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South African Journal of Economic and Management Sciences

On-line version ISSN 2222-3436

S. Afr. j. econ. manag. sci. vol.14 no.1 Pretoria  2011

 

ARTICLES

 

Assessing entrepreneurship perceptions of high school learners in Pietermaritzburg, Kwazulu-Natal

 

 

Darma MahadeaI; Shaun RamroopI; Temesgen ZewotirII

ISchool of Economics and Finance, University of KwaZulu-Natal
IISchool of Statistics and Actuarial Science, University of KwaZulu-Natal

 

 


ABSTRACT

Although South Africa achieved positive economic growth rates since the advent of democracy in 1994, the formal sector has not been able to absorb the annual increasing number of job-seekers on the market and solve the unemployment problem. The exercise of entrepreneurship, through business formations and expansions, is regarded as a vehicle for job creation and output expansion. According the Global Entrepreneurship Monitor (GEM) reports, South Africa's level of early stage total entrepreneurial activity (TEA) is rather low relative to other countries at a similar level of development. This is partly owing to skills and resource limitations. If more individuals could realistically be exposed to practical entrepreneurship education at the secondary school level, South Africa's base for entrepreneurial capacity can be enhanced.
This study uses quasi logistic regression to examine the probability of secondary school learners, in Pietermaritzburg, the capital of Kwazulu-Natal province in South Africa, to start their own business in the future. It also probes the association between the socio-economic attributes of these learners and entrepreneurship. On the basis of a survey of 275 senior school learners from 5 schools, the regression results indicate that gender, ethnic background and having a role model as well as acquiring personal skills to run one's own business are significant factors influencing an individual's propensity to venture into small firm self-employment in the future. Black learners are perceived to have a significantly greater disposition to enter into business than other groups, and male scholars are found to have a greater probability of starting their own business than female. As potential entrepreneurs do not necessarily come exclusively from a business family background, the supply of effective entrepreneurship can be augmented, if more young individuals with the relevant skills endowment can start opportunity firms and necessity ventures.

Key words: entrepreneurship, school learners, economic growth, gender, employment creation

JEL J00, O17, 55, Z13


 

 

1 Introduction

Although South Africa registered positive economic growth rates since the advent of democracy in 1994, this economic expansion has not been accompanied by significant growth in employment. Indeed, South Africa achieved an average economic growth rate of 3 per cent over the period 1994-2003, around 5 per cent during 2004-2007 and 2.8 per cent in 2008 (SARB, 2009). After a period of contraction, amid global recession, during two quarters in 2009, the economy bounced back with a growth of 4.6 per cent in the first quarter of 2010 (SARB, 2010). Despite these robust growth rates in a strengthening economy, unemployment rates in post-apartheid South Africa remain extremely high.

Increasingly, there are signs of economic disillusionment as the South African economy has not generated enough employment opportunities to absorb an increasing annual number of school leavers. Lack of employment opportunities is associated with rising poverty, as partly evidenced by the number of people receiving social grants, rising from 2.8 million in 1994 to 13.5 in 2009, whilst the number of taxpayers is around 4 million (Cilliers, 2009). On an expanded definition, South Africa's unemployment rate, which includes the discouraged worker effect, is close to 30 per cent, while the 'official unemployment rate is about 25 per cent in the first quarter of 2010 (SARB, 2010). Statistics South Africa estimates that about 40 per cent of the South African population is below the age of 20 and another 19 per cent is in the 20-30 age group (Statistical release PO302, 2008). In the South African context, persons in the 15-35 age category are regarded as the youth group (National Youth Policy, 1997:7), from which future leaders and wealth producers of the South African economy will emerge.

The youth of South Africa are valued members of the nation. They represent the hopes and aspirations of the country's future development. Although the young individuals have a tremendous potential to make a contribution to the value-adding activities of the country, a high proportion of the youth, about 50 per cent are unemployed or underemployed, and many are condemned to a marginalized existence of poverty on the fringes of the informal economy (Mlatsheni & Rospabe, 2002; Statistics South Africa, 2008). According to a report commissioned by the Umsobomvu Youth Fund, about a third of the South African youth live in poverty (Morrow, Pandey & Ritcher, 2005). Many young individuals lose their self-dignity when they are without a gainful employment for a prolonged period, after years of secondary or tertiary education. Some young persons, out of desperation, resort to criminal activities. Over a third of the prison population in South Africa is under the age of 26, reflecting a high incidence of crime among the South African youth (Morrow et al., 2005).

According to Herrington, Kew and Kew (2010:15), a culture of entrepreneurship can unleash the economic potential of all people in South Africa, particularly the youth. The South African youth need to be provided with options that allow them to contribute towards the economy. The question then arises as to whether the young secondary school learners tend to become engaged in the entrepreneurial environment in the country. This paper thus examines the socio-economic attributes of the secondary school learners in Pietermaritzburg, the capital of Kwazulu-Natal province, and seeks to isolate certain factors that may influence their dispositions to venture into small business entrepreneurship in the future. It is understood that youth entrepreneurship can create employment and income oppor-tunities for young individuals who think imaginatively and apply their skills to risk-taking associated with starting up and running a small firm with a view to answering customer needs. This article consists of five sections. After the introduction, Section 2 presents a brief review of the literature on entrepreneurship in the context of South Africa and with particular reference to the youth. Sections 3 and 4 describe the research objectives and methodology. The results of the study are presented in Section 5. Sections 6 and 7 present some recommendations and concluding remarks.

 

2 Entrepreneurship

Harnessing the creative talents of the youth and promoting a culture of entrepreneurship among our school leavers is critical for fostering youth economic participation and for advancing economic growth and development. An estimated 826 000 youth arrive annually on the labour market, having completed Grade 12 or having dropped out of school and seek employment (Morrow et al., 2005). Given the labour market dynamics in South Africa, it is a reality that many individuals will not find employment after finishing their secondary education. Young people need to be able to think of self-employment as a route to self-empowerment rather than seeking wage employment. This route may be more appealing to the youth if they are adequately exposed to the basics of micro business entrepreneurship at school.

The development of an entrepreneurial spirit among the youth is thus vital to pushing back the frontiers of poverty and generating employment opportunities in South Africa, as well as to addressing problems of delinquency and crime arising from joblessness. Encoura-gingly, various institutions, Ntsika Enterprise Promotion Agency and Khula Enterprise, now merged as the Small Enterprise Development Agency (SEDA), the Umsobomvu Youth Fund (UYF) and recently the National Youth Development Agency (NYDA) have been created by the government to nudge people to self-employment and to support young entrepreneurs. More recently, against the background of a high rate of unemployment in the country, the Youth Entrepreneurship Campaign 2010 (YEC2010) has been set up as partnership between UYF, South African Youth Chamber of Commerce and NAFCOC youth, to promote the culture of youth entrepreneurship and increase the total entrepreneurial activity in South Africa. It is hoped that through these interventions, many individuals in the informal sector may graduate to the mainstream economy in years ahead.

South Africa suffers from a deficiency in high levels of entrepreneurship. According to the Global Entrepreneurship Monitor (GEM) reports, the perceived availability of business opportunity and business skill levels of the people studied in the 2001, 2002 and 2008 were well below the international mean (Driver, Wood, Fisher, Herrington & Segal, 2003:3; Herrington, Kew & Kew, 2009). The GEM report 2005 (Von Broembsen, Wood, Herrington, Shay & Sheppers, 2005) revealed that South Africa displays the lowest levels of entrepreneurial activity of all developing countries, ranking lower than countries such as India, Brazil, Mexico and Argentina. According to the 2009 GEM global report, South Africa ranked 35th out of 54 participating countries with a total early stage entrepreneurial activity rate (TEA) of 5.9 per cent in 2009, which is below the average (11.7 per cent). South Africa's TEA decreased from 9.4 per cent in 2001 to 5.9 per cent in 2009, reflecting that in 2009 fewer individuals (5.9 out of 100) between the ages of 18-64 went into business than in 2001 (GEM, 2010; Herrington, Kew & Kew, 2010). It thus seems that the level of entrepreneurial activity is not high enough to sustain South Africa's growth and employment expectations (Maas & Herrington, 2007). The GEM reports also noted education and training, with gender discrimination as two limiting factors in the environment for entrepreneurship. Similarly, Janse van Vuuren (2005) argues that low entrepreneurial activity in South Africa may result from a lack of knowledge or self-confidence among individuals to start a business. Encouragingly, the proportion of young individuals in the 18-24 age group involved in early-stage entrepreneurial activity increased from 16 per cent to 17 per cent in 2008, and the TEA increased from 5.2 per cent in 2006 to 7.8 per cent in 2008. However, the TEA rate at 7.8 per cent is still below the average (10.6 per cent) for the all GEM countries (Herrington, Kew & Kew, 2010).

Burger, O'Neill and Mahadea (2004:190) point out that in South Africa an increasing number of people start businesses not because they have found an appropriate niche in the market, but because of necessity. Burger et al. (2004:190), Orford et al. (2003:10) and Driver et al. (2001:11) refer to this as necessity entrepreneurship and contrasted it to opportunity entrepreneurship where people start business ventures to react to opportunities which they have perceived in the market. Unlike the opportunity enterprisers, the necessity entrepreneurs usually end up earning below the poverty level, just as is the situation with at least 45 per cent of self employed people in South Africa (Bhorat & Leibrandt, 1998:28).

In spite of the recognition that entrepreneurship is vital to job creation and economic growth in a rapidly flat globalizing world, we do not have sufficient knowledge regarding the 'optimal' way to promote this critical factor from the youth sector. Most of the studies in this area have focused on men and women as adult entrepreneurs, on the informal sector, small, micro and medium-sized enterprises (SMMEs), and large firms in the corporate sector. Accordingly, not much is known about potential entrepreneurs among the secondary school-going learners and the benefits that they may generate to improve youth livelihoods. This study addresses this gap. However, it must be stated that a unique feature of the revised national curriculum (2005) of the outcome based education (OBE) relating to economic and management sciences learning hinge on the development of skills to taking initiative and calculated risks in conceptualizing, starting and running a business. In short, the schooling system should equip the learner to develop entrepreneurial attitudes, knowledge and skills. According to the GEM reports, the proportion of young people who believe they have the skills to start a new business is significantly lower than that in other developing countries. People who believe that they have the ability to start a business are five times more likely than others to attempt starting one (GEM Report 2005:34). The report further states that while there are many different factors which are likely to influence an individual's beliefs in his ability to start a business venture, such as exposure to entrepreneurs among family members and role models or close friends, the education system is a primary influence on an individual's attitudes towards entrepreneurship (Von Broembsen et al., 2005; GEM, 2009; Herrington et al., 2010).

 

3 Aims of the study

This study aims for an improved understanding of potential youth entrepreneurship particularly among secondary school learners in Pieter-maritzburg, in an attempt to determine their pre-entrepreneurial characteristics, their basic understanding of entrepreneurship and whether the school, gender and family environment influence nascent entrepreneurial behavior among the school learners. Some of the entrepreneurial characteristics included whether or not the students' parents owned business, whether or not the students worked at a small business, whether or not a student has a business role model, an exposure to entrepreneurial activity at school and the necessary personal skills and confidence to run a business. There are other entrepreneurial characteristics that are relevant to small business entrepreneurship, such as achieve-ment motivation (n-Ach), locus of control, agreeableness, innovation and extraversion (Timmons, 2007; Shane, 2003). But owing to pressing resource constraints, these latter attributes were not considered in the present study. The main objectives of this study are, thus, to identify the profile of students who aspire to entrepreneurship as a potential career and to examine the socio-economic and demographic influences which motivate them to entrepreneurship.

 

4 Research methodology

This study uses the survey method. To gather information relevant to the research, five secondary schools were chosen randomly in central Pietermaritzburg, the capital of Kwazulu-Natal province. Data collection was made through the use of questionnaires, consisting mainly of closed ended questions, and interviews. The data was analysed by using SPSS. Questions elicited information on issues of learners' demographic profile, socio-economic and family background, acquired skills, experience in and exposure to a small business, role models, and interest in starting a business in the future. The sample consisted of 275 learners from one private, one semi-private and three government schools. The subjects were senior secondary school-going youth learners, specifically grade 10, 11 and 12 scholars. In addition to descriptive statistics, a generalized linear model (GLM) of a quasi logistic regression nature was used to examine propensity of the learners to venture into entrepreneurship at the small firm level. The quasi logistic regression was chosen after examining the model for under and over dispersion. Dispersion exists when the variance of a variable exceeds the mean.

 

5 Results

The results regarding the entrepreneurship perceptions of high school learners in Pietermaritzburg are presented below in two stages. Initially, the results deal with the descriptive statistics, summarized largely in a tabular form. Thereafter, the learners' aspirations towards entrepreneurial activity in the starting of a small business, based on the findings of the quasi logistic regression model, are presented.

5.1 Descriptive statistics

In this study, an almost equal number of learners were randomly drawn from each grade. About 31 per cent, 33 per cent and 36 per cent of the respondents were from grades 10, 11 and 12, respectively. The socio-demographic variables as predictors are encoded as race (Black, Coloured, Indian or White), sex (Boy or Girl), residential area (Urban or Rural), parents own business (Yes or No), have ever worked at a small business (Yes or No), have a business role model (Yes or No) and exposed to entrepreneurial activity at school (Yes or No). The dispositions include having the necessary personal skill to run own business (Yes or No) and confidence to manage own business (Yes or No). Finally, the response variable of interest is whether a learner is interested in starting a small business of his/her own in the future or not. The results on socio-economic attributes of the learners are summarised in Table 1 below.

 

 

Most of the learners that participated in this study (53.5 per cent) came from the private school, 14.2 per cent of the learners came from a semi-private school and 32.4 per cent came from three government schools. With regard to gender, there were more female learners (69.8 per cent) than male (30.2 per cent). The highest number of learners came from the 16-17 years age group (64.7 per cent), whilst the representation from the 14-15 and 18-19 age groups were 20.7 per cent and 14.2 per cent respectively. Of the learners 42 per cent were white, 35 per cent black, 19.3 per cent Indian and 3.6 per cent were coloured. This is so because the majority of the white learners came from the private school. As far as area of location is concerned, 87.1 per cent of the respondents came from the urban area and 12.9 per cent came from the rural area.

Respondents were asked various questions regarding their personal and parental background, involvement in business and acquired skills. Results to the questions of interest are presented below in Tables 2-8.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

•Does your parent own their own business?

The majority of the learners (65.8 per cent) indicated that their parents do not have their own business.

•Have you ever worked at a small business?

As far as work experience is concerned, over half (55.3 per cent) of the learners did not have any work experience in a small business. Only about 45 per cent had some work experience in a business.

• Do you have a business role model?

Here, there was an almost even split with 50.5 per cent of the learners not having a role model and 49.5 per cent having a role model. The eminent business persons, such as Tokyo Sexwale, Patrice Motsepe, Cyril Ramaphosa, Mark Shuttleworth, Bill Gates and their parents were some of the people that learners offered as their role models.

• Have you been exposed to any entrepreneurial activity at school?

Only 52 per cent of the learners have been exposed to an entrepreneurial activity at school whilst 48 per cent have not been exposed to such an activity.

• Do you have the necessary personal skills to run your own business?

Almost 70 per cent of the learners felt that they have the necessary skills whilst 30 per cent felt that they do have the necessary personal skills to run a business.

• Do you have the confidence to manage your own business?

Importantly, 85.5 per cent have the confidence to manage their own business whilst 14.5 per cent felt that they do not have the confidence to manage their own business.

• Are you interested in starting your own small business in the future?

It is worthwhile noting that almost four fifths (78.5 per cent) of the learners are interested in starting their own small business in the future. A generalised linear model approach is used to examine the socio-economic and acquired skills as possible factors in influencing the learners' interest in starting a business in the future. The nature and results of this model are presented below.

5.2 Generalised Linear Model (GLM)

A generalised linear model (GLM) analysis was carried out to investigate the demographic, socio-economic and locational factors affecting the students' interest in starting a small business of his/her own in the future. Since the response variable of interest is dichotomous i.e. yes or no, it may not be reasonable to assume that data are normally distributed. As a result the classical linear model is not applicable. A generalized linear model extends the traditional linear model to a wider range of data analysis problems and a function can be used to link the expected response mean and a linear function of the explanatory variables. Accordingly, the GLM model is used, by choosing an appropriate link function and response probability distribution (McCullagh & Nelder, 1989; Agresti, 2002). The link function simply links the mean response to the explanatory variables whilst the chosen probability distribution is used to model the response variable.

The best known class of generalised linear models for dichotomous responses assume a binomial distribution for the response variable. Although a generalised linear model can be applied to a binomial distribution using a probit, logit or complementary log-log link, the logit link is particularly attractive for a binomial distribution. The resulting model which is called logistic regression is used in this study.

Logistic regression describes the relation-ship between the dichotomous response variable and a set of explanatory variables. The explanatory variables may be quantitative or qualitative. The logistic regression model overcomes the problem of linear regression for binary data by "linking" the binary response to to the explanatory variables through the probability (i.e. π ) of either outcome, which does not vary continuously from 0 to 1. The transformed probability is then modeled linearly with the explanatory variables. The logistic regression uses the logit transformation of the probability, π, of the event of interest, which is starting a business of one's own in the future.

 

 

Therefore, π, the probability of outcome of interest for a given value X1 = x1, X2 =x2, …, Xp=xp is given by:

 

 

Where β0 is the intercept, the βs are regression coefficients of the independent factors (i = 1, 2.. p) .., and Xs are a set of predictors. The βs are typically estimated by the maximum likelihood (ML) method, and it is preferred over the conventional weighted least squares approach. The ML method is designed to maximize the likelihood of reproducing the data given the parameter estimates.

The interpretation of results is rendered using the odds ratio, OR. The OR indicates a measure of the strength of a probabilistic relationship between the explanatory variable and the response variable. This measure ranges from 0 to infinity, with a higher value indicating a stronger relationship between the two variables. If b is the logistic regression coefficient estimate for predictor X, then exp(b) is the OR corresponding to X. In other words, the chance of the outcome of interest for a given category of X is OR(= exp(b)) times that of the reference category of X. The complementary interpretation is the sign of the coefficients: the positive coefficients show the increase of the chances for the given category of X relative to its reference category, and the negative coefficients show the decrease.

Deviance and Pearson Chi-square divided by the degrees of freedom are used to detect over-dispersion or under-dispersion in the logistic regression. Values greater than 1 indicate over-dispersion, that is, the true variance of the response variable is greater than what it should be under the given model. If this happens the resulting estimates are consistent; however, estimates of the variance are not. The over or under-dispersion can result in spuriously small/large standard errors of the estimates (Barron, 1992). This inconsistent variance estimate invalidates any hypothesis testing. The most widely implemented approach to remedy this is the use of "quasi-likelihood", which adjusts the logistic regression to overcome the problem of over and under-dispersion. This adjustment provides for a valid inference (Allison, 1999).

5.3 Logistic regression results

Table 9 shows the results of the logistic regression fit statistic in explaining the interest of high school students in starting a small business in the future.

Based on the results of Table 9, the model does not fit the data well as the values of Pearson Chi-square (233.5885) and deviance divided by the degrees of freedom (225) are significantly less than 1, which shows evidence for some under-dispersion (0.9160). This means that the computed 95 per cent confidence intervals (CIs) are too wide (Table 11) and represent a generous upper bound for the true odds ratios. We refitted the model by adjusting for under-dispersion using the quasi logistic regression. The result is presented in Table 10. The values of Pearson Chi-square (1.0223) and deviance (1.0612) divided by the number of degrees of freedom are both close to 1.

It is reasonable to assess the magnitude of the effect of several factors on an individual learner's intention to start a small business. The results from the quasi logistic regression analysis are presented in Table 11. If the confidence interval includes an exact value of 1, then the result is insignificant and can be interpreted as there being no difference at the 5 per cent level (in the chance of having an interest in starting one's own small business in the future) between a particular category and the reference category. This means that there is no significant difference in the probability of starting one's own business between specified levels of different explanatory or independent variables and the reference category. Otherwise, the chance of having interest in starting own small business in the future for a given category is OR times that of the reference category. In Table 11, if we look at rural area as a reference category, the confidence interval (-0.8766, 1.2190); accordingly the comparison between urban and rural location is not different. Thus, there is no difference in the probability of starting one's own business whether the learner comes from a rural or urban background.

For the same race and grade students, boys are more likely to start their own business than girls. In fact, the chance of a girl's aspiration to have their own business in the near future is 0.3814 (=exp(-0.9638)) times less than the chance for a boy (Table 11). In terms of gender difference, the probability of a girl being interested to run her own business in the future is thus less than that of a boy. This statement is also confirmed by the negative coefficient (-0.9638) associated with the gender predictor.

When controlling for all other variables, the Black learners have the higher aspiration to have their own business as compared to the Indian learners. The Black learners are 7.74 (=exp(2.0465)) times more likely than Indian learners to start their own business in the future. The probability of students who have an interest to own business in the future is identical for Coloured, White and Indian race groups. This is confirmed from the results in Table 11. The comparison between Coloured and Indian learners does not show a difference in their propensity to start a business; the confidence interval of Coloured learners versus Indian learners is (1.5773, 3.1285). Similarly, when comparing White and Indian learners there is no difference between these groups in their propensity to start a business; the confidence interval between the White learners versus Indian learners which is (-0.7009, 0.9191).

For a given race, grade 11 students' aspiration rate to own a business is 0.402 (=exp(-0.9106)) times that of grade 12 students. To the contrary, grade 10 students' aspiration rate is not significantly different, at the 5 per cent level, from that of grade 12 students' aspiration rate to own business in the future. The proportion of learners who have an interest to own business in the future is identical for the grade 10 and grade 12 learners.

Those scholars who feel that they have the necessary personal skills to run their own business are about 2.68 (=exp(0.9883)) times more likely to start their own business than those who feel they do have the personal skills to start their own business. This result accords with the findings of the GEM reports.

With regard to having a role model or not, the results indicate that learners who have a role model are 2.14 (=exp(0.7615)) times more likely to start their own business than their counterparts that do not have a role model. Thus, having a business role model and the necessary personal business skills are critical significant factors in influencing someone to start a new business. Of great interest to increase potential entrepreneurship is the influence of ethnic background. It must be reiterated that the results indicate that black school learners are found to have a significantly greater likelihood (7.74 times) to start their own ventures than the Indian learners (Table 11). This result tends to accord with those of Burger et al. (2004) and the GEM report (2009).

Similarly, learners who do not have the necessary personal skills to run their own ventures are more likely to enter the labour market as wage employees rather than as employers. On the other hand, the confidence to manage a business, work experience in a small business, the locational background of the learner, and whether or not the learner's parents owned a business do not appear to significantly influence a learner's propensity to start a small business of their own in the future. This tends to suggest that entrepreneurship is a complex phenomenon that is not necessarily confined to an individual that comes from a business background or an urban location. Entrepreneurship is thus a learnable attribute (Drucker, 2002), and potential entrepreneurs come from diverse backgrounds and not necessarily from a business family. However, certain elements of entrepreneurship cannot be taught, as these can be an inborn trait into an individual's DNA. Nevertheless, potential entrepreneurs can be 'made' and their entrepreneurial potentials can be activated or switched on through openness to experience, learning and ideas (Harrison, 2005:16).

 

6 Limitations

One of the shortcomings of this study is that the schools considered are only from urban areas, though the learners are both from urban and rural areas. Perhaps one of the reasons why the black learners have a higher aspiration to have their own business as compared to the other race group learners might be linked to the immediate need to contribute their family livelihood. Accordingly, a future direction of this study is to investigate the entrepreneurial aspirations of the high school learners in both urban and rural schools of South Africa.

Basically, most high school learners in a general education program are preparing to enter the labour market as job-seekers rather than self-employed job-creators, and only a small proportion pursue university education. Career guidance is rather limited. We are curious why boys have a greater propensity toward entrepreneurship than girls. Perhaps the business role models are mainly men and the perception that entrepreneurship a male-dominated field meant mainly for men will be the main obstacle against the effort exerted in building a culture of entrepreneurship in South Africa. Another aspect of the future direction of this study is to assess whether the high school learners believe that entrepreneurship is predominantly a masculine or gender related activity.

Further this study was rather narrow in its consideration of entrepreneurial characteris-tics. It is important to consider whether other entrepreneurial attributes, such as need for achievement, locus of control, extraversion and innovation, do influence young learners' propensity to consider business entre-preneurship as a career option in South Africa. Hopefully, the results of a future study on these attributes may serve to support the literature and findings of other researchers, such as McClelland (1961), Rotter (1966), Evans and Leighton (1986), Storey (1994), Hirsch and Peters (2001), Shane (2003), and Herrington, Kew and Kew (2010). They have found that, inter alia, the level of education, n-Ach, locus of control, innovative behavior, experiential or environmental factors and gender, as well as access to resources are critical determinants of an individual's propensity to venture into business entrepreneurship and succeed in such a role.

 

7 Recommendations

Youth are favourably disposed towards small business entrepreneurship. The youth constitute the major percentage of the South African population and their significance for future economic expansion cannot be discounted. Against a background of low labour low absorption capacity of the formal sector in South Africa, that decreased from 80 per cent in the 1970s to 50 per cent after 2000 (Barker, 2007), and of low employment elasticity of economic growth, that has decreased from 0.55 in the 1980s to 0.33 in the early 2000s (Barker, 2007), it is encouraging that the many young individuals at the Pietermaritzburg secondary schools, particularly among the black learners display high potential levels of entrepreneurial propensity. A very high proportion of the learners (about 70 per cent) have a fair understanding and skills of how to manage or run their own business and possess reasonably high levels of entrepreneurial confidence. With the creative energy and vibrancy of the youth group, it is possible that many young individuals are likely to be grabbers of opportunity rather than reactive necessity enterprisers who venture into entrepreneurship because they have no alternative option.

Business is about competitiveness, innova-tion, knowledge, resources and people skills to serve customer needs. Over half of the learners (52 per cent) have been exposed to business entrepreneurship at schools. Almost two thirds (69.8 per cent) believe that they have acquired the necessary skills to create and manage their own business and about half have suitable business role models to whom they want to aspire. This result is consistent with the findings of Burger et al. (2004) and various GEM reports in South Africa (Driver et al., 2005; Orford et al., 2003; Herrington et al., 2010). The learners felt that their participation in entrepreneurial ventures at schools enhances their entrepreneurial propensity. While entrepreneurship confidence among the youth in South Africa is growing, it should be recognised that not all young educated people can become entrepreneurs. Although the positive value of entrepreneurship education at secondary schools cannot be ignored, a stronger base for self-employment can be created if this positive mind-set is extended to tertiary education learners with possibilities for business incubators and strategic alliances among learners and institutions.

The majority of the surveyed learners in government and semi-private schools may not necessarily have strong financial backgrounds and thus see the opportunity of starting their own businesses as a means to gain income and improve the overall quality of their lives. Fewer learners (37 per cent) attending the private school compared to learners in the public schools indicated that they would start a business of their own in the future. However the private school learners were specifically from a girls' high school. It is to be understood that many of the girls from the surveyed private learning institution are from a comfortable background, as many of their parents are in well-remunerated professions. And the female learners may have career aspirations and marriage with future family plans that limit their propensity to go into self-employment. So for the latter group, entrepreneurship is a less preferred career option relative to professional employment, as the opportunity cost for the entrepreneurial path may be perceived to be rather high in terms of forgone income, quality of life, leisure time, risk-taking hazards owing to high crime rates and intrinsic rewards.

Entrepreneurial education is one of the keys to solving the economic problem in South Africa. Burger, Mahadea and O'Neil (2004:203) state that "entrepreneurship is critical to combating unemployment and poverty in South Africa". However, transforming generations of young learners is by no means an easy feat. Many individuals in South Africa perceive that obtaining a job in the government sector is a preferred career option because of the attractions of security, gravy train or rent-seeking tendencies and corruption. However, the fact that the revised national high school curriculum now includes topics that cover entrepreneurship and self-employment is extremely positive and a step in the right direction towards attitudes to enterprise development and building a culture of entrepreneurship in South Africa.

 

8 Conclusion

From the current research it is apparent that race group plays an important role in determining a learner's propensity to become an entrepreneur. Black learners have a greater positive disposition towards becoming entrepreneurs compared to learners belonging to other ethnic groups. This fact is also echoed in Burger et al. (2004:203) and GEM reports (Orford et al., 2003; Herrington et al., 2009). The type of school or the learning environment that an individual is exposed to also plays a pivotal role in determining whether or not a learner is favourably disposed towards becoming an entrepreneur.

It is an established fact that drugs, child abuse, teenage pregnancies and school drop-outs are major setbacks among learners in certain schools. Having the relevant entrepreneurial skills and career choice knowledge as well as relevant counseling can influence youth learners in becoming entrepreneurs and hence minimise business failures. Burger et al. (2004:204) state that "with relevant education and training as well as adequate entrepreneurial development support, youth entrepreneurship can be further empowered". In particular, exposing the emerging youth entrepreneurs to cutting edge education and training, modern business ideas and technology, and global markets, and addressing constraints specific to their business entry or expansion phases are challenges that need to be addressed. Overall it is positive to see the extent to which learners' desires and ambitions are being adapted and shaped through relevant entrepreneurship education in secondary schools in Pietermaritzburg, KZN. This could form a sound basis for an enhanced total entrepreneurship activity rate in South Africa, much needed for employment creation and economic development against a background of job losses and recessionary circumstances.

 

References

AGRESTI, A. 2002. The analysis of categorical data, New York: Wiley.         [ Links ] ALLISON, P. 1999. Logistic regression using the SAS System, SAS Publishing.         [ Links ] BARKER, F. 2007. The South African labour market, Pretoria: Van Schaik.         [ Links ]

BARRON, D. 1992. The analysis of count data: overdispersion and autocorrelation in Sociological Methodology, Peter V. Marsden (ed.): 179-220: Blackwell.         [ Links ]

BHORAT, M. & LEIBRANDT, M. 1998. Poverty amongst the self employed. Studies in Economics and Econometrics, 22(3):25-41        [ Links ]

BURGER, L; O'NEILL, C. & MAHADEA, D. 2004. Perceptions of entrepreneurship as a career option in South Africa: an exploratory study among grade 12 learners. South African Journal of Economics and Management Science, 2:187-205        [ Links ]

CILLIERS, S. 2009. For richer or for poorer, in Weekend Witness, 5 Dec.         [ Links ]

DRIVER, A., WOOD, E., SEGAL, N. & HERRINGTON, M. 2001. Global entrepreneurship monitor, South African Executive Report, Cape Town: INCE.         [ Links ]

DRIVER. A., WOOD, E., FISHER, C., HERRINGTON, M. & SEGAL, N. 2003. Global entrepreneurship monitor: 2001, South African Executive Report, Cape Town: INCE.         [ Links ]

DRUCKER, P. 2002. Innovation and entrepreneurship, New York: Harper & Row.         [ Links ]

GEM. 1999. Global Entrepreneurship Monitor, Executive Report Babson College, Kauffman Foundation and London.         [ Links ]

GEM. 2003. Global Entrepreneurship Monitor, Executive Report, Babson College, Kauffman Foundation and London.         [ Links ]

GEM. 2009. Global Entrepreneurship Monitor, Executive Report Babson College, Kauffman Foundation and London.         [ Links ]

EVANS, D.S. & LEIGHTON, L.S. 1986. Some empirical aspects of entrepreneurship. American Economic Review, 76 (4):519-535.         [ Links ]

HARRISON, T.L. 2005. Instinct: tapping your entrepreneurial DNA, New York: Warner Business Books.         [ Links ]

HERRINGTON, M., KEW, J. &. KEW, P. 2009. Global entrepreneurship monitor: 2008, South African Executive Report, UCT: Graduate School of Business.         [ Links ]

HERRINGTON, M., KEW, J. &. KEW, P. 2010. Tracking entrepreneurship in South Africa: A GEM perspective, UCT: Graduate School of Business.         [ Links ]

HISRICH, R.D. & PETERS, M.P. 2001. Entrepreneurship, New York: McGraw-Hill.         [ Links ]

JANSE VAN VUUREN. 2005. Land het gemiddeld minder woekeraars as sy ontwikkelende eweknieë: SA gaan mank aan entrepreneurs. Sake-Beeld: 20, 11Feb.         [ Links ]

KASSIEM, A. 2003. 75 per cent of matriculants won't get jobs or further education. Cape Times, December 24. [Online} Available at: http://www.capetimes.co.za/index/php.         [ Links ]

MAAS, G. & HERRINGTON, M. 2007. Entrepreneurship: low levels threaten growth. Management Today, 23(2).         [ Links ]

McCLELLAND, D. 1961. The achieving society, Van Nostrand: Princeton.         [ Links ]

McCULLAGH, P. & NELDER, J.A. 1989. Generalised linear models, London: Chapman & Hall.         [ Links ]

MLATSHENI, C. & ROSPABE, S. 2002. 'Why is youth unemployment so high and unequally spread in South Africa', DPRU Working Paper No. 02/65, Development Policy Research Unit. University of Cape Town.         [ Links ]

MORROW, S., PANDAY, S., RICHTER, L. 2005. Where are we now and where are we going: Young people in South Africa, Johannesburg: Umsobmvu Youth Fund.         [ Links ]

ORFORD, J., WOOD, E., FISCHER, C., HERRINGTON, M. & SEGAL, E. 2003. Global entrepreneurship monitor, South African Executive Report, UCT: Graduate School of Business.         [ Links ]

REPUBLIC OF SOUTH AFRICA. 1997. National youth policy, Pretoria: National Youth Commission.         [ Links ]

REPUBLIC OF SOUTH AFRICA. 2005. Revised national curriculum statement, Pretoria: Department of Education.         [ Links ]

REPUBLIC OF SOUTH AFRICA. 2005. Revised national curriculum statement additional, Pretoria: Department of Education.         [ Links ]

ROTTER, J.B. 1966. Generalised expectancies for internal and external control of reinforcement, Psychological Monographs: General and Applied, 80(1).         [ Links ]

SARB. 2009. South African Reserve Bank Quarterly Bulletins: 251-253 (March)         [ Links ]

SARB. 2010. South African Reserve Bank Quarterly Bulletins: 256 (June), Pretoria.         [ Links ] SHANE, S. 2003. A general theory of entrepreneurship, Cheltenham: Edward Elgar.         [ Links ]

STATISTICS SOUTH AFRICA. 2001. The youth of South Africa report, Pretoria: Statistics South Africa        [ Links ]

STATISTICS SOUTH AFRICA. 2008. Mid-year population estimates 2008, Statistical release PO302, Pretoria        [ Links ]

STOREY, D.J. 1994. Understanding the small business sector, London, Routledge.         [ Links ] TIMMONS, J.A. 2007. New venture creation, New York: McGraw-Hill.         [ Links ]

VON BROEMBSEN; WOOD, E.; HERRINGTON, M.; SHAY, D. & SHEPPERS, R. 2005. Global entrepreneurship monitor, South African Report, UCT, Cape Town.         [ Links ]

 

 

Accepted November 2010