1. BARRIERS TO ICT ADOPTION FOR MICRO-BUSINESSES IN SOUTH AFRICA
Dipalesa Mpye, University of Cape Town, mpydip001@mail.uct.ac.za, +27-21-6504256
Shabnam Osman, University of Cape Town, shabnamosman@gmail.com, +27-21-6504256
Jean-Paul Van Belle (contact author), University of Cape Town, Jean-paul.VanBelle@uct.ac.za, +27-21-6504256
ABSTRACT
This research investigated the barriers to ICT adoption among micro-businesses in the Cape Town metropolitan
area. A set of barriers identified in prior research was investigated to see how applicable these barriers were to
South African micro-businesses. A second research objective was to look specifically at how the ICT barriers
differed between businesses in suburbs with extremely different socio-economic profiles. Although the sample was
relatively small, the research suggests that the barriers to adoption of ICTs in a developing world context may differ
substantially from those found in developed countries. The relative importance of some of these barriers appears to
depend on the socio-economic profile of the suburb.
1 INTRODUCTION
Information and Communication Technologies (ICTs) have transformed the way businesses operate. The Internet,
especially, has become an essential medium for communication and business exchanges (Chau, 2003). While large
businesses have fully embraced ICT, the uptake and implementation of ICT in small business practices has not been
the same (Docherty & Simpson, 2004). This study looks at the key ICT use or adoption barriers faced by micro
businesses in substantially different socio-economic suburbs in Cape Town. ICTs for the purpose of this research
are understood to be desktop (personal) computer applications (i.e. productivity, financial and vertical applications)
and Internet. Previous research identified some ICT barriers for micro businesses in South Africa (e.g. Bowen,
Kaatz & Shakantu, 2002; DTI, 1995; Gumede & Rasmussen, 2002). This study explores these barriers, and attempts
to find correlations between them and barriers identified in micro businesses oversees abroad.
While much research has been done on ICT barriers for SMEs (Small & Medium Enterprises), micro businesses
have not been researched to the same extent despite the fact that the latter contribute a quarter of South Africa’s
economy (Bowen et al., 2002). This sector generates a lot of employment and has thus been identified by the
government as a priority. Current government initiatives in support of micro business have been largely
unsuccessful. This may be due to a lack of knowledge about the factors which affect micro businesses (Nieman,
2001). This study thus also hopes to provide policy makers with valuable insights about ICT barriers currently
facing micro businesses.
2 PRIOR RESEARCH ON KEY ICT ISSUES FACING MICRO BUSINESSES (abbreviated)
Braven et al. (2000) investigated micro businesses in the Netherlands and found the following barriers to ICT usage:
firm awareness and access to infrastructure, ICT use among business partners, confidence in the security
framework, and adaptation of business processes. Additional organisational and manager-owner factors were
identified by Fillis, Johansson and Wagner (2003). The lack of both financial and human resources of micro
businesses causes a typical ICT use barrier (Poon & Swatman, 1998). The cost associated with ICTs has been
reported to be a significant barrier to the access and use of these ICTs within micro businesses (Gray, 2003).
Ignorance has also been found to be a significant barrier to ICT usage. Alcock et al. (2003) found that a large
proportion of small enterprises in Chile were unfamiliar with the internet, and unaware of the benefits it can lend to
their businesses, and hence do not to adopt it. The lack of sufficient guidance available to small businesses about the
internet “start-up” process could be the reason why these businesses do not take advantage of the technology in the
first place (Docherty & Simpson, 2004).
Micro businesses claim to not have time to refine their business processes to suit the particular technology adopted
(Alcock et al.,2003).Some also claim to not have the time to train employees on the use the particular technology
implemented (Braven et al., 2000). Poon & Swatman (1998) reveals that micro businesses are concerned that the
use of Internet technology within the workplace will result in decreased productivity levels, due to the potential
misuse of the technology by employees. Managers or owners of small businesses manage a very small workforce
and possess a high locus of control within the business (Braven, et al, 2000). Thus the manager or owner’s attitudes
toward and perception of ICTs are fundamental to a micro businesses usage of technology (Fillis et al, 2003).
Education levels of the manager or owner of a micro business is a strong characteristic to explain computer

2. knowledge and use within the business. The level of schooling held by the manager or owner is positively correlated
with the presence of a computer in the business (Pierson, 2000, Grandon & Pearson, 2004).
The focus of most of the literature reviewed in the previous section has been on micro businesses in a context of
developed countries. Previous research has failed to take into account the possible role of the socio economic
disparities between developing and developed nations in determining the ICT use barriers faced by micro
businesses. Socio-economic disparities nations present a “digital divide”, a term commonly used to describe the
pattern of unequal ICT access across developing and developed countries, as well as the pattern of unequal ICT
access within the borders of a country. This is traditionally the divide between urban and rural regions or the rich
and the poor (Fink & Kelly, 2003).
3 RESEARCH METHODOLOGY
The primary objective of this research is to uncover the key ICT use issues and barriers faced by micro businesses in
Cape Town. Prior research stresses that not much research has been done on ICT issues of micro businesses.
However, the limited previous research that is available has identified some factors. This research aims to determine
if these factors do in fact also play a role in the South African context. Secondly, the South African economy still
exhibits large disparities with regards to income and skills, prompted us to determine whether there is a relationship
between location and the type of ICT barriers that micro businesses face.
The sample for this study are micro businesses in the Cape Town Metropolitan Area. Our sample was stratified
according to geographical area, namely Gugulethu, Athlone and Rondebosch. These areas were chosen because very
different socio-economic conditions are prevalent in each of these areas (Table 1). There has been significant
empirical evidence of local “digital divides” within relatively small regions in South Africa based on physical
location (see e.g. Vosloo & Van Belle, 2007).
Suburb Socio-economic Profile
Popu-
lation
Density
Avg.
House-
Hold size
Median
Ann. HH
Income
Monthly
Per capita
Income
Gugulethu Almost 100% black lower-income community 131.89 5.5 R14745 R 384
Athlone A predominantly coloured & muslim, median
income community
59.69 3.9 R34330 R1057
Rondebosch Historically and predominantly white upper
income suburb with large student community
20.20 2.6 R62352 R3077
Table 1: Socio-economic profile of three survey areas (City of Cape Town, n.d.)
The survey instrument incorporated parts of the instruments used in two prior studies on the ICT issues of SMEs in
Europe (Pierson, 2000 and Braven et al., 2000). A copy is available from the authors on simple request.
4 DESCRIPTIVE DATA ANALYSIS
From the 180 questionnaires that were distributed, only 68 completed ones could be collected, even after repeated
visits to the businesses, of which only a disappointing 62 responses were usable. Despite this somewhat
disappointing response, it is believed that most of the findings below are of considerable interest. Luckily the
responses were very evenly split between the three suburbs, though not according to major industry sector. The
average number of employees was 4 with no business reporting more than 9 full time employees. The age of the
micro business owner ranged from 20 to 69 with an average of 40 years. Most respondents indicated that their
highest education level was high school. There were a number of respondents in Athlone and Rondebosch with post
graduate degrees; some of these could be attributed to the professionals and manufacturers in these locations.
Nearly all respondents owned a cell (mobile) phone and a land (fixed) line telephone. Four respondents in
Gugulethu did not have a landline. Many respondents owned fax machines, computers and had Internet access,
though this number was significantly lower in Gugulethu, for all three of these technologies. Overall about 60% of
micro businesses indicated that they used a computer for business purposes. However, only 6 out of 19 of the
Gugulethu respondents said that they used a computer for business purposes. Despite the small sample, this relative
“under-provision” of PCs in Gugulethu is statistically significant at a 5% confidence level (χ2
= 8.988; p = 0.00272).

3. 5 ICT BARRIERS FACED BY MICRO-BUSINESSES IN CAPE TOWN.
Of particular interest to a developing world context is the question of whether high technology costs – hardware,
software and internet – present a barrier to ICT. Table 2 below presents the average rating for why respondents did
not have a computer or Internet access. The relative importance (ranking) of these barriers is also given. Note that a
5-point Likert scale was used with 3 being the neutral point and higher scores (>3) representing agreement with the
statement that this represents a barrier or problem.
Cost Issue Gugulethu Athlone Rondebosch Overall
Hardware Cost 3.25 (2nd
) 3.00 (-) 3.33 (3rd
) 3.21 (4th
)
Software Cost 3.69 (1st
) 3.17 (3rd
) 3.17 (4th
) 3.44 (1st
)
Internet (startup cost) 3.20 (3rd
) 3.25 (2nd
) 3.38 (2nd
) 3.27 (3rd
)
Internet (monthly cost) 2.90 (-) 3.38 (1st
) 3.75 (1st
) 3.31 (2nd
)
Technology Costs (Avg) 3.26 3.20 3.41 3.31
Table 2: Technology Cost as a Barrier to Infrastructural Access.
There appears to be a ‘digital divide’ between Gugulethu and the two more affluent areas. In Gugulethu, the prime
barrier appears to be access to basic computer resources whereas the higher income areas are more concerned with
Internet access costs and other considerations. The initial impact of the investment on overall cash flow appears to
be a significant factor because only two respondents indicated that they would prefer buy outright rather than to
lease a fully inclusive computer package. Of particular interest is the issue of the (perceived) high software cost –
ranked as the highest obstacle overall. This was investigated by a follow-up question: respondents were also asked
whether they would buy a computer if software were to be free. 80% of the respondents said that they would, which
confirms the cost of software as a critical barrier. The fast rise of open source software in the developing countries
and the high priority given to OSS by the South African government and NGOs such as the Shuttleworth
Foundation and Translate.org are aiming to address this particular issue (Brink, Roos, Weller & Van Belle, 2006),
but this has apparently not yet made a visible impact.
Respondents were also asked to rate their perceptions in respect of the benefits which ICTs could provide for their
business. it emerges that the non-adopters of computers or Internet in Athlone did so because they did not perceive
any cost or business benefits from it. By contrast, non-adopters in both Gugulethu and Rondebosch generally
perceived significant benefits from ICT adoption so the adoption barriers were other factors. This difference by
suburb in perceived benefits is statistically significant (ANOVA test F(2,118) = 5.296; p = 0.00627). Interestingly
enough, “Internet cost savings” is consistently rated lowest possible perceived benefit of all four. This can be
attributed to the low Internet penetration among South African consumers and the high costs of Internet access.
Technology Benefits Gugulethu Athlone Rondebosch Overall
No cost savings (PC) 2.46 4.17 2.33 2.84
No cost savings (Internet) 2.90 3.75 3.38 3.31
Business process not more efficient (PC) 1.92 4.33 2.83 2.72
Business process not more efficient (Internet) 2.50 3.25 2.75 2.81
Overall (average score) 2.65 3.34 2.68 2.83
Table 3: Perceived Benefits of Technology
Non-adopters of ICTs were also asked to which extent their lack of technical knowledge presented a barrier. This
lack of know how included knowledge with regards to buying and implementing technology, as well as the
knowledge required to use the relevant technology (Table 4).
Know-how Item Gugulethu Athlone Rondebosch Overall
Don’t know what to buy 3.54 3.17 3.17 3.36
Don’t know how to implement Internet 3.30 3.25 2.13 2.92
No computer skills 3.23 3.83 3.00 3.32
No Internet skills 3.70 3.50 2.13 3.15
Overall (average score) 3.44 3.44 2.60 3.19
Table 4: Lack of Technical Skills.

4. As can be seen from Table 4 most of the barriers relating to technical use seem to be significant. Overall, knowledge
about how to implement the Internet does not appear to be a significant barrier; however it can be seen from the
table that this barrier is considerable in both Gugulethu and Athlone. This difference by suburb in lack of know-how
is statistically significant (ANOVA test F(2,99) = 6.0738; p = 0.00325). The highest overall mean value indicates
that most respondents do not know what computer hardware or software to buy and this barrier seems highly
prevalent in all three locations. This is closely followed by the barrier which states that many respondents do not
have the technical skills to use computers, and once again this barrier is prevalent in all three locations.
Not surprisingly, there was a strong and statistically significant correlation of between computer ownership and
whether respondents had had computer training. When looking at the education of PC owners, there is an almost
identical split in ownership for those owners who had a high school or technical college degree. However, not
surprisingly, almost all respondents who have a postgraduate qualification also owned a PC and used it for business
use. Thus, as the level of education increases, the proportion of respondents who have a computer also does.
Because there is strong call on the government to play a more pro-active role in the support of the micro-business
sector, the awareness of government support initiatives related to ICTs was also investigated. It is revealing to note
that, of the 16 out of 62 respondents who were aware of government initiatives, virtually all (12) were located in
Gugulethu. No clear explanation exists for this highly significant difference between locations (χ2
= 19.97;
p<0.0001). However, of those that were aware, only 3 respondents indicated that they had used the initiatives.
6 SUMMARY
Findings reveal that high technology costs, lack of technical knowledge to use the technology, resistance to adapt
business to incorporate technology and lack of awareness of government support programmes are all significant
barriers to ICT use by micro businesses in the Western Cape. However, contrary to some previous research, our
findings suggest that micro businesses are aware of the technology and the benefits it can achieve. Security concerns
did also not seem to be a significant barrier. Training considerations were also not considered a major barrier by the
micro businesses, except in Gugulethu.
Importantly, the research shows that there are clear differences between the ICT barriers faced by micro businesses,
based on location/socio-economic context. For instance, the respondents from Athlone indicated that unfamiliarity
with technology benefits to business was a significant reason for them not to adopt ICTs. The lack of awareness to
government support infrastructure was found to be a significant barrier to ICT use in all except the ‘poorest’ area
Gugulethu. However, the latter did also not make use of government support. Respondents from Gugulethu also felt
that decreased productivity due to the misuse of technology by employees was a significant barrier; a sentiment not
shared by the other locations. These differences could be a direct result of sampling errors caused by the small size
of the sample or, more interestingly the potential socio-economic differences between the three locations.
7 SELECTED REFERENCES
Other references were omitted due to space limitations but a full list is available on simple request from the authors.
Braven, G., Lundgren, H. & Walczuch, R. (2000). Internet Adoption Barriers for Small Firms in the Netherlands.
European Management Journal, 18(5), 561-572.
Docherty, A. J. & Simpson, M. (2004). E-commerce Adoption Support and Advice for UK SMEs. Journal of Small
Business and Enterprise Development, 11(3), 315-328.
Grandon, E. & Pearson, J. M. (2004). E-Commerce adoption: Perceptions of managers/owners of small and medium
sized firms in Chile. Communications of the Association for Information Systems, 12, 81-102.
Nieman, G. (2001). Training Entrepreneurs and Small Business Enterprises in South Africa: a situational analysis.
Education and Training, 43, 445-450.
O’Dwyer, M. & Ryan, E. (2000). Management Development Issues for Owners/Managers of Micro-Enterprises.
Journal of European Industrial Training, 24(6), 345-353.
Poon, S. & Swatman, P. (1998). An exploratory study of small business Internet commerce issues. Information &
Management, 35, 9-18.
Vosloo, S & Van Belle J.P. (2007) The Influence of Location on the E-Readiness of South African Non-Profit
Organisations. In Garg, R. & Jaiswal, M. Bridging Digital Divide, New Delhi, MacMillan, pp.127-139.