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THE DETERMINANTS OF SUCCESS OF MICRO AND
SMALL ENTERPRISES IN ADDIS ABABA
RAHEL BELETE (PhD) ANDADDIS KASSAHUN (PhD)
ABSTRACT
Micro and Small Enterprises (MSEs) are considered as a “seedbed” of entrepreneurship. Thus, this
study was conducted to identify the determinants of entrepreneurial success of MSEs in the manufacturing,
construction, urban agriculture, and trade and service sectors.
The study used primary data from interviews conducted on one hundred MSE operators and four
government officials in Addis Ababa and secondary data of Federal MSEDA‟s Bulletin 2014, the Federal
MSE Development agency database and Director 2014.
Through descriptive and quantities study, it intended to describe and verify determinants of MSEs
success. The hypothesis was that entrepreneurial success is significantly determined by three factors:
individual dimension, organization dimensions and external environmental. The study used interview guide
and Statistical Package for the Social Sciences (SPSS) for data organization and analyses using
descriptive, correlation and multiple linear regressions.
Based on the result of the study, MSE's success is determined by multi-dimensional factors of
individual, institutional and external nature. However, among the three determinants institutional factor
have strong predictor. In addition, the study also indicated the variation of success factors across the five
sectors. Hence, to ensure the success of MSEs the importance of sector based approach is one of the main
finding of this study.
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INTRODUCTION
Ethiopia with more than 88 million (CSA) inhabitants has one of the largest
populations in Sub Saharan Africa. In 2012/13 agriculture accounted for 42.9 percent of
GDP compared to 46.5 percent in 2009/10. The share of the industrial sector in GDP
increased to 12.4 percent in 2012/13 from 10.3 percent in 2009/10, while the service
sector accounted for 45.2 percent in 2012/13 compared to 44.1 percent in 2009/10.Thus
although the composition of the economy has changed in favor of industry and service
sectors over the last three years, the process need to be accelerated to bring about a
significant shift in the structure of the economy. Particularly to set the economy on a
rapid process of industrialization and structural transformation, the growth of the
industrial sector and particularly the manufacturing industry has to be accelerated even
further. This in turn entails extensively promoting investment in the industrial sector,
particularly in manufacturing, and enhancing productivity of agriculture so as to support
the process of industrialization and export development.
Before 1991, the country followed a socialistic command economic policy whereby
the state was a key player in the economy. As a result, private sector development was
severely hampered.In 1991, the current Ethiopian government introduced a market
economy, with a view to develop a vibrant private sector. Since 1992, following the
World Bank and IMF‟s Structural Adjustment Program (SAP), a series of reform
programs that are aimed at transforming the economy from a quais-communist command
structure to a market economy have been initiated and implemented. In recognition of the
significance of micro and small enterprise (MSEs), the government issued a National
Micro and Small Enterprises Strategy in 1997 and established theFederal Micro and
Small Enterprises Development Agency (MSEDA) in 1998. The country‟s industrial
policy in 2003 and the poverty reduction strategy in 2006 have singled out MSEs as
major instruments to create a productive and vibrant sector to reduce poverty. The role of
Micro and Small Enterprises (MSEs) has also been argued that the sector may serve as a
“seedbed” of entrepreneurship, with entrepreneurs graduating to run large industries
(McPherson, 1996). Such a seedbed might be especially important given the role of
entrepreneurship in economic development (Kilby,1971).
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There is no commonly agreed upon international definition of MSE‟s. Countries
use different definition in their identification of MSEs and use head count of full time
staff, annual turnover, total assets, net asset and paid capital either separately or together
to define the enterprises. According to the Micro and Small Enterprise Development
strategy of Ethiopia, the working definitions of MSEs are based on the size of capital,
number of people and the type of business. The sector encompasses both the industrial
and service sectors. The small industrial sector includes manufacturing, construction and
mining. It operates with 6-30 persons and/or with a paid up capital of total assets of Birr
100,000 and not exceeding Birr 1.5 million. The service sector on the other hand
comprises retailer, transport, hotel and tourism, ICT and maintenance. It operates with 6 -
30 persons or/and total asset, or a paid up capital of Birr 50,000 and not exceeding Birr
500,000.
Enterprise
level
Sector Hired labor Capital, Birr
Industry <5 <100,000
Micro Service <5 < 50,000
Industry 6-30 <1.5million
Small Service 6-30 <500,000
Source: FDRE, 2011 Micro and Small Enterprise Development Strategy,
provision framework and methods of Implementation (Approved) January 2011,
Addis Ababa, Ethiopia
The legal framework and development of MSEs dates back to the 1940s and
1960s. According to Teshome 1994, the proclamation No. 242/1966 provided tax relief,
access to land and buildings, public utilities and other facilitations of advisory and
administrative nature to the sector. The Communist regime proclamation No.76/1975,
restricted acquisition of private businesses to a single license and capital ceiling set at
Birr 300,000 for wholesale trade, Birr 200,000 for retail trade and 500,000 for industrial
establishments. By proclamation No. 124/1977, the Handicrafts and Small Scale
Industries Development Agency (HASIDA) was established. Proclamation No. 9/1989
the Small Scale Industry Development Special Decree and Special Degree on Investment
No.17/1990 are the additional two decrees the Derg declares to boost the sector.
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Proclamation of No. 41/1993 provides the establishments of Industry and Handicrafts
Bureaus in the Regional Governments replaced the HASIDA proclamation. Proclamation
No. 40/1996 decreed was issued for the establishment of Micro Financing Institution. The
National Micro and Small Enterprise (MSEs) strategy was issued in 1996/1997. Federal
Micro and Small Enterprises Development Agency (FMSEDA) and Regional Micro and
Small Scale Enterprise Development Agencies (RMSEDAs) were established by the
Council of Ministers of Ethiopia Regulations No.33/ 1998.
The first MSEs Development Strategy was designed in 1997. This strategy was
intended to create coherence with the other economic sectors and outline duties and
responsibilities of all the stakeholders at all level (from Federal to Kebele level). The
revised MSEs Development Strategy was designed in 2011 in order to integrate the
development of the sector with the country‟s 5 year (2003-2007 E.C) Growth and
Transformation Plan (GTP), hoped to bring about rapid economic growth and lift up the
country to middle income level. The MSEs Development was integrated in the GTP as
one of the pillars of the Industrial Development Plan and taken as one of the best tools to
implement the country‟s Industrial Development Strategy. According to revised strategy
MSEs are defined on the base of total capital and working labor engaged. The 2013,
Micro and Small Enterprise Development Strategies articulate the critical role of MSEs
as a forerunners in leading industrial development. The strategy‟s crucial mission is to
enable all responsible bodies, individually or jointly, execute their responsibility, replace
rent-seeking attitudes and practices in the sector with developmental thinking through
continuous education and trainings.
This research work has focused on studying the determinants of MSEs success in
Addis Ababa. In particular, it studied MSEs across sectors that aremanufacturing,
constriction, urban agriculture,trade, and service and try to understand the determinants
of success in each sector to give a better input to the right policy to achieve better results
from the respective sector. It sought to give answer to the general problem and try to see
the determinants of success in MSEs in Addis Ababa with particular attention with each
sectors of MSE.Specifically, the study sought answers to the following areas:First, it
answers how the characteristics of the entrepreneur in terms of personal, institutional and
environmental factors determine success. Secondly, it tries to giveanswer to what
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entrepreneurial and motivational factors play in each sector. Thirdly, it try to identify
success factors in terms of growth, capital, profitability, number of products and
employments and then identify which factor play most for each success.Finally, the
researcher reviewed the economic strategies and policies and suggested directions based
on the findings of the study.
RELENANT THEORIES AND RELATED LITERATURES
Various approaches have been taken to describing the emergence of the field of
entrepreneurship and the most influential contributions are: Knight's Risk Bearing
Theory. Knight (1964) first introduced the dimension of risk-taking as a central
characteristic of entrepreneurship. He adopts the theory of early economists such as
Richard Cantillon and J B Say, and adds the dimension of risk-taking. Marshall’s
Theory of Entrepreneurship.Marshall (1920) in his “Principles of Economics” held
land, labor, capital, and organization as the four factors of production, and considered
entrepreneurship as the driving factor that brings these four factors together.
Schumpeter’s Innovation Theory (1947): Schumpeter‟s innovation theory of
entrepreneurship holds an entrepreneur as one having three major characteristics:
innovation, foresight, and creativity. Kuratko and Hodgetts (Entrepreneurship:
Theory, Process, and Practice, 1998- 2007) is very relevant theory for the present study
in such a way that frames the independent variables of the study. The school of thought
analyzed six different schools of thought, whereby entrepreneurship thought emanates
from macro and micro views: The Macro View of Entrepreneurship: Presents a broad
array of factors that relate to success or failure in contemporary entrepreneurial ventures.
This array includes external processes that are sometimes beyond the control of the
individual entrepreneur, for they exhibit a strong external locus of control point of view.
These include Environmental School of Thought, Financial/Capital School of Thought,
Displacement School of Thought (which includes Political Displacement, Cultural
Displacement, Economic Displacement), Entrepreneurial Trait School of Thought
(People School), Venture Opportunity School of Thought, Strategic Formulation School
of Thought.
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With regard to MSEs, a number of theoretical models have been developed to
describe the growth of small businesses, which is based on a micro perspective. One set
of theoretical model focuses on the learning process (active or passive) and the other on
stochastic and deterministic approaches. In the passive learning model, a firm enters a
market without knowing its own profitability. In the active learning model, a firm
explores its economic environment actively and invests to enhance its growth under
competitive pressure from both within and outside the firm. According to this model,
owners or entrepreneurs could raise their efficiency through formal education and
training that increases their endowments. Entrepreneurs with higher formal education,
work experience and training would therefore be expected to grow faster.The other set of
theories include the 'stochastic' and' deterministic approaches'. The stochastic model (also
known as Gilbert‟s law) argues that all changes in size are due to chance. Thus, the size
and age of firms has no effect on the growth of small enterprises. The deterministic
approach assumes, on the contrary, that differences in the rates of growth across firms
depend on a set of observable industry and firm specific characteristics (Pier, 2002).
Both the Macro and Micro view of entrepreneurship are very relevant to the
present study. Through these theories the success determinants of MSEs both from
internal and external factors were analyzed and discussed. According to Morris &Kuratko
(2001),the degree of entrepreneurship is dependent on three dimensions, namely,
innovativeness; risk-taking; and pro-activeness. There are two distinct schools of
researchers in the field of entrepreneurial psychology. The more traditional group of
researchers have focused on the personality characteristics of the individual such as:
locus of control, risk taking, achievement motivation, problem solving style and
innovativeness, perception, and work values. The second group of researchers has taken a
social cognitive approach, looking at the relationship between an individual and his or her
environment. The relationship between the entrepreneur, personality characteristics,
values, and other dimensions helps explain why some become entrepreneurs and others
do not. This model has implications for entrepreneurial educators and policy makers.
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METHOD OF RESEARCH
This study is based on pragmatist worldview whereby the researcher is not
committed to any one system of philosophy and reality. According to Creswell 2007, this
applies to mixed methods research in that inquirers draw liberally from both quantitative
and qualitative assumptions when they engage in their research.The study used primary
data from interviews conducted on 100 MSEs in Addis Ababa, key informant interview
with government officials including MFI‟s and secondary data from the Federal MSE
Development Agency (Federal MSEDA's Bulletins 2014, MSEDA's database, and
MSEDA's Directory 2014). Simple descriptive analysis is used to generate results from
the data. Figure 2 shows that 100 entrepreneurs have been selected randomly from the
five sectors( 20 from manufacturing, 20 from Construction, 20 from urban agriculture, 20
from trade and 20 service ). In addition to the main MSEs operators, additional data has
been collected from the government officials responsible in the implementation and
execution of MSE and entrepreneurship development policy and strategy and regulatory
bodies. Figure 1 presents the schematic diagram on how the sampling procedure was
utilization.
Source population
Equally distributed to 5 sectors (20 to each sector)
Equally distributed to 10 sub cities
10 MSEs randomly selected from 10 sub cities from 5 sectors
Figure 1. Schematic Diagram of the Sampling Procedure
9,943 MSEs available in Addis
Ababa
SRS
100 MSEs
Service Urban -
Agriculture
Trade Construction Manufacturing
100 MSEs
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PRESENTATION, ANALYSIS AND INTERPRETATION OF DATA
The first part of the presentation describes the MSE characteristics in terms
ofindividual factors (personal factor, entrepreneurial motivation, and orientations)
followed by key institutional factors namely firm attributes, size of the firm, and age of
the firm, location and starting capital. Then external factorssuch as i.e. enabling business
environment consists infrastructure, licensing, taxation and access to business
development services and accessibility of micro financing and social network size and
network interaction presented. The second part of the presentation describes the level of
success of the MSEs considering profitability, capital growth and employee‟s growth
variables. The third part of the presentation present therelationships between MSEs
characteristics and their level of success in terms of profitability, capital growth and
employees growth by sector (manufacturing, construction, trade, service and urban
agriculture) and for all sectors.The last part of the presentation presents the key
informant interview findings on major obstacles and challenges the MSEs are facing for
expansion and to contribute their part in private sector development.
Part I: Demographic and Other Entrepreneurial Characteristics. Individual
characteristics of MSEs included in this study were the personal factors, the institutional
factors and the external factors.The personal factors included in this study are the
demographic profiles of the entrepreneurs namely: age, sex, educational attainment, and
years of experience, entrepreneurial orientation, entrepreneurial motivation, need for
Achievement, Risk Taking, Internal Locus of Control and Self-Efficacy by Sector.Age
wise, as shown in table 1, the majority of the study participants 45(45%) were in the age
group of 30-39 years followed by those less than 30 years 30(30%).Themedian age of the
study participants/operators was 35 years.
According to Staw (1991), at the start of any business, age is not a key factor; but,
with enough training and preparation, the earlier someone starts business the better. He
also noted that age is related to business success if it includes both sequential age and
entrepreneurial age.This means that the older an entrepreneur is, the more experience in
business s/he has. Age thus implies wide experience.
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Table 1
Distribution of MSEs Entrepreneursby Age
Sector
Age group
<30 30-39 40-49 >50 Total
f % f % F % f % F %
Trade 10 50 9 45 1 5 0 0 20 100 Manufacturing 4 20 10 50 5 25 1 5 20 100 Service 3 15 12 60 5 25 0 0 20 100 Construction 6 30 8 40 5 25 1 5 20 100 Urban
agriculture 7 35 6 30 4 20 3 15 20 100
Total 30 30 45 45 20 20 5 5 100 100 Minimum = 20 Max 70 Mean = 35.52 STD = 8.3
Other similar empirical study in the area of SMEs by Mohammed, (2012) found that the
majority of respondents, a total of 111 (49.4%) were aged between 31 to 40 years old,
23.6% each (21 each) were aged between 21 to 30 and 41 to 50 years old, 3.4% (8) were
above 50 years old, while no respondent is less than 20 years old.
Sex.As reflected in table 2 most of the MSEs are predominantly owned by men
(70%). When we look at the distribution of female owned micro and small enterprises by
sector, the majority (70%) of respondents in the trade sector was female followed by
service sector where 30% are females. On the other hand, construction (90%),
urbanagriculture (80%) and manufacturing (80%) sectors were owned by men.Other
related studies by Mohammed and Obeleagu (2014) using descriptive analysis showed
that, out of 89 MSE respondents, there were more male than female respondents. The
results show that 82% of the respondents are male and the remaining 18% are female.
(Fischer, 1992; Fischer et al., 1993; Kalleberg and Leicht, 1991) showed that the lesser
size of women-owned firms holds true regardless of whether size is measured by gross
revenues, number of employees, or profit levels Some evidence also shows that women-
owned firms grow less quickly than male-owned firms (Cliff, 1998). Cliff (1998) found
no differences between male and female entrepreneurs in their growth intentions.
However, Brush and Bird (1996) stated that firms owned or managed by males had more
sophisticated planning compared to female owned or managed businesses.
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Table 2
Distribution of MSEs Entrepreneurs by Sex
Sex
Sector Female Male Total
f % f % f %
Trade 14 70 6 30 20 100
Manufacturing 4 20 16 80 20 100
Service 6 30 14 70 20 100
Construction 2 10 18 90 20 100
Urban agriculture 4 20 16 80 20 100
Total 30 30 70 70 100 100
Other related studies by Mohammed and Obeleagu (2014) using descriptive
analysis showed that, out of 89 MSE respondents, there were more male than female
respondents. The results show that 82% of the respondents are male and the remaining
18% are female. (Fischer, 1992; Fischer et al., 1993; Kalleberg and Leicht, 1991) showed
that the lesser size of women-owned firms holds true regardless of whether size is
measured by gross revenues, number of employees, or profit levels Some evidence also
shows that women-owned firms grow less quickly than male-owned firms (Cliff, 1998).
Cliff (1998) found no differences between male and female entrepreneurs in their growth
intentions. However, Brush and Bird (1996) stated that firms owned or managed by
males had more sophisticated planning compared to female owned or managed
businesses.
Educational attainment. Reflected in table 3 is the distribution of the MSEs
entrepreneurs by educational attainment.Almost all 99(99%) of the operators attended
formal educationof which 27 (27%) and 20 (20%) had diploma and first degree
respectively.In this study, looking at education status by sector, construction and urban
agriculture sectors have higher level of education status as compared to the other sectors.
Other related studies[Kallerberg and Leicht (1991), Rowe et al., (1993); Masuo et al.,
(2001); Rose et al. (2006)] have stated that the success of a business depends on skills,
and training.
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Table 3
Distribution of MSEs Entrepreneurs by Educational Attainment
Educational attainment
Illiterate Grade 1-8
Grade 9-12
Diploma First
degree Masters
& above Total
f % f % F % f % f % f % f % Trade 1 5 4 20 3 15 11 55 1 5 0 0 20 100 Manufacturing
0 0 2 10 5 25 10 50 3 15 0 0 20 100
Service 0 0 1 5 6 30 9 45 3 15 1 5 20 100
Construction 0 0 1 5 3 15 10 50 6 30 0 0 20 100
Urban
agriculture 0 0 1 5 2 10 10 50 7 35 0 0 20 100
Total 1 1 9 9 19 19 50 50 20 20 1 1 100 100
Gebreeyesus (2009) found vocational training to have a strong effect on
innovation andthat firms owned by females and older entrepreneurs are less likely to get
involved in innovation.Minniti and Bygrave (2003) have found that people with more
education are not necessarily more entrepreneurial. This difference could be due to the
variation on the operational definition of„more education‟ and study setting as well as
time of the study.
Entrepreneurial Motivation.Entrepreneurial motivation is reflected in table 4
from the perspective of financial gain, employment creation and personal satisfaction.
About 97 (97%) of the entrepreneurial motivation is not financial gain. The disaggregated
review by sector indicated thatnone of the MSEs engaged in the trade sector, the service
sector and the urban agriculture relate to financial gain as the motivator.
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Table4
Distribution of MSEs Entrepreneurs by Entrepreneurial Motivation
Sector
Entrepreneurial Motivation
Financial Gain Employment
Creation Personal Satisfaction
No Yes No Yes No Yes
f % f % f % f % f % f % Trade 20 100 0 0 19 95 1 5 10 50 10 5 Manufacturing 19 95 1 5 6 30 14 70 19 95 1 5 Service 20 100 0 0 14 70 6 30 18 90 2 10 Construction 18 90 2 10 5 25 15 75 14 70 6 30 Urban
agriculture 20 100 0 0 10 50 10 50 19 95 1 5
Total 97 100 3 3 54 54 46 46 80 80 20 20
Only three entrepreneur‟s 2 from the construction sector and 1 from the
manufacturing sector indicated that their entrepreneurial motivation is financial gain.
Almost half 46(46%) of the principal respondent MSEs stated employment creation as
their motivator. The majority of the MSEs engaged in the construction sector and
manufacturing sector 70% (14/20),the construction 75% (15/20) and the urban agriculture
50% (10/20) have shown more inclination to this motivator.For those in trade sector
employment creation had very minimum influence as entrepreneurial motivation since
only 5% (1/20) identify the factor as motivation.As shown in Table 4, 20 (20%) MSEs
stated that personal satisfaction as their motivator. The disaggregated review by sector
indicated that in the trade sector, 10 out of 20 enterprises are in business due to personal
satisfaction, followed by 6 in theconstructionsector and 2 in the service sector.Therefore
despite the list of challenges that the MSEs present such as lack of working capital,
loss,un-competitiveness, illegal operation, infrastructure i.e. water, electricity supply,
bureaucratic hurdle and lack of profitability, high cost of rent for premises, lack of market
and profitthey choose toremain in business. Other studies conducted by Cooper (1985),
Green and Pryde (1989), Raman (2004) found that motivational factors such as
initiatives, third party assistance, encouragement by family and friends, skill and
economic conditions led to the success of the entrepreneurs.
Entrepreneurial Orientation.Reflected in table 5, is the distribution of the
MSEsentrepreneurs by weighted need for achievement, risk taking, internal locus of
control and self- efficacy by sector.The mean score for the „need for achievement‟ was
4.9 out of maximum 5 likert scale which showed that participants strongly supported the
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idea that “even if I have achieved success in my business, I want to become better”.
Service and construction sectors had the maximum need for achievement. The mean
score for „risk taking behavior‟ of the participants was 3.0 which indicated participants
were neutral in terms of taking risk related to their business. Urban agriculture sector
participants were relatively better in terms of taking risks compared to the other sectors as
shown in Table 5. The mean score for „internal locus of control‟ of the study participants
was 5 which indicatedthat almost all participants had high internal locus of
control.Service and construction sectors had the highest weighted score for internal locus
of control. Similarly themean weighted score for „self-efficacy‟ of the study
participantswas 4.4 which indicated that most participants agreed to the idea of being
self-efficacious in their business activities. The manufacturing sector (4.8) was found to
have the highest self-efficacy behavior followed by the construction sector(4.5). The
findings are in line with other similar studies. For example, the need for achievement was
found to be higher in small business students assessing their entrepreneurial orientation
(Sagie and Elizur, 1999). Entrepreneurial orientation predicted higher performance
among smaller firms as consistently found by different studies conducted since early
1990s: Brown (1996), Dess et al. (1997), Wilklund (1999), Lumpkin and Dess (2001),
Kreiser et al. (2002), and Wilklund and Shepherd (2003). Other related studies
conducted by Tanveer et al. (2013) stated that personal background of an entrepreneur
doesnot directly contribute to organizational success, rather it has great impact on
psychological characteristics, managerial and leadership capabilities. Opportunity
recognition and exploitation skills have strong positive impact on an organization‟s
success and performance.Brockhaus (1982, as cited in Sexton and Smilor, 1986) found
no significant statistical difference in the general risk patterns of a group of entrepreneurs
and a group of managers.
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Table 5
Distribution of MSEs Entrepreneurs by Weighted Need for Achievement, Risk
Taking, Internal Locus of Control and Self-Efficacy by Sector
Sector Weighted need for achievement
N Mean Median Minimum
value
Maximum
value
Manufacturing 20 4.8 5 4 5
Construction 20 4.7 5 4 5
Urban agriculture 20 4.6 4.7 3 5
Trade 20 4.3 4.3 3.7 5
Service 18 4.8 5 4.3 5
Total 98 4.7 4.9 3 5
Weighted risk taking Manufacturing 20 3 3 1.7 4
Construction 20 3 3 2.3 3.7
Urban agriculture 18 3.3 3.5 2.3 3.7
Trade 20 2.9 3 1.7 3.7
Service 19 3.5 3.3 2.3 5
Total 97 3.2 3.0 1.7 5
Weighted Internal locus of control
Manufacturing 20 4 4 2 5
Construction 20 4.2 5 3 5
Urban agriculture 20 4 4 2 5
Trade 18 4.4 4.5 3 5
Service 17 4.5 5 3 5
Total 95 4.2 5 2 5
Weighted self-efficacy
Manufacturing 20 3 3 1.7 4
Construction 20 3 3 2.3 3.7
Urban agriculture 18 3.3 3.5 2.3 3.7
Trade 20 2.9 3 1.7 3.7
Service 19 3.5 3.3 2.3 5
Total 97 3.2 3.0 1.7 5
In another study, Sexton and Smilor (1986) found that students studying to be
entrepreneurs scored higher on the variables of autonomy, change, dominance,
endurance, innovation and self-esteem. McCarthy's (2000) longitudinal study of Irish
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entrepreneurs suggests that although the personality trait view is relevant to the study of
risk, other variables are also relevant. Specifically, social learning and external factors
had an impact on the perception of risk. Overall, previous related studies indicate that
personality traits, motivation, individual competencies and personal background are
important factors for the success of micro andsmall enterprises (Baum et al., 2001; Shane
et al., 2003).
The institutional dimensions ofMSEsincludedinthisstudywerethefirm attributes
namely size of the firm, age of the firm, location and starting capital.
Table 6
Distribution of MSEsEntrepreneurs by Number of employees
Number of Employees
Sector <10 10-19 20-49 >50 Total
f % f % F % f % f %
Manufacturing 10 50 3 15 6 30 1 5 20 100
Construction 4 20 6 30 9 45 1 5 20 100
Urban agriculture 14 70 3 15 3 15 0 0 20 100
Trade 18 90 1 5 1 5 0 0 20 100
Service 15 75 2 10 3 15 0 0 20 100
Total 61 61 15 15 22 22 2 2 100 100
Size of the Firm.As reflected in table 6 the number of employees was used to express
size of the firm. The majority, 61 (61%) of micro and small enterprises had less than 10
employees followed by MSEs with20-49 employees. When disaggregated by sector,
thedata showed that construction had the highest number of employees i.e. greater than
10 (75%) followed by manufacturing (45%) which are the major employer
sectors.Specifically, the majority of MSEs in trade sector had less than 10 employees.
That is, only 2 MSEs in trade sector had more than 10 employees while 16 MSEs in
construction, 10 in manufacturing and 6 in urban agriculture sectors had more than 10
employees.The study finding was consistent with a study conducted by (Mead and
Liedholm, 1998); Bigsten and Gebreeyesus, 2007) which state that the most commonly
used measure of success for small firms is employment growth. The implicit assumption
is that growth in employment size (firm size) is associated with higher profits
(McPherson, 1996). For others, Coady and Tamvada (2008) found size and age have a
negative impact on firm growth in the majority of specifications
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Age of the Firm.As reflected in table 7, about 73% of the micro and small
enterprises had the age of less than 10 years,out of which 43% had the age of less than 2
years since establishment.When the data is disaggregated by sector, construction firms
had relatively longer years of age (40% were 10 years or more since established)
followed by firms in manufacturing (35%).According to Chandler (2009), the longer a
firm exists and the bigger it is and the more it signals that it can weather tough economic
conditions. Furthermore, by staying in business, a firm can signal that it does not adopt
opportunistic behavior.
Table 7
Distribution of MSEs Entrepreneurs by Age of the Firm
Age of the firm
Sector <2 2-5 6-9 >10 Total
f % F % F % f % f %
Manufacturing 4 20 9 45 4 20 3 15 20 100
Construction 6 30 6 30 6 30 2 10 20 100
Urban agriculture 11 55 5 25 1 5 3 15 20 100
Trade 16 80 1 5 0 0 3 15 20 100
Service 6 30 9 45 2 10 3 15 20 100
Total 43 43 30 30 13 13 14 14 100 100
Min = 0 Max = 11 Mean = 4.33STD =3.34
According to Klapper (2010), younger firms (less than 4 years) rely less on bank
financing and more on informal financing.Related studies conducted by Ngoc et al.,
(2009) found that it is often difficult and expensive for young SMEs to access bank
financing, due in large part to information asymmetry between the banks and firms.
Bougheas, Mizen and Yalcin (2005), pointed out that young firms are more failure prone
than older ones. Therefore, it is hypothesized that, there is a positive relationship between
the age of the firm and access to debt finance from commercial banks.
Business Location.The location of the firm on this study was reflected in table
8based on the proximity of the business location from its customer, raw materials the
enterprise require and competitors. Of the total 100 MSEs, 46% werenear business
customers while 35% werelocated near raw materials and 19% near their competitors.
Sector wise, 11 in construction and 12 in urban agriculturewere located near the raw
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materials they require while 10 in manufacturing and 15 in service werelocated near their
customers.
Table 8
Distribution of MSEs Entrepreneurs by Business Location
Sector
Business location Near to
customer Near to raw
material Near to
competitor Total
f % F % f % f %
Manufacturing 10 50 8 40 2 10 20 100
Construction 4 20 11 55 5 25 20 100
Urban agriculture 8 40 12 60 0 0 20 100
Trade 9 45 2 10 9 45 20 100
Service 15 75 2 10 3 15 20 100
T Total 46 46 35 35 19 19 100 100
Most of the MSEs in trade wereequally located near their customers and
competitors. Some of the respondents, especially, in manufacturing, trade and service
sectors complained that although their businesses were near their customers, the locations
and settings of the
buildings were not convenient for making business with their clients.
Start Up Capital. Reflected in table 9 is the distribution of MSEs entrepreneurs
by start-up capital.
Table 9
Distribution of MSEs Entrepreneurs by Start-up Capital
Sector
Startup capital (in 1000 ETB)
<10 10 – 99.999 100 – 499.99 Total
f % f % f % f %
Manufacturing 10 50 7 35 3 15 20 100
Construction 4 20 11 55 5 25 20 100
Urban agriculture 7 35 8 40 5 25 20 100
Trade 14 70 6 30 0 0 20 100 Service 11 55 8 40 1 5 20 100 Total 46 46 40 40 14 14 100 100 Min = 21 Max = 450,000 Mean = 37,676.71 STD = 63,087.45
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Out of 100 MSEs, 46 had starting capital of below 10,000 Ethiopian birr (ETB)
while 40 MSEs had a startingcapital between 10,000 and 99,999ETB. In short, 86 MSEs
had start-up capital of less than 100,000ETB and only 14 MSEs had a start-up capital
between 100,000 and 500,000ETB. There were not asingle MSE who had a start-up
capital above 500,000ETB.Looking at the data by sector, most of the MSEs in trade (14)
service (11) and manufacturing (10) had relatively lower (less than 10,000ETB) start-up
capital compared to those MSEs from construction (16) and urban agriculture (13)
whichhad more than 10,000ETB initial capital to start their business.Table 9shows that
total average start-up capital was37, 676.71 ETB. Construction and urban agriculture had
a relatively higher startup capital compared to other sectors. Other related studies, for
example, Kraut and Grambsch (1987);Kallerberg and Leicht (1991) have found that size
of investment and accesses to capital determine MSEs' success.
External EnvironmentFactor: These include the socio-economic, political,
technological factors along with the enabling environment.The external environment
included in this study are enabling business environment, licensing, taxation, access to
business development service, accessibility of micro financing, social networks i.e.
network size and network interaction and access to micro financing. For this EEA
presentation, we focus on some of the major enabling business environment variables.
Formality of the MSEs.Formality of the MSEs is seen from the fulfillment of
licensing and taxation requirements. As reflected in table 10, the distribution of MSEs
entrepreneurs by rating of licensing procedure. The MSEs in this study all operate
formally respecting the rules and the regulation of the country.
Almost all (94%) of the micro and small enterprises had certificate from
Municipality. This registration indicates their status and operation as formal sectors.
About 27% of the MSEs had also certificate from two levels that is from both Ministry of
Industry &Municipality. Among MSEs which have been raised to the next levels and
sampled in this study, 27% have received investment licenses which gives them the right
for expansion by acquiring investment lands, duty free import permits and long term
financial leverage through loans, but only few of them have got access to these rights.
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Most of them complained that they were required to pass through the standard
government bureaucracy and requirements to access investment lands and loans for their
investments.
Table 10
Distribution of MSEs Entrepreneurs by Rating of Licensing Procedure
This isan indication of the high level of dependency and lack of end-to-end
sustained MSEsgraduation or transition strategy tomedium and high enterprise levels.
Other countries‟ experienceswhich in the case of Malaysia is a four stage support
i.e.start-up, growth, expansion and maturity and in the case of Japanatthree stage support
i.e. the launching stage, strengthening stage and securing stage, This needs to be studied
further and adopted to address these issues in the Ethiopian context.This study found that
61(61%) of the respondents rated the licensing procedure as good and very good. The
result also shows that 62%of the MSEs‟ perception of no bias in the government
licensing procedure. The largest proportion of respondents from the urban agriculture
sector confirmed that there is bias in the system and that land ownership/entitlement and
related issues are cited the key challenges.
Taxation.As reflected in table 11,majority 83(83%) of the MSEs are paying tax
to the respected authorities.When we closely see the taxpaying status of these MSEs by
sector, those engaged in construction (100%) pay tax, followed by the manufacturing
sector (95%) and trade (90%). But only 9(45%) pay tax from those MSEs who are
engaged in the urban agriculture sector.MSEs registered as association are not currently
paying tax in spite of higher profit they earn since they have tax break status.The average
rate of tax corresponds to the yearly profit of the sector.
Sector Licensing procedure
V. Good Good Fair Poor Total
f % f % f % f % F %
Manufacturing 4 20 11 55 5 25 0 0 20 100
Construction 6 30 7 35 5 25 2 10 20 100
Urban agriculture 1 5 7 35 3 15 9 45 20 100
Trade 1 5 11 55 4 20 4 20 20 100
Service 3 15 10 50 6 30 1 5 20 100 Total 15 15 46 46 23 23 16 16 100 100
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Table 11
Distribution of MSEs by Tax Payment
Sector Pay tax currently
No Yes Total
f % f % f %
Manufacturing 1 5 19 95 20 100
Construction 0 0 20 100 20 100
Urban agriculture 11 55 9 45 20 100
Trade 2 10 18 90 20 100
Service 3 15 17 85 20 100 Total 17 17 83 83 100 100
Min = 0 Max = 380,000 Mean= 29,697 SD = 59,465
Looking in detail the construction sector pay the highest yearly average tax ETB
60,052 followed by the service sector ETB 53,700. The list taxpayer sector is the trade
sector ETB 1,322 followed by the urban agriculture sector ETB 1,561. There is a huge
disparity in the yearly average tax amount that the sectors pay. The total average yearly
tax for the MSEs in this study was ETB 29,697.
Access to Business Development Services (BDS).MSEs are receiving a number
of business development supports by the government. As reflected in table 12, 73(73%)
of MSEs have received at least one type of (Business Development Support) BDS.
Regarding the accessibility and frequency of getting BDS service, 13 (13%) got three
times support, 34 (34%) got two times support and 26 (26%) got one time support.
Table 12
Distribution of MSEs Entrepreneurs byAccess to Business Development Services
Frequency of getting BDS
f % Valid
Percent
Cumulative
Percent
No BDS 27 27.0 27.0 27.0
Took one type of BDS support 26 26.0 26.0 53.0
Took two types of BDS support 34 34.0 34.0 87.0
Took three types of BDS
support 13 13.0 13.0 100.0
Total 100 100.0 100.0
Regarding the benefit of the business development service, most of the study
participants (54%) mentioned thatthe BDS has helped themacquire marketing skill
followed by 27% who claimed that it has helped them acquire finance and 23% claimed
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that it has providedthem with acquiring better project ideas. It has been noted by the
responsible government officials that the training approach the government is using to
support MSEs isthrough Technical and Vocational Education and Training(TVET) and
which is an outcome based training approach. It starts by doing assessment to identify
gaps and design the training followed by finalizing the training through assessment to
confirm competence. However, this has not been applied in MSE trainings due to a
number of challenges i.e. relevance, meeting training need, quality of trainers and
training, shortage of resource, high staff turnover, lack of commitment of trainers and
trainees etc. Currently, BDS support is replaced by Industry Extension Support (IES) and
this has four basic supportareas: Kaizen, Technology, Training and Enterprise.Sector
wise, most of the respondents who got BDS service were from manufacturing (80%),
construction (75%) and trade sectors. Yet, there are enormous complains in the quality of
the training and the approached used.
Accessibility of Micro Financing.Micro finance is considered as a lifeline for
MSEs. Reflected in table 13, about 88% of MSEs obtained loan from credit and saving
institutions or other sources.From 88 micro and small enterprises that got loan, 39(44%)
said that the loan solved their financial constraint.
Table 13
Distribution of MSEs Entrepreneurs Accessibility of Micro financing
Obtained loan from credit and saving institutions or other sources
Sector No Yes Total
F % f % f %
Manufacturing 2 10 18 90 20 100
Construction 0 0 20 100 20 100
Urban agriculture 6 30 14 70 20 100
Trade 1 5 19 95 20 200
Service 3 15 17 85 20 100
Total 12 12 88 88 88 100
Other related studies Kinyua (2014) found that that access to finance was
significantly associated with profits (P<0.05). This implies that an increase in access to
finance results in an increase in profits of SMEs. Findings also indicate that macro
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environment was not significantly associated with profits (P> 0.05). This implies that an
increase in macro environment resulted not in profits of SMEs in the study area.From
those MSEs that got access and got loan from micro-finance institutes, most of them
mentioned that the loan they got were less than they requested to run their operations as
planned and yet 88%(50/57) acknowledged that the credit they got solved their financial
problem.According to key informant interviews with MFI, current beneficiaries have
reached up to 320,000 with a loan portfolio ofETB 1.9 billion outstanding loan as of Dec
31, 2014.Moving at the same speed with MSE formation, 100,000 job opportunitieshave
been created by MSEs and in the same period, only 18,000 got loan.
PART II Level of Success of the MSEs
The levels of success of the MSEs included in this study are profitability, capital growth
and employee‟s growth.
Profitability of MSEs.As reflected in table 14,about 50% of MSEs had yearly
average profit of more than 50,000 ETB. Out of these, 40% had registered yearly
average profit of more than 200,000 ETB.
Table 14
Distribution of MSEs Entrepreneurs by Profitability
Sector
Profitability (in 1000 ETB)
<10 10-
49.999 <50 50-
99.999
100-
200
>200
Total
f % f % F % f %
f % f % f %
Trade 18 90 1 5 19 95 0 0 1 5 0 0 20 100
Manufacturing 0 0 1 6 1 6 3 18 6 35 7 41 17 85
Service 3 16 4 21 7 37 4 21 4 21 4 21 19 95
Contraction 0 0 0 0 0 0 4 24 4 24 9 53 17 85 Urban
agriculture 5 6 7 39 12 67 3 17 3 17 0 0 18 90
Total 26 29 13 14 39 43 14 15 18 20 20 22 91 91 Minimum =200 Max = 1,300,000 Mean = 165,418 STD= 224,624
From those which enjoyed more than 200,000 ETB annualprofits, 80% were in
the manufacturing and construction sectors (45% construction and 35% manufacturing).
Out of the total respondents, 39 MSEs earned a yearly average profit of less than
50,000ETB. Of these 26 had less than 10, 000ETB yearly profit while 13 had between10,
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000ETB and 50,000 ETB yearly average profits. There were no MSEs from trade and
urban agriculture sectors in the range of average profit above 200,000ETB. Almost all
90% (18/20) of the MSEs in the trade sector had yearly average profit of less than 10,000
ETB.From those MSEs which registered more than200, 000 ETB annual profits, 75%
were male owned ones and 69% of the owners had completed at least 12grade.
The overall average yearly profit was found to be 165,418 ETB. Construction had
the highest average yearly profit of 389,000ETB followed by manufacturing with
240,765ETB and service with 134,989ETB. MSEs in the trade sector had the lowest
yearly average profit of 9,133ETB followed by urban agriculture 52,222ETB.
Capital growth. Reflected in table 15, is the distribution of MSEs entrepreneurs
by capital growth.
Table 15
Distribution of MSEs Entrepreneurs by capital growth
Sector
Capital growth (in 1000 ETB)
<10 10-49.999 <50 50-99.999 100-
199.999 >200 Total
f % f % F % f % f % f % f %
Trade 0 0 0 0 0 0 7 35 3 15 10 50 20 100
Manufacturing 0 0 0 0 0 0 0 0 1 5 19 95 20 100
Service 2 10 2 10 4 20 3 15 0 0 13 65 20 100
Contraction 0 0 1 5 1 5 0 0 0 0 19 95 20 100 Urban
agriculture 1 5 2 10 3 15 1 5 2 10 14 70 20 100
Total 3 3 5 5 8 8 11 11 6 6 75 75 100 100
Of the total 100 respondents, only 3 had a capital growth of less than 10%. About
92% of the total respondent had more than 50% capital growth during their operations.
Of these 92, 75 MSEs achieved more than 200% capital growth. Sector wise, those in
manufacturing (19) and construction (19) sectorsachieved more than 200% growth in
capital whereas only 10 from trade, 13 from service and 14 from urban agriculture
showed a capital growth of more than 200%. High firm-growth is rarely the prerequisite
of high profitability (Markman&Gartner, 2002; Davidsson et al., 2009). In addition, high-
growth is multidimensional and research has found difficulty in conceptualizing and
measuring it (Venkataraman&Ramanujam, 1986; Weinzimmer et al., 1998). A deeper
look of the present study data by sexalong with current capital growth indicates that from
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those MSEs registered with more than 1 million capital, 82% were maleowned. Similarly,
from those MSE owners that registered capital between 500,000and 1 million ETB, 89%
were male owned. The data also showed that male owned MSEs had 1.6 times higher
capital growth compared to those owned by females. Of the total 100 respondents, 48
MSEs had more than 500,000ETB current capital. From 40 MSEs that had current capital
above 1million ETB, females run only 7 MSEs. There was less variation in number of
female and male led MSEs with current capital less than 500,000ETB (22 verse 28)
compared to the variation above 500,000ETB range which is 8 female led verse 40 male
led MSEs.
The finding shows that of the total MSEs, 92 (92%) showed more than 50%
capital growth since their establishment out of which 75 MSEs showed more than 200%
growth in their capital while 17 MSEs showed between 100-200% capital growth and/or
change in capital.
Growth in Number of Employees.Reflected in table 16, is the distribution of
MSEs entrepreneurs by growth in number of employees.
Table 16
Distribution of MSEs Entrepreneurs by growth in number of employees
Sector
Mean number of employees
% change in
number of
employees
Number of
employees during
start up
Current number of
employees
Manufacturing 8.40 20.4 58.82 Construction 8.55 30.4 72.77 Urban agriculture 4.04 10.7 62.15 Trade 2.5 3.45 27.54 Service 6.65 20.2 67.08 Mean 6.03 17.23 11.2
The average total number of employees during the startup of the MSEs was 6.03
but currently on average MSEs had 17.23employees.The average change in number of
employees was 11.2 or 113% (11.42/6.03). Sector wise, construction sector had the
highest change in number of employees (22.85) followed by service and manufacturing
sectors. On the other hand, trade sector showed anominal growth.The study finding was
consistent with a study conducted by (Mead and Liedholm, 1998); Bigsten and
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Gebreeyesus, 2007) which state that the most commonly used measure of success for
small firms is employment growth. The implicit assumption is that growth in
employment size is associated with higher profits (McPherson, 1996).
PART III: Relationships between MSEs characteristics and their level of success
factors affecting micro and small enterprises’ success
The summary study finding shows that individual, organizational and external
factor have different level of significant disaggregate and analyzed by sector as reflected
in table 17.
For the trade sector sex, education status, business location, current capital, access
to telephone shows a very strong significant for average yearly profit while for capital
growth age in years, year of experience and weighted self- efficacy showed significant
relation. For the manufacturing sector number of employees showed significant relation
with average profit. The capital growth for the service sector shows significant with
number of employees. For the construction sector years of experience showed significant
relation with capital growth. For the urban agriculture sector current capital showed
significant relation with profitability. In accordance to this study, many empirical studies
reveal that microenterprise success varies across sectors (e.g., Liedholm and Mead, 1998;
McPherson, 1996; Gebreeyesus, 2009). For example, Liedholm (2002) found, for
selected African countries (Botswana, Kenya, Lesotho, Malawi, Swaziland, and
Zimbabwe) that manufacturing and service sector performed significantly better (higher
growth rate) compared to trading sector. This could be because enterprises in different
sectors face different demands and varying cost structures (Liedholm and Mead 1998).
However, some empirical studies (e.g. McPherson, 1995) indicate that country context
matters if one wants to know which sector is characterized by a higher growth rate and
caution against pooling countries and conducting an aggregate analysis.Other related
studies by Capelleras and Robetino (2008) showed that growth is a complex and
multidimensional phenomenon and cannot be adequately explained from a single
perspective across sectors.
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Table 17
Summary of Multiple Linear Regression of Profitability, Capital growth and
Employees Growth on Characteristics of MSEs in Sector
Independent
variables
Profitability Capital growth Employment growth
T M C S UA T M C S
U
A T M S C UA
Sex .245*
.358
*
Age in years
Educational
status .594* 2.678**
Years of
experience
-
.690**
1.210* .793*
Success_
employment
Success_
Satisfaction .452*
Weighted self-
efficacy
.442
*
.-
742**
number of
employees .193**
1.294*
1.054*
-.529**
Business place
location -.421*
-
.502**
Current capital 1.272*
1.131*
1.635**
.838**
1.090**
Accessibility
_telephone -.471*
.598
**
Amount of tax
per year
-
.540
**
Network size -
.534*
*
-
1.985
**
-
.568
**
.366*
*
*significant at 0.05 level (2-tailed) **boarder line significance at 0.05 level (2 –tailed)
T -trade sector
M -manufacturing sector
C -construction sector
S -service sector
UA -urban agriculture
The overall regression finding shows that the success of MSEs are determined by
multidimensional factors of the individual, institutional and external factors. However,
among the three determinants of success the institutional factors have strong significant
effect on the success of MSEs.This finding is consistent with other related studies, for
example, Zhou and Gerrit, 2009 found that organizational determinants have the most
influence on firm growth.In addition, the study also indicated the variation of success
factors across the five sectors. Hence, in designing appropriate strategiesthat is to
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ensurethe success of MSEs, the importance of sector wise approach can be proposed.
Other related research across a wide spectrum of units of observation, spanning the
establishment, the enterprise, the industry, the region, and the countryhave verified the
positive and statistically robust link between entrepreneurship and economic growth and
a lack of entrepreneurship incurring a cost in terms of forgone economic growth
(Audretsch and Thurik, 2000; Audretsch, 2002).
KEY FINDINGS OF THE STUDY
In the socio-demographic aspect of the MSEs, the study shows more than two
third of the micro and small enterprises operating in Addis Ababa were found to be male
owned. Three forth of the study participants had age less than 40 years and the average
age of the study participants/operators were 35 years. Almost all of the operators attended
formal education and more than half of them had diploma and above.
Concerning entrepreneurial motivation, about three fourth of the study
participants‟ pursued and continued operation after starting business which implied that
they were persistent with their initial business and had strong motivation for survival. For
a quarter of them who quitted at least once after starting their business the common
reasons were: lack of working capital, loss and un-competitiveness, operating illegally,
seeking better opportunity, stiff competition,lack of infrastructure i.e. water, electricity
supply, bureaucratic condition, disagreement among members, high cost of renting
premises and lack of market and profit. A quarter of the respondents had intentions to
switch to other business and sectors. Better market opportunity, perception of better
government support, better sustainable future and better income were the reasons
mentioned to switch to other business.
With respect to the MSE's Entrepreneurial orientations/skills, the finding
shows that the need for achievement was high which participants strongly supported the
idea that “even if I have achieved success in my business, I want to become better”.
Service and construction sectors had the maximum need for achievement. However, the
risk taking behavior of the participants was relatively low which indicated participants
were neutral in terms of taking risk related to their business. In addition, the internal
locus of control of the study participants was maximum which indicated that almost all
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participants had high internal locus of control.Considering the institutional factors of the
MSEs, for example, year of operation or the age of the firms, about the majority of the
micro and small enterprises had the age of less than 10 years. Construction and
manufacturing had relatively longer years of age compared to others. Considering
business location, half of the MSEs were near to business customers while one- third of
them werelocated near to raw materials. However, some of the buildings constructed by
the government as working premises and/or business centers for the MSEs were not well
thought, that is, neither near to raw materials nor convenient to the business customers
given the existing set ups and access to the customers. As a result, in some of the
business centers though they were occupied they were not actively operational.
Regarding the starting capital and source, two-third of the enterprises used their
personal saving as a startup capital while the rest got access to loan from MFIs. Nearly
half of the MSEs had a start- up capital of less than 10,000 birr. Trade, Service and
manufacturing were the sectors with relatively lower start- up capital. Considering the
current capital, about half of the small and micro enterprises registered over 1 million of
which more than three fourth of them have registered over one million birr capital. More
than three fourth of micro and small enterprises engaged in construction and
manufacturing sectors respectively had registered more than 1 million birr capital. In
summary, the average startup capital of 37,397 ETB has increased to average current
capital of 917,451ETB which is a tremendous growth in capital. The growth was very
significant in construction and manufacturing sectors in particular. The study also showed
that male owned MSEs had 1.6 times higher capital growth compared to female owned
ones. Regarding the formality of MSEs, almost all of the small and medium enterprises
had certificate from Municipality registration which shows that they all are formal
sectors. However, there were many of the graduates MSEs who have registered with
trade and industry as well as investment licensing bodies. With regards to tax, more than
three fourth of MSEs are paying tax to the respected authorities.
Construction,manufacturing and trade sectors had better record of paying government
taxes. It was found out three fourth of MSEs have received at least one type of
business development service (BDS) form the government and most of the study
participants mentioned the development service helped them to acquire better marketing
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skills, get finance, access working premises and to generate better project ideas. Most
respondents feel that there is a difference in supply of institutional support between tax
payers and non-tax payers. In addition, it was found out that half of the MSEs benefited
from micro- finance institutions and almost all acknowledged that the credit they got
solved their immediate financial problems.
Concerning the social network of MSEs, the majority had a network number
between 1 and 10 and when it comes to the frequency of interaction of MSEs within their
social networks, half of the MSEs do meet weekly or monthly. More than half of the
sampled respondents confirmed that they cooperate with otherMSEs. A similar
percentage of sampled respondents mentioned that there is mutual trust and helping each
other among MSEs. However, 67% of the sample respondents mentioned they didn‟t get
any skill, innovation and new research product from higher firms. Only 28% of the
sample respondents have mentioned having inter-firm cooperation with other business
firms and also only 8% of the MSEs are members of Addis Ababa Chamber of
Commerce and Sectorial Association (AACCSA). These are an indication of MSEsweak
interaction with other business and commerce association.
With regards to growth pattern of MSEs, almost all indicated that their enterprise
is showing growth. Almost two third of the MSEs reported that the success or growth
came from personal and institutional factors. It was found that, three fourth of MSEs
achieved more than 200% capital growth. Manufacturing and construction sectors
achieved more than two fold growth in capital. The data showed that male led ones and
MSEs run by educated owner had better capital growth. Moreover, theaverage yearly
profit was found to be 158,363 Birr. Construction had the highest average yearly profit of
389,000 Birr followed by manufacturing with 240,795 birr and service with
134,989birr.The finding alsoshows that one third of the MSEs have sufficient current
capital which warrant to get investment license and plan for long term expansion in their
business. This shows that as more MSEs pass their growth and entered their maturity
stage, it became very difficult to realize their investment dreams independently by
competing with others in the broader market.
The key informant interview results found that, lack of working premises, access
to working capital/finance, lack of market information and linkages, lack of machinery
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and lease, lack of technical and managerial skills, lack of skill based trainings, lack of
credit facility, lack of show rooms for their products and lack of government follow up &
support were mentioned as constraints of MSEs for expansion in Addis Ababa. Similarly,
the three major assistances they need from the government were: access to working
premises, working capital /finance, and support in market information and linkages.
KEY CONCLSUION AND RECOMMENDATIONS
Given the above key findings, challenges and opportunities, the researcher
recommends
1. It seems that there are few female owned MSEs in Addis Ababa and in addition,
majority of female tend to engaged on those sectors with less growth and turnover.
Therefore, the MSE Development Agency needs to design strategies to improve
female participation and make them policy beneficiaries.
2. A quarter of MSEs quitted at least once after starting business.The interruption might
also affect the growth and success of the enterprise.Therefore, further explorations of
the reasons need to be worked out and addressed to promote further entrance to the
sector.
3. The risk taking behavior of the participants was relatively low and that needs to be
improved through training and other means to make them effective and successful
entrepreneurs.
4. Business location areas of MSEs need to be close to where it maximizes the success
of the MSEs and should not be dictated by availability of space. Some of the
buildings constructed by the government as working premises and/or business centers
for the MSEs were not well thought.
5. Majority of MSEs are formal and do pay taxes. This needs to be further encouraged
and supported by concerned authority. However, there are some MSEs who are
organized as associations and getting tax relief privilege even if they earn huge profits
which need closer government monitoring and follow ups to take appropriate policy
measures.
6. Almost all MSEs were profitable and have shown growth. However, there were
variations across sectors that need deeper assessment and documenting the success
factors and sharing with the other ones. It was apparent that external factor
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(government supports in particular) have played vital role for the success of MSEs in
the manufacturing and construction sectors along personal and institutional factors
compared to the other sectors. Therefore, though manufacturing and construction
sectors are among the priority sectors in the government strategies, it is important to
consider multidimensional success factors for MSEs and bring balanced growth when
designing further the MSE development strategies in the GTP II phase.
7. The diversity, level of growth and the associated challenges and opportunity in the
MSEs may warrant for upgrading the Federal MSE Development Agency to Ministry
level in Ethiopia. Further study needs to be conducted covering all the regions with
more samples to get strategic information to make such decision. In addition, other
country experience such as India might help further in the design of the structure and
support system.
8. Education were correlated with growth and profit, hence it should be taken as success
factor and improved going forward through formal and non –formal education such as
knowledge and skill based training, continues education access.
9. Most of the MSEs have accesses and benefited from the available Business
Development Services(BDS). However, the government needs to expand and
strengthen the type and quality BDS it provides to the MSEs by making it more need
based.
10. It has been apparent that the MSEDA led periodic bazaars have helped the MSEs a
lot. Most of the MSEs have confirmed that they got the highest level of promotion,
marketing, sales and returns when they got the opportunity to participate in Bazzaars.
Therefore, it is one of the key areas for the government to put high investment to
avail sufficient spaces in the various city center to construct modern business centers
for the MSE's products.
11. The finding shows that one third of the MSEs investment licenses and plan for long
term expansion in their business. But only few of them have materialized their
investment dreams to acquire lands and loans for investment. Therefore, the
government needs to make a critical review of the criteria for MSEs transition process
including objective accounting of their assets and financial resources when granting
investment licenses.
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12. With respect to social interaction most of the MSEs lacks inter firm cooperation,
interaction with higher firms, membership with other professional and business
associations which is to get additional business development support including
technical skills, new research products or innovation, market linkage and business
information services. For the MSEs to further flourish both government and non-
government stakeholders need to work together to boost MSEsgrowth and
development. The interaction with broader private sector will enhance the MSEs
competitiveness and easy integration after graduation.
13. According to the government strategy and policy direction, all MSEs were expected
to raise their initial startup capital from their own source (personal savings, family
and related sources) to minimize dependency on the government system. The study
finding revealed that 67% of the sampled respondents used their personal saving as a
startup capital while 25% got access to loan from MFIs for startup. More has to be
done by the government and non government actors to engage those new entrants to
the MSEs in business that do not require initial capital in order to create their saving.
Alternatively, the government and/or MFI need to strengthen and diversify credit
guarantee system.
In nutshell, both the personal, institutional and external factors have
contributed to the success of the MSEs in Addis Ababa. Specifically, in the
manufacturing and construction sectors, which are the key priority sectors of the
government strategy, external factors (government supports) played a pivotal role for the
sectors success. Hence, it is important to see the multidimensional factors in designing
the MSE's strategy in the GTP II. Since the MSEs strategy also state balanced support to
MSEs attention needs to be given for the other sectors to bring diverse growth.
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