Search Results (94)

Industrial tree plantations (ITPs) are increasingly recognized as a sustainable response to deforestation and the decline in native wood resources in the Philippines. This study presents LUNTIAN (Labor, UNiversity, Timber Investment, and Agent-based Nexus), an agent-based model that simulates an experimental ITP operation within a mountain forest managed by University of the Philippines Los Baños. The model integrates biophysical processes—such as tree growth, hydrology, and stand dynamics—with socio-economic components such as investment decision making based on risk preferences, employment allocation influenced by local labor availability, and informal harvesting behavior driven by job scarcity. These are complemented by institutional enforcement mechanisms such as forest patrolling, reflecting the complex interplay between financial incentives and rule compliance. To assess the model’s validity, its outputs were compared to those of the 3PG forest growth model, with results demonstrating alignment in growth trends and spatial distributions, thereby supporting LUNTIAN’s potential to represent key ecological dynamics. Sensitivity analysis identified investor earnings share and community member count as significant factors influencing net earnings and management costs. Parameter calibration using the Non-dominated Sorting Genetic Algorithm yielded an optimal configuration that ensured profitability for resource managers, investors, and community-hired laborers while minimizing unauthorized independent harvesting. Notably, even with continuous harvesting during a 17-year rotation, the final tree population increased by 55%. These findings illustrate the potential of LUNTIAN to support the exploration of sustainable ITP management strategies in the Philippines by offering a robust framework for analyzing complex social–ecological interactions. Full article

Modern beef cattle reproductive management faces increasing challenges due to the growing global demand for beef. Reproductive efficiency is a critical factor determining the productivity and profitability of beef cattle operations. Optimal reproductive performance in a beef cattle herd is achieved when each cow produces one calf per year, maintaining a calving interval of 365 days. However, this goal is difficult to achieve, as the gestation period in beef cows lasts approximately 280 days, leaving only 80–85 days for successful conception. Traditional methods, such as visual estrus detection, are becoming increasingly unreliable due to expanding herd sizes and the subjectivity of visual observation. Additionally, silent estrus—where ovulation occurs without noticeable behavioral changes—further complicates the accurate estrous-based identification of the optimal insemination period. To enhance reproductive efficiency, advanced technologies are increasingly being integrated into cattle management. Sensor-based monitoring systems, including accelerometers, pedometers, and ruminoreticular boluses, enable the precise tracking of activity changes associated with the estrous cycle. Furthermore, infrared thermography offers a non-invasive method for detecting body temperature fluctuations, allowing for more accurate estrus identification and optimized timing of insemination. The use of these innovative technologies has the potential to significantly improve reproductive efficiency in beef cattle herds and contribute to overall farm productivity and sustainability. The objective of this review is to examine advancements in smart technologies applied to beef cattle reproductive management, presenting commercially available technologies and recent scientific studies on innovative systems. The focus is on sensor-based monitoring systems and infrared thermography for optimizing reproduction. Additionally, the challenges associated with these technologies and their potential to enhance reproductive efficiency and sustainability in the beef cattle industry are discussed. Despite the benefits of advanced technologies, their implementation in cattle farms is hindered by financial and technical challenges. High initial investment costs and the complexity of data analysis may limit their adoption, particularly in small and medium-sized farms. However, the continuous development of these technologies and their adaptation to farmers’ needs may significantly contribute to more efficient and sustainable reproductive management in beef cattle production. Full article

This research investigates the liability management of Thai life insurers in a prolonged low-interest rate environment. It examines the impact of interest rate changes on life insurance products, solvency, and profitability. The study identifies a significant shift in product portfolios toward non-interest-sensitive products, which helps mitigate financial risk and enhance solvency. The solvency of Thai life insurers is influenced by their return on assets, with higher risk exposures requiring more capital, potentially lowering solvency levels. However, the proportion of risky investment assets is not significantly related to the solvency position in the Thai market. The market index return is a significant predictor of stock returns for Thai life insurers, while changes in interest rate sensitivity are not statistically significant between low-rate and normal periods. The average solvency level under Thailand’s regulatory regime is also not statistically different between normal and prolonged low-interest rate situations. This study contributes to the understanding of liability management practices among life insurers in Thailand and provides insights into the challenges and strategies for maintaining solvency and profitability in a low-interest rate environment. Full article

Over the past decade, multifactor models have shown enhanced capability compared to single-factor models in explaining asset return variability. Given the common assertion that higher risk tends to yield higher returns, this study empirically examines the augmented human capital six-factor model’s performance on thirty-two portfolios of non-financial firms sorted by size, value, profitability, investment, and labor income growth in the Indian market over the period July 2010 to June 2023. Moreover, the current study extends the Fama and French five-factor model by incorporating a human capital proxy by labor income growth as an additional factor thereby proposing an augmented six-factor asset pricing model (HC6FM). The Fama and MacBeth two-step estimation methodology is employed for the empirical analysis. The results reveal that small-cap portfolios yield significantly higher returns than large-cap portfolios. Moreover, all six factors significantly explain the time-series variation in excess portfolio returns. Our findings reveal that the Indian stock market experienced heightened volatility during the COVID-19 pandemic, leading to a decline in the six-factor model’s efficiency in explaining returns. Furthermore, Gibbons, Ross, and Shanken (GRS) test results reveal mispricing of portfolio returns during COVID-19, with a stronger rejection of portfolio efficiency across models. However, the HC6FM consistently shows lower pricing errors and better performance, specifically during and after the pandemic era. Overall, the results offer important insights for policymakers, investors, and portfolio managers in optimizing portfolio selection, particularly during periods of heightened market uncertainty. Full article

Bank operations are contingent upon investor confidence, particularly during periods of economic distress. If investor confidence drops, a bank faces difficulties obtaining money, higher borrowing costs, and lower stock values. Non-performing loans (NPLs) potentially jeopardize a bank’s long-term viability and short-term profitability, and investors are naturally wary of institutions that pose a high credit risk. The purpose of the study was to explore how non-performing loans influence investor confidence in banks. A purposive sampling technique was used to identify 253 New York Stock Exchange banks in the Thomson Reuters Eikon DataStream that satisfied all the inclusion and exclusion selection criteria. The Common Correlated Effects Mean Group (CCEMG) and Generalized Method of Moments (GMM) models were used to analyze the data, providing insight into the relationship between the variables. The study discovered that NPLs had a negative and significant influence on price–earnings (P/E) and price-to-book value (P/B) ratios. Furthermore, the bank’s age was found to have a positive and significant relationship with the P/E and P/B ratio. The moderating relationship between NPLs and bank age was found to have a negative and significant influence on price–earnings (P/E) and price-to-book value (P/B) ratios. The findings underscore the importance of asset quality and institutional reputation in influencing market perceptions. Bank managers should focus on managing non-performing loans effectively and leveraging institutional credibility to sustain investor confidence, particularly during financial distress. Full article

The B Corp certification is a voluntary designation granted by B Lab. This nonprofit organization evaluates two main aspects of a company’s operations: the positive impact generated by its daily activities and how its business model reflects unique practices that yield positive outcomes for its stakeholders. Sistema B is at the forefront of the B movement in Latin America and the Caribbean, working to develop an ecosystem that enables B Corps to harness market forces to address social and environmental challenges. However, the B Corp movement in this region faces significant challenges, primarily due to a lack of government support, including tax benefits and legal recognition. This study aims to advance the existing literature on B Corps by examining sustainability-oriented hybrid organizations that strive to reconcile profit generation with social impact within the context of Mexico’s socioeconomic landscape. Additionally, it seeks to enhance the understanding of how ventures navigate trade-offs between financial and social objectives, and to identify factors that can help address these challenges. Twenty semi-structured interviews were conducted with Mexican B Corps to explore the entrepreneurial motivations related to social objectives, the B Corp movement, and the internal organizational dynamics of balancing social and economic logics. We discuss how tensions arise and are managed, as well as the issues regarding regulatory tensions in Mexico and the challenges that stem from organizational complexities. Future research directions are also outlined. Full article

This study aims to analyze the determinants of bank profitability in Angola by employing panel data econometric models, specifically, the Generalized Method of Moments (GMM), to assess the impact of internal and external factors on the financial indicators ROE, ROA, and NIM for the period 2016 to 2023. The results reveal that credit risk, operational efficiency, and liquidity are critical determinants of banking performance. Effective credit risk management and cost optimization are essential for the sector’s stability. Banking concentration presents mixed effects, enhancing net interest income while potentially undermining efficiency. Economic growth supports profitability, whereas inflation exerts a negative influence. The COVID-19 pandemic worsened asset quality, increased credit risk, and led to a rise in non-performing loans and provisions. Reforms implemented by the National Bank of Angola have contributed to strengthening the banking system’s resilience through restructuring and regulatory improvements. The rise of digitalization and fintech presents opportunities to enhance financial inclusion and efficiency, although their success relies on advancing financial literacy. This study contributes to the literature by providing updated empirical evidence on the factors influencing bank profitability within an emerging economy’s distinctive institutional and economic context. Full article

The current study examines the application of advanced machine learning (ML) techniques for forecasting credit risk in Islamic (participation) and traditional banks in the United Kingdom in 2010–2023. Leveraging an equally weighted panel dataset and guided by robust empirical literature, we integrate structural econometric modeling—i.e., the stochastic frontier approach (SFA) to measuring the Lerner index of market power—with current best-practice tree-based ML algorithms (CatBoost, XGBoost, LightGBM, and Random Forest) to predict non-performing loans (NPLs). The results show that bank-level financial performance measures, particularly loan ratio, profitability, and market power, outperform macroeconomic factors in forecasting credit risk. Among the models tested, CatBoost was more accurate and explainable, as confirmed by SHAP-based explainability analysis. The implications of the research have practical applications for risk managers, regulators, and policymakers in terms of valuing the explanatory power of explainable AI tools to enhance financial oversight and decision-making in post-crisis UK banking. Full article

This study investigates the relationship between capital structure and financial performance in South African firms, focusing on the potential non-linear, inverse U-shaped effect of leverage on profitability. Drawing on data from 1548 firm-year observations covering 183 publicly listed South African companies between 2013 and 2022, the analysis employs both Fixed Effects (FE) and System Generalized Method of Moments (System-GMM) models to address endogeneity and capture dynamic adjustments. The findings indicate that moderate levels of debt enhance profitability, but excessive leverage leads to diminishing returns, confirming an inverse U-shaped relationship. System-GMM results further reveal the persistence of past profitability and validate the dynamic nature of capital structure decisions. Larger firms appear more capable of sustaining higher leverage without adverse effects, while smaller firms benefit from maintaining lower debt levels. The study concludes that strategic debt management, tailored to firm size and economic context, is critical for optimizing financial performance in emerging markets like South Africa. The study identifies the optimal leverage ratio for South African firms and shows how firm size moderates the relationship between debt and profitability, offering tailored insights for firms of different sizes. These insights offer valuable guidance for managers, investors, and policymakers aiming to strengthen financial stability and efficiency through informed capital structure choices. Full article

This study investigates how Environmental, Social, and Governance (ESG) scores and the Corporate Governance Index (CGI) jointly influence firm value in Türkiye. To address the contextual limitations of global ESG metrics, this study incorporates the CGI, a country-specific governance measure developed by Capital Markets Board of Türkiye, as a complementary indicator. Using panel data from 44 non-financial firms listed on the Istanbul Stock Exchange between 2019 and 2023, the study applies a random effects regression model with robust standard errors. The findings indicate that both ESG and CGI scores are positively and significantly associated with firm value, along with profitability (ROA), while financial leverage and liquidity (CR) show negative effects. The results underscore the strategic value of aligning sustainability performance with governance quality, particularly in emerging market contexts. This study contributes to the literature by providing empirical evidence for an integrated ESG–CGI framework and offers practical insights for corporate managers, investors, and policymakers. Full article

The United Kingdom has enacted rules to support green investment, enhancing the financial sustainability of enterprises adopting sustainable practices. These enactments offer financial incentives to enterprises that invest in sustainable initiatives. Companies that do not adopt sustainable practices face increasing operating expenses, a declining market share, and diminished investor trust. This study leveraged the stakeholder theory to examine the impact of sustainable finance on business financial performance. The study focused on 143 non-financial companies listed on the London Stock Exchange, using 17 years of data between 2008 and 2024 obtained from Thomson Reuters Eikon DataStream. The data were analyzed using the two-step Generalized Method of Estimation (GMM) due to endogeneity identified in the data. The study discovered that green financing initiatives, policies for emission reduction, and sustainable product initiatives had a positive and significant impact on business financial performance. The study also revealed that environmental investment initiatives negatively and significantly impacted business financial performance. Investing in green finance and sustainable products enhances financial performance by fostering investor trust and bolstering corporate reputation, fortifying firms. Adhering to international sustainability standards promotes long-term value creation and market alignment. To mitigate financial strain, environmental investments necessitate stringent cost management. An equitable strategy ensures that, by mitigating risks, sustainability measures enhance profitability. By meticulously integrating these projects, companies can achieve environmental and financial benefits while sustaining a competitive advantage in a rapidly evolving corporate landscape. Full article

As nonprofits operate in a competitive environment with limited resources, they constantly seek new ways to optimize their resources. This study investigates factors influencing nonprofits’ decision to integrate flexible labor, such as independent contractors, into their workforce. Using longitudinal data from 2008 to 2018 in the arts and cultural sector in the United States, this study tests hypotheses related to the impact of an organization’s financial health, cost of permanent employment, reliance on government funding and donations, organizational size, and service demand variations on flexible labor use. The findings confirm that nonprofits offering higher fringe benefits and facing greater service demand fluctuations rely more on flexible labor. However, contrary to our expectations, this study also finds that nonprofits with stronger long-term financial health are more inclined to adopt flexible labor, while larger nonprofits use less flexible labor than their smaller counterparts. This study advances our understanding of the organizational and sector-level factors behind flexible labor adoption in nonprofits and offers practical implications for managing it. Full article

This study investigates the non-linear effect of the cash conversion cycle (CCC) on a firm’s profitability for a sample of 6072 firms from five countries (Germany, Spain, France, Great Britain, and Italy) from 2006 to 2015. Additionally, this study explores the sensitivity of economic crises to the non-linear effect of the CCC on a firm’s performance. This study employs fixed-effects unbalanced panel data and weighted least squares (due to heteroscedasticity) to examine a firm’s performance, using return on assets (ROA) to measure profitability. The cash conversion cycle, financial leverage, size, and tangibility are independent variables. The results of this study show that the effect of the cash conversion cycle on firms’ performance is an inverted U-shape (non-linear). It also shows that the economic conditions vis-à-vis crises influence firm performance. This study found the optimal number of the CCC to be 90 days for the entire sample, 85 days for the non-crisis period, and 92 days for the crisis period. It also finds that the marginal effect of the CCC on ROA is 3.9 times higher during economic crises versus non-economic crisis periods. This study contributes to the existing working capital management literature by examining the non-linear effect of the cash conversion cycle on profitability and the sensitivity of these effects during economic crises. Thus, empirical evidence can serve scholars, business policymakers, and corporate finance professionals in managing their working capital strategically. Full article

In an increasingly competitive construction industry, quality management systems (QMSs) play a critical role in improving operational performance and customer satisfaction. Despite growing interest, limited research has examined how customer-oriented QMSs affect financial and non-financial outcomes in construction firms, particularly in emerging markets such as Kazakhstan. This study investigates the relationship between QMS implementation and company performance by analyzing data from 23 Kazakhstani construction companies. The methodology combines regression analysis, multivariate analysis, and k-means clustering to assess the impact of QMSs on sales volume, product profitability, quality management costs, and customer satisfaction. Regression analysis revealed that customer satisfaction (CSL), product profitability (PP), and economic efficiency of the QMS (EEQMS) have a statistically significant positive effect on sales volume (SV), while excessive quality costs (QMC) may negatively influence performance if not optimized. Cluster analysis further identified distinct groups of companies with varying levels of QMS effectiveness and profitability. This study offers empirical evidence on the financial value of customer-oriented QMSs in the construction sector. It contributes to the literature by highlighting performance drivers in QMS implementation and provides practical recommendations for managers and policymakers to improve quality strategies in similar regional contexts. Full article

This study aims to investigate the impact of environmental accounting disclosures on the financial performance of banks listed on Borsa Istanbul (BIST). In this study, sustainability and integrated reports for 2019–2023 are analyzed, and environmental accounting disclosures are classified into two categories as operational and financial activities. Using the Environmental Accounting Reporting Score, the relationship with financial performance indicators such as return on assets, return on equity, earnings per share, and profit margin is analyzed using the seemingly unrelated regression (SUR) method. The results show that environmental accounting disclosures do not have a direct and statistically significant effect on financial performance. However, control variables such as bank size, debt-to-asset ratio, and loan-to-asset ratio are found to have a positive effect on financial performance. In particular, larger banks tend to have higher profitability and earnings per share, while higher non-interest expenses have a negative impact on profitability. The study shows that the direct contribution of environmental accounting practices to financial performance is limited, but that banks’ operational and financial structures are greater determinants of performance. These findings highlight the need for improvements in areas such as standardization of sustainability reporting, stakeholder awareness, and environmental risk management for policy makers and banks. Full article