Social Capabilities and Corporate Zakat Commitment: Evidence from Mission-Driven and Stakeholder Management Perspectives

This study investigates the influence of social capabilities on corporate zakat commitment, drawing on the Social Resource-Based View (SRBV) framework. While corporate zakat represents an important Islamic social finance mechanism, its implementation remains largely voluntary, resulting in inconsistent participation among firms. This study focuses on two key dimensions of social capabilities, mission-driven capabilities and stakeholder management capabilities, to explain variations in corporate zakat commitment among zakat-paying companies in Malaysia. Using survey data collected from the senior management of 142 corporate Zakat payers, the study applies partial least squares structural equation modelling (PLS-SEM) to test the proposed relationships. The findings indicate that stakeholder management capabilities have a significant positive effect on corporate zakat commitment, whereas mission-driven capabilities do not exhibit a statistically significant influence. These results suggest that effective stakeholder engagement, communication, and accountability mechanisms are more critical to motivating corporate Zakat practices than the formal inclusion of Zakat within organisational mission statements. The study contributes to accounting and Islamic governance literature by providing empirical evidence on the role of social capabilities in shaping voluntary zakat commitment. From a practical perspective, the findings highlight the importance of stakeholder-oriented governance strategies for zakat institutions, regulators, and corporations seeking to enhance zakat compliance and reporting practices

Halal Literacy and Its Influence on Consumer Behavior: Factors Driving Food Purchase Decisions

This study investigates the purchase intention of halal food products and how halal literacy moderates the relationship in a consumer behavior study. Attitude, subjective norms, and perceived behavioural control influence purchase intention. Halal literacy is vital in determining purchase intention and consumer behaviour of halal food. Data will be collected from 190 Muslim consumers aged between 20 and 50 years with purchasing power. Screening questions will be used to engage suitable respondents. Data will be analysed for descriptive analysis, and relationships between the independent and dependent variables will be determined. The moderating factor of halal literacy will also be analysed. The findings will stress the importance of attitude, subjective norms, and perceived behavioural control in consumer behaviour and its relations with purchase intention. Halal literacy in halal food purchases will be a contributing factor for food marketers to enhance their significance in consumer behaviour, according to a study of halal product purchases

Beyond Adoption: Drivers, Challenges and Farmer-Led Recommendations for Sustained “Internet of Things” (IoT) Use in Malaysian Smallholder Farming

Smart farming technologies are essential for enhancing food security and the welfare of the farmers. The Internet of Things (IoT) facilitates real-time monitoring and administration of agricultural activities. In Malaysia, IoT is vigorously endorsed through the National Agrofood Policy 2.0 and Agriculture 4.0, yet its implementation and sustained utilization are inconsistent. Previous research has mostly emphasized quantitative determinants of adoption, leaving farmers' lived experiences largely unexplored. This study examines the factors, obstacles, and farmers’ generated suggestions for the adoption of IoT among farmers in Selangor and Negeri Sembilan. In these two central region states, smart farming efforts are vigorously encouraged. A semi-structured interview was performed with 10 farmers who had utilized IoT for over one year, and the data were thematically analyzed to discern factors affecting acceptance, obstacles faced, and farmers’ suggestions. The results indicated that adoption is influenced by perceived utility, user friendliness, institutional and external assistance, elevated expenses, technological apprehension, and operational challenges. To strengthen the adoption, they recommended strengthening system usability, augmenting technical support and accountability, securing ongoing government backing, broadening training options, offering financial aid, and presenting solutions that demonstrate the real value

Talent Management Practices and Performance of MDAs in Uganda

This study examined the effect of talent management practices on the performance of Ministries, Departments, and Agencies (MDAs) in Uganda, guided by four objectives focusing on talent acquisition, talent development, performance management, and succession planning. Anchored in a positivist paradigm, the study adopted a sequential explanatory mixed-methods approach using a cross-sectional survey design. Quantitative data were collected from 95 MDAs, representing a 92 percent response rate, and analyzed using Pearson correlation and hierarchical regression techniques. In contrast, qualitative data were analyzed thematically to complement the quantitative results. The regression results indicate that talent acquisition (B = 0.246, p < .01), talent development (B = 0.142, p < .01), and performance management (B = 0.414, p < .01) have positive and statistically significant effects on the performance of MDAs in Uganda, with performance management emerging as the strongest predictor. Succession planning exhibited a negative but statistically insignificant effect on MDA performance (B = ?0.003, p > .05). Overall, the model explains 37.6 percent of the variation in the performance of MDAs (Adjusted R² = .376) and is statistically significant (F = 71.657, p < .01). Based on these findings, the study recommends strengthening merit-based recruitment, continuous staff development, and robust performance management systems, while redesigning succession planning frameworks to enhance their contribution to institutional performance. The study provides empirical evidence to inform human resource policy reforms aimed at improving efficiency, effectiveness, accountability, and fiscal compliance within Uganda’s public sector MDAs

Financial Risk Management and Financial Performance of Construction Companies in Greater Kampala Metropolitan Area

The financial performance of construction companies depends significantly on their ability to manage financial risks. This study examined the effect of financial risk management on the financial performance of construction companies focusing on three dimensions: risk identification, risk assessment and evaluation, and risk management strategy. Guided by Modern Portfolio Theory, the study adopted a cross-sectional survey design and collected data from 191 construction companies selected through proportionate sampling. Structured questionnaires were used for data collection and the validity and reliability of the instruments were confirmed through expert review and Cronbach’s Alpha. Data were analyzed using descriptive statistics, correlation analysis, and hierarchical regression. Findings revealed that all three financial risk management components were positively associated with financial performance. Risk identification showed a significant but modest relationship with financial performance (r = .300, p < .01), while risk assessment and evaluation exhibited the strongest association (r = .591, p < .01). Risk management strategy also demonstrated a significant positive relationship (r = .428, p < .01). Hierarchical regression results further indicated that risk assessment and evaluation contributed the largest increase in explained variance (24.9 percent), followed by risk management strategy (7.1 percent), whereas the influence of risk identification diminished after additional predictors were introduced. Overall, the models explained 42.7 percent of the variation in financial performance. The study concludes that financial risk management significantly improves financial performance, particularly when firms invest in thorough assessment and evaluation of risks and implement structured mitigation strategies. It recommends that construction firms adopt comprehensive risk management frameworks, strengthen analytical capacities and integrate proactive financial planning tools to enhance profitability, reduce exposure to uncertainty and improve long-term sustainability

Multiscale Transmission of Volatility Between Short and Long-Term Investment Preferences: Evidence from Malaysia's KLCI

This study examines how short-term and long-term investments in Malaysia’s stock market influence each other through volatility spillovers. Using daily data from the KLCI index from 2014 to 2024, the research applies a combination of wavelet analysis and the Dynamic Granger Causality Multivariate Stochastic Volatility (DGC-t-MSV) model. This method allows us to study market behavior across different time periods and frequencies. The results show that there are significant volatility spillovers between short-term and long-term investments, with stronger effects coming from long-term (institutional) investments to short-term (retail) investments. Both types of investments also show strong persistence in volatility, meaning that once volatility appears, it tends to last. These findings are important for investors who need to manage risks and returns more effectively. They also provide useful insights for policymakers who aim to improve the stability of financial markets. By introducing a new approach to analyzing volatility spillovers, this research contributes to a better understanding of risk management in emerging markets like Malaysia

Asset Management and Financial Performance of Construction Companies in Greater Kampala Metropolitan Area

The financial performance of construction companies is increasingly dependent on effective asset management practices that enhance operational efficiency, reduce project delays, and strengthen long-term sustainability. Despite the construction sector’s significant contribution to Uganda’s economic development, firms within the Greater Kampala Metropolitan Area continue to experience weak profitability, high debt ratios, and cost overruns, partly attributed to poor asset management systems. This study examined the effect of asset management on the financial performance of construction companies in the region, focusing on three key dimensions: asset register accessibility, repair and maintenance scheduling, and budget tracking and forecasting. Guided by the Dynamic Capabilities Theory, the study adopted a cross-sectional survey design and collected data from 191 construction companies selected through proportionate sampling. Structured questionnaires were used to gather quantitative data, and instrument validity and reliability were confirmed through expert review and Cronbach’s Alpha. Data were analyzed using descriptive statistics, correlation analysis, and hierarchical regression. Findings revealed that all three asset management practices were positively associated with financial performance. Asset register accessibility showed a moderate significant relationship with financial performance (r = .313, p < .01), while repair and maintenance scheduling demonstrated a weaker but significant association (r = .273, p < .01). Budget tracking and forecasting also exhibited a positive relationship (r = .168, p < .01). Hierarchical regression results further indicated that asset register accessibility contributed the largest increase in explained variance (9.4%), followed by budget tracking and forecasting (2.7%), while the contribution of repair and maintenance scheduling was positive but minimal and statistically insignificant in the final model. Overall, the models explained 15% of the variance in financial performance. The study concludes that effective asset management enhances financial performance, particularly when firms maintain accessible and up-to-date asset registers and implement robust budgeting and forecasting systems. It recommends that construction firms strengthen digital asset management systems, adopt preventive maintenance schedules, and integrate data-driven financial planning tools to improve profitability, ensure timely project delivery, and enhance financial resilience in an increasingly competitive construction environment

Foreign Exchange Rate and GDP Growth Vis-À-Vis Trade Balance in Sub-Saharan Africa

We investigate the interaction effect of foreign exchange rate and economic growth on the trade balance in Sub-Saharan Africa (SSA). We utilize balanced annual panel data for 20 SSA countries covering the period 2005 to 2024. We source the data from the World Development Indicators. We employ the Generalized Method of Moments (GMM) estimator to address endogeneity, dynamic effects, and unobserved country-specific heterogeneity. Empirical results reveal a negative and statistically significant interaction between foreign exchange rate and GDP growth. Specifically, the estimated coefficient of the interaction term (FER*GDP) of -0.190271 implies that a simultaneous 10 percent increase in exchange rate and GDP growth is associated with a deterioration of the trade balance by approximately 1.9 percent. These findings indicate that economic growth occurring alongside exchange rate depreciation is linked to weaker trade balance outcomes, consistent with import-intensive growth structures and limited export supply responsiveness in SSA economies. These results highlight the importance of accounting for structural characteristics when assessing trade balance effects of exchange rate movements and growth dynamics

Government Expenditure and Inflation Vis-À-Vis Trade Balance in Sub-Saharan Africa

We investigate the interaction effect of government expenditure and inflation on the trade balance in Sub-Saharan Africa (SSA). We utilize balanced annual panel data for 20 SSA countries over the period 2005 to 2024 sourced from the World Development Indicators. We apply the Generalized Method of Moments (GMM) estimator to control for endogeneity, unobserved heterogeneity, and the dynamic nature of trade balance adjustment. Empirical results indicate a positive and statistically significant interaction between government expenditure and inflation. The estimated coefficient of the interaction term (GEX*INF) is 0.033026, implying that a simultaneous 10 percent increase in government expenditure and inflation improves trade balance by approximately 0.33 percent. This suggests that, in SSA, expansionary fiscal policy combined with moderate inflation can enhance trade balance performance, likely through increased domestic output, improved competitiveness, and reduced import dependence. We recommend coordinated fiscal-monetary policy frameworks that emphasize productive public spending and inflation control to strengthen external sector sustainability

Modeling Premature Adult Mortality From Non-Communicable Diseases in The United States

We model mortality from cardiovascular diseases (CVD), cancer, diabetes, and chronic respiratory diseases (CRD) among individuals aged 30–70 years in the United States using quarterly time-series data covering the period 2000 to 2024. We adopt an autoregressive integrated moving average (ARIMA) framework to examine both the long-run trajectory and short-run fluctuations in premature adult mortality. Quarterly data obtained from the World Bank are employed, with mortality from CVD, cancer, diabetes, or CRD specified as the dependent variable, while autoregressive (AR) and moving average (MA) terms capture the inherent temporal dependence in mortality dynamics. Parameter estimation is conducted using the conditional least squares (CLS) technique. Results reveal a positive and statistically significant AR(1) coefficient of 0.987144, indicating strong persistence and inertia in mortality patterns, whereby current mortality outcomes are heavily influenced by their past realizations. In contrast, the MA(4) coefficient is negative and statistically significant at –0.697195, suggesting that short-run shocks to mortality, such as transitory health crises or policy interventions are gradually corrected over time. This dynamic adjustment mechanism reinforces the tendency of the series to revert toward its long-run path. The estimated ARIMA(1,1,4) model satisfies both covariance stationarity and invertibility conditions, confirming its econometric soundness and suitability for forecasting. The adjusted R-squared value of 0.835857 indicates that approximately 83.6% of the variation in premature adult mortality is explained by the model’s dynamic structure, underscoring its strong explanatory power. Out-of-sample forecasts extending to 2050 project a sustained and gradual decline in mortality rates, with levels converging toward approximately 4% by mid-century. These projections are consistent with ongoing improvements in healthcare access, disease prevention strategies, medical technology, and public health interventions in the United States. The study recommends sustained and targeted investments in non-communicable disease prevention, early diagnosis, and health system resilience to consolidate and accelerate the observed long-term decline in premature adult mortality