Malete Journal of Accounting and Finance
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UNLOCKING INDUSTRIAL GROWTH IN WEST AFRICA: HOW FINANCIALIZATION AND TECHNOLOGICAL INNOVATION SHAPE THE FUTURE
Full text linkThis study examines the moderating effect of technological innovation on the relationship between financialization and industrial output growth in West Africa. Despite the critical role of innovation in industrial transformation, the region faces barriers such as limited capital, poor infrastructure, and skill shortages. Using data from 16 West African countries and grounded in Kaldor’s Theory of Economic Growth, the study employs panel unit root tests and ARDL cointegration analysis to explore long-run relationships among financialization, technological innovation, government effectiveness, human capital, and trade openness. Results show that financialization has a negative and statistically significant effect on industrial output growth, reflecting a preference for short-term financial gains over productive investment. Technological innovation, while statistically significant, has only a marginal positive effect, and its moderation with financialization is negative and insignificant. Notably, a 1% increase in technological innovation is linked to a 2.39 percentage point decline in industrial output growth, challenging conventional assumptions. The study concludes that financialization undermines industrial development and limits the benefits of technological innovation. It recommends policy measures such as tax incentives, mandated industrial lending, financial regulation, R&D support, and workforce training to promote long-term investment, enhance technological adoption, and boost industrial output in West Africa
AUDITING SYSTEMS AND FINANCIAL INFRACTIONS AMONGST GOVERNMENT ENTITIES IN KWARA STATE
Full text linkFinancial infractions among government entities in Nigeria, such as embezzlement and misappropriation of public funds, have persisted largely due to ineffective auditing. This study aims to examine the impact of the auditing system on financial infractions by specifically assessing the impact of internal controls and financial audits on the prevention of financial infractions among government entities in Kwara State, Nigeria. The Primary data was collected from a population of 295 auditors across 76 MDAs in Kwara State. A descriptive survey research design was employed, involving 170 senior employees sampled from various MDAs in Kwara State through a random sampling technique. Data were collected through structured questionnaires and analyzed using Multiple Regression analysis. The findings revealed that internal controls have a positive impact on preventing financial infractions (β = 0.064, t = 2.848, p = 0.005), while financial audits have a negative and insignificant impact (β = -0.028, t = -0.306, p = 0.760). The study concluded that internal controls play a critical role in mitigating financial infractions within government entities in Kwara State, whereas financial audits appear to lack effectiveness in addressing these issues. The study recommended that the Kwara State Government entities enhance internal controls through regular assessments and training, and improve transparency in audit reporting to better mitigate financial infractions
RISK MANAGEMENT AND FINANCIAL REPORTING QUALITY OF ORGANISED COOPERATIVE SOCIETIES IN SOUTH-WEST, NIGERIA
Full text linkCooperative societies have shown evidence of resilience as a result of the pooled nature of funding, this has enhanced its prominent role in financial inclusion and economic development globally. However, despite these roles, cooperative societies in Nigeria still experience challenges such as poor financial reporting quality, high loan default rate and inadequate risk management strategies. Effect of risk management on financial reporting quality of organised cooperative societies in South-west, Nigeria is examined in this research. Longitudinal research design was employed. 812 and 152 were population and sample respectively which was achieved through purposive sampling technique. Data were sourced from audited financial reports of sampled cooperative societies for twelve years (2012-2023). And analysed with aid of regression analysis techniques. The result revealed that leverage {z=0.598(p=0.004} and rate of loan default {z=0.304(p=0.044} have affirmative statistically significant effect on discretionary accrual while cash flow volatility {z=-0.0088(p=0.924} has adverse statistically insignificant effect. The study then concludes that the measures of risk management have positive statistically significant influence on financial reporting quality. In accord with the results of this research, the study then recommends that management committee of cooperative societies have to put in place strategic policies such as periodic evaluation of loan schedule to ensure members repay their loans as at when due in line with the loan contract agreement and defaulters are adequately penalise
CONTROL PACKAGE AND TEACHING QUALITY IN NIGERIAN POLYTECHNICS
Full text linkThe incessant report of abysmal teaching quality in Nigeria polytechnics necessitate the appraisal of the management control system in place in this public higher institute of learning. The study examine the effect of control packages on the teaching quality of polytechnics in Nigeria. The study adopt a survey research design. Data were obtained from 169 respondents through structured questionnaires. Multiple regression analysis was employed and the study revealed that administrative control (β = -0.311; p < 0.000) was found with significant negative effect; cybernetic controls (β = 0.758; p < 0.000) have a notable and positive effect while the rewards and compensations control (β = -0.047; p > 0.353) was found with negligible and negative effects on the quality of teaching in Nigeria public polytechnics. The study concludes that effective control element such as administrative, reward and compensation, and cybernetics controls improved the utilization of the resource and ensure attainment of optimum performance. The study recommends the Nigeria polytechnics managements should implement efficient policies and procedure, effective renumerations, and accurate financial and non-financial metrics in attempt to improve their performance and able to compete with foreign counterpart
RISK MANAGEMENT PRACTICES AND FINANCIAL PERFORMANCE OF SMALL AND MEDIUM SCALE AGRICULTURAL VALUE CHAIN IN KWARA STATE, NIGERIA.
Full text linkThe role of risk management practices in agricultural value chains has generated increasing attention, especially in developing economies like Nigeria. Sequel to this, this study aimed at examining the effect of risk management practices on financial performance of small and medium scale agricultural value chain in Kwara State, Nigeria. Data for the analysis was collected through field surveys filled out by SMEs in the agricultural value chain in Kwara state, with responses gathered from key decision-makers and managers. The study utilized logistic regression for the models. The empirical findings indicated that financial risk management practices and operational risk management practices were significant determinants of the financial performance of SMEs agricultural value chain Kwara State. These components were shown to positively impact profitability and operational sustainability. The study concludes that emerges of financial risk management practices and operational risk management practices were the key determinants of financial performance of SMEs agricultural value chain. The study therefore recommends among others that agricultural SMEs should enhance their market research capabilities to better understand consumer demands and trends, focus on improving operational efficiency through technology adoption, and more so invest in sustainable farming practices such as water and soil conservation
EFFECT OF CONOIL PLC’S LIQUIDITY ON ITS PROFITABILITY: EVIDENCE FROM NIGERIA
Full text linkThe economy of Nigeria has had periods of recession, thus exposing indigenous firms, specifically the oil sector and gas sector, to liquidity and profitability problems. The objective of this research is to analyze the impact of liquidity on the profitability of Conoil Plc, Nigeria. The research design adopted was causal-comparative and utilized secondary financial data for the period covering 2010-2024. The applicable analyses comprised descriptive and inferential statistics, for which Ordinary Least Squares (OLS) regression analysis was conducted via E-Views 9. The findings indicate that at 5% significance level, current ratio (beta 0.0749 & p-value 0.2314), cash ratio (beta 0.0798 & p-value 0.0513), and quick ratio (beta 0.0498 & p-value 0.5341) which are measures of liquidity have a positive but statistically insignificant effect on return on assets (ROA) which is a measure of profitability. This indicates that efforts at better management of liquidity can only serve to substantially enhance the company\u27s overall financial performance. Furthermore, with F-statistic (value 2.8484 & p-value .0975) as the basis of conclusion, it is concluded that Conoil Plc\u27s liquidity has no significant effect on its profitability. Therefore, based on the discussed findings, it is recommended that the company should look for other key drivers of ROA aside from the current ratio, hold cash in an effective way, without holding too much idle cash, focus on the quality of liquid assets and their utilization and lastly, consider broader factors for its optimal balance, not necessarily reliant on the individual ratios used in this study
DIGITAL FINANCE, INSTITUTIONAL QUALITY AND GREEN TRANSITION: A SYSTEM-GMM ANALYSIS OF FINTECH’S ROLE IN RENEWABLE INVESTMENT
Full text linkRenewable energy financing in the Global South remains inadequate due to structural impediments like institutional weakness, policy uncertainty, and limited access to capital markets. This study investigates the dynamic interplay between financial technology (fintech) and renewable energy investment (REINV) across 60 developing countries from 2010 to 2023. Leveraging a robust panel dataset (N=840) and applying a System-GMM estimation strategy, the analysis explores how various fintech components, including foreign portfolio investment (FPI), mobile payments, digital lending, and crowdfunding, affect REINV. Empirical findings demonstrate that FPI significantly drives REINV 1.112), while mobile payments (0.789), digital lending (0.445), and crowdfunding (0.334) also contribute meaningfully to investment inflows. Importantly, the positive interaction between FPI and institutional quality (0.189) underscores the role of governance in enhancing fintech’s impact on green finance. The robustness of these findings is confirmed through alternative estimation techniques and sub-sample analyses. Policy implications emphasize the importance of financial openness, digital infrastructure development, regulatory clarity, and institutional reform to optimize fintech’s role in clean energy transitions. The study recommends capacity-building, targeted policy toolkits, and enhanced data integration to support inclusive and sustainable fintech ecosystems in the Global South
ECONOMIC GROWTH, URBANISATION, TRADE, AND ENVIRONMENTAL QUALITY IN THE EUROPEAN UNION: ARDL AND GRANGER CAUSALITY ANALYSIS
Full text linkThe relationship between economic development, urbanisation, trade openness, and environmental quality has emerged as a critical focus of empirical and policy-oriented research, particularly in the context of sustainable development. This study investigates the long-run and dynamic interactions between economic development, urbanisation, trade openness, institutional quality, energy use, and environmental quality in 26 European Union (EU) countries over the period 1970–2022. The analysis is grounded in panel unit root and cointegration tests, Pooled Mean Group (PMG) Autoregressive Distributed Lag (ARDL) models, and Dumitrescu–Hurlin panel Granger causality tests. The findings confirm the Environmental Kuznets Curve (EKC) hypothesis, revealing a non-linear relationship between income and CO₂ emissions. Urbanisation and trade openness were found to significantly increase emissions, while institutional quality plays a mitigating role in environmental degradation. Energy consumption remains a primary driver of emissions, with strong evidence of causality from economic activity, urbanisation, and energy use to CO₂ emissions. The PMG model results are robust across alternative estimators, and cointegration analysis confirms the existence of stable long-run relationships among the variables. The results have important implications for EU policy, suggesting the need for integrated approaches that couple economic growth with decarbonisation strategies. Strengthening institutional quality can improve environmental governance. Investment in sustainable urban planning and energy transition will be key to curbing emissions while maintaining competitiveness. Future research should focus on disaggregating energy sources, modelling structural breaks, and employing spatial methods to capture regional spillovers within the EU
EXAMINING THE PSYCHOLOGICAL AND ETHICAL IMPACTS OF ALGORITHMIC MANAGEMENT ACROSS CULTURAL CONTEXTS IN PLATFORM LABOUR
Full text linkThe expansion of the gig economy has introduced algorithmic management systems that fundamentally reshape work processes and worker experiences, raising critical concerns about worker autonomy, fairness, and psychological wellbeing. This study investigates the psychological and ethical implications of algorithmic surveillance on gig workers\u27 wellbeing across four countries using a cross-sectional survey of 1,204 respondents. Drawing on theories of techno-stress and algorithmic control, the analysis employs multilevel modeling, mediation, and moderation techniques to explore the direct, indirect, and context-dependent effects of surveillance. The results reveal a strong negative association between surveillance intensity and psychological wellbeing ( -4.213), partially mediated by perceptions of unfair algorithmic decision-making (indirect effect = 2.548). Furthermore, cultural dimensions significantly moderate this relationship: high power distance amplifies the negative effects of surveillance, while individualism mitigates them. These findings indicate that algorithmic surveillance systems may exacerbate psychological distress among platform workers, especially in hierarchical or collectivist cultures. The study recommends that platform operators adopt fairness-by-design and culturally sensitive algorithmic management practices. Policymakers are urged to develop enforceable standards for algorithmic transparency and worker participation in digital governance frameworks
FORECASTING GLOBAL STOCK PRICES USING GATED RECURRENT UNIT, LONG SHORT-TERM MEMORY WEIGHTED-LSTM AND LSTM WITH ATTENTION
Full text linkThis research assesses the forecasting potential of four deep learning models: Gated Recurrent Unit (GRU), Simple Long Short-Term Memory (LSTM), LSTM with Attention, and Weighted LSTM (W-LSTM), specifically for predicting stock prices in five African countries - Tanzania, South Africa, Nigeria, Kenya, and Morocco. The evaluation utilized historical price data, and model performance was measured using four metrics: Mean Squared Error (MSE), Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and the Coefficient of Determination (R²). The GRU model consistently produced the lowest error rates and highest accuracy in South Africa (MSE: 0.87, MAE: 0.89, RMSE: 0.87, R²: 0.94) and Nigeria (MSE: 0.90, MAE: 0.89, RMSE: 0.92, R²: 0.93), demonstrating a strong predictive power in these regions. Meanwhile, in Kenya and Morocco, the Simple LSTM model excelled, achieving R² scores of 0.92 and 0.91, respectively, along with commendable MSE and RMSE figures (Kenya RMSE: 0.84, Morocco RMSE: 0.84). Although both the LSTM with Attention and W-LSTM models produced competitive results, they did not consistently achieve lower error metrics or higher R² values compared to the simpler models. These results indicate that streamlined architectures like GRU and LSTM are effective for stock price forecasting in emerging markets. The findings offer valuable insights into the predictive effectiveness of sophisticated recurrent neural network models. The study holds practical significance for financial organizations, investors, and policymakers in utilizing deep learning for informed decision-making and risk management, while pinpointing areas for future improvements in model development and data integration