Description
South Africa has entered the era of industry transformation charters that have to be harmonised with the Department of Trade and Industry's broad-based black economic empowerment (B-BBEE) scorecard and codes of good practice. In these charters, targets are set with regard to ownership, management, skills development, BEE procurement, enterprise development, facilitation of finance for BEE and corporate social investment (CSI).
58 Southern African Business Review Volume 14 Number 1 2010
An empirical analysis of a private company’s
corporate social investment in SMME development
in South Africa
E. Swanepoel, J.W. Strydom & C. Nieuwenhuizen
A B S T R A C T
South Africa has a very high unemployment rate, low economic
growth and dismal Total (early-stage) Entrepreneurial Activity (TEA)
preformance. Both government and private businesses are attempting
to address this problem. A private company, the South African
Breweries (SAB), as part of their corporate social investment, runs
the SAB KickStart Programme to establish and grow entrepreneurial
small businesses among young South Africans. The programme
applies four interventions: General Enterprising Tendency test; two-
week live-in business management training; funding and mentoring;
and a national competition for prize money. Taking into consideration
the cost of funding and operating the programme, its e?ectiveness
required investigation. The population for the study comprised all
the participants of the SAB KickStart Programme, from 2001 to
2006. From an analysis of variance (ANOVA) applied to the turnover
and percentage pro?t ?gures of respondents, it was deduced that
funding and mentoring, after training, add value to the programme.
The programme contributes to enterprise sustainability ,as 80 per
cent of the respondents were still operating their initial businesses,
while a further six percent have started another business – hence, a
‘failure’ rate of only 14 per cent. In conclusion, it can be said that the
SAB KickStart Programme adds value, advances entrepreneurship,
and can be replicated by other large institutions in South Africa.
Key words: entrepreneurship, SME development, SMME development, corporate social
investment, training, funding, mentoring, SAB KickStart Programme, youth
development
Dr E. Swanepoel is a Senior Lecturer of Entrepreneurship in the Department of Business Manage-
ment, School for Manage ment Sciences, University of South Africa. Prof. J.W. Strydom is a Profes sor
of Business Management in the same department, and Prof. C. Nieuwenhuizen is a Profes sor in the Depart-
ment of Business Management, University of Johannesburg.
E-mail: [email protected]
An empirical analysis of a private company’s corporate social investment in SMME development
59
Introduction
South Africa has entered the era of industry transformation charters that have to
be harmonised with the Department of Trade and Industry’s broad-based black
economic empowerment (B-BBEE) scorecard and codes of good practice. In these
charters, targets are set with regard to ownership, management, skills development,
BEE procurement, enterprise development, facilitation of finance for BEE and
corporate social investment (CSI). It is possible for companies to spend some of the
CSI on entrepreneurial and small and medium enterprise (SME) development. The
purpose of this study is to analyse the effectiveness of a highly regarded CSI SME
development programme and to use the findings as a benchmark for subsequent
comparative studies of similar CSI programmes in South Africa. In 2002, after
completing a study on SME training in the Northern Province (which has since
been renamed Limpopo Province), Ladzani and Van Vuuren (2002) concluded that
SME service providers should benchmark their services against similar successful
institutions.
Despite good economic growth in the past, a major concern for South African
economists is the lack of job creation, which results in high unemployment, for
example, 21.9% in March 2009 (StatsSA 2009). In South Africa, the sector including
micro, very small and small businesses comprised 93% of all enterprises (in March
2007), contributed 27–34% of total gross domestic product (GDP) in 2006 (dti 2008)
and accounted for 38% of employment (Rogerson, in dti 2008). From these statistics,
it is evident that the sustainability and growth of small business are vital topics for
research.
The low level of entrepreneurial activity in South Africa is of concern, because
entrepreneurs are involved in the establishment and growth of new and existing
enterprises of varying sizes, including small businesses. The cross-national data of the
Global Entrepreneurship Monitor (GEM) indicate that South Africa’s Total (early-
stage) Entrepreneurial Activity (TEA) performance, in terms of relative position,
has consistently been below the median since 2001 (Herrington, Kew & Kew 2008).
The authors found that South Africa’s nascent entrepreneurship rate (which relates
to setting up a business) of 5.7% is below the GEM average of 6.2% as well as the
average of 6.7% for efficiency-driven economies. In terms of new firm activity (which
relates to firms up to 3.5 years old), South Africa ranked 38
th
out of the 43 countries
with a new business prevalence rate of only 2.1% (which was below the 4.6% average
for all GEM countries and 4.9% average for all efficiency-driven countries). In terms
of established business activity (which relates to firms older than 3.5 years), South
Africa ranked 41
st
out of the 43 countries, with an established business rate of 2.3%
E. Swanepoel, J.W. Strydom & C. Nieuwenhuizen
60
(which was below the 7.7% average for all GEM countries and 6.9% for all efficiency-
driven countries).
The GEM results seem to indicate that not only does the need exist in South
Africa to increase the number of start-up businesses, but also to grow businesses
beyond the start-up and new firm stages to the established stage in order to increase
their contribution to job creation and economic growth. To remedy this situation, the
GEM 2004 report (Orford, Herrington & Wood 2004) recommends, among other
things, rethinking support to small enterprises (concentrating on facilitating private
sector service provision) and improving the financial and general management
capacity of small enterprises to increase start-up survival rates through targeted
training and experienced mentoring.
Objectives of the study
The objective was to investigate an existing programme by evaluating the
effectiveness of the interventions used by the SAB KickStart Programme to establish
and grow entrepreneurial SMMEs. Botha, Nieman and Van Vuuren (2007) pointed
out that in the area of entrepreneurship, an aspect that is not researched much is
the effectiveness of training interventions, especially considering the cost of such
programmes to sponsors and participants alike. Their study proved that their
Women Entrepreneurship Programme was effective in training potential, start-up
and established women entrepreneurs in South Africa.
To increase the number of start-up businesses and grow businesses beyond the
start-up and new firm stages to the established stage, the GEM 2004 report (Orford
et al. 2004) recommends, among other things, rethinking support to small enterprises
(concentrating on facilitating private sector service provision) and improving the
financial and general management capacity of small enterprises to increase start-
up survival rates through targeted training and experienced mentoring. The South
African Breweries (SAB) has for many years complied with both these suggestions
through several of its programmes as part of corporate social investment (CSI) and
black economic empowerment (BEE) programmes such as the barley farmer scheme,
owner truck driver scheme, distribution operator scheme, customised delivery service
scheme, HoneyBEE franchised distribution centres, retail normalisation of taverners
and their flagship programme, and the SAB KickStart Youth Entrepreneurship
Programme (SAB Ltd 2006).
SAB Ltd is the largest subsidiary of SABMiller plc, the second-biggest brewer
by volume in the world, present in over 40 countries in Europe, North and Latin
America, Asia and Africa (SABMiller 2008). It is the biggest contributor to the South
An empirical analysis of a private company’s corporate social investment in SMME development
61
African fiscus – contributing R6 billion in tax and excise duty in 2004 (SABMiller
2005). Another reason for evaluating the existing SAB KickStart Programme stems
from the fact that SAB intends to emulate the SAB KickStart Programme in other
countries in Africa, South America and the rest of the world.
SAB Kickstart Youth Entrepreneurship Programme
There were two fundamental reasons for selecting the SAB Ltd’s KickStart
Programme. Firstly, the SAB KickStart Programme is recognised by the South
African government in its Integrated Strategy on the Promotion of Entrepreneurship
and Small Enterprises (dti 2007) as a benchmark programme for fostering business
start-ups. Secondly, SAB is highly regarded by its fellow corporations as the strongest
contributor to job creation and entrepreneurial development in a 2007 survey (De
Wet 2007). Since the advent of industry transformation charters, companies may look
to emulating the SAB KickStart Programme, because SAB has managed to score
points by leveraging BEE procurement and CSI funds for optimal developmental
impact. SAB, as part of its CSI initiatives, has invested more than R36 million in
entrepreneurial BEE SMMEs through the SAB KickStart Programme.
Nature of the SAB KickStart Programme
Since its inception in May 1995, the SAB KickStart Programme has helped
launch over 3 000 businesses, many of which have grown into multi-million Rand
concerns. In 2001, the SAB KickStart Programme switched from a numbers-
driven approach, which focused on poverty alleviation, to a quality-driven and
carefully monitored intervention at the SMME level with the aim of inculcating a
culture of entrepreneurship and creating sustainable enterprises among previously
disadvantaged young adults (blacks, coloureds and Asians – official terminology
used in South Africa to describe different races) between the ages of 18 and 35.
Fewer participants are selected for training, while greater emphasis is placed on post-
training mentorship and assistance. The SAB KickStart Programme takes about
15–18 months for a cycle to be completed.
In April every year, the SAB KickStart Programme launches an awareness
campaign, requesting interested nascent and existing entrepreneurs between the
ages of 18 and 35 years to apply. Judged by the information on the application
form, the business plans and financial statements, the thousands of applicants are
whittled down to 40 candidates per SAB region (five regions), who complete the
General Enterprising Tendency (GET) test. The applicants with acceptable scores
E. Swanepoel, J.W. Strydom & C. Nieuwenhuizen
62
appear before a regional panel, which selects 20 entrepreneurs per region (100 in
total per year) to attend a two-week live-in training session that includes training in
entrepreneurship and business skills, such as production management, marketing,
financial management, human resources management and the business plan.
Training is presented by an independent trainer, and a training manual is handed
out to the participants. On completion of the course, the participants are given one
month in which to prepare a business plan on a preferred business idea. In each
region, they present their business plans to a panel of adjudicators. Based on the
results, each region allocates discretionary grants from its R300 000 budget to ‘kick-
start’ five to eight of the most promising potential businesses or existing businesses.
The grants could range from R50 000 to R120 000 per business. The grant includes
eight months of mentoring. SAB also provides direct support through networking to
stimulate business development and helps the small businesses gain public relations
exposure. About six months later, each region selects its three top performers. The
regional finalists present their businesses to a national adjudicating panel, which
chooses the national prize winners. The top winners take a share of R700 000 in
prize money, which includes business mentorship for a further six months. At all
stages, adjudication is based on business plans, performance data and presentations
by the participants.
Four interventions are used to enhance the effectiveness of the programme, namely
a selection process (involving the General Enterprising Tendency test, business plans
and presentations to adjudicating panels), two-week in-house training, funding and
mentoring, and prize money. Owing to the fact that the continued involvement with
the participants through the provision of funding after completion of the training
(27 participants received R2.7 million in grants and prizes in 2006) and mentoring
(paid for by SAB) is costly and time consuming, as it involves a substantial amount
of organisation, administration and monitoring by both the SAB head office and
regional offices, the following research question surfaced: Does the performance of
those participants who received training, funding and mentoring exceed those who
received only training? This question translates into the following hypothesis:
Null hypothesis (H
0
): No difference exists between the performance of businesses of
SAB KickStart participants who received training, grants and mentoring and those
businesses of SAB KickStart participants who received only training.
Alternate hypothesis (H
1
): The businesses of SAB KickStart participants who
received training, grants and mentoring perform better than the businesses of SAB
KickStart participants who received only training.
An empirical analysis of a private company’s corporate social investment in SMME development
63
Testing this hypothesis is of particular relevance in the economic climate of
recession, as private enterprises could easily consider cutting back on their corporate
social investment and in particular on entrepreneurial development.
Theoretical background
Entrepreneurial ventures versus small businesses
Entrepreneurship is an evolving concept. Recognising this fact, Kuratko and
Hodgetts (2004: 30) developed an integrated definition that acknowledges the critical
factors needed for this phenomenon, including the cognitive scripts of arrangements,
willingness and ability:
Entrepreneurship is a dynamic process of vision, change and creation. It requires an applica-
tion of energy and passion towards the creation and implementation of new ideas and creative
solutions. Essential ingredients include the willingness to take calculated risks – in terms of
time, equity, or career; the ability to formulate an effective venture team; the creative skill to
marshal needed resources; the fundamental skill of building a solid business plan; and, finally,
the vision to recognize opportunity where others see chaos, contradiction, and confusion.
Owing to the comprehensive nature of this definition, it is accepted for the purposes
of this study. The difference between entrepreneurial ventures and small businesses
is explained by Wickham (2004), who claimed that it is the combination and depth
of three characteristics, namely innovation, potential for growth and strategic
objectives, that add up to distinguish the key characteristic of the entrepreneurial
venture, namely that it is a business that makes significant changes to the world.
The entrepreneur as prime mover of economic development
In 1911 Joseph Schumpeter published his work, Theory of Economic Development, in
which he identified the entrepreneur as the prime mover of economic development
through the introduction of new combinations, such as new products, new techniques,
new forms of organisation, new markets and new sources of materials (Schumpeter
1934, 1939, 1942, in High 2004). Several studies on the impact of entrepreneurship
on economic growth (Brock & Evans 1989 and Carree & Thurik 2000, in Fisher
2004; Carree & Thurik 2003) confirmed that entrepreneurship contributes to
economic growth. A “causal relationship between the GDP per capita of a country
and the extent and nature of its entrepreneurial activity” was established in 2004 by
the Global Entrepreneurship Monitor (GEM) international research team and the
findings confirmed by the GEM 2005 Executive Report (Von Broembson, Wood
E. Swanepoel, J.W. Strydom & C. Nieuwenhuizen
64
& Herrington 2005: 15). Research by Van Stel, Carree and Thurik (2004), using
the Total Entrepreneurial Activity (TEA) variable from the GEM and the Growth
Competitiveness Index, found that entrepreneurial activity affects economic growth.
In a World Bank survey, Voices of the Poor, of 60 000 poor people interviewed in
more than 50 countries, the majority claimed that they had escaped from poverty
by starting their own business (World Bank 2006: 1). The World Bank advises that
“jobs in the formal economy are a priority for countries in Africa – which have the
most obstacles to doing business and are reforming more slowly than anywhere else”.
The relationship between training and entrepreneurial perfor-
mance
Wickham (2004) developed a model illustrating that successful entrepreneurial
performance is the outcome of the integration of industry knowledge, general
management skills, personal motivation and people skills. The general management
skills include strategy, planning, marketing, financial, project management and time
management skills, while the people skills include leadership, motivation, delegation,
communication and negotiation skills. Entrepreneurship and SME training facilitate
the acquisition of these skills. Researchers such as Kennedy and Drennan (2000)
found that the performance of new ventures improves for those entrepreneurs who
have higher levels of education, previous entrepreneurial experience and experience
in similar businesses. According to Timmons and Spinelli (2004: 64), “successful
entrepreneurs possess not only creative and innovative flair, but also solid general
management skills, business know-how, and sufficient contacts”.
Factors that may inhibit potential entrepreneurs from pursuing entrepreneurship
include a lack of training for entrepreneurs, the risks posed by the business
environment, a lack of suitable human resources and legal restrictions on business
activity (Wickham 2004). However, to eliminate these inhibitors, entrepreneurs
can access a range of support initiatives, such as funding, mentoring, networking,
incubation space, start-up training, development training, third-level facilities
(institutions), and third-level expertise (De Faoite, Henry, Johnston & Van der Sijde
2004).
Funding and entrepreneurial performance
One of the inhibitors to becoming an entrepreneur is an inability to secure start-up
capital and the high cost of start-up capital (Wickham 2004). Audretsch (interviewed
by Landström 2005: 230) suggested that “having financial support – not necessarily
An empirical analysis of a private company’s corporate social investment in SMME development
65
venture capital, because most small businesses don’t use venture capital – but to
have the kind of institutions that provide loans to small business seems to be very
important”.
Value-added by the suppliers of capital
‘Classic’ venture capitalists providing seed, start-up and early growth finance often
deal with talented but inexperienced teams (Bygrave & Timmons 1992 and Reynolds
et al. 2002, in Maula, Autio & Murray 2005). Being able to impart critical knowledge
and experience in addition to finance may be instrumental in the survival and success
of the portfolio firm (Gorman & Sahlman 1989; Hellman & Puri 2002; MacMillan
et al. 1989; Sapienza 1992; Sapienza et al. 1994; Sapienza et al. 1996, in Maula et
al. 2005). MacMillan et al. (1989, in Maula et al. 2005: 104) reported that activities
that attracted the highest degree of venture capitalist involvement are: “serving as a
sounding board to the entrepreneur team, helping the firm obtain alternative further
sources of equity financing, interfacing with the investor group, monitoring financial
performance, monitoring operating performance, and helping their portfolio firms
attract alternative sources of debt financing”. Gorman and Sahlman (1989, in
Maula et al. 2005: 104) found similar results: “help with the obtaining of additional
financing, strategic planning, management recruitment, operational planning,
introduction to potential customers and suppliers, and resolving compensation
issues”. In their research comparing value added by independent venture capitalists
with corporate venture capitalists, Maula et al. (2005) found that independent
venture capitalists seem to be better at satisfying the needs of entrepreneurs when
assisting with arranging finance, recruiting key employees, advising on competition
and developing the organisational resources of the growing enterprise. Corporate
venture capitalists seem to be more effective in attracting new domestic and foreign
customers and helping start-ups develop their technologies.
From the discussion, it would seem that in order to ensure success, the provider of
finance should be involved in a range of additional activities that border on mentoring.
Mentoring and entrepreneurial performance
Collin’s (1979, in Sullivan 2000: 169) defines mentoring as “a protected relationship
in which learning and experimentation can occur, potential skills can be developed,
and in which results can be measured in terms of competencies gained, rather than
curricular territory covered”. It implies a long-term relationship between the mentor
and the protégé(e), allowing time for experimentation and reflection, as well as for
E. Swanepoel, J.W. Strydom & C. Nieuwenhuizen
66
collaboration and advice (Graham & O’Neil 1997, in Bisk 2002). Research that used
previous or existing entrepreneurs to support and advise new start-up entrepreneurs
has proved that mentors provide added-value interventions that are likely to bring
long-term benefits to entrepreneurs (Sullivan 2000). Hisrich and Peters (2002: 74) are
of the opinion that “a mentor–protégé relationship is an excellent avenue of securing
needed professional advice, as well as providing an additional source of moral
support”. Research that established the importance of the trainer-motivator, whose
qualifications and experience were found to be vital to the success of the Indian
Entrepreneurial Development Programme (Awasthi & Sebastian 1996, in Watson
2004), corroborates this statement. In a British study, Kent, Dennis and Tanton
(2003) found that a one-year mentoring programme enabled SME retailers to reach
their objectives – maximising sales, adapting to change and developing new ideas.
Methodology
This case study research design incorporated positivistic and phenomenological
research paradigms. Both the qualitative and quantitative approaches to research
were utilised (Leedy & Ormrod 2005: 94–95). The study started off as exploratory
research followed by descriptive research, progressing to analytical/explanatory and
predictive research (Hussey & Hussey 1997: 13).
The population for this study consisted of all the entrepreneurs selected to
participate in the SAB KickStart Programme from 2001 to 2006. (In order to include
the 2006 intake, who completed their programme in 2007, the survey was undertaken
at the end of 2007.) The database provided by SAB consisted of 502 names. Owing
to the limited size of the population, a sample was not drawn; instead, a serious
and prolonged attempt was made to contact every person in the population of SAB
KickStart participants, and 442 were traced. A total of 143 questionnaires was
eventually returned, which represented 28.5% of the population of 502.
Since a sample from the population was not drawn, the question whether the
sample is representative of the population is not relevant. The possibility of respondent
bias, however, was a concern, and the question arose whether only a certain type
of person had responded to the questionnaire. The distribution of the respondents
was compared with the only available attributes of the SAB KickStart population
distribution, and it was found that by year, by SAB region and by gender, the two
distributions are similar. A sufficient percentage of grant winners were among the
respondents (45%) in comparison to the SAB KickStart population (37%).
The participants in the SAB KickStart Programme are spread throughout all
nine provinces in South Africa, mostly in the major cities but also in rural areas. A
An empirical analysis of a private company’s corporate social investment in SMME development
67
paper-and-pencil questionnaire was e-mailed, faxed or posted to the participants.
The questionnaire was only available in English, a fairly commonly used language
in South Africa, which has 11 official languages. Participants were assured of
anonymity and confidentiality. Demographic information about the respondents,
performance information about their businesses and experiences, and perceptions
regarding the four interventions that constitute the SAB KickStart Programme were
obtained. However, in this article only two of these interventions will be addressed,
namely ‘training’ and ‘funding and mentoring’. Some of the questions required the
respondent to select an appropriate option from a range of options on a four-point
Likert scale, which results in the Likert scaling being a bipolar scaling method,
measuring either a positive or negative response to a statement. The chi-squared test
is a common statistical procedure used after this transformation (Keller & Warrack
2000). Both descriptive and inferential statistics are utilised in the study of the
effectiveness of the SAB KickStart Programme.
With regard to the variable of ‘receiving training, funding and mentoring’, a
static group comparison was used to show that “change occurs following, but only
following, a particular treatment” (Leedy & Ormrod 2005: 236). In the study, all
respondents had received training, but only a selected number had received funding
and mentoring. The pre-experimental design of this variable is illustrated in Table 1.
Table 1: Pre-experimental design: static group comparison
Group Time ?
SAB KickStart
participants
Baseline treatment
(training)
Funding (regional grant)
and mentoring
Additional funding (national
prize) and mentoring
Group 1 Trained T
xa
Group 2 Trained T
xa
Funded and mentored T
xb
Group 3 Trained T
xa
Funded and mentored T
xb
Funded and mentored T
xc
Although the original intention was to compare the three groups, this was not
possible because the number of respondents in group 3 was too small. Groups 2 and 3
were collapsed into a single group of respondents who had been trained, funded and
mentored. A limitation of the pre-experimental design is that it fails to determine the
pre-treatment equivalence of the groups.
In the study, all the respondents had received training, but only the participants
who received funding also received mentoring by design. With 79 respondents who
received only training and 64 respondents who, in addition to training, received
E. Swanepoel, J.W. Strydom & C. Nieuwenhuizen
68
funding and mentoring, it was possible to test for statistically significant differences
between these two groups, using the General Linear Model approach to analysis of
variance. The two independent variables are ‘trained only’, compared with ‘trained,
funded and mentored’, with performance being the dependent variable.
Results
Demographic pro?le of SAB KickStart participants
The contribution of the SAB KickStart Programme is better appreciated if one looks
at the demographics of the participants. Demographically, the characteristics of the
respondents reflected the SAB KickStart population with regard to the following
attributes. Respondents were from each of the six start years (2001 to 2006), with 51%
from the two latter years owing to the greater accuracy of the contact details. Each of
the five SAB regions was represented. The gender distribution was exactly the same
as the population distribution – 70% male and 30% female. It should be noted that
the gender distribution of the South African population is about 49% male and 51%
female (Stats SA 2007).
The majority of the respondents (75%) were between the ages of 26 and 35 years,
while 15% were between 18 and 25 years. This is in line with the programme policy of
assisting youth between the ages of 18 to 35. It also addresses the fact that, according
to the GEM data, a larger number of younger entrepreneurs are entering the market,
taking into account the fact that South Africa has a relatively young population, with
43% below 20 years of age, and a further 19% between the ages of 20 and 29 (Maas
& Herrington 2006).
With regard to race distribution, the respondents were predominantly black
(88%, with 11% coloured and 1% Asian). Concerning education level, only 8%
of the respondents had a degree, and a further 60% claim to have a certificate or
diploma (discipline and quality unknown). Half of the respondents had no business
management qualifications or training, and a further 27% had very limited training
(workshop or short course) prior to participating in the SAB KickStart Programme.
Respondents had to indicate on an ordinal scale the level of managerial experience
they had at the time of starting their business (ranging from none to supervisor,
middle manager or senior manager). The largest percentage of the respondents (43%)
had no managerial experience at all, while 26% had been supervisors, 21% had been
middle managers, and only 10% had management experience at senior management
level.
An empirical analysis of a private company’s corporate social investment in SMME development
69
To determine the extent to which the respondents had had previous experience
in a similar business (for example, manufacturing or selling a similar product, or
delivering a similar service) when they started their business, the respondents could
select one of four options on a Likert scale. Almost a quarter (24%) of the respondents
had no prior experience, 28% had some experience, 26% had ‘quite a bit’, while only
22% had ‘a lot’ of experience in a similar business.
The respondents were split into two groups according to the status of the business:
57% of the respondents had start-up businesses, while 43% had existing businesses
when they commenced with the SAB KickStart Programme.
The respondents were split into two groups according to the type of SAB KickStart
support: 45% of the respondents had received funding (including mentoring) after
their training, while 55% had received only training.
Regarding ownership of the business and the changed nature of the business,
80% of the respondents still owned the business they had when they started with
the SAB KickStart Programme. This figure could be skewed by the fact that 51% of
the respondents were from start years 2005 and 2006. The nature of the businesses
had changed in the case of 77% of the respondents in that the product range and/or
service type had been diversified.
According to South Africa’s classification of enterprises in the National Small
Business Amendment Act (Act No. 29 of 2004), the SAB KickStart Programme
assists predominantly micro (5 employees), very small (20 employees) and small
enterprises (50 employees).
Hypothesis testing
In two separate analyses, an analysis of variance (ANOVA) was conducted on the
turnover and profit percentage figures of respondents to establish whether the type
of KickStart support rendered to respondents (‘trained only’ = 0; or ‘trained, funded
and mentored’ = 1) had a significant effect on turnover and profits. The General
Linear Model (GLM) approach to analysis of variance was used to this end. The
SAB KickStart data proved to be unbalanced with respect to the support categories,
and the GLM approach to analysis of variance makes provision for unbalanced data.
Although the effect of SAB KickStart support was of primary concern in these
analyses, it was argued that the effect of support on both turnover and profit could
be estimated more accurately if, true to the principles of analysis of variance, the
effect of other probable influential variables measured in the study were taken into
consideration as well. Data for the present study were collected over a period of
time, and the effect of years had to be considered as well. (Data for each of the 143
E. Swanepoel, J.W. Strydom & C. Nieuwenhuizen
70
respondents were collected over a maximum period of six years; thus the profit and
turnover datasets made provision for a maximum of 6*143 = 858 possible profit and
turnover data values for the 143 respondents.)
Initial analyses of variance of the profit and turnover datasets indicated that the
effect of years had to be accommodated differently for the two datasets. The effect
of years (in addition to KickStart support) proved to be significant in the case of the
profit percentage data and was accommodated in the final profit analysis (presented
in Table 2) by entering the years-effect into the ANOVA model along with the
KickStart support-effect. In this way, the variation in the data due to years and due
to support could be estimated separately, resulting in a more accurate estimate of the
effect of KickStart support. In contrast, initial analysis of the turnover data indicated
that the effect of years did not significantly affect turnover figures. This situation
was accommodated in the final analysis (presented in Table 4) by adding the effect of
years to the error term of the model. The analysis results are discussed in more detail
in the subsequent paragraphs.
Final analysis of variance on the profit percentage dataset
Once the general significance of the ANOVA model on the profit percentage data
had been verified (Table 2; a significance level of 1% is associated with the general
F-statistic of 3.04), the significance of the effect of KickStart support and years could
be investigated. From Table 2, it can be deduced that support-effect is significant
at the 5% level of significance (and years at the 1% level). The null hypotheses of
no significant effect of support (and years) could thus be rejected in favour of the
alternative hypotheses of significance. It can thus be deduced that, in addition to
years affecting profit figures, the type of support rendered affected profit figures
significantly. Table 2 illustrates these deductions.
A Bonferroni Multiple Comparisons of means test was conducted on the profit
mean values according to support categories. The test indicated how profit figures
were affected by the support-effect. Means that differ significantly from one another
are indicated in Table 3. The table indicates that the mean profit for respondents
who had received training, funding and mentoring was significantly greater than for
those who received only training. (A similar test could be conducted to demonstrate
years-effect but is not of relevance in the present context.)
An empirical analysis of a private company’s corporate social investment in SMME development
71
Table 2: Analysis of variance results on pro?t percentage data with e?ect of KickStart
support and years entered into the ANOVA model
Source
Degrees of
freedom
(df)
Sum of
squares
Mean sum of
squares
F value
Probability
(F-statistic >
F-critical)
Model 6 7965.1942 1327.5324 3.04 0.0067**
Support 1 1685.2120 1685.2120 3.85 0.0505*
Year 5 6588.1221 1317.6244 3.01 0.0113**
Error 312 12642.8999 437.2208
Corrected
total
318 144278.0940
Signi?cance level
* : 5% level of signi?cance
** : 1% level of signi?cance
*** : 0.1% level of signi?cance
319 of the possible 6*143 = 858 pro?t data
values over the six-year period were available/
reported for the pro?t dataset.
Table 3: Mean pro?t percentage values according to KickStart support levels, with
Bonferroni Multiple Comparisons of means test results indicated
Bonferroni grouping Mean N Support level
A 23.0860 163 1
B 18.9290 156 0
Means with di?erent letters (either a or b) next to them di?er signi?cantly.
Final analysis of variance on the turnover dataset
Once the general significance on the ANOVA model of the turnover data had been
verified (Table 4, a significance level of 0.1% is associated with the general F-statistic
of 10.78), the significance of the effect of the support-effect could be investigated.
From Table 4 it can be deduced that support-effect is significant at the 0.1% level of
significance. The null hypothesis of no significant effect of support could thus be
rejected in favour of the alternative hypothesis of significance. It can thus be deduced
that the type of support rendered affected turnover figures significantly. Table 4
reports on these deductions.
A Bonferroni Multiple Comparisons of means test was conducted on the turnover
mean values calculated according to support categories. The test gives an indication
of how turnover figures are affected by the support-effect. Means that differ
significantly from one another are shown in Table 5 and indicate that the mean
E. Swanepoel, J.W. Strydom & C. Nieuwenhuizen
72
turnover for respondents who had received training, funding and mentoring were
significantly greater than for those who received only training.
Table 4: Analysis of variance results on turnover data with the e?ect of KickStart
support entered into the ANOVA model (and e?ect of years added to the
error term)
Source
Degrees of
freedom (df)
Sum of
squares
Mean sum of
squares
F value
Probability
(F-statistic >
F-critical)
Model 1 8.1812E12 8.1812E12 10.78 0.0011***
Support 1 8.1812E12 8.1812E12 10.78 0.0011***
Error 353 2.6783E14 7.5873E11
Corrected
total
354 2.7601E14
Signi?cance level
* : 5% level of signi?cance
** : 1% level of signi?cance
*** : 0.1% level of signi?cance
355 of a possible 6*143 = 858 data values over
the six-year period were available/reported
for the pro?t dataset.
Table 5: Mean pro?t percentage values according to KickStart support levels, with
Bonferroni Multiple Comparisons of means test results indicated
Bonferroni grouping Mean N Support level
A 464 533 190 1
B 160 162 165 0
Means with di?erent letters (either a or b) next to them di?er signi?cantly.
Discussion
It was not possible to separate the effect of funding from the effect of mentoring, as
no group received only funding or only mentoring after training. To understand the
value of the funding and mentoring in context, the following contributing factors
should be appreciated:
• The role of funding. Although the amount of money received by a respondent was
not large, it did make a significant difference in the growth of these businesses.
The regional grants received by the respondents ranged from as little as R7 000 to
R100 000, while the prize money ranged from R10 000 to R180 000. A mitigating
factor is the fact that the size of the businesses of these respondents ranged from
An empirical analysis of a private company’s corporate social investment in SMME development
73
micro to very small or small. For a small business, the money was sufficient to
make a difference, and even more so when it was a start-up business.
• The availability of funding for micro and small enterprises. South African studies
by Statistics South Africa (StatsSA 2005) on micro enterprises and by Orford,
Wood, Fischer, Herrington and Segal (2003) on start-up businesses found that
the primary source of funds used, or expected to be used, by the owners of such
businesses is from own savings and income. A second source of financing is from
personal networks, which include family and friends, and lastly from institutions
or venture capitalists. Researching the financing of micro-entrepreneurs by South
African banks, Schoembee (2000) identified four possible reasons why these
banks are hesitant: high-risk of micro-entrepreneurs defaulting; high costs of
screening applicants without sufficient collateral; low returns on transacting with
these entrepreneurs; and socioeconomic, language and cultural barriers. The SAB
KickStart Programme incurs the costs of carefully screening the applicants, and
collateral is not required. SAB donates the funding, and this eliminates concerns
about defaulting or low returns. By providing mentoring, socioeconomic, language
and cultural barriers are overcome.
• The role of mentoring to supplement training. A comparison of the content of
the SAB KickStart training manual with internationally acceptable training
requirements for SME owners/entrepreneurs reveals that it covers most of the
standard topics. However, the content needs to expand on financial management
and some of the critical business management skills and people skills, as well as
to include sections on the management of rapid growth and development of the
new venture beyond start-up, the formation of strategic alliances, and legislation
critical to South African businesses. It is possible for mentors to fill these training
gaps, as and when required, as each mentor mentors about five participants.
• The role of mentoring to support unqualified and inexperienced participants. The
overall satisfaction of the respondents with their mentors was high, but this
should be mitigated by the fact that they had few or no business management
qualifications, managerial experience or previous experience in a similar business.
In such a scenario, any assistance would be of value. Based on research among
entrepreneurs by Bisk (2002: 264), the type of mentoring provided by the SAB
KickStart Programme can be classified as formal mentoring – SAB KickStart
selects the mentors and allocates them to participants (this is more an allocation
than a match). More than 80% of the respondents seemed to be satisfied with the
assistance received from mentors with regard to writing monthly reports, financial
management and business planning, while about 70% were satisfied with the
marketing assistance from mentors. Of the respondents with start-up businesses,
E. Swanepoel, J.W. Strydom & C. Nieuwenhuizen
74
about 44% were dissatisfied with the assistance received from mentors in the areas
of human resources management, operations management and networking.
• Adaptation of product/service line. A German study examined the impact of
knowledge types on the transition from unemployment to entrepreneurship.
Dencker, Gruber and Shah (2006: 48) found that “prior knowledge of industry/
product, and the adaptation of product line following market entry increases the
likelihood of success”. In the case of the participants, only 48% had some or a lot
of experience in a similar business, but 77% of the respondents diversified the
product range and/or service type after market entry. This may have contributed
to their success.
Practical implications
The value of the study lies therein that it contributes to the body of knowledge on
SMME development in a developing economy by offering guidelines for academia
with regard to the value contributed by multiple interventions in entrepreneurship
development programmes and the training needs of entrepreneurial SMMEs in
a developing economy. It provides practical insights for managers responsible for
corporate venture capital investment through corporate social investment in young
entrepreneurial firms into the structuring and management of entrepreneurship
development programmes.
The practical implications of the study lie in contributing to efforts to initiate
and support entrepreneurial action and the successful exploitation of promising
opportunities by identifying and describing appropriate interventions and structures
to help investors, corporate social investment departments, consultants, educators,
non-profit organisations, government departments and other professionals
understand the benefits – and limitations – of a youth entrepreneurship development
programme.
Limitations and future research
A limitation of the study is that the interventions, funding and mentoring could not be
separated, because only those SAB KickStart participants who received funding were
entitled to mentoring. The use of turnover or profit figures to measure success among
small businesses in a developing country poses problems due to the incompleteness
of the data. A few respondents were not able to provide turnover figures because of
the business being a start-up, while some others claimed not to possess such data.
Nevertheless, enough data were collected for the statistical analysis.
An empirical analysis of a private company’s corporate social investment in SMME development
75
Future research should focus on determining the effect of mentoring on business
growth. If mentoring could be made available to the SAB KickStart participants
who did not receive funding, it would be possible to test whether funding contributed
more than mentoring to the success of the businesses. If the mentoring period could
be extended to two years for a group of participants, it would be possible to measure
whether prolonged mentoring contributes more to business growth. Research
should also be conducted to determine the mentoring and networking needs of
entrepreneurial SMMEs in a developing economy.
A comparative study comparing the success of South African SAB KickStart
participants with those in Colombia where the SAB KickStart Programme was
launched in 2006 should be attempted. A major difference between these two
countries is that Colombia had the second highest TEA percentage in the 2006 GEM
survey, while South Africa ranked 30
th
(Maas & Herrington 2006).
Conclusion
With regard to training for new business creation, Storey (in Henry, Hill & Leitch
2004: 250) notes that despite the “claims of the administrators of intervention and
its effectiveness, the academic community has been slow to investigate this matter”.
This study has taken up this challenge and investigated the effectiveness of the
interventions used by a programme, the SAB KickStart Programme, which has as its
objective the development of young entrepreneurs to start or grow their businesses in
South Africa, a developing economy.
The findings of the research suggest that in the complex process of conceiving,
launching and running new ventures, entrepreneurial SMMEs in a developing
economy not only need training in entrepreneurship and business management, but
also need funding and mentoring, preferably over an extended period, to support
them in their efforts to convert their dreams, ideas and visions into functioning,
profitable companies that create jobs and to boost the growth potential of the venture
and its sustainability.
References
Bisk, L. 2002. ‘Formal entrepreneurial mentoring: the efficiency of third party managed
programs’, Career Development International, 7(5): 262–270.
Botha, M., Nieman, G. & Van Vuuren, J. 2007. ‘Measuring the effectiveness of the
Women Entrepreneurship Programme on potential, start-up and established women
entrepreneurs in South Africa’, South African Journal of Economic and Management
Sciences 10(2): 163–183.
E. Swanepoel, J.W. Strydom & C. Nieuwenhuizen
76
Carree, M.A. & Thurik, A.R. 2003. ‘The impact of entrepreneurship on economic growth’,
In Acs, Z.J. & Audretsch, D.B. (eds), Handbook of Entrepreneurship Research: an
Interdisciplinary Survey and Introduction. New York: Springer Science + Business
Media.
De Faoite, D., Henry, C., Johnston, K. & Van der Sijde, P. 2004. ‘Entrepreneurs’ attitudes to
training and support initiatives: evidence from Ireland and the Netherlands’, Journal of
Small Business and Enterprise Development 11(4): 440–448.
Dencker, J., Gruber, M. & Shah, S.K. 2006. ‘Knowledge-related success factors on the path
from unemployment to entrepreneurship’, Conference proceedings of the 26
th
Babson
College Entrepreneurship Research Conference, Bloomington, Indiana (USA), 8–10
June 2006.
De Wet, H. (ed.). 2007. The CSI Handbook, 10
th
edition. Cape Town: Trialogue.
dti (Department of Trade and Industry). 2008. Annual Review of Small Business in South
Africa: 2005–2007. Pretoria: Enterprise Development Unit, dti.
dti (Department of Trade and Industry). 2007. Integrated Strategy on the Promotion of
Entrepreneurship and Small Enterprises. Pretoria: Enterprise Development Unit, dti.
[Online] Available at:http://www.dti.gov.za. Accessed: 12 February 2007.
Fisher, G. 2004. An exploration of innovative teaching methods in the area of entrepreneurship
on MBA programmes. MBA research report, Gordon Institute of Business Science,
University of Pretoria.
Henry, C., Hill, F.M. & Leitch, C.M. 2004. ‘The effectiveness of training for new business
creation: a longitudinal study’, International Small Business Journal 22(3): 249–271.
Herrington, M., Kew, J. & Kew, P. 2008. Global Entrepreneurship Monitor 2008. Cape Town:
Centre for Innovation and Entrepreneurship, Graduate School of Business, University
of Cape Town.
High, J. 2004. ‘The roles of entrepreneurship in economic growth: toward a theory of
total factor productivity’, in De Groot, H.L.F., Nijkamp, P. & Stough, R.R. (eds),
Entrepreneurship and Regional Economic Development: a Spatial Development.
Northampton, MA: Edward Elgar.
Hisrich, R.D. & Peters, M.P. 2002. Entrepreneurship, 5
th
edition. Boston, MA: McGraw-Hill/
Irwin.
Hussey, J. & Hussey, R. 1997. Business Research: a Practical Guide for Undergraduate and
Postgraduate Students. Hampshire: Palgrave.
Keller, G. & Warrack, B. 2000. Statistics for Management and Economics, 5
th
edition. Pacific
Grove, CA: Duxbury Thomson Learning.
Kennedy, J. & Drennan, J. 2001. ‘A review of the impact of education and prior experience on
new venture performance,’ Entrepreneurship and Innovation, October: 160–172.
Kent, T., Dennis, C. & Tanton, S. 2003. ‘An evaluation of mentoring for SME retailers’,
International Journal of Retail and Distribution Management, 31(8): 440–448.
Kuratko, D.F & Hodgetts, R.M. 2004. Entrepreneurship: Theory, Process, Practice, 6
th
edition.
Mason, OH: Thomson South-Western.
An empirical analysis of a private company’s corporate social investment in SMME development
77
Ladzani, W.M & Van Vuuren, J.J. 2002. ‘Entrepreneurship training for emerging SMEs in
South Africa’, Journal of Small Business Management, 40(2): 154–161.
Landström, H. 2005. Pioneers in Entrepreneurship and Small Business Research. New York:
Springer Science + Business Media.
Leedy, P.D. & Ormrod, J.E. 2005. Practical Research: Planning and Design, 8
th
edition. Upper
Saddle River, NJ: Pearson.
Maas, G. & Herrington, M. 2006. Global Entrepreneurship Monitor: South African Report.
Cape Town: Centre for Innovation and Entrepreneurship, Graduate School of Business,
University of Cape Town.
Maula, M., Autio, E. & Murray, G. 2005. ‘Corporate venture capitalists and independent
venture capitalists: What do they know, who do they know, and should entrepreneurs
care?’, In Elfring, T. (ed.) Corporate Entrepreneurship and Venturing. New York: Springer.
Orford, J., Wood, E., Fischer, C., Herrington, M. & Segal, N. 2003. Global Entrepreneurship
Monitor: South African Executive Report 2003. Cape Town: Graduate School of Business,
Centre for Innovation and Entrepreneurship, University of Cape Town.
Orford, J., Herrington, M. & Wood, E. (eds). 2004. Global Entrepreneurship Monitor: South
African Report. Cape Town: Centre for Innovation and Entrepreneurship, Graduate
School of Business, University of Cape Town.
SAB Ltd. 2006. Stepping up to the Future: Sustainability Report 2006. Johannesburg: CSR
Department, Corporate Affairs, SAB.
SABMiller plc. 2005. Annual Report ’05. London: SABMiller.
SABMiller plc. 2008. Annual Report: SABMiller plc Annual Report 2008. London: SABMiller.
Schoembee, A. 2000. ‘Getting South African banks to serve micro-entrepreneurs: an
analysis of policy options’, Development South Africa,17(5): 751–767.
StatsSA (Statistics South Africa). 2005. Survey of Employers and the Self-employed. [Online]
Available at:http://www.statssa.gov.za/publications/P0276/P02762005. Accessed: 7
August 2007.
Stats SA (Statistics South Africa). 2007. Key Findings: Mid-year Population Estimates, 2007.
Statistical release P0302. [Online] Available at: www.statssa.gov.za. Accessed: 10
December 2007.
Stats SA (Statistics South Africa). 2009. Quarterly Labour Force Survey (QLFS), 4
th
Quarter
2008. Statistical release P0211. [Online] Available at:http://www.statssa.gov.za.
Accessed: 30 March 2009.
Sullivan, R. 2000. ‘Entrepreneurial learning and mentoring’, International Journal of
Entrepreneurial Behaviour and Research, 6(3): 160–175.
Timmons, J.A. & Spinelli, S. 2004. New Venture Creation: Entrepreneurship for the 21
st
Century, 6
th
edition. Boston, MA: Irwin McGraw-Hill.
Van Stel, A., Carree, M. & Thurik, R. 2004. The Effect of Entrepreneurship on National
Economic Growth: an Analysis using the GEM Database. [Online] Available at: http://
www.babson.edu/entrep/fer/FER_2004/web-content/section%20XIX//XIX. Accessed:
4 April 2006.
E. Swanepoel, J.W. Strydom & C. Nieuwenhuizen
78
Von Broembson, M., Wood, E. & Herrington, M. 2005. Global Entrepreneurship Monitor:
South African Report. Cape Town: UCT Graduate School of Business, Centre for
Innovation and Entrepreneurship.
Watson, G.E.H. 2004. A situational analysis of entrepreneurship mentors in South Africa.
MCom dissertation, University of South Africa, Pretoria.
Wickham, P.A. 2004. Strategic Entrepreneurship, 3
rd
edition. Harlow: Financial Times
Prentice-Hall.
World Bank. 2006. Doing Business in 2006: Creating Jobs. Washington: World Bank.
doc_939361703.pdf
South Africa has entered the era of industry transformation charters that have to be harmonised with the Department of Trade and Industry's broad-based black economic empowerment (B-BBEE) scorecard and codes of good practice. In these charters, targets are set with regard to ownership, management, skills development, BEE procurement, enterprise development, facilitation of finance for BEE and corporate social investment (CSI).
58 Southern African Business Review Volume 14 Number 1 2010
An empirical analysis of a private company’s
corporate social investment in SMME development
in South Africa
E. Swanepoel, J.W. Strydom & C. Nieuwenhuizen
A B S T R A C T
South Africa has a very high unemployment rate, low economic
growth and dismal Total (early-stage) Entrepreneurial Activity (TEA)
preformance. Both government and private businesses are attempting
to address this problem. A private company, the South African
Breweries (SAB), as part of their corporate social investment, runs
the SAB KickStart Programme to establish and grow entrepreneurial
small businesses among young South Africans. The programme
applies four interventions: General Enterprising Tendency test; two-
week live-in business management training; funding and mentoring;
and a national competition for prize money. Taking into consideration
the cost of funding and operating the programme, its e?ectiveness
required investigation. The population for the study comprised all
the participants of the SAB KickStart Programme, from 2001 to
2006. From an analysis of variance (ANOVA) applied to the turnover
and percentage pro?t ?gures of respondents, it was deduced that
funding and mentoring, after training, add value to the programme.
The programme contributes to enterprise sustainability ,as 80 per
cent of the respondents were still operating their initial businesses,
while a further six percent have started another business – hence, a
‘failure’ rate of only 14 per cent. In conclusion, it can be said that the
SAB KickStart Programme adds value, advances entrepreneurship,
and can be replicated by other large institutions in South Africa.
Key words: entrepreneurship, SME development, SMME development, corporate social
investment, training, funding, mentoring, SAB KickStart Programme, youth
development
Dr E. Swanepoel is a Senior Lecturer of Entrepreneurship in the Department of Business Manage-
ment, School for Manage ment Sciences, University of South Africa. Prof. J.W. Strydom is a Profes sor
of Business Management in the same department, and Prof. C. Nieuwenhuizen is a Profes sor in the Depart-
ment of Business Management, University of Johannesburg.
E-mail: [email protected]
An empirical analysis of a private company’s corporate social investment in SMME development
59
Introduction
South Africa has entered the era of industry transformation charters that have to
be harmonised with the Department of Trade and Industry’s broad-based black
economic empowerment (B-BBEE) scorecard and codes of good practice. In these
charters, targets are set with regard to ownership, management, skills development,
BEE procurement, enterprise development, facilitation of finance for BEE and
corporate social investment (CSI). It is possible for companies to spend some of the
CSI on entrepreneurial and small and medium enterprise (SME) development. The
purpose of this study is to analyse the effectiveness of a highly regarded CSI SME
development programme and to use the findings as a benchmark for subsequent
comparative studies of similar CSI programmes in South Africa. In 2002, after
completing a study on SME training in the Northern Province (which has since
been renamed Limpopo Province), Ladzani and Van Vuuren (2002) concluded that
SME service providers should benchmark their services against similar successful
institutions.
Despite good economic growth in the past, a major concern for South African
economists is the lack of job creation, which results in high unemployment, for
example, 21.9% in March 2009 (StatsSA 2009). In South Africa, the sector including
micro, very small and small businesses comprised 93% of all enterprises (in March
2007), contributed 27–34% of total gross domestic product (GDP) in 2006 (dti 2008)
and accounted for 38% of employment (Rogerson, in dti 2008). From these statistics,
it is evident that the sustainability and growth of small business are vital topics for
research.
The low level of entrepreneurial activity in South Africa is of concern, because
entrepreneurs are involved in the establishment and growth of new and existing
enterprises of varying sizes, including small businesses. The cross-national data of the
Global Entrepreneurship Monitor (GEM) indicate that South Africa’s Total (early-
stage) Entrepreneurial Activity (TEA) performance, in terms of relative position,
has consistently been below the median since 2001 (Herrington, Kew & Kew 2008).
The authors found that South Africa’s nascent entrepreneurship rate (which relates
to setting up a business) of 5.7% is below the GEM average of 6.2% as well as the
average of 6.7% for efficiency-driven economies. In terms of new firm activity (which
relates to firms up to 3.5 years old), South Africa ranked 38
th
out of the 43 countries
with a new business prevalence rate of only 2.1% (which was below the 4.6% average
for all GEM countries and 4.9% average for all efficiency-driven countries). In terms
of established business activity (which relates to firms older than 3.5 years), South
Africa ranked 41
st
out of the 43 countries, with an established business rate of 2.3%
E. Swanepoel, J.W. Strydom & C. Nieuwenhuizen
60
(which was below the 7.7% average for all GEM countries and 6.9% for all efficiency-
driven countries).
The GEM results seem to indicate that not only does the need exist in South
Africa to increase the number of start-up businesses, but also to grow businesses
beyond the start-up and new firm stages to the established stage in order to increase
their contribution to job creation and economic growth. To remedy this situation, the
GEM 2004 report (Orford, Herrington & Wood 2004) recommends, among other
things, rethinking support to small enterprises (concentrating on facilitating private
sector service provision) and improving the financial and general management
capacity of small enterprises to increase start-up survival rates through targeted
training and experienced mentoring.
Objectives of the study
The objective was to investigate an existing programme by evaluating the
effectiveness of the interventions used by the SAB KickStart Programme to establish
and grow entrepreneurial SMMEs. Botha, Nieman and Van Vuuren (2007) pointed
out that in the area of entrepreneurship, an aspect that is not researched much is
the effectiveness of training interventions, especially considering the cost of such
programmes to sponsors and participants alike. Their study proved that their
Women Entrepreneurship Programme was effective in training potential, start-up
and established women entrepreneurs in South Africa.
To increase the number of start-up businesses and grow businesses beyond the
start-up and new firm stages to the established stage, the GEM 2004 report (Orford
et al. 2004) recommends, among other things, rethinking support to small enterprises
(concentrating on facilitating private sector service provision) and improving the
financial and general management capacity of small enterprises to increase start-
up survival rates through targeted training and experienced mentoring. The South
African Breweries (SAB) has for many years complied with both these suggestions
through several of its programmes as part of corporate social investment (CSI) and
black economic empowerment (BEE) programmes such as the barley farmer scheme,
owner truck driver scheme, distribution operator scheme, customised delivery service
scheme, HoneyBEE franchised distribution centres, retail normalisation of taverners
and their flagship programme, and the SAB KickStart Youth Entrepreneurship
Programme (SAB Ltd 2006).
SAB Ltd is the largest subsidiary of SABMiller plc, the second-biggest brewer
by volume in the world, present in over 40 countries in Europe, North and Latin
America, Asia and Africa (SABMiller 2008). It is the biggest contributor to the South
An empirical analysis of a private company’s corporate social investment in SMME development
61
African fiscus – contributing R6 billion in tax and excise duty in 2004 (SABMiller
2005). Another reason for evaluating the existing SAB KickStart Programme stems
from the fact that SAB intends to emulate the SAB KickStart Programme in other
countries in Africa, South America and the rest of the world.
SAB Kickstart Youth Entrepreneurship Programme
There were two fundamental reasons for selecting the SAB Ltd’s KickStart
Programme. Firstly, the SAB KickStart Programme is recognised by the South
African government in its Integrated Strategy on the Promotion of Entrepreneurship
and Small Enterprises (dti 2007) as a benchmark programme for fostering business
start-ups. Secondly, SAB is highly regarded by its fellow corporations as the strongest
contributor to job creation and entrepreneurial development in a 2007 survey (De
Wet 2007). Since the advent of industry transformation charters, companies may look
to emulating the SAB KickStart Programme, because SAB has managed to score
points by leveraging BEE procurement and CSI funds for optimal developmental
impact. SAB, as part of its CSI initiatives, has invested more than R36 million in
entrepreneurial BEE SMMEs through the SAB KickStart Programme.
Nature of the SAB KickStart Programme
Since its inception in May 1995, the SAB KickStart Programme has helped
launch over 3 000 businesses, many of which have grown into multi-million Rand
concerns. In 2001, the SAB KickStart Programme switched from a numbers-
driven approach, which focused on poverty alleviation, to a quality-driven and
carefully monitored intervention at the SMME level with the aim of inculcating a
culture of entrepreneurship and creating sustainable enterprises among previously
disadvantaged young adults (blacks, coloureds and Asians – official terminology
used in South Africa to describe different races) between the ages of 18 and 35.
Fewer participants are selected for training, while greater emphasis is placed on post-
training mentorship and assistance. The SAB KickStart Programme takes about
15–18 months for a cycle to be completed.
In April every year, the SAB KickStart Programme launches an awareness
campaign, requesting interested nascent and existing entrepreneurs between the
ages of 18 and 35 years to apply. Judged by the information on the application
form, the business plans and financial statements, the thousands of applicants are
whittled down to 40 candidates per SAB region (five regions), who complete the
General Enterprising Tendency (GET) test. The applicants with acceptable scores
E. Swanepoel, J.W. Strydom & C. Nieuwenhuizen
62
appear before a regional panel, which selects 20 entrepreneurs per region (100 in
total per year) to attend a two-week live-in training session that includes training in
entrepreneurship and business skills, such as production management, marketing,
financial management, human resources management and the business plan.
Training is presented by an independent trainer, and a training manual is handed
out to the participants. On completion of the course, the participants are given one
month in which to prepare a business plan on a preferred business idea. In each
region, they present their business plans to a panel of adjudicators. Based on the
results, each region allocates discretionary grants from its R300 000 budget to ‘kick-
start’ five to eight of the most promising potential businesses or existing businesses.
The grants could range from R50 000 to R120 000 per business. The grant includes
eight months of mentoring. SAB also provides direct support through networking to
stimulate business development and helps the small businesses gain public relations
exposure. About six months later, each region selects its three top performers. The
regional finalists present their businesses to a national adjudicating panel, which
chooses the national prize winners. The top winners take a share of R700 000 in
prize money, which includes business mentorship for a further six months. At all
stages, adjudication is based on business plans, performance data and presentations
by the participants.
Four interventions are used to enhance the effectiveness of the programme, namely
a selection process (involving the General Enterprising Tendency test, business plans
and presentations to adjudicating panels), two-week in-house training, funding and
mentoring, and prize money. Owing to the fact that the continued involvement with
the participants through the provision of funding after completion of the training
(27 participants received R2.7 million in grants and prizes in 2006) and mentoring
(paid for by SAB) is costly and time consuming, as it involves a substantial amount
of organisation, administration and monitoring by both the SAB head office and
regional offices, the following research question surfaced: Does the performance of
those participants who received training, funding and mentoring exceed those who
received only training? This question translates into the following hypothesis:
Null hypothesis (H
0
): No difference exists between the performance of businesses of
SAB KickStart participants who received training, grants and mentoring and those
businesses of SAB KickStart participants who received only training.
Alternate hypothesis (H
1
): The businesses of SAB KickStart participants who
received training, grants and mentoring perform better than the businesses of SAB
KickStart participants who received only training.
An empirical analysis of a private company’s corporate social investment in SMME development
63
Testing this hypothesis is of particular relevance in the economic climate of
recession, as private enterprises could easily consider cutting back on their corporate
social investment and in particular on entrepreneurial development.
Theoretical background
Entrepreneurial ventures versus small businesses
Entrepreneurship is an evolving concept. Recognising this fact, Kuratko and
Hodgetts (2004: 30) developed an integrated definition that acknowledges the critical
factors needed for this phenomenon, including the cognitive scripts of arrangements,
willingness and ability:
Entrepreneurship is a dynamic process of vision, change and creation. It requires an applica-
tion of energy and passion towards the creation and implementation of new ideas and creative
solutions. Essential ingredients include the willingness to take calculated risks – in terms of
time, equity, or career; the ability to formulate an effective venture team; the creative skill to
marshal needed resources; the fundamental skill of building a solid business plan; and, finally,
the vision to recognize opportunity where others see chaos, contradiction, and confusion.
Owing to the comprehensive nature of this definition, it is accepted for the purposes
of this study. The difference between entrepreneurial ventures and small businesses
is explained by Wickham (2004), who claimed that it is the combination and depth
of three characteristics, namely innovation, potential for growth and strategic
objectives, that add up to distinguish the key characteristic of the entrepreneurial
venture, namely that it is a business that makes significant changes to the world.
The entrepreneur as prime mover of economic development
In 1911 Joseph Schumpeter published his work, Theory of Economic Development, in
which he identified the entrepreneur as the prime mover of economic development
through the introduction of new combinations, such as new products, new techniques,
new forms of organisation, new markets and new sources of materials (Schumpeter
1934, 1939, 1942, in High 2004). Several studies on the impact of entrepreneurship
on economic growth (Brock & Evans 1989 and Carree & Thurik 2000, in Fisher
2004; Carree & Thurik 2003) confirmed that entrepreneurship contributes to
economic growth. A “causal relationship between the GDP per capita of a country
and the extent and nature of its entrepreneurial activity” was established in 2004 by
the Global Entrepreneurship Monitor (GEM) international research team and the
findings confirmed by the GEM 2005 Executive Report (Von Broembson, Wood
E. Swanepoel, J.W. Strydom & C. Nieuwenhuizen
64
& Herrington 2005: 15). Research by Van Stel, Carree and Thurik (2004), using
the Total Entrepreneurial Activity (TEA) variable from the GEM and the Growth
Competitiveness Index, found that entrepreneurial activity affects economic growth.
In a World Bank survey, Voices of the Poor, of 60 000 poor people interviewed in
more than 50 countries, the majority claimed that they had escaped from poverty
by starting their own business (World Bank 2006: 1). The World Bank advises that
“jobs in the formal economy are a priority for countries in Africa – which have the
most obstacles to doing business and are reforming more slowly than anywhere else”.
The relationship between training and entrepreneurial perfor-
mance
Wickham (2004) developed a model illustrating that successful entrepreneurial
performance is the outcome of the integration of industry knowledge, general
management skills, personal motivation and people skills. The general management
skills include strategy, planning, marketing, financial, project management and time
management skills, while the people skills include leadership, motivation, delegation,
communication and negotiation skills. Entrepreneurship and SME training facilitate
the acquisition of these skills. Researchers such as Kennedy and Drennan (2000)
found that the performance of new ventures improves for those entrepreneurs who
have higher levels of education, previous entrepreneurial experience and experience
in similar businesses. According to Timmons and Spinelli (2004: 64), “successful
entrepreneurs possess not only creative and innovative flair, but also solid general
management skills, business know-how, and sufficient contacts”.
Factors that may inhibit potential entrepreneurs from pursuing entrepreneurship
include a lack of training for entrepreneurs, the risks posed by the business
environment, a lack of suitable human resources and legal restrictions on business
activity (Wickham 2004). However, to eliminate these inhibitors, entrepreneurs
can access a range of support initiatives, such as funding, mentoring, networking,
incubation space, start-up training, development training, third-level facilities
(institutions), and third-level expertise (De Faoite, Henry, Johnston & Van der Sijde
2004).
Funding and entrepreneurial performance
One of the inhibitors to becoming an entrepreneur is an inability to secure start-up
capital and the high cost of start-up capital (Wickham 2004). Audretsch (interviewed
by Landström 2005: 230) suggested that “having financial support – not necessarily
An empirical analysis of a private company’s corporate social investment in SMME development
65
venture capital, because most small businesses don’t use venture capital – but to
have the kind of institutions that provide loans to small business seems to be very
important”.
Value-added by the suppliers of capital
‘Classic’ venture capitalists providing seed, start-up and early growth finance often
deal with talented but inexperienced teams (Bygrave & Timmons 1992 and Reynolds
et al. 2002, in Maula, Autio & Murray 2005). Being able to impart critical knowledge
and experience in addition to finance may be instrumental in the survival and success
of the portfolio firm (Gorman & Sahlman 1989; Hellman & Puri 2002; MacMillan
et al. 1989; Sapienza 1992; Sapienza et al. 1994; Sapienza et al. 1996, in Maula et
al. 2005). MacMillan et al. (1989, in Maula et al. 2005: 104) reported that activities
that attracted the highest degree of venture capitalist involvement are: “serving as a
sounding board to the entrepreneur team, helping the firm obtain alternative further
sources of equity financing, interfacing with the investor group, monitoring financial
performance, monitoring operating performance, and helping their portfolio firms
attract alternative sources of debt financing”. Gorman and Sahlman (1989, in
Maula et al. 2005: 104) found similar results: “help with the obtaining of additional
financing, strategic planning, management recruitment, operational planning,
introduction to potential customers and suppliers, and resolving compensation
issues”. In their research comparing value added by independent venture capitalists
with corporate venture capitalists, Maula et al. (2005) found that independent
venture capitalists seem to be better at satisfying the needs of entrepreneurs when
assisting with arranging finance, recruiting key employees, advising on competition
and developing the organisational resources of the growing enterprise. Corporate
venture capitalists seem to be more effective in attracting new domestic and foreign
customers and helping start-ups develop their technologies.
From the discussion, it would seem that in order to ensure success, the provider of
finance should be involved in a range of additional activities that border on mentoring.
Mentoring and entrepreneurial performance
Collin’s (1979, in Sullivan 2000: 169) defines mentoring as “a protected relationship
in which learning and experimentation can occur, potential skills can be developed,
and in which results can be measured in terms of competencies gained, rather than
curricular territory covered”. It implies a long-term relationship between the mentor
and the protégé(e), allowing time for experimentation and reflection, as well as for
E. Swanepoel, J.W. Strydom & C. Nieuwenhuizen
66
collaboration and advice (Graham & O’Neil 1997, in Bisk 2002). Research that used
previous or existing entrepreneurs to support and advise new start-up entrepreneurs
has proved that mentors provide added-value interventions that are likely to bring
long-term benefits to entrepreneurs (Sullivan 2000). Hisrich and Peters (2002: 74) are
of the opinion that “a mentor–protégé relationship is an excellent avenue of securing
needed professional advice, as well as providing an additional source of moral
support”. Research that established the importance of the trainer-motivator, whose
qualifications and experience were found to be vital to the success of the Indian
Entrepreneurial Development Programme (Awasthi & Sebastian 1996, in Watson
2004), corroborates this statement. In a British study, Kent, Dennis and Tanton
(2003) found that a one-year mentoring programme enabled SME retailers to reach
their objectives – maximising sales, adapting to change and developing new ideas.
Methodology
This case study research design incorporated positivistic and phenomenological
research paradigms. Both the qualitative and quantitative approaches to research
were utilised (Leedy & Ormrod 2005: 94–95). The study started off as exploratory
research followed by descriptive research, progressing to analytical/explanatory and
predictive research (Hussey & Hussey 1997: 13).
The population for this study consisted of all the entrepreneurs selected to
participate in the SAB KickStart Programme from 2001 to 2006. (In order to include
the 2006 intake, who completed their programme in 2007, the survey was undertaken
at the end of 2007.) The database provided by SAB consisted of 502 names. Owing
to the limited size of the population, a sample was not drawn; instead, a serious
and prolonged attempt was made to contact every person in the population of SAB
KickStart participants, and 442 were traced. A total of 143 questionnaires was
eventually returned, which represented 28.5% of the population of 502.
Since a sample from the population was not drawn, the question whether the
sample is representative of the population is not relevant. The possibility of respondent
bias, however, was a concern, and the question arose whether only a certain type
of person had responded to the questionnaire. The distribution of the respondents
was compared with the only available attributes of the SAB KickStart population
distribution, and it was found that by year, by SAB region and by gender, the two
distributions are similar. A sufficient percentage of grant winners were among the
respondents (45%) in comparison to the SAB KickStart population (37%).
The participants in the SAB KickStart Programme are spread throughout all
nine provinces in South Africa, mostly in the major cities but also in rural areas. A
An empirical analysis of a private company’s corporate social investment in SMME development
67
paper-and-pencil questionnaire was e-mailed, faxed or posted to the participants.
The questionnaire was only available in English, a fairly commonly used language
in South Africa, which has 11 official languages. Participants were assured of
anonymity and confidentiality. Demographic information about the respondents,
performance information about their businesses and experiences, and perceptions
regarding the four interventions that constitute the SAB KickStart Programme were
obtained. However, in this article only two of these interventions will be addressed,
namely ‘training’ and ‘funding and mentoring’. Some of the questions required the
respondent to select an appropriate option from a range of options on a four-point
Likert scale, which results in the Likert scaling being a bipolar scaling method,
measuring either a positive or negative response to a statement. The chi-squared test
is a common statistical procedure used after this transformation (Keller & Warrack
2000). Both descriptive and inferential statistics are utilised in the study of the
effectiveness of the SAB KickStart Programme.
With regard to the variable of ‘receiving training, funding and mentoring’, a
static group comparison was used to show that “change occurs following, but only
following, a particular treatment” (Leedy & Ormrod 2005: 236). In the study, all
respondents had received training, but only a selected number had received funding
and mentoring. The pre-experimental design of this variable is illustrated in Table 1.
Table 1: Pre-experimental design: static group comparison
Group Time ?
SAB KickStart
participants
Baseline treatment
(training)
Funding (regional grant)
and mentoring
Additional funding (national
prize) and mentoring
Group 1 Trained T
xa
Group 2 Trained T
xa
Funded and mentored T
xb
Group 3 Trained T
xa
Funded and mentored T
xb
Funded and mentored T
xc
Although the original intention was to compare the three groups, this was not
possible because the number of respondents in group 3 was too small. Groups 2 and 3
were collapsed into a single group of respondents who had been trained, funded and
mentored. A limitation of the pre-experimental design is that it fails to determine the
pre-treatment equivalence of the groups.
In the study, all the respondents had received training, but only the participants
who received funding also received mentoring by design. With 79 respondents who
received only training and 64 respondents who, in addition to training, received
E. Swanepoel, J.W. Strydom & C. Nieuwenhuizen
68
funding and mentoring, it was possible to test for statistically significant differences
between these two groups, using the General Linear Model approach to analysis of
variance. The two independent variables are ‘trained only’, compared with ‘trained,
funded and mentored’, with performance being the dependent variable.
Results
Demographic pro?le of SAB KickStart participants
The contribution of the SAB KickStart Programme is better appreciated if one looks
at the demographics of the participants. Demographically, the characteristics of the
respondents reflected the SAB KickStart population with regard to the following
attributes. Respondents were from each of the six start years (2001 to 2006), with 51%
from the two latter years owing to the greater accuracy of the contact details. Each of
the five SAB regions was represented. The gender distribution was exactly the same
as the population distribution – 70% male and 30% female. It should be noted that
the gender distribution of the South African population is about 49% male and 51%
female (Stats SA 2007).
The majority of the respondents (75%) were between the ages of 26 and 35 years,
while 15% were between 18 and 25 years. This is in line with the programme policy of
assisting youth between the ages of 18 to 35. It also addresses the fact that, according
to the GEM data, a larger number of younger entrepreneurs are entering the market,
taking into account the fact that South Africa has a relatively young population, with
43% below 20 years of age, and a further 19% between the ages of 20 and 29 (Maas
& Herrington 2006).
With regard to race distribution, the respondents were predominantly black
(88%, with 11% coloured and 1% Asian). Concerning education level, only 8%
of the respondents had a degree, and a further 60% claim to have a certificate or
diploma (discipline and quality unknown). Half of the respondents had no business
management qualifications or training, and a further 27% had very limited training
(workshop or short course) prior to participating in the SAB KickStart Programme.
Respondents had to indicate on an ordinal scale the level of managerial experience
they had at the time of starting their business (ranging from none to supervisor,
middle manager or senior manager). The largest percentage of the respondents (43%)
had no managerial experience at all, while 26% had been supervisors, 21% had been
middle managers, and only 10% had management experience at senior management
level.
An empirical analysis of a private company’s corporate social investment in SMME development
69
To determine the extent to which the respondents had had previous experience
in a similar business (for example, manufacturing or selling a similar product, or
delivering a similar service) when they started their business, the respondents could
select one of four options on a Likert scale. Almost a quarter (24%) of the respondents
had no prior experience, 28% had some experience, 26% had ‘quite a bit’, while only
22% had ‘a lot’ of experience in a similar business.
The respondents were split into two groups according to the status of the business:
57% of the respondents had start-up businesses, while 43% had existing businesses
when they commenced with the SAB KickStart Programme.
The respondents were split into two groups according to the type of SAB KickStart
support: 45% of the respondents had received funding (including mentoring) after
their training, while 55% had received only training.
Regarding ownership of the business and the changed nature of the business,
80% of the respondents still owned the business they had when they started with
the SAB KickStart Programme. This figure could be skewed by the fact that 51% of
the respondents were from start years 2005 and 2006. The nature of the businesses
had changed in the case of 77% of the respondents in that the product range and/or
service type had been diversified.
According to South Africa’s classification of enterprises in the National Small
Business Amendment Act (Act No. 29 of 2004), the SAB KickStart Programme
assists predominantly micro (5 employees), very small (20 employees) and small
enterprises (50 employees).
Hypothesis testing
In two separate analyses, an analysis of variance (ANOVA) was conducted on the
turnover and profit percentage figures of respondents to establish whether the type
of KickStart support rendered to respondents (‘trained only’ = 0; or ‘trained, funded
and mentored’ = 1) had a significant effect on turnover and profits. The General
Linear Model (GLM) approach to analysis of variance was used to this end. The
SAB KickStart data proved to be unbalanced with respect to the support categories,
and the GLM approach to analysis of variance makes provision for unbalanced data.
Although the effect of SAB KickStart support was of primary concern in these
analyses, it was argued that the effect of support on both turnover and profit could
be estimated more accurately if, true to the principles of analysis of variance, the
effect of other probable influential variables measured in the study were taken into
consideration as well. Data for the present study were collected over a period of
time, and the effect of years had to be considered as well. (Data for each of the 143
E. Swanepoel, J.W. Strydom & C. Nieuwenhuizen
70
respondents were collected over a maximum period of six years; thus the profit and
turnover datasets made provision for a maximum of 6*143 = 858 possible profit and
turnover data values for the 143 respondents.)
Initial analyses of variance of the profit and turnover datasets indicated that the
effect of years had to be accommodated differently for the two datasets. The effect
of years (in addition to KickStart support) proved to be significant in the case of the
profit percentage data and was accommodated in the final profit analysis (presented
in Table 2) by entering the years-effect into the ANOVA model along with the
KickStart support-effect. In this way, the variation in the data due to years and due
to support could be estimated separately, resulting in a more accurate estimate of the
effect of KickStart support. In contrast, initial analysis of the turnover data indicated
that the effect of years did not significantly affect turnover figures. This situation
was accommodated in the final analysis (presented in Table 4) by adding the effect of
years to the error term of the model. The analysis results are discussed in more detail
in the subsequent paragraphs.
Final analysis of variance on the profit percentage dataset
Once the general significance of the ANOVA model on the profit percentage data
had been verified (Table 2; a significance level of 1% is associated with the general
F-statistic of 3.04), the significance of the effect of KickStart support and years could
be investigated. From Table 2, it can be deduced that support-effect is significant
at the 5% level of significance (and years at the 1% level). The null hypotheses of
no significant effect of support (and years) could thus be rejected in favour of the
alternative hypotheses of significance. It can thus be deduced that, in addition to
years affecting profit figures, the type of support rendered affected profit figures
significantly. Table 2 illustrates these deductions.
A Bonferroni Multiple Comparisons of means test was conducted on the profit
mean values according to support categories. The test indicated how profit figures
were affected by the support-effect. Means that differ significantly from one another
are indicated in Table 3. The table indicates that the mean profit for respondents
who had received training, funding and mentoring was significantly greater than for
those who received only training. (A similar test could be conducted to demonstrate
years-effect but is not of relevance in the present context.)
An empirical analysis of a private company’s corporate social investment in SMME development
71
Table 2: Analysis of variance results on pro?t percentage data with e?ect of KickStart
support and years entered into the ANOVA model
Source
Degrees of
freedom
(df)
Sum of
squares
Mean sum of
squares
F value
Probability
(F-statistic >
F-critical)
Model 6 7965.1942 1327.5324 3.04 0.0067**
Support 1 1685.2120 1685.2120 3.85 0.0505*
Year 5 6588.1221 1317.6244 3.01 0.0113**
Error 312 12642.8999 437.2208
Corrected
total
318 144278.0940
Signi?cance level
* : 5% level of signi?cance
** : 1% level of signi?cance
*** : 0.1% level of signi?cance
319 of the possible 6*143 = 858 pro?t data
values over the six-year period were available/
reported for the pro?t dataset.
Table 3: Mean pro?t percentage values according to KickStart support levels, with
Bonferroni Multiple Comparisons of means test results indicated
Bonferroni grouping Mean N Support level
A 23.0860 163 1
B 18.9290 156 0
Means with di?erent letters (either a or b) next to them di?er signi?cantly.
Final analysis of variance on the turnover dataset
Once the general significance on the ANOVA model of the turnover data had been
verified (Table 4, a significance level of 0.1% is associated with the general F-statistic
of 10.78), the significance of the effect of the support-effect could be investigated.
From Table 4 it can be deduced that support-effect is significant at the 0.1% level of
significance. The null hypothesis of no significant effect of support could thus be
rejected in favour of the alternative hypothesis of significance. It can thus be deduced
that the type of support rendered affected turnover figures significantly. Table 4
reports on these deductions.
A Bonferroni Multiple Comparisons of means test was conducted on the turnover
mean values calculated according to support categories. The test gives an indication
of how turnover figures are affected by the support-effect. Means that differ
significantly from one another are shown in Table 5 and indicate that the mean
E. Swanepoel, J.W. Strydom & C. Nieuwenhuizen
72
turnover for respondents who had received training, funding and mentoring were
significantly greater than for those who received only training.
Table 4: Analysis of variance results on turnover data with the e?ect of KickStart
support entered into the ANOVA model (and e?ect of years added to the
error term)
Source
Degrees of
freedom (df)
Sum of
squares
Mean sum of
squares
F value
Probability
(F-statistic >
F-critical)
Model 1 8.1812E12 8.1812E12 10.78 0.0011***
Support 1 8.1812E12 8.1812E12 10.78 0.0011***
Error 353 2.6783E14 7.5873E11
Corrected
total
354 2.7601E14
Signi?cance level
* : 5% level of signi?cance
** : 1% level of signi?cance
*** : 0.1% level of signi?cance
355 of a possible 6*143 = 858 data values over
the six-year period were available/reported
for the pro?t dataset.
Table 5: Mean pro?t percentage values according to KickStart support levels, with
Bonferroni Multiple Comparisons of means test results indicated
Bonferroni grouping Mean N Support level
A 464 533 190 1
B 160 162 165 0
Means with di?erent letters (either a or b) next to them di?er signi?cantly.
Discussion
It was not possible to separate the effect of funding from the effect of mentoring, as
no group received only funding or only mentoring after training. To understand the
value of the funding and mentoring in context, the following contributing factors
should be appreciated:
• The role of funding. Although the amount of money received by a respondent was
not large, it did make a significant difference in the growth of these businesses.
The regional grants received by the respondents ranged from as little as R7 000 to
R100 000, while the prize money ranged from R10 000 to R180 000. A mitigating
factor is the fact that the size of the businesses of these respondents ranged from
An empirical analysis of a private company’s corporate social investment in SMME development
73
micro to very small or small. For a small business, the money was sufficient to
make a difference, and even more so when it was a start-up business.
• The availability of funding for micro and small enterprises. South African studies
by Statistics South Africa (StatsSA 2005) on micro enterprises and by Orford,
Wood, Fischer, Herrington and Segal (2003) on start-up businesses found that
the primary source of funds used, or expected to be used, by the owners of such
businesses is from own savings and income. A second source of financing is from
personal networks, which include family and friends, and lastly from institutions
or venture capitalists. Researching the financing of micro-entrepreneurs by South
African banks, Schoembee (2000) identified four possible reasons why these
banks are hesitant: high-risk of micro-entrepreneurs defaulting; high costs of
screening applicants without sufficient collateral; low returns on transacting with
these entrepreneurs; and socioeconomic, language and cultural barriers. The SAB
KickStart Programme incurs the costs of carefully screening the applicants, and
collateral is not required. SAB donates the funding, and this eliminates concerns
about defaulting or low returns. By providing mentoring, socioeconomic, language
and cultural barriers are overcome.
• The role of mentoring to supplement training. A comparison of the content of
the SAB KickStart training manual with internationally acceptable training
requirements for SME owners/entrepreneurs reveals that it covers most of the
standard topics. However, the content needs to expand on financial management
and some of the critical business management skills and people skills, as well as
to include sections on the management of rapid growth and development of the
new venture beyond start-up, the formation of strategic alliances, and legislation
critical to South African businesses. It is possible for mentors to fill these training
gaps, as and when required, as each mentor mentors about five participants.
• The role of mentoring to support unqualified and inexperienced participants. The
overall satisfaction of the respondents with their mentors was high, but this
should be mitigated by the fact that they had few or no business management
qualifications, managerial experience or previous experience in a similar business.
In such a scenario, any assistance would be of value. Based on research among
entrepreneurs by Bisk (2002: 264), the type of mentoring provided by the SAB
KickStart Programme can be classified as formal mentoring – SAB KickStart
selects the mentors and allocates them to participants (this is more an allocation
than a match). More than 80% of the respondents seemed to be satisfied with the
assistance received from mentors with regard to writing monthly reports, financial
management and business planning, while about 70% were satisfied with the
marketing assistance from mentors. Of the respondents with start-up businesses,
E. Swanepoel, J.W. Strydom & C. Nieuwenhuizen
74
about 44% were dissatisfied with the assistance received from mentors in the areas
of human resources management, operations management and networking.
• Adaptation of product/service line. A German study examined the impact of
knowledge types on the transition from unemployment to entrepreneurship.
Dencker, Gruber and Shah (2006: 48) found that “prior knowledge of industry/
product, and the adaptation of product line following market entry increases the
likelihood of success”. In the case of the participants, only 48% had some or a lot
of experience in a similar business, but 77% of the respondents diversified the
product range and/or service type after market entry. This may have contributed
to their success.
Practical implications
The value of the study lies therein that it contributes to the body of knowledge on
SMME development in a developing economy by offering guidelines for academia
with regard to the value contributed by multiple interventions in entrepreneurship
development programmes and the training needs of entrepreneurial SMMEs in
a developing economy. It provides practical insights for managers responsible for
corporate venture capital investment through corporate social investment in young
entrepreneurial firms into the structuring and management of entrepreneurship
development programmes.
The practical implications of the study lie in contributing to efforts to initiate
and support entrepreneurial action and the successful exploitation of promising
opportunities by identifying and describing appropriate interventions and structures
to help investors, corporate social investment departments, consultants, educators,
non-profit organisations, government departments and other professionals
understand the benefits – and limitations – of a youth entrepreneurship development
programme.
Limitations and future research
A limitation of the study is that the interventions, funding and mentoring could not be
separated, because only those SAB KickStart participants who received funding were
entitled to mentoring. The use of turnover or profit figures to measure success among
small businesses in a developing country poses problems due to the incompleteness
of the data. A few respondents were not able to provide turnover figures because of
the business being a start-up, while some others claimed not to possess such data.
Nevertheless, enough data were collected for the statistical analysis.
An empirical analysis of a private company’s corporate social investment in SMME development
75
Future research should focus on determining the effect of mentoring on business
growth. If mentoring could be made available to the SAB KickStart participants
who did not receive funding, it would be possible to test whether funding contributed
more than mentoring to the success of the businesses. If the mentoring period could
be extended to two years for a group of participants, it would be possible to measure
whether prolonged mentoring contributes more to business growth. Research
should also be conducted to determine the mentoring and networking needs of
entrepreneurial SMMEs in a developing economy.
A comparative study comparing the success of South African SAB KickStart
participants with those in Colombia where the SAB KickStart Programme was
launched in 2006 should be attempted. A major difference between these two
countries is that Colombia had the second highest TEA percentage in the 2006 GEM
survey, while South Africa ranked 30
th
(Maas & Herrington 2006).
Conclusion
With regard to training for new business creation, Storey (in Henry, Hill & Leitch
2004: 250) notes that despite the “claims of the administrators of intervention and
its effectiveness, the academic community has been slow to investigate this matter”.
This study has taken up this challenge and investigated the effectiveness of the
interventions used by a programme, the SAB KickStart Programme, which has as its
objective the development of young entrepreneurs to start or grow their businesses in
South Africa, a developing economy.
The findings of the research suggest that in the complex process of conceiving,
launching and running new ventures, entrepreneurial SMMEs in a developing
economy not only need training in entrepreneurship and business management, but
also need funding and mentoring, preferably over an extended period, to support
them in their efforts to convert their dreams, ideas and visions into functioning,
profitable companies that create jobs and to boost the growth potential of the venture
and its sustainability.
References
Bisk, L. 2002. ‘Formal entrepreneurial mentoring: the efficiency of third party managed
programs’, Career Development International, 7(5): 262–270.
Botha, M., Nieman, G. & Van Vuuren, J. 2007. ‘Measuring the effectiveness of the
Women Entrepreneurship Programme on potential, start-up and established women
entrepreneurs in South Africa’, South African Journal of Economic and Management
Sciences 10(2): 163–183.
E. Swanepoel, J.W. Strydom & C. Nieuwenhuizen
76
Carree, M.A. & Thurik, A.R. 2003. ‘The impact of entrepreneurship on economic growth’,
In Acs, Z.J. & Audretsch, D.B. (eds), Handbook of Entrepreneurship Research: an
Interdisciplinary Survey and Introduction. New York: Springer Science + Business
Media.
De Faoite, D., Henry, C., Johnston, K. & Van der Sijde, P. 2004. ‘Entrepreneurs’ attitudes to
training and support initiatives: evidence from Ireland and the Netherlands’, Journal of
Small Business and Enterprise Development 11(4): 440–448.
Dencker, J., Gruber, M. & Shah, S.K. 2006. ‘Knowledge-related success factors on the path
from unemployment to entrepreneurship’, Conference proceedings of the 26
th
Babson
College Entrepreneurship Research Conference, Bloomington, Indiana (USA), 8–10
June 2006.
De Wet, H. (ed.). 2007. The CSI Handbook, 10
th
edition. Cape Town: Trialogue.
dti (Department of Trade and Industry). 2008. Annual Review of Small Business in South
Africa: 2005–2007. Pretoria: Enterprise Development Unit, dti.
dti (Department of Trade and Industry). 2007. Integrated Strategy on the Promotion of
Entrepreneurship and Small Enterprises. Pretoria: Enterprise Development Unit, dti.
[Online] Available at:http://www.dti.gov.za. Accessed: 12 February 2007.
Fisher, G. 2004. An exploration of innovative teaching methods in the area of entrepreneurship
on MBA programmes. MBA research report, Gordon Institute of Business Science,
University of Pretoria.
Henry, C., Hill, F.M. & Leitch, C.M. 2004. ‘The effectiveness of training for new business
creation: a longitudinal study’, International Small Business Journal 22(3): 249–271.
Herrington, M., Kew, J. & Kew, P. 2008. Global Entrepreneurship Monitor 2008. Cape Town:
Centre for Innovation and Entrepreneurship, Graduate School of Business, University
of Cape Town.
High, J. 2004. ‘The roles of entrepreneurship in economic growth: toward a theory of
total factor productivity’, in De Groot, H.L.F., Nijkamp, P. & Stough, R.R. (eds),
Entrepreneurship and Regional Economic Development: a Spatial Development.
Northampton, MA: Edward Elgar.
Hisrich, R.D. & Peters, M.P. 2002. Entrepreneurship, 5
th
edition. Boston, MA: McGraw-Hill/
Irwin.
Hussey, J. & Hussey, R. 1997. Business Research: a Practical Guide for Undergraduate and
Postgraduate Students. Hampshire: Palgrave.
Keller, G. & Warrack, B. 2000. Statistics for Management and Economics, 5
th
edition. Pacific
Grove, CA: Duxbury Thomson Learning.
Kennedy, J. & Drennan, J. 2001. ‘A review of the impact of education and prior experience on
new venture performance,’ Entrepreneurship and Innovation, October: 160–172.
Kent, T., Dennis, C. & Tanton, S. 2003. ‘An evaluation of mentoring for SME retailers’,
International Journal of Retail and Distribution Management, 31(8): 440–448.
Kuratko, D.F & Hodgetts, R.M. 2004. Entrepreneurship: Theory, Process, Practice, 6
th
edition.
Mason, OH: Thomson South-Western.
An empirical analysis of a private company’s corporate social investment in SMME development
77
Ladzani, W.M & Van Vuuren, J.J. 2002. ‘Entrepreneurship training for emerging SMEs in
South Africa’, Journal of Small Business Management, 40(2): 154–161.
Landström, H. 2005. Pioneers in Entrepreneurship and Small Business Research. New York:
Springer Science + Business Media.
Leedy, P.D. & Ormrod, J.E. 2005. Practical Research: Planning and Design, 8
th
edition. Upper
Saddle River, NJ: Pearson.
Maas, G. & Herrington, M. 2006. Global Entrepreneurship Monitor: South African Report.
Cape Town: Centre for Innovation and Entrepreneurship, Graduate School of Business,
University of Cape Town.
Maula, M., Autio, E. & Murray, G. 2005. ‘Corporate venture capitalists and independent
venture capitalists: What do they know, who do they know, and should entrepreneurs
care?’, In Elfring, T. (ed.) Corporate Entrepreneurship and Venturing. New York: Springer.
Orford, J., Wood, E., Fischer, C., Herrington, M. & Segal, N. 2003. Global Entrepreneurship
Monitor: South African Executive Report 2003. Cape Town: Graduate School of Business,
Centre for Innovation and Entrepreneurship, University of Cape Town.
Orford, J., Herrington, M. & Wood, E. (eds). 2004. Global Entrepreneurship Monitor: South
African Report. Cape Town: Centre for Innovation and Entrepreneurship, Graduate
School of Business, University of Cape Town.
SAB Ltd. 2006. Stepping up to the Future: Sustainability Report 2006. Johannesburg: CSR
Department, Corporate Affairs, SAB.
SABMiller plc. 2005. Annual Report ’05. London: SABMiller.
SABMiller plc. 2008. Annual Report: SABMiller plc Annual Report 2008. London: SABMiller.
Schoembee, A. 2000. ‘Getting South African banks to serve micro-entrepreneurs: an
analysis of policy options’, Development South Africa,17(5): 751–767.
StatsSA (Statistics South Africa). 2005. Survey of Employers and the Self-employed. [Online]
Available at:http://www.statssa.gov.za/publications/P0276/P02762005. Accessed: 7
August 2007.
Stats SA (Statistics South Africa). 2007. Key Findings: Mid-year Population Estimates, 2007.
Statistical release P0302. [Online] Available at: www.statssa.gov.za. Accessed: 10
December 2007.
Stats SA (Statistics South Africa). 2009. Quarterly Labour Force Survey (QLFS), 4
th
Quarter
2008. Statistical release P0211. [Online] Available at:http://www.statssa.gov.za.
Accessed: 30 March 2009.
Sullivan, R. 2000. ‘Entrepreneurial learning and mentoring’, International Journal of
Entrepreneurial Behaviour and Research, 6(3): 160–175.
Timmons, J.A. & Spinelli, S. 2004. New Venture Creation: Entrepreneurship for the 21
st
Century, 6
th
edition. Boston, MA: Irwin McGraw-Hill.
Van Stel, A., Carree, M. & Thurik, R. 2004. The Effect of Entrepreneurship on National
Economic Growth: an Analysis using the GEM Database. [Online] Available at: http://
www.babson.edu/entrep/fer/FER_2004/web-content/section%20XIX//XIX. Accessed:
4 April 2006.
E. Swanepoel, J.W. Strydom & C. Nieuwenhuizen
78
Von Broembson, M., Wood, E. & Herrington, M. 2005. Global Entrepreneurship Monitor:
South African Report. Cape Town: UCT Graduate School of Business, Centre for
Innovation and Entrepreneurship.
Watson, G.E.H. 2004. A situational analysis of entrepreneurship mentors in South Africa.
MCom dissertation, University of South Africa, Pretoria.
Wickham, P.A. 2004. Strategic Entrepreneurship, 3
rd
edition. Harlow: Financial Times
Prentice-Hall.
World Bank. 2006. Doing Business in 2006: Creating Jobs. Washington: World Bank.
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