Whether foreign direct investment (FDI) inflows provide predictive information for stock market returns at the sectoral level remains insufficiently understood, particularly in emerging markets. This study examines the short-term predictive relationship between sectoral FDI inflows and stock market returns across major sectors of the Turkish equity market. Monthly data covering January 2010 to November 2025 were analysed for the banking, finance and insurance, services, manufacturing, industrial, and wholesale and retail sectors. Separate Vector Autoregression (VAR) models were specified for each sector, with Borsa İstanbul 100 (BIST 100) index returns and USD/TRY exchange-rate returns included as control variables to account for broad market and exchange-rate conditions. Lagged predictive relationships were assessed using Granger causality tests, while the dynamic responses of the variables to shocks were examined through impulse response analysis. Model adequacy was evaluated using standard diagnostic tests, and substantive interpretation was restricted to the banking and finance and insurance models that satisfied the required diagnostic criteria. No statistically significant Granger-predictive relationship was identified in either direction between sectoral FDI inflows and the corresponding sectoral stock market returns in either of these diagnostically adequate models. The impulse response results likewise provide limited evidence of a persistent or systematic transmission from sectoral FDI inflows to sectoral stock market returns. Overall, the findings suggest that sector-specific FDI inflows should not be regarded as a robust short-term predictor of sectoral equity returns in Türkiye over the sample period. The results also indicate that sectoral stock market dynamics may be driven more strongly by broader market conditions and other macro-financial factors than by contemporaneous changes in sector-specific FDI inflows.
Informal savings and credit associations have become important mechanisms for extending financial services to underserved populations in developing economies, particularly where access to formal financial institutions remains constrained. Nevertheless, weaknesses in financial knowledge may adversely affect borrowers’ ability to understand credit obligations and manage repayment schedules, thereby increasing the risk of delinquency and undermining the sustainability of savings-based lending institutions. This study examines the association between financial literacy and loan repayment performance among members of accumulated savings and credit associations (ASCAs) affiliated with the Kericho Community Development Trust (KCDT) in Kenya. Primary data were collected from 135 members across 14 active ASCA groups and analysed using correlation and regression techniques. Financial literacy was assessed in relation to members’ understanding of loan terms, interest obligations, repayment schedules and related financial-management practices, while loan repayment performance was evaluated using indicators of repayment behaviour and portfolio-at-risk (PAR) exposure. A statistically significant positive association was identified between financial literacy and loan repayment performance (r = 0.412, p < 0.001). Regression analysis further indicated that financial literacy accounted for 17.0% of the variation in loan repayment performance (R² = 0.170). These findings suggest that members with higher levels of financial literacy were more likely to demonstrate sounder repayment behaviour and lower exposure to repayment-related risks. The findings further indicate that financial literacy constitutes an important complementary factor in strengthening credit management within informal savings groups. Accordingly, the integration of structured financial education into ASCA operations, together with pre-loan financial literacy assessment and periodic refresher training, is recommended to strengthen members’ capacity to manage credit obligations and improve the financial sustainability of ASCA-based lending programmes.
Artificial intelligence (AI) is increasingly transforming internal audit practices, yet empirical evidence concerning its adoption in public-sector auditing in Sub-Saharan Africa remains limited. This study examines whether age, gender, and educational level are associated with internal auditors’ perceptions of AI adoption in public universities in Ghana. Drawing on the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), a quantitative cross-sectional survey was conducted among 177 internal audit staff from six public universities. Perceptions of AI adoption were assessed across four dimensions: AI adoption and accountability, fraud detection effectiveness, implementation challenges, and strategies and enablers. Overall, a favourable orientation towards AI adoption was observed, with a composite mean score of 3.614 on a five-point scale. Multiple ordinary least squares (OLS) regression indicated that the demographic model was statistically significant, F(3, 173) = 3.098, p = 0.028, although the explanatory power was modest (R² = 0.051). Age was found to be negatively associated with perceptions of AI adoption (B = −0.058, β = −0.185, p = 0.024), indicating that more favourable perceptions were reported by younger internal auditors. Educational level showed a positive association with perceptions of AI adoption and represented the strongest predictor among the demographic variables examined (B = 0.064, β = 0.220, p = 0.007), suggesting that higher levels of academic and professional education may be associated with greater readiness for AI adoption. No statistically significant association was observed for gender (p = 0.664). The findings extend empirical research on technology acceptance to public-sector internal auditing in an African context and highlight the relevance of demographic heterogeneity in understanding AI adoption readiness. In particular, age-sensitive training and opportunities for continuing academic and professional development may provide appropriate mechanisms for strengthening AI-related competencies among internal audit staff in Ghanaian public universities.
Increasing pressure on relevant stakeholders to shoulder environmental responsibility has compelled businesses to minimize their environmental impact through the provision of, say, improved accounting information. For the accounting profession to effectively contribute to this shift, practitioners should demonstrate both awareness and practical application of environmental management accounting (EMA). This study investigated the level of awareness and utilization of EMA among Maltese Certified Public Accountants (CPAs or accountants), while also examining the influence of job experience, environmental training, size of firm, and business sector. A quantitative research approach was adopted and data was collected through a self-administered online questionnaire distributed to Maltese accountants. Descriptive statistics were used to analyze frequencies of response, while the Chi-square and Kruskal-Wallis tests were applied to assess relationships and test hypotheses. Consistent with existing literature, the findings revealed that both EMA awareness and utilization were low to moderate. They also indicated that accountants who had been trained in EMA while occupying entry-level or executive roles in their organizations exhibited a slightly higher EMA awareness than others. On the other hand, those employed within the larger firms, particularly the Big Four, displayed a slightly higher EMA use than others, indicating differences across firm sizes and sectors. Despite the ongoing limitations, the presence of certain awareness and applications highlighted the existence of a real potential for gradual improvement. Over time, the increased EMA awareness and adoption could enhance environmental practices, and, ultimately, support the country’s long-term environmental objectives, thus contributing to progress toward achieving carbon neutrality by 2050.
Artificial intelligence is increasingly being adopted across financial institutions to enhance operational efficiency, strengthen risk management, and improve the quality of assurance services. However, empirical evidence regarding its influence on audit quality in developing economies remains limited. This study investigated the impact of artificial intelligence adoption on audit quality within the commercial banking sector of Zimbabwe. A quantitative research design was employed, and primary data were collected through structured questionnaires administered to auditors and managerial personnel working in commercial banks. The findings indicate that the integration of artificial intelligence technologies into audit processes is associated with significant improvements in audit quality. Specifically, the quality and reliability of audit evidence were reported to be enhanced, the likelihood of material misstatements was perceived to be reduced, and greater efficiency in audit execution and decision-making was achieved. Despite these benefits, several barriers to implementation were identified, including inadequate technological infrastructure, limited financial capacity for artificial intelligence investment, and shortages of personnel with specialized artificial intelligence-related competencies. Nevertheless, strong support for the adoption of artificial intelligence-based auditing practices was observed among respondents. The results suggest that artificial intelligence has considerable potential to enhance audit quality by improving the accuracy, consistency, and reliability of audit procedures and evidence evaluation. It is therefore recommended that commercial banks increase investment in artificial intelligence-enabled audit technologies. Furthermore, supportive regulatory frameworks, professional standards, and implementation guidelines should be established by policymakers and financial regulators to facilitate responsible artificial intelligence adoption, mitigate emerging risks, and promote consistency in audit practices across the banking sector. These findings contribute to the growing body of literature on artificial intelligence-driven auditing and provide practical insights for financial institutions operating in developing economies.
The relationship between exchange rate volatility and foreign direct investment (FDI) inflows in emerging economies has remained a central issue in international finance, particularly in economies exposed to macroeconomic instability and external shocks. In this study, the impact of real exchange rate volatility (VOLREXR) on FDI inflows in Egypt was examined using quarterly data spanning the period from 2001 to 2024. Exchange rate volatility was first estimated through the Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) model in order to capture asymmetric responses to exchange rate shocks and to generate a more accurate measure of exchange rate uncertainty. Subsequently, the dynamic relationship between exchange rate volatility and FDI was investigated within the Autoregressive Distributed Lag (ARDL) framework, which enabled the estimation of both short-run adjustments and long-run equilibrium effects in the presence of mixed orders of integration. The empirical analysis was supported by unit root testing, bounds cointegration testing, and an error correction specification, while model adequacy and robustness were verified through a comprehensive set of diagnostic and stability tests, including serial correlation, heteroskedasticity, normality, multicollinearity, and structural stability assessments. The results indicate that VOLREXR exerts a statistically significant and negative effect on aggregate FDI inflows in Egypt in both the short run and the long run, suggesting that heightened exchange rate uncertainty weakens investor confidence and discourages capital commitment. Among the control variables, market size, represented by gross domestic product (GDP), was found to exert a positive and statistically significant influence on foreign investment, confirming the importance of domestic economic expansion in attracting international capital. By contrast, inflation and external debt were found to impose adverse effects on investment performance, reflecting the destabilizing consequences of macroeconomic imbalances. Market capitalization, however, was shown to contribute positively to FDI inflows, highlighting the role of financial market development in strengthening investment attractiveness. Overall, the findings underscore the importance of exchange rate stability and coherent macro-financial policy coordination in fostering a predictable investment climate and supporting sustainable long-term capital inflows into the Egyptian economy.
The relationship between corporate sustainability performance and firm valuation has attracted considerable scholarly and practical attention; however, empirical evidence remains inconclusive, particularly within environmentally sensitive and carbon-intensive industries. This study examines the association between corporate sustainability performance and firm valuation in the global oil and gas (O&G) sector and further investigates whether external sustainability assurance moderates this relationship. Grounded in Stakeholder Theory and Legitimacy Theory, an empirical analysis was conducted using a sample of 100 publicly listed O&G companies across multiple jurisdictions during the 2022–2023 period. Corporate sustainability performance was measured using Environmental, Social, and Governance (ESG) scores, while firm valuation was employed as the primary indicator of financial outcomes. In addition, the presence of independent third-party sustainability assurance was incorporated as a moderating variable to assess whether externally verified sustainability disclosures enhance the credibility and economic relevance of sustainability initiatives. The findings indicate that corporate sustainability performance is not significantly associated with firm valuation within the O&G industry. Furthermore, no significant moderating effect of external sustainability assurance was identified. These results suggest that sustainability-related activities and disclosures may not yet be perceived by investors as value-enhancing mechanisms in carbon-intensive sectors. It is also possible that stakeholders regard such initiatives as symbolic responses to legitimacy pressures rather than as substantive drivers of long-term economic performance. The findings challenge the widely accepted assumption that superior sustainability performance necessarily translates into improved market valuation and financial benefits. By providing evidence from a sector characterised by substantial environmental exposure, regulatory scrutiny, and stakeholder pressure, this study contributes to the growing literature on the economic consequences of corporate sustainability. The results further underscore the importance of developing industry-specific sustainability frameworks and assurance practices capable of strengthening stakeholder confidence and improving the integration of sustainability considerations into corporate value creation processes.
This study examined the challenges faced by internal auditors in adopting AI for the internal audit functions of the public universities in Ghana. The study used a qualitative research design that involved semi-structured interviews with six audit professionals from six prominent public universities; it was guided by the Technology-Organization-Environment (TOE) and Diffusion of Innovation (DOI) theory. The study employed NVivo 14 software to analyses data thematically. The findings revealed four critical themes influencing AI adoption: technological readiness, organizational culture, capacity and competency gaps, and regulatory and ethical ambiguities. The most significant obstacles were identified as technological constraints, such as outmoded infrastructure and inadequate data systems. Furthermore, innovation was impeded by bureaucratic leadership structures and inadequate management commitment. The adoption of AI was further restricted by the ambiguities surrounding its ethical and regulatory use, as well as skill deficiencies. The study underscored the need for leadership commitment and governance innovation to realize the full potential of AI in public audit transformation. It contributes to the literature by contextualizing the challenges of AI adoption in the higher education sector of a developing economy, specifically Ghana, to offer theoretical insights into the intersection of digital readiness and institutional culture. For policymakers, it also provides practical recommendations such as targeted capacity building, infrastructure enhancement, and policy reforms to support AI-driven auditing.
Advanced and developing countries are strengthening budgetary regulation to reduce economic vulnerabilities and control budget deficits and public debt. Additionally, public institutions are required to maintain financial sustainability and pursue good economic governance. This study evaluated isomorphic factors influencing Supreme Audit Institutions (SAIs) in developing countries to effectively drive government policies, including public finance sustainability. Using phenomenological qualitative methodology, the study conducted online exploratory focus groups with selected African SAIs. Three focus group discussions and validated interviews were employed. The research applied institutional theory to reveal how isomorphic pressures impact SAIs in developing countries. Key isomorphic factors identified by participants from the selected African countries include legislative requirements, outdated legal mandates, lack of independence, financial viability, effective audit recommendations, professional competency, and capacity constraints. Analysis revealed that the legislative mandate policy framework significantly impacts SAI effectiveness and public finance sustainability. The findings provide practical insights for governments and lawmakers to create institutional environments featuring regulatory mandates, SAI financial independence, and professional capacity for effective public sector audits and reporting. This exploratory study offers new theoretical and methodological perspectives on SAIs and public finance sustainability, providing opportunities for future research. It establishes a foundation for independently testing each identified factor regarding public sector audit efficacy.
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