dc.description.abstract |
Small and medium-sized enterprises (SMEs) are a key driver of global economic
growth, which implies that they are critical to national economic growth. As a
result, they are priorities in most governments' development agendas. Thus, it is
critical for SME owners and managers to be aware of the factors influencing their
companies' performance and to be able to act when necessary.
Although scholars have conducted research on SME performance and growth
factors for more than two decades, we still have a limited understanding of this
type of research. This cross-sectional quantitative exploratory study examined
SME owner-managers perspectives on factors influencing SME performance in
South Africa and China. The Tshwane University of Technology provided
secondary data for the study. The dataset included 401 participants, of whom
approximately 66% (266) were South African and 34% (135) Chinese.
Proportions and count were used to summarize all categorical information, and
Pearson's chi-square test was used to test for association between each pair of
categorical variables. Pearson's chi-squared test, with a 0.05 error rate, revealed
that the factors d4 (contribution of networking towards SME success), d5 (quality
services and products determine entrepreneur success), e8 (high rental costs),
and f7 (innovation and creativity) were insignificantly associated with the country
(South Africa and China). Otherwise, participants in the two countries had very
different perspectives on the latent constructs under investigation. In other
words, the study reported that the Chinese and South African SME owners had
different perceptions of the factors that influenced SME performance or success.
The exception was observed in terms of innovation and creativity, where they
perceived this aspect to be important in overcoming SMEs' challenges.
The study concluded that SME performance and, as a result, SME growth rate,
may be influenced by managerial traits, internal factors, and external factors. If
visual analogue scale data had been used instead of Likert-scale data, either the
same or different results would have been obtained. Furthermore, the results of
the study that employed multivariate data analysis would be more trustworthy
because the model would have considered a large number of covariates. |
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