Analysis of Performance Determinants in Micro-Enterprises. The Case of Dodola District, Oromia Region

Master's Thesis, 2012

90 Pages, Grade: A


Table of Contents






1.1. Background of the Study
1.2. Statement of the Problem
1.3. General Objective of the Study
1.4. Specific Objectives of the Study
1.5. Hypothesis
1.6. Significance of the Study
1.7. Delimitation of the Study
1.8. Limitation of the Study
1.9. Organization of the Study

2.1. Theoretical Literature
2.2. Conceptual Framework
2.3. Definition and Concept of Micro and Small Enterprises
2.4. Empirical Literature
2.4.1. Personal attributes
2.4.2. Demographic characteristics
2.4.3. Socio-cultural variables
2.4.4. Business Characteristics of the Enterprise
2.4.5. Infrastructure
2.4.6. Business Development Services
2.4.7. Legal and regulatory environment
2.4.8. Access to finance
2.4.9. Lack of Linkage or Business Cooperation amongst Enterprises
2.4.10. Access to market
2.5. Micro-enterprises in Ethiopia

3.1. Description of the study area
3.2. Research Design
3.3. Sample Size Determination
3.4. Sampling Methods
3.5. Methods of Data collection
3.6. Data analysis techniques
3.6.1. Model specification
3.7. Description of Variables
3.7.1. Independent variables
3.7.2. Dependent variables

4.1. Demographic Information of respondents
4.2. Basic Characteristics of the Micro-enterprises
4.3. Source of initial capital
4.4. Characteristics of micro-enterprises in Dodola town
4.5. Reason for starting business
4.6. Financial Management
4.7. Use of Business Development Services
4.8. Performance of micro-enterprises
4.9. Socio-economic characteristics of micro-entrepreneurs
4.12. Multinomial logistic regression results of annual profit and selected explanatory variables
4.13. Regression results of employment growth and selected explanatory variables
4.2. Discussion

5.1. Summary and conclusion
5.2 Recommendation




Table 2.1.Classification of enterprises by paid up capital and number of employees

Table 2.2. The new definitions of micro and small enterprises

Table 3.1. Sample size taken from the five strata

Table 4.1.Percentage distribution of demographic characteristics of micro-entrepreneurs

Table 4.2. Percentage distribution of key characteristics of micro-enterprises

Table 4.3. Percentage distribution of sources of start-up capital for micro-enterprises

Table 4.4. Descriptive results of characteristics of micro-enterprises during and after establishment

Table 4.5. Results of paired sample t-test for comparing business characteristics of micro enterprise during establishment and at the time of the survey

Table 4.6. Percentage distribution of motives for starting micro-enterprises

Table 4.7. Percentage results of major business characteristics of micro-enterprises

Table 4.8. Percentage results of use of Business Development Services (BDS) among micro- enterprise

Table 4.9. Percentage results of performance indicators among micro-entrepreneurs

Table 4.10.Descriptive results of income and expenditures of micro-enterprise operators

Table 4.11. Results of paired sample t-test for comparing income and expenditure on different components before and after starting micro-enterprise business

Table 4.12.Chi-square results of association between average annual profit and some explanatory variables

Table 4.13.Chi-square analysis for employment growth and selected factors

Table 4.14. Regression results of average annual profit and selected explanatory variables

Table 4.15. Regression results of employment growth and selected explanatory variables


Figure 2.1. Conceptual framework

Figure 3.1 Map of the study area


First and foremost, may praise be to the almighty God who gave me hope at times when I could not see even a glimmer of hope and for being a source of spiritual strength during times of sorrow and despair There are many people who made this study possible. Had there not been the support and inspiration of such generous people around me, the completion of this study would have been unthinkable. It is very difficult to mention all of them in this short document. However, I can mention just a few. Likewise, I would like to extend my heartfelt gratitude to my advisor, A. Joseph (Ph.D), for he devoted his precious time to read through the paper and made valuable advice and constructive comments. My appreciation also goes to Mr. Cheru Atsmegiorgis, lecturer of statistics at the University, for his unreserved support and guidance. I thank him for sharing his valuable time and giving me priceless expert opinion

My deepest gratitude also goes to my dearest wife, Mrs. Meklit Tsegaye, whose unconditional and soothing care throughout the study has always been my source of strength and inspiration. I am also delighted to thank my father, Mr. Habte Melkamu. This endeavor would not be successful without his encouragement. He has always been there for me whenever I need him. His fatherly care keeps me going and his love that never fails empowers me all the time. It is also a pleasure to pay tribute to the participants of the study who were keen and interested to provide me with the required information. Last but not least, I am grateful to all my friends and colleagues who had always been there when I was really in need

I thank you all!

Alemayehu Habte Melkamu


May the dedication of this paper be to my baby boy whom my wife and I longed to see the most but unfortunately lost we will remember you always!!


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Nowadays, the contribution of micro-enterprises in employment creation, poverty reduction and hence economic growth is getting widespread acknowledgement. However, their performance is usually constrained by various factors. Thus, this research is basically aimed at investigating key determinants of performance among micro-enterprise businesses in Dodola town of Oromia region. It examines the extent to which performance of micro-enterprises is associated with characteristics of the owner and business constraints. To this end, primary data were gathered using interview schedule from a sample of 112 micro-enterprises selected using stratified random sampling. Besides, two Focus Group Discussions were held with fourteen randomly selected micro-entrepreneurs. To further triangulate the data Key informant interviews were held with three MSE office heads. Then after primary data was analyzed using both descriptive and inferential statistics. Characteristics of the enterprises and their entrepreneurs were analyzed using percentage, mean, median and standard deviation. On the other hand, Pearson ’ s chi-square(x2 ), paired sample t-test and multinomial logistic regression were used to make inferences about the subject under investigation. In this study, performance of micro-enterprises was measured in terms of two main indicators namely profit and employment growth. The results of paired t-test indicated statistically significant mean difference in socio-economic status of entrepreneurs before and after starting micro-enterprise business. The multinomial logistic regression analysis revealed that education, experience, location and access to formal credit source are significant predictors of profit growth. However, only education was found as a significant predictor of employment growth.

Key Words: Micro-enterprise; Performance; Multinomial Logistic Regression; Performance Determinants.


1.1. Background of the Study

Micro-enterprises are integral parts of developing economies. In South East Asian countries of Indonesia, Philippines and Thailand, for instance, they account for 95.6%, 88.4% and 79.4 % of the total firms (Harvie, 2004). Micro-enterprises, defined as firms employing one to nine workers including the owner (ILO, 2003) , are huge sources of employment and income in urban areas of developing countries. It is increasingly recognized that these enterprises contribute substantially to job creation and poverty alleviation. The 2005 World Development Report suggests that creating sustainable jobs and opportunities for micro-entrepreneurs are the key corridors out of poverty for the poor (World Bank, 2004). Micro-enterprises contribute to the reduction of poverty and vulnerability of the poor particularly women and unskilled labor through enabling them to break the vicious circle of poverty and also enabling them to enhance self empowerment, and economic self-sufficiency. They make possible to the poor to enhance their income, build up assets, and enter into mainstream economy. These firms contribute to innovations, jobs and economic growth. Given that they mostly use local resources and expertise, they serve as a means of developing indigenous entrepreneurship which is indeed necessary for sustained industrialization (Fasika and Daniel, 1999 cited in Mulat et al., 2006).

Different studies such as that of Gomez (2008) revealed that micro-enterprises face challenges and most enterprises that start small subsequently remain small. About 5% to 20% of micro- enterprises die each year and a similar amount are born each year (Harvie, 2004). Only small numbers of such firms ever grow to small enterprises. About 75% of new enterprises do not survive the first two years and of those which survive, only 20% grow at all (Gomez, 2008). The challenges of micro-enterprises in developing countries are even greater as compared to the developed countries. In Kenya, for instance, past statistics indicated that three out of five businesses fail within the first few months of operation (Kenya National Bureau of Statistics, 2007 cited in Bowen et al, 2009). Inadequate credit, lack of raw materials, sluggish demand, insufficient working space and infrastructural services are among the major bottlenecks (Siebel, 1996).

In Ethiopia the micro-enterprises, along with small firms, are employers of last resort holding 78% of the total urban economically active population compared to 62% for Africa as a whole (ILO, 1995/97 cited in Michael, 2006). According to the Ethiopian Central Statistical Authority (2004), almost 50% of all new jobs created in Ethiopia are attributable to small enterprises. The majority of firms in Ethiopia are micro and small. According to Aregash (2005), they account for 98% of all business firms. The micro-enterprise manufacturing sector alone absorbed 1.3 million persons (CSA, 2003). Employment in the informal micro-enterprises is growing much faster than employment in the formal sector accounting for 71% of urban employment by 2005 (World Bank, 2009). As a more recent study confirmed, micro-enterprises account for 97% of all manufacturing firms and for 19% of the gross value of production in the sector (Desta, 2010). Thus, formalized medium and large firms absorb only a very small share of the annual increase in the Ethiopian workforce, and the majority of new entrants to the labor market are forced to engage in own-account work (Altenburg, 2010).

The population of Ethiopia, according to 2007 census, was 73,918,505 (FDRE Population Census Commission, 2008). The same year, 39% of the population was estimated to live below the poverty line of US $ 1.25 a day (Altenburg, 2010). Besides, the labor force of the country is projected to reach 81.9 million in 2030, growing with 2.4% per annum (Mulat et al. 2006). Similarly, urban unemployment rate in 2005 was 21% with an escalating urban labor supply at a sustained annual pace of 3.5% (World Bank, 2007). The same report identified signs revealing a rising incidence of poverty among household heads involved in non agricultural activities in urban areas. Oromia region holds a total population of 27,158,471; taking 36.7% of the population in Ethiopia (FDRE Population Census Commission, 2008). However, the performance of the micro-enterprises is yet below expectation and only few firms graduate to the next level, while most of them never grow at all. Many operators hunt for a narrow market, creating no incentive for business expansion. Furthermore, limited access to credit; lack of premises; lack of business skills; lack of infrastructure; limited entrepreneurial orientation and the like affected the performance of these enterprises.

1.2. Statement of the Problem

Micro-enterprises are major sources of employment and income for the poor in Ethiopia. They account for 99.6% of employment and 94.7% of gross value of production and 95.1% of the value added (CSA, 1997 cited in HCLEP, 2006). They also supply goods and services at an affordable price which directly benefits the lower sect of the society. In spite of these promising contributions; however, it is recognized that micro-enterprises face unique problems which affect their growth and profitability and hence diminish their ability to contribute successfully to sustainable development. Despite the huge number of people earning their livelihood from the sector, the enterprises have been performing below capacity and their growth has been inhibited by numerous factors (Mulat et al., 2006). Boosting their contribution, hence, hinges on identifying the fundamental constraints and targeting the potentially successful entrepreneurs. An examination of the characteristics of the entrepreneurs and enterprises with high potential to survive and grow is therefore essential (Mulu, 2007). On the other hand, the rate of unemployment in urban areas of Ethiopia in 2010 was 18.9% (CSA, 2011). In Oromia region, according to a 2004 survey, 41.3% of the working population is engaged in the informal sector while the unemployment rate was 16 % (CSA, 2011). This considerable rate of unemployment and potential role of micro-enterprises to avert the problem accentuate the importance of studying determinants of micro-enterprises’ performance. In addition, the relatively scant information about enterprises found in small towns like Dodola is a rationale that is worth considering. Therefore, this study aims at investigating demographic and firm-related characteristics which determine performance of micro-enterprises in Dodola town.

1.3. General Objective of the Study

The general objective of this study is to investigate the nature and characteristics of microentrepreneurs and analyze the impacts of demographic and firm-related factors on performance and eventual growth of micro-enterprises in Dodola town.

1.4. Specific Objectives of the Study

- To examine the nature and characteristics of micro-enterprises and their entrepreneurs in Dodola town.
- To examine the socio-economic conditions of entrepreneurs of micro-enterprises in the study area.
- To evaluate the impact of micro-enterprises on the economic empowerment of entrepreneurs in Dodola town.
- To identify and analyze the demographic and firm-related factors which determine performance of micro-enterprises and ascertain their relative significance.

1.5. Hypothesis

- Male-owned enterprises exhibit higher performance than female-owned enterprises.
- Enterprises headed by young entrepreneurs (less than 30 years old) perform better than the other age groups.
- Enterprises whose owners have secondary education and above perform better than those headed by less educated owners.
- Enterprises whose owners/managers had previous experience perform better than those led by with no experience.
- Accession of credit from MFIs is positively correlated with higher performance of microenterprises.
- Micro-enterprises which operate in clusters exhibit higher performance than other.
- Enterprises with better infrastructure exhibit higher performance.

1.6. Significance of the Study

In Ethiopia enormous numbers of people live under extreme poverty with limited employment opportunity. Thus, understanding performance determinants of micro-enterprises in small towns may help policy designers to take in to account their unique needs during policy formulation. Secondly, it may help implementers to provide proper support to solve the actual bottlenecks of micro-enterprises by revealing areas of deficiency. Thirdly, it may contribute to the academic literature supplementing to the understanding of the nature and characteristics of micro- enterprises in small towns. Fourthly, it may benefit other stakeholders such as NGOs and microfinance institutions by throwing light on the betterment of their services.

1.7. Delimitation of the Study

The main purpose of this study is to explore the determinants of performance of micro- enterprises in Dodola town. Performance can be measured by numerous criteria such as profit, number of employees, sales volume, investment in fixed asset, among other things. However, due to the nature of the enterprises surveyed, the study used only profit and number of employees as performance indicators. Even though some other indicators were mentioned in the study, the purpose is rather descriptive than inferential. To this end, the participants of the study were micro-enterprise entrepreneurs and heads of MSEs development office. The study considers enterprises with a capital below 50,000 birr for those which operate in the service sector and below a capital of 100,000 birr for manufacturing sector enterprises (FeMSEDA, 2011).

1.8. Limitation of the Study

The aim of the study was to investigate determinants of micro-enterprises’ performance in their operation for growth and analyze the level of impact of each factor. Due to financial and time constraints, the scope of the study is limited to those enterprises operated by urban dwellers. Moreover, since large numbers of micro-enterprises operate in the informal sector without license and registration and the resulting difficulty to access them, the study only takes those registered in the district’s MSEs development office. Limited empirical information is one of the characteristics of micro-enterprise business mainly because the operators seldom keep records. In this study, recorded information was thoroughly looked for to analyze past and present performance of the enterprises. And in areas where registered data is limited, data collection was supplemented with reported perception of the entrepreneurs. Besides, data was triangulated by using mixed techniques and collecting data from diverse sources of information.

1.9. Organization of the Study

The first chapter deals with introduction, where background of the study, statement of the problem, objectives of the study, hypotheses, significance of the study, scope and limitation of the study were fairly discussed. The second chapter will deal with review of related literature which comprises of theoretical and conceptual framework as well as empirical literature. The third chapter mainly focuses on the description of the study area and methodology adopted for the study. The fourth chapter will deal with analysis of data and interpretation. Eventually, the last chapter deals with summary, conclusion and recommendation of the study.


2.1. Theoretical Literature

Performance of micro-enterprises is constrained by factors that are attributable to characteristics of both the firm and the entrepreneur. For instance, relying on data from several countries Chuta and Liedholm (1990) and Mcpherson (1996) suggested that growth of micro firms is dependent on characteristics of the firm and its owner. Theories like, Jovanic’s “learning theory” claimed a negative relationship between growth and size and age of the firm. In the same way, human capital of the entrepreneur such as education, age, and experience are positively correlated with firm growth (Vandersluis et al. 2005, Brown et al. 2005; Akoten & Outuska, 2007). Correspondingly, Okurut (2008) proposed that income/profit growth of micro-enterprises are positively and significantly influenced by education level, experience and business assets but negatively influenced by being female-owned and rural based.

With regard to gender, many previous findings revealed that women-headed firms perform below that of their counterparts and rarely grow at all. As Downing and Daniels (1992) suggested, this might be due to domestic responsibilities of women which may enforce them to be more risk aversive. Some other findings like that of Sexton and Robinson (1989) claimed that performance of women-owned enterprises is lower because women have fewer opportunities to build up relevant experiences and may have fewer networks to get support. It seems that women may have different goal than men. Unlike men, women are more family oriented and be less keen in pursuing economic goals related to expansion of the firm (Brush, 1992). Consequently, women tend to engage in businesses that are easy to begin and returns from the enterprise are used as a means of supporting family expenses. In this case, much of earned income is invested in house hold consumption instead of activities that promote firm growth. Confirming this, Cooper et al. (1994) found negative correlation between being female and growth of micro- enterprises, while he found no evidences to verify its impact on survival. Carter et al. (2001) also noted that women are less likely to have prior business experience or training and have difficulties in accessing resources such as financial, human and social capital. The status of women in developing countries has made them lag behind men in terms of education and training. For centuries, society of the developing world assumed the right place of women to be at home where main activities are looking for children and preparing food. As a result, in the mean time when women have a chance to start a business, they engaged in those activities which they have already learnt. This has made most women-owned enterprises to be relatively younger and operate mainly in retail trade and service sectors (Carter et al., 2001), leading them perform less due to less return. More to the point, the ease of entry has resulted in fierce competition and poor market demand. Similarly, conducting a study in Bangladesh, the Philippines, Zimbabwe and Tunisia, Marcucci (2001) stated that women-owned firms are younger, smaller, use less modern technology and concentrate in low investment and less profitable sectors. Owing to this, women-owned enterprises perform less well on measures of sales, employment and growth.

Age of the entrepreneur has an impact on performance and eventual growth of micro-enterprises. Orukut (2008) argued that as the age of the owner increases, the mean efficiency of the enterprise declines. Human capital of the entrepreneur, mainly education and previous experience, affect firm growth. According to McPherson (1996) completion of high school positively affects growth of micro and small enterprises in Zimbabwe and Botswana but not significant in Swaziland. Micro and small enterprises operating in manufacturing and service grow faster than those in trade (Liedholm, 2002). The same author claimed that firms located in rural towns and villages and home based are less likely to grow than their counterparts.

Aczel (2000) conducted a study in Thailand on the role of micro finance in promoting micro- enterprise performance. His findings revealed that MFIs play a fundamental role in serving as a source of goods and services, income, savings and employment. In a study by Mochona (2006), conducted in Addis Ababa found that only a few of the women entrepreneurs reported increased incomes from their enterprises. The study also noted that majority of the respondents expressed dissatisfaction with the loan processing procedure and time taken to secure the loan. A study conducted in Indonesia by Rahmat and Maulance (2006) indicated a positive relationship between MFIs and performance of MSEs which was measured in terms of sales.

Evidences indicated clustering has a positive impact on performance of enterprises since it allows entrepreneurs to access reliable market information, support institutions, effective market linkage, and quality and innovation among firms in the cluster. Location economies can reduce transaction costs of purchasing inputs and marketing outputs by pooling traders through eased information flows that facilitate labor sharing and subcontracting (Weijiland, 1999). The concentration of economic activities in particular location may result in cost saving economies of scale and location economies to micro-enterprises operating in a cluster. A study by Merima and Peerling (n.d) which was conducted on enterprises engaged in handloom sector, found a significant profit difference among enterprises working in clusters and those dispersed out of clusters.

2.2. Conceptual Framework

Promotion of micro-enterprises is viewed as a vehicle to employment creation and poverty reduction. They are among the ways for effective link between economic growth and poverty reduction. Although their role in development is indisputable, their performance is largely constrained by different factors which are economical, personal, socio-cultural and demographic in nature. Particularly, the enterprises are affected by demographic attributes of the entrepreneur and firm-related factors. Consequently, characteristics of the entrepreneur (namely gender, age, education level and experience) and firm-related factors such as operating location, infrastructure and accession of credit from Microfinance institutions were selected as independent variables in this study. The dependent variable, on the other hand, is performance of micro-enterprises which is measured using two chief indicators Viz. trend of annual profit and growth in number of employees.

Fig 2.1. Conceptual framework

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Source: Adapted and modified from the work of Bamidele, A.(n.d)

2.3. Definition and Concept of Micro and Small Enterprises

There is no single definition of micro and small enterprises around the world. Countries define them based on their level of economic development and industrialization. Number of employees, assets, turnover, and capital investment are the usual criteria for defining enterprises as micro, small, medium and large enterprises. Out of 120 economies covered by the World Bank survey, 26 countries have more than one definition (Krystna et al., 2011). In addition to size of employment, capital investment or turnover, scales of operation are used as a criterion (HCLEP, 2006). Although the definitions vary according to the country context, it is generally agreed that the informal sector, whether rural or urban, comprises small scale and micro-enterprises producing and distributing goods and services in unregulated but competitive markets (Mulat et al., 2006).

In Ethiopia, there is no single definition of micro and small enterprises. There is lack of uniformity at the national level. While the Ministry of Trade and Industry uses capital investment as a parameter, the Central Statistical Authority (CSA) utilizes employment as a yardstick (HCLEP, 2006). The informal sector is absorbing an increasing number of the labor force particularly in urban areas. They have an immense potential in creating employment opportunities and hence poverty reduction. The unemployment rate for the urban areas of Ethiopia is estimated at 20.6%, which was about ten times higher than in the rural areas (MoFED, 2010).This clearly shows the role micro and small enterprises play in urban employment. Employment in informal micro enterprises is growing much faster than employment in the formal sector. Between 1999 and 2005, informal employment (defined as employment in firms with fewer than 5 employees) increased by 144% compared to only 16% in formal employment. By 2005, 71% of urban employment was in the informal sector (World Bank, 2009 cited in Altenburg, 2010:09).

Two authorities, mainly the Central Statistical Authority (CSA) and the Ministry of Trade and Industry (MoTI), supply definition of micro and small enterprises in Ethiopia. MoTI employs capital investment as a parameter to categorize enterprises as micro, small, medium and large.

The definition used by MoTI, which uses capital investment has been developed for formulating micro and small enterprise development strategy in 1997 (HCLEP, 2006).According to MoTI micro-enterprises are those business enterprises in the formal and informal sector with a paid up capital not exceeding Birr 20,000 and excluding consultancy firms and other high tech establishment. On the other hand, Small enterprises are those business enterprises with a paid up capital of above Birr 20,000 and not exceeding Birr 500,000 and excluding high tech consultancy and other high tech establishments.

The Central Statistical Authority divides the enterprises based on the number of employees and the type of equipment utilized in the production process. According to CSA, Small scale manufacturing enterprises are those enterprises employing less than ten persons and using motor operated equipment. The authority divides micro enterprises in to informal sector operations and cottage industries (HCLEP, 2006).Cottage and handicraft industries are those establishments performing their activities by hand and using non power driven machines. The informal sector, on the other hand, is defined as household type establishments or activities which are non registered companies and cooperatives operating with less than ten persons (ibid).The above discussions indicate the unavailability of a single definition of micro and small enterprises at national level. The CSA does not use the term micro and small enterprises rather chooses terms like informal sector, small scale manufacturing industry and cottage and handicrafts (AEMFI, 2009).

Table 2.1.Classification of enterprises by paid up capital and number of employees

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Source: Support for Growth-oriented Women Entrepreneurs in Ethiopia, ILO 2005

However, the two definitions have their own limitations. On one hand, there is lack of uniformity. On the other hand, they do not consider the current economic situation. The definition by MoTI, for instance, needed to be revised in a way that should consider technology and consultancy services. This is necessary if the enterprises have to go in line with the country’s Growth and Transformation Plan. Similarly, the definition by CSA emphasized on manufacturing activities; overlooking the other sectors. Besides, it failed to consider size of capital. To overcome such limitations and formulate a uniform definition at national level, the Micro and Small Enterprises Development Agency recently revised the definition of micro and small enterprises. Consequently, the improved definition of micro-enterprise according to the new MSE Development Strategy (FeMSEDA, 2011) under the Industry sector (manufacturing, construction and mining) is defined as a firm which employs five persons including the owner with a total asset not exceeding 100,000 ETB. Similarly under the service sector (retailer, transport, hotel and tourism, ICT and maintenance services) it is a defined as a firm with five employees including the owner of the enterprise and/or with a total asset value of not more than 50,000 ETB.

Table 2.2. The new definitions of Micro and Small Enterprises

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Source: MSE Development Strategy (2011)

2.4. Empirical Literature

2.4.1. Personal attributes

The characteristics and quality of operators is a determinant factor that affects the overall operation of enterprises. The entrepreneur’s possession of entrepreneurial orientation, achievement motivation and goals contribute to business success. Entrepreneurship has been defined differently by various scholars. Schumpeter (1934) defined the concept as an individual’s innovative capacity and creative activity in terms of goods and services produced methods of production, markets, sources of supply and industrial reorganization. For Hisrich (1990) entrepreneurship is a behavior which consists of initiatives and creative thinking as well as organizing social and economic mechanisms to change resources and opportunities into practice, concomitantly accepting risk and failure. Drucker (1993) viewed the concept as behavior that enables a person to look for change, respond to it and exploit it as an opportunity to increase the value and satisfaction obtained from resources by consumers.

The effects of human capital and demographic factors on innovation and business success have been examined by various scholars. Hausman (2005), for instance, confirmed that in the USA innovative firms are led by more educated executives or owners. A study by Robson, et al. (2008) conducted in Ghana, revealed that innovation is positively correlated to the education level of owners. Equally important is the experience of owners which consists of level of skill and knowledge (ibid). Khan and Manopichetwattana (1989) found that firms led by in average younger owners, are proactive, risk taking, and more innovative.

Many people in Ethiopia engage in micro and small businesses not because they wanted to, but when they cannot engage in the formal sector like the civil service. Most of them access startup capital from informal channels such as own savings, loan from family and friends, or other informal sources. The absence of entrepreneurial orientation among the MSE operators resulted in businesses which do not generally innovate but chase for limited market in already identified business opportunities. There is a general lack of knowledge of entrepreneurial and managerial capacity and marketing experience. Moreover, MSEs lack resources required for research and development and there is inadequate technical and entrepreneurial skills (HCLEP, 2006).It is partly due to inadequate entrepreneurial capacity that most enterprises produce the same kind of items and compete for the same small local market. They lack the entrepreneurship to identify niche markets and to bring some dynamic qualities such as flexibility to respond to changes in the environment, initiative taking, innovativeness and diversity (Mulat et al., 2006).On the other hand, demand for credit is highly constrained due, mainly, to low entrepreneurship. Many clients, as can be expected, are very much risk-averse that even with the availability of credit and Business Development Services, many do not like to venture into activities other than those inherited from their fathers or for-fathers (Getaneh, 2007).The lack of entrepreneurship has impacted the growth and expansion of micro enterprises which compete for small markets to a great deal. The Federal Micro and Small Enterprise Development Agency and international development agencies confirm that micro and small firms rarely ever grow into a medium-sized segment, reflecting a lack of entrepreneurial and managerial capability (Altenburg, 2010).

2.4.2. Demographic characteristics

The demographic components such as age, sex, educational status, marital status and family size of the entrepreneur are worth considering while assessing the performance of their enterprises. Age, sex and marital status are important determinants of the entrepreneur’s ability and aggressiveness (Kiggundu, 2002). Many enterprises in Ethiopia are headed by men due to social and cultural factors which block women from income generating activities. This is evidenced by many studies conducted on micro and small enterprises. For example, a study conducted by Haftu et al. (2010), indicated more male are engaged in the micro enterprise than female accounting for 56% compared to 44% respectively. The same study revealed the predominance of male operators over female operators in small scale business activities with male operators constituting 74%. Another finding by Mulu (2007) showed immense proportion of businesses are men-owned comprising 74% while their female counterparts owned only 22% of the firms. A bulk of women-owned businesses focused on activities such as, retail trading, beauty salon, bars and restaurants, and local drink brewing (ibid).

Education plays crucial role in identifying niche market and making sound investment decision. Efficient management of enterprises demands entrepreneurs’ understanding of the business environment and other particulars. King and McGrath (2002) stated that education is one of the variables which positively affect firm growth. Entrepreneurs with better educated and (or) vocationally trained can easily adapt their enterprises to persistently changing business environments (King and McGrath, 1998).

In Ethiopia many micro-enterprise operators are not well educated which has led to poor record keeping and analysis in decision making. A study by Eshetu and Zeleke (2008) revealed that among failed firms, 71.4% of non-operational enterprises accounted for owners whose education level is below secondary level. Majority of micro and small enterprise owners (about 42%) have attended secondary education and about 15% mentioned some years of education above high school while owners with some primary education and illiterate constitute for about 29% and 12% respectively (Mulu, 2007). Similarly, a study by Haftu et al. (2010) revealed that 71% of the small enterprise operators have at least secondary education while another 20% have vocational training. Quite recently, numerous studies reported the involvement of university graduates in micro and small enterprises.

The youth and women are the primary focuses of the micro and small enterprise development strategy. In terms of age, the dominant age group is 20-39 (accounting for close to 55%) followed by those aged 40-49 (constituting about 31%). Those younger than 20 and over 60 constitute only 3% and 4%, respectively. Thus, the sector is providing employment opportunity to the most economically active section of the society (Haftu et al., 2010).

2.4.3. Socio-cultural variables

The cultural and social setting where many were born has made them less innovative and highly risk avoiders. As a result, they tend to concentrate their enterprises on the business opportunities which were already identified by others. According to HCLEP (2006), the main cultural and social problems affecting the development of micro and small enterprises in Ethiopia are lack of enterprise culture, considerable lack of positive attitude and excessive corruption. There is a general tendency to undermine some income generating activities on irrational prejudice. Some activities which could provide alternative employment opportunities like blacksmithing, weaving, tannery, pottery, sewing, and other handicrafts are rather frowned at since they are considered to be jobs traditionally given for citizens of the lower class (Getaneh, 2007).

Besides, some other sociological factors affect entrepreneurs in micro and small enterprises. These factors disproportionately impacted women entrepreneurs in MSEs. Women encounter problems of accessing credit facilities, suppliers and rental charges. They have been segregated from the mainstream social, economic and political arena. Even if they work for longer hours, most of their activities long stayed to be reproductive chores that are not worth paying in monetary terms. Women in Ethiopia still remain at the lower end of an isolated labor market and continue to be concentrated in a few occupations, to hold positions of little or no authority and to receive less payment than men. More importantly, women workers are not aware of their rights and related issues in general, they also lack education, resource and opportunities (MoFED, 2009).

Although women take the lion’s share in the informal sector, financial accession through the formal channels by women is significantly minimal. According to AEMFI (2005), out of a total of 658,708 active borrowers, women account only 30% in Ethiopia. This is very low as compared to the active borrowers of Women in Africa, which is 65.3 percent (WABEKBON, 2007).The literature clearly shows that small businesses and enterprises operated by women entrepreneurs are not being provided with adequate strategic support in terms of policy, access to finance, tax assessment, skills development and managerial training, technological transfer and infrastructural development (Berhanu, Abraham and Van Der Berg, 2007 cited in Eshetu and Zeleke, 2008:05).

In addition to the same challenges and constraints they face, women have reported other gender related problems. More than half of all women entrepreneurs in Ethiopia often face gender related challenges related to establishing new businesses as well as operating or expanding existing businesses (Amha and Admassie, 2004 cited in Eshetu and Zeleke 2008:05).However, the constraints faced by women have not attracted due attention yet. The scarcity of data on the MSEs sector in general, as well as on the participation and role of women in MSEs, and the lack of any national profile of women entrepreneurs or their enterprises, does not allow for any kind of extensive analysis of their situation (Stevenson and St-Onge, 2006).Many women turn to micro-enterprise because they are essentially marginalized in the labor force and unable to find employment alternatives (Stevenson and St-Onge, 2006). About 52.8% of women responded that being dependent on their husband’s salary, coupled with low income levels; do not even satisfy their monthly expense, which forces them to be engaged in MSEs (Rahel and Paul, 2010).

The working place is one of the main components that are needed for a successful and sustainable growth of enterprises because it is essential in creating access to resources and the necessary markets. Most women entrepreneurs do not have their own working premises. Only 16.3% of the respondents work in their own premises. The majority of the respondents (71.5%) claimed that their working place is shared with other members in the cooperative (Rahel and Paul, 2010).Microenterprises run by women were generally started as a result of unsatisfied household subsistence needs (such as food, clothes and education of children; girls dropping out of school and being unable to find wage employment; family pressures on girls to earn their own living; credit facilities being directly offered to women on their doorsteps ( Zewde and Associates, 2002).

Studies have shown that women are highly work-loaded compared to men. Women spend lots of time which might be used for generating additional income for family and community responsibilities. In many SSA countries, women work up to 16 hours a day, managing both productive work and household responsibilities. Their responsibility for child care restricts their mobility and obliges them to generate income in less conducive environment for business (Yeshihareg, 2007).

2.4.4. Business Characteristics of the Enterprise

The two forms of businesses in micro and small enterprise sector are sole proprietorship and cooperatives. Irrespective of the operational scale or owners’ gender, the two most common forms of business are sole proprietorship and cooperatives , the former being the most dominant (Haftu et al., 2010). The same study indicated that trade business and agri-business are the mainstay of micro enterprises with a share of 39% and 32% respectively. For the small enterprises, the majorities (40%) are engaged in trade and 33% are involved in the service sector (ibid). A significant number of small firms are involved in manufacturing activities. Textiles and apparel, food and beverages, and wood and forest products are the three most important activities. Findings suggest that these three categories comprise about 75% of manufacturing enterprises in urban areas of many developing countries and 90% in rural areas.


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Analysis of Performance Determinants in Micro-Enterprises. The Case of Dodola District, Oromia Region
Hawassa University  (governance and development studies)
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micro-enterprises, Performance, Multinomial Logistic Regression, Performance Determinants
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Alemayehu Habte (Author), 2012, Analysis of Performance Determinants in Micro-Enterprises. The Case of Dodola District, Oromia Region, Munich, GRIN Verlag,


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