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Asian Business Research Journal 
Vol. 4, 35-43, 2019 
ISSN(E) : 2576-6759 
DOI: 10.20448/journal.518.2019.41.35.43 
© 2019 by the authors; licensee Eastern Centre of Science and Education, USA 

 
 

 

 
Does Electricity Access Relate to Stakeholders’ Satisfaction?  Empirical Evidence 
from Small and Medium Enterprises in North-West, Nigeria 

 
Abubakar Sabo1 
Olusegun Kazeem Lekan2 
 

 
( Corresponding Author) 

 
 

 

1Department of Business Administration, Faculty of Management Sciences, Usmanu Danfodiyo University, 
Sokoto, Nigeria. 
2Department of Business Management, Faculty of Management Sciences, Federal University Dutsinma, Katsina, 
Katsina State, Nigeria. 

 
Abstract 

Several scholarly studies have been conducted to establish relationships of electricity access to 
business financial performance. Nonetheless, little is known about energy-stakeholders’ 
satisfaction relationships. The few studies that do exist on the topic often lack control variable. 
Thus, this is the motivation behind the present study. Therefore, this paper provides an empirical 
analysis of the effect of controlling firm characteristics in the energy-stakeholders’ satisfaction 
relationships. A multiple linear regression model is applied to primary data collected through 
structured questionnaire in five–point rating scale format to test the hypothesis via SPSS version 
23. Results based on cross-sectional survey data from 245 sampled SMEs operating in the city of 
Kaduna, Kano, Katsina and Sokoto state in manufacturing, hotel & restaurant and wholesale & 
retail sector show evidence of a strong positive statistically significant relationships between 
electricity access and SMEs stakeholders’ satisfaction with electricity access t (245) = 9.138, p < 
0.001; firm age t (245) = 4.404, p < 0.001. Subject to appreciable effect on stakeholders’ 
satisfaction, this study recommends an urgent need to step up electricity supply to SMEs in order 
to accelerate satisfaction level of firms’ stakeholders. Increasing electricity access should involve 
optimal production and utilization of generation capacity and/or reduction of transmission and 
distribution losses. Above all, SMEs villages/clusters should be built to promote industrial 
activities on the basis that access to reliable electricity supply is collectively and affordably 
provided by the relevant host authorities to investors and operators. 

 
Keywords: Electricity access, Stakeholders’ satisfaction, Firm age, Firm size, Leverage, SMEs. 

JEL Classification: L25. 

 

Contribution of this paper to the literature 
This paper provides an empirical analysis of the effect of controlling firm characteristics in the 
energy-stakeholders’ satisfaction relationships. 

 

1. Introduction 
Access to a reliable electricity supply is widely considered to be vital and indispensable to the operations of 

most small and medium enterprises (SMEs). A scholar (Krizanic, 2007) likened indispensability of reliable electric 
power to the role of food in the body. Just as food is needed to survive and grow, reliable electricity is also a 
necessary condition for businesses to thrive. Electricity consumption will increase productivity and therefore 
growth is achieved. Not surprising, most economists today agree that modern energy is a necessary ingredient for 
stimulating the emergence, growth and continued development of small scale businesses subsector in all societies.  

However, surveys suggest that, in middle and lower income countries, firms themselves consider access to 
electricity to be one of the biggest constraints to their business. In the World Economic Forum Global 
Competitiveness Report 2013 – 2014, quality of Nigeria’s electricity supply ranks 141 out of148 countries. 
Furthermore, 60% of Nigerian SMEs reported losing more than 10% of their sales to power outages. Electricity 
goes on and off five times in an hour (Okafor, 2014). This creates serious problems for firms. Equipment is 
damaged by power surges that usually accompany epileptic power and goods at various stages of manufacturing 
are damaged. Limited access to quality and quantity of electricity has remained an unresolved scourge in Nigeria. 

Empirical evidence which can be used to validate the relationship between electricity and enterprises 
stakeholders’ satisfaction is surprisingly scarce. The few studies that do exist on the topic often lack control 
variable. The research implication is that holistic relationships between the dependent and independent variables 
may be blurred and drawing clear-cut conclusion might be complicated. This was the motivation behind the 
present study. Hence, the current study seek to contribute to the existing literature by providing an extensive 
analytical framework that explore the role of control variable that is firm characteristics (firm size, firm age and 
leverage) in the relationships between electricity access and firms stakeholders’ satisfaction in order to establish a 

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true link between the studies variables and keep the results reasonable with stronger conclusion. The findings of 
this research are hoped to add to the existing body of literature, provide a better understanding of the subject 
matter to entrepreneurs, energy suppliers, policy makers and other modern energy stakeholders, and serve as a 
frame of future reference to researchers, academics and students. 
 

2. Literature Review 
2.1. Review of Empirical Literature 

To date existing empirical evidence on the relationship between electricity and stakeholders’ satisfaction of 
Nigerian SMEs is too sparse for satisfactorily conclusion. Substantial studies on this subject matter only give 
considerable attentions to financial performance of enterprises (profitability, liquidity, growth). For instance, using 
1970-2000 panel data for South Africa, and a range of 19 infrastructure measures, Fadderke and Bogetic (2006) 
found that electricity generation is positively related to labour productivity and total factor productivity growth in 
South Africa. Furthermore, Kirubi et al. (2009)analysed community-based micro-girds in rural Kenya, and showed 
that use of electricity can increase productivity per worker by approximately 100-200% for carpenters and by 50-
170% for tailors, depending on the item being produced. In another study, Grimm et al. (2011) found that tailors in 
Burkina Faso with access to electricity have revenues 51% higher than tailors without electricity, and attribute this 
to the use of electric sewing machines and longer working hours. Although the evidence shows a correlation 
between electricity consumption and firm productivity, and firms with access to electricity tend to have higher 
productivity than firms without, establishing causality is complex. This is partly due to the range of exogenous 
factors, and partly to the nature of the impact of electricity itself. 

Ukpong (1993) applied production function approach to investigate the impact of erratic power supply on 
selected firms in commercial and industrial sectors in Nigeria from 1965-1966. His finding shows that about 130 
KW/H and 172KW/H were not supplied to the firms in the two periods. The estimated cost of this is N1.68 
million in 1965 and N2.75 in 1966. By implication, he noted that erratic power supply has adverse impact on 
productivity growth of manufacturing sector in Nigeria. In the same vein, Akuru and Okoro (2011) assessed effect 
of electricity power outages on the growth and survival of firms in Nigeria, established that, between 2000 and 
2008 around 820 manufacturing firms were closed down, with the figure moving up to 834 in the following year, 
all because of poor electricity power supply and high cost on the alternative energy supply.  

Aligned with the foregoing, Doe and Asamoah (2014) examined effect of electric power fluctuations on the 
profitability and competitiveness of SMEs within Accra business district of Ghana is cross-sectional survey 
involved a mixed method approach. A sample of 70 Ghanaian SMEs was selected using a systematic sampling 
approach. Data was collected with an interviewer-administered structured questionnaire which focused on the 
effect of power fluctuation on the operations of SMEs, especially on the profitability and its resulting effect on the 
firms’ competitiveness. The SPSS statistical package was used to group and analyse the data. The study is a single-
factor analysis of the exogenous problems facing the Small and Medium Enterprise sector. The study found that 
without reliable energy supply, SMEs are unable to produce in increased quantities and quality leading to poor 
sales hence low levels of profitability. It is established that low profitability negatively affects Return on Assets 
(ROA) and Return on Investment (ROI) of SMEs. Consequently, if the level of profitability is high, it is expected 
that ROA and ROI will be high and vice versa. With high profits, SMEs are able to increase their competitiveness. 

A seminal work by Solomon and Yao (2015) in a case study among the cold store operators in the Asafo 
Market area of the Kumasi Metro in Ghana on electricity power insecurity and SMEs growth. Both primary and 
secondary data are utilized while purposive and stratified sampling technique are used to select 240 samples. The 
research findings indicate that, power outage experience has a negative effect on SMEs growth and pushes the 
operation cost of businesses high due to the high cost of alternative energy supply and the damages of assets 
through the power fluctuations. The operational cost in effect also have a damming effect on the growth of the 
SMEs, since most of the revenue meant for reinvesting will rather goes to the servicing of electricity and 
alternative power bills. 

To clinch the above finding, Wang (2002) confirmed negative correlation between frequent (announced) power 
fluctuations and unannounced power outages with ROA and ROI. The costs of alternate power sources such as 
power generators, as well as expenditure on overtime pay to staff and outsourcing service cannot be avoided when 
there is power outage and that tends to affect the firms ROA and ROI. 

It is evident from the aforementioned studies that empirical evidence which explicitly look at the correlation 
between electricity and satisfaction of SMEs stakeholders is too scanty for reasonable conclusion. Consequently, 
further research would be necessary. 
 

2.2. Theoretical Framework 
There are four major theoretical approaches to study SMEs performance. The first approach comprises the 

Balanced Scorecard (BSC) theory. BSC is a good strategy-management tool; it reviews the entire organization from 
four balanced perspectives. However, BSC is not sufficient to help SMEs because it does not examine many 
competitive and external factors. Furthermore, previous research has shown that BSC does not fit the flexible 
environment of SMEs because of BSC’s inherent mechanization and inflexibility (McAdam, 2000). The second 
approach involves Performance Prism. It is not a prescriptive measurement framework; instead, it is a tool 
(framework) that helps management teams to think about key questions and strategies to address them. Yet, 
performance prism does not fit into flexible environment and lack dynamic adaptability. Besides, it lacks both 
internal and external determinants measurement. The very same benefits that make the Performance Prism a 
strong, comprehensive model, however, also make it difficult to easily utilize. The third approach comprises the 
Activity-Based Costing (ABC) which measures the cost of a resource used to perform organizational activities and 
then links the activity to the costs of the outputs. ABC is a significant SMEs theory as it includes key performance 
indicators and based on objective-oriented measures. However, it is difficult to employ ABC to measure external 
factors because it lacks flexibility and dynamic adaptabilities. In addition, ABC approach does not reflect 
competitive performance nor respond tostrategy development. Finally, the forth approach is the System Theory 



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which regards an organization as a holistic system. Each part of the organization contributes to the system and 
ensures its survival and continuity. To achieve this objective, managers should not only understand the various 
parts of their organization and interconnection, but also the relationship of the system to its external environment 
(Jackson, 2003). System Theory can help SMEs to set-up a dynamic and flexible PM system which can measure 
both internal and external information, including competitive performance and respond quickly to strategy 
development. Subject to the SMEs performance requirements, system theory satisfies more SMEs performance 
(stakeholders’ satisfaction) requirements than other theoretical approaches. Consequently, this theoretical approach 
is adopted in building a performance measurement framework for electricity-reliant SMEs.  
 

3. Research Methodology 
Correlational survey research design which is cross-sectional in nature was adopted for this study because data 

was collected at one time.There are three variables in this research. The independent variable is electricity access; 
dependent variable is SMEs stakeholders’ satisfaction and control variable is firm characteristics. The unit of 
analysis is individual owner-manager. The target population consisted of SMEs operating in the city of Kaduna, 
Kano, Katsina and Sokoto state, Nigeria. Multi-stage sampling was applied to collected data from three stratums i.e 
manufacturing, hotel & restaurant and wholesale & retail sector SMEs. In the first stage, the SMEs were 
purposively selected; the next stage involved stratified sampling while SMEs were randomly selected in the third 
stage. A total of 340 sampled SMEs found with the aid of Krejcie and Morgan (1970) were invited to participate in 
the survey.  

The available data to answer the research questions are readily quantitative and subjective in nature, and were 
obtained mainly through primary source. A structured questionnaire with closed ended questions is used to gather 
the study data with a five-point rating scale. Out of the 340 questionnaires distributed only two hundred and sixty 
two questionnaires were returned, which showed that seventy seven percent (77%) of the respondents answered the 
questionnaires. Due to incomplete responses for some of the questions, nineteen (19) questionnaires were not 
analyzed. The final analysis was performed for only two hundred and forty five questionnaires (72%). The 
questionnaire consists three parts and was designed to explore the relationships between the research variables. 
Part one comprises questions on SMEs stakeholders’ satisfaction which was measured using a multi- item scale 
adopted from previous studies such as Hoskisson et al. (2008). Thirty items were used to measure SMEs 
stakeholders’ satisfaction. Each item was measured using a five- point rating scale on which the owners had to rate 
the business satisfaction level over the last three years. 1 indicates short of below average and 5 indicating well 
above average. In part two, ten (10) items were developed to measure electricity access. Part three consists fourteen 
(14) items to measure firm characteristics. 

The face and content validity of the questionnaire was ascertained by the assessment of specialists on the topic 
in order to determine the appropriateness of the items of the instrument, ascertain relevance and clear ambiguity. 
The coefficient of the Cronbach's Alpha was employed to determine internal reliability of the instrument which was 
0.82 thus, indicated that the items used for the measurement model are technically free from error. Descriptive 
statistics, mainly the frequency, percentage, mean and standard deviation, were used to analyze the data while 
multiple regression model was applied to test the hypotheses via SPSS version 23. All statistical tests were carried 
out at 95% significant level. The results of the hypothesis are presented in the next section. 
 

4. Data Analysis and Results 
4.1. Descriptive Analysis of the Main Variables 

Table 1 depicts the mean, standard deviation and Pearson correlation between the study variables. The total 
sample selected from the population of this study consists of two hundred and forty five (245) SMEs. The 
dependent variables selected for this study is stakeholders’ satisfactions. The independent variable is electricity 
access while control variables are firm size, firm age and leverage. Stakeholders’ satisfactions had a mean of 83.42 
with a standard deviation of 17.65. This signifies a fairly high increase in customers’, employees’ and owners’ 
satisfaction. The results further indicate that during the period of study, accessibility per hour of electricity supply 
had a mean of 19.9 with a standard deviation of 6.47. Low variability of standard deviation implies that electricity 
supply average is a true representation of the sample mean. However, mean value of 19.9 reflects that the present 
capacity of electricity supply fall short of requirement. This creates serious problems for electricity-reliant firms. In 
terms of firm years of operation, the mean and standard deviation are 7.13 and 1.59 while the mean and standard 
deviation are 7.59 and 1.60 for firm size respectively. This signifies that the firms were dominated by young small 
scale businesses. It is also revealed that leverage has a mean of 9.10 with a standard deviation of 2.98. This 
indicates a weak gearing position by the firms with a relatively low variability which could be attributed to the 
high cost of borrowing as a result of prevailing high interest rates in Nigeria. 

Table 2 further provides a matrix of the correlation coefficients for the study variables. Each variable is 
perfectly correlated with itself and so r = 1 along diagonal of the table. All the correlations were significant at 0.05 
level. For instance, it is found that electricity access was positively related to stakeholder satisfaction at 0.05 
significant levels with Pearson correlation coefficient of r = 0.646. The result suggests that electricity supply is 
vital for SMEs stakeholders’ satisfaction. This lends credence to the assertion that nearly all organizations need 
electricity services for proper functioning.  

On the other hand, weak positive relationship exists between SMEs stakeholders’ satisfaction and firm size. 
The relationship was significant at 0.05 levels. Pearson correlation coefficient was 0.386 with stakeholder 
satisfaction. The results give an indication that firm size is positively related to performance in terms of owners, 
customers and employees satisfaction.  

Furthermore, firm age registered 0.493 correlations with stakeholder satisfaction. The result revealed that firm 
age has a significant weak positive correlation with SMEs stakeholder satisfaction. Finally, leverage showed a 
significantly weak positive relationship with SMEs performance. Leverage Pearson correlation coefficients was 
0.166 with stakeholder satisfaction. The results suggest that firm leverage has comparatively lesser positive but 
significant correlation to SMEs stakeholder satisfaction. 



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Table-1.Mean and standard deviation of study variables. 
Variables Mean Std. Deviation N 

Elect access 19.19 6.470 245 
S. Satisfaction 83.42 17.654 245 

Age 7.13 1.597 245 
Size 7.59 1.608 245 

Leverage 9.10 2.988 245 

 
Table-2.Pearson correlation coefficients of study variables. 

 Elect access Stakeholders satisfaction Age Size Leverage 

Elect access    Pearson correlation 1 .646** .456** .330** .059 
   Sig. (2-tailed)  .000 .000 .000 .358 
   N 245 245 245 245 245 

S.Satisfaction    Pearson correlation .646** 1 .493** .386** .166** 
   Sig. (2-tailed) .000  .000 .000 .009 
   N 245 245 245 245 245 

Age    Pearson correlation .456** .493** 1 .264** .032 
   Sig. (2-tailed) .000 .000  .000 .615 
   N 245 245 245 245 245 

Size     Pearson correlation .330** .386** .264** 1 .014 
    Sig. (2-tailed) .000 .000 .000  .830 
    N 245 245 245 245 245 

Leverage     Pearson correlation .059 .166** .032 .014 1 
    Sig. (2-tailed) .358 .009 .615 .830  
     N 245 245 245 245 245 

 

4.2. Test of Hypotheses 
Since positive relationships were found between electricity access, SMES stakeholders’ satisfaction and firm 

characteristics in the correlation analysis, it is deemed necessary to employ regression analysis in order to 
determine whether there are any predictive relationship between dependent and independent variables. Hence 
multiple regression analysis was performed to predict the research hypothesis. In this analysis, model was 
developed to establish whether electricity access is significantly related to SMEs stakeholder satisfaction. If the P-
value is less than 0.05 the null hypothesis stands rejected. But the study accept null hypothesis if otherwise. 
 

4.2.1. Hypothesis 
HO: Electricity access is not significantly related to SMEs stakeholders’ satisfaction.  
Electricity was run against SMEs stakeholder satisfaction while firm characteristics were included as control 

variables on two hundred and forty five (245) observations. The result revealed that the model had an R square 
equal to 0.507 indicating that 50.7% of the variations in SMEs stakeholder satisfaction are explained by the four 
variables entered in the model (electricity access, firm size, firm age and leverage). As can be seen in Table 3 the 
difference between the value of R square and adjusted R square (0.507 – 0.499 = 0.006) is very small. This 
shrinkage value means that if the model were derived from the population rather than a sample it would account 
for approximately 0.006% less variance in the outcome. Consequently adjusted R square indicates that the cross 
validity of this model is very good. This result was further buttressed with prediction of whether change in R 
square was significant at an F-ratio of 61.778, which is again significant (P < 0.001). The change statistics 
therefore revealed the difference made by adding firm characteristics to the model. Similarly, the F-statistics 
(ANOVA) of the model in Table 4 equal 61.778, with a p-value equal to 0.000. The ANOVA finding showed that 
the overall model is a significant predictor of the SMEs stakeholders’ satisfaction. 
 

Table-3.Relationship between SMEs stakeholder satisfaction and predictors. 

Model R 
R 

square 
Adjusted 
R square 

Std. Error 
of the 

estimate 

Change statistics 
Durbin-
Watson 

R square 
change 

F 
change 

df1 df2 Sig. F change 

1 .712a .507 .499 12.495 .507 61.778 4 240 .000 2.409 
a. Predictors: (Constant), Leverage, Size, Age, Elect Access. 
b. Dependent Variable: Stakeholder  Satisfaction. 

 
Table-4.Variance analysis of SMEs stakeholder satisfaction and predictor. 

Model Sum of squares Df Mean square F Sig. 

1 Regression 38578.016 4 9644.504 61.778 .000b 
Residual 37467.682 240 156.115   

Total 76045.698 244    
a. Dependent Variable: Stakeholder Satisfaction. 
b. Predictors: (Constant), Leverage, Size, Age, Elect Access. 

 
The results further indicate in Table 5 individual contribution of each predictor to the t-test model. The slope 

that is b-values show the relationship between SMEs stakeholder satisfaction and each predictor. For these data all 
the four predictors have positive b-values signifying positive relationships. So, as electricity access increases by one 
unit, SMEs stakeholder satisfaction increase by 1.311 units provided the effect of firm characteristics that is firm 
age, firm size and leverage are held constant. Besides, every additional firm age increase is associated with an extra 
2.501 of SMEs stakeholder satisfaction provided electricity access, firm size and leverage are held constant. Beta 
weight under unstandardized coefficient also indicated that a unit increase on both firm size and leverage can 
expect addition of SMEs stakeholder satisfaction of 1.826 and 0.754 respectively provided other predictors too are 



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held fixed. For this model, electricity supply and firm age were significant predictors of SMEs stakeholder 
satisfaction. Electricity access t (245) = 9.138, p < 0.001; firm age t (245) = 4.404, p < 0.001; firm size t (245) = 
3.434; and leverage t (245) = 2.813.  

From the magnitude of the t-statistics, electricity supply had the greatest predictive power followed by firm 
age whereas both firm size and leverage had similar less impact. However, in order to evaluate the strength of each 
predictor variable in the model, it is important to use the standardized coefficients (beta). The beta weight indicated 

that electricity supply is the strongest predictor (β = 0.480, P = 0.000). This value indicates that as electricity 
supply increases by one (1) standard deviation (6.470), SMEs stakeholder satisfactions increases by 0.480 standard 
deviation. The standard deviation of SMEs stakeholder satisfactions is (17.654) and so this constitutes a change of 
(0.480 X 17.654 = 8.473). Therefore, for every 6.470 rises on electricity supply, an extra 8.473 is associated to 

SMEs stakeholder satisfactions provided other predictors are held constant likewise, firm age (standardized β = 
0.226) this value indicates that as firm age increases by one standard deviation (1.597), SMEs stakeholder 
satisfactions also increases by 0.226 standard deviation, the standard deviation for SMEs stakeholder satisfactions 
is (17.654) and so this constitute a change of 3.989 stakeholder satisfactions (0.226 X 17.654 = 3.989). Therefore, as 
firm age rises by 1.597 units, 3.989 extra stakeholder satisfactions can be expected. This interpretation is true only 

if the effects of electricity supply, firm size and leverage are held constant. In additions, firm size (standardized β = 
0.166) which implies that as the size increases by one (1) standard deviation (1.608), SMEs stakeholder satisfactions 
increases by 0.166 standard deviation. SMEs stakeholder satisfactions standard deviation is (17.654) and so this 
result in 2.930 growths (0.166 X 17.654 = 2.930), therefore, a firm with size rating 1.608 higher than another can 
expect 2.930 additional stakeholder satisfactions. This interpretation is true only if the effects of electricity supply 
firm age and leverage are held constant.  

Finally, leverage (standardized β = 0.128) signifies that as firm leverage increases by one (1) standard deviation 
(2.988), SMEs stakeholder satisfactions also increases by 0.128 standard deviation. The standard deviation for 
SMEs stakeholder satisfactions is (17.654) and so this constitutes a change of 2.259 stakeholder satisfactions (0.128 
X 17.654). Therefore, for every 2.988 rises on leverage, an extra 2.259 is related to SMEs stakeholder satisfactions 
unless other predictors are held constant. 
 

Table-5.Multiple regression coefficients of SMEs stakeholder satisfaction and predictor. 

Model 

Unstandardized 
coefficients 

Standardized 
coefficients 

t Sig. 

Correlations 
Collinearity 

statistics 

B 
Std. 
error Beta 

Zero-
order Partial Part 

Toler
ance VIF 

1 (Constant) 19.698 5.229  3.767 .000      
Elect access 1.311 .143 .480 9.138 .000 .646 .508 .414 .743 1.346 

Age 2.501 .568 .226 4.404 .000 .493 .273 .200 .778 1.286 
Size 1.826 .532 .166 3.434 .001 .386 .216 .156 .875 1.143 

Leverage .754 .268 .128 2.813 .005 .166 .179 .127 .996 1.004 
    a. Dependent variable: Stakeholder satisfactions. 

 

4.2.2. Collinearity Statistics 
Table 5 further provided collinearity statistics. The model showed that multi-collinearity was not serious, since 

the tolerance values all well above 0.2 and VIF value are all well below 10; therefore this study safely conclude that 
there is no multi-collinearity within the data. Moreover, the Durbin-Watson value was 2.409, suggesting no 
evidence of auto-correlation of the errors. The value of cook’s distance 0.099 less than 1.00 suggest that there is no 
potential problems with the outliers. 
 

4.2.3. Linearity Normality andHomoscedastiaty Statistics  
The graph of ZRESID and SPRED in Figure A (see appendix B) showed a random array of dots evenly 

dispersed around zero (0). This is an indicative of a situation in which the assumptions of linearity and 
homoscedasticity were accomplished, for test of normality of residuals, both histogram and normality probability 
plot in Figure A shows that histogram reflects a normal distribution (a bell-shaped curve) while normal probability 
plot reveals a straight line implies a normal distribution, and the points represents the observed residuals. Finally 
scatter plot, shows the strong positive relationship to SMEs stakeholder satisfactions. For electricity supply with 
cloud of dots evenly spaced out around the gradient line, indicating homoscedaslicity. 
 

4.3. Discussion of Findings 
The objective of this research was to explore the relationships between electricity supply and SMEs 

stakeholder satisfactions. Hypothesis was tested using multiple regression analysis to establish the relationships. 
The multiple regression analysis found statistically significant positive relationship between electricity access and 
SMEs stakeholder satisfactions while firm characteristics: firm size, age and leverage were held constant. 
Electricity access and firm age were the strongest predictors of SMEs stakeholder satisfactions. These results 
provide compelling evidence in support of the relationships between electricity access and stakeholder satisfactions. 
Generally the results suggest that those who aim to achieve higher satisfaction for business owners, employees and 
customer etc should consider access to electricity supply and firm age. These results are certainly in parallel with 
prior writings on the importance of electricity supply and SMEs performance such as Fadderke and Bogetic (2006); 
Grimm et al. (2012) and Kirubi et al. (2009).  

The findings of the present study agree with Ukpong (1993) that irregular electricity supply has been a major 
bane to output growth and that erratic power supply has adverse impact on productivity growth of manufacturing 
sector in Nigeria. They recommended that the power sector by means of guided private sector initiative should be 
given more attention for the growth of the nation’s economy to thrive. 



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The statistically significant relationships between electricity supply and SMEs performance affirms the view of 
Solomon and Yao (2015) who indicate that power outage experience has a negative effect on SMEs growth and 
pushes the operation cost of businesses high due to the high cost of alternative energy supply and the damages of 
assets through the power fluctuations. The operational cost in effect also have a damming effect on the growth of 
the SMEs, since most of the revenue meant for reinvesting will rather goes to the servicing of electricity and 
alternative power bills. 
 

5. Conclusion and Recommendations 
Based on the hypothesis results and the research discussion, it can be concluded that there is a strong positive 

link between energy and SMEs stakeholder satisfactions while firm characteristics (firm size, firm age and 
leverage) are kept constant. This significant relationship leads to high prediction power of electricity access, firm 
characteristics and stakeholder satisfactions. Hence, this study recommend that entrepreneurs, energy policy 
makers and researchers should take cognizance of the significant of electricity access and firm characteristics (firm 
size, age, leverage) in the process of investigating and analyzing SMEs stakeholder satisfactions. This is because 
some variables (electricity access, firm age) are found to have a strong power in predicting stakeholder satisfactions 
while some variables (firm size and leverage) have weak power in predicting stakeholder satisfactions in Nigerian 
firms. 

As access to electricity is found to be related to SMEs stakeholder satisfactions, increasing energy supply in 
Nigerian SMEs will have a positive influence on stakeholder satisfactions. Increasing electricity supply should 
involve optimal production and utilization of generation capacity and/or reduction of transmission and distribution 
losses. When this is achieved, the SMEs subsector will be in position to effectively lead in the drive towards 
industrializing the Nigerian economy. 

The government should ensure that the SMEs subsector enjoys higher proportion of the power supply 
compared with the totality of the other sectors of the economy. SMEs villages/clusters should be built to promote 
industrial activities on the basis that access to reliable electricity supply is collectively and affordably provided by 
the relevant host authorities to investors and operators. In the absence of a better quality supply of electricity, 
improved quality and information about outages can help. Policy makers should help SMEs by providing reliable 
load shedding schedules. This would enable them to plan production around outages. 

Above all, if off-grid electrification project is properly harnessed, is a likely solution to the perennial problem of 
power outages to small scale businesses subsector with the abundance of oil, gas resources and the renewable 
energies (solar and wind) in Nigeria. Therefore, efforts should be made by relevant authorities, tasked with the 
promotion of SMEs in Nigeria, to facilitate the provision and subsidized costs of procuring these renewable energy 
systems. 
 

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Fadderke, J. and Z. Bogetic, 2006. Infrastructure and growth in South Africa: Direct and indirect productivity impacts of nineteen 
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Appendix A 
Part A: Electricity Supply Survey Questionnaire. 

Instruction: Please respond as candidly as possible to the following statements by rating (√) a number between 
1 and 5 that best represents your organization in term of availability per hour of electricity supply as it was during 
the past three years. Use the scale provided below to indicate the option that most accurately reflects your 
assessment on each statement. Choose only ONE option for each statement. 

 
 
 
 
 
 



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Very low Low Average High Very high 

1 2 3 4 5 

 

Electricity supply 

ES01 Number of uninterrupted power supply in a typical month 1 2 3 4 5 
ES02 Duration of a typical reliable electricity supply 1 2 3 4 5 
ES03 If there were uninterrupted power supply, average duration of a 

typical reliable power supply 
1 2 3 4 5 

ES04 Maximum percentage voltage fluctuation during a month. 1 2 3 4 5 
ES05 Number of enterprises rely only on grid electricity 1 2 3 4 5 
ES06 Duration of firm operation relying on grid electricity 1 2 3 4 5 
ES07 Gains due to reliable electricity access in terms of percentage annual 

sales 
1 2 3 4 5 

ES08 Monthly quality of reliable electricity consumed 1 2 3 4 5 
ES09 Average outage time during a month. 1 2 3 4 5 
ES10 If grid electricity is used, average proportion of electricity supply 

from grid 
 

1 
 

2 
 

3 
 

4 
 

5 

 

Part B:SMEs Performance Survey Questionnaire. 
Instruction: Please respond as candidly as possible to the following statements by rating (√) a number between 

1 and 5 that best represent your organization non-financial performance (stakeholders satisfaction) as it was during 
the past three years. Use the scale provided below to indicate the option that most accurately reflects your 
assessment on each statement. Choose only ONE option for each statement. 
 

Very low Low Average High Very high 
1 2 3 4 5 

 

Employees satisfaction 

ES01 Investments in employees development and training 1  2 3 4 5 
ES02 Extent of employees turnover 1  2 3 4 5 
ES03 Number or percentage of employees promoted during a year 1  2 3 4 5 
ES04 Percentage of employees who rated their careers development 

opportunities as above or excellent in the annual employee survey 
 
1 

 
 2 

 
3 

 
4 

 
5 

ES05 Extent of competitiveness of compensation package 1  2 3 4 5 
ES06 Safe work conditions 1  2 3 4 5 
ES07 Pleasant work environment 1  2 3 4 5 
ES08 Fairness of your firm wage and reward policies 1  2 3 4 5 
ES09 Extent of inclusion on list of best companies your employees wish to 

work for. 
 
1 

 
 2 

 
3 

 
4 

 
5 

ES10 Extent of employees’ inclusion in decision matter to them. 1  2 3 4 5 

Customers satisfaction  

CS01 Number of complaints per customers per year 1  2 3 4 5 
CS02 Percentage of time customers ranking products/services very good or 

excellent on survey  
1  2 3 4 5 

CS03 Average number of time customers report on products/services quality. 1  2 3 4 5 
CS04 Perceived customers fair treatment during transaction 1  2 3 4 5 
CS05 Extent of your organization product safety concern 1  2 3 4 5 
CS06 Percentage of time customers ranking your company innovation very 

good or excellent on survey 
1  2 3 4 5 

CS07 Repurchase rate 1  2 3 4 5 
CS08 Number of new products/services launched during a year. 1  2 3 4 5 
CS09 Number of goods returned per year. 1  2 3 4 5 
CS10 General customers satisfaction 1  2 3 4 5 

Owners satisfaction 

OS01 Extent of return on investment 1  2 3 4 5 
OS02 Extent of liquidity soundness 1  2 3 4 5 
OS03 Perceived riskiness of investment 1  2 3 4 5 
OS04 Average number of stockholders proposals per year 1  2 3 4 5 

OS05 Extent of compensation levels of top managers 1  2 3 4 5 
OS06 Extent of stability of investment 1  2 3 4 5 
OS07 Extent of price-to-earnings ratio 1  2 3 4 5 
OS08 Rate of market-share growth 1  2 3 4 5 
OS09 Extent of ownership concern and attention 1  2 3 4 5 
OS10 General stockholders satisfaction. 1  2 3 4 5 

 
PART C: SMEs Characteristics Survey Questionnaire. 

Instruction: Please respond as candidly as possible to the following statements by rating (√) a number between 
1 and 5 that best represents your organization in term of size and leverage as it was during the past three years. 
Use the scale provided below to indicate the option that most accurately reflects your assessment on each 
statement. Choose only ONE option for each statement. 
 
 
 



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© 2019 by the authors; licensee Eastern Centre of Science and Education, USA 

 

 

Very low Low Average High Very high 

1 2 3 4 5 

 

Size 

S01 Total asset turnover 1 2 3 4 5 
S02 Sales level 1 2 3 4 5 
S03 Number of employee 1 2 3 4 5 
S04 Ability to fund growth 1 2 3 4 5 
S05 Working capital to sales 1 2 3 4 5 
Leverage 
LE01 Debt to equity 1 2 3 4 5 
LE02 Long – term debt to equity 1 2 3 4 5 
LE03 Time interest earned 1 2 3 4 5 
LE04 Stockholders capital to total capital 1 2 3 4 5 
Age 

 
A01: How long has your firm been in operation? 

Less than 5 years 1 

5 – 10 years 2 
11 – 15 years 3 
16 – 29 years 4 
Above 20 years 5 

 
A02: When was your enterprise incorporated? 

Less than 5 years ago 1 

5 – 10 years ago 2 
11 – 15 years ago 3 
16 – 29 years ago 4 
More than 20 years ago 5 

 
A03: How many years of business experience does your enterprise has? 

Less than 5 years 1 

5 – 10 years 2 
11 – 15 years 3 
16 – 29 years 4 
Above 20 years 5 

 
A04: How long was your enterprise in existence? 

Less than 5 years 1 

5 – 10 years 2 
11 – 15 years 3 
16 – 29 years 4 
Above 20 years 5 

 
A05: How long was your enterprise in business trading? 

Less than 5 years 1 

5 – 10 years 2 
s11 – 15 years 3 
16 – 29 years 4 
Above 20 years 5 

 
Appendix B 
 

 
Figure-A. Histogram, normal p-p plot and scatterplot. 

 



Asian Business Research Journal, 2019, 4: 35-43 

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© 2019 by the authors; licensee Eastern Centre of Science and Education, USA 

 

 

 
Figure-B. Scatterplot. 

 

 
Figure-C. Normal P-P plot. 

 
 
 

 

 

 

 

 

 

 

 

 

 

 

Citation | Abubakar Sabo; Olusegun Kazeem Lekan (2019). Does 
Electricity Access Relate to Stakeholders’ Satisfaction?  Empirical 
Evidence from Small and Medium Enterprises in North-West, 
Nigeria. Asian Business Research Journal, 4: 35-43. 
History:  
Received: 17 September 2019 
Revised: 21 October 2019 
Accepted: 26 November 2019 
Published: 30 December 2019 
Licensed: This work is licensed under a Creative Commons 

Attribution 3.0 License  
Publisher:  Eastern Centre of Science and Education 
 

Acknowledgement: Both authors contributed to the conception and design of 
the study. 
Funding: This study received no specific financial support. 
Competing Interests: The authors declare that they have no conflict of 
interests. 
Transparency: The authors confirm that the manuscript is an honest, 
accurate, and transparent account of the study was reported; that no vital 
features of the study have been omitted; and that any discrepancies from the 
study as planned have been explained. 
Ethical: This study follows all ethical practices during writing.   
 

Eastern Centre of Science and Education is not responsible or answerable for any loss, damage or liability, etc. caused in relation to/arising out of the use 
of the content. Any queries should be directed to the corresponding author of the article. 

 

http://creativecommons.org/licenses/by/3.0/
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