




































Asian Finance & Banking Review 

 Vol. 6, No. 1; 2022 

                                       ISSN 2576-1161   E-ISSN 2576-1188 

Published by CRIBFB, USA 

 

1 

GENDER DIVERSITY ON BOARD AND ITS RELEVANCE TO 

FIRM PERFORMANCE: A STUDY ON PHARMACEUTICAL 

INDUSTRY OF BANGLADESH 

 

 

Hossain Ahmmed Fahad 

Post-Graduate 

Faculty of Business Studies 

University of Dhaka, Dhaka, Bangladesh 

E-mail: Fahadhossain.frg@gmail.com 

https://orcid.org/0000-0002-1004-8660 

 

Imran Mahmud 

Post-Graduate 

Faculty of Business Studies 

University of Dhaka, Dhaka, Bangladesh 

E-mail: Imran.mahmud.du@gmail.com 

https://orcid.org/0000-0002-9255-462X 

 

Atkia Nabiha Rahman 

Post-Graduate 

Faculty of Business Studies 

University of Dhaka, Dhaka, Bangladesh 

E-mail: A.nabiharahman@gmail.com 

https://orcid.org/0000-0002-9961-164X 

 

 
Received: September 23, 2021        Accepted: November 12, 2021      Online Published: January 01, 2022 

 

DOI: 10.46281/asfbr.v6i1.1520                                URL: https://doi.org/10.46281/asfbr.v6i1.1520 

 

 

ABSTRACT 

The study tries to examine the relationship between gender diversity on the Board and firms' 

profitability in Bangladesh's Pharmaceutical industry. The study employs a panel data approach 

with all the Pharmaceutical companies listed under Dhaka Stock Exchanges. The sample period 

covers eight years from 2012-2019. To conduct the study, Return on Equity and Tobin's Q was 

taken as a proxy of accounting measure of profitability and market measure of profitability, 

respectively. The proportion of women on board structure was taken as a proxy for gender 

diversity. Some other variables: board size, firm age, leverage, and firm size, were incorporated 

to control the effect of these variables on profitability. The study reveals that gender diversity 

shows a positive but insignificant relationship with the firm's performance in terms of ROE. The 

R square of this model was 11.67%. In terms of Tobin's Q, gender diversity exhibited a significant 

positive relationship with firm performance. The R square of this model was 17%. This implies 



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that the market ascribes a great value to the inclusion of women in board structure since it 

increases the board structure's independence and profitability. 

 

Keywords: Gender Diversity, Profitability, Board, Pharmaceutical Sector, Bangladesh. 

 

JEL Classification Codes: C12, F65, L25. 

 

INTRODUCTION 

Bangladesh is among the few countries in South Asia that have increased women's employment 

and cut the wage gap between men and women in the past decade. But women still have limited 

choices, decision-making power in the jobs and economic environment.  The Board of Directors 

is the internal mechanism of a company. Increased involvement of women on Board is said to 

increase transparency, accountability in the company. Women on Board can mitigate fraudulent 

activities and ensure the protection of investors' capital. So, women on Board may improve the 

financial health of a company. 

Many companies failed in the past two decades due to a lack of good governance, poor 

accountability, earnings management, asset revaluation, and the use of creative accounting, etc. 

The company's Board of directors is responsible for setting up strategic plans that outline the 

corporation's growth path and sustainability. Hence, it is essential to investigate the board 

characteristic and diversity as these can significantly influence the company's performance.  

Various empirical studies have been conducted worldwide, but the studies conducted in 

Bangladesh regarding this are pretty minimal if compared. A similar study was conducted on DSE-

listed seven pharmaceutical companies in Bangladesh using ROE, ROA, and NAVPS to measure 

financial performance (Islam, 2018). Another study used 259 listed companies in Bangladesh 

(Munira, 2020). Both found a positive association between women's representation in the 

boardroom and firm financial performance indicators. Where one study focused on a few 

companies of pharmaceutical sectors of Bangladesh, the other study looked into all the industries 

but for the years 2018 and 2019. These two studies do not provide a clear look at the actual state 

of a sector like pharmaceutical in terms of gender diversity.  

This report studied the effects of gender diversity in the Board of directors on the 

profitability of the pharmaceutical industry in Bangladesh. Firm size, Firm Age, Board Size, Debt-

Asset Ratio, and Gender Diversity on Board were considered independent variables. ROA and 

Tobin's Q as the dependent variable. 
 

LITERATURE REVIEW 

Gender diversity on the board structure of companies began to beg the question of the interplay 

among the firm performance and women participation on the Board. The presence of multiple 

schools of thought has shown varieties of supports regarding this argument. Hambrick and Mason 

(1984) have established a negative relationship between firm performance and women's 

participation. The contrary has also been found. 

Diversity has been viewed under agency theory as a measure of independence and a source 

of fair and transparent decision-making (Jensen & Meckling, 1976; Luoma & Goodstein,1999). 

Some have found proof of a lower degree of fraudulent activities for increased participation of 

women in corporate board structure.  However, the degree to which increased participation of 

women will contribute to good corporate governance lies in what goal corporate governance 

should try to achieve. Brown et al. (2002) contemplated that women's participation would not 



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3 

contribute to the enhanced value of a firm if the existence of corporate governance does not 

promote performance improvement of the firm. As good corporate governance and an increase in 

women's participation on Board is essential for enhanced performance for a company, many 

countries have made it a compulsory requirement for the Board to have a high percentage of 

women composition. Norwegian companies were required to have 40% of their board members 

be represented by women (Huse, 2007).  

Previous literature has shown that female participation on board increase firm performance. 

A positive impact on firm performance was found for Fortune 500 companies that incorporated at 

least three women on board structures from 2004-2008. (Joy et al., 2008). MSCI World Index 

reported that companies under the strong leadership of women had higher annual financial returns 

(11.1% versus 7.4%) and price-to-book ratios (1.76 versus 1.56) compared to companies with no 

such leadership of women (Lee et al., 2015).  

With the introduction of control variables in this trajectory, somewhat ambiguous results 

have been found underlying the actual link between gender diversity and firm performance. Adams 

and Ferreira (2009) found that gender diversity among board members could produce poor firm 

performance. This result was inconsistent with previous literature. Another study on Nigerian 

firms with 122 samples and for the period 1991-2008 found a negative relationship between gender 

diversity and firm performance (Ujunwa, 2012). A 2014 study in the Economic Journal found no 

evidence to support the link between gender diversity in companies in the U.K. and corporate 

performance. The study concluded that gender diversity should be structured around the morals of 

variety. (Gregory et al., 2014) 

But not all studies showed such results, even with the introduction of control variables. 

Nguyen et al. (2015), using a sample of 120 publicly listed companies as the sample for 2008 to 

2011, found a positive relation between board gender diversity and firm performance. This study 

also added that the inclusion of more women on the Board increased firms' performances.  

Moreover, using 638 American Fortune 1000 companies as a sample, Carter et al. (2003) 

found a significant positive correlation. In this study, company size, sector, and corporate 

governance characteristics were considered as control variables. A similar result was found in 

Erhardt et al. (2003) study, which examined the Return on Investment of 127 large U.S. companies 

with their proportion of women and minorities involved on the Board for 1993 and 1998. Evidence 

of such a link between the increase in the presence of women on Board and enhanced performance 

of firms was also found in Romanian companies (Ionascu et al., 2018). This study was conducted 

during 2012-2016 on the companies listed on Bucharest Stock Exchange. 

In Bangladesh, Islam (2018) conducted a study on seven listed companies of the Dhaka 

Stock Exchange under the pharmaceutical sector. The study concluded that the companies should 

include trained and mature women on Board to increase shareholder value. Further research was 

done considering 259 listed companies in DSE for the years 2018 and 2019. This study also found 

a positive association. Despite the result of these two studies being positive, the studies were not 

conclusive enough.  
 

RESEARCH QUESTION 

Is gender-diverse boards of directors relevant to the financial performance of pharmaceutical 

companies listed in DSE?     

 

 

 



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METHOD 

Sample Selection 

The population for this study comprised all companies listed in the pharmaceutical sector of DSE 

in the last eight years (2012–2019). The sample consists of companies, of which all the data for 

those years was available. Thus, the number of companies came down from 31 to 27. All the 

relevant data were collected from secondary sources; these involve mainly the audited financial 

statements and the web portals of the selected companies. 

 

Variables Selection 

Following some literature (Vafaei et al., 2015; Haslam et al., 2010; Ionascu et al., 2018), market-

based and accounting-based variables have been selected to enhance the viability. For market-

based variables, Tobin's Q (Sá et al., 2017) has been chosen, as it is expected to capture the current 

and future outlook of the company. Return on Asset has been selected as an accounting-based 

variable as it is told to state a company's present and recent past performance adequately. 

 

Dependent Variables 

Return on Asset (ROA): ROA is a better estimation of profitability considering financial leverage. 

(Rezina et al, 2020; Munira, 2020; Ionascu et al, 2018) If a company can secure a higher ROA, it 

is utilizing its Asset more efficiently. ROA is calculated as net income divided by total assets.  

Tobin's Q: Tobin's Q (Sá et al., 2017) has been selected for the market-based variable. Tobin's Q 

equals the summation of Market Value of Equity, Total Debt, and Preferred Share by Total Asset. 

It captures the current and future outlook of the company.  

 

Independent Variables 

Diversity: The proportion of women on the Board was used to measure diversity; this was selected 

as the primary independent variable, whose effect is the study's primary concern. It is calculated 

as the number of female board members divided by the number of total board members in a given 

year. (Vafaei et al, 2015; Haslam et al, 2010; Ionascu et al, 2018). A study investigated 259 listed 

companies on DSE and found a positive association between women's representation in the 

boardroom and firm financial performance indicators. (Munira, 2020). Meca et al. (2015) studied 

the link between boards' gender diversity and bank performance on a sample of 159 banks across 

nine countries for 2004–2010. The study showed that banks' performance is improved by gender 

diversity. Another study found that gender diversity among board members could result in poor 

firm performance. (Adams & Ferreira, 2009) 

Firm Size: Firm Size has been calculated using the literature of Asimakopoulus et al. 

(2009), Nunes et al. (2009), Pratheepan (2014), and Nakatani (2019). They found firm's size has a 

positive influence on a firm's performance. It is calculated as the Natural Log of Total Asset. It is 

one of the control variables of the study. Some researchers also found a negative relationship 

between a firm's size and firm's performance (Goddard et al. 2005) 

Firm Age: Firm age has been calculated following Rezina et al. (2020). Blažková and 

Dvouletý (2019) found positive relationships between the firm's age and the firm's performance. 

On the other hand, some researchers found the relation was negative (Coad et al., 2013). The 

calculation method is: Natural Log of Firm Age (difference between the year of incorporation and 

time t) 

Board members: It is calculated as a Natural Log of Board Size. Board members are 

expected to protect the interest of the investors via mediating any conflicts that arise. Thus, 



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5 

enhancing the firm's performance. While agency theory and resource dependency theory suggest 

that the board size positively affects performance, stewardship theory favors smaller board size 

and argues that larger board size negatively impacts firm performance. A study was carried out for 

five years from 2008 to 2012 using 145 non-financial companies listed in the NSE CNX 200 Index 

of India, which found that board size and the firm performance had a positive relation. (Kalsie & 

Shrivastav, 2016). 

Leverage: The leverage of the firm is measured as the Debt-Asset ratio. Leverage and a 

firm's performance are negatively related. (Asimakopoulus et al., 2009). Most empirical studies 

have found an inverse leverage-profitability relationship. 

 

Table 1. Definition of Variables Used in Study 

 

Variable Notation Expected Signs Definition 

Dependent Variable    

Return on Asset ROA  The ratio of net income/total assets 

Tobin's Q Tobin's Q  (Market Value of Equity + Total 

Debt + Preferred Share)/Total Asset 

Independent 

Variable 

   

Firm Size Firm Size +/- Natural Log of Total Asset 

Firm Age Firm Age +/- Natural Log of Firm Age (difference 

between the year of incorporation 

and time t) 

Board Size Board Size +/- Natural Log of Board Size 

Diversity  Diversity +/- The proportion of female members 

on Board 

Leverage Debt to Asset 

Ratio 

- Interest Bearing Liability/Total 

Asset 

 

Hypotheses  

Taking the theoretical arguments into consideration, the following hypothesis is proposed: 

 H0: Financial performance for pharmaceutical companies listed in DSE has not influenced 

gender-diverse boards of directors. 

 H1: Financial performance for pharmaceutical companies listed in DSE has influenced 

gender-diverse boards of directors. 

 

Model of the Study 

To investigate whether diversity on board affects firm’s profitability, the model is used given 

below: 

 

ROA =α + β1Diversityit + β2FirmSizeit + β3FirmAgeit + β4BoardSizeit + β5Leverageit + εit 

Tobin’s Q =α + β1Diversityit + β2FirmSizeit + β3FirmAgeit + β4BoardSizeit + β5Leverageit + 

εit 

 



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Where i = 1, 2, …. n and t = 1, 2, … t represent firm and a year respectively; β is the parameter, 

and ε represents the error term or disturbance 

 

EMPIRICAL RESULTS 

Descriptive Statistics 

Descriptive statistics of all variables have been presented in the following table.  

 

Table 2. Descriptive Statistics of Study 

 

Variable Obs Mean Std. Dev. Min Max 

ROA 216 0.0715 0.0972 -0.4971 0.4402 

MKt to Book 216 4.8542 12.8614 0.0000 166.4684 

TobinsQ 216 1.8747 1.9446 0.0015 13.4145 

Diversity 216 0. 2250 0.1810 0.0000 0. 5714 

Board Size 216 1.9248 0.2551 1.3863 2.4849 

Firm Size 216 21.8397 1.5146 18.2006 24.8986 

Firm Age 216 3.2205 0.6691 0.6931 4.1744 

Debt Asset 

Ratio 

216 0.2286 0.1947 0.0000 0.7034 

Source: Author's Calculation 

In the following table, the comparison of the means for companies with or without women 

on boards of directors is shown. Based on the t-test results, it appears that there are no differences 

between the groups at 0.05 significant level. As all the values of the t-test stayed within the region 

on ±1.96, we could not state that there is any difference between the groups. 

 

Table 3. Comparison of the means 

  
Average Average 

 

 
Companies with Female 

Members on Board 

Companies without 

Female Members on Board 

T-test 

ROA 0.0687 0.0780 -1.4335 

Tobin's Q 2.1346 1.2574 -0.0001 

MKt to Book 6.1724 1.7235 0.00003 

Board Size 1.9285 1.9158 0.0004 

Firm’s Age 3.7480 3.7480 0.0000 

Firm Size 21.8646 21.7805 -0.00004 

Debt to Asset 

Ratio 

0.2322 0.2200 -0.0013 

Source: Author's Calculation 

 

 

 

 

 



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Multicollinearity Test 

Table 4. Results of VIF Test 

  
VIF 1/VIF 

Board Size 1.15 0.8731 

Firm’s Age 1.14 0.8759 

Debt to Asset Ratio 1.06 0.9411 

Diversity 1.04 0.9579 

Firm’s Age 1.02 0.9775 

Mean VIF  1.08 
 

Source: Author's Calculation 

 

Here, none of the variables exceed 2.5. If any variables exceeded 2.5, a multicollinearity 

problem would have been spotted. Multicollinearity problem disturbs the individual effects of the 

independent variable on the dependent variable. 

 

Heteroscedasticity Test 

Model 1 shows no presence of heteroscedasticity, as Prob>Chi2 is higher than .05, but the problem 

of heteroscedasticity is present in Model 2. This will need to be fixed. Homoscedasticity is one of 

the assumptions of the OLS (Ordinary Least Square) model. 

 

Table 5. Results of Heteroscedasticity Test 

 

Breusch Pagan /Cook-Weisberg test for heteroscedasticity 

Model Chi2(1) Prob>Chi2 Presence of Heteroscedasticity 

Model 1-ROA 0.01 0.907 NO 

Model 2-Tobin’s 

Q 

55.87 0.000*** YES 

Note: * represents significance at 10% level, ** represents significance at 5% level and *** 

represents significance at 1% level. 

Source: Author's Calculation 

 

Autocorrelation Test 

Table 6. Results of Autocorrelation Test 

 

Wooldridge test for autocorrelation in panel data 

Model F Prob>F Presence of Autocorrelation 

Model 1-ROA 9.912 0.004 YES 

Model 2-Tobins Q 7.485 0.011 YES 

Note: * represents significance at 10% level, ** represents significance at 5% level and *** 

represents significance at 1% level. 

Source: Author's Calculation 

 

The Wooldridge test has been used in this study. The null hypothesis of the test states no 

autocorrelation. For both models, autocorrelation is present at a 0.05 significant level. The absence 

of autocorrelation is one of the assumptions of the OLS model. 

 



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Test for Cross-Sectional Dependency 

This is a crucial test to determine whether a Fixed-Effect or Random-Effect Model is enough to 

predict the relationship of variables or not. The null hypothesis is, there is no cross-sectional 

dependency among the panel. For Model 2, the null hypothesis has been rejected at 0.10 significant 

level Pesaran's value but can't be dismissed for Friedman's value. Thus, the average value of off-

diagonal has been checked; it is higher than .25. So, there is the presence of cross-sectional 

dependency in this model. This needs to be considered while interpreting the data. The presence 

of cross-sectional dependence might lead to biased results from Fixed Effect or Random Effect 

model. Panel Corrected Standard Error (PCSE) Model should be used for a better result. 

 

Table 7. Results of Test for Cross Sectional Dependency 

 

Model Pesaran’s 

value 

P Value Friedman’s 

Value 

P Value Avg. 

value of 

Off-

diagonal 

elements 

(abs) 

Cross-

Sectional 

Dependency 

Model 1-

ROA 

-0.857 0.3917 4.074 1.0000 0.384 NO 

Model 2 

– Tobin’s 

Q 

2.609 0.0091 17.840 0.8815 0.511 YES 

Source: Author's Calculation 

 

Hausman Test 

It is necessary to determine the model between the fixed and random effect models, which will 

better analyze the data. This is done via using Stata/MP 13 software and conducting Hausman 

Test. In this test, the null hypothesis is random effect model is appropriate. 

 

Table 8. Results of Hausman Test 

 

Model Chi2(9) P value Decision 

Model 1-ROA 10.04 0.0741* Fixed Effect Model 

Model 2-Tobins Q 8.30 0.1405 Random Effect Model 

Note: * represents significance at 10% level, ** represents significance at 5% level and *** 

represents significance at 1% level. 

Source: Author's Calculation 
 

At Model 1, P-value is lower than the 0.10 level of significance; for this null hypothesis is rejected, 

the Fixed Effect Model is used to analyze data. 

 

At Model 2, the P-value is higher than the 0.10 level of significance, for this null hypothesis is not 

rejected, and the Random Effect Model is used for this model. 

 

 

 



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Fixed Effect Model 

Table 9. Summary of Fixed Effect Model for Model 1  

 

Variables Coef. t P>│ t│ Significance 

Diversity 0.0525 0.4400 0.6620 No 

Board Size 0.0044 0.1000 0.9190 No 

Firm’s Age 0.1816 2.1800 0.0300** At 0.05 

Debt to Asset Ratio -0.1291 -2.6700 0.0080*** At 0.01 

Firm Size -0.0382 -3.0100 0.0030*** At 0.01 

Constant 0.2352 0.8600 0.3930 
 

R-Sq 0.1167 
 

F 4.86 
 

Prob>F 0.0003 
 

Note: * represents significance at 10% level, ** represents significance at 5% level and *** 

represents significance at 1% level. (Underline) represents wrong sign. 

Source: Author's Calculation 

 

The table reflects the impact of the firm-specific accounting-based performance measure, 

ROA. The R-square value is 11.67%, and P-value is less than 0.05. The model is somewhat 

acceptable. The model shows diversity even though having a positive coefficient is insignificant. 

Among other variables, the Firm's Age is significant at 0.05, whereas, Debt to Asset Ratio and 

Firm Size are significant at 0.01 level. Even though Firm Size is significant, they are exhibiting 

the wrong sign. 

 

Random Effect Model 

Table 10. Summary of Random Effect Model for Model 2  

 

Variables Coef. z P>│ z│ Significance 

Diversity 1.7382 1.2800 0.2000 No 

Board Size 0.3516 0.5600 0.5750 No 

Firm’s Age 7.7580 6.0800 0.0000*** At 0.01 

Debt to Asset Ratio -0.7871 -1.1000 0.2700 No 

Firm Size -0.4184 -2.6800 0.0070*** At 0.01 

Constant 0.2352 0.8600 0.3930 
 

R-Sq 0.1879 
 

Chi2 42.98 
 

Prob>Chi2 0.0000 
 

Note: * represents significance at 10% level, ** represents significance at 5% level and *** 

represents significance at 1% level. (Underline) represents wrong sign. 

Source: Author's Calculation 

 

The table reflects the impact of firm-specific on a market-based performance measure, 

Tobin's Q. The R-square value is 18.79%, and P-value is less than 0.05. The model is somewhat 



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acceptable. The model shows diversity even though having a positive coefficient is insignificant. 

Among other variables, the Debt to Asset Ratio and Firm Size are significant at 0.01 level. Even 

though Firm Size is significant, they are exhibiting the wrong sign. 

 

Panel Corrected Standard Error (PCSE) Model 

Table 11. Summary of Panel Corrected Standard Error (PCSE) Model for Model 2  

 

Variables Coef. z P>│ z│ Significance 

Diversity 1.6566 2.3000 0.0210** At 0.05 

Board Size 0.0855 0.1900 0.8490 No 

Firm’s Age 6.3317 2.6900 0.0070*** At 0.01 

Debt to Asset Ratio -0.4098 -0.7800 0.4380 No 

Firm Size -0.4483 -4.6300 0.0000*** At 0.01 

Constant -12.7755 -1.4400 0.1500 
 

R-Sq 0.1755 
 

Chi2 30.4300 
 

Prob>Chi2 0.0000 
 

Note: * represents significance at 10% level, ** represents significance at 5% level and *** 

represents significance at 1% level. (Underline) represents wrong sign. 

Source: Author's Calculation 

 

The table reflects the impact of firm-specific on a market-based performance measure, 

Tobin's Q. The R-square value is 17.55%, and P-value is less than 0.05. This is an improvement 

from the random-effect model. In this model, diversity is positive and significant at 0.05 level. So, 

a 1 percent increase in variety on Board will cause a 1.66 percent increase in profitability. Among 

other variables, Firm Size and Firm Age is significant at 0.01 level. Even though Firm Size is 

significant, they are exhibiting the wrong sign. 

 

FINDINGS AND DISCUSSIONS 

Upon examining the effect of gender diversity in the Board of Directors, the current study found 

that diversity on the Board has positive effects on both ROA and Tobin's Q but significantly affects 

only Tobin's Q or the market measure of profitability. Tobin's Q includes the present and future 

outlook of the company. So, it seems that investors are somewhat optimistic due to the increase in 

diversity on Board, as this may result in more transparency and accountability. Board Size, even 

though positive, does not have any significant effect on profitability measures. It can be argued 

that board size has little to no impact on a firm's profitability. 

Firm Age and Firm Size are statistically significant in both models, but the latter is exhibiting a 

theoretically wrong sign. So, high firm size will translate to high profitability cannot be stated for 

this study. The debt Asset ratio displays a theoretically correct sign in both models but is not 

significant for Model 2.  

 

 

 

 



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Table 12. Comparison of two Models 

 

Variable  Expected 

Sign 

Fixed Effect (Model 1 

ROA) 

PCSE Model (Model 2 Tobin's 

Q) 

Actual 

Sign 

Significance Actual Sign Significance 

Diversity Positive/ 

Negative 

Positive No Positive Yes 

Board Size Positive/ 

Negative 

Positive No Positive No 

Firm’s Age Positive/ 

Negative 

Positive Yes Positive Yes 

Debt to Asset Ratio Negative Negative Yes Negative No 

Firm Size Positive/ 

Negative 

Negative Yes Negative Yes 

 

CONCLUSION AND IMPLICATIONS 

The Pharmaceutical Industry of Bangladesh presents the most significant white-collar job creation 

opportunity after the banking industry. In Bangladesh, though women's employment has been the 

talk of the town, women in decision-making is still a questionable issue. The study attempts to 

analyze the contribution of gender diversity among the Board of directors on the profitability of a 

firm in Bangladesh's pharmaceutical industry.  With the help of a panel data approach, this study 

attempts to find the link with eight years of the sample period. Descriptive statistics, 

Multicollinearity test, Heteroscedasticity test, Autocorrelation test, Cross-Sectional Dependency 

tests, Regression Analysis, have been done to interpret the study. After analyzing, the PCSE model 

and Fixed effects models were chosen to interpret the data. For market measure, gender diversity's 

impact on Tobin's Q is significant, but gender diversity's impact on ROA is not significant for 

accounting measure. Hence, it can be stated that the inclusion of women on the Board can enhance 

the company's perception among the investors. This study can be a good source for investors, 

policymakers, and researchers to contend with and make viable decisions and policies to improve 

the performance of the firms. 

This study incorporates only the listed companies of DSE. But to get a robust result and 

clearer outlook, further study needs to be conducted incorporating the companies that are not listed 

yet. So there is a scope of future investigation on this. 

 

AUTHOR CONTRIBUTIONS 

Conceptualization:  Hossain Ahmmed Fahad 

Data Curation: Imran Mahmud 

Formal Analysis: Atkia Nabiha Rahman 

Funding Acquisition: Hossain Ahmmed Fahad; Imran Mahmud; Atkia Nabiha Rahman 

Project Administration: Hossain Ahmmed Fahad; Imran Mahmud 

Software: Hossain Ahmmed Fahad; Imran Mahmud 

Validation: Atkia Nabiha Rahman 



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Writing – Original Draft: Hossain Ahmmed Fahad; Imran Mahmud 

Writing – Review & Editing: Hossain Ahmmed Fahad; Atkia Nabiha Rahman 

 

CONFLICT OF INTEREST STATEMENT 

The authors declare that they have no competing interests. 

 

ACKNOWLEDGEMENT 

All authors contributed equally to the conception and design of the study 

 

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APPENDICES 

 

Appendix A: List of Textile Companies 

 

No. Codes in DSE No. Codes in DSE 

1 ACI 15 JMISMDL 

2 ACIFORMULA 16 KEYACOSMET 

3 ACMELAB 17 KOHINOOR 

4 ACTIVEFINE 18 LIBRAINFU 

5 AFCAGRO 19 MARICO 

6 AMBEEPHA 20 ORIONINFU 

7 BEACONPHAR 21 ORIONPHARM 

8 BXPHARMA 22 PHARMAID 

9 BXSYNTH 23 RECKITTBEN 

10 CENTRALPHL 24 RENATA 



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11 FARCHEM 25 SALVOCHEM 

12 GHCL 26 SQURPHARMA 

13 IBNSINA 27 WATACHEM 

14 IMAMBUTTON 
  

 

 

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