Micro and Small Enterprises (MSEs):
What are the Best Indicators of Their Performance?
Henny Indrawati
Economics Education Studies Program, Faculty of Teachers Training and Education,
Universitas Riau, Kampus Bina Widya Km. 12,5 Simpang Baru, Pekanbaru, Indonesia
Keywords: Capital access, business plan, business networking, government support.
Abstract: MSE is one of the sectors that contribute to economic development, especially in the creation of
employment and value added. One of the developing MSEs in Riau Province is MSEs of crispy mushroom.
The MSEs’ performance is influenced by a number of variables. This study aims to analyze the variables
that affect the MSEs’ performance. The subjects of this research were MSEs of crispy mushroom in Riau
Province, Indonesia. The data were collected by interviews based on the questionnaire, and then analyzed
using multiple linear regression analysis. The study found: 1) Capital access, business plans, business
networks, and government support have significant and positive impacts on MSEs’ performance; and 2)
business networking has the most significant impact on MSEs’ performance. To improve their performance,
MSEs have to expand their business networking, so that the existence of the business can be maintained,
and even grow better.
1 INTRODUCTION
Micro and Small Enterprises (MSEs) have been
recognized as very important sectors, not only for
economic growth but also for income distribution.
Viewed from the business scale, from 26.7 million
businesses (outside the agricultural sector), 98.33
percent are micro and small enterprises. Meanwhile,
medium and large enterprises are only 0.45 million,
or only about 1.6 percent of the total 26.7 million
businesses or non-agricultural enterprises in
Indonesia. In Riau Province, out of 278 thousand
businesses, 98.66 percent are micro and small
enterprises and only 1.34 percent of medium and
large enterprises (Indonesian Central Bureau of
Statistics, 2016).
Therefore, both central and local governments
continue to make various efforts in the development
of MSEs, with the hope that the impact of such
development can increase the contribution of MSEs
significantly in improving the regional economy and
national economic resilience. These conditions are in
line with the studies’ results of Ivanová (2011), Rao
(2014), Ratten (2014), ulHaq et al. (2014) which
concluded that the success of MSEs has a direct
impact on economic development, especially in
developing countries.
One type of MSEs in Riau Province is MSEs of
crispy mushroom. This business utilizes mushrooms
that grow on empty bunches of palm oil as raw
material production. In Riau province, palm oil is
the main commodity that many cultivated by society
and business entity. Based on data from the
Directorate General of Plantation (2015), the
production of fresh palm fruit bunches of 1,792,481
tons in 2000 increased to 7,442,557 tons in 2015.
The increase in the production also resulted in the
increase of empty palm fruit bunch waste. One effort
to overcome the waste is to change the empty
bunches of oil palm into a medium of growing
mushrooms. For every 1,600 kg of oil palm empty
bunches for 40 days will produce 65-70 kg of fresh
mushroom. This is a potential for MSEs of crispy
mushroom to increase production. With the potential
it is expected that MSEs of crispy mushroom can
increase their sales and ultimately can improve
business performance.
But, the fact indicates that the sale of crispy
mushroom has not increased significantly in the last
five years. The sales average of crispy mushroom in
2016 was 40 kg per month, and only increased by 5
kg compared to 2013. It can be said that its business
performance is still poor. Allegedly the cause is lack
of business networks owned by business actors.
Indrawati, H.
Micro and Small Enterprises (MSEs): What are the Best Indicators of Their Performance?.
In Proceedings of the 2nd International Conference on Economic Education and Entrepreneurship (ICEEE 2017), pages 309-314
ISBN: 978-989-758-308-7
Copyright © 2017 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
309

According to Polo-Pena et al., (2012) and Lane
(2017), there are many variations in assessing
MSEs’ performance. Profitability and non-financial
measures can be used to measure the success of
MSEs (Lucky and Minai, 2011). Blackburn et al.
(2013) assesses the small business performance of
changes in employment, capital turnover and profit
growth. Meanwhile, in the research of Pinho and de
Sa (2014), the MSEs’ performance is measured from
the perception of business actors towards the
company's growth due to the sensitivity surrounding
the profit data. In contrast to previous research, this
study does not only assess business actors'
perceptions of business profit growth as an indicator
of MSEs’ performance, but also assess market
growth and sales growth from the MSEs
perceptions.
There are several factors that affect the MSEs’
performance. Capital is one important factor to
improve business performance. Even equity access
to capital for all segments of society is believed to
be an alternative to equitable income. It is based on
the idea that with capital, we can optimize the
existing resources to increase business profits, which
in turn can increase revenue. There-fore, the lack of
access to capital is the first determinant of the failure
of small businesses in Pakistan (Lussier, 2016). In
Indonesia, Indrawati and Caska (2015) found that
lack of access to the capital of sago cake craftsmen
caused most craftsmen not able to produce cakes
regularly, so that consumers' demand for cakes was
often not met.
Besides capital, the business plan is also one of
the factors that determines of MSEs’ performance
(Jasra et al., 2011). Business plan is a written
document that describes the employer's plan to take
advantage of business opportunities that exist in the
company's external environment. It also explains the
competitive advantage of the business, and explains
the various steps that must be taken to make the
business opportunity into a real business form. The
first failure to start a business is due to the inability
to design a good business plan, so that when
entering the business world, many unexpected things
arise and cause the business not knowing what to do.
One of the benefits of creating a business plan is that
it can reduce the risk of business failure. A directed
plan will help to show a general description of what
and why a mistake or failure can occur. In addition,
it can also minimize high cost expenses that are not
in accordance with the plans and needs.
Business networking and government support are
also key determinants of MSEs’ performance (Jasra
et al., 2011). Business networking is the process of
building a mutually beneficial relationship with
other entrepreneurs or customers in order to increase
business revenue. Business networking is an
important entrepreneurial tool that contributes to the
formation, development and growth of small
businesses (Salavisa et al., 2009). The government'
support for improving MSEs’ performance, among
others, can be done by facilitating access to markets,
or access to formal financial institutions (Indrawati
and Caska, 2015).
Jasra et al. (2011) find that the business plan,
business networking and government support is a
determining factor on MSEs’ performance in
Pakistan. However, the results of research by Pinho
and de Sa (2014) found that government support did
not affect the performance of MSEs in Portugal.
Another study by Lane (2017) also found that
business plans did not affect the success of MSEs in
California. Whereas business actors who make
written business plans are more likely to experience
higher levels of capital turnover and employment in
the UK (Blackburn et al., 2013).
Several previous studies have shown the
diversity of research results. Therefore, to know
clearly the variables that have the greatest impact on
the performance of crispy mushroom MSEs in Riau
Province of Indonesia, it is very important to do this
research with the aim of analyzing the variables that
affect the MSEs’ performance. In this study, the
variables that affect the MSEs’ performance are
measured from capital access, business planning,
business networking, and government support. The
results of the research will be useful for MSEs and
government as decision makers in connection with
the MSEs’ development.
2 METHODS
2.1 General Background of Research
This research is a quantitative research using a
survey as a method of data collection. The research
was conducted in Indragiri Hulu, Pelalawan,
Kampar, and Siak, Riau Province, Indonesia.
2.2 Sample of Research
The research samples were 225 MSEs of crispy
mushrooms. The samples were taken by purposive
random sampling, with the criteria of MSEs that
have been existed for at least 5 years.
ICEEE 2017 - 2nd International Conference on Economic Education and Entrepreneurship
310

2.3 Instrument and Procedures
The data collected consist of primary and secondary
data. The primary data were obtained from MSEs
through interviews based on questionnaires. The
secondary data were obtained from the offices
related to this research, i.e. Directorate General of
Plantation, Industry and Trade Agency, and
Indonesian Central Bureau of Statistics.
The variables tested in this study consist of
dependent and independent variables. The dependent
variable is MSEs’ performance with three indicators
(sales growth, market growth, and profit growth).
The independent variable consists of capital access
with two indicators (capital access from bank,
capital access from other financial institutions),
business planning with two indicators (MSEs
knowledge about business planning benefits in
improving performance, awareness about business
planning needs), business networking with three
indicators (business network with school cafeteria,
business network with food store, online business
network), and government support with three
indicators (government support in the form of
promoting products when certain activities are held,
government support in the form of equipment
production, government support in the form of
guidance activities and guidance from relevant
offices).
The measurement of research variables were
conducted based on perceptions or responses of
respondents on all indicators of variables that have
been built on the model. Respondents' answers to
each statement were scored, that is score 1 for the
lowest score and score 3 for the highest score. The
range of research criteria can be seen in Table 1.
Table 1: The Range of Research Criteria.
No.
Category
Interval
1
Good
2,34 – 3,00
2
Pretty Good
1,67 – 2,33
3
Not Good
1,00 – 1,66
2.4 Data Analysis
To analyze the influence of independent variable to
dependent variable, multiple linear regression
analysis was used. The research hypotheses are as
follows:
H1: capital access has a significant and positive
impact on the MSEs’ performance.
H2: business planning has a significant and positive
impact on the MSEs’ performance.
H3: business networking has a significant and
positive impact on the MSEs’ performance.
H4: government support has a significant and
positive effect on the MSEs’ performance.
To answer the research hypotheses, F test
(simultaneous) and t test (partial) were used with 5%
significance level. The coefficient of determination
(R
2
) was also analyzed to see the contribution of the
independent variable in explaining the dependent
variable. If the value of R Square approaches is 1, it
means that the independent variable gives almost all
the information needed to predict the variation of the
dependent variable. In other words, the model is
getting better (Gozali, 2011).
3 RESULTS AND DISCUSSION
This study is aimed at analyzing the variables that
affect the MSEs’ performance. The analysis used
was multiple linear regressions. The feasibility of
the model used in the study was analyzed from the
coefficient of determination presented in Table 2.
The coefficient of determination (R Square) is 0.755.
According to Gozali (2011), if R Square is close to
1, the independent variables gives almost all the
information needed to predict the variation of the
dependent variable. In other words, the model is
more appropriate. The significance value of the F
test 0.000 <0.05 shows that simultaneously all the
independent variables significantly influence the
dependent variables.
Table 2: Test Result of Feasibility of Research Model.
Model
R Square
F
Sig.
1
0.755
34.581
.000
Partial analysis of the variables affecting the
performance of MSEs can be seen in Table 3. The
Table shows that the capital access, business
planning, business network, and government support
partially have positive and significant impacts on the
MSEs’ performance. The significance level of all
variables shows smaller than α = 5%.
According to the respondents, the business
performance is perceived to be in pretty good
category with an average value of 2.12. Most of the
respondents classified their sales grew quite well in
the last five years. The good growth also happened
to the market and profit.
Capital access has a significant and positive
impact of 0.273 on the MSEs’ performance.
Therefore, the first hypothesis in this study is
Micro and Small Enterprises (MSEs): What are the Best Indicators of Their Performance?
311

accepted. Average of capital access is 1.78 which is
in the pretty good category. MSEs have difficulties
to access capital from formal financial institutions,
such as banks. The capital owned by most of MSEs
comes from their own capital although it is not
sufficient for the capital requirement. Only 24
percent of MSEs are able to access capital from
banks and 10 percent of loan sharks. These loan
sharks are the last option sought by MSEs when they
need money, despite of the fact that the interest is
very high. The loan sharks are more attractive to
access because financing procedures are not
complicated. The process is quick, no collateral, and
trust based. Shibia and Barako (2017) stated that
MSEs’ growth in Kenya is also positively influenced
by access to formal credit.
Tabel 3: Test Results of Variables Affecting the MSEs’
Performance.
Model
Unstandardized
Coefficients
t
Sig.
B
Std.
Error
1
(Constant)
.395
.205
1.925
.061
Capital
Access
.273
.112
2.424
.019
Business
Planning
.247
.096
2.561
.014
Business
Networking
.293
.117
2.511
.016
Government
Support
.253
.091
2.771
.008
a. Dependent Variable: Performance
Business planning has a significant and positive
effect of 0.247 on the MSEs’ performance, so that
the second hypothesis in this study can be accepted.
The average of business planning is 1.82 in the
pretty good category. Knowledge of most MSEs
about benefit business planning in improving
business performance is still low. Only 28 percent of
MSEs know the benefits of business planning can
improve business performance. Likewise with the
awareness of MSEs of the need to make business
planning, it is found that 10 percent of MSEs have
the awareness of the need to make business
planning. They have even made it, although the
business plan is still simple. The business planning
made still includes the location of the business, the
name of the business owner, the reason for
establishing the business, the product produced, the
production process, and the amount of capital
needed. The MSEs that make written business
planning are more likely to experience higher levels
of capital turnover and employment in the UK
(Blackburn et al., 2013). The findings of this study
support the findings of Jasra et al., (2011) in which
business planning shows a significant impact on
business success in Pakistan, but are inconsistent
with Lane's (2017) study that found business
planning did not affect to the success of MSEs in
California.
Business networking has a significant and
positive effect of 0.293 on the MSEs’ performance.
Therefore, the third hypothesis in this study can be
accepted. The average respondents’ answer about
business networking is 2.00 in pretty good category.
35 percent of MSEs of crispy mushrooms have
business networks with school cafeteria, 20 percent
have with food store, but no one has an online
business network. In this study, business networking
is the best variable that affects MSE performance.
The wider of MSEs’ business network are there is a
tendency of better performance. In the context of
small business, certain resources must be met by the
MSEs by creating a business networking. But
Hernandez-Carrion et al. (2017) state that not all
business networks allow MSEs in Spain to access
relevant resources, with only a few sources provided
by each network that actually proves to be valid
from a business standpoint.
The fourth hypothesis in this study can be
accepted because government support has a
significant and positive impact on the MSEs’
performance. The average answer of respondents
about government support is 1.93 which is in fairly
good category. According to 22 percent of
respondents, the Department of Industry and Trade,
and Social Services have supported the efforts of
MSEs by promoting products when there are
activities such as exhibitions and seminars held in
the region and outside the region. Production
equipment aid has also been received by 5 percent of
respondents from the Department of Industry and
Trade, which is an electronic plastic press tool.
However, because the electric power of the business
is still low, the tool can’t be used optimally by the
MSEs. This finding is inconsistent with Pinho and
de Sa’ (2014) study which found that government
support did not impact on MSEs’ performance in
Portugal. However, in this study government support
through coaching and guidance is still lacking, as
only 8 percent of respondents have ever received
coaching from the local government.
ICEEE 2017 - 2nd International Conference on Economic Education and Entrepreneurship
312

4 CONCLUSIONS
This study concludes that capital access, business
planning, business networking and government
support have positive and significant impacts on
MSEs’ performance. Business networking is the best
variable that affects MSEs’ performance. The
implication of this study is that the findings provide
valuable insights for MSEs, and governments as
policy makers. MSEs must expand their business
network so that the existence of their business can be
maintained, and even better. In addition, through
business networking, MSEs are able to compensate
or accumulate resource constraints. Some efforts that
can be done are to form a network of production and
marketing network. MSEs can join with other MSEs
to add variety to the products, and work together to
penetrate new markets. Governments are expected to
implement appropriate policies and incentives to
develop MSEs and reduce the burden of bureaucracy
for new businesses, facilitate business licensing, and
facilitate MSEs and formal financial institutions in
an effort to reduce the difficulties of accessing
MSEs’ capital.
ACKNOWLEDGEMENTS
The author would like to thank to the
Directorate General for Strengthening Research and
Development of Ministry of Research, Technology
and Higher Education for the funding provided
through the MP3EI research grant in 2017.
REFERENCES
Blackburn, R.A., Hart, M. and Wainwright, T., 2013.
Small business performance: business, strategy and
owner-manager characteristics. Journal of small
business and enterprise development, 20(1), pp.8-27.
Directorate General of Plantation, 2015. Statistik
Perkebunan Indonesia Komoditas Kelapa Sawit 2013-
2015 (Plantation Statistics Indonesia Palm Oil
Commodities 2013-2015), Jakarta.
Gozali, I., 2011. Aplikasi Analisis Multivariate dengan
Program IBM SPSS 19 (Application of Multivariate
Analysis with IBM SPSS Program 19), Badan Penerbit
Universitas Diponegoro. Semarang, Edisi Kelima.
Hernandez-Carrion, C., Camarero-Izquierdo, C., and
Gutierrez-Cillan, J., 2017. Entrepreneurs' Social
Capital and the Economic Performance of Small
Businesses: the Moderating Role of Competitive
Intensity and Entrepreneurs' Experience. Strategic
Entrepreneurship Journal, 11(1), pp. 61-89.
Indonesian Central Bureau of Statistics, 2016. Economic
Census of 2016, Jakarta.
Indrawati, H., & Caska. 2015. Financing Models for sago
cake makers in supporting the acceleration of family
economic improvement. Mediterranean Journal of
Social Sciences, 6(6), pp. 310-318.
Ivanová, E., 2011. Interconnectivity of Factors of
competitiveness at the microeconomic and
macroeconomic levels in Slovakia. In Proceedings,
The 9th International Conference Economic Policy in
The European Union Member Countries, Dolní
Moravice: Czech Republic.
Jasra, J.M., Khan, M.A., Hunjra, A. I., Rehman, R.A.U.,
and Azam, R.I., 2011. Determinants of Business
Success of Small and Medium Enterprises.
International Journal of Business and Social Science,
2(20), pp. 274-280.
Lane, E.E.G.G.M.D., 2017. Rural entrepreneurs: what are
the best indicators of their success?. Journal of Small
Business and Enterprise Development, 24(2), pp. 1-26.
Lucky, E.OI., and Minai, M. S., 2011. The Conceptual
Framework of Entrepreneur and Self Management.
International Journal of Business and Social Science,
2(20), pp 180-185.
Lussier, S.H.R., 2016. Why Businesses Succeed or Fail:
A Study on Small Businesses in Pakistan. Journal of
Entrepreneurship in Emerging Economies, 8(1), pp.
82-100.
Pinho, J.C., and Sampaio de Sa, E., 2015. Personal
characteristics, business relationships and
entrepreneurial performance: Some empirical
evidence. Journal of Small Business and Enterprise
Development, 21(2), pp. 284-300.
Polo-Peña, A. I., Frías-Jamilena, D. M., and Rodríguez-
Molina, M. Á., 2012. Marketing practices in the
spanish rural tourism sector and their contribution to
business outcomes. Entrepreneurship and Regional
Development, 24(7-8), pp. 503-521.
Rao, S., 2014., Nurturing entrepreneurial women: Insights
from a developing country. Journal of
Entrepreneurship in Emerging Economies, 6(3), pp.
268– 297.
Ratten, V., 2014. Encouraging collaborative
entrepreneurship in developing countries: The current
challenges and a research agenda. Journal of
Entrepreneurship in Emerging Economies, 6(3), pp.
298–308.
Salavisa, I., Videia, P., and Santos, F., 2009.
Entrepreneurship and social networks in ITsectors: the
case of the software industry in Portugal. Journal of
Innovation Economics, 2(2) pp. 15-39.
Shibia, A.G., and Barako, D.G., 2017. Determinants of
micro and small enterprises growth in Kenya. Journal
of Small Business and Enterprise Development,
24(10), pp. 105-118.
Micro and Small Enterprises (MSEs): What are the Best Indicators of Their Performance?
313

ulHaq, M.A., Usman, M., Hussain, N., and Anjum, Z.,
2014. Entrepreneurial activity in China and Pakistan:
A GEM data evidence. Journal of Entrepreneurship in
Emerging Economies, 6(2), pp.179–193.
ICEEE 2017 - 2nd International Conference on Economic Education and Entrepreneurship
314