Board characteristics and sustainable energy performance of selected companies in South Africa

Sustainable Production and Consumption 18 (2019) 190–199

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Board characteristics and sustainable energy performance of selected companies in South Africa ∗

Michael Bamidele Fakoya , Mancheleng Vanessa Nakeng Africa Centre for Sustainability Accounting and Management (ACSAM), School of Accountancy, University of Limpopo, South Africa

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Article history: Received 22 October 2018 Received in revised form 24 January 2019 Accepted 3 February 2019 Available online 19 February 2019 Keywords: Corporate governance Environmental sustainability performance Energy usage Johannesburg Stock Exchange

a b s t r a c t The study examines the influence of board characteristics on environmental sustainability performance. Companies’ sustainability performance is affected by many factors such as board composition, lack of knowledge, policies and resources of companies, competition from other companies and market trends. The King IV Code of Corporate Governance suggests that the composition of board members ought to contain a diversity of race and gender and independence. The Code states that the board members should consist of both independent members and non-independent members that would act in the interest of the companies. The study used the multiple regression analysis to analyse data from Johannesburg Stock Exchange (JSE)’s Socially Responsible Index (SRI) listed banking and retail companies from 2007–2017 to test how board characteristics influence environmental (energy usage) sustainability of JSE SRI listed firms. Results indicate that the number of female board members has a negative and insignificant influence on corporate energy usage; board independence positively and significantly influences energy usage, and market capitalisation has a positive but an insignificant influence on energy usage. The study suggests that though not all board characteristics influence companies’ environmental performance, having a considerable number of independent board members could have a positive impact on environmentally-related decisions. © 2019 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

1. Introduction The challenge of focusing exclusively on financial returns by companies’ management while striving to be socially and environmentally responsible is daunting. In recent times, corporate sustainability performance has been amplified because of the impact of companies’ activities on both society and the environment. Moreover, the characteristics of those entrusted with corporate governance are crucial to achieving a balance between satisfying the craving for a higher return to the shareholders and meeting the needs of the different stakeholders. As such, it is expedient to examine how the different characteristics of the board of directors can influence improved sustainability performance. According to Meinzen-Dick et al. (2014), gender is not the only characteristics that affect the sustainability performances of companies. However, many factors affect the sustainability performances of companies such as company size and industry type. Notwithstanding, gender distribution is believed to affect the environmental sustainability performance significantly (Kassinis et al., 2016). Also, having a sustainability-focused ∗ Corresponding author. E-mail addresses: [email protected] (M.B. Fakoya), [email protected] (M.V. Nakeng).

workforce can influence improvement in the environmental performance of companies (Rae et al., 2015). Companies’ can modify existing strategy to improve sustainability performance from both environmental and social perspectives (Ezzi and Jarboui, 2016). Bukair and Rahman (2015) argue that the sustainability performance of industries is not only influenced by the gender or race of the board of directors but by the chief executive officer’s (CEO) age and the CEO’s duality as well. Although some companies have less challenge with maintaining energy efficiency (Clancy et al., 2017); however, they strive to enhance their social sustainability performance to ensure legitimacy (Tantawi and Youssef, 2012). Again, companies with a large board membership are said to experience improved environmental performance (Kassinis et al., 2016). Companies’ operating structures can affect their sustainability performances (Keeble et al., 2003) depending on their selected projects (Searcy et al., 2005). Race distribution can affect the board of director’s choice of sustainability projects (Preston and McLafferty, 2016). Moreover, the educational background of board members can affect companies’ sustainability performance regardless of gender and race (Vick and Fontanella, 2017). A company’s energy usage is affected by how its energy is allocated and utilised by the different departments regardless of its size (Wilson et al., 2016). However, a company’s size can

https://doi.org/10.1016/j.spc.2019.02.003 2352-5509/© 2019 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

M.B. Fakoya and M.V. Nakeng / Sustainable Production and Consumption 18 (2019) 190–199

influence the type of sustainability projects it undertakes to implement (Hopenhayn, 2016). Moreover, board independence can influence its choice of environmental and social project (Ortas et al., 2017). As such, both the social and environmental aspects of corporate sustainability projects should be considered when measuring the impact on the financial growth of the company in the long-term (Jang et al., 2017). In contrast, some boards embark on sustainability projects for economic benefits rather than to improve its sustainability performance (Evangelista et al., 2017). However, it is the growth in company size that affects its cost of capital and not its sustainability performance (Al-Dhamari et al., 2014). This paper argues that the board of directors makes the bulk of corporate sustainability decisions, it is not entirely clear about improving sustainable energy performance which board characteristic influences the choice of projects to improve sustainable business practice. While sustainable energy usage may well encroach on corporate financial performance, it is critically significant to the success of corporate sustainability performance. Hence, it is reasonable to assume that sustainable energy usage decisions will be influenced by board characteristics that consider sustainability issues to be motivated by a concern for the environment and, therefore, with a desire to improve the condition of our natural environment or in the least, to reduce the rate of damage caused to it. However, it is uncertain that such decisions to improve and promote sustainable energy use are influenced by only one feature of the board for environmental concern. Moreover, there is no evidence to suggest that current conventional business energy usage may well have been misplaced despite that the efficacy of conventional business practices in preserving the natural environment through efficient energy usage is unreliable. Hence, this paper examines which of the board characteristics influence sustainable energy performance among selected Johannesburg Stock Exchange (JSE) Socially Responsible Investment (SRI) Index companies. 2. Materials and methods 2.1. Stakeholder theory The stakeholder theory posits that value creation is an essential and explicit component of doing business whereby managers articulate specific relationships among stakeholders to create a sense of shared value (Freeman et al., 2004). There is a need to embrace a diversity of knowledge and value-based decisionmaking approach to tackle the growing, complex and dynamic nature of environment-related challenges confronting organisations today (Reed, 2008). The stakeholder theory emphasises the need to establish a good relationship with stakeholders to improve the company’s performance (Ranängen, 2017). Moreover, stakeholder engagement companies can achieve improved environmental performance that satisfies the different needs of stakeholders (Arayssi et al., 2016). Board members regardless of whether they are independent or not have a duty to make decisions on energy usage plans which are beneficial to the firm either with much firm size or not and other stakeholders who will be consistent for the improvement of environmental performance (Liao et al., 2015). Hence, since different stakeholders have different needs, organisations should endeavour to find a way to balance these expectations without alienating the needs of other stakeholders. 2.2. Legitimacy theory Legitimacy theory presumes that companies need to behave in accord with societal values and norms to ensure its continued existence (Dowling and Pfeffer, 1975). The legitimacy theory adopts that a company’s actions are socially desirable and

191

should be based on societal values (Suchman, 1995: 574). Companies need to create congruence between the values resulting from their activities and the norms acceptable by the larger society in which they belong. In achieving a balance between corporate and societal values, companies should strive to manage the disparity which exists between the two values to avoid potential threats to a company’s legitimacy (Dowling and Pfeffer, 1975). Since it is often challenging for companies to gain legitimacy support from its stakeholder, they constantly pursue legitimacy through a variety of approaches and practices (Ashforth and Gibbs, 1990). As such, if the board of directors in a company implement environmentally-related projects, it will maximise the company’s sustainability performance thereby enhancing its legitimacy (Hummel and Schlick, 2016). Environmental projects and community engagements activities such as skills development and disclosure of sustainability activities can foster legitimacy and enhance sustainability performance (Fernando and Lawrence, 2014). Often some environmental projects are negatively correlated with the environmental performance of companies (Liao et al., 2015). As such, corporate boards should pursue those actions that enhance the values of both the society and environment by harnessing the different attributes of its members. 2.3. Agency theory It is erroneous to assume that good corporate governance and environmental sustainability should work together to ensure an environmentally-responsible company due to the recent spate of corporate environmental negligence that resulted from agency problems. It seems that the broadening of managerial responsibilities to meet the needs of various stakeholder groups have exacerbated the occurrence of agency problems (Heath and Norman, 2004). While the agency theory encourages the board of directors to act in the interest of its shareholders (Bhuiyan and Hooks, 2016); companies with active independent board members tend to protect its environmental reputation (Zhang, 2012). However, disputes between the independent board members and the executive board provide avenues for companies’ management to pursue their self-interest (Bhuiyan and Hooks, 2016). As such, having more female members can increase monitoring and provide strategic ways to resolve disputes among board members (Arayssi et al., 2016). Such intervention can provide opportunities to implement strategies to achieve improved environmental performance as it increases integrity among board members (Bhuiyan and Hooks, 2016). Despite that board characteristics can be harnessed to further shareholder interests; such attributes should be used to resolve conflicts arising between environmental and financial performances. 2.4. Environmental sustainability performance and gender Companies’ environmental policies often incorporate ways of saving energy, and the board members tend to have a different view of implementing these policies based on their gender (Fraune, 2016). If both females and males board members agree on ways to manage corporate energy usage, it could improve the company’s environmental sustainability (Sun and Hong, 2017). Moreover, female board members find it easier to make decisions on how to uplift their companies’ environmental sustainability and are likely to add more value on such decisions as energy usage (Liao et al., 2015). Additionally, companies that whose members are more gender diversified are likely to be more involved in improving its sustainability performance (Hansen et al., 2016). The involvement of female board members in most companies’ environmental projects tends to improve their sustainability performance (Kassinis et al., 2016). However, Hansen et al.

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Table 1 Descriptive statistics on energy usage. Source: Authors’ results of descriptive data (2018). Energy usage Board independence Females Market capitalisation Sales ROA

2.6. Board independence performance

Obs

Mean

Std. Dev.

Min

Max

308 308 308 308 308 308

293450.4 55.18909 16.39818 2030133 7.369351 11.48705

257760.7 26.21765 12.23206 2102408 12.21634 12.57746

0 0 0 0

999000 88.89 60 9980600 83.82 46.85

−88.91 −30.52

(2016) found a weak relationship between sustainability performance and board gender diversity. On the other hand, female board members are found to enhance a company’s environmental sustainability performance through communication mechanisms among stakeholders and participation in environmental projects’ decision-making (Arayssi et al., 2016). Most companies are opting for energy conservation as an environmental sustainability approach to improve their environmental performances which are instead proposed by male rather than female members (Holley and Lecavalier, 2017). Notwithstanding, the benefits of pursuing energy usage plans include cost-savings and resource efficiency (Maistry and Annegarn, 2016). Moreover, female board members prefer the use of alternative energy savings to improve companies’ environmental performance (Ding et al., 2014). A gender-diverse company often approves of renewable energy systems as an alternate energy source to improve their environmental performance (Cucchiella et al., 2017). Notwithstanding, it is important to determine whether gender characteristics is an issue that influences corporate environmental sustainability in the selected banking and retail companies in South Africa. Hence, we developed the hypothesis below: H1: The number of female board members does not influence environmental sustainability performance (energy usage) among JSE SRI banking and retail companies. 2.5. Firm size and environmental sustainability performance Large companies receive more scrutiny on their environmental performance from the stakeholders than the smaller companies because of their size (Mensah, 2014). Some industries such as manufacturing and retail consume more energy in their operations than others because of their size (Cho, 2016). As such, firm size is a crucial factor when determining a firm’s energy consumption (Safa et al., 2017). For instance, most banks have high energy consumption from the daily use of technology and the number of branches they operate (Cho, 2016). Essentially, companies need to evaluate whether the number of their field operations need to be reconsidered when planning for energy usage strategies to improve environmental performance (Safa et al., 2017). To measure a firm’s environmental performance, the board of directors should consider whether their firm size significantly affects their environmental sustainability (Solakoglu and Demir, 2016). Moreover, Azizi et al. (2015) argue that companies’ board of directors should consider their firm size when formulating their energy usage strategies to improve their environmental performance to boost firm performance. Knowing whether firm size is crucial in determining the environmental sustainability performance of selected banking and retail companies in South Africa will add to the current debate on what influences corporate environmental performances. Hence, we developed the hypothesis below: H2: Firm size (market capitalisation) does not influence environmental sustainability performance (energy usage) among JSE SRI banking and retail companies.

on

environmental

sustainability

Board of directors is answerable for directing their companies’ activities and are known for making decisions which are suitable for the company (Rao and Tilt, 2016). Although most companies’ board are male-dominated with executive positions are not independent do get involved in the environmental sustainability projects of their companies (Abad et al., 2017). However, independent board members should support their firm environmental sustainability projects especially the ones involving energy and climate changes (Dixon-Fowler et al., 2017) after understanding all aspects of economic, social and environmental sustainability that improve its performances (Yakovleva, 2017). Also, most companies that are environmentally-friendly have more female board members because they tend to be independent on matters relating to the firm’s sustainability performance to satisfy their stakeholders (Post et al., 2015). While the conduct of most independent members of the board can influence sustainability actions like energy usage savings (Vallascas et al., 2017); in contrast, some independent board members contribute less to sustainability issues of their companies (Vallascas et al., 2017). Moreover, having a balanced board with significant independent members would assist to satisfy their stakeholder needs regarding their environmental sustainability performance (Harjoto et al., 2015). To achieve an improved environmental performance, companies should consider addressing their environmental concerns as it arises during the planning and decision-making process to allow the independent board members voice their concerns (Dixon-Fowler et al., 2017), through independent evaluation to manage their companies’ environmental practices (De Villiers et al., 2011). It is, therefore, essential to determine whether having a considerable number of independent board members can influence environmental sustainability performance in the South African banking and retail companies. Hence, we developed the hypothesis below: H3: Board independence does not influence environmental sustainability performance (energy usage) among JSE SRI banking and retail companies. 2.7. Method The study used the multiple regression analysis to estimate models to describe the distribution of the response variable (energy usage) with the help of several predictor variables (female board members, board independence, firm size, sales growth and return on assets). The rationale is to determine predictor variables that help to explain significant variation in the response variable (Aiken et al., 1991; Cohen et al., 2014). The identification of significant predictors will help in managing risks of and maximise the odds of favourable outcomes. Energy usage in any company may depend on several issues such as industrial charters, size, type of energy technology available or used, type of energy solutions designed for company buildings and transport systems, prices of alternative energy sources and sustainability goal or agenda of the company. However, we intend to understand the sustainability behaviour of the selected listed companies by analysing the relevant data. Also, we seek to determine whether those factors mentioned above are relevant to understanding the sustainability behaviour of the selected listed companies. The study sampled 28 banking and retail companies on the JSE SRI Index for 11 years (2007–2017). The study made use of these banking and retail companies because their data are steadily available on the stock exchange for the selected period and their character on sustainability engagement activities. Additionally, they applied and complied with the King IV corporate

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Table 2 Two-sample test with equal variances — sales growth and ROA (unpaired). Source: Authors’ results of t-test (2018). Variable

Obs

Mean

Std. Err.

Std. Dev.

[95% Conf.

Interval]

Sales growth ROA Combined Diff

308 308 616

7.369221 11.48773 9.428474 −4.11851

0.696136 0.717023 0.506133 0.999363

12.21713 12.5837 12.5619

5.99942 10.07683 8.434515 −6.08109

8.739022 12.89863 10.42243 −2.15592

diff = mean(sales) - mean(roa); t = −4.1211; Ho: diff = 0; degrees of freedom = 614; Ha: diff < 0; Ha: diff != 0; Ha: diff > 0; Pr(T < t) = 0.0000; Pr(|T| > |t|) = 0.0000; Pr(T > t) = 1.0000. Table 3 Regress test for energy usage. Source: Authors’ results of regress test (2018).

code of governance. 26 retails, and seven (7) banking companies were listed on the JSE as at the time of data collection (30 January 2018). Of the 28 sampled companies, 21 or 75% were retail companies, and seven (7) or 25% were banking institutions. Data was collected from the companies integrated annual reports which are publicly available and through the IRESS database. The study employed correlational research design and a quantitative approach using the panel data analysis for the fixed effect model, random effect model and the Hausman test to identify a suitable model to analyse the data. Below is the formulated regression equation for the study: ENUSAGEit = αit + β FemBoardit1 + β BoardIndepenit2

+ β FirmSzit3 + β SalesGroit4 + β ROAit5 + ε

(1)

Where: ENUSAGEit = Energy Usage α = intercept β = gradient/slope β FemBoardit1 = Number of females on the board β BoardIndepenit2 = proportion of non-executive board of directors β FirmSzit3 = Firm Size (Market Capitalisation) β SalesGroit4 = sales growth β ROAit5 = Return on Asset ε = error In testing the hypothesis above, the dependent variable for the study is energy usage, and independent variables are the number of female board members, board independence and firm size. Sales growth and return on assets are the control variables in

Table 4 Durbin–Watson test (energy usage). Source: Authors’ results of autocorrelation test (2018). Durbin–Watson d-statistic (6, 308) = 1.009233

this study. The rationale for the use of these control variables was based on the assumption that the number of female board members, board independence and firm size are not the only variables that are likely to influence a company’s energy usage. We argue that a company’s sales growth spurred by an increase in the volume of inventory turnover (and other sales generating activities) and the effectiveness of its management team measured by return on asset (ROA) could have considerable influence on its energy usage level. 3. Results Results in Table 1 indicates 308 observations for the JSE SRI banking and retail companies between 2007–2017. Mean for energy usage (Rand) is 293450.4 while independent variables board independence, females and market capitalisation (Rand) is 55.18909, 16.39818, and 2 030 133 respectively. The mean variable for the control variables is as follows sales growth (%) and ROA (%) is 7.369351 and 11.48707 respectively. Furthermore, Table 1 indicates a minimum and maximum variation of 0 and 999 000 for energy usage, and the minimum and maximum for independent variables are as follows; board independence 0 and 88.9, females 0 and 60 and market capitalisation 0 and 9 980 600, while for the control variables sales growth −88.91 and 83.83 and ROA −30.52 and 46.85 respectively.

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Table 5 Durbin’s alternative test for autocorrelation (energy usage). Source: Authors’ results of autocorrelation test (2018) a

Durbin’s alternative test for autocorrelation (energy usage) Breusch–Godfrey LM test for autocorrelation (energy usage)b

lags(p)

chi2

Df

Prob > chi2

1 1

96.919 75.018

1 1

0.0000 0.0000

a

H0 : no serial correlation. Null hypothesis: residuals are homoscedastic Alt: residuals are not homoscedastic. H0 : no serial correlation. Null hypothesis: residuals are not serially correlated; Alternate hypothesis: residuals are serially correlated. The table above indicates a p-value of 0.0000 which is less than 0.005 which means that the null hypothesis cannot be rejected therefore there is no serial correlation between energy usage and independent variables.

b

Table 2 present the t-test result using a combined sample of 616 obs for Sales growth and ROA to determine its influence on energy usage. The t-test ascertains if the variances in the two samples are the same. Moreover, the control variables tested are appropriate because they are of a different population and are independent variables. The regress tests are based on the dependent variable — energy usage and the independent variables which are as follows; board independence, females and market capitalisation lastly on control variables which are sales growth and ROA. Table 3 indicates the regression results for energy usage and checking if the number of observations shows any effect of autocorrelation which may have prediction errors in the regression results. Table 3 indicates the significant statistics where the pvalues are taken note of; the significant level is at 95% where p-values > 0.05 are considered insignificant. Result in Table 3 indicates a Prob > F = 0.0000 making the model suitable and significant because the independent variables jointly affect the dependent variable. An R-squared of 0.1486 indicates the degree of variation of energy usage as influenced by the independent variables. Moreover, the residual is the error term which explains that the variation in energy usage can be explained by some independent variables not stated in this study. To further explain this result, the null hypothesis is used as follows: -

• Null hypothesis: independent variables do not jointly affect energy usage, and

• Alternative hypothesis: independent variables do jointly affect energy usage. Therefore, F (5, 302) = 10.54 and Prob = 0.0000 < 0.005. Meaning that we reject the null hypothesis while accepting the alternative hypothesis since the independent variables do jointly affect the dependent variable. Table 4 tests for autocorrelation where the significant statistics with p-values at a significant level of 95% where p-values > 0.05 are interpreted as insignificant. In some of the tests below, autocorrelation residuals were used to determine the differences between the dependent variables and the predicted value which were predicted using the data through the regression test. The table below is based on the dependent variable — energy usage while independent variables are as follows; board independence females, market capitalisation and control variables as sales growth and ROA. The Durbin–Watson test is to detect autocorrelation in the panel analysis. Generally, the Durbin–Watson statistic is between 0 and 4, where a value of 2 or approximately 2 indicates no autocorrelation in the sample. Table 4 shows Durbin-Watson statistic results as 1.009233 shows no autocorrelation in the study sample. The table below tests for serial correlation between the given time series and lagged version of the study data. Table 5 indicates a p-value of 0.0000 less than 0.005 for both Durbin’s alternative test for autocorrelation (energy usage) and Breusch–Godfrey LM test for autocorrelation (energy usage)

Table 6 Shapiro–Wilk W test for normal data (energy usage). Source: Authors’ results of autocorrelation test (2018). Variable

Obs

W

V

Z

Prob>z

EU

308

0.93153

14.931

6.354

0

Null hypothesis: residual is not normally distributed. Alt: residual is normally distributed the table above indicates a p-value of 0.0000 which is less than 0.005 which means the null hypothesis cannot be accepted and the alternative is accepted. Table 7 Breusch–Pagan/ Cook–Weisberg test for heteroskedasticity (energy usage). Source: Authors’ results of heteroskedasticity test (2018). Ho: Constant variance Variables: fitted values of energy usage chi2(1) = 10.50 Prob > chi2 = 0.0012

meaning that the null hypothesis is rejected while the alternative hypothesis is accepted. Therefore, both test shows no serial correlation between the dependent and independent variables. Table 6 is a test for normality of data using the Shapiro–Wilk W test. The scatter plot (Fig. 1) shows the relationship between energy usage and board independence, female board members and market capitalisation lastly on control variables which are sales growth and ROA. From Fig. 1 there is no clear indication of the relationship between the energy usage and females and board independence variables since it does not bear the resemblance of a linear pattern as indicating a negative correlation between variables the results as energy usage decreases the market capitalisation increases and vice versa. Table 7 is based on the dependent variable — energy usage while independent variables are as follows; board independence females, market capitalisation and control variables as sales growth and ROA. Heteroskedasticity test is used to test the existence of variance errors that may be constant across the observations if the constant errors exist in the observations they are called homoscedastic. In Table 7, the chi-square is 0.0012 which illustrates that there is no homoscedastic meaning there is no constant error in the observations. Table 8 is the result of the correlation matrix. The correlation between the independent variable board independence and itself is perfect at +1, the same applies to variables such as females and market capitalisation. Moreover, all control variables are correlated perfectly at +1.0000. The correlation matrix table above shows a strong but negative relationship between board independence and females by −0.6035 and a weak negative correlation of −0.2226 for board independence and market capitalisation, while the percentage of female board members and market capitalisation show an extremely weak positive correlation at 0.0326 and 0.1516 for market capitalisation and sales growth. The control variable sales growth and the independent variable board independence show an extremely weak

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Fig. 1. Scatter plot for energy usage. Source: Authors’ results of the scatter plot (2018). Table 8 Correlation matrix for dependent variable energy usage. Source: Authors’ results of the correlation matrix (2018). Board independence Board independence Females Market capitalisation Sales growth ROA _cons

Females

Market capitalisation

Sales growth

ROA

_cons

1

−0.6035 −0.2226 −0.1632 −0.079 −0.5676

1

−0.0326 0.1516 −0.0289 −0.0255

Table 9 VIF – Multicollinearity test – energy usage. Source: Authors’ results of multicollinearity test (2018). Variable

VIF

1/VIF

Board independence Females Sales growth ROA Market capitalisation Mean VIF

1.81 1.67 1.25 1.23 1.11 1.41

0.552663 0.600029 0.800953 0.814162 0.902168

but negative relationship of −0.1632 and an extremely weak but positive relationship between independent variable market capitalisation and ROA of 0.0041. Table 9 is the result of the multicollinearity test. The multicollinearity test was performed to enhance the validity of the multiple linear regression. However, there could be statistical biases in the probability value (p-value) in case the independent variables correlate with one another. As such, the Variance Inflation Factor (VIF) was performed to test if there is multicollinearity. Based on a result of 1.41 (VIF), we can conclude that there is no multicollinearity between the independent variables since the VIF is less than 5. Table 10 presents the fixed effect model for energy usage. Table 10 indicates the significant statistics where the p-values is set at the significant level of 95% where p-values > 0.05 are deemed insignificant, and it indicates that there is a Prob>F = 0.0000 which make the model good. Results in Table 10 indicates that board independence positively and significantly influences

1

−0.0155

1

0.0041 −0.134

−0.3966 −0.0237

1

−0.1967

1

energy usage with a p-value of 0.000. However, results from Table 10 indicate that the number of female board members has a positive but insignificant influence on energy usage (pvalue of 0.294). Also, results from Table 10 shows that market capitalisation positively but insignificantly affect energy usage with a p-value of 0.111. However, sales growth negatively and insignificantly influence energy usage (a p-value of 0.509). Also, ROA has a positive but an insignificant influence energy usage (a p-value of 0.261). The Hausman test was used in deciding the appropriate model for the sample. The result indicates the random effects as the appropriate model. Hence, Random Effect Model result is presented below. Table 11 indicates the significant statistics where the regressors and p-values are taken note of at a significant level of 95% where p-values > 0.05 is interpreted as insignificant. The above results show that board independence has a positive but significant influence on energy usage with a p-value of 0.000. Additionally, results in Table 11 indicates that the number of female board members has a positive yet an insignificant influence on energy usage as indicated with a p-value of 0.258. Furthermore, results from Table 11 indicate that market capitalisation has a positive but an insignificant influence on energy usage with a p-value of 0.081. Moreover, sales growth is insignificantly and negatively influences energy usage (a p-value of 0.539). Also, ROA positively but insignificantly influences energy usage (a p-value of 0.275). Table 12 present the Hausman test. In selecting the appropriate model, we used the Hausman test.

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M.B. Fakoya and M.V. Nakeng / Sustainable Production and Consumption 18 (2019) 190–199 Table 10 Fixed effect model for energy usage. Source: Authors’ results of the fixed effects model (2018).

Table 11 Random effect model for energy usage. Source: Authors’ results of the random effect model (2018).

• Null hypothesis: random effect model is the appropriate model for the sample.

• Alternative hypothesis: the fixed effect is the appropriate model for the sample.

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Table 12 Hausman test on energy usage. Source: Authors’ results of the Hausman test (2018).

BoardIndependence Females Market capitalisation Sales growth ROA

(b)

(B)

(b-B)

Fixed

Random

Difference

3501.557 1676.627 0.01099 −755.53 2439.053

3325.139 1699.527 0.011544 −688.654 1846.257

176.4182 −22.8998 −0.00055 −66.8766 592.7965

sqrt(diag(V_b-V_B)) S.E.

188.3919 532.2647 0.00189 220.7852 1350.292

b = consistent under Ho and Ha; obtained from xtreg; B = inconsistent under Ha, efficient under Ho; obtained from xtreg; Test: Ho: difference in coefficients not systematic chi2(4) = (b − B)′ [(V _b − V _B)^(−1)](b − B) = 1.76 Prob > chi2 = 0.7800

The results from Table 12 indicate that the use of the random effect model is the most appropriate for the sample with a Prob > chi2 = 0.7800 which is higher than 0.05. This means that the null hypothesis cannot be rejected. Therefore, we used the random effect model to determine the relationship between energy usage and independent variables (board independence, females and firm size). 4. Discussion The study determines how board characteristics influence environmental sustainability performance of banking and retail companies on the JSE SRI. This study used 28 banking and retail companies between 2007–2017. The Hausman test was used to determine the appropriate model between the fixed effect model and random effect model with the random effect model deemed to be appropriate because its Prob > chi2 is higher than 0.005. 4.1. Random effect model: Number of female board members and environmental sustainability performance The research hypothesis (H 1 ) states that the number of female board members does not influence environmental sustainability (energy usage) among selected banking and retail companies listed on the JSE SRI. The random effect model results in Table 12 indicates that the number of female board members has a positive yet an insignificant influence on energy usage with a p-value of 0.258 at a significance confidence interval of 95%. Since the p-value of less than 0.05 was set to be significant and p-value greater than 0.05 was set to be insignificant. We conclude that the number of female board members in our sample does not influence energy usage performance. This result is consistent with that of Alazzani et al. (2017) who focused on the influence of female board members on the environmental performance of companies where the statistical results indicated the estimated p-value of 0.446, where the p-value is more significant than 0.05. They conclude that the number of female board members negatively correlates to environmental performance. The study also indicates that whether there is a high or low number of female board members, companies’ environmental performance may not depend on that. Although a company’s sustainability report reflects the values and cultures within the companies and the mechanisms of its corporate governance agenda. In contrast, our result is inconsistent with the study by Post et al. (2015) that examined whether board composition influences environmental performance where board composition involved female representative on board. Their result indicates that gender distribution positively influences environmental performance with a p-value less than 0.05 meaning that increasing the number of female board members can improve the environmental performance of

companies. This shows that there are inconsistencies in results by different scholars on whether increasing the number of female board members will improve the environmental performance of the companies because having a high number of female board members positively influences environmental sustainability performance. These inconsistencies may be because of the influence these female board members commands in the different countries and the impact of their corporate governance regulations. Moreover, the King IV (Institute of Directors in Southern Africa, 2016) indicated that the board of directors of companies should have a balance of gender distribution since many companies have more males on the board than females and should disclose such in their annual integrated reports. Meanwhile, the agency theory suggests that board members of companies whether females or not have to engage more in sustainability projects of the companies and by so doing they will be acting in the best interest of companies (Mori and Towo, 2017). Our results, therefore, support the study hypothesis that the number of female board members does not influence the environmental performance of companies. Hence, the alternate hypothesis is accepted, and the null hypothesis is rejected. 4.2. Random effect model: Firm size (market capitalisation) on environmental sustainability performance The research hypothesis (H 2 ) states that firm size (market capitalisation) does not influence environmental sustainability (energy usage) in selected banking and retail companies listed on the JSE SRI. The random effect model results indicate that market capitalisation has a positive but an insignificant influence on energy with a p-value of 0.081 with a significance confidence interval of 95% where a p-value < 0.05 is considered significant and a p-value > 0.05 insignificant. The results indicate that the bigger the firm size, the higher the occurrence of energy usage of companies. Our result is consistent with that of Lei et al. (2017) where they found that firm size positively influences the environmental performance of companies. Moreover, our result supports that of Azizi et al. (2015) who found that firm size influences energy usage with the suggestion for a need to let employees know about the organisation’s energy efficiency strategies. They further suggest that organisations’ energy usage strategies should be communicated to the individuals frequently to be able to achieve better environmental performance (Azizi et al., 2015). Our results do not sustain the study hypothesis that firm size does not influence the environmental performance of companies. Although result indicates that market capitalisation positively influences energy usage, however, it is insignificant to determine a strong influence on companies’ energy usage performance in the selected companies. Hence, the alternate hypothesis is accepted, and the null hypothesis is rejected.

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4.3. Random effect model: Board independence on environmental sustainability performance Research hypothesis (H 3 ) states that board independence does not influence environmental sustainability (energy usage) in selected banking and retail companies listed on the JSE SRI. Results from the random effect model indicate that board independence positively and significantly influences energy usage with a pvalue of 0.000 with a significance confidence interval of 95% and a p-value < 0.05 is considered significant and a p-value > 0.05 insignificant. This means that by increasing the number of independent board members, there is the likelihood that companies will perform better environmentally through energy usage. Also, the independence of the non-executive board members as advisors to the executive board means they can influence the environmental sustainability performance of companies. According to the King IV Code, companies should have a balanced board of both independent and non-independent board members. The result agrees with that of Safa et al. (2017) where they explain that having a considerable number of independent board members will help to protect the shareholders and enable the board to focus on promoting stakeholders’ interest for better environmental performance. The results, therefore, do not support the study hypothesis that board independence does not influence the environmental performance of companies. Hence, the alternate hypothesis is rejected, and the null hypothesis is accepted. 5. Conclusions Meeting the needs of the different stakeholders by those saddled with corporate governance requires a blend of their different characteristics to achieve a balance between satisfying the demand for a higher return on investment to the shareholders and improving corporate sustainability performance. However, it is indeterminate to conclude that decisions to improve and promote corporate sustainable energy usage are predisposed to only one of the features of the board. From the stakeholder perspective, organisations need to ensure a balance of meeting the different stakeholder’ expectations without alienating the needs of others. Moreover, corporate decisions need to promote societal values and improve environmental performance to legitimise its operations. Board characteristics should be harnessed to resolve conflicts between shareholder interests and environmental and financial performances. The result does not support the notion that an increase in energy usage performance of the companies examined is a direct consequence of an increase in the number of female board members. Also, firm size does not influence improved energy usage in the selected companies but rather indicates an insignificant relationship. However, it is board independence that influences sustainable energy usage in the companies examined. Although not all board characteristics influence sustainable energy performance among selected JSE SRI Index companies, having a considerable number of independent board members is significant in improving companies’ environmental sustainability performance. CRediT authorship contribution statement Michael Bamidele Fakoya: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Writingoriginal draft, Writing- review & Editing. Mancheleng Vanessa Nakeng: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Writing- original draft, Writingreview & Editing.

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