Banking under catastrophic crisis on corporate governance and performance in Bangladeshi Private and State-Owned Banks during COVID-19 pandemic: Insights from a multiple linear regression analysis

Banking under catastrophic crisis on corporate governance and performance in Bangladeshi Private and State-Owned Banks during COVID-19 pandemic: Insights from a multiple linear regression analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Banking under catastrophic crisis on corporate governance and performance in Bangladeshi Private and State-Owned Banks during COVID-19 pandemic: Insights from a multiple linear regression analysis Md Ibrahim Khalid, Tanvir Ahmed Tuhin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6343886/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study investigates how corporate governance affected the performance of private and state-owned banks in Bangladesh during the COVID-19 epidemic. Using a multiple linear regression technique, the study examines how governance structures and financial performance metrics were influenced. The study evaluates eleven banks from 2019 to 2020, using key variables such as Return on Assets (ROA) and Return on Equity (ROE) as dependent variables, and independent variables such as bank size, capital adequacy ratio, liquidity ratio, non-performing loans ratio, board size, board meetings, CEO duality, and independent directors. The findings reveal substantial relationships between corporate governance practices and banking performance, providing insight into the usefulness of governance frameworks in navigating economic upheavals. The study uses quantitative research approaches to identify the primary drivers of banking efficiency and its implications for financial stability. The study adds to our understanding of corporate governance's role in performance assessment and makes recommendations for enhancing governance frameworks in the banking industry. Despite of restrictions such as data accessibility and confidentiality, the study provides useful information about the link between governance and financial success in Bangladesh's banking system. Figures Figure 1 Figure 2 Introduction Corporate governance has emerged as a hot subject due to its significant contribution to national growth and development. The absence of adequate corporate governance is a primary cause of failure in many well-performing businesses. Corporate governance refers to the rules, procedures, and processes that guide and control a firm. Corporate governance is fundamentally about balancing the interests of a company's many stakeholders, which include shareholders, management, consumers, suppliers, financiers, the government, and the community. Because corporate governance also serves as a framework for achieving a company's goals, it incorporates nearly every aspect of management, from action plans and internal controls to performance measurement and corporate transparency. The goal of corporate governance is to enable effective, entrepreneurial, and responsible management that can generate long-term success for the organization. Corporate governance is thus concerned with what a company's board of directors does and how it establishes the company's values, as opposed to the company's day-to-day operations. The significance of corporate governance is: I) Corporate Governance Promotes community confidence II) Encourages elected members and council officers to be confident III) Results in better decisions IV) Assists local governments in meeting their statutory duties. V) Promotes ethical decision making. Cash is a valuable asset for every company. Cash is one of the assets that appear on each firm's balance sheet. Cash plays an important function in a company's finances. Corporate governance and performance assessment are most closely associated in all organizations since they do not apply to private enterprises that are not long-term players. Performance measurement is a crucial aspect for financial management; this is connected not only to operations and business improvement, but also to corporate governance. The dependent variable is performance measurement (ROA, ROE), whereas the independent variables are corporate governance Bank size, capital adequacy, liquidity ratio, operations management, non-performing loans ratio, board size, board meetings, duality, and independent directors. Literature Review Bourke (1989) Between 1972 and 1981, researchers looked at the success of banks in 12 nations across Europe, North America, and Australia. Focus, liquidity, inflation, and scale, he found, all had a favorable impact on bank efficiency and profitability. The technique of Bourke (1989) is replicated in Molyneux and Thornton's (1992) investigation. Between 1986 and 1989, the determinants of banking success were studied in 18 European nations. The findings backed up Bourke's observations. Return on average assets (ROAA) is a method of determining a bank's efficiency. Amplitude of any global pandemic has a serious dominance on job sector, human health, economy, education, environment, social life and so on. Global economy already affected by the prevalence of COVID-19 pandemic adversely. Like other crisis, the COVID-19 pandemic has negative effect on Business, production, consumption and service sector so that it also affects the banking sector. An investigation by (Boone, 2020),Pasiouras and Kosmidou (2007) In the years 1995-2001, the profitability of 584 commercial domestic and foreign banks operating in the 15 European Union nations was examined. The results reveal that the profitability of local and multinational banks in the European Union is impacted by basic bank attributes (size, capital adequacy, managerial efficiency 1857-7431), financial market infrastructure (concentration), and macroeconomic indicators (growth rate of profit). In addition, Athanasoglou et al. (2008) Between 1985 and 2001, a study was released to examine the effects of bank-specific, industry-specific, and macroeconomics variables of Greek bank profitability. Except for the size of the business, the calculations revealed that all bank-specific characteristics had a significant impact on transaction profitability. The research also revealed that bank profitability is unaffected by concentration and governance. De Andres and Vallelado (2008) From 1995 to 2005, a sample of 69 major commercial bank boards from Canada, France, the United Kingdom, Italy, Spain, and the United States were used. They discovered that bank success was strongly linked to board meetings, with an inverted U-shaped relationship between board size and the share of outside directors.(Murtaza, 2020) argued that by the second half of 2020, the majority of banks will be in a precarious position in terms of operating earnings. Almost all of the banks have experienced a gradual increase in profits when compared to the previous year. indicated that the banking industry is experiencing liquidity and loan recovery issues. Staikouras et al. (2007) Over the year 2002-2004, researchers looked examined the relationship between two of the most important corporate governance metrics – the size of the board of directors and the number of non-executive directors – and the firm production of 58 large European banks. The findings show that bank profitability is inversely correlated with board size, but the influence of board structure, while positive in all models, is minor in most circumstances. Moreover, Covid-19 has effects on shape and mind and is breaking the concept of the world economy and global village. Even the globe’s life science is deteriorating to curb the disease. Liang et al. (2013) The qualities of the board's effect on bank efficiency and bank asset valuation in China were investigated. They found that the composition of the board had a significant The proportion of independent directors and the number of board meetings had a significant positive influence on both bank performance and asset quality, whereas the proportion of independent directors and the number of board meetings had a large negative impact., using panel data from the 50 largest Chinese banks from 2003 to 2010. Trujillo-Ponce (2013) from 1999 to 2009, researchers looked into the elements that influenced the performance of Spanish banks. Following that, the analysis reveals inefficiencies in the efficiency of commercial and savings banks. Second, Asset quality, capitalization, concentrations, inflation, economic expansion, and real interest rates all showed a strong positive association, according to the data, as well as between ROA and ROE Furthermore, Akhtar, Ali, Sadaqat (2011) used panel data for Pakistani banks from 2006 to 2009 and found a gearing ratio, non-performing loans, and asset management that had a substantial effect on the profitability of traditional Pakistani banks. Macit (2011), paper on Turkish commercial banks, a Turkish scholar found that the non-performing loan percentage is negatively related to return on assets and return on equity, which has an impact on the banking sector's success. Shamim, (2019) Bangladeshi banks are facing vast uncertainties and skepticism particularly about refunds of credits by their customers when their commercial activities are in disarray. Babu, (2020) Nonperforming loans are those that leave banks but do not return to their records, resulting in a loss of financial health.When a bank's bad loan rate is high, it weakens the bank's ability to offer loans and puts stockholders at risk. Oman (2001) Company governance is defined as rules, regulations, and business practices that govern the relationship between corporate managers and stakeholders in both private and public institutions. Corporate governance is defined by the Singapore Ministry of Finance (corporate governance 2001) as "the processes and structure by which the company's business and affairs are directed and managed, to enhance long-term shareholder value through corporate mechanism. As a result, good corporate governance encapsulates enterprise performance and accountability, as well as adherence. Filatotchev, Lien, and Piesse (2004) studied Corporate Governance and Performance in Taiwanese Publicly Listed, Family-Owned Businesses. They looked at the impact of ownership structure and board characteristics on performance in large, publicly traded companies run by family businesses. The authors stated that East Asian enterprises operate in a different culture and legal and institutional context than firms in the West and Europe, and that these cultural variations may have a significant impact on governance- performance linkages, as shown by agency and strategy research. The authors found no direct link between family ownership and management entrenchment and extraction of private gains from this control, which could be a contributing factor to poor financial performance. La Porta, Silanes, and Shleifer (2000, 2002) Consider corporate governance to be a set of procedures that safeguard outside investors (shareholders) from insiders (managers). Corporate governance is defined by the Organization for Economic Cooperation and Development as the framework by which business corporations are directed and governed. The corporate governance structure defines out the rules and methods for making corporate decisions, as well as the distribution of rights and obligations among different players in the organization, such as the Board of Directors, management, shareholders, and other stakeholders. It also offers the frameworks through which the company's goals are determined, as well as the means of achieving those goals and monitoring performance. Lastly, McColgan (2001) presented a comprehensive perspective on agency theory and corporate governance His research was primarily focused on the region where the interests of managers differ from the interests of shareholders. He kept the agency relationship in mind, as well as the agency expense that comes with it. He built on Jensen and Meckling's definition of an agency relationship as a type of contract in which the principal retains the agent to perform the firm's services on his behalf. As the principal delegate some decision-making authority to the, the agency dilemma occurs owing to competing interests and a conflict between ownership and control. Research Objectives This paper evaluates the compatibility of COVID-19 in the banking sector, presenting an overview of its effects and calculating the efficiency levels of various banks during sudden crisis situations. The main objective is to understand the role board member and its contribution to sustainable performance, particularly corporate governance. To attain the principal objective there are some specific objectives are: firstly, to analyze the financial analysis on banking sector in Bangladesh; and secondly, to examine dependent variable’s influence on others independent variables which are statistically significance or not. A part from that, to find out the relationship (positive or negative) among corporate governance and performance measurement and whether board size has any impact on firm performance. Background of the study This paper examines the variables that impact banks' success in Bangladesh. We pick eleven private banks and public banks as a sample to find those variables, and we also try to find out their data on variables over the last two years (2019 & 2020). We implemented three types of variables for the calculation of variables. These are: profitability, bank-specific determinants, and bank governance. We have used two types of factors in the case of profitability, which are Return on Assets and Return on Equity. On the other hand, under bank-specific determinants, we took four variables-the size of the bank, the capital adequacy ratio, the liquidity ratio and the non-performing loans ratio. We took four factors, which are Board Size, Duality, Board Meetings and Independent Directors as a variable. As we measure the outcome of those variables after defining them, and aim to find statistical values, such as F-significance, R value, adjusted R and R-square so we want to figure out the implications of the panel regression. As a consequence, the factors or variables influencing Bangladesh’s banking efficiency can be easily established. Limitation of the study The limited information during pandemic we could able to collect in person evidence so collecting information from the website was very difficult for us because it is not enriched with information, although we both tried our hardest to collect full data. Employees are not allowed to provide sensitive and depth information or confidential data. The data contained in this report are also collected from secondary sources because of lacking in primary data collection, so the authenticity of the report may be questionable to some people. Research Methodology This research will be analytical and descriptive in nature. A quantitative data research would be used to analyze and present the study issues. This study employs multiple regression analysis to examine the impact of selected factors on performance on banking sector in Bangladesh. Multiple regressions are a widely used statistical technique for estimating the parameters of a linear regression model. It is particularly suitable for analyzing relationships between a dependent variable and one or more independent variables, as is the case in this study. Sources of Data In the collection of secondary data, various organizations annual reports are playing a crucial role, including national bank and private bank, Bangladesh Bank, and the Google scholar are being utilized to gather information. This paper will develop a summary metric for the governing score that will be used to assess the firm's governing strength. We were gathered data on corporate governance and business performance from annual reports and available to the public information sources. Although we were trying to obtain data from credible sources such as annual reports and journals, we will largely rely on secondary sources for my study. This paper will use a large number of individual firms as a sample for this study, ensuring that it is representative of real- world events. This article will use data from the 2019 and 2020 fiscal years to assess firm performance. Variables of the Study and Sources of Data The study uses secondary data mostly from annual, as displayed in Figure 1, were gathered. The years 2019 through 2020 are included in these sources. The local bank's dataset provided the data on ROA and ROE, which were the dependent variable. The study takes into account the H8_Ind, H3_Liquidity, H5_Meetigns, H4_Npl, H2_Capital Adequacy, H6_Board size, H1_Bank’s Size, H7_Dua Analytical model Model Summary b R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change .997 a .994 .970 .12533 .994 40.905 Dependent Variable: ROA Predictors: (Constant), H8_Ind, H3_Liquidity, H5_Meetigns, H4_Npl, H2_Capital Adequacy, H6_Board size, H1_Bank’s Size, H7_Dua Model summary • R: shows that the R value was 0.997, which is high. This indicates the independent variables. ROA is significantly correlated with Independent variable. • R square: in the model summary table, R Square is .994, meaning that independent variable can explain 99.4% of the variance, which is the standard for R square, and the remaining 1.6 % is influenced by elements that have not been explored. These variables were also analyzed. • Adjusted R square: R-square was converted into an adjusted R-square. The modified R-squared value indicates that the addition of variables improves the regression model. To comprehend the adjusted R-squared value after rationalizing the inaccuracies, the adjusted number was 0.970, down from 0.994. • Standard error of the estimation: the standard error of the estimate measures the Regression model prediction accuracy. The probability of the best fit increased with a lower standard error of the estimation. In this model summary, the estimated standard error was 0.12533 ANOVA a Model Sum of Squares df Mean Square F Sig. Regression 5.140 8 .642 40.905 .024 b Residual .031 2 .016 Total 5.171 10 a. Dependent Variable: ROA b. Predictors: (Constant), H8_Ind, H3_Liquidity, H5_Meetigns, H4_Npl, H2_Capital Adequacy, H6_Board size, H1_Bank’s Size, H7_Dua The ANOVA Table indicates a significance level of 0.024, below 0.05. The null hypothesis was rejected; hence, the alternative hypothesis that independent factors could explain the dependent variable was accepted. Coefficient The coefficient determines the independent relationship. By measuring the coefficients, we can determine the variables that significantly affect ROA. The significance level for AI and ML-gathered consumer H1_Bank’sSize is .010 ,H2_CapitalAdequacy is 008,H3_Liquidity is .011 ,H4_Npl is .021,H5_Meetigns is .531,H6_Board size is .008,H7_Dua is .011,and, which is less than the alpha value of 0.05,H8_Ind is .496, which is not less than the alpha value of 0.05 Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) -1.328 .508 -2.613 .121 H1_Bank’s Size .537 .054 1.795 9.894 .010 H2_Capital Adequacy .462 .040 1.931 11.442 .008 H3_Liquidity -.206 .021 -1.987 -9.591 .011 H4_Npl .090 .013 .798 6.859 .021 H5_Meetigns .012 .016 .074 .752 .531 H6_Board size -.147 .014 -2.598 -10.887 .008 H7_Dua -5.51 .579 -2.310 -9.512 .011 H8_Ind -.006 .007 -.104 -.826 .496 Dependent Variable: ROA Predictors: (Constant), H8_Ind, H3_Liquidity, H5_Meetigns, H4_Npl, H2_Capital Adequacy, H6_Board size, H1_Bank’s Size, H7_Dua We can include seven-factor variables because they reject the null hypothesis, thus proving our alternative hypothesis. On the other hand one variable accept null hypothesis. Statistical Interpretation : H1 _Bank’sSize _F: sig. value .010 < 0.05; H0 rejected , The positive coefficient of.537 indicates that an increase in bank size leads to .537 unit increase in banking sector performance, with a p-value less than.010 at the 5% level means its statistically significant. H2 _Capital Adequacy _ sig. value 008 < 0.05; H0 rejected, The study reveals that a.462 positive coefficient indicates that a 5% increase in Capital Adequacy leads to a.462 unit increase in bank performance, with a p-value less than.008, indicating statistical significance. H3 _Liquidity _F: sig. value .011 < 0.05; H0 rejected The study reveals that a 5% increase in Liquidity results in a.206 unit decrease in bank performance, with a p-value less than.011, indicating a statistically significant effect at the 5% level. H4 _Npl _F: sig. value .021 < 0.05; H0 rejected The positive coefficient of.090 indicates that an increase in Npl results in a.090 unit increase in bank performance, with a p-value less than.021 indicating statistical significance at the 5% level. H5 _Meetigns _F: sig. value .531< 0.05; H0 rejected The positive coefficient indicates that an increase in meetings leads to a.012 unit increase in bank performance, but the p-value is not statistically significant at the 5% level. H6 _Board size _F: sig. value .008 < 0.05; H0 rejected The study reveals that a 5% increase in board size results in a .147 unit decrease in bank performance, with a p-value less than.008, indicating statistical significance. H7 _Dua _F: sig. value .011 < 0.05; H0 rejected The study reveals that a 5% increase in Dua results in a 5.51 unit decrease in bank performance, with a p-value less than.011, indicating a statistically significant effect at the 5% level. H8 _Ind ,_F: sig. value0.496> 0.05; H0 Accepted The negative coefficient indicates that a percentage point increase in the Ind results in a decrease in bank performance by 006 units, with a p-value greater than.496 indicating no statistical significance at the 5% level Model Summary b Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change 1 .998 a .997 .984 .04921 .997 79.787 a. Dependent Variable: ROE b. Predictors: (Constant), H8_Ind, H6_Board size, H5_Meetigns, H3_Liquidity, H4_Npl, H2_Capital Adequacy, H7_Dua, H1_Bank’s Size Model summary • R: shows that the R value was 0.998, which is high. This indicates the independent variables. ROA is significantly correlated with Independent variable. • R square: in the model summary table, R Square is .997, meaning that independent variable can explain 99.7% of the variance, which is the standard for R square, and the remaining 1.3 % is influenced by elements that have not been explored. These variables were also analyzed. • Adjusted R square: R-square was converted into an adjusted R-square. The modified R-squared value indicates that the addition of variables improves the regression model. To comprehend the adjusted R-squared value after rationalizing the inaccuracies, the adjusted number was 0.984, down from 0.997. • Standard error of the estimation: the standard error of the estimate measures the Regression model prediction accuracy. The probability of the best fit increased with a lower standard error of the estimation. In this model summary, the estimated standard error was 0.04921 ANOVA a Model Sum of Squares df Mean Square F Sig. 1 Regression 1.546 8 .193 79.787 .012 b Residual .005 2 .002 Total 1.551 10 Dependent Variable: ROE Predictors: (Constant), H8_Ind, H6_Board size, H5_Meetigns, H3_Liquidity, H4_Npl, H2_Capital Adequacy, H7_Dua, H1_Bank’s Size The ANOVA Table indicates a significance level of 0.12, below 0.05. The null hypothesis was rejected; hence, the alternative hypothesis that independent factors could explain the dependent variable was accepted. Coefficient The coefficient determines the independent relationship. By measuring the coefficients, we can determine the variables that significantly affect ROE. The significance level for H1_Bank’sSize is .012,H3_Liquidity is .013 ,H4_Npl is .019,H5_Meetigns is .002,H6_Board size is .006,H7_Dua is .048, and H8_Ind is .008 which is less than the alpha value of 0.05.H2_CapitalAdequacy is .460, which is not less than the alpha value of 0.05 Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 2.992 .233 12.825 .006 H1_Bank’s Size -.213 .024 -1.003 -8.904 .012 H2_Capital Adequacy -.009 .010 -.072 -.908 .460 H3_Liquidity -.027 .003 -.484 -8.662 .013 H4_Npl -.039 .005 -.629 -7.234 .019 H5_Meetigns -.099 .005 -1.087 -20.734 .002 H6_Board size .125 .009 1.154 13.323 .006 H7_Dua .503 .115 .385 4.375 .048 H8_Ind -.033 .003 -1.093 -10.917 .008 a. Dependent Variable: ROE b. Predictors: (Constant), H8_Ind, H6_Board size, H5_Meetigns, H3_Liquidity, H4_Npl, H2_Capital Adequacy, H7_Dua, H1_Bank’s Size We can include seven-factor variables because they reject the null hypothesis, thus proving our alternative hypothesis. On the other hand one variable accept null hypothesis. Statistical interpretation: H1 _ Bank’s Size _F: sig. value .012 < 0.05; H0 rejected The study reveals that increasing bank size results in a decrease in banking sector performance by.213 units, a statistically significant effect at the 5% level. H2 _ Capital Adequacy _F : sig. value .460 > 0.05; H0 accepted The study indicates that a 0.009 percentage point increase in Capital Adequacy results in a decrease in bank performance, but this effect is not statistically significant at the 5% level. H3 _ Liquidity _F: sig. value .013 < 0.05; H0 rejected The negative coefficient indicates a statistically significant decrease in bank performance with every percentage point increase in liquidity, affecting all other variables. At 5% level p-value is significant effect on performance. H4 _ Npl _F: sig. value .019 < 0.05; H0 rejected The study indicates that a 5% increase in Npl results in a.039 unit decrease in bank performance, indicating a statistically significant effect. H5 _Meetigns _F: sig. value 002< 0.05; H0 rejected The study reveals a significant decrease in bank performance with every percentage point increase in meetings, indicating a.099 unit decrease in performance at the 5% level. H6 _ Board size _F: sig. value .006 < 0.05; H0 rejected The study reveals that a.125 positive coefficient indicates a statistically significant increase in bank performance with every percentage point increase in board size. H7 _ Dua _F: sig. value .048 < 0.05; H0 rejected The study reveals a significant positive correlation between the Dua percentage and bank performance, with a p-value less than.048 at the 5% level. H8 _ Ind ,_F: sig. value0.008< 0.05; H0 rejected The negative coefficient indicates a statistically significant decrease in bank performance with every percentage point increase in the Ind, indicating a decrease in performance. Author’s findings During research work, we have found the followings: Bank size, liquidity, and capital adequacy ratio (CA) are key factors affecting the success of the banking industry in Bangladesh. Bank size has a negative relationship with dependent variables, such as ROA and ROE, suggesting that the size of the bank affects the success of the backing industry. Liquidity is positively linked to ROE and ROA, and banks should be cautious when raising loans, as it can decrease profitability. The capital adequacy ratio has a positive effect on the output of Bangladeshi banks, indicating that lower profitability is expected due to a higher CA. Non-performing loans negatively affect Bangladesh's banking efficiency, and board meetings have negative relationships with dependent and independent variables. Duality also has a negative relation with dependent variables, indicating that these factors negatively affect the banking sector performance in Bangladesh. That implies that the size of the bank did effect on the success of the backing industry in Bangladesh. We learned from the theoretical portion that liquidity is positively linked to both ROE and ROA. Bangladeshi banks should be very careful to raise the amount of loans in the even to a bad performance, since it brings in a decrease in profitability. This is because Bangladeshi banks have suffered large losses from rising rates of non-performing loans. Banks currently have a lot of capital, but little incentive to use their assets. One of the bank-specific variables affecting the level of bank profitability is CA. In both cases, we find good capital adequacy ratio outcomes according to the findings of panel and multiple regression analysis. The capital adequacy ratio has a positive effect on the output of Bangladeshi banks because of the positive outcome, which is statistically important, contrary to predictions. The finding indicates that lower profitability is caused or expected by a higher capital ratio. We observed from the empirical portion that in research methods panel regression, the non-performing loan negative relationship between dependent variables and independent variables was observed. That means a non-performing loan that affects Bangladesh’s banking efficiency. Negative relationships between dependent and independent variables occur in the case of a board meeting. In Bangladesh, there are several banks that have not scheduled more than 15 meetings in a few years. In case of Duality, there is a negative relation between dependent variables. That means duality did affect the banking sector performance of Bangladesh. Moreover, from our above investigation we have found that bank size, non-performing loan, board size, board meeting, duality and independent variables has a negative relation with dependent variables ROA and ROE. That means those variables had a detrimental impact on the performance of the banking industry in Bangladesh during the COVID pandemic. Conclusion To conclude, The COVID-19 epidemic may be one of the most perplexing difficulties facing the banking industry in recent history. Financial institution stability is a boost to a country's economic growth and development. Bangladesh's financial institutions have previously encountered a number of challenges, including a high rate of non-performing loans, a less structured market, and regulatory deficiencies. We discovered a meaningful and consistent outcome: the pandemic epidemic has a negative impact on the financial industry. It reduced income and raised costs, and the bank lost assets versus obligations. We also observed that the impacts of the COVID-19 epidemic on the financial health of government banks differed from those of private banks in terms of technical efficiency, with private banks handling the pandemic with greater effectiveness than state banking sectors. This report analyzes the impact of bank-specific characteristics, governance, determinants, and economic conditions on banking efficiency in Bangladesh during pandemics. It found that management cost decisions, such as cost to income ratio, non-performing loan ratio, board size, and board meeting, negatively affect bank success. Bank scale, capital adequacy ratio, independent directors, and growth rate of profit have no significant impact on efficiency. Corporate governance, which aims for effective, entrepreneurial, and responsible management, is also gaining interest among policymakers. Declarations Funding The study received no funding, grants, or other support during or before the preparation of this manuscript from any 3rd party, agency, or institute. Author Contribution The author participated in the development of the study design, data analysis, and implementation phases. All writers granted their approval upon reviewing the final product. 1. Md Ibrahim khalid ­- The process of conceptualization includes data creation, formal evaluation, literature review writing, methodology, resources, supervision, visualization, original draft writing, review, and editing. 2. Tanvir Ahmed Tuhin - Data organizing, supervision, investigation, research, project management, original draft writing, and review. Acknowledgments We would like to thank Dr. Md. Rashidul Islam, Associate Professor Department of Business Administration of East West University for his tireless assistance made our research paper complete. A statement of conflicting interests The authors assert that none of the work presented in this study was influenced by any recognized competing financial interests or personal relationships. References Hossain, M. T. (2018). The Trend Of Default Loans In Bangladesh: Way Forward And Challenges. International Journal Of Research In Business Studies And Management, 24-30. FE REPORT. (2020, January 02). 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Journal of Banking & Finance, 13(1), 65-79 Pasiouras, F., & Kosmidou, K. (2007). Factors influencing the profitability of domestic and foreign commercial banks in the European Union. Research in International Business and Finance, 21(2), 222-237. Athanasoglou, P. P., Brissimis, S. N., & Delis, M. D. (2008). Bank-specific, industry-specific and macroeconomic determinants of bank profitability. Journal of international financial Markets, Institutions and Money, 18(2), 121-136. De Andres, P., & Vallelado, E. (2008). Corporate governance in banking: The role of the board of directors. Journal of banking & finance, 32(12), 2570-2580 Trujillo‐Ponce, A. (2013). What determines the profitability of banks? Evidence from Spain. Accounting & Finance, 53(2), 561-586. Staikouras, P. K., Staikouras, C. K., & Agoraki, M. E. K. (2007). The effect of board size and composition on European bank performance. European Journal of Law and Economics, 23(1), 1- 27. Akhtar, M. F., Ali, K., & Sadaqat, S. (2011). Liquidity risk management: a comparative study between conventional and Islamic banks of Pakistan. Interdisciplinary journal of research in business, 1(1), 35-44. Sufian, F., & Habibullah, M. S. (2009). Bank specific and macroeconomic determinants of bank profitability: Empirical evidence from the China banking sector. Frontiers of Economics in China, 4(2), 274-291. Akhtar, M. F., Ali, K., & Sadaqat, S. (2011). Factors influencing the profitability of Islamic banks of Pakistan. International Research Journal of Finance and Economics, 66(66), 1-8 Macit, F. (2012). Bank specific and macroeconomic determinants of profitability: Evidence from participation banks in Turkey. . Economics bulletin, 32(1), 586-595. Mahmud, Z. U. (2020). (2021, November 29). The Impact Of Covid-19 In Banking Sector Of Bangladesh. The Daily Observer. Retrieved from www.observerbd.com:https://www.observerbd.com/cat.php?cd=186 Babu, M. U. (2020, April 17). Banking sector the biggest risk to Bangladesh economy: Survey. Retrieved from THE BUSINESS STANDERD: https://www.tbsnews.net/economy/banking/banking-sector-biggest-risk-bangladesh-economy-survey-45535 Hasan, M. (2020, July 01). First half of 2020: Operating profits of most commercial banks dip. Retrieved from Dhaka Tribiune: https://www.dhakatribune.com/business/banks/2020/07/01/first-half-of-2020- operating-profits-of-most-commercial-banks-dip Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6343886","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":436265016,"identity":"7c516c8c-53a5-47c5-899e-07b6e662fc2d","order_by":0,"name":"Md Ibrahim Khalid","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABKklEQVRIie2Rv0sDMRTHXwjkllzj+MKJf0NAUKHC/Ss9BLs4OFaQI8dBbvEPsKD+DU6lY+SgXe4PqDjYInSyqyj4685zM2JHh3wgbwj58H15D8Dj+YcISopnGABnQLI5DuorWx+iaV17TkUWuUaoYFMAzdVeBfinoqqpRmJgX+rAbJyYNRSYJVoBA65sLd5epWnH0kkUjrsggiPlMsh5onvAW2UxHJUoLTuMwqoP8uzRqVBMdPmKH1zdL4ptObKoLN+5C00JauZOYZhkGlSbEr1dpLUinr6U+BeF85u8+SeXmhiUmjYprE1Bt4JBZppVcAEkVzgp5bBkuy+XVZ9jtTx2KXEZLIG8Q8wgWMzxNBWdaf6gVuPuligOrt1T/jmR75bXfO7xeDweB59hJV6zdbK2agAAAABJRU5ErkJggg==","orcid":"","institution":"East West University","correspondingAuthor":true,"prefix":"","firstName":"Md","middleName":"Ibrahim","lastName":"Khalid","suffix":""},{"id":436265017,"identity":"cc295b28-2187-4c87-b173-31e995c6db25","order_by":1,"name":"Tanvir Ahmed Tuhin","email":"","orcid":"","institution":"University of Dhaka","correspondingAuthor":false,"prefix":"","firstName":"Tanvir","middleName":"Ahmed","lastName":"Tuhin","suffix":""}],"badges":[],"createdAt":"2025-03-31 10:23:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6343886/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6343886/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":79635953,"identity":"20ec103f-ed37-4bfd-876d-b7eb0e69fea9","added_by":"auto","created_at":"2025-04-01 04:30:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":85509,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6343886/v1/2962344f4dec6924e5351379.png"},{"id":79635954,"identity":"20bf1a26-ee6c-48ad-9569-9a1e9a17a7c7","added_by":"auto","created_at":"2025-04-01 04:30:40","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":50439,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6343886/v1/9e9a47c1d4465c4a8aaed567.png"},{"id":79957047,"identity":"d911f56e-5e01-4bf1-beda-f323bef57c50","added_by":"auto","created_at":"2025-04-05 08:31:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":782585,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6343886/v1/b7f60c9d-456e-4ab1-829a-707d839b8356.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Banking under catastrophic crisis on corporate governance and performance in Bangladeshi Private and State-Owned Banks during COVID-19 pandemic: Insights from a multiple linear regression analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCorporate governance has emerged as a hot subject due to its significant contribution to national growth and development. The absence of adequate corporate governance is a primary cause of failure in many well-performing businesses. Corporate governance refers to the rules, procedures, and processes that guide and control a firm. Corporate governance is fundamentally about balancing the interests of a company\u0026apos;s many stakeholders, which include shareholders, management, consumers, suppliers, financiers, the government, and the community. Because corporate governance also serves as a framework for achieving a company\u0026apos;s goals, it incorporates nearly every aspect of management, from action plans and internal controls to performance measurement and corporate transparency. The goal of corporate governance is to enable effective, entrepreneurial, and responsible management that can generate long-term success for the organization. Corporate governance is thus concerned with what a company\u0026apos;s board of directors does and how it establishes the company\u0026apos;s values, as opposed to the company\u0026apos;s day-to-day operations. The significance of corporate governance is: I) Corporate Governance Promotes community confidence II) Encourages elected members and council officers to be confident III) Results in better decisions IV) Assists local governments in meeting their statutory duties. V) Promotes ethical decision making. Cash is a valuable asset for every company. Cash is one of the assets that appear on each firm\u0026apos;s balance sheet. Cash plays an important function in a company\u0026apos;s finances. Corporate governance and performance assessment are most closely associated in all organizations since they do not apply to private enterprises that are not long-term players. Performance measurement is a crucial aspect for financial management; this is connected not only to operations and business improvement, but also to corporate governance. The dependent variable is performance measurement (ROA, ROE), whereas the independent variables are corporate governance Bank size, capital adequacy, liquidity ratio, operations management, non-performing loans ratio, board size, board meetings, duality, and independent directors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eLiterature\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e\u0026nbsp;\u003cstrong\u003eReview\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eBourke (1989) Between 1972 and 1981, researchers looked at the success of banks in 12 nations across Europe, North America, and Australia. Focus, liquidity, inflation, and scale, he found, all had a favorable impact on bank efficiency and profitability. The technique of Bourke (1989) is replicated in Molyneux and Thornton\u0026apos;s (1992) investigation. Between 1986 and 1989, the determinants of banking success were studied in 18 European nations. The findings backed up Bourke\u0026apos;s observations. Return on average assets (ROAA) is a method of determining a bank\u0026apos;s efficiency. Amplitude of any global pandemic has a serious dominance on job sector, human health, economy, education, environment, social life and so on. Global economy already affected by the prevalence of COVID-19 pandemic adversely. Like other crisis, the COVID-19 pandemic has negative effect on Business, production, consumption and service sector so that it also affects the banking sector. An investigation by (Boone, 2020),Pasiouras and Kosmidou (2007) In the years 1995-2001, the profitability of 584 commercial domestic and foreign banks operating in the 15 European Union nations was examined. The results reveal that the profitability of local and multinational banks in the European Union is impacted by basic bank attributes (size, capital adequacy, managerial efficiency 1857-7431), financial market infrastructure (concentration), and macroeconomic indicators (growth rate of profit).\u003c/p\u003e\n\u003cp\u003eIn addition, Athanasoglou et al. (2008) Between 1985 and 2001, a study was released to examine the effects of bank-specific, industry-specific, and macroeconomics variables of Greek bank profitability. Except for the size of the business, the calculations revealed that all bank-specific characteristics had a significant impact on transaction profitability. The research also revealed that bank profitability is unaffected by concentration and governance. De Andres and Vallelado (2008) From 1995 to 2005, a sample of 69 major commercial bank boards from Canada, France, the United Kingdom, Italy, Spain, and the United States were used. They discovered that bank success was strongly linked to board meetings, with an inverted U-shaped relationship between board size and the share of outside directors.(Murtaza, 2020) argued that by the second half of 2020, the majority of banks will be in a precarious position in terms of operating earnings. Almost all of the banks have experienced a gradual increase in profits when compared to the previous year. indicated that the banking industry is experiencing liquidity and loan recovery issues. Staikouras et al. (2007) Over the year 2002-2004, researchers looked examined the relationship between two of the most important corporate governance metrics \u0026ndash; the size of the board of directors and the number of non-executive directors \u0026ndash; and the firm production of 58 large European banks. The findings show that bank profitability is inversely correlated with board size, but the influence of board structure, while positive in all models, is minor in most circumstances.\u003c/p\u003e\n\u003cp\u003eMoreover, Covid-19 has effects on shape and mind and is breaking the concept of the world economy and global village. Even the globe\u0026rsquo;s life science is deteriorating to curb the disease. Liang et al. (2013) The qualities of the board\u0026apos;s effect on bank efficiency and bank asset valuation in China were investigated. They found that the composition of the board had a significant The proportion of independent directors and the number of board meetings had a significant positive influence on both bank performance and asset quality, whereas the proportion of independent directors and the number of board meetings had a large negative impact., using panel data from the 50 largest Chinese banks from 2003 to 2010. Trujillo-Ponce (2013) from 1999 to 2009, researchers looked into the elements that influenced the performance of Spanish banks. Following that, the analysis reveals inefficiencies in the efficiency of commercial and savings banks. Second, Asset quality, capitalization, concentrations, inflation, economic expansion, and real interest rates all showed a strong positive association, according to the data, as well as between ROA and ROE\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurthermore, Akhtar, Ali, Sadaqat (2011) used panel data for Pakistani banks from 2006 to 2009 and found a gearing ratio, non-performing loans, and asset management that had a substantial effect on the profitability of traditional Pakistani banks. Macit (2011), paper on Turkish commercial banks, a Turkish scholar found that the non-performing loan percentage is negatively related to return on assets and return on equity, which has an impact on the banking sector\u0026apos;s success. Shamim, (2019) Bangladeshi banks are facing vast uncertainties and skepticism particularly about refunds of credits by their customers when their commercial activities are in disarray. Babu, (2020) Nonperforming loans are those that leave banks but do not return to their records, resulting in a loss of financial health.When a bank\u0026apos;s bad loan rate is high, it weakens the bank\u0026apos;s ability to offer loans and puts stockholders at risk. Oman (2001) Company governance is defined as rules, regulations, and business practices that govern the relationship between corporate managers and stakeholders in both private and public institutions. Corporate governance is defined by the Singapore Ministry of Finance (corporate governance 2001) as \u0026quot;the processes and structure by which the company\u0026apos;s business and affairs are directed and managed, to enhance long-term shareholder value through corporate mechanism. As a result, good corporate governance encapsulates enterprise performance and accountability, as well as adherence. Filatotchev, Lien, and Piesse (2004) studied Corporate Governance and Performance in Taiwanese Publicly Listed, Family-Owned Businesses. They looked at the impact of ownership structure and board characteristics on performance in large, publicly traded companies run by family businesses. The authors stated that East Asian enterprises operate in a different culture and legal and institutional context than firms in the West and Europe, and that these cultural variations may have a significant impact on governance- performance linkages, as shown by agency and strategy research. The authors found no direct link between family ownership and management entrenchment and extraction of private gains from this control, which could be a contributing factor to poor financial performance. La Porta, Silanes, and Shleifer (2000, 2002) Consider corporate governance to be a set of procedures that safeguard outside investors (shareholders) from insiders (managers). Corporate governance is defined by the Organization for Economic Cooperation and Development as the framework by which business corporations are directed and governed. The corporate governance structure defines out the rules and methods for making corporate decisions, as well as the distribution of rights and obligations among different players in the organization, such as the Board of Directors, management, shareholders, and other stakeholders. It also offers the frameworks through which the company\u0026apos;s goals are determined, as well as the means of achieving those goals and monitoring performance.\u003c/p\u003e\n\u003cp\u003eLastly, McColgan (2001) presented a comprehensive perspective on agency theory and corporate governance His research was primarily focused on the region where the interests of managers differ from the interests of shareholders. He kept the agency relationship in mind, as well as the agency expense that comes with it. He built on Jensen and Meckling\u0026apos;s definition of an agency relationship as a type of contract in which the principal retains the agent to perform the firm\u0026apos;s services on his behalf. As the principal delegate some decision-making authority to the, the agency dilemma occurs owing to competing interests and a conflict between ownership and control.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eResearch Objectives\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis paper evaluates the compatibility of COVID-19 in the banking sector, presenting an overview of its effects and calculating the efficiency levels of various banks during sudden crisis situations. The main objective is to understand the role board member and its contribution to sustainable performance, particularly corporate governance. To attain the principal objective there are some specific objectives are: firstly, to analyze the financial analysis on banking sector in Bangladesh; and secondly, to examine dependent variable\u0026rsquo;s influence on others independent variables which are statistically significance or not. A part from that, to find out the relationship (positive or negative) among corporate governance and performance measurement and whether board size has any impact on firm performance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eBackground\u0026nbsp;of\u0026nbsp;the\u0026nbsp;study\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis paper examines the variables that impact banks\u0026apos; success in Bangladesh. We pick eleven private banks and public banks as a sample to find those variables, and we also try to find out their data on variables over the last two years (2019 \u0026amp; 2020). We implemented three types of variables for the calculation of variables. These are: profitability, bank-specific determinants, and bank governance. We have used two types of factors in the case of profitability, which are Return on Assets and Return on Equity. On the other hand, under bank-specific determinants, we took four variables-the size of the bank, the capital adequacy ratio, the liquidity ratio and the non-performing loans ratio. We took four factors, which are Board Size, Duality, Board Meetings and Independent Directors as a variable. As we measure the outcome of those variables after defining\u0026nbsp;them, and aim to find statistical values, such as F-significance, R value, adjusted R and R-square so we want to figure out the implications of the panel regression. As a consequence, the factors or variables influencing Bangladesh\u0026rsquo;s banking efficiency can be easily established.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eLimitation\u0026nbsp;of\u0026nbsp;the\u0026nbsp;study\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe limited information during pandemic we could able to collect in person evidence so collecting information from the website was very difficult for us because it is not enriched with information, although we both \u0026nbsp;tried our \u0026nbsp;hardest to collect full data. Employees are not allowed to provide sensitive and depth information or confidential data. The data contained in this report are also collected from secondary sources because of lacking in primary data collection, so the authenticity of the report may be questionable to some people.\u003c/p\u003e"},{"header":"Research Methodology","content":"\u003cp\u003eThis research will be analytical and descriptive in nature. A quantitative data research would be used to analyze and present the study issues. This study employs multiple regression analysis to examine the impact of selected factors on performance on banking sector in Bangladesh. Multiple regressions are a widely used statistical technique for estimating the parameters of a linear regression model. It is particularly suitable for analyzing relationships between a dependent variable and one or more independent variables, as is the case in this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSources of Data\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the collection of secondary data, various organizations annual reports are playing a crucial role, including national bank and private bank, Bangladesh Bank, and the Google scholar are being utilized to gather information. This paper will develop a summary metric for the governing score that will be used to assess the firm\u0026apos;s governing strength. We were gathered data on corporate governance and business performance from annual reports and available to the public information sources. Although we were trying to obtain data from credible sources such as annual reports and journals, we will largely rely on secondary sources for my study. This paper will use a large number of individual firms as a sample for this study, ensuring that it is representative of real- world events. This article will use data from the 2019 and 2020 fiscal years to assess firm performance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eVariables of the Study and Sources of Data\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study uses secondary data mostly from annual, as displayed in Figure 1, were gathered. The years 2019 through 2020 are included in these sources. The local bank\u0026apos;s dataset provided the data on ROA and ROE, which were the dependent variable. The study takes into account the H8_Ind, H3_Liquidity, H5_Meetigns, H4_Npl, H2_Capital Adequacy, H6_Board size, H1_Bank\u0026rsquo;s Size, H7_Dua\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAnalytical model\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" style=\"width: 624px;\"\u003e\n \u003cp\u003eModel Summary\u003cstrong\u003e\u0026nbsp;\u003csup\u003eb\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003eR Square\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003eAdjusted R Square\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003eStd. Error of the Estimate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 184px;\"\u003e\n \u003cp\u003eChange Statistics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 69px;\"\u003e\n \u003cp\u003eR Square Change\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 115px;\"\u003e\n \u003cp\u003eF Change\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.997\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.994\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.970\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.12533\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e.994\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e40.905\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 99.8408%;\"\u003e\n \u003col\u003e\n \u003cli\u003eDependent Variable: ROA\u003c/li\u003e\n \u003cli\u003ePredictors: (Constant), H8_Ind, H3_Liquidity, H5_Meetigns, H4_Npl, H2_Capital Adequacy, H6_Board size, H1_Bank\u0026rsquo;s Size, H7_Dua\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eModel summary\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026bull; R: shows that the R value was 0.997, which is high. This indicates the independent variables. ROA is significantly correlated with Independent variable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026bull; R square: in the model summary table, R Square is .994, meaning that independent variable can explain 99.4% of the variance, which is the standard for R square, and the remaining 1.6 % is influenced by elements that have not been explored. These variables were also analyzed.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026bull; Adjusted R square: R-square was converted into an adjusted R-square. The modified R-squared value indicates that the addition of variables improves the regression model. To comprehend the adjusted R-squared value after rationalizing the inaccuracies, the adjusted number was 0.970, down from 0.994.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026bull; Standard error of the estimation: the standard error of the estimate measures the Regression model prediction accuracy. The probability of the best fit increased with a lower standard error of the estimation. In this model summary, the estimated standard error was 0.12533\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" style=\"width: 624px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eANOVA\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 1px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 145px;\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003eSum of Squares\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003edf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003eMean Square\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 116px;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003eSig.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eRegression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e5.140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e.642\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003e40.905\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.024\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eResidual\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e5.171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ea. Dependent Variable: ROA\u003c/p\u003e\n\u003cp\u003eb. Predictors: (Constant), H8_Ind, H3_Liquidity, H5_Meetigns, H4_Npl, H2_Capital \u0026nbsp; Adequacy, H6_Board size, H1_Bank\u0026rsquo;s Size, H7_Dua\u003c/p\u003e\n\u003cp\u003eThe ANOVA Table indicates a significance level of 0.024, below 0.05. The null hypothesis was rejected; hence, the alternative hypothesis that independent factors could explain the dependent variable was accepted.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCoefficient\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe coefficient determines the independent relationship. By measuring the coefficients, we can determine the variables that significantly affect ROA. The significance level for AI and ML-gathered consumer H1_Bank\u0026rsquo;sSize is .010 ,H2_CapitalAdequacy is 008,H3_Liquidity is .011 ,H4_Npl is .021,H5_Meetigns is .531,H6_Board size is .008,H7_Dua is .011,and, which is less than the alpha value of 0.05,H8_Ind is .496, which is not less than the alpha value of 0.05\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"663\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 663px;\"\u003e\n \u003cp\u003e\u0026nbsp;Coefficients\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" valign=\"bottom\" style=\"width: 205px;\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 193px;\"\u003e\n \u003cp\u003eUnstandardized Coefficients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003eStandardized Coefficients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003et\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003eSig.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003eStd. Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003eBeta\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"10\" valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e(Constant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e-1.328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e.508\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e-2.613\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.121\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eH1_Bank\u0026rsquo;s Size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e.537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e1.795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e9.894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.010\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eH2_Capital Adequacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e.462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e1.931\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e11.442\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eH3_Liquidity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e-.206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e-1.987\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e-9.591\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eH4_Npl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e.090\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e.798\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e6.859\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eH5_Meetigns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.752\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.531\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eH6_Board size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e-.147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e-2.598\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e-10.887\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eH7_Dua\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e-5.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e.579\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e-2.310\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e-9.512\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eH8_Ind\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e-.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e-.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e-.826\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.496\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003col style=\"list-style-type: lower-alpha;\"\u003e\n \u003cli\u003eDependent Variable: ROA\u003c/li\u003e\n \u003cli\u003ePredictors: (Constant), H8_Ind, H3_Liquidity, H5_Meetigns, H4_Npl, H2_Capital \u0026nbsp; Adequacy, H6_Board size, H1_Bank\u0026rsquo;s Size, H7_Dua\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eWe can include seven-factor variables because they reject the null hypothesis, thus proving our alternative hypothesis. On the other hand one variable accept null hypothesis. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStatistical Interpretation\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eH1\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e_Bank\u0026rsquo;sSize\u003c/em\u003e\u003cem\u003e_F: sig. value\u0026nbsp;\u003c/em\u003e\u003cem\u003e.010\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026lt; 0.05; H0 rejected\u003c/em\u003e,\u003c/p\u003e\n\u003cp\u003eThe positive coefficient of.537 indicates that an increase in bank size leads to .537 unit increase in banking sector performance, with a p-value less than.010 at the 5% level means its statistically significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eH2\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e_Capital Adequacy\u003c/em\u003e\u003cem\u003e_ sig. value\u003c/em\u003e\u003cem\u003e\u0026nbsp;008\u003c/em\u003e\u003cem\u003e\u0026lt; 0.05; H0 rejected,\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe study reveals that a.462 positive coefficient indicates that a 5% increase in Capital Adequacy leads to a.462 unit increase in bank performance, with a p-value less than.008, indicating statistical significance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eH3\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e_Liquidity\u003c/em\u003e\u003cem\u003e_F: sig. value\u0026nbsp;\u003c/em\u003e\u003cem\u003e.011\u003c/em\u003e\u003cem\u003e\u0026lt; 0.05; H0 rejected\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe study reveals that a 5% increase in Liquidity results in a.206 unit decrease in bank performance, with a p-value less than.011, indicating a statistically significant effect at the 5% level.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eH4\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e_Npl\u0026nbsp;\u003c/em\u003e\u003cem\u003e_F: sig. value\u003c/em\u003e\u003cem\u003e.021\u003c/em\u003e\u003cem\u003e\u0026lt; 0.05; H0 rejected\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe positive coefficient of.090 indicates that an increase in Npl results in a.090 unit increase in bank performance, with a p-value less than.021 indicating statistical significance at the 5% level.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eH5\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e_Meetigns\u003c/em\u003e\u003cem\u003e_F: sig. value\u003c/em\u003e\u003cem\u003e\u0026nbsp;.531\u0026lt;\u0026nbsp;\u003c/em\u003e\u003cem\u003e0.05; H0 rejected\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe positive coefficient indicates that an increase in meetings leads to a.012 unit increase in bank performance, but the p-value is not statistically significant at the 5% level.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eH6\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e_Board size\u0026nbsp;\u003c/em\u003e\u003cem\u003e_F: sig. value\u0026nbsp;\u003c/em\u003e\u003cem\u003e.008\u003c/em\u003e\u003cem\u003e\u0026lt; 0.05; H0 rejected\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe study reveals that a 5% increase in board size results in a .147 unit decrease in bank performance, with a p-value less than.008, indicating statistical significance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eH7\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e_Dua\u0026nbsp;\u003c/em\u003e\u003cem\u003e_F: sig. value\u003c/em\u003e\u003cem\u003e\u0026nbsp;.011\u003c/em\u003e\u003cem\u003e\u0026lt; 0.05; H0 rejected\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe study reveals that a 5% increase in Dua results in a 5.51 unit decrease in bank performance, with a p-value less than.011, indicating a statistically significant effect at the 5% level.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eH8\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e_Ind\u003c/em\u003e\u003cem\u003e,_F: sig. value0.496\u0026gt; 0.05; H0 Accepted\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe negative coefficient indicates that a percentage point increase in the Ind results in a decrease in bank performance by 006 units, with a p-value greater than.496 indicating no statistical significance at the 5% level\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 620px;\"\u003e\n \u003cp\u003eModel Summary\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 56px;\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003eR Square\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003eAdjusted R Square\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003eStd. Error of the Estimate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003eChange Statistics\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003eR Square Change\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003eF Change\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.998\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e.984\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e.04921\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e79.787\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 620px;\"\u003e\n \u003cp\u003ea. Dependent Variable: ROE\u003c/p\u003e\n \u003cp\u003eb. Predictors: (Constant), H8_Ind, H6_Board size, H5_Meetigns, H3_Liquidity, H4_Npl, \u0026nbsp; \u0026nbsp; \u0026nbsp;H2_Capital Adequacy, H7_Dua, H1_Bank\u0026rsquo;s Size\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eModel summary\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026bull; R: shows that the R value was 0.998, which is high. This indicates the independent variables. ROA is significantly correlated with Independent variable.\u003c/p\u003e\n\u003cp\u003e\u0026bull; R square: in the model summary table, R Square is .997, meaning that independent variable can explain 99.7% of the variance, which is the standard for R square, and the remaining 1.3 % is influenced by elements that have not been explored. These variables were also analyzed.\u003c/p\u003e\n\u003cp\u003e\u0026bull; Adjusted R square: R-square was converted into an adjusted R-square. The modified R-squared value indicates that the addition of variables improves the regression model. To comprehend the adjusted R-squared value after rationalizing the inaccuracies, the adjusted number was 0.984, down from 0.997.\u003c/p\u003e\n\u003cp\u003e\u0026bull; Standard error of the estimation: the standard error of the estimate measures the Regression model prediction accuracy. The probability of the best fit increased with a lower standard error of the estimation. In this model summary, the estimated standard error was 0.04921\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"663\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 586px;\"\u003e\n \u003cp\u003eANOVA\u003csup\u003ea\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 145px;\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003eSum of Squares\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003edf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 99px;\"\u003e\n \u003cp\u003eMean Square\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003eSig.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eRegression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e1.546\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e.193\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e79.787\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.012\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eResidual\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e1.551\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 99px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" valign=\"top\" style=\"width: 586px;\"\u003e\n \u003col style=\"list-style-type: lower-alpha;\"\u003e\n \u003cli\u003eDependent Variable: ROE\u003c/li\u003e\n \u003cli\u003ePredictors: (Constant), H8_Ind, H6_Board size, H5_Meetigns, H3_Liquidity, \u0026nbsp;H4_Npl, H2_Capital Adequacy, H7_Dua, H1_Bank\u0026rsquo;s Size\u003c/li\u003e\n \u003c/ol\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe ANOVA Table indicates a significance level of 0.12, below 0.05. The null hypothesis was rejected; hence, the alternative hypothesis that independent factors could explain the dependent variable was accepted.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCoefficient\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe coefficient determines the independent relationship. By measuring the coefficients,\u003c/p\u003e\n\u003cp\u003ewe can determine the variables that significantly affect ROE.\u003c/p\u003e\n\u003cp\u003eThe significance level for H1_Bank\u0026rsquo;sSize is .012,H3_Liquidity is .013 ,H4_Npl is .019,H5_Meetigns is .002,H6_Board size is .006,H7_Dua is .048, and H8_Ind is .008 which is less than the alpha value of 0.05.H2_CapitalAdequacy is .460, which is not less than the alpha value of 0.05\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"663\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 586px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Coefficients \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" valign=\"bottom\" style=\"width: 205px;\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 193px;\"\u003e\n \u003cp\u003eUnstandardized Coefficients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003eStandardized Coefficients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003et\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"bottom\" style=\"width: 77px;\"\u003e\n \u003cp\u003eSig.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003eStd. Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003eBeta\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"9\" valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e(Constant)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e2.992\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e.233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e12.825\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eH1_Bank\u0026rsquo;s Size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e-.213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e-1.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e-8.904\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eH2_Capital Adequacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e-.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e.010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e-.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e-.908\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.460\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eH3_Liquidity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e-.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e-.484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e-8.662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eH4_Npl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e-.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e-.629\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e-7.234\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eH5_Meetigns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e-.099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e-1.087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e-20.734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eH6_Board size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e.125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e1.154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e13.323\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eH7_Dua\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e.503\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e.115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e.385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e4.375\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.048\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003eH8_Ind\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e-.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 111px;\"\u003e\n \u003cp\u003e-1.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e-10.917\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ea. Dependent Variable: ROE\u003c/p\u003e\n\u003cp\u003eb. Predictors: (Constant), H8_Ind, H6_Board size, H5_Meetigns, H3_Liquidity, H4_Npl, H2_Capital Adequacy, H7_Dua, H1_Bank\u0026rsquo;s Size\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe can include seven-factor variables because they reject the null hypothesis, thus proving our alternative hypothesis. On the other hand one variable accept null hypothesis. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStatistical interpretation:\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH1\u003c/strong\u003e_\u003cem\u003eBank\u0026rsquo;s Size\u003c/em\u003e\u003cem\u003e_F: sig. value\u0026nbsp;\u003c/em\u003e\u003cem\u003e.012\u0026nbsp;\u003c/em\u003e\u003cem\u003e\u0026lt; 0.05; H0 rejected\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe study reveals that increasing bank size results in a decrease in banking sector performance by.213 units, a statistically significant effect at the 5% level.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH2\u003c/strong\u003e_\u003cem\u003eCapital\u0026nbsp;\u003c/em\u003e\u003cem\u003eAdequacy\u003c/em\u003e\u003cem\u003e_F\u003c/em\u003e\u003cem\u003e: sig. value\u003c/em\u003e\u003cem\u003e\u0026nbsp;.460\u003c/em\u003e\u003cem\u003e\u0026gt; 0.05; H0 accepted\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe study indicates that a 0.009 percentage point increase in Capital Adequacy results in a decrease in bank performance, but this effect is not statistically significant at the 5% level.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH3\u003c/strong\u003e_\u003cem\u003eLiquidity\u003c/em\u003e\u003cem\u003e_F: sig. value\u0026nbsp;\u003c/em\u003e\u003cem\u003e.013\u003c/em\u003e\u003cem\u003e\u0026lt; 0.05; H0 rejected\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe negative coefficient indicates a statistically significant decrease in bank performance with every percentage point increase in liquidity, affecting all other variables. At 5% level p-value is significant effect on performance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH4\u003c/strong\u003e_\u003cem\u003eNpl\u0026nbsp;\u003c/em\u003e\u003cem\u003e_F: sig. value\u003c/em\u003e\u003cem\u003e.019\u003c/em\u003e\u003cem\u003e\u0026lt; 0.05; H0 rejected\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe study indicates that a 5% increase in Npl results in a.039 unit decrease in bank performance, indicating a statistically significant effect.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH5\u003c/strong\u003e\u003cem\u003e_Meetigns\u003c/em\u003e\u003cem\u003e_F: sig. value\u003c/em\u003e\u003cem\u003e\u0026nbsp;002\u0026lt;\u0026nbsp;\u003c/em\u003e\u003cem\u003e0.05; H0 rejected\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study reveals a significant decrease in bank performance with every percentage point increase in meetings, indicating a.099 unit decrease in performance at the 5% level.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH6\u003c/strong\u003e_\u003cem\u003eBoard size\u0026nbsp;\u003c/em\u003e\u003cem\u003e_F: sig. value\u0026nbsp;\u003c/em\u003e\u003cem\u003e.006\u003c/em\u003e\u003cem\u003e\u0026lt; 0.05; H0 rejected\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe study reveals that a.125 positive coefficient indicates a statistically significant increase in bank performance with every percentage point increase in board size.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH7\u003c/strong\u003e_\u003cem\u003eDua\u0026nbsp;\u003c/em\u003e\u003cem\u003e_F: sig. value\u003c/em\u003e\u003cem\u003e\u0026nbsp;.048\u003c/em\u003e\u003cem\u003e\u0026lt; 0.05; H0 rejected\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe study reveals a significant positive correlation between the Dua percentage and bank performance, with a p-value less than.048 at the 5% level.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eH8\u003c/strong\u003e_\u003cem\u003eInd\u003c/em\u003e\u003cem\u003e,_F: sig. value0.008\u0026lt; 0.05; H0 rejected\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe negative coefficient indicates a statistically significant decrease in bank performance with every percentage point increase in the Ind, indicating a decrease in performance.\u003c/p\u003e"},{"header":"Author’s findings","content":"\u003cp\u003eDuring\u0026nbsp;research\u0026nbsp;work,\u0026nbsp;we\u0026nbsp;have\u0026nbsp;found\u0026nbsp;the\u0026nbsp;followings:\u003c/p\u003e\n\u003cp\u003eBank size, liquidity, and capital adequacy ratio (CA) are key factors affecting the success of the banking industry in Bangladesh. Bank size has a negative relationship with dependent variables, such as ROA and ROE, suggesting that the size of the bank affects the success of the backing industry. Liquidity is positively linked to ROE and ROA, and banks should be cautious when raising loans, as it can decrease profitability. The capital adequacy ratio has a positive effect on the output of Bangladeshi banks, indicating that lower profitability is expected due to a higher CA. Non-performing loans negatively affect Bangladesh\u0026apos;s banking efficiency, and board meetings have negative relationships with dependent and independent variables. Duality also has a negative relation with dependent variables, indicating that these factors negatively affect the banking sector performance in Bangladesh. That implies that the size of the bank did effect on the success of the backing industry in Bangladesh. We learned from the theoretical portion that liquidity is positively linked to both ROE and ROA. Bangladeshi banks should be very careful to raise the amount of loans in the even to a bad performance, since it brings in a decrease in profitability. This is because Bangladeshi banks have suffered large losses from rising rates of non-performing loans. Banks currently have a lot of capital, but little incentive to use their assets. One of the bank-specific variables affecting the level of bank profitability is CA. In both cases, we find good capital adequacy ratio outcomes according to the findings of panel and multiple regression analysis. The capital adequacy ratio has a positive effect on the output of Bangladeshi banks because of the positive outcome, which is statistically important, contrary to predictions. The finding indicates that lower profitability is caused or expected by a higher capital ratio. We observed from the empirical portion that in research methods panel regression, the non-performing loan negative relationship between dependent variables and independent variables was observed. That means a non-performing loan that affects Bangladesh\u0026rsquo;s banking efficiency. Negative relationships between dependent and independent variables occur in the case of a board meeting. In Bangladesh, there are several banks that have not scheduled more than 15 meetings in a few years. In case of Duality, there is a negative relation between dependent variables. That means duality did affect the banking sector performance of Bangladesh. Moreover, from our above investigation we have found that bank size, non-performing loan, board size, board meeting, duality and independent variables has a negative relation with dependent variables ROA and ROE. That means those variables had a detrimental impact on the performance of the banking industry in Bangladesh during the COVID pandemic.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eTo conclude, The COVID-19 epidemic may be one of the most perplexing difficulties facing the banking industry in recent history. Financial institution stability is a boost to a country\u0026apos;s economic growth and development. Bangladesh\u0026apos;s financial institutions have previously encountered a number of challenges, including a high rate of non-performing loans, a less structured market, and regulatory deficiencies. We discovered a meaningful and consistent outcome: the pandemic epidemic has a negative impact on the financial industry. It reduced income and raised costs, and the bank lost assets versus obligations. We also observed that the impacts of the COVID-19 epidemic on the financial health of government banks differed from those of private banks in terms of technical efficiency, with private banks handling the pandemic with greater effectiveness than state banking sectors. This report analyzes the impact of bank-specific characteristics, governance, determinants, and economic conditions on banking efficiency in Bangladesh during pandemics. It found that management cost decisions, such as cost to income ratio, non-performing loan ratio, board size, and board meeting, negatively affect bank success. Bank scale, capital adequacy ratio, independent directors, and growth rate of profit have no significant impact on efficiency. Corporate governance, which aims for effective, entrepreneurial, and responsible management, is also gaining interest among policymakers.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study received no funding, grants, or other support during or before the preparation of this manuscript from any 3rd party, agency, or institute.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthor Contribution\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe \u0026nbsp;author \u0026nbsp; participated \u0026nbsp;in \u0026nbsp;the \u0026nbsp; development \u0026nbsp;of \u0026nbsp;the \u0026nbsp; study \u0026nbsp;design, \u0026nbsp;data \u0026nbsp; analysis, and implementation phases. All writers granted their approval upon reviewing the final product.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1. \u003cstrong\u003eMd Ibrahim khalid\u003c/strong\u003e\u0026shy;- The process of conceptualization includes data creation, formal evaluation, literature review writing, methodology, resources, supervision, visualization, original draft writing, review, and editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e2. \u003cstrong\u003eTanvir Ahmed\u003c/strong\u003e \u003cstrong\u003eTuhin\u003c/strong\u003e- Data organizing, supervision, investigation, research, project management, original draft writing, and review. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgments\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank\u0026nbsp;Dr. Md. Rashidul Islam, Associate Professor\u0026nbsp;Department of Business Administration of East West University\u0026nbsp;for his tireless assistance made our research paper complete.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eA statement of conflicting interests\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors assert that none of the work presented in this study was influenced by any recognized competing financial interests or personal relationships.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eHossain, M. T. (2018). The Trend Of Default Loans In Bangladesh: Way Forward And Challenges. International Journal Of Research In Business Studies And Management, 24-30.\u003c/li\u003e\n \u003cli\u003eFE REPORT. (2020, January 02). Banks\u0026rsquo; rural branches rise to 10,467. Retrieved from Financial Express:https://thefinancialexpress.com.bd/Economy/Banks-Rural-Branches-Rise-To-10467-1577939972\u003c/li\u003e\n \u003cli\u003eKumar, D., Z;, Hossain, \u0026amp; Islam, S. (2020). Non-Performing Loans In Banking Sector Of Bangladesh: An Evaluation. International Journal Of Applied Economics, 22\u0026ndash;29.\u003c/li\u003e\n \u003cli\u003eMurtaza. (2020, Octobar 06). 12 Banks Suffer Tk 17,658cr Capital Shortfall Till Sept-End. Retrieved from New Age Bangladesh: https://www.newagebd.net/Article/95707/12-Banks\u003c/li\u003e\n \u003cli\u003ePaul, T. C. (2020, June 19).COVID-19 and its impact on Bangladesh economy. Retrieved from The Financial Express: https://thefinancialexpress.com.bd/Views/Covid-19-And-Its-Impact-On-Bangladesh-Economy- 1592580397\u003c/li\u003e\n \u003cli\u003eShamim, S. (2019, Octobar 24). FDI up marginally in 2016. 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Journal of banking \u0026amp; finance, 32(12), 2570-2580\u003c/li\u003e\n \u003cli\u003eTrujillo‐Ponce, A. (2013). What determines the profitability of banks? Evidence from Spain. Accounting \u0026amp; Finance, 53(2), 561-586.\u003c/li\u003e\n \u003cli\u003eStaikouras, P. K., Staikouras, C. K., \u0026amp; Agoraki, M. E. K. (2007). The effect of board size and composition on European bank performance. European Journal of Law and Economics, 23(1), 1- 27.\u003c/li\u003e\n \u003cli\u003eAkhtar, M. F., Ali, K., \u0026amp; Sadaqat, S. (2011). Liquidity risk management: a comparative study between conventional and Islamic banks of Pakistan. Interdisciplinary journal of research in business, 1(1), 35-44.\u003c/li\u003e\n \u003cli\u003eSufian, F., \u0026amp; Habibullah, M. S. (2009). Bank specific and macroeconomic determinants of bank profitability: Empirical evidence from the China banking sector. Frontiers of Economics in China, 4(2), 274-291.\u003c/li\u003e\n \u003cli\u003eAkhtar, M. F., Ali, K., \u0026amp; Sadaqat, S. (2011). Factors influencing the profitability of Islamic banks of Pakistan. International Research Journal of Finance and Economics, 66(66), 1-8\u003c/li\u003e\n \u003cli\u003eMacit, F. (2012). Bank specific and macroeconomic determinants of profitability: Evidence from participation banks in Turkey. . Economics bulletin, 32(1), 586-595.\u003c/li\u003e\n \u003cli\u003eMahmud, Z. U. (2020). (2021, November 29). The Impact Of Covid-19 In Banking Sector Of Bangladesh. The Daily Observer. Retrieved from www.observerbd.com:https://www.observerbd.com/cat.php?cd=186\u003c/li\u003e\n \u003cli\u003eBabu, M. U. (2020, April 17). Banking sector the biggest risk to Bangladesh economy: Survey. Retrieved from THE BUSINESS STANDERD: https://www.tbsnews.net/economy/banking/banking-sector-biggest-risk-bangladesh-economy-survey-45535\u003c/li\u003e\n \u003cli\u003eHasan, M. (2020, July 01). First half of 2020: Operating profits of most commercial banks dip. Retrieved from Dhaka Tribiune: https://www.dhakatribune.com/business/banks/2020/07/01/first-half-of-2020- operating-profits-of-most-commercial-banks-dip\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6343886/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6343886/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study investigates how corporate governance affected the performance of private and state-owned banks in Bangladesh during the COVID-19 epidemic. Using a multiple linear regression technique, the study examines how governance structures and financial performance metrics were influenced. The study evaluates eleven banks from 2019 to 2020, using key variables such as Return on Assets (ROA) and Return on Equity (ROE) as dependent variables, and independent variables such as bank size, capital adequacy ratio, liquidity ratio, non-performing loans ratio, board size, board meetings, CEO duality, and independent directors. The findings reveal substantial relationships between corporate governance practices and banking performance, providing insight into the usefulness of governance frameworks in navigating economic upheavals. The study uses quantitative research approaches to identify the primary drivers of banking efficiency and its implications for financial stability. The study adds to our understanding of corporate governance's role in performance assessment and makes recommendations for enhancing governance frameworks in the banking industry. Despite of restrictions such as data accessibility and confidentiality, the study provides useful information about the link between governance and financial success in Bangladesh's banking system.\u003c/p\u003e","manuscriptTitle":"Banking under catastrophic crisis on corporate governance and performance in Bangladeshi Private and State-Owned Banks during COVID-19 pandemic: Insights from a multiple linear regression analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-01 04:30:36","doi":"10.21203/rs.3.rs-6343886/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9d552834-f6b8-4025-9a2e-3ebc0f0a224b","owner":[],"postedDate":"April 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-05T08:23:23+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-01 04:30:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6343886","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6343886","identity":"rs-6343886","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}