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Effect of Corporate Charcteristics on Triple Bottom Line Reporting of Quoted Commercial Banks in Nigeria

  • Chukwuebuka Victor Onovo
  • Prof. Uche Lucy Onyekwelu
  • Prof. Chike Nwoha
  • 150-166
  • Jul 25, 2023
  • Accounting & Finance

Effect of Corporate Charcteristics on Triple Bottom Line Reporting of Quoted Commercial Banks in Nigeria

Chukwuebuka Victor Onovo; Prof. Uche Lucy Onyekwelu, PhD & Prof. Chike Nwoha, PhD
Accountancy Department Enugu State University of Science and Technology, Enugu State, Nigeria

DOI: https://dx.doi.org/10.47772/IJRISS.2023.70710

Received: 25 January 2023; Revised: 25 June 2023; Accepted: 01 July 2023; Published: 25 July 2023

ABSTRACT

The study investigated effect of ‘corporate characteristics (cc) measured by Firm Size (FS), Firm Age (FA) and Firm Leverage (FLEV) on Triple Bottom Line Reporting measured by Environmental Bottom Line Reporting (EBLR), Social Bottom Line Reporting (SBLR) and Return on Assets (ROA)’. An ex-post facto research design approach was adopted for the study. The population of the study comprises of 13 quoted commercial banks in Nigeria. The study used panel data from the period of eleven (11) years (2006-2015) and 13 quoted commercial banks were chosen as the sample size using purposive sampling technique. The study utilized secondary data obtained from the annual reports of quoted commercial banks listed on the Nigerian Stock Exchange (NSE) for the period 2010-2020. Content analysis was applied in measuring disclosure, descriptive statistics and panel regression Analysis using Eview version 8 was applied in testing hypotheses. The study result revealed that there was positive (t-statistics, 0.380644) but non-significant (p-value, 0.7040) effect of Firm Size on Environmental Bottom Line Reporting (EBLR) of commercial banks. Also there was a negative (t-statistics, -1.239531) but non-significant (p-value, 0.2172) effect of Firm Age (FA) on SBLR quoted commercial banks. Finally there was a positive (t-statistics, 3.131350) but significant (p-value, 0.021) association between Firm Leverage (FLEV) and ROA. This implies that the level of environmental & social performance and reporting does not depend on the size or age of company. Based on the findings, the study recommended among others, that the Central Bank Nigeria and those charged with governance in commercial banks should initiate policies to improve sustainable social and environmental performance practices especially in the area of afforestation, erosion control, mother – child health care and pandemic sensitization and support.

Keywords: Triple Bottom Line Reporting, Environmental bottom Line Reporting, Social Bottom Line Reporting, Economic Bottom Line Reporting.

INTRODUCTION

1.1 Background of the Study

In the last 20th century, sustainability became a burning issue in the world that affects all industries around the globe. This affects all markets, some of which are less affected, while some are more affected. Corporations engage in sustainability to show their credibility, as well as strengthen processes, drive for growth and to create value for their businesses. Traditionally, profitability was the only the important bottom-line. The business success was understood as a financial success and effectiveness was the only measure in business. Such way of thinking was most probably the consequence of the past decades when awareness of social and environmental part of business success was rather low (Hammer, 2015).

Globally, early demands for sustainability reporting came largely from civil society and special interest groups. A number of governments and regulators have subsequently developed sustainability reporting guidelines and are the key forces driving the development of sustainability reporting as a matter of corporate responsibility and good governance. More recently, mainstream investors have begun to take note of the tangible impact of sustainability on the bottom line and are seeing potential to include environmental and social assessments in their investment analysis. There is a widely established expectation that companies wanting to obtain a leadership position and become competitive in the global marketplace need to effectively manage their environmental and social performance, disclosing challenges and achievements in a sustainability report. (International Finance Corporation, 2011 in Hammer, 2015). Nowadays many successful business organizations implement all three components of triple bottom line (TBL) equally, as each of the three parts of the TBL is of equal importance. If a company really wants to be successful in long term it has to take care of its stakeholder, not only of its shareholders. A triple bottom line is not a quest for a new bottom-line ‘metric’ but rather an approach for performance assessment and management that stresses the interdependence of economic, environmental and social criteria. Triple bottom line is therefore best seen as a process that includes managing, measuring and publicly reporting multi-dimensional performance and integrating with management process.

Primarily it is a platform for the discussion of these integrated issues within the council and the community. Triple Bottom Line is simply an analogy and process for the broader notion of sustainability reporting (Sauvente, 2011).

1.2 Statement of the Problem

The negative social and environmental impacts of economic development have become a matter of public concern in different parts of the world. These economic developmental impacts, such as climate change and global warming, natural disasters and pollution, have increased concerns of Governmental bodies, Environmentalists, Shareholders. Creditors, and society about the need to protect the world’s natural environment. To this end, prior researcher sexamined Triple Bottom Line (TBL)reporting in relation to corporate performance. There is paucity of research carried out on corporate characteristics as determinants of TBL reporting in quoted commercial banks in Nigeria. Subsequently, this study sets out to determine the effect of corporate characteristics on TBL reporting in quoted commercial banks in Nigeria.

1.3  Objectives of the Study

The objective of the study is to evaluate effect of Corporate Characteristics on Triple Bottom Line Reporting of Quoted commercial banks in Nigeria. To achieve the major objective, the following specific objectives are to:

  1. Determine the effect of Firm Size (FS) on Environmental Reporting of quoted commercial banks in Nigeria.
  2. Evaluate the effect of Firm Age (FA) on Social Reporting of quoted commercial banks in Nigeria.
  3. Ascertain the effect of Firm Leverage (FLEV) on Economic Reporting of quoted commercial banks in Nigeria.

1.4 Research Questions

To achieve the objectives of the study the following research questions were raised.

  1. To what extent has Firm Size (FS)affected Environmental Bottom Line Reporting of quoted commercial banks in Nigeria?
  2. How has Firm Age (FA) affected Social Bottom Line Reporting of quoted commercial bank in Nigeria?
  3. How has Firm Leverage (FLEV) affected Economic Bottom Line Reporting of quoted commercial bank in Nigeria?

1.5  Statement of Hypotheses

The following null Hypotheses were formulated and tested in the study

  1. Firm Size (FS) does not significantly affect Environmental Bottom Line Reporting of quoted commercial bank in Nigeria.
  2. Firm Age (FA) has no significant effect on Social Bottom Line Reporting of quoted commercial bank in Nigeria.
  3. Firm Leverage (FLEV) has no significant effect on Economic Bottom Line Reporting of quoted commercial bank in Nigeria.

REVIEW OF RELATED LITERATURE

2.1       Conceptual Review

2.1.1    Corporate characteristics

Corporate characteristics are elements controlled, directed, determined or influenced by management. It constitutes the size of the entity, profitability, liquidity, age, leverage, asset growth, sales growth, and turnover of the organization (Dioha, Mohammed & Okpanachi, 2018).

2.1.2    Firm Size

Large firms are often more impactful in the society, this makes large companies tend to receive more attention from the public and put them under public pressure to demonstrate social responsibility. Companies with higher environmental impacts are found to disclose social and environmental information more than others because there are greater public pressure against the company. Environment – sensitive industries will be more transparent about their environmental strategies and spend more time in environmental management to gain community trust. (Zuhroh & Sucmawati, 2003 in Andreas & Liani 2015). The firm size measurement can be carried out in several methods through sales, number of employees, assets or value added futures (Kaen &Baumann, 2003 in Zadeh & Eskandari, 2012). In this study, the researchers applied assets method to measure the size of firms.

2.1.3    Firm Age

The older a firm becomes, expectations are high that it will participate more in sustainable environmental practices to increase and maintain their corporate image as well as validate their corporate existence. Matured businesses tend to be larger and well-disposed to report sustainable information that influences their going concern. Older firms may have up to date information about recent developments and changes in the industry they operate, which makes them willing to implement new policies that ensures the going concern assumption of their entity (Kabiru, 2020).

2.1.2    Firm Leverage

Leverage is used to measure debt ratios with assets and own capital owned by the company. This ratio acts as information on the amount of assets and funds used as collateral to creditors. This ratio describes the extent to which debt can be guaranteed by the company. The company’s management decision in the use of debt is a signal given by investors in assessing the company’s prospects. Companies with good prospects will choose to use debt as an alternative funding compared to self-financing (Cushmere 2011 in Widyastuti, 2019). Leverage Ratio represent was represented with Debt Equity Ratio (DER), this ratio shows the ability of the company’s own capital to finance the debt held by the company.

DER = Total Debt/Total Equity.

Financial leverage gives value to the organization because of the interest tax shield offered with corporate tax by most government organizations needs to evaluate the amount of debt capital they require to examining their needs and the financial market (kaluarachi, Fernando, & Mallawarachchi, 2021).

Triple Bottom Line

Before now, entities traditionally recognize one principal form of capital contribution incorporations, and that is cash capital. Cash capital consists of all tangibles assets, intellectual property and sometimes services. The term bottom line refers to the return on that investment (profit), also known as economic capital (Sauvante, 2011).

In 1994, John Elkington, a pioneer in the field of sustainability and corporate responsibility, introduced the term “triple bottom line (TBL)”. His 1998 book, CannibalswithForks:TripleBottomLineof21stCenturyBusiness detailed the importance and benefits of going beyond the financial bottom line to express value creation. It also cited wider economic benefits, social and environmental returns. The TBL concept recognizes that there are two other formsof capital contribution that should also receive a return on investment even though they do not appear on the bottom line in the traditional accounting statements. The two are natural and social capital. (Sauvante, 2001). Since then, the concept of ‘profit, people, and planet’ has gained momentum and recognition. Today, many of the world’s top companies publish specific reports expressing their triple bottom line returns. These businesses detail how their commercial objectives fit client needs and environmental safety along with profit motives, to be successful. Non–‐profits, government entities, the UN, and foundations all have examples of expressing multiple values.

Triple Bottom Line (TBL) reporting is a measure used in business accounting to explain stakeholders’ knowledge of the company. It goes beyond the traditional, financial aspects and reveals the company’s impact on the world around it. (Global Reporting Initiative, 2006 cited in Amos & Uniamikogbo, 2016).

There is no universal standard method of calculating the TBL. Neither is there a universally accepted standard for the measure that comprise each of the three TBL categories. This can be viewed as a strength because it allows a user to adapt the general framework to the needs of different entities (businesses or non – profit), different projects or policies (Infrastructure investment or educational programs), or different geographic boundaries (a city, region or country) (Slaper & Hall, 2011).

2.1.2 Environmental Bottom Line Reporting

Environmental accounting disclosure has become more important among the business community as it is an element of disclosure of corporate social responsibility (CSR). The meaning of environmental accounting is to achieve sustainable growth and development and foremost to maintain the relationship between the communities (Ministry of the Environment, 2005 cited in Menike, 2020). It helps to increase the confidence in the information provided to stakeholders and to achieving the desired environmental consensus. as well as, it helps in strengthening the competitive position of companies by adopting productive policies in line with the expectations of society and the needs of consumers to produce and use environmentally friendly products. As a result, companies become complementary to society in addressing these environmental issues (Rifai, 2012 cited in Ala, 2019).

2.1.3 Social Bottom Line Reporting

The social line of TBL refers to conducting beneficial and fair business practices to the labour, human capital and the community (Elkington, 1997 cited in Amos & Uniamigbo 2016). The idea is that these practices provide value to the society and give back to the community. This line includes fair wages, providing health care coverage. Aside from the moral aspect of being good to the society, disregarding social responsibility can affect the performance and sustainability of the business. Recent examples in the industries have revealed that there are economic cost associated with ignoring social responsibility. The social performance simply focuses on the interaction between the community and the organization and addresses the issues related to community involvement, employee relations and fair wages (Goel, 2010 cited in Amos & Uniamikogbo, 2016). The concept of CSR is very dynamic. In this present day, companies rely on CSR activities to obtain public trust in company products, which might increase company profits. However, this point is still a debate among society. This condition is essentially the same as expressed by Friedman 1970 (in Aji and Castek, 2020) that stated: “Social responsibility is a difficulty experienced by almost all companies in the private competitive world. It would encourage certain parties to take responsibility for their actions and leaves them less likely to manipulate others for selfish purposes. People can do their best but only at their own cost”. Many business activities pretend to do benevolence as they consider it as part of their social responsibility (Aji and Castek, 2020).

2.1.4 Economic Bottom Line Reporting

The economic line of TBL framework refers to the impact of the organizations business practices on the economic system (Elkington, 1997 cited in Amos & Uniamikogbo, 2016). It pertains to the capability of the economy as one of the subsystem of sustainability to survive and evolve into the future in other to support future generations (Spangenberg, 2005 cited in Amos & Uniamikogbo, 2016). The economic ties the growth of the organization to the growth of the economy and how well it contributes to support it. In other words, it focuses on economic value provided by an organization to the surrounding system in a way that prospers it and promotes its capability to support future generations. Return on Assets (ROA) represents the ability of the entity to earn a profit from the utilization of its assets. ROA measures the percentage of net income of the total assets of the company (Aji & Castek, 2020).

2.2 Theoretical Framework

There are many theories backing corporate reporting, but for the purpose of understanding the theoretical concept of TBL Reporting Stakeholder theory was discussed.

2.2.1 Stakeholder Theory

The theory argues that firms should pay attention to all their constituencies, this stance is more consistent with value maximization which impels that managers must pay attention to all constituencies that can affect the firm.  In order for organizations to succeed and be sustainable overtime, executives must keep the interest of stakeholders aligned and going in the same direction. Stakeholder theory begins with the assumption that values are necessarily and explicitly a part of doing business. It asks managers to articulate the shared sense of the value they create and what brings its core stakeholders together (Jensen, 2001).

2.3 Empirical Review

Schutte, Kabir, & Huang (2008) studies the effect of leverage on financial performance: an analysis of European listed firms using ordinary least square regression analysis for the period of 2009 to 2017.

The result showed that there is a significant negative association between leverage and Return on Assets.

Sulaiman, Abdullah & Fatima (2014) examined determinants of environmental reporting quality in Malaysia using content analysis and regression analysis. The findings revealed a significant positive association between firm size and leverage with quality of environmental reporting.

Akbas (2014), studied the association between firm characteristics and environmental disclosure of quoted Borsa Istanbul for a period of 1 year. The researcher applied regression analysis and content analysis. The result showed that the quality of environmental disclosure is affected by the size, profitability and industry membership. Furthermore, leverage and age have a non- significant association with Environmental disclosure.

Nadeem, Ahmed, Ahmed, Ahmad & Batool (2015) studied the effect of leverage on financial health of firms: a study from cement industry of Pakistan using regression analysis and descriptive statistics for the period of 2008 to 2012. The findings revealed that leverage (long term debt to equity) has a negative and significant relationship profitability (ROA) of firms.

Habbash (2015) examined corporate governance ownership, company structure and environmental disclosure evidence from Saudi Arabia using content analysis and regression analysis for the period of 2007 to 2011. The findings revealed that firm leverage have a significant negative correlation with environmental disclosure while firm sixe and profitability positively affect environmental disclosure.

Abubakar (2017) examined influence of firms attributes on environmental disclosure in listed brewery companies in Nigeria using multiple regression analysis and content analysis. The findings revealed that firm size have positive significant influence on environmental disclosure.

Waluyo (2017) studied firm size, firm age, and firm growth on corporate social responsibility in Indonesia: the case of real estate companies using multiple linear regression analysis for the period of 2012 to 2016. The findings revealed that firm size age has significant effect on corporate social responsibility disclosure.

Hossain, Dey, & Chandrasil (2018) studied effect of firm size, firm age and independent director on corporate social responsibility (CSR) disclosure in Bangladesh: a study of banking sector using multiple regression analysis for the period of 2011 to 2015. The findings revealed that firm age has no significant influence on CSR disclosures of the banks operating in Bangladesh banking industry.

Badulescu, Saveanu & Hatus (2018) examined the relationship between firm size and age, and its social responsibility actions – focus on a developing country (Romania) using correlation, independent sample T-tests and linear regression modelling for a period of 2016. The finding revealed that firm age does not determine corporate social responsibility.

Rahman, Saima, & Jahan (2020) examined the impact of financial leverage on firm’s profitability: an empirical evidence from listed textile firms of Bangladesh using pooled ordinary least square method. The findings revealed a significant negative relationship between leverage and firms profitability.

Moruff, Salisu, Muhammed, Garba & Nasiru (2021), examined firm – specific attributes and environmental disclosure of listed oil and gas firms in Nigeria using generalized least square. The result showed a positive and significant relationship between board composition, financial leverage, existence of foreign directors on the board and environmental disclosure (ED). However, firm age and financial performance was found not to have significant relationship with ED.

Moshud, Sani, &Olanrewaju (2021) examined firm size and environmental disclosure of quoted firms in Nigeria from 2012 to 2016 using binary regression techniques. The findings revealed that firm size has a negative coefficient and significant negative relationship with environmental disclosure.

Aloshaibat (2021) examined effect of financial leverage on the financial performance of Jordanian public shareholding companies: applied study on the financial sector of Jordan for the period of 2015 to 2019 using descriptive statistics and regression analysis. The findings revealed that financial leverage does not affect Return on Assets (ROA).

METHODOLOGY

3.1       Research Design

This study adopted an ex-post facto design and as a result, relied on historical data. A longitudinal time series data drawn from the cross section of fourteen (13) commercial banks listed on the floor of Nigerian Stock Exchange (NSE), for the period of ten (11) years were used for the empirical investigation. Similarly, the trendy nature of sustainability reporting disclosure and the availability of such non-financial related disclosure data in annual reports underlines the choice of time period used in the study. The study seeks to examine the effect of Corporate Characteristics (with FS, FA and FLE as proxies) on Triple Bottom Line Reporting (with EBLR, SBLR, and ECR as proxies).

3.2       Population of the Study        

The population of this study is made up of thirteen (13) quoted commercial banks listed in Nigeria Stock Exchange at 31 December, 2020.

Table 3.2.1:  Lists of Population Size.

S/No Names
1. Zenith Bank Plc
2. Wema Bank Plc
3. First Bank of Nigeria Plc
4. Eco Bank Plc
5. Unity Bank Plc
6. First City Monument Bank Plc
7. Fidelity Bank Plc
8. Stanbic IBTC Bank Plc
9. Guarantee Trust Bank Plc
10. Union Bank Plc.
11. United Bank for Africa Plc.
12. Access Bank Plc
13. Sterling Bank Plc

Source: Quoted Commercial Banks in Nigeria

3.3       Sample Size Determination

The sample size was made up of thirteen (13) quoted commercial banks.

3.3b     Method of Data Analysis

Global Reporting Initiative (GRI) framework G4 disclosure guidelines was adapted for the purpose of developing disclosure index and assessing environmental and social performance. The researchers adapted Samuel, Aruna, & Amahalu (2020) index scoring method of content analysis in analyzing the indicators. These indicators were scaled into two (2) points, for every full and partial disclosure bearing qualitative and quantitative description a point is scored for the indicator while for every non – disclosure the indicator is scored zero (0). The total score for the content analysis on environmental dimension are sixteen (16) expected points, while the social dimension gives fifteen (15) expected points. The total scores are expected to sum up to a maximum of 31 thirty – one scores (that is 1 x 31 = 31).

Table 3.3.1 Disclosure Index/Indicators

S/N Environmental Dimension Non- – Disclosure Partial/Full Disclosure
1 Waste reduction 0 1
2 Recycling 0 1
3 Control and emission 0 1
4 Energy consumption 0 1
5 Biodiversity 0 1
6 Management of environmental policies system 0 1
7 Management on the impact on the environment and life cycle of product and services 0 1
8 Eco-efficiency 0 1
9 Environmental Justice 0 1
10 Environmental Education and training 0 1
11 High risk projects, climate strategy and governance 0 1
12 Environmental reports 0 1
13 Mention of Sustainability report 0 1
14 Environmental certification 0 1
15 Waste management 0 1
16 Water usage 0 1
Total (16 disclosure indices x 1) 16
Social Dimension
1 Labour practices and working conditions 0 1
2 Labour practices and relations with employees 0 1
3 Relationships with the local community 0 1
4 Engagement of stakeholders 0 1
5 Financing and constructing of social action 0 1
6 Society, competition and pricing policies 0 1
7 Concepts of social justices 0 1
8 Relationship with supplier and contractors 0 1
9 Product and services 0 1
10 Human rights 0 1
11 Social reports 0 1
12 Gender diversity 0 1
13 Customer relation & support 0 1
14 Customer service centers 0 1
15 Employee turnover 0 1
MSS (15 disclosure indices x 1) 15

Source: GRI G4 framework.

Therefore EBLR = TEDP/MES

                 SBLR = TSDP/MSS

Where:

EBLR = Environmental Bottom Line Reporting

 SBLR = Social Bottom Line Reporting

TEDP = Total Environmental Disclosure Points

TSDP = Total Social Disclosure Points

 MES = Maximum Environmental scores

MSS = Maximum Social Scores

Descriptive statistics is planned towards specifying the nature of a given phenomenon (0nyekwelu, 2020). While the descriptive provides an insight into the average level and the univariate relation between the variables, as well as their joint effect using panel regression analysis through E view version 8 was also used as a statistical technique to analyze effect and relationship that exist between corporate characteristics and TBL reporting.

3.4 Model Specification

The study adopted the regression model used by Mohamad, Salleh, Ismail & Chek (2014) with little modifications to suit the requirement of the study.

The model used for the study is therefore, stated as follows:

TBLR = ƒ (CC)

TBLR = βo + β1 (FS) + β2 (FA) + β3 (FLEV) + e

EBLR = βo + β1 (FS) + e                      —  —  —  —  —  —   Model 1

SBLR = βo + β2 (FA) + e                         —  —  —  —  —  —  Model 2

ECBLR = βo + β3 (FLEV) + e              —  —  —  —  —  –Model 3

Where: TBLR = Triple Bottom Line Reporting (constitutes EBLR. SBLR, ECBLR)

EBLR = Environmental Bottom Line Reporting/Disclosure Index Scores.

SBLR = Social Bottom Line Reporting/Disclosure Index Scores.

ECBLR = Economic Bottom Line Reporting (Proxied with ROA).

ROA = Return on Assets (Calculated as EBIT/Total Assets).

CC = Corporate Characteristics (constitutes FS, FA, FLEV).

FS = Firm Size (Natural log of Total assets).

FA = Firm Age (The age of an entity since incorporation).

FLEV = Firm Leverage (Calculated as Debt/Equity)

β0 = Regression constant.

β1, β2, β3 =       regression co-efficient associated with independent variables.

e = Stochastic error term.

The apriori expectation is that the elements (FS, FA, and FLEV) of Corporate Characteristics has a positive effect on TBL (EBLR, SBLR, & ECBLR – ROA).

Decision: Accept null hypothesis if the estimated p-value is greater than 0.05 level of significance, otherwise reject null hypothesis and accept alternative hypothesis.

DATA PRESENTATION AND ANALYSIS

4.1  Data Presentation

This chapter presents the analysis of the secondary data collected from annual reports of the thirteen (13) listed Nigerian banks. The data from these sources are therefore presented in this chapter using tables showing time series and cross sectional data of banks. Corporate characteristics was represented with Firm Size (FS), Firm Age (FA), and Firm Leverage (FLEV), while Triple Bottom Line Reporting proxies include Environmental Bottom Line Reporting (EBLR), Social Bottom Line Reporting (SBLR) and Return on Assets (ROA for Economic Bottom Line Reporting). See Appendix 1.

4.2  Data Analysis

In this chapter, we also provided two types of data analysis; namely descriptive analysis and inferential analysis. The descriptive analysis helps us to describe the relevant aspects of the phenomena under consideration and provide a detailed information about each relevant variable. For the inferential analysis, we used panel data regression analysis.

Table 1 Descriptive Statistics

FS FA FLEV EBLR SBLR ROA
 Mean  9.125874  45.38462  2.971844  0.142510  0.307692  0.922724
 Median  9.000000  31.00000  0.724600  0.062500  0.333300  0.111800
 Maximum  10.00000  126.0000  69.69750  0.687500  0.666700  13.44230
 Minimum  8.000000  4.000000 -170.1239  0.000100  0.000700  0.023600
 Std. Dev.  0.542128  31.67416  19.03942  0.150786  0.109595  2.859170
 Skewness  0.086712  1.230729 -4.289200  1.124741  0.554568  3.354460
 Kurtosis  3.202961  3.416020  51.20944  3.713750  4.258176  12.66486
 Jarque-Bera  0.424643  37.13146  14286.53  33.18555  16.76193  824.7471
 Probability  0.808705  0.000000  0.000000  0.000000  0.000229  0.000000
 Sum  1305.000  6490.000  424.9737  20.37900  43.99990  131.9495
 Sum Sq. Dev.  41.73427  142461.8  51474.92  3.228592  1.705583  1160.829
 Observations  143  143  143  143  143  143

 Source: Eview 8 Ouput, 2022.

Table 1 shows the descriptive statistics with 143 observations. And the p – value JB statistics for FA, FLEV, EBLR, SBLR, and ROA variables were abnormally distributed at 0.000000,0.000000, 0.000000, 0.000229 and 0.000000 respectively, while FS is normally distributed at 0.808705. This is above 0.05 probability level of significance. The maximum values for the variables used for FS, FA, FLEV, EBLR, SBLR, & ROA were 10, 126, 69.69750, 0.687500, 0.666700, 13.44230 respectively, while the minimum values for the variables employed were 8, 4, -170.1239, 0.000100, 0.000700, and 0.023600 for FS, FA, FLEV, EBLR, SBLR, and ROA respectively.

4.3       Test of Hypotheses

Hypothesis 1

Ho1:     Firm Size does not significantly affect Environmental Bottom Line Reporting (EBLR) of quoted commercial banks in Nigeria.

H1:       Firm Size significantly affects Environmental Bottom Line Reporting (EBLR) of quoted commercial banks in Nigeria.

Table 2: Panel Least Square Regression analysis showing the effect of FS ON EBLR.

Dependent Variable: EBLR
Method: Panel Least Squares
Date: 01/21/22   Time: 10:31
Sample: 2010 2020
Periods included: 11
Cross-sections included: 13
Total panel (balanced) observations: 143
Variable Coefficient Std. Error t-Statistic Prob.
C 0.061186 0.214024 0.285885 0.7754
FS 0.008911 0.023411 0.380644 0.7040
R-squared 0.001027     Mean dependent var 0.142510
Adjusted R-squared -0.006058     S.D. dependent var 0.150786
S.E. of regression 0.151243     Akaike info criterion -0.925977
Sum squared resid 3.225277     Schwarz criterion -0.884538
Log likelihood 68.20733     Hannan-Quinn criter. -0.909138
F-statistic 0.144890     Durbin-Watson stat 0.344592
Prob(F-statistic) 0.704040

 Source: Review 8, Regression Output, 2022

Interpretation of Regression Coefficient Result

The following regression equation was obtained from table 2:

EBLR = 0.061186 + 0.008911

With the model above, it is possible to ascertain the relationship between FS and EBLR of quoted commercial banks. If all other factors are held constant, an increase in one unit of the FS results into 0.008911 increase in EBLR. In addition, the slope coefficient (β1 = 0.008911) indicates that Firm Assets positively relates with EBLR, with a t – statistics of 0.380644 as well as P – value of0.7040< 0.05. This means that Firm size has an insignificant positive relationship with EBLR at 5% level of significance. The adjusted R – squared for the model is -0.006058 meaning that the Independent variables explained -0.606% of the variation in EBLR of quoted commercial banks. The probability value of the F – statistics = 0.704040 implies that the regression model is insignificant in predicting the effect of Firm size on banks’ Environmental Bottom Line Reporting (EBLR). The significance between the variable is more than a = 0.05.

Decision:

Going by the rule of thumb, since the probability of the test = 0.7040 is more than the a – value of 0.05;

Conclusion:

Therefore H01 is accepted which confirms that Firm Size does not significantly effect on Environmental Bottom Line Reporting of quoted commercial banks in Nigeria at 5% level of significance.

Hypothesis 2

Ho2:     Firm Age (FA) has no significant effect on Social Bottom Line Reporting (SBLR) of   quoted commercial bank in Nigeria.

H1: Firm Age has significant effect on Social Bottom Line Reporting (SBLR) of quoted commercial bank in Nigeria.

Table 3: Panel Least Square Regression analysis showing the effect of FA on SBLR.

Dependent Variable: SBLR
Method: Panel Least Squares
Date: 01/21/22   Time: 10:43
Sample: 2010 2020
Periods included: 11
Cross-sections included: 13
Total panel (balanced) observations: 143
Variable Coefficient Std. Error t-Statistic Prob.
C 0.323995 0.016021 20.22265 0.0000
FA -0.000359 0.000290 -1.239531 0.2172
R-squared 0.010779     Mean dependent var 0.307692
Adjusted R-squared 0.003764     S.D. dependent var 0.109595
S.E. of regression 0.109389     Akaike info criterion -1.573926
Sum squared resid 1.687198     Schwarz criterion -1.532488
Log likelihood 114.5357     Hannan-Quinn criter. -1.557088
F-statistic 1.536438     Durbin-Watson stat 0.920775
Prob(F-statistic) 0.217208

Source: Review 8, Regression Output, 2022.

Interpretation of Regression Coefficient Result

The following regression equation was obtained from table 3:

SBLR = 0.323995 – 0.000359

With the model above, it is possible to ascertain the relationship between FA and SBLR of quoted commercial banks in Nigeria. If all other factors are held constant, an increase in one unit of the FA results into 0.000359 decrease in SBLR. In addition, the slope coefficient (β1 = -0.000359) indicates that Firm Assets negatively relates with SBLR, with a t – statistics of -1.239531 as well as P – value of 0.2172< 0.05. This means that FA has a significant negative relationship with SBLR at 5% level of significance. The adjusted R – squared for the model is 0.003764 meaning that the Independent variables explained 0.3764% of the variation in SBLR of listed Beverage Companies. The probability value of the F – statistics = 0.217208 implies that the regression model is insignificant in predicting the effect of Firm Age on Social Bottom Line Reporting (SBLR). The significant between the variable is less than a = 0.05.

Decision

Going by the rule of thumb, since the probability of the test = 0.2172 is less than the a – value of 0.05.

Conclusion:

Therefore H02 is accepted which confirms that Firm Age has aninsignificant positive effect on quoted commercial banks in Nigeria at 5% level of significance.

Hypothesis 3

Ho3:     Firm Leverage (FLEV) has no significant effect on Economic Bottom Line Reporting of quoted commercial bank in Nigeria.

H1:       Firm Leverage (FLEV) has a significant effect on Economic Bottom Line Reporting (ROA) of quoted commercial bank in Nigeria.

Table 4: Panel Least Square Regression analysis showing the effect of FLEV on ROA.

Dependent Variable: ROA
Method: Panel Least Squares
Date: 01/21/22   Time: 12:43
Sample: 2010 2020
Periods included: 11
Cross-sections included: 13
Total panel (balanced) observations: 143
Variable Coefficient Std. Error t-Statistic Prob.
C 0.808926 0.234840 3.444588 0.0008
FLEV 0.038292 0.012229 3.131350 0.0021
R-squared 0.065020     Mean dependent var 0.922724
Adjusted R-squared 0.058389     S.D. dependent var 2.859170
S.E. of regression 2.774443     Akaike info criterion 4.892664
Sum squared resid 1085.352     Schwarz criterion 4.934103
Log likelihood -347.8255     Hannan-Quinn criter. 4.909503
F-statistic 9.805352     Durbin-Watson stat 0.582400
Prob(F-statistic) 0.002116

Source: Review 8, Regression Output, 2022.

Interpretation of Regression Coefficient Result

The following regression equation was obtained from table 4:

FLEV = 0.808926 + 0.038292

With the model above, it is possible to ascertain the relationship between FLEV and ROA of listed Beverage Companies. If all other factors are held constant, an increase in one unit of the FLEV results into 0.038292 increase in SBLR. In addition, the slope coefficient (β1 = 0.038292) indicates that Firm Leverage positively relates with Economic bottom line (ROA), with a t – statistics of 3.131350 as well as P – value of 0.0021< 0.05. This means that Firm Leverage has a significant positive relationship with ROA at 5% level of significance. The adjusted R – squared for the model is 0.058389 meaning that the Independent variables (FLEV) explained 5.84% of the variation in ROA of quoted commercial banks in Nigeria. The probability value of the F – statistics = 0.002116 implies that the regression model is significant in predicting the effect of Firm Leverage on Return on Assets (ROA) of quoted commercial banks in Nigeria. The significant between the variable is less than a = 0.05.

Decision

Going by the rule of thumb, since the probability of the test = 0.0021 is less than the a – value of 0.05.

Conclusion

Therefore H3 is accepted which confirms that Firm Leverage has a significant positive effect on Economic Bottom Line (ROA) of quoted commercial banks in Nigeria at 5% level of significance.

DISCUSSION OF FINDINGS

The Regression analysis result of hypothesis one in Table 2 indicates that Firm Size has an insignificant positive effect on the Environmental Bottom Line reporting of banks. Positive effect implies that an increase in Firm Size (FS) will tend to increase the level of Environmental reporting and vice versa. This finding is in contrast with the studies of Sulaiman et al (2014), and Abubakar (2017) which found positive but significant relationship between Firm size and environmental reporting. It is also in line with the studies of Habbash (2015) and Moshud, Sani & Olanrewaju (2021) which found negative and non-significant association between Firm size and Environmental disclosure.

The result of hypothesis two in Table 3 shows that there is a negative but non-significant effect of Firm Age (FA) on Social Bottom Line Reporting. This negative impact implies that an increase in Firm Age will tend to decrease the level of Social Bottom Line reporting. This is consistent with the findings made by Moruff, Salisu, Muhammed, Garba, & Nasim (2021), Hossain et al (2018), Badulescu et al. (2018) & Akbas (2014) which showed a statistical non-significant relationship that exist between Firm Age and sustainability return. In the contrary, Waluyo (2017) found a significant association between firm age and corporate social responsibility.

The result of hypothesis three in table 4 reveals that there is a significant positive association between Firm Leverage (FLEV) and banks’ Return on Assets. The positive impact implies that an increase in Firm Leverage will tend to increase the level of reported economic benefits (ROA). This finding is inconsistent with the studies of Kaluarachchi, Fernando, & Mallawarac (2014)which found a non – significant relationship between financial leverage and return on assets. In addition, Nadeem et al (2015), Schutte et al (2008), and Rahman et al (2020) found a negative and significant relationship between leverage and ROA. In the contrary, Aloshaibat (2021) found a non-significant association between firm leverage and ROA.

CONCLUSION AND RECOMMENDATIONS

5.3  Recommendations

Based on the findings of the study,

  1. It is recommended therefore that those at the helm of affairs of commercial banks should engage more in sustainable environmental performance activities and reporting as these does not depend on size of the business. Commercial banks should design and implement policies to foster continuous involvement that contributes positively towards the improvement of sustainable environment and consequently reporting on environmental bottom line. Especially in the area of afforestation, erosion control etc.
  2. Since sustainable social practices does depend on age of a company, the Central Bank of Nigeria (CBN) should make policies that will persuade and encourage banks irrespective of age to improve on and continuously align socially sustainable related performance practices as well as its
  3. The CBN should also update the Regulatory Prudential Guidelines for commercial banks to include among other things additional responsibility to external auditors to verify environmental and social claims made by banks in their annual report and consequently make a statement to that effect in other matter paragraph in the Auditors Report.

5.2 Conclusion

The broad objective of this study is to ascertain the effect of corporate characteristics on Triple Bottom Line Reporting.

The result of the study shows that non-financial corporate characteristics elements (that is Firm Size and Firm Age)have a non-significant effect on commercial banks in Nigeria, this implies that the level of environmental & social performance and reporting does not depend on the size or age of company.

The financial corporate characteristics (that is Firm leverage) of banks has a positive significant effect on Economic bottom line reported (that is ROA), this is because savings, demand and term deposits of customers are liabilities to banks, These deposits are applied by banks in their lending activities to earn interest incomes and consequently increase economic benefits.

Therefore, we conclude that non-financial corporate characteristics have no effect on Triple bottom line performance and reporting of quoted commercial banks in Nigeria.

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