In light of the on-going debates about the widely debated trade-off between environmental responsibility and financial performance of companies, this study was conducted to investigate the relationship between environmental clean-up costs and the financial performance of plastic manufacturing companies in Douala. An ex-post facto research design was employed and the analysis based on 40 firm-year observations from 2016 to 2023. The data analysis was conducted using the Ordinary Least Square technique applied to the pooled panel data. The empirical evidence disclosed that the direct financial burden of environmental clean-up costs does not significantly impair the overall profitability of the company. Secondly, the key drivers of financial success in the plastic manufacturing companies appear to be the firm size and the operational efficiencies associated with it rather than environmental clean-up costs. Thirdly, most successful firms are the larger ones that have likely integrated more efficient processes, leading simultaneously to better financial outcomes and a reduced need for reactive environmental clean-up cost spending. Based on these findings the policy recommendations are that: plastic manufacturing concerns should prioritize investments in operational efficiency, modern production technologies, and waste minimization processes; the government should institute a policy approach that supports and enables firms to modernize by creating incentive structures such as tax credits or grants that encourage firms of all sizes to invest in cleaner production technologies.
In this paper, we analyzed the relationship between sustainable development practices and the financial performance of Iraqi industrial companies and investigated the moderating effect of artificial neural networks. Given the significance of sustainability as a worldwide issue, this study seeks to fill the research gap regarding sustainability in developing economies. Different metrics for sustainability and financial performance are evaluated through analysis of empirical data of Iraqi industrial organizations. This study uses artificial neural networks to assess their contribution to improving these interactions. It finds that sustainability activities lead to better financial performance, so the focus on environmental, social and governance (ESG) issues does indeed matter. Moreover, artificial neural networks significantly improve the accuracy of the prediction of financial performance using sustainability criteria. Corporations that employ sustainable practices and advanced computational techniques also obtain superior financial results through those applications. This publication contributes to the theoretical discourse on sustainability, financial performance, and artificial intelligence by developing action-oriented suggestions for industry leaders in Iraq. It also directs the next phase of research and policy development for sustainable industrial advancement.
Objective: This study investigates the effect of intangible assets on the financial performance of companies in Georgia. The focus is on how intangible resources, measured by the Representativeness of Intangible Assets (RIA), influence Return on Assets (ROA) as a key performance indicator. Methodology: The research utilizes a panel regression analysis with a fixed-effects model to examine the relationship between intangible assets and company performance. The dataset comprises financial reports from 845 Georgian companies, spanning the period from 2019 to 2022, obtained from the Service for Accounting, Reporting, and Auditing Supervision of Georgia. The study excludes companies from the financial industry and those with negative equity. Results: The findings indicate that intangible assets have a significant and positive impact on firm performance. The study reveals that companies with a higher proportion of intangible assets outperform their peers, supporting the hypothesis that investment in intangible resources leads to improved profitability. Company-specific factors also play a substantial role in determining firm performance. Conclusions: This study provides empirical evidence that intangible assets are key drivers of profitability in Georgian companies. It highlights the importance of intangible resources in achieving competitive advantages, particularly in emerging markets transitioning towards knowledge-based economies. Limitations include incomplete disclosure of intangible assets in company financial statements, which may affect the analysis' comprehensiveness. Implications: The study offers insights for corporate strategy and policy, emphasizing the need for companies to invest in intangible assets and for policymakers to foster an environment conducive to the development of these resources.
The Kuwait and other countries of the Gulf Cooperation Council (GCC) have traditionally based their economic model on the receipts from the sales of oil. Fluctuations in the price of oil in the global markets has since rendered these economies more vulnerable to such financial risks and through policymaking, the economies have started to look for ways of diversifying on the risks. While the world today is working towards a new energy mix, those changes toward renewables and sustainability have led the reliance on oil towards economic, strategic and developmental issues. For Kuwait, a country that depends on oil as its major source of export, the issue of diversifying the country’s investment portfolio is even more important. It is stated that Kuwait needs to diversify investments to minimise the risk linked with fluctuating oil prices. With regards to this study, the analyses of the current state of economy of Kuwait, the impacts of instability of oil prices and the possible opportunities for diversification of investments will help in a more informed understanding of how Kuwait can better ensure a sustainable economy.
University Rankings exert considerable influence in higher-education decision-making. Yet, as an artifact of their construction, rankings are largely unhelpful in conveying practical strategic insights to university administrators intent on improving their college’s rank. Machine learning tools such as interpretable machine learning (IML) and explainable artificial intelligence (XAI), taking aim at piercing obscure, black-box algorithms have gained a lot of interest recently. However, there appear to be few deployments of their use in appraising University rankings. In this work, using data representing QS Rankings data of USA MBA programs we show how counterfactual XAI can support proactive responses by educational stakeholders to Rankings outcomes. Explaining individual predictions opens great opportunities for intervention and strategizing. The method is applicable to any extant rankings.
As the world economy undergoes a rapid digital transformation, Internet financial reporting (IFR) has evolved into an important platform for the dissemination of information to investors. It has also been a central topic of discussion among practitioners and researchers due to the lack of rigorous regulations to govern IFR practices, resulting in disclosures of financial reports varying across listed companies. This study aims to assess the level of compliance with the qualitative characteristics of IFR for companies listed on Bursa Malaysia. This study involves adopting 34 constructed index items based on prior literature and the use of a 5-point Likert scoring scale anchored from "very poor" (1) to "excellence" (5) to measure the fundamentals and enhance the qualitative characteristics of IFR, which is also in line with the "Revised Conceptual Framework for Financial Reporting" issued by the Malaysian Accounting Standards Board (MASB) in 2018. Non-probability purposive sampling was employed to select the companies from 11 relevant industries, comprising 160 listed companies from the main market of Bursa Malaysia. Annual reports and corporate governance statements were extracted from corporate websites for 2018. Findings suggest that most corporations that are listed in the main market of Bursa Malaysia have yet to fully comply with the MASB’s financial reporting framework, notably timeliness, which requires urgent improvement. Without strict IFR regulations, managers may also be free to act opportunistically by planning their IFR disclosure in a way that benefits both the company's reputation and their interests. This research enriches the body of literature on IFR and provides a measuring mechanism that can gauge the level of compliance with the qualitative characteristics of IFR. It acknowledges the importance of collective efforts from regulatory bodies to implement accounting reforms and the best IFR governance practices to harness information's usefulness in the Industrial Revolution era. 4.0.
A large amount of money in the economy remains in the form of trade receivables that are created from the business to business (B2B) transactions among the firms. There are 7.818 million firms in Bangladesh and 99% of them are in the categories of cottage, micro, small, and medium enterprises (CMSMEs). They supply the raw materials, semi-finished goods, and services on credit to the large and blue-chip corporate manufacturers. CMSMEs generally wait for a period of 30 days, 60 days, 90 days and so on for the payment. During this period, CMSMEs suffer from the lack of working capital that remains tied in trade receivables against their credit sales to the corporate buyers. The study provides a financing solution through trade receivable exchange (TRX) to release the fund into cash from the investment locked into trade receivables. The study presents the concept and modus operandi of TRX. It shows the global practice of TRX. It assesses the application of TRX in the context of Bangladesh and in doing so; it has explored market space, readiness, FinTech industry, and stakeholders related to TRX. The academic research on TRX in Bangladesh is rare that presents a research gap for the study. Here, around 51% CMSMEs close their business for the shortage of working capital. The study addresses this working capital problem through TRX that brings a novelty and significance for the research.
The advent of digital technologies and the increasing adoption of artificial intelligence (AI) have transformed various industries and firms, including auditing. Manual auditing procedures have proven to be time-consuming and labor-intensive, leading to lower audit quality and higher costs. The integration of digital transformation and AI in auditing practices offers potential solutions to enhance efficiency and effectiveness in Saudi Arabia. Therefore, this research focuses on examining the impact of digital technologies and AI on audit efficiency, effectiveness, challenges faced during adoption, adjustments in auditors' roles, and the regulatory and ethical considerations arising from the integration. A cross-sectional research design was adopted to collect data from a sample of 400 participants through an online survey, analyzed by statistical tools, including descriptive statistics and correlation and examined the relationships between variables. The findings indicate a positive relationship between the level of digital transformation and the adoption of AI in auditing practices in Saudi Arabia, along with significant challenges, such as resistance to change, technological infrastructure, skills gap, and regulatory compliance concerns, paving a way for further advancements in the field of auditing and digital transformation.
There are hundreds of mutual funds in the market, each offering different returns. The investors always look at funds which give high returns and have low risk. Thus while making a portfolio the asset management company should make investment allocations where returns are definite and to give justified returns for every rupee the investors pay, considering the different risks. The objective of the study was to find the short-term effects of portfolio allocation on the performance of mutual funds. The data for the study was consisted of the portfolio allocations and the performance statistics of one hundred and fifty-nine open-ended mutual funds, of which fifty were diversified debt/ income funds and one hundred and nine were diversified equity funds. These funds were further classified into different mutual fund schemes. Each of the mutual funds had a different portfolio and investments were made in different instruments like bonds, certificates of deposit, commercial papers, etc. (in case of debt) and in different sectors like technology, chemicals, services, etc. (in case of equity). The findings from the study indicate that, for debt funds, allocation in bonds and government securities tend to impact the performance of the fund, while for equity funds, allocation in engineering, energy, and service sector stocks tend to impact the performance of the fund. Keywords: asset management company, portfolio allocations, returns, performance, debt funds, equity funds.
Financial inclusion refers to people’s ability to hold a current account with a bank. The degree of financial inclusion is measured by the share of individuals and businesses that use the financial services offered by banks and other financial institutions. Financial inclusion has become extremely relevant among financial sector operators and supervisory authorities as a mean to evaluate both growth and development potential and to guarantee adequate controls to safeguard the stability of the system. Interest in this topic has also been growing because it is included in the UN’s sustainable development goals (the 2030 Agenda for Sustainable Development). This note intends to identify where countries currently stand in relation to the inclusion target, with a focus on Central, South and Eastern European (CESEE) countries, by using the new data from Global Findex, updated by the World Bank in July 2022. The Global Findex is a vital source of data that is only partially used here to evaluate the degree of diffusion of accounts and basic banking services (deposits and credit) in the CESEE sample. Financial inclusion had improved further by 2021. In many countries, it has become very high and is now at the level of major high-income countries. Most of the unbanked are still concentrated in a few Asian countries. Digital payments strengthened in all regions, especially in Asia. However, the gap between ownership and utilisation of credit and debit cards remained large in 2021, suggesting there is a need to further incentivise use. Customers often have an account but still prefer to use cash. Ownership is not utilisation. The UN’s Sustainable Development Goal could realistically be reached by 2030, but now it is necessary to improve financial education and digital literacy to encourage more effective and extensive use of financial accounts. Nevertheless, the ample diffusion of financial inclusion can be reached mainly with a more even income distribution, in all countries and in all the different development models which are spreading in the world.
Indian financial markets have witnessed very high levels of volatility in recent months, with a sharp decline in the BSE-SENSEX from a peak of around 21,000 points to a nadir below 11,000 points, with as much as a 700-point fall on one single day. Indian economic conditions have also seemed to stagnate, with an overall slow-down in economic growth, along with the pressures of increasing crude oil prices and increasing inflation. In fact, the overall global scenario has also been quite bleak, especially with the onset of recession in the US. Mutual fund investments, which are generally considered to be less risky than other financial instruments such as shares and debentures, have also suffered in the general atmosphere of volatility. The present study investigates the effect of macroeconomic variables on mutual fund schemes, in terms of returns and volatility. The study uses the Granger causality test to analyze these effects. The results of these causality tests would identify the specific macroeconomic factors which affect the returns and volatility of particular mutual fund schemes, which, on the one hand, would enable fund managers to manage the risk profiles of their portfolios more effectively; and, on the other hand, would enable investors to understand the specific risk factors affecting their investments, so that they can take more informed investment decisions pertaining to mutual funds. The data to be used in the study were the weekly returns and volatilities of different macroeconomic variables, such as market returns (calculated from the BSE-SENSEX), USD/INR and EURO/INR exchange rates, interest rates (Mumbai Inter-Bank Offer rates), inflation rates, and crude oil prices, over the period October ‘06 - June ‘08. The weekly returns and volatilities of a sample of major mutual fund schemes over the same period would be considered for the analysis.
This paper proposes an analysis of the factors that most influence the corporate value of 64 European listed companies surveyed through Amadeus Bureau van Dijk's database over the 2020 period. Following the prevailing literature, for our study we adopt the multiple linear regression model with ROE, as dependent variable explicative of value, and LIQUID, LEVERAGE, SIZE, CFTA, DATA as explanatory variables. The result of our model indicates that value is positively affected by all explanatory variables except the SIZE variable.
A public accountant has an obligation in providing good audit quality but with the case of freezing the license of the public accounting firm karana violation of SPAP, the public began to doubt the quality of the audit itself. The purpose of this study is to empirically test the quality of audits influenced by audit fees and audit quality influenced by the audit agreement period. The methods used are descriptive and verifikative. The population is 16 Public Accounting Firms in bandung area, using saturated sampling techniques or census, while the respondents are senior auditors, partners. Statistical testing uses correlation analysis, multiple regression analysis, coefficient of determination and to test the hypothesis then used t test. The results showed that the quality of audit is influenced by the audit fee, between the quality of the audit and the audit fee has a positive relationship which means that when the audit fee is large, the quality becomes better. The quality of audit is also influenced by the period of auditor's alliance and has a negative relationship where when the alliance period becomes long, the audit quality becomes poor, the quality of the audit is also influenced by other factors that are not researched such as independence, competence, professionalism and so on. Based on the results of the study the authors suggest that when accepting work from clients, the approved audit fee must be adjusted to the audit fee structure so that the quality is better and the complexity of the services provided while the contracting period with the client should be the second year of auditing the auditing team of auditors in rotation to keep the audit quality good.
The aim of this paper will be achieved through analysis of data for the 8-year period from 2009 to 2016 for all 30 companies listed on the Dow Jones Industrial Average (DJIA). The analysis utilizes eight indicators aiming to provide information regarding four areas of a company’s operations i.e profitability ratios: return on assets (ROA) and return on equity (ROE); liquidity ratios (Current Ratio); Leverage Ratio (Debt to Equity) and Market-based ratios earnings per share (EPS), dividend per share (DPS), price to book ratio (P/B), price-earnings ratio (P/E). The results from our model indicate that fundamental analysis is weak given that results designate insignificant relationship between most of the explanatory variables and the stock returns.
This study attempts to identify some of the firm specific factors that might have an impact on lessor financial performance after the application of EAS 49 and the Financial Leasing and Factoring Act (Law 176 of 2018). Numerical data were collected for five years during 2016-2020 from financial reports obtained from the Egyptian Financial Regulatory Authority (FRA). Study sample comprised 43 observations. The dependent variable is the firm financial performance signified by total debt/total equity, earnings per share EPS, return on equity ROE, asset turn over, return on capital employed ROCE, current ratio, return on assets ROA, and total debt/total assets. The independent variables are sales, financial liabilities, EBIT/operating profit or loss, and financial leased fixed assets. The study used pooled model, fixed effect model, and random effect model. Results indicate the sales, financial liabilities, EBIT/operating profit or loss, and financial leased fixed assets have an effect on lessor financial performance after the application of both IFRS 16 equivalent of EAS 49 and the Egyptian Financial Leasing and Factoring Act (Law 176 of 2018). The data is accurate and complete. The length of the study period makes it possible to track progress of lessor firms. This study tries to identify the impact of some firm specific factors on lessor financial performance after application of EAS 49 and Financial Leasing and Factoring Act (Law 176 of 2018). Thus, this study is a modest contribution to better decision making of investors, creditors, lessors, and lessees.
Human Capital (HC) is the sole intervening factor for a competitive hedge in all firms: merchandising, manufacturing, or servicing. However, the need for HC is enhanced in service firms because only they can act. All requisite tangible and intangible assets of firms are accounted for as material investments in their financial reports for improved decisions by managers and other stakeholders. However, contemporary organizations are unable to account for their HC investments because there is no Generally Accepted Legal Framework (GALF). This is even though HC accounting discipline has attracted attention in most jurisdictions, although it was largely disregarded in some parts of the world and the deliberations date back to the early sixties of the last century. Could the exploration of HC accounting underpinning theories offer practitioners research insights?
Liquidity is the risk to a bank's earnings and capital arising from its inability to timely meet obligations when they come due without incurring unacceptable losses. Bank management must ensure that sufficient funds are available at a reasonable cost to meet potential demands from both fund providers and borrowers. Also, Lending is the process by which a financial institution provides funds to a borrower. Often called a lender, the institution typically receives interest in return for the loan. Lending in banking benefits lenders and borrowers alike by increasing liquidity within the marketplaces where loans are originated and used. This article aims to identify the impact of liquidity on bank lending. We used a sample of 12 banks in Tunisia over the period (2005….2022). By employing a method of panel static we found that liquidity has a significant impact on bank lending.
This study proposes a vector autoregressive form for the market model and tests its significance against the market model for information technology (IT) sector stocks in the Indian stock market. The analysis was performed for a sample of nineteen IT sector stocks listed on the National Stock Exchange of India, of which nine stocks were large-cap, six were mid-cap, and four were small-cap. The study period considered was Jan. 1, 2018 – Dec. 31, 2018. The key contribution of the study was the finding that the vector autoregressive model is a better model of stock returns than the market model for IT sector stocks. Thus, IT sector stocks seem to react more to market movements from the previous day than on the day itself. The implication for asset pricing modelling is that systematic risk may be further decomposed into a component corresponding to sensitivity to market movements on the day and a component corresponding to sensitivity to market movements on the previous day. The asset pricing model would be extended to include market risk premia for both of these components of systemic risk. Keywords: market model, vector autoregressive model, IT sector, asset pricing modelling, systematic risk.
The main goal of this paper is to investigate the random walk hypothesis in Fiji using monthly data from January 2000 to October 2017. Applying augmented Dickey Fuller (ADF 1979, 1981) and Phillips-Perron (1988), Zivot-Andrews (1992), and Narayan and Popp (2010) unit root tests, this study finds that stock prices is best characterized as non-stationary. The estimated multiple structural break dates in the stock prices corresponds with devaluation of Fijian dollar by 20 percent in 2009 and General Elections in September 2014, which Fiji First Party won by majority votes. The empirical results indicate that stock prices are best characterized as a unit root (random walk) process, indicating that the weak-form efficient market hypothesis holds in Fiji’s stock market. Hence, it will be difficult to predict future returns based on historical movement of stock prices in Fiji’s stock market.
Diversity of board members has become a recent topic by which it has been linked to board’s effectiveness. It can be postulated that directors from a different generation will exhibit different values, knowledge and behavior that can influence the decisions and actions of a firm. However, earlier studies have produced mixed findings on the effect of director's age and firm performance. This study proposes that in order to examine the influence of age diversity, researchers must capture the difference in the age cohort of directors. Different generations carry its own common and unique characteristics. Consistent with the diversity concept, age diversity should be examined based on the inclusion of different generations to the board, and not just the average number of directors’ age as practiced in earlier studies.
