Asian Journal of Economics, Business and Accounting
Not a member yet
2059 research outputs found
Sort by
Effect of Financial Technology on Financial Inclusion in Ethiopia: A Systematic Review
No full textThis systematic review examines the impact of financial technology innovations on financial inclusion in Ethiopia, using the Technology Acceptance Model and Diffusion of Innovation theory. It analyzes the role of digital financial services, such as internet banking, ATMs, and point-of-sale systems, in addressing Ethiopia’s historically low participation in the formal financial sector. Covering empirical, analytical, and policy literature from 2005 to 2025, the review finds that while DFS have expanded access and reduced transaction costs, adoption is still limited by challenges like low financial literacy, inadequate digital infrastructure, gender disparities, and regulatory uncertainty. Key factors influencing financial inclusion include financial innovation, poverty levels, financial sector stability, economic conditions, financial literacy, and regulatory frameworks, which often vary due to issues like poor system maintenance. The paper concludes that sustainable financial inclusion in Ethiopia requires investments in connectivity, consumer protection, and pro-poor financial products, offering targeted policy recommendations for the National Bank of Ethiopia and commercial banks to foster a transition from cash-based to digitally inclusive finance. It also highlights areas for future research, addressing ongoing challenges in achieving broad financial inclusion
Artificial Intelligence and Board of Directors’ Monitoring Strategies on Firms’ Financial Performance: A Dynamic Approach
No full textThis study analyses the dynamic effects of board monitoring mechanisms and Artificial Intelligence (AI) related knowledge on the financial performance of financial services firms listed on the Nigerian Exchange Group (NGX) over the period 2013–2022. Firm-level data were obtained from annual reports and accounts and analysed using a two-step System Generalised Method of Moments (GMM) estimator to address endogeneity, unobserved heterogeneity, and performance persistence. The results show that lagged financial performance positively and significantly influences current profitability, indicating dynamic adjustment behaviour. AI-related knowledge acquired by board members contributes directly to improved financial performance by strengthening information processing, oversight quality, and strategic decision-making. In addition, effective risk management committee diligence, larger board size, and greater audit committee independence are associated with higher profitability, underscoring the importance of robust governance structures. Managerial shareholding and return on equity also exert positive effects, reflecting improved alignment between managers’ and shareholders’ interests. Conversely, leverage negatively affects financial performance, suggesting that excessive reliance on debt weakens financial stability. Other governance attributes, including ownership concentration, gender diversity, and firm size, exhibit limited impact. Overall, the findings highlight that board-level AI knowledge complements traditional monitoring mechanisms and enhances financial performance in Nigerian financial institutions
AI Adoption in Accounting and Finance: Impact on Organizational Performance
No full textThe rapid integration of artificial intelligence (AI) into accounting and finance functions is reshaping how organizations manage information, processes, and strategic decisions; however, empirical evidence on its performance implications remains limited, particularly in emerging economies. This study investigates the effect of AI adoption on organizational performance by examining financial, operational, and strategic outcomes. A quantitative research approach was employed using survey data collected from 370 accounting and finance professionals working in banking, manufacturing, information technology, and service organizations. The data were analyzed using descriptive statistics, correlation analysis, and regression models to assess the relationship between AI adoption and performance dimensions. The results indicate a high level of AI adoption and organizational preparedness, with AI adoption exerting a significant and positive influence on all three performance dimensions. Financial performance demonstrates the strongest association, followed by operational efficiency and strategic effectiveness, suggesting that AI enhances cost control, process optimization, and data-driven decision-making. While organizations continue to face challenges related to skill development, system integration, and change management, these constraints do not outweigh the overall performance benefits. The study concludes that AI adoption in accounting and finance functions serves as a strategic enabler that strengthens organizational performance and supports the transition of professionals toward higher-value analytical and advisory roles
Lean Management Practices and Organizational Competitiveness: The Mediating Role of Operational Performance in SMEs in Bandung, Indonesia
No full textAims: This study aims to examine the impact of lean management practices on organizational competitiveness, with operational performance positioned as a mediating mechanism. Specifically, the study seeks to analyse how lean management practices influence operational performance and how these operational improvements subsequently contribute to enhancing the competitive position of small and medium-sized enterprises (SMEs).
Study Design: This study employs a quantitative explanatory research design using a cross-sectional survey approach. The relationships among lean management practices, operational performance, and organizational competitiveness are examined through Partial Least Squares Structural Equation Modeling (PLS-SEM).
Place and Duration of Study: The study was conducted among small and medium-sized enterprises located in the Greater Bandung area, Indonesia. Data collection took place between 15 November to 5 December 2025.
Methodology: Data were collected from 186 SME owner–managers in Bandung, Indonesia, and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The measurement items were adapted from established literature on lean management, operational performance, and competitiveness. The data were analysed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess the reliability and validity of the measurement model and to test the proposed structural relationships, including the mediating role of operational performance.
Results: The results indicate that lean management practices have a significant positive effect on operational performance. Operational performance, in turn, significantly enhances organizational competitiveness. In addition, lean management practices also exert a direct positive effect on organizational competitiveness. Mediation analysis reveals that operational performance partially mediates the relationship between lean management practices and organizational competitiveness, indicating that the competitive benefits of lean management are achieved primarily through improvements in operational performance.
Conclusion: The study concludes that lean management serves as an effective strategic approach for enhancing the competitiveness of SMEs when it is implemented in a manner that strengthens operational performance. The findings underscore the importance of focusing on operational improvements as a key mechanism through which lean management translates into sustainable competitive advantages
The Impact of Customer Analytics on Sales Funnel Conversion and Customer Retention in the E-Commerce Industry
No full textThe fast development of e-commerce has made competition stiffer and made the necessity of knowing customer behaviour stronger in digital touchpoints. This has led to customer analytics becoming one of the most important capabilities of maximizing sales funnel conversion and customer retention. This review analyses how customer analytics can influence the performance of sales funnel and retention of customers in the e-commerce sector with specific focus on the importance of predictive modelling, machine learning (ML) and artificial intelligence (AI) as well as real-time data analytics.
The study relies on peer-reviewed scientific sources published between 2013 and 2025 and synthesises the evidence on the effectiveness of analytics-driven practices in increasing the convert ratio, including customer segmentation, lead scoring, recommendations, churn prediction, and customer lifetime value (CLV) modelling, in improving efficiency in conversion and long-term loyalty.
The results show that customer analytics can also increase funnel conversion to a large extent because it can personalize at scale, minimize friction between funnel phases, and help guide decisions based on the available data using advanced predictive methods. On the same note, proactive predictive churn, tactical engagement programs, and individualized loyalty programs enhance retention performance. Nevertheless, the review also indicates significant limitations to the current literature, such as a large dependence on short-term case studies, focus on big companies in the developed markets, and the lack of incorporation of the behavioural theory. Data privacy, algorithmic bias, and model transparency are also relevant ethical issues that make the implementation more complex.
In general, the review summarizes that customer analytics has high potential to convert and retain in e-commerce, but the effectiveness of this tool in the long run presupposes longitudinal evidence, adaptation, and responsible and transparent data utilization. The research can be useful in the future as it summarizes the nonspecific body of work and sets the trends of further research regarding the topic of sustainable, customer-centric analytics practices
Assessing the Impact of Oil Industry Deregulation on Rural Development: Evidence from Mudzi Rural District, Mashonaland East, Zimbabwe
No full textThis study evaluates the impact of major policy reforms that deregulated Zimbabwe’s oil industry, with particular emphasis on their implications for rural development in Mudzi Rural District, Mashonaland East Province. The research examines how liberalising the importation, distribution, and retailing of oil products has reshaped market structure, pricing dynamics, competitive behaviour, investment trends, fuel accessibility, and foreign exchange utilisation. Findings indicate that deregulation has the potential to greatly improve fuel access and service provision in underserved rural areas by enhancing market efficiency, increasing competition, and diversifying fuel import sources. Consequently, the reforms have also created new investment opportunities for Zimbabweans, especially in rural markets, including roles in infrastructure development, import substitution, storage, and procurement. Emerging models such as containerised fuel stations demonstrate how deregulation can expand rural fuel availability and stimulate local enterprise development. However, the study highlights ongoing challenges—among them regulatory gaps, illicit fuel trading, and inadequate infrastructure—which undermine the full benefits of deregulation. Therefore, to address these issues, the research recommends that there be targeted support for small-scale fuel operators, strengthened regulatory oversight, enhanced community engagement, and local capacity-building initiatives. Overall, the study concludes that with strategic policy refinement, deregulation can play a pivotal role in advancing Zimbabwe’s broader objectives of energy security, inclusive rural development, and sustainable economic growth
Assessing the Economic Consequences of Structural Failures in Newly Built National Highways in Kerala, India
No full textNewly built national highways in Kerala were intended to catalyse regional economic development by reducing transport costs, improving market connectivity, and strengthening supply chains. However, recurrent structural failures and rapid asset degradation have substantially weakened these anticipated benefits and generated adverse socio-economic outcomes. This paper reconceptualizes newly constructed highways as Common-Property Resources and appliesOstrom’s polycentric governance framework to examine how institutional fragmentation, inadequate maintenance regimes, and weak accountability mechanisms transform infrastructure investments into economic liabilities. Employing a mixed-methods approach, the study integrates structured household surveys (n = 300), stakeholder interviews, and secondary administrative data. Quantitative analyses—including descriptive statistics, correlation matrices, multivariate regression models, and robustness checks—are complemented by qualitative thematic coding to trace the causal pathways linking highway failures to supply-chain disruptions, income volatility, health and insurance costs, environmental externalities, and disproportionate impacts on vulnerable groups.
Empirical results indicate a statistically significant negative association between age and reported highway disruption (β = −0.058, p = 0.047), which is more plausibly explained by demographic usage patterns and adaptive behaviour—such as reduced mobility intensity among older populations—rather than superior infrastructure performance. In contrast, income level shows no statistically significant relationship with disruption (p = 0.975), suggesting that economic status alone does not predict exposure to highway failures. Although age emerges as a relatively stronger predictor, the adjusted R² value of 0.347 indicates that substantial variation remains unexplained, underscoring the importance of omitted institutional, physical, and environmental determinants, including design quality, maintenance effectiveness, traffic density, and climatic stress.
Overall, the findings demonstrate that while highway infrastructure holds significant growth-enhancing potential, weak governance structures erode its developmental returns. The study advances actionable policy recommendations centered on decentralized monitoring, participatory maintenance mechanisms, strengthened accountability, and sustainable financing models to restore infrastructure performance and socio-economic benefits
Analysis of the Influence of Online Customer Reviews, E-Service Quality, Content Marketing and e-WOM on Purchase Decisions on Tokopedia: A Case Study on UMP Students
No full textAims: This study aims to examine the effects of Online Customer Reviews, E-Service Quality, Content Marketing, and Electronic Word of Mouth (e-WOM) on Purchasing Decisions.
Study Design: A quantitative approach using a survey-based method was employed.
Place and Duration of Study: The study was conducted at Universitas Muhammadiyah Purwokerto from October to December 2025.
Methodology: The population comprised 21,674 students from 11 faculties, with 130 respondents selected through purposive sampling. Data were analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS).
Results: The results of this study show that Online Customer Reviews and E-Service Quality have a positive and significant effect on Purchasing Decisions. In contrast, Content Marketing and E-WOM show positive but insignificant effects on Purchasing Decisions.
Conclusion: The results confirm that Online Customer Reviews and E-Service Quality are key determinants of Purchasing Decisions on Tokopedia. However, Content Marketing and e-WOM have not yet been able to significantly influence Purchasing Decisions, suggesting limitations in building consumer trust. The model explains only part of the variance in Purchasing Decisions; therefore, future studies are encouraged to include additional variables such as Consumer Trust, Perceived Risk, Price, and Seller Reputation, as well as broader samples to enhance generalizability
Financing through Crisis: Empirical Evidence of How Covid-19 Reshaped the Capital Structure Choices in Emerging Economy
No full textPurpose: This research aims to explore the factors influencing capital structure and the effect of the COVID-19 pandemic on leverage decisions. Due to the disruptions caused by COVID-19, this study identifies the impact of pandemic on the capital structure choices and their determinants, as well as the adjustment dynamics, among listed companies of pharmaceutical and chemical in Bangladesh.
Design/Methodology/Approach: To perform the study has undertaken 196 firm year observation sample extending from 2015 to 2024 and a panel data from listed firms in the Pharmaceuticals and Chemicals sector on the Dhaka Stock Exchange (DSE) in Bangladesh. A fixed effects panel regression model, incorporating a lagged dependent variable, is estimated to account for dynamic adjustments while controlling for unobserved, time-invariant firm-specific effects. A comparative analysis of pre-post covid impact on the capital structure has been also analyzed. For examining the stationarity of the variables, the Fisher-type Augmented Dickey-Fuller (ADF) panel unit root test is utilized in this study.
Findings: The findings of the study reveal that lagged leverage and firm size have a significant impact on all the measures at 5% level of confidence interval which confirms the path dependency nature of capital structure decisions. In oppose to that tangibility and profitability shows insignificant while liquidity reveals a weak negative effect which interprets conservative liquidity management during the periods of crisis. However, The COVID-19 dummy variable shows negative impact on leverage, highlighting a shift towards internal financing. In addition to that pre- and post-pandemic analysis reveal increased leverage persistence and a greater importance of firm size, along with a diminished role of liquidity as firms prioritize cash reserves. Overall, capital structure decisions in Bangladesh are influenced more by institutional constraints and risk aversion than by traditional collateral-based mechanisms, providing partial support for both trade-off and pecking-order theories.
Originality/Value: The article adds to the body of knowledge on capital structure by providing sector-specific insights and examining capital structure during crises in an under-researched emerging market, thereby expanding the discourse on dynamic capital structure to include Bangladesh
Does Cost of Debt Condition the Debt–Value Nexus? Quantile Regression Evidence from Nigerian Manufacturing Firms
No full textThis paper investigates how the composition of corporate debt relates to shareholders’ wealth across the distribution of firm valuation in a high cost borrowing environment. Using a balanced panel of 43 listed Nigerian manufacturing firms from 2013 to 2023, we compare pooled Ordinary Least Squares with year effects to quantile regressions at the 25th, 50th and 75th quantiles of shareholders’ wealth. Shareholders’ wealth is proxied by market capitalisation; the key regressors are short-term and long-term interest-bearing debt ratios, with the cost of debt as a conditioning variable and profitability and firm size as controls. Interaction terms between cost of debt and debt structure are constructed from mean-centred regressors. The results show that short-term debt is positively associated with shareholders’ wealth throughout the distribution, while long-term debt is negatively associated. The cost of debt is adverse on average and most pronounced around the median quantile. Interaction terms are not statistically significant across quantiles, which suggests that, conditional on observables, the cross-quantile differences are driven largely by the level effects of debt structure and borrowing costs rather than by moderation. The findings highlight distributional heterogeneity in the debt–value nexus that is not captured by mean regressions alone and have implications for tenor policy, treasury management, investor screening and credit-market design in emerging economies