Search Results (25)

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

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

The Cuckoo Catfish Optimizer (CCO) is a recent swarm method with four built-in movement strategies. Its weakness is not the moves themselves but the way it chooses among them: a fixed chain of random-versus-threshold ($\mathrm{rand}>C$) tests that ignores how each agent is actually doing and keeps no memory of which move has been paying off. On harder, higher-dimensional problems, this rigidity drains diversity and the search stalls. We propose CCO-RL, which hands the choice of move to a small tabular Q-learning controller. For every agent at every iteration, the controller reads a 48-state summary of the agent’s crowding, its recent stagnation and how far the run has progressed, then picks one of the four moves. A bounded reward and a decaying $\epsilon$-greedy rule let it learn a policy online with no extra function evaluations. We test CCO-RL against the original CCO and eight popular metaheuristics on CEC2017 ($D=30,50$) and CEC2022 ($D=20$): 70 instances, 30 runs each. CCO-RL earns the best overall Friedman rank ($1.69$) and significantly beats every external competitor according to the Nemenyi test. It also finds the best mean design in three engineering problems. Full article

This study examines how institutional quality (INST) affects the contribution of natural resource endowments (NREs) to citizens’ happiness and life satisfaction. It also identifies the INST threshold above which NREs enhance citizens’ life satisfaction and happiness. Consistent with challenges of low happiness levels, weak institutions, and the pervasive resource curse in Africa’s resource-rich economies, we analyse a dataset of these economies from 2012 to 2022. This study employs a robust standard-error Driscoll–Kraay nonparametric covariance matrix, dynamic common correlated effects, fully modified least squares, the method-of-moments quantile regression, and a dynamic panel threshold estimator. The findings suggest that natural resource endowment is a curse that lowers life satisfaction. Meanwhile, threshold analysis indicates that most resource-rich African countries fall short of the institutional development required to transform this curse into a blessing by encouraging the efficient allocation of resource earnings to initiatives that increase people’s happiness. Most of Africa’s resource-rich economies operate below this threshold. This study concludes that in Africa’s resource-rich countries, institutions are vital to incentivise the effective distribution of the proceeds from these resources to initiatives that enhance citizens’ happiness. Full article

The growing generation of household hazardous waste (HHW) presents critical environmental and public health challenges worldwide. This study investigates prevailing trends in HHW management and analyzes the socio-economic and demographic determinants that influence public perceptions, attitudes, and behaviors toward HHW recycling practices. A comparative mass flow analysis is also conducted to evaluate the limitations of current HHW management practices in Greece and outline policy implementation plans. Statistical findings indicate that income significantly influences recycling behavior. Individuals with annual incomes between €10,001 and €30,000 are less likely to engage in HHW recycling, whereas those earning over €70,000 demonstrate higher levels of recycling participation. The public recognizes the need for green collection points for appropriate HHW management. However, no statistically significant correlation is found between income levels and perceived importance of these facilities. This outcome is attributed to the high proportion (46.7%) of dichotomous variables in the χ² independence test, exceeding the recommended threshold of 25%, which limits interpretability. Such findings indicate the complex interplay of behavioral and socio-economic variables in HHW recycling. The study highlights the importance of targeted public policies, educational interventions, and infrastructure improvements to increase recycling participation and promote sustainable HHW management in Greece. Full article

In this study, we develop a game-theoretic optimization framework to analyze competing vessels’ technology choices between shore power (SP) and low-sulfur fuel oil (LSFO) within a maritime supply chain which is regulated by a cap-and-trade mechanism. Using a Stackelberg game approach, we construct two models—one port-led and the other vessel-led—to derive closed-form equilibrium for pricing, service quantities, profits, emissions, and social welfare. The results reveal three key findings. First, the leader in either Stackelberg structure always achieves higher profits, while total supply chain profits remain identical across power structures. Second, at low carbon prices, LSFO-equipped vessels provide more services and earn higher profits due to cost advantages. As the carbon price rises—which directly incentivizes emission reduction and accelerates maritime decarbonization—SP becomes more attractive and eventually dominates in profitability despite higher initial investment. Notably, although SP has lower unit emissions, its total emissions may surpass those of LSFO at certain carbon-price thresholds because the SP-equipped vessel optimally expands output. Third, intensified competition reduces service quantities, profits, and emissions, with a more substantial reduction effect on LSFO vessels. Overall, our results provide mathematically grounded insights for optimizing low-carbon technology adoption in maritime transport and offer actionable policy implications for carbon pricing that balance environmental objectives and supply chain efficiency. This research contributes specifically to the United Nations’ Sustainable Development Goals (SDGs), specifically SDG 13 (Climate Action) and SDG 9 (Industry, Innovation and Infrastructure). Full article

This study re-examines the ongoing debate over corporate disclosure frequency amid renewed calls to replace quarterly with semiannual reporting in U.S. markets. While traditional theories hold that frequent disclosure enhances informational efficiency by reducing asymmetry, emerging evidence highlights trade-offs involving managerial myopia, earnings management, and heightened short-term volatility. Using data from 2007 to 2024, the study compares Dow Jones Industrial Average firms, which report quarterly, with STOXX 50 firms, which report semiannually, to assess how disclosure cadence affects market reactions to earnings news The methodology involves identifying volatility regimes using Self-Exciting Threshold Autoregressive (SETAR) models, estimating dynamic betas with the GARCH(1,1) model, and analyzing shock transmission through vector autoregressions with cumulative impulse response functions (CIRFs). The results show that quarterly reporters exhibit larger immediate price reactions but faster normalization, implying that more frequent reporting accelerates information assimilation while amplifying contemporaneous volatility. Sectoral heterogeneity is pronounced: cyclical industries display higher beta volatility and steeper, but shorter-lived responses, whereas defensive stocks exhibit smoother convergence. These findings suggest that disclosure frequency influences both the intensity and duration of information shocks, providing insights for regulators who aim to balance transparency, market efficiency, and reporting costs across varying volatility and sectoral environments. Full article

This study estimates student loan borrowers’ repayment burdens (RBs) in South Korea. Using data from the Survey Report on Labor Conditions by Employment Type and novel administrative records, we estimate life-cycle earnings profiles by income quantile through RIF regression. These estimates are then used to derive RBs for hypothetical borrowers under income-contingent loans (ICLs) and mortgage-type loans, and to evaluate RBs for actual ICL borrowers by matching them with estimated income profiles. The findings suggest that Korea’s student loan system plays a positive role in expanding access to higher education, particularly through ICLs. Many low-income students who benefited from ICLs are later found in the top income deciles. However, raising the repayment threshold irrespective of borrower income may delay repayment and reduce system efficiency. These results underscore the importance of aligning repayment rules with borrowers’ earnings trajectories to ensure both equity and the long-term sustainability of the loan system. Full article

This paper examines stochastic cooperation in markets with two sellers who exhibit one-sided dependency. The independent seller’s pricing influences the dependent seller’s demand, but not vice versa. We study the one-dimensional hybrid game class whose parameter is the exogenously given probability of cooperation. In each game of this class, both sellers simultaneously choose prices that determine their endogenous threats, i.e., conflict profits. The sellers are aware of the cooperation probability but cannot condition prices on whether or not there is cooperation. We characterize the equilibrium prices and the sellers’ expected profits. Our main result shows that the independent seller earns higher expected profits when cooperation is more likely. In contrast, the dependent seller earns lower expected profits when the likelihood of cooperation is below a threshold that we characterize explicitly, and higher profits are earned thereafter. These findings suggest that, within our framework, antitrust concerns may be mitigated. Since dependent sellers can incur losses from cooperation, collusion attempts become less viable in markets with one-sided dependency. Full article

Urban transportation demands are growing rapidly. Concurrently, the sharing economy continues to expand. These dual trends establish ride-hailing dispatch as a critical research focus for building sustainable smart transportation systems. Current ride-hailing systems only serve passengers. However, they ignore an important opportunity: transporting packages. This limitation causes two issues: (1) wasted vehicle capacity in cities, and (2) extra carbon emissions from cars waiting idle. Our solution combines passenger rides with package delivery in real time. This dual-mode strategy achieves four benefits: (1) better matching of supply and demand, (2) 38% less empty driving, (3) higher vehicle usage rates, and (4) increased earnings for drivers in changing conditions. We built a Dynamic Heterogeneous Demand-aware Ride-hailing Dispatch System (DHDRDS) using deep reinforcement learning. It works by (a) managing both passenger and package requests on one platform and (b) allocating vehicles efficiently to reduce the environmental impact. An empirical validation confirms the developed framework’s superiority over conventional approaches across three critical dimensions: service efficiency, carbon footprint reduction, and driver profits. Specifically, DHDRDS achieves at least a 5.1% increase in driver profits and an 11.2% reduction in vehicle idle time compared to the baselines, while ensuring that the majority of customer waiting times are within the system threshold of 8 min. By minimizing redundant vehicle trips and optimizing fleet utilization, this research provides a novel solution for advancing sustainable urban mobility systems aligned with global carbon neutrality goals. Full article

The influence of educators’ demographic characteristics on learner academic performance has garnered attention, particularly in developing countries. However, gaps remain in understanding the relationship between demographic factors, professional qualifications, and student academic performance, especially in under-resourced educational environments; this study examines the impact of educator demographics and qualifications on learner performance. The study investigates four key objectives: (i) analysing the relationship between educator qualifications and learner academic performance, (ii) evaluating the effect of educator demographic factors on learner academic performance, (iii) comparing the relative influence of demographic characteristics and professional qualifications, and (iv) assessing the validity of Mincer’s Earnings Function in capturing diminishing returns to experience. Using secondary data from the South African School Administration and Management System (SA-SAMS), this study examines 70 educators across five secondary schools. An Ordinary Least Squares (OLS) regression model is employed for estimation, with Robust Least Squares (RLS) used as a validation technique to ensure result consistency. The empirical results reveal that teaching experience and gender significantly influence learner performance, whereas age and formal qualifications exhibit no statistical effect. The findings further confirm diminishing returns to experience, indicating that while teaching experience enhances academic performance, its marginal impact declines beyond a certain threshold. Full article

This study investigates the occurrence and persistence of abnormal stock returns surrounding corporate earnings announcements, particularly emphasizing how varying frequencies of financial reporting influence market behavior. Specifically, this research examines the effects of the timing and frequency of disclosures on market reactions and stock price volatility during critical earnings announcement periods. By analyzing firms within the Dow Jones Industrial Average (DJIA) from 2014 to 2024, this study evaluates the interplay between financial reporting schedules and market responses to stock prices. Furthermore, it considers the impact of peer firms’ reporting practices on the assimilation of firm-specific information into stock prices. Using econometric models, including Vector Auto Regression (VAR), Impulse Response Functions (IRFs), and Self-Exciting Threshold Autoregressive (SETAR) models, causal relationships between reporting frequency, stock price volatility, and abnormal return patterns across different volatility regimes are identified. The findings highlight that quarterly reporting practices intensify market responses and contribute to significant variations in stock price behavior in high-volatility periods. These insights provide a deeper understanding of the role of financial disclosure practices and forward-looking guidance in shaping market efficiency. This study contributes to ongoing discussions about balancing the transparency benefits of frequent reporting with its potential to amplify market volatility and sector-specific risks, offering valuable implications for policymakers, investors, and corporate managers. Full article

Although the relationship between earnings management and firm performance has been well explored in the literature, sustainable performance has not yet been examined. Furthermore, the literature has not addressed the issue of nonlinearity between earnings management and firm performance. Therefore, this paper aims to examine the potential nonlinear relationship between earnings management and sustainable firm performance in Saudi Arabia using a sample of 70 listed firms over the 2015–2022 period. Specifically, it investigates the operational risk disclosure threshold effect in the earning management–sustainable firm performance nexus. To do so, the dynamic panel threshold regression model (DPTR) is performed. The result proves that there is a threshold effect of operational risk disclosure in the relationship between earning management and sustainable firm performance. Specifically, the threshold values of operational risk disclosure for the three models are estimated at 6 between the low- and the high-operational-risk-disclosure regimes. In the lower regime, firm performance decreases when earning management increases; however, in the higher regime, firm performance increases when earning management increases. These outcomes support the predictions of agency and positive accounting theories. Full article

The MET gene plays a vital role in cellular proliferation, earning it recognition as a principal oncogene. Therapies that target MET amplification have demonstrated promising results both in preclinical models and in specific clinical cases. A significant obstacle to these therapies is the ability to distinguish between focal amplification and polysomy, a task for which simple MET copy number measurement proves insufficient. To effectively differentiate between the two, it is crucial to utilize comparative measures, including in situ hybridization (ISH) with the centromere or next generation sequencing (NGS) with adjacent genes. Despite the promising potential of MET amplification treatment, the judicious selection of patients is paramount to maximize therapeutic efficacy. The effectiveness of MET inhibitors can fluctuate depending on the extent of MET amplification. Future research must seek to establish the ideal threshold value for MET amplification, identify the most efficacious combination therapies, and innovate new targeted treatments for patients exhibiting MET amplification. Full article

This article explores selected aspects of the Mariology of Blessed John Duns Scotus, a medieval Franciscan philosopher and theologian. Even though the Subtle Doctor did not develop a theological synthesis as mature as that of St. Thomas Aquinas, his observations continue to provide a relevant source of inspiration for a more in-depth look at Franciscan protological and soteriological concepts. Duns Scotus earned his place in the history of theology as a eulogist of the mystery of the Incarnation and defender of the truth about the Immaculate Conception. In fact, what he had accomplished laid the necessary foundation for the dogmatic ruling on that matter in 1854. The article begins by presenting the scholar’s view of the relation between creation and Redemption from the standpoint of Christ’s perfect mediation. The Marian Doctor was an advocate of emphasizing the objectivity of Redemption, although he himself stopped short of the “threshold” of the mystery of the Father with respect to the Mother of the Son of God, the most perfect Mediator—also for the Virgin Mary. In the end, the Subtle Doctor did not draw all the possible conclusions from his theological vision of creation and salvation history. Next, the article outlines the perspective of God’s eternal plan. Blessed John Duns Scotus’s theology reveals a vision of history in which everything is directed toward the fulfilment of God’s eternal plan: the very plan of which St. Paul wrote very forcefully yet subtly and to which St. John Paul II often referred. The interpretation of that plan is the foundation of an “objective Mariology”. Finally, the author addresses the question of the freedom of both the Creator and His creation from the perspective of the Creator’s plan and in accordance with the Marian Doctor’s assumptions. An analysis of Duns Scotus’s Mariology reveals its depth and innovative character and, at the same time, certain limitations which—in his time—were mentally unsurmountable. Full article