Search Results (291)

The relationship between capital structure and firm market valuation remains a central yet unresolved question in corporate finance, with outcomes shaped critically by industry-specific asset structures and financing environments. This study investigates how capital structure influences market valuations across two structurally divergent sectors in India, the asset-light information technology (IT) industry and the asset-intensive automobile industry, using balanced panel data for 14 firms in each sector over 2005–2024. Fixed effect and random effect panel regression models are employed to isolate the direct effect of leverage on earnings per share (EPS), with model selection determined by the Hausman specification test. Complementing these estimations, the Graphical Lasso is applied to recover a sparse conditional dependence network among key financial variables, an approach particularly suited to this research question, as capital structure, profitability, tangibility, and growth are jointly determined, rendering pairwise correlations insufficient for identifying genuine financial linkages. The findings establish that debt exerts a positive and statistically significant effect on market valuations in both sectors, but through distinct economic channels: moderate leverage amplifies profitable growth signals in IT firms, while tax shield benefits drive valuation in automobile firms, constrained by asset tangibility and debt-servicing thresholds. These results support trade-off theory in the automobile sector and pecking order logic in the IT sector, underscoring that sector-specific financing strategies yield superior valuation outcomes compared to universally applied capital structure prescriptions. Full article

Environmental uncertainty (EU) has become one of the key determinants influencing corporate decision-making, yet the existing literature has not sufficiently explored its effects. Based on the data from Chinese non-financial public companies during the period from 2010 to 2023, we examine the impact of EU on carbon emission. The empirical results show that EU has a significant negative impact on corporate carbon emission. Specifically, a one-unit increase in EU leads to approximately a 9.13 percent decline in carbon emission. Furthermore, we find that EU increases firms’ financing constraints, thereby reducing capacity-utilization and carbon emission. Meanwhile, EU can spur innovation, resulting in active decarbonization. Finally, the finding is more pronounced in non-state-owned enterprises (N-SOEs). The above findings shed light on promoting carbon reduction for policymakers and corporate operators. Full article

The aquafeed industry is seeking sustainable alternatives to fishmeal, and insect meals are promising candidates. However, quantitative syntheses of their effects on non-fish aquatic animals like shrimp, crabs, turtles, and frogs are limited. This meta-analysis evaluated five insect meals—black soldier fly, Coleoptera, housefly, silkworm, and Orthoptera—on specific growth rate (SGR), weight gain rate (WGR), and feed conversion ratio (FCR). A total of 69 studies (2004–2025) were included. Hedges’ g was pooled using random-effects models, and meta-regressions examined dose–response relationships. Among all categories, only silkworm meal improved or maintained growth, showing no significant negative dose–response relationship. In contrast, black soldier fly and Coleoptera meals impaired growth, with a negative linear dose–response. Subgroup analyses revealed species-specific responses; shrimp, particularly Litopenaeus vannamei, exhibited growth depression, whereas some crab species, including Scylla paramamosain and Eriocheir sinensis, showed tolerance or improved performance. Housefly and Orthoptera meals were evaluated in fewer studies, precluding firm conclusions. Thus, the efficacy of insect meal substitution is jointly determined by insect type and host physiology. Silkworm pupae meal is a favourable fishmeal alternative, while black soldier fly and Coleoptera meals require conservative inclusion limits, especially for shrimp. Full article

Currently, a major challenge for European economies is the volatility of electricity prices, which affects costs borne by households and firms, as well as inflation, economic competitiveness, and energy security. Although the literature has analysed various determinants of electricity prices, there is still limited evidence on the comparative short- and long-term effects of fiscal factors, the natural gas market, and the transition to renewable energy within the Member States of the European Union. This paper analyses the relationship between household electricity prices and a set of economic, climate, and fiscal determinants in EU countries over the period 2017–2025, using panel data econometric methods. The methodology includes pooled OLS models, fixed and random effects estimators, unit root tests, cross-sectional dependence (Pesaran CD) tests, cointegration analysis, and a Panel ARDL-PMG framework, complemented by robustness checks using FMOLS and DOLS-type estimators. The results indicate the existence of a stable long-run equilibrium relationship between the analysed variables, as well as significant cross-sectional dependence among countries, reflecting common shocks and interconnected dynamics in EU energy markets. Fixed effects models are used as the baseline specification, while PMG-ARDL and other dynamic estimators are employed for robustness analysis. The results are consistent across different econometric specifications. The conclusions highlight the dominant role of Household Gas Prices as the main determinant of electricity prices, while energy productivity shows a positive association with electricity price levels. Climate variables exhibit weak and unstable effects, and environmental taxes do not show statistically significant impacts within the sample period. Overall, the findings underline the importance of energy market dynamics, structural factors, and the ongoing energy transition in shaping electricity price developments in the European Union. 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

Construction management, from the contractor’s perspective, is led by the Construction Manager (CM). The work motivation and leadership style of the CM are critical variables for the successful execution of construction projects. The scientific literature identifies participative leadership as the most effective style for mitigating conflicts among various stakeholders. However, analyzing the specific variables that influence a CM’s conflict resolution capacity remains an underexplored area. Furthermore, while the CM must act as a leader for their team (subcontractors, suppliers, etc.), they remain accountable to the contractor’s senior management. Therefore, this study aims to analyze the mediating role of CM motivation in the relationship between leadership and conflict resolution capacity using Partial Least Squares Structural Equation Modeling (PLS-SEM). In the construction industry, conflict resolution is not merely a situational fix but a critical process of capturing and externalizing tacit knowledge. Knowledge management and the ability to resolve conflicts in the construction sector are directly linked, critical, and strategic in nature. Construction is an industry characterized by fragmentation, the temporary nature of its projects, diversity of stakeholders (developers, builders, subcontractors, engineering firms) and a high level of uncertainty. In this environment, conflict is virtually inevitable. However, the way in which a CM handles a conflict determines whether it becomes a destructive dispute or an opportunity for improvement. Full article

This study investigates how eco-efficiency and socio-efficiency influence firms’ default risk across the European financial, industrial, and consumer service sectors from 2010 to 2024. This study aims to determine whether integrating environmental and social performance into corporate strategies mitigates financial distress over time. The Pooled Mean Group ARDL estimator was employed to capture the short- and long-term dynamics. The results indicate that higher eco- and socio-efficiency significantly reduce long-term default risk, particularly in the financial and industrial sectors. Short-term effects were found to be insignificant, suggesting that sustainability benefits gradually emerged. This study offers novel sector-specific evidence linking sustainability efficiency to default risk in European firms and provides insights into how environmental and social efficiencies enhance corporate resilience and financial stability. Full article

This study investigates the determinants and predictability of stock return volatility by integrating firm-specific financial characteristics with advanced econometric and volatility modeling techniques. Using an unbalanced panel dataset comprising 1596 firms and 19,752 firm-year observations from MENA stock markets over the period 2010–2024, the analysis employs fixed-effects panel regression models, conditional volatility models, and machine learning-based forecasting approaches. Following extensive diagnostic testing, including tests for heteroskedasticity, serial correlation, cross-sectional dependence, and model specification, a two-way fixed-effects model with Driscoll–Kraay standard errors is adopted as the preferred estimation framework. The results indicate that liquidity ratio, cash ratio, sales growth, firm age, lagged volatility, and lagged returns are significant determinants of stock return volatility, whereas leverage, tangibility, board independence, firm size, Tobin’s Q, and profitability do not exhibit statistically significant effects after controlling for firm-specific and time-specific heterogeneity. The volatility analysis reveals substantial persistence in stock return volatility, with the EGARCH-t specification providing the best fit among the competing GARCH-family models according to the Akaike Information Criterion. The estimated asymmetry parameters indicate that volatility responds differently to positive and negative shocks, supporting the presence of asymmetric volatility dynamics and the suitability of asymmetric volatility models. The forecasting analysis shows that advanced machine learning and deep learning models achieve competitive predictive performance; however, differences in predictive accuracy across models are generally modest. Full article

This study aims to examine whether and how environmental, social, and governance (ESG) performance is related to corporate tax avoidance in a non-linear and threshold-dependent manner using explainable machine learning. Based on 6461 firm-year observations of publicly listed European firms over the 2018–2023 period, this study employs a multi-algorithmic machine-learning classification framework. Model interpretability is achieved through SHAP, which identifies feature importance, marginal effects, interaction patterns, and ESG-related threshold dynamics. The results demonstrate that the ESG–tax relationship is highly non-linear. While the Country and Industry factors establish baseline tax risks, ESG sub-dimensions act as critical firm-level determinants. Specifically, high Corporate Social Responsibility (CSR) and Human Rights scores effectively constrain tax avoidance. In contrast, exceptionally high Management scores correlate with increased tax-avoidance risk. These findings support the legitimacy buffer argument and show that strong governance may also reflect managerial sophistication and capacity for less visible tax planning. The study contributes by revealing non-linear ESG threshold effects and by demonstrating how XAI/SHAP can distinguish between symbolic and substantive sustainability practices in corporate tax behavior. Full article

Polygalacturonase (PG) is a key enzyme in cell wall metabolism and fruit ripening. Atemoya (Annona cherimola Mill. × A. squamosa L.) is a high-value tropical fruit that undergoes rapid postharvest softening at room temperature. However, the role of the atemoya PG gene family in this process remains unknown. This study determined that storing atemoya at 28 °C significantly reduced fruit firmness and the total pectin content but increased water-soluble pectin (WSP) and PG activity compared to storage at 15 °C. Genome-wide identification of the AaPG gene family in atemoya revealed that 40 AaPG genes were unevenly distributed across seven chromosomes. Nineteen genes were located within six tandem duplication clusters. AaPG proteins exhibited clade-specific differences: Clades B-E contained the polysaccharide lyase family 6 (PL-6) superfamily domain, while Clade A harbored the Aspergillus niger polygalacturonase 1 (Pgu1) domain and lacked several conserved motifs. Expression profiling and reverse transcription quantitative polymerase chain reaction (RT-qPCR) showed that AaPG19, AaPG21, AaPG23 and AaPG24 were specifically induced at 28 °C. Subcellular localization confirmed that these four proteins were located on the plasma membrane. These findings provide insights into the evolution and temperature-dependent regulation of the AaPG family, identifying candidate genes responsible for the rapid softening of atemoya fruit. Full article

Although small and medium enterprises (SMEs) anchor employment and output across Sub-Saharan Africa, their uptake of artificial intelligence (AI) lags global benchmarks, and prevailing explanations dwell on capital, infrastructure, and institutional voids while overlooking the leadership competencies that determine whether available resources are mobilised at all. Addressing this gap, the present study asks how the digital leadership capabilities of SME owner-managers shape their intention to adopt AI in Nigeria, and through what organisational mechanisms and under what boundary conditions this influence operates. Anchored in the Diffusion of Innovation Theory and the Tigre–Henriques–Curado model of digital leadership, a cross-sectional survey was administered to owner-managers of registered SMEs drawn from six states; a sample of 390 was derived from a population of 23,290 firms using the Taro Yamane formula with proportionate allocation, and 306 valid responses were retained. Partial Least Squares Structural Equation Modelling (WarpPLS 8.0) was applied after confirming reliability (Cronbach’s $\alpha$: 0.69–0.84; composite reliability: 0.83–0.88), convergent validity (AVE: 0.56–0.67), and common method bias control. Strategic ($\beta$ = 0.298), interpersonal ($\beta$ = 0.245), and personal attribute ($\beta$ = 0.129) capabilities each significantly raised AI adoption intention. In contrast, delivery-related capabilities ($\beta$ = 0.090, p = 0.057) did not, indicating that pre-adoption intention is governed by cognitive-strategic and relational competencies rather than execution skills. Organisational innovation climate partially transmitted the effects of strategic and interpersonal capabilities, and firm size amplified the interpersonal pathway in medium-sized firms. The study contributes a leadership-centred account of AI adoption in an under-researched African setting and, by estimating mediation and moderation within a single framework, clarifies both why and when digital leadership translates into AI readiness, yielding capability-specific guidance for owner-managers and SME support policy. Full article

As climate change challenges intensify, the low-carbon transition has emerged as a fundamental structural transformation reshaping the global economic system and promoting sustainable development. In China, the “Dual Carbon” goals announced in September 2020 represent a landmark policy shift that imposes substantial environmental and regulatory pressure on high-carbon-emission enterprises. Against this backdrop, understanding how firms are adjusting their financial reporting practices to align with the low-carbon transition holds considerable significance for fostering their long-term sustainable development. Unlike previous studies that primarily attributed accounting conservatism to firm-specific risks or general economic uncertainty, this paper views the low-carbon transition as a structural institutional shock that reshapes firms’ external governance environment and information conditions, thereby offering a policy-driven explanation for accounting conservatism. Analysis using the Difference-in-differences method demonstrates that the low-carbon transition significantly enhances accounting conservatism among these enterprises (coefficient = 0.008, t = 4.13). Furthermore, mechanism analysis reveals that the low-carbon transition increases accounting conservatism through financing constraints and media attention. Heterogeneity analysis further indicates that the relationship between the low-carbon transition and accounting conservatism is more pronounced in non-state-owned enterprises, firms located in the eastern region, those facing intense industry competition, and companies with low levels of green innovation. Overall, the findings suggest that accounting conservatism is shaped not only by firm-level factors but also by large-scale institutional and policy transitions. By emphasizing that environmental regulation is a structural determinant of financial reporting behavior, this study extends the accounting conservatism literature. Furthermore, it demonstrates that improving financial reporting quality and risk identification capabilities enhances firms’ ability to address the challenges of the low-carbon transition, thereby fostering their long-term sustainable development. Full article

Background: The sensory quality of melon (Cucumis melo L.) is determined by the complex interplay of metabolites within the fruit. However, the underlying metabolic mechanisms based on consumer sensory experience remain underexplored. Methods: Sensory evaluation was conducted on twelve melon cultivars, recording flesh color and quantitatively scoring acidity, sweetness, firmness, and aroma intensity. Based on the sensory results, eight cultivars were selected to establish two contrasting groups: sweet-type vs. acidic-type and orange-fleshed vs. green-fleshed. Untargeted metabolomics (UPLC-QTOF-MS) was then performed to analyze the samples, and differential metabolites were screened using OPLS-DA combined with univariate analysis. Results: Pathway enrichment analysis revealed that the key distinction between sweet and acidic taste profiles was associated with the specific accumulation of citric acid within the tricarboxylic acid (TCA) cycle in the acidic-type group. Regarding flesh color, the orange-fleshed group was enriched with carotenoid derivatives like β-citraurinene and the oxidized tocopherol product α-tocopherolquinone, whereas the green-fleshed group mainly accumulated phytol, a chlorophyll degradation product, along with more abundant terpenoids. Conclusions: By integrating sensory phenotyping with metabolomic analysis, this study identified key differential metabolites and candidate pathways associated with taste and color in melon, providing metabolic insights and data resources for quality evaluation and regulation. Full article

This study explores the informativeness of forward-looking disclosures in managers’ speeches in U.S. quarterly earnings conference calls, focusing on time-frame specificity—whether statements provide precise temporal horizons. Using a keyword search, forward-looking statements (FLSs) in managers’ speeches in U.S. quarterly earnings conference calls are classified into those with and without specific time frames, and tests of their determinants, market responses, and implications for firms’ future performance are conducted. First, uncertainty is positively associated only with FLSs without time frames, likely because managers find it more difficult to specify time frames under uncertainty or are less willing to be held accountable. Second, investors respond more quickly to FLSs with time frames and more slowly to those without, while analysts use both types to improve forecasts; however, FLSs without time frames increase forecast dispersion, whereas those with time frames reduce it, suggesting greater information processing difficulty. Third, larger changes in future earnings and discretionary accruals are associated with more FLSs without time frames, while capital investment increases only with more FLSs with time frames. Collectively, these findings indicate that time-frame specificity conveys differential informational value. Full article

The climate emergency in Latin America and the Caribbean (LAC) has transformed sustainability from an aspirational goal into a strategic imperative, particularly in the context of decoupling economic growth from natural capital depletion. This research analyzes eco-innovation within the frameworks of the National Innovation System (NIS), open innovation, and absorptive capacity, with the objective of examining the moderating role of collaboration in overcoming financial, knowledge, and market-related obstacles to innovative behavior. Employing a quantitative methodology using firm-level microdata from the Latin American Harmonized Innovation Surveys (LAIS) between 2007 and 2017, this study focuses on eco-innovative outcomes specifically linked to reductions in energy and material consumption. By estimating models that assess the role of technical cooperation and public policy support, this study seeks to determine whether collaborative strategies operate as an effective buffer against uncertainty and the limitations of local innovation systems. Expanding the scope of previous analyses centered on a single country, this work provides a regional perspective that underscores institutional and sectoral disparities in emerging contexts. Ultimately, this research examines how integrating an environmental purpose into corporate strategy and strengthening absorptive capacity enable LAC firms to transform ecological pressures into sustainable competitive advantages, mitigating the barriers that traditionally hinder technological progress in the region. Full article