A Quantitative Analysis of Selected Variables on their Impact to Small Business Growth in the eThekwini Region



Tinaye Mahohoma1, Albert Tchey Agbenyegah2



Abstract: Over the years researchers and academics have used several terminologies to elucidate small business growth. However, underlining events which each entity undergo still remains more or less the same. The purpose of this quantitative study was to investigate the impact of selected variables on the growth of small businesses in the eThekwini Region of KwaZulu Natal in South Africa. From a total population of 220 small businesses with more than ten years of active business operations within the research settings, a sample of 119 owners- managers were randomly selected to provide empirical data. Data collection was based on primary data, by using closed ended questionnaire as the main research instrument. The bivariate correlation analysis is employed to ascertain the set study objective. The final outcomes revealed that business growth might not be positively linked to educational achievement of owner-managers. The researchers recommend that entrepreneurial education should be introduced and be prioritised to every grade 12 learners across the educational settings in the research settings. Further collaboration is required between educators and trainers of potential industry-based entrepreneurs across the eThekwini Region to enable all the role players utilise the rich experiences of members. The level of collaboration could be of utmost benefits to educators in all the learning institutions throughout the region in designing entrepreneurial training programmes and education curriculum in all the schools.

Key words: Small business growth; business size; business age; entrepreneurs; e-Thekwini

JEL Classification: C20



1. Introduction

In any country, small businesses are the major drivers of vibrant economic development, employment creation as well as vigorous economic growth (Nafukho & Muya, 2010). Entrepreneurs are those individuals who intend to manage such enterprises. Hence, entrepreneurship is that kind of proprietorship which focus on a new arrangement so as to manufacture fresh goods and services. Small business, according to Seda (2016) are deemed to create about 80% of all new job opportunities and more than 70% of the South African workforce is employed in this sector.

Despite the enormous role played by small business the economy, they continue to face serious threats associated with the establishment, growth and development and some these threats include growth challenges of small businesses. Lack of financial resources; lack of managerial skills; inadequate equipment and technology; legal/regulatory issues, and poor/limited access to markets (Abor and Quartey 2010). These are some of the hindrances to growth and development of small businesses.

South Africa faces tremendous socio-economic challenges, and many of these challenges are, to a large extent, linked to the high level of unemployment. According to the Quarterly Labour Force Survey (2019), the unemployment rate for the third quarter of 2019 was approximately 29%. Despite the role played by small business in terms of employment creation, innovation, economic growth and development the failure rate is very high in South Africa (Lings 2014) cannot account for the needed economic growth, especially with proportional to the challenge of employment creation.

Studies conducted in other countries (Lucas & Laverde, 2018; Sajilan et al., 2015) also highlighted the important role of demographic factors on the small business growth. In South Africa little research was conducted to determine the impact of selected variables on small business growth. In an attempt to partially address this gap, the authors seek to discuss the impact of business age, educational qualification and business size on small business growth through quantitative analytical tools.



2. Theoretical Framework

The theoretical background is utilized with a view to formulate the overall structure of specific theory that underline this study. The following section give an account of a theoretical framework that explains the research problems. This empirical study employs the Penrose’s firm growth theoryat the main starter to provide solutions to the phenomenon.



2.1. Penrose’s Firm Growth Theory

Growth refers to a change in size or magnitude from one period of time to another (Wieland 1998) Penrose (1959) provided some key characteristics that regulates and standardise the growth of small businesses and the level at which these enterprises grow successfully. The small businesses create a linkage between internal environment and external resources in order to enhance the increase in the size of the entity and to attain the competitive advantage (McKelvie & Wiklund, 2010). Penrose’s growth theory defines resources as the physical things a firm buyS, leases or produces for its own use and the labour force that make them effectively part of the firm. Johannisson (2017) defines the contribution these resources can make to the productive operations of the firm as services.

The primary objective of private firm is the desire to accumulate significant amounts of profit margin as expounded in the Penrose growth theory (Penrose, 2019). Given the general perspectives of the growth theory, every individual firm is to demonstrate particular productive prospect that stands out to demonstrate the firm’s distinctiveness. The Penrose growth theorem views the sizes of entities as incidence to potential growth processes (Gupta et al., 2013). Coad et al. (2016) postulate that effective and innovative managerial resources results in the small business growth (in the main assumption of Penrose growth theory). Penrose argued that differential aspect among firms in the same industry occurs because even firms with similar resource quantities can configure them in unique combinations that yield a variety of services (Burvill et al., 2018). According to Penrose (2019), “Firm growth occurs because of the availability of excess resources-such excesses develop because of the lumpiness and indivisibilities of the resources that firms acquire”. In contrast, lack of capabilities causes internal obstacles to growth.



2.2. Characteristics of Small Businesses

Yazdanfar et al. (2014) posit that small business general use a large percentage of lowly skilled and unskilled people than larger organisations and they become labour intensive sector. The labour intensiveness of small business promote a more equitable distribution of income than larger organisations (Olawale and Garwe, 2010). In terms of relationships, Biekpe (2011) argues that small businesses have a more direct relationship with the local community, and they often reside in a single city or region and become a familiar presence in that area (Biekpe 2011). During turbulent market conditions small businesses tend to be are more flexible and they can easily adapt (Sánchez et al., 2013). Additionally, in terms of organisational structure, the small businesses have a very simple rather than complex, often requiring flexibility from employees to adapt their competences and skills to different tasks in their daily duties (Ogbokor 2012).

Established small businesses often own their facilities and equipment outright, which, in addition to other factors, helps to keep costs lower than more leveraged businesses (Olfert 2012). Arend (2014) and Nicolini (2001) in their work argued that small businesses mainly rely on the personal assets of owners and management as long sources of finance the company. Walker and Brown (2004), as well as Radipere and Dhliwayo (2014) argue that small businesses have unique products or services, such as their own designs, products, systems or some other aspect, which sets them apart. As one of their shortcoming, Coad, Segarra and Teruel (2013) stated that small businesses have limited bargaining power when purchasing inputs from suppliers; hence, they receive lower volume discounts and trade discounts than larger organisations (Boubakary, 2015). In small business, according to Xiang and Worthington (2015) the owner is part of the management team, and is often responsible for many different tasks and important decisions. Small businesses due to their size, are not in a dominant position compared to their suppliers, and this results in small businesses having less bargaining power with their suppliers than larger companies (Radipere and Dhliwayo 2014; Chowdhury et al., 2013).



3. Empirical Literature

3.1. Empirical Findings on Business Growth of Small Businesses

The terms “growth”, “success” and “performance” are closely linked and often interchangeable (Reijonen & Komppula, 2007). However, in this study the authors are concerned of small business growth as such the concept of growth is defined in the ensuing section. While the definitions of these terms are seemingly intertwined, the term business growth is applied in this study. Singh et al. (2008) outline the measurement of business growth is done through analysing the ration between the twin concepts of outputs and inputs.

Scholars like Gupta and Batra (2016) and Zimon (2018) define business growth as the general improvement in sales, profit or market share. This line of definition is supported by Ruigrok and Wagner (2003) who categorised business growth into two core dimensions: financial and operational (nonfinancial). Anggadwita and Mustafid (2014) elaborate that efficiency, financial results, level of production and number of customers are some of quantified business growth measures (Alpkan et al., 2007). Furthermore, Sheehan (2013) and Gopang et al. (2017) add that achievement goals, leadership style, employee behaviour, customer satisfaction, and innovative process, organisational and marketing innovation as qualitative indicators. Yazdanfar et al. (2014) contend that qualitative techniques of business growth may be obtained by ranking or scaling variables (based on individual perceptions), such as knowledge and business experience, the ability to offer quality products and services, the capacity to develop new products and processes, the ability to manage and work in groups, labour productivity, and corporate responsibility to the environment (Sarwoko et al., 2013). Drawing from these definitions, the authors made the decision to adopt both financial and non-financial indicators of business growth.



4. The Conceptual Framework and Hypotheses Formulation

The conceptual framework of this study was driven by extant scientific evidence that consisted of selected dependent and independent variables of demographic factors and small business growth. In this paper the selected variables that were used to model the conceptual framework features the business age, educational qualification and number of full time employees. Figure 1 below depicts the related variables that formed the foundation of this study.

Figure 1. Selected Demographic Model on Small Business Growth

Source: Compiled for the Study

4.1. The Relationship between Business Age and Small Business Growth

In African countries the study between business age and growth are very limited (Hui, et al. 2013). Storey (1994) as well as, Delmar et al. (2003) observed that business age and growth are inter-dependent variables. Business age is defined as the number of years that an enterprise has been operate within the confinements of law as indicated by most studies (Abu Bakar 2011; and LiPuma et al., 2013). The study conducted by Wiklund and Shepherd (2005) and Radipere and Dhliwayo (2014) reflected positive relationships between business age and business growth. Urban (2004) emphasised that business age leads to positive business growth but up to a certain size where they become sluggish.

Bhayani (2010) conducted quantitative data analysis through regression analysis, the results showed that older small business performs better than the younger firms. This finding are supported by the study conducted by Chang et al. (2002) that concluded that older firms enjoy great benefit from their greater business experience, and therefore experience higher growth than younger firms. Older firms tend to build good network business partners and customers, and have good relationship with financial institutions. Opposite to the above mentioned findings, in this study conducted in India, Gaur (2011) examined the link of business age and growth, it was proved that the business age is statistically insignificant. Agarwal and Gort (2002) pointed out a negative correlation between business age and growth due to the fact that business age leads to poor growth. Loderer and Waelchli (2010) and found that as the firm ages its growth drops, thus firm age having a negative effect on growth. Business age in this study was measured through the following categories: less than 5 years; 5-10 years; 11-15 years; 16-20 years and 20 years and more. Given the above discussions, the authors define the formulated hypotheses (null hypothesis (H0), and alternative hypothesis as H1) as follows:

H0a: There is no statistically signification relationship between business age and growth.

H1a: There is statistically signification relationship between business age and growth.



4.2. The Link between Business Size and Small Business Growth

Business size can be defined as the number of full time employees (work force) (Takalashi, 2009; GEM, 2010). Recent study by Alasadi and Abdelrahim (2007) observed that small business growth depends on business size and also business size depends on business growth. As the business grows, it increases the operations that requires a lot of employees (Takahashi 2009). Small business size is associated with how the entity has access to both the resources and the operational costs incurred by the firm (Arend, 2014; Nicolini, 2001). Firm size as an internal factor of a company has been considered a very important attribute of profitability. Driffield et al. (2005) contend that business size has great influence to the level of economic activities and the possible economics of scale enjoyed by the firm. Anton and Onofrei (2016) argues that entities that enjoys greater business size generate higher business growth. Anton and Onofrei (2016) revealed the positive correlation between growth and business size. However, Gibrat’s law (1931) states that the business size plays no role in influence the success of the business. Research by Mateev and Anastasov (2010) found evidence that business size and growth. In this study the business size was measured through the following categories: less than 50 employees; 51-100 employees; 101-150 employees; 151-200 employees and above 200 employees. Given the above discussions, the authors define the formulated hypotheses as follows:

H0b: There is no statistically signification relationship between business size and growth.

H1b: There is statistically signification relationship between business size and growth.



4.3. The Association between Education and Small Business Growth

Radipere and Dhliwayo (2014) in agreeing with Chowdhury et al. (2013) noted that educational qualifications of entrepreneurs are critical factor that leads to the success of small business in complex environments. In order to achieve entrepreneurial development, a good quality education enhance an individual’s level of self-efficacy and self-confidence (GEM, 2012). Vallabh and Mhlanga (2014) emphasised that education aids the process of building cognitive thinking of owners/managers such as confidence, psychology, knowledge and skills which will impact the growth of the business. Fatoki (2014) emphasised that education plays a critical role in distinguishing high growth and low growth small firms. Panda (2002) indicated that formal educational qualification of entrepreneurs has no significant impact to the level of business growth. This was echoed by Gupta and Muita (2013) who undertook a study in Jordon, which concluded that the entrepreneur’s level of education positively influences the success of his/her business. Similarly, Kokeno and Muturi (2016) proved that education had positive effect on firm growth the study was conducted in Nairobi. In contrast, some studies (Gottesman and Morey 2010; Clarke et al., 2013) failed to establish the relationship the level of education and business growth. The findings indicated that education does not influence firm growth. Given the above discussions, the authors define the formulated as follows:

H0c: There is no statistically signification relationship between education and growth.

H1c: There is statistically signification relationship between education and growth.



5. Research Methodology

The research employed a quantitative technique as empirical data was collected through closed ended questionnaire. Nardi (2018) postulates that quantitative research is generally deductive and particularistic through the formulation of the research questions and verifying them empirically on a specific set of data and this is favoured by positivism philosophy. Parahoo (2014) supports that objectivism is well achieved in positivism since the researchers’ own values, biases, and subjective preferences are subdued. Corry et al. (2019) noted that the importance of positivism, particularly logical positivist explanation, is recognised as one of the most viable approach to explain a phenomenon. The quantitative research involved gathering data through the use of a structured questionnaire (Sekaran & Bougie, 2016; Cooper & Schindler 2014), which was electronically mailed to the chosen sample.



5.1. Sample Profile

Two hundred and forty eight (248) respondents were identified and approached for the survey. These respondents represented the target population of the owners/managers residing in the eThekwini region of KwaZulu-Natal in South Africa. The sample respondents of the target population were randomly sampled using a random number table.



5.2. Research Instrument

This study is quantitative; thus, a 5-point Likert-scale questionnaire was utilized to measure the dependent and independent variables. This study made use of closed ended questionnaires to ensure that empirical data gathered allowed the authors not only to perform credible statistical evaluations but to also ascertain insightful data interpretations (Creswell, 2014). Greater considerations regarding how the proposed variables should be evaluated to realise the study objectives were well thought off. As such, relevant scales of measurement were identified and operationalized in line with extant literature review



5.3. Reliability and Validity

Mohajan (2017) defines reliability as the uniformity and standardisation of results provided by the independent but comparable measures of the same object or construct. Cronbach’s alpha was used as the primary measure of reliability in this study and the value was 0.76. Creswell and Clark (2017) refer validity as to the degree at which the measurement process is free of both systemic and random errors. The face validity of the questionnaire was tested using experts (in the areas of small businesses), who analysed and interrogated the questionnaire to establish whether it covered the study objectives.



6. Data Analysis

In data analysis, the raw data (unprocessed information) is ordered and organised to enable the extraction of useful information from it. In this study the data from the 119 respondents was captured and coded on Microsoft Excel spreadsheets, and was processed using the Statistical Package for the Social Sciences (SPSS), version 25, software. In this study the descriptive statistical tools that were used were frequency distribution tables. Correlation and regression analysis are the inferential techniques that were employed to measure the strength of the association and relationship between selected demographic factors and small business



7. Empirical Results

7.1 Descriptive Statistics

Table 1. Measures of Central Tendency

Statement/ Item

Valid

Missing

Mean

Median

Mode

To which does your business belong

119

5

6.19

7.00

7

No.of (full of time) employees

119

8

2.64

2.00

2

How long have you owned your current enterprise

119

11

2.62

2.00

2

Indicate your highest of level of formal education

119

9

2.15

2.00

2

Which of the following measures do you use to evaluate the business growth of the organisation

119

13

2.23

200

2

Business growth trend over the past 2 years

119

13

1.38

1.00

1

The rate of business growth

119

13

1.71

2.00

2

In terms of which business sector does the enterprise belong, the mean value of five (5) is lower than the mode and median values, the implication is that most enterprises belong to the catering and accommodation sector. In terms of the number of full time employees, the mean is greater than the median and the mode, this indicate that on average owners-managers has labour force ranging from 101 to 150. From the results displayed in the Table 1 above, it can be concluded that the average duration period of the firms is between 11-15 years. This contradict that most of small business cannot survive for more than 2 years. The respondents indicated that they possess Diploma/ Degree. This shows that most of the owners-managers had received formal education. Net income is the mostly used as a measure of business growth. The study indicate the majority owners-managers prefer financial measures in defining their business growth. The study indicate that the financial measures has increased in the last 2 years. Finally, the results of the study indicate that most of SMEs were successful in the last 2 years.

7.2. Inferential Statistics

Table 2. Bivariate Pearson Correlation (R)

Statement/ Item

N

R

No. of full time employees

119

-0.091

How long have you owned your current enterprise

116

-0.113

Indicate your highest level of formal education

119

-0.044

Which of the following measures do you use to evaluate the business growth of the organisation

119

-0.071

Business growth trend over the past 2 years

119

0.363

The rating of business growth

119

1

The results displayed in Table 2 indicates a weak negative relationship is depicted on business size and business growth. This implies that the small businesses are also adopt the use of technology and starting to be capital intensive in nature. The relationship between business age and business growth is a negative weak relationship. This implies that the success of an enterprise does not depend if the business is young or old. There is negative weak relationship between education qualification and business growth rate. This implies that formal education does not have any role to play in improving the success rate, so uneducated owners-mangers may be very successful than the educated ones. The results also indicate that a negative weak relationship is depicted between the business growth measures and the success rate. This implies the use of either financial or non-financial measures does not influence the success of the business. Lastly, a moderate positive relationship exists between the growth trend of and the growth rate. This implies that the daily growth significantly impacts on the business success in the long run.

Table 3. Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.190a

.036

001

.659

The correlation of the whole mode shows a weak positive relationship. This implies all the three selected variables that is business age, business size and education had less significant impact on the small business growth. In terms of coefficient of determination, 3.6% variation in the rating of the business growth is explained by the stated independent variables. This implies that 96.4% variation in the business growth rate is explained by other factors that are not included in this model and hence the model is very weak to ascertain if these three selected demographic factors possess great influence on small business growth.

Table 4. Regression Equation

Model

Unstandardized

Beta

Coefficients

Std Error

Standardized Beta

t

Sig.

(Constant)

1.871

.290


6.448

.000

No. of (full-time) employees

-.048

.066

-.070

-.719

.474

How long have you owned your current enterprise

-.053

.059

-.089

-.903

.369

Indicate your highest level of formal education

-.022

.088

-.023

-.246

.806

Conceptualising of the Variables

Let:

 

 

 

 

 

 

 

 

Discussions

The model above reflects without modifications the independent variables. The business growth is 1.871 when there is no influence all independent variables. Regarding business size, the coefficient of -0.048 implies that small sized firms performs better than the larger size ones (measured by number of full time employees). The results of the study contradicts the assertion of Anton and Onofrei (2016) who argued that entities that enjoys greater business size generate higher business growth. In terms of the business age, a negative relationship is depicted on the business growth. This implies that younger firms perform better than older firms. This can be attributed to the notion that when the firm is small the owner/manager has greater control of all the functions of manager and decision are made without delay. Agarwal and Gort (2002) is in agreement with the findings of the study as the authors pointed out a negative correlation between business age and growth due to the fact that business age leads to poor growth.

A negative relationship between the level of education and business growth is revealed in this study. This implies that managers who attained lower level of education are likely to perform better in contrast to holders of post graduate qualifications. This is supported by recent research commissioned by Panda (2002), Gottesman and Morey (2010), and Clarke et al. (2013) which revealed that formal educational qualification of entrepreneurs has no significant impact to the level of business growth. This finding is very contradictory since the general notion is that higher education achievement is associated with higher growth (Gupta and Muita, 2013); Alkali, 2012).





8. Discussions and Conclusions

The aim of this research was to determine the impact of the three selected variables (business size, business age and education) to the small business growth. The research analysis was conducted on the small business that resides in eThekwini Region, Kwa-Zulu Natal in South Africa. The total number of firms included in the analysis amounted to 248. Small business was chosen due to its significant contribution to the economy in terms of total production (56%) and total employment (70%), as well as due to the overall data availability. Based on the findings from this study, it has been shown that the three demographic factors (education, business age and business size) had negatively influence the business growth. Thus, education by the owners-managers might not be relevant to positively influence the business growth.

Based on the findings, the researchers suggested a number of recommendations. Initially the researchers recommend that entrepreneurial education should be introduced to all learners. Furthermore, there should be ongoing collaborative effort between educators and industry-based entrepreneurs to provide educators with business related curriculum assistance to educators and training programmes. Lastly, government should redefined the definition of SME in terms of market capitalisation or the general business asset values using US dollar as denomination.

Further researches may be oriented towards the investigating the impact of entrepreneurial education on the business growth in the small businesses with the inclusion of additional explanatory variables (excluding business size, business age).



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1 Durban University of Technology (DUT), South Africa, Address: ML Sultan Campus, Durban, South Africa, E-mail: tinasm@12gmail.com.

2 Durban University of Technology (DUT), South Africa, Address: Riverside Campus, Pietermaritzburg, Durban, South Africa, Corresponding author: alberta@dut.ac.za.

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