Research Article: 2022 Vol: 26 Issue: 5
Sayed Abbas Ahmed, Ajman University
Citation Information: Ahmed, S.A. (2022). Corporate governance and firm performance in the emerging market: a case study of deposit-taking institutions in the uae. Academy of Accounting and Financial Studies Journal, 26(5), 1-10.
Scholars in the field of Accounting and Finance have provided a controversial result with respect to the relationship between corporate governance and firm performance. An emphasis of scholars has been placed on developed rather than emerging and developing economies. In addressing the debatable issue of this relationship, the study is intended to investigate the relationship between corporate governance mechanism and profitability performance of banks, operating in the competitive financial market of the gulf region. The corporate governance was derived from the operational nature of banks. Profitability performance was measured by ROTA, ROE and the PM. Nine banks out of the population of 21 national banks have been selected as a research sample for the period 2010-2019 (post-era of the International Financial Crisis of 2008 and pre-pandemic COVID-19 crisis). The data has been analysed through the use of E-views software. The findings reveal strong relationship between lending capacity and optimal allocation of resources and profitability. This impliedly gives connotation to other variables which influence lending capacity. The results may help banks management understand the influence of corporate governance on operational performance of banks.
CG, Banks, Emerging.
The United Arab Emirates' economy is considered as the second largest economy within the GCC after Saudi Arabia. The country`s GDP was 1.50 trillion AED with annual growth of 4.5% and per capital income of $58466 in 2020. Diversity is one of the efficient strategies that the UAE applied in its economy. In this regard, the UAE has managed to build a strong basis for a thriving economy, attracting a considerable number of entrepreneurs and investors from across the world who have viewed the UAE as a good launch pad for business growth and success. More importantly, and significantly, the UAE has been witnessing an outstanding banking growth in the financial sector. There are 21 national banks and 28 foreign banks in the UAE. It should be noted that the merger between the First Gulf Bank (FGB) and National Bank of Dubai (NBAD) has been viewed as one of the most successful accomplishments in the banking sector in the MENA, having created the biggest bank in the entire region (Bhunia & Khan, 2011).
The banking system in the UAE could be described as hypercompetitive in the debt-oriented community. Within this context, the banking sector has faced higher Non-Performing Loans (NPLs) averaging 5.1 present. The banks incorporated in Dubai and Abu Dhabi possess more than 90% of the total assets and the other five emirates share the remaining 10%.
Based on the Goldsmith equation on the Banking Density Ratio (BDR); the banking sector in the UAE shows a positive deviation of 16%. With respect to banking technology, during the year 2017, the number of ATM devices was 5243, reaching 5293 in 2018. In line with the Patel Model of BDR, the UAE banking sector is beyond 3.37 BDR. We could observe that the largest bank (NBD) is one with the good numbers of ATMs spreading across the emirates (Natalya, 2014).
Corporate governance is introduced in the UAE for companies and banks listed in the capital market. The corporate governance rules in the UAE were issued in 2016 by the Securities Commodities Authority of the UAE. On July 2019, corporate governance guidelines and rules were launched to optimize corporate governance policies for banks. The central bank has a clear goal which is to look after advancing the proficient turn of events and working of the financial framework of banking system in the UAE. Accordingly, banks are needed to have a far-reaching way to deal with corporate administrative to guarantee the banks flexibility and upgrade in general monetary steadiness (Ng'ang'a, 2013).
It is well documented in the body of knowledge that bank model is built around the exploitation of the financial safety compared to non-financial firms. Thus, good corporate governance is associated with more bank risk taking. This has special meaning to the UAE economy, under rapid economic expansion, following the era of the international financial crisis of 2008-2009. The study examines the relationship between the corporate governance as operationalised into a number of operational variables and the profitability performance of banks. The study is structured around three interrelated questions; Does corporate governance have an influence on profitability of banks?; Is there a relationship between good corporate governance as measured into low non-performing loans, significance of deposits, the volume of lending`s capacity and operational profitability of banks?; How does corporate governance as exemplified into board structure, Banking Density Ratio (BDR) and operational costs affect the efficiency of banks in the emerging economy?.
Many scandals and numerous cases of corporate governance malpractice brought about more attention to corporate governance issue in the financial sector. The study is responding to establish a relationship between strategic and operational mechanisms of corporate governance and operational profitability of banks regardless of size and nature (Pushner, 1995).
Corporate governance is known to be a mechanism used to enhance the performance of firms. Ahmadu et al. (2005) argued that: Corporate governance refers to a set of mechanisms that influence the decisions made by managers when there is a separation of ownership and control. Corporate governance issue has gained significant attention in management research especially among listed firms in developed economy. However, less attention has been given to corporate governance and financial performance with respect to developing countries and emerging capital market (Peni & Vähämaa, 2012).
The importance of corporate governance lies in the regulations it imposes on business. A number of studies have shown that the mechanisms of corporate governance may have influence on a firm`s performance (Abubakar, 2015), where factors such as planning behavior, management set-up, decision making process and internal control are playing a huge role in the enhancement of the performance of firms. A study conducted by Al?Tamimi (2012), examined the impact of segregation between control and ownership on performance of the UAE- based economic activities. The study reached a conclusion that owner-controlled firms performed significantly better than management -controlled firms in the UAE.
Beltratti & Stulz (2009), examined the impact of internal control as exemplified into structure of board of directors, independence of the board, board leadership and institutional investors, on ROTA and ROE. The study concluded that there was a positive relation between the independence of the board and firm performance, and a negative relationship both board size and institutional investors on a firm`s performance (Gweyi & Karanja, 2014).
It was established in the body of knowledge that banks are an essential part in any economy. Thus, the corporate governance of the capital providers will not be taken from narrow perspectives. Many research works were conducted on corporate governance of banks but failed to capture the impact of operational corporate governance on bank`s performance. This marks the scope of the paper as compared to the previous research works on relationship between corporate governance and firm performance.
An empirical study conducted by scholars Berger & Di Patti (2006) reached a conclusion that there was a relationship between share price to book ratio, gearing ratio, ROTA, agency cost, board size and market capitalization and corporate governance of the banking sector. This school of thoughts received the support of a number of scholars (Brunnermeier & Krishnamurthy, 2014) who viewed the corporate governance in broader perspective.
In examining the impact of corporate governance on bank performance in Ethiopia, Caprio & Levine (2002) and based on regression analysis have examined the effect of capital adequacy, board size, bank size as proxied by the total assets, loans to deposits ratio and ownership as proxies for corporate governance. Fosu (2013) studied the effect of corporate governance on the performance of the Nigerian banking sector. A positive correlation was observed between the level of corporate governance and ROE which is the proxy for performance. The operational aspects of the banks have been taken as a proxy for good corporate governance. Feroz et al. (2008) found a negative correlation between the size of the board and financial performance of the bank in the emerging market, (Ibrahim, 2011) examined corporate governance and financial performance of banks (Keay & Loughrey, 2015). They found a positive correlation between operational corporate governance mechanisms as exemplified into total financial resources, loans to deposits ratio, financing pattern and operational performance of banks operating in the emerging financial market (Macey & O'hara, 2003). Friend & Lang (1988) examined the relationship between corporate governance and profitability of Islamic banks in Pakistan. The Author was adopting the narrow approach in operationalizing corporate governance. This Study is built around broad approach in operationalizing corporate governance and financial performance of banks (McKinnon, 2009). The adherence to the broad approach is important for a number of reasons. First, banks are well regulated and operating in a competitive and expansionary money market. The narrow approach will not be able to explain the relationship between corporate governance and bank`s performance. In the UAE, banks began the process of consolidation and restructuring as a growth strategy in connection with massive banking technology investment and expansion (BDR), Thus, the innovative operational services, financial resources, credit-scoring mechanisms, probably affected the performance rather than the board size. In this connection a number of scholars found a positive relationship between Financial Leverage (FL) and financial performance of banks. Amongst those scholars are (Akhtar et al., 2012). With respect to financial performance, there is general consent. Amongst scholars (Bhaumik & Dimova, 2004; Ojo, 2012; Rehman, 2013; Fungacova et al., 2016), that the bank performance could better be measured by profitability, degree of resources utilization, financial leverage and liquidity.
Based on critical review of the relevant literature, we developed a number of hypotheses that we have intention to test:
H1: There is a relationship between good corporate governance and firm performance.
H2: The high significance of deposits is an indication of good corporate governance and has a positive impact on bank financial performance.
H3: The operational expenses, banking density ratio and lending capacity have an effect on ROTA, ROE and PM.
The purpose of the study is to establish relationship between corporate governance mechanisms and bank`s performance in the UAE. The total number of banks in the country was 49 banks in 2019 with 21 of them being national banks and 28 international foreign banks. To ensure the accuracy of the results, 90 annual reports were collected for 9 banks of different nature, covering the period between 2010-2019. The research sample is stratified into 3 Islamic banks and 6 Conventional banks. The chosen banks varied in terms of the number of branches, with the National Bank of Fujairah having the lowest number of branches and the Emirates NBD having the highest number of branches. The collected data has been classified as cross-sectional data and the analysis is conducted using the E-views software to test the variables (Fukao, 2022).
In examining the impact of corporate governance on the financial performance, ROE, ROTA and PM have been taken as dependent variables. With respect to corporate governance, a number of independent variables have been considered; operating expenses to Revenue, Bank Density Ratio (BDR), significance of deposit, Assets Turnover (ATO), Financial Resources (FR), Equity Multiplier (EQM), Lending Capacity (LC), and board structure. This represents the uniqueness of this piece of work as the study build a relationship between operating corporate governance in broad scope and firm performance (Hassan & Halbouni, 2013) Table 1.
In the previous part, we classified and identified both the independent and dependent variables used in the analysis process to examine the relationship between each of the variables (Ibrahim et al., 2010). As documented in the body of knowledge, the association between corporate governance and firm performance remains a puzzling question. Based on the identified variables and the statistical model, the analysis attempts to give an explanation to the relationship between corporate governance mechanisms and firm performance as stated and expressed clearly in the research hypotheses. The financial performance has been operationalized into ROTA, ROE and PM (Ibrahim, 2015).
Table 1 shows the relationship between each of the dependent variables, namely, PM, ROTA and ROE, and the independent variables that were selected for the purpose of the study.
| Table 1 Correlation Analysis |
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|---|---|---|---|---|---|---|---|---|---|---|---|
| PM | ROTA | ROE | Significance Deposits | Op. Exp. | LC | FR | EQM | Fin & Board | BDR | ATO | |
| To Rev | |||||||||||
| PM | 1 | ||||||||||
| ROTA | 0.57947 | 1 | |||||||||
| ROE | 0.34639 | 0.49039 | 1 | ||||||||
| Significance Deposits | 0.07917 | 0.15449 | -0.00067 | 1 | |||||||
| Op. Exp. | 0.05979 | -0.01591 | -0.10067 | 0.06618 | 1 | ||||||
| To Rev | |||||||||||
| LC | 0.18131 | -0.08954 | -0.02641 | 0.36914 | -0.0046 | 1 | |||||
| FR | 0.37 | -0.06274 | 0.09327 | 0.2541 | 0.05703 | 0.6532 | 1 | ||||
| EQM | 0.02286 | -0.05064 | 0.24194 | -0.09087 | 0.13027 | -0.062 | 0.02899 | 1 | |||
| Fin & Board | 0.29229 | 0.020656 | 0.06356 | 0.49551 | 0.046 | 0.3828 | 0.78674 | -0.0473 | 1 | ||
| BDR | -0.05944 | 0.019177 | -0.07723 | 0.49524 | -0.0137 | 0.2266 | 0.10764 | -0.2017 | 0.29063 | 1 | |
| ATO | -0.00384 | 0.050231 | -0.12675 | 0.71365 | 0.11797 | 0.5897 | 0.36874 | -0.182 | 0.57224 | 0.5396 | 1 |
The first observation from this table is that all 3 dependent variables have a weak relationship correlation with all 8 independent variables.
The dependent variables PM has a positive relationship with each independent variable: Significance of Deposits, Operating Expenses to Revenue ratio, Lending Capacity, Financial Resources, Equity Multiplier, Financing and board structure. On the contrary, Assets Turnover and Bank Density Ratio have a negative relationship with PM.
The Dependent Variable ROTA has a positive relationship with the following independent variables: Significance of Deposits, Financing and board structure, Bank Density Ratio and Assets Turnover. On the other hand, the rest of the independent variables, namely, Operating Expenses to revenue, Lending Capacity, Financial Resources and Equity Multiplier have a negative relationship with ROTA.
The Dependent Variables ROE has a positive relationship with the following dependent variables: Financial Resources, Equity Multiplier, Financing and board structure. We also detected the existence of a negative relationship between ROE on the one hand and Lending Capacity, Bank Density Ratio, Assets Turnover, Operating Expenses to Revenue, and Significance Deposits on the other hand.
Descriptive Analysis
Table 2 reflects the descriptive analysis for both independent and dependent variables. In regard to the mean for the dependent variables, the value for ROTA is 0.018; ROE is 0.123 and PM is 0.376. The second Deviation value for ROTA is 0.008; ROE is 0.042, and PM is 0.117. The maximum and minimum values for the dependent variables are as following, ROTA Max 0.056 and Min. 0.002; ROE with a Max. of 0.269 and a Min of 0.019; PM with a Max. of 0.610 and a Min. of 0.078.
| Table 2 Descriptive Analysis |
||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Opexp | Bdr | Bdr | Bdr | Ato | Fr | Equity Multiplier | Lc | Finboard | Pm | Rota | Roe | |
| Mean | 0.3867 | 0.107 | 0.1072 | 0.1072 | 0.05916 | 1.2924E+11 | 7.02727 | 7.5189E+10 | 97099903200 | 0.37662 | 0.01829 | 0.123 |
| Median | 0.367 | 0.092 | 0.0919 | 0.0919 | 0.04332 | 8.9823E+10 | 7.12489 | 4.22E+10 | 60949792500 | 0.36518 | 0.01612 | 0.126 |
| Maximum | 0.5703 | 0.233 | 0.2329 | 0.2329 | 1.03099 | 6.0171E+11 | 9.27885 | 3.5284E+11 | 5.00369E+11 | 0.61009 | 0.05629 | 0.27 |
| Minimum | 0.2545 | 0.026 | 0.0256 | 0.0256 | 0.02805 | 1.2917E+10 | 3.83258 | 71921000 | 9395056000 | 0.07813 | 0.00219 | 0.02 |
| Std.Dev | 0.0755 | 0.06 | 0.0601 | 0.0601 | 0.10519 | 1.2046E+11 | 1.21882 | 7.6878E+10 | 96255396000 | 0.11687 | 0.00863 | 0.042 |
| Skewness | 0.7974 | 0.461 | 0.4609 | 0.4609 | 8.91112 | 1.64598 | -0.5638 | 1.35653 | 1.70534 | -0.1287 | 2.35898 | 0.907 |
| Kurtosis | 2.6947 | 1.849 | 1.8489 | 1.8489 | 82.78458 | 5.54181 | 2.91816 | 4.27025 | 5.89271 | 2.60665 | 9.86744 | 5.096 |
| Jarque-Bera | 9.8859 | 8.156 | 8.1557 | 8.1557 | 25062.04 | 64.86656 | 4.79349 | 33.65346 | 75.00198 | 0.82849 | 260.328 | 28.82 |
| Profitability | 0.0071 | 0.017 | 0.0169 | 0.0169 | 0 | 0 | 0.09101 | 0 | 0 | 0.66084 | 0 | 1E-05 |
| Sum | 34.801 | 9.647 | 9.6474 | 9.6474 | 5.32407 | 1.1632E+13 | 632.454 | 6.7668E+11 | 8.73899E+12 | 33.8959 | 1.6467 | 11.09 |
| Sum Sq. Dev | 0.5074 | 0.321 | 0.3214 | 0.3214 | 0.98477 | 1.29144 | 132.211 | 5.26015 | 8.24594 | 1.21567 | 0.00662 | 0.158 |
| Observation | 90 | 90 | 90 | 90 | 90 | 90 | 90 | 90 | 90 | 90 | 90 | 90 |
Regression Analysis
| Table 3 Regression Analysis For Rota |
||||
|---|---|---|---|---|
| Variables | Coefficient | Std. Error | t-Statistic | Prob. |
| C | -0.022148 | 0.009739 | -2.274123 | 0.0259 |
| OP_EXP_TO_REV | 0.007825 | 0.006724 | 1.163775 | 0.2484 |
| LC | 0.000782 | 0.000346 | 2.260476 | 0.0268 |
| DSIGNDEPOSITS | 0.009513 | 0.012656 | 0.751631 | 0.4547 |
| DFR | 0.00101 | 0.005128 | 0.196884 | 0.8445 |
| DEIN | 0.002534 | 0.006569 | 0.385831 | 0.7008 |
| DEQUITYMULTI | -0.002206 | 0.000686 | -3.214355 | 0.002 |
| DBDR | -0.000304 | 0/044953 | -0.006759 | 0.9946 |
| DATO | -0.00826 | 0.005814 | -1.420711 | 0.1597 |
| ROOT MSE | 0.003763 | R-squared | 0.190085 | |
| Mean dependent var | 0.000216 | Adjusted R-squared | 0.100094 | |
| S.D dependent var | 0.004207 | S.E of regression | 0.003991 | |
| Akaike info criterion | -8.104971 | Sum s squared resid | 0.001147 | |
| Schwarz criterion | -7.838922 | Log likelihood | 337.2513 | |
| Hannan-Quinn criter | 1.833938 | F-statistic | 2.112273 | |
| Durbin-Watson stat | Prob (F-statistic) | 0.045429 | ||
Testing Hypothesis 1
Table 3 represent the regression analysis results for ROTA, which represents the first dependent variable in the relation to the surrogate measurements of Corporate Governance. It also tests the validity of the first hypothesis and whether it is accepted or rejected. The hypothesis is about examining the existence of a relationship between ROTA, ROE and PM that represent the dependent variables for the banking performance on the one hand, and good corporate governance on the other.
The answer to determining whether this hypothesis is accepted is based on the probability of F-Statistics for all three dependent variables. And according to the F-Statistics probabilities of the analysis given, i.e o.045 for ROTA; 0.33 for ROE, and 0.45 for PM, we reached the conclusion that the first hypothesis is indeed accepted and that there is an obvious and strong relationship between Corporate Governance mechanisms and bank performance for the banking sector in the UAE based on F-Statistics (probability) on ROTA, while the regression analysis F-Statistics results of ROE and PM showed a weak relationship with the performance based on probability. We found that by looking at the R-squared values for ROTA, ROE and PM measure the percentage of the impact by the selected independent variables in this study. R-squared value for ROTA is 19%, ROE is 11.4% and PM is 10.2%, the remaining of 100% of each of the dependent variables are affected by the other independent variables. (THIS BIT NEEDS TO BE PRESENTED MORE CLEARLY)
Testing Hypothesis 2
Table 4 illustrates the relationship between ROE, which is the second dependent variable, and all the 8 independent variables related to the Corporate Governance. It also concludes if the second hypothesis is accepted or rejected. This hypothesis requires us to test if the significance deposits that represent one of the independent variables has an impact on the bank performance. We tested this hypothesis by checking the probability for this variable for all three dependent variables, concluding that if the probability is lower than 0.05 it is accepted, and if it is higher than that, it is rejected. The results of the probability of the Significance deposits are 0.454 for ROTA, 0.300 for ROE and 0.467 for PM. This means that our second hypothesis for this study is rejected and that there is a weak or no relationship between the significance deposits and the banking performance of banks in the emerging market.
| Table 4 Regression Analysis For Roe |
||||
|---|---|---|---|---|
| Variables | Coefficient | Std. Error | t-Statistic | Prob. |
| C | -0.139524 | 0.060626 | -2.301399 | 0.0243 |
| OP_EXP_TO_REV | 0.0.39314 | 0.041854 | 0.939304 | 0.3507 |
| LC | 0.005213 | 0.002154 | 2.420536 | 0.018 |
| DSIGNDEPOSITS | -0.082144 | 0.078784 | 1.042647 | 0.3006 |
| DFR | 0.004437 | 0.031925 | 0.138971 | 0.8899 |
| DEIN | -0.005306 | 0.040889 | -0.129776 | 0.8971 |
| DEQUITYMULTI | 0.005387 | 0.004272 | 1.260951 | 0.2114 |
| DBDR | 0.131515 | 0.279832 | 0.469978 | 0.6398 |
| DATO | -0.060266 | 0.036192 | -1.665181 | 0.1002 |
| ROOT MSE | 0.023425 | R-squared | 0.114139 | |
| Mean dependent var | 0.002022 | Adjusted R-squared | 0.01571 | |
| S.D dependent var | 0.025043 | S.E of regression | 0.024846 | |
| Akaike info criterion | -4.447821 | Sum s squared resid | 189.1367 | |
| Schwarz criterion | -4.181771 | Log likelihood | 1.159612 | |
| Hannan-Quinn criter | -4.341078 | F-statistic | 0.335429 | |
| Durbin-Watson stat | 1.788414 | Prob (F-statistic) | ||
Testing Hypothesis 3
Table 5 illustrates different probabilities that define the relationship between the third and final dependent variable representing Return on Equity (ROE). It tests this variable`s relationship with all 8 independent variables that are related to corporate governance. The results of the analysis will help us accept or reject the third hypothesis. The third hypothesis requires us to test the relationship between the operating expenses to revenue, Bank Density Ratio and Lending capacity. To test our hypothesis, we need to check the probabilities for each of these variables that determine their relationship with banking performance for the UAE banking sector. Listed below are the probabilities for each of the variables:
| Table 5 Regression Analysis For Pm |
||||
|---|---|---|---|---|
| Variables | Coefficient | Std. Error | t-Statistic | Prob. |
| C | -0.359184 | 0.207302 | -1.732665 | 0.0874 |
| OP_EXP_TO_REV | 0.160961 | 0.143115 | 1.124695 | 0.2645 |
| LC | 0.012343 | 0.007364 | 1.67607 | 0.0981 |
| DSIGNDEPOSITS | 0.196703 | 0.269392 | 0.730174 | 0.4677 |
| DFR | 0.145141 | 0.109162 | 1.329587 | 0.1879 |
| DEIN | -0.087655 | 0.139816 | -0.626928 | 0.5327 |
| DEQUITYMULTI | -0.021098 | 0.014607 | -1.444361 | 0.153 |
| DBDR | 0.232622 | 0.956865 | 0.243113 | 0.8086 |
| DATO | -0.174249 | 0.123754 | -1.408031 | 0.1634 |
| ROOT MSE | 0.080098 | R-squared | 0.102226 | |
| Mean dependent var | 0.007207 | Adjusted R-squared | 0.002474 | |
| S.D dependent var | 0.085062 | S.E of regression | 0.084957 | |
| Akaike info criterion | -1.988904 | Sum s squared resid | 0.519674 | |
| Schwarz criterion | -1.722854 | Log likelihood | 89.5506 | |
| Hannan-Quinn criter | -1.882161 | F-statistic | 1.024798 | |
| Durbin-Watson stat | 1.921118 | Prob (F-statistic) | 0.42557 | |
1) Operating Expenses has a probability of 0.248 with ROTA; 0.351 with ROE; and 0.265 with PM.
2) Bank Density Ratio has a probability of 0.995 with ROTA; 0.639 with ROE; and 0.801 with PM.
3) Lending Capacity has a probability of 0.027 with ROTA; 0.018 with ROE; and 0.098 with PM.
After stating the probabilities, we conclude that ROTA, ROE and PM have no relationship with Operating Expenses to Revenue and Banking Density Ratio but has a strong relationship with Lending Capacity.
The central objective of the study was to conduct an explanatory work on the impact of operational corporate governance mechanisms on the financial performance of the UAE.
Banking sector between 2010 and 2019. This signifies the uniqueness of the study as taking corporate governance in the operational perspective of the most regulated economic sector after the international economic crises and pre-COVID -19 pandemic crisis.
Nine banks with different characteristics were selected. Based on the identified dependent and independent variables, we detected from the regression analysis strong relationship between dependent and independent variables, as a sum as expressed by f-statistics probability. The results validate one of the hypotheses. Taking each variable separately the data provided evidence that not all independent variables share a strong relationship with ROTA, ROE and PM. Hence, we could conclude that all independent variables except Lending Capacity (LC) had a weak or no relationship with the dependent variables.
The study documents the impact of operational corporate governance on the financial performance of banks. The paper provides evidence that better corporate governance contributes to bank profitability (ROTA) and equity multiplier. This calls for more valid measures to be taken by commercial banks to strengthen its operational corporate governance mechanisms and particularly the significance of deposits, credit scoring, optimal balance between banking technology and geographical distribution of banks` branches within the context of corporate governance.
The study provides evidence that most of the board members are traders and investors. This calls for policy recommendations to consider inclusion of professional people in the board structure. This will mitigate the gap between the executive body and the policy- making board.
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Received: 19-Apr-2022, Manuscript No. AAFSJ-22-11799; Editor assigned: 21-Apr-2022, PreQC No. AAFSJ-22-11799(PQ); Reviewed: 05-May-2022, QC No. AAFSJ-22-11799; Revised: 09-June-2022, Manuscript No. AAFSJ-22-11799(R); Published: 16-June-2022