Scenario 2). Both use consistent biological, operational, and market assumptions with no hired labor, and the analysis covers capital expenditure (CapEx), operating costs (OpEx), profitability, payback, and break-even thresholds, complemented by sensitivity analysis of parameters such as biological efficiency and contamination rates. Both scenarios were technically and financially viable. Scenario 1 achieved a net present value (NPV) of $1761, an internal rate of return (IRR) of 10%, a 4.7-year discounted payback, and a 133% five-year return on investment (ROI); Scenario 2 attained an NPV of $85,437, a 66% IRR, a 1.6-year payback, and a 366% ROI. Because gross margins were consistent across scales, the expansion’s advantage stemmed from more efficient CapEx amortization rather than improved unit profitability. Cordyceps cultivation emerges as a viable family-operated, small-scale enterprise that can diversify family income, generate supplementary or primary earnings, and support urban and rural livelihoods. Full article

This study investigates place-based barriers to initial teacher training (ITT) recruitment in rural-coastal regions of England, focusing on Cornwall as a case study. Utilizing semi-structured interviews with nine ITT provider leaders and nine trainee teachers, the research applies the concept of educational isolation to ITT providers in areas that are geographically remote, socioeconomic disadvantaged, and culturally isolated. The analysis is framed by the critical pedagogy of place and social capital theory, moving beyond deficit-based interpretations of rurality to critically examine how place-based inequities are produced through urban-normative policy and resource allocation. Primary data were analyzed using reflexive thematic analysis. Four substantive themes emerged: transport dependency and accessibility constraints that structurally exclude lower-income and disabled trainees; housing displacement driven by the tourist economy, which compounds financial insecurity; an “employment precarity problem” where localized primary school oversaturation coexists with secondary teacher shortages; and cultural and professional isolation that disproportionately impacts ethnically diverse trainees in demographically homogeneous communities. The research further identifies that community resilience, while enabling individuals to navigate structural barriers, can obscure infrastructural inadequacy and diminish impetus for systemic policy reform. This paper contributes to international scholarship on spatial justice and rural teacher education by presenting an integrated conceptual framework with transferable relevance to similar rural-coastal and peripheral contexts globally and by offering policy recommendations for place-weighted ITT funding, infrastructure investment in educationally isolated areas, and the development of collaborative provider models. Full article