Research Article: 2019 Vol: 25 Issue: 4
Yohannes Worku, Tshwane university of technology Business School
Zeleke Worku, Tshwane University of Technology Business School
Mommo Muchie, Tshwane University of Technology Business School
The paper is based on a survey of 228 women entrepreneurs of Ethiopian origin living and working in the nine provinces of South Africa. The purpose of the survey was to explain socioeconomic factors that affect the profitability of businesses operated by women entrepreneurs of Ethiopian origin. The study found that about 74% of businesses were profitable. Profitability in businesses operated by women migrant entrepreneurs was influenced by level of entrepreneurial skills, the ability to raise business loans from social capital associations, and the ability to order merchandise in bulk on credit, in a decreasing order of strength.
Women Entrepreneurs, Access to Loan, Migrants, Discriminant Analysis.
The study is based on data collected from 228 women migrant entrepreneurs of Ethiopian origin who conduct business in the nine provinces of South Africa with a view to shade light on the living and working conditions of migrant women entrepreneurs in South African cities and townships. Migrant entrepreneurs from Ethiopia have been operating formal and informal retail businesses since the early 1990s in South African cities, townships and locations. Such migrant entrepreneurs are often exposed to different cultural, language and socioeconomic norms and standards in South Africa. Worku (2018); Landau (2018); Landau & Freemantle (2016) have highlighted the plight of migrant entrepreneurs conducting business in South Africa. Cornelissen, Cheru & Shaw (2016) have argued that South Africa should make the effort to meet the basic needs and operational requirements of migrant entrepreneurs who live and work in South African cities and townships in order to transform migrant entrepreneurs into regular taxpayers. By citing examples from migrant communities in the USA, Landau (2018); Worku (2018) have argued that fulfilling the basic operational needs of migrant entrepreneurs is economically wise and prudent. Yang et al. (2016) have pointed out that potential benefits of creating an economically enabling environment for migrant entrepreneurs, and have provided specific areas of intervention that should be tackled by national governments and local municipalities. The key areas of need are residence permits, trade license and bank accounts. Lack of access to finance is a well-known predictor of failure among newly established SMMEs operating in South African cities and townships (Storey, 2016). The authors have shown that the basic needs of migrant entrepreneurs are often not met adequately due to lack of leadership and vision. One key area of need is access to a bank account that could be used for successful business operation. The aim of study was to assess the relationship between low level of business ethics and the culture of non-payment of loans obtained from social capital schemes. The study is based on a study conducted by Worku (2018) in which socioeconomic factors that are known to affect entrepreneurial activities conducted by migrant entrepreneurs of Ethiopian origin in South Africa have been identified.
Mersha & Ayenew (2017) have shown that start-up businesses are often dependent upon financial contributions made by immediate family members with a view to help a fellow family member start a career in business. The authors have shown that siblings and immediate family members are expected to help start-up enterprises by way of contributing money, establishing networks for the supply of stocks and merchandise, the provision of coaching and mentoring services to novice entrepreneurs in areas such as drawing up business plans, ordering merchandise and performing bookkeeping, auditing and tax return duties. Nagler & Naude (2017) have shown that women entrepreneurs rely upon their siblings and immediate family members for securing start-up capital, marketing and networking skills. Belwal et al. (2012) have shown that the majority of women entrepreneurs in Ethiopia borrow their start-up capital from social capital schemes in which money is contributed by close friends and family members who know and mutually trust each other. The authors have pointed out various socioeconomic obstacles that are peculiar to women entrepreneurs.
Based on a survey conducted in three major cities of Ethiopia, Hundera (2014) has found that business enterprises operated by women entrepreneurs rely relatively more heavily on money raised from social capital schemes in comparison with money raised from commercial banks and microfinance agencies. The author has identified two major obstacles to business enterprises that are owned and operated by women entrepreneurs. These barriers are failure to produce adequate collateral to commercial banks and coping up with high interest rates imposed by microfinance agencies.
Deribe (2012) has highlighted various policy related barriers that stifle businesses that are owned and operated by women entrepreneurs in the various geographical regions of Ethiopia. The author has argued that the Ethiopian Government needs to support women entrepreneurs by way of easing the demand for collateral required by commercial banks. Kiliswa & Bayat (2014) have called for measures in which Ethiopian commercial banks and microfinance agencies follow examples from the Grameen Bank of Bangladesh (Bairagi & Azzam, 2014) in which the Government of Bangladesh eased collateral requirements in the interest of enabling poor rural women who needed to borrow money from commercial banks such as the Grameen Bank of Bangladesh.
Slabbert (2017) stated that the lack of economic opportunities for young women in Ethiopian cities and towns prompt them to migrate to foreign destinations. Since the early 1990s, young Ethiopian women have been migrating to South African cities and townships in order to live as entrepreneurs. Worku (2018) has found that migrant entrepreneurs of Ethiopian origin operating in South African cities and townships are coping with the challenges of life in South Africa fairly well, and that both men and women entrepreneurs are actively engaged with retail activities. The author has pointed out that migrant entrepreneurs of Ethiopian origin are coping with life in South Africa although there are a few minor challenges to be overcome. The key obstacles are related to residence permits, driver’s licenses and the difficulty involved with opening up bank accounts. The author has found that migrant entrepreneurs of Ethiopian origin raise money needed for business operations from social capital schemes that are similar to South African stockvel associations.
Okeke-Ihejirika et al. (2018) have identified numerous difficulties that are commonly encountered by migrant women entrepreneurs conducting business operations in North American and European cities. These difficulties are gender-based, cultural, traditional, faith-based and educational in nature. The same difficulties are encountered by migrant women entrepreneurs of Ethiopian origin living and working in South African cities and townships. Studies conducted by Landau (2018); Worku (2018) have shown that migrants living and working in South Africa need to be integrated into mainstream South African society in order to let them be productive and happy citizens.
Abebe (2017) has listed down the most pressing basic socioeconomic challenges faced by young women graduating from Ethiopian high schools, colleges and universities. The author has suggested that regional governments and local municipalities should attract foreign direct investment actively as a means of creating livelihoods for the youth. Mendoza (2011); Reda (2018) have shown that poor young women suffer more than any other segment of society in developing nations such as Ethiopia due to poverty, poor infrastructure, failure to attract foreign direct investment, the promotion of tribal politics, lack of leadership, failure to respect the basic rights of women and lack of good governance.
Objectives of Study
The objective of study was to assess determinants of profitability in small business enterprises that are operated by migrant women entrepreneurs of Ethiopian origin in South Africa.
Maes & Kalofonos (2013); Cornelissen et al. (2016); Storey (2016); Landau & Freemantle (2016); Landau (2018); Worku (2018) have identified and quantified socioeconomic factors that affect profitability in small business enterprises that are operated by migrant entrepreneurs in South Africa. Donnelly et al. (2015) have highlighted health-related and economic factors that adversely affect young Ethiopian women, and have called for radical measures with a view to improve the plight of young women in Ethiopia. Newton-Levinson et al. (2014) have identified various socioeconomic and cultural factors that adversely affect the plight of women entrepreneurs in Ethiopia. The authors have shown that stigmatisation undermines the development of women in the field of entrepreneurship. Stark, et al. (2018) have highlighted the plight of refugee girls who migrate to large cities from small towns and villages in search of livelihoods and employment opportunities. The authors have argued that the underlying causes of migration to large cities and towns are lack of economic opportunities for young women in this regard.
Thomas & Godfrey (2018) have shown that the national Government of Ethiopia needs to prioritise the basic socioeconomic needs of young women in all parts of Ethiopia as a means of curbing the migration of women into large cities.
Landau (2018); Landau & Freemantle (2016); McKeever (2016); Rose-Ackerman & Palifka (2016); Atkinson & Storey (2016) have pointed out that valuable economic contributions are made by migrant entrepreneurs who live and work in South African cities, townships and locations. Studies conducted by Crush & Ramachandran (2017); Lawlor & Tolley (2017); Tengeh & Nkem (2017); Bhachu (2017) have shown that migrant entrepreneurs are viewed as a competition to local entrepreneurs and unemployed youth in some South African communities. The authors have recommended strategies such as awareness campaigns and improved financial and technical assistance to local youth who aspire to set up their own business ventures. Landau & Freemantle (2016) have highlighted the need to balance the basic needs of local communities with that of migrant entrepreneurs with a view to create an economically enabling environment for all people who live and work in South African cities, townships and rural communities. The unemployment rate among South African youth (South Africans with ages of 14 to 35 years) is about 27.1% (Statistics South Africa, 2018). Shisana et al. (2010) have written about the plight of poor South African women and youth, and have highlighted the need to implement community based poverty alleviation programmes as a means of improving the provision of basic health and socioeconomic services.
The South African Government has development assistance programmes that are designed in order to provide a combination of administrative and financial assistance to start-up businesses that are owned and operated by local South Africans. Wadee & Padayachee (2017) have shown that such development assistance programmes have failed to produce successful results due to lack of discipline and commitment and lack of entrepreneurial and managerial skills. Lack of awareness about the contributions made by migrant entrepreneurs to the South African economy often leads to ill-informed resentment (Crush & Ramachandran, 2017).
Tefera & Van Engen (2016) has shown the numerous difficulties experienced by Ethiopian women. The authors have highlighted male-dominated and male-centred policies and traditions that stifle and frustrate efforts made by aspiring women entrepreneurs. The authors have suggested that high achieving and ambitious women should be assisted by way of legislation. Access to finance is highly restricted by commercial banks and microfinance agencies. Most moneylenders demand fixed assets as collateral. The Ethiopian Government has failed to step in as a guarantor of fixed collateral in support of women loan applicants although this strategy has worked quite successfully in Bangladesh (Bekele & Worku, 2008). Ending conditions are quite stringent. Loan repayment conditions are strict. Interest rates are high. As a result, women entrepreneurs often struggle to thrive in Ethiopia. Kuma & Limenih (2015) have shown that migrant entrepreneurs of Ethiopian origin are prompted to migrate to foreign countries due to lack of economic opportunities and intense competition among entrepreneurs.
Deen-Swarray et al. (2013) have shown that women entrepreneurs in Sub-Saharan African countries such as Ethiopia are often not given recognition for their contribution to GDP and the creation of livelihoods. The authors have shown that lack of good governance, wrong policies, lack of leadership, corruption and the abuse of power by municipal officials hinder sustained growth and development in businesses that are owned and operated by women entrepreneurs. Based on a study conducted in Haiti, Mauconduit et al. (2013) have shown that women entrepreneurs in developing nations such as Ethiopia need to be supported by national governments by way of providing training on entrepreneurial skills, marketing skills, networking skills, and by easing requirements for loan applications at commercial banks.
Van Blerk (2016) has pointed out socioeconomic difficulties experienced by young Ethiopian women. The educational curriculum used at high school and undergraduate levels in Ethiopia does not prepare young women adequately on vocational, artisan and entrepreneurial skills. The educational curriculum needs an overhaul with a view to equip young women with the skills they require in order succeeding as entrepreneurs. Workineh et al. (2015) have identified socio demographic and health-related predictors of early marriage among teenage girls in Ethiopia. The authors have highlighted the need for poverty alleviation programmes among teenage girls.
The aspiration of migrant women entrepreneurs to thrive in business in highly competitive business environments and foreign destinations could be explained by the theory of entrepreneurial feminism (Dy et al., 2017). The theory is based on the principles of social feminism, and explains how feminist values are enacted through the venture creation process to improve the position of women in society. Pettersson et al. (2017) have shown that hardworking women migrant entrepreneurs have made significant contributions to national economies globally. Santarelli & Tran (2013) have shown the benefits of social capital schemes for raising start-up capital in small, micro and medium-sized enterprises in Vietnam. Mitiku et al. (2016) have identified barriers that stifle socioeconomic and entrepreneurial achievements by young Ethiopian women who aspire to be self-supporting. Examples of such barriers are lack of awareness about the plight of women, the domination of women by men, lack of respect for the basic rights of women, and failure of regional and national governments to devote adequate resources for the provision of basic health and educational services to young women. Setegn et al. (2016) have shown how many Ethiopian women are made to suffer due to lack of awareness about the harmful nature of genital mutilation and early pregnancy.
Social capital schemes are quite indispensable to migrant women entrepreneurs living and working in South Africa. The schemes operate based on trust and solidarity among members of the schemes (Fatoki & Patswawairi, 2012; Molla et al., 2015; Akanle et al., 2016; Cornelissen et al., 2016). Less than 6% of members of social capital schemes default on the repayment of loans (Worku, 2018).
An exploratory cross-sectional design was used in the survey. The survey consisted of 228 women entrepreneurs of Ethiopian origin who lived and worked in the nine provinces of South Africa. Data was collected by using a self-administered questionnaire of study. A composite index developed by Bell (2016) was used for assessing entrepreneurial skills. A composite index developed by Wedel and Kannan (2016) was used for assessing marketing skills. Discriminant analysis (Tibshirani et al., 2015) and ordered logit analysis (Faraway, 2016) were used for identifying and quantifying influential predictors of profitability in businesses that were operated by the 228 women entrepreneurs in the study.
Results of Study
Table 1 show that about 46% of migrant entrepreneurs came to South Africa in search of better socioeconomic conditions. About 73% of them were formal migrants. About 99% of them rented their business premises. About 38% of them were in business for 8 years or longer at the time of the survey. About 51% of them had low level of formal education (Grade 12 or less). About 59% of them had ages of 21 to 40 years of age. About 30% of them were married.
|Table 1 General Characteristics of Migrant Entrepreneurs (n=228)|
|Variable of study||Number of respondents and percentage|
|Motivation for migrating|| Free society: 32 (14.04%)
Better infrastructure: 26 (11.40%)
Safety and security: 19 (8.33%)
Better socioeconomic conditions: 104 (45.61%)
Better socioeconomic values: 47 (20.61%)
|Type of migrant|| Formal migrant: 167 (73.25%)
Informal migrant: 61 (26.75%)
|Renting business premises||Own premises: 2 (0.88%)
Rent premises: 226 (99.12%)
|Duration of business operation||Three years or less: 82 (35.96%)
Four to Seven years: 60 (26.32%)
Eight years or longer: 86 (37.72%)
|Highest level of formal education|| Grade 12 or less: 116 (50.88%)
Certificate: 44 (19.30%)
Diploma: 35 (15.35%)
Bachelor’s degree: 31(13.60%)
Master’s degree or more: 2 (0.88%)
|Age of entrepreneur||20 years or less: 32 (14.04%)
21 to 40 years: 134 (58.77%)
41 years or more: 62 (27.19%)
|Marital status of entrepreneur|| Single: 43 (18.86%)
Married: 68 (29.82%)
Divorced: 24 (10.53%)
Widowed: 9 (3.95%)
Living together: 84 (36.84%)
Table 2 shows that about 74% of businesses were profitable. About 45% of women entrepreneurs owned the businesses they operated. About 79% of respondents possessed adequate entrepreneurial skills by the standards of Bell (2016). About 72% of respondents possessed adequate marketing skills by the standards of Wedel & Kannan (2016). About 51% of respondents possessed adequate networking skills by the standards of Bone (2017). About 44% of respondents were capable of ordering merchandise in bulk on credit from wholesale suppliers.
|Table 2 Assessment of Profitability of Businesses (n=228)|
|Variable of study||Percentage|
|Profitability of business||Profitable: 169 (74.12%)
Not profitable: 59 (25.88%)
|Status of person operating business||Owner: 103 (45.18%)
Employed manager: 125 (54.82%)
|Entrepreneurial skills by the standards of Bell (2016)||Adequate: 181 (79.39%)
Inadequate: 47 (20.61%)
|Marketing skills by the standards of Wedel and Kannan (2016)||Adequate: 164 (71.93%)
Inadequate: 64 (28.07%)
|Networking skills by the standards of Bone (2017)||Adequate: 117 (51.32%)
Inadequate: 111 (48.68%)
|Ability to order merchandise in bulk on credit from wholesale suppliers||Adequate: 101 (44.30%)
Inadequate: 127 (55.70%)
|Business plan seen by data collector during survey||Yes: 54 (23.68%)
No: 174 (76.32%)
|Proof of inventory of stock seen by data collector during survey||Yes: 209 (91.67%)
No: 19 (8.33%)
|Proof of accounting seen by data collector during survey||Yes: 162 (71.05%)
No: 66 (28.95%)
|Proof of auditing seen by data collector during survey||Yes: 133 (58.33%)
No: 95 (41.67%)
|Proof of bookkeeping seen by data collector during survey||Yes: 139 (60.96%)
No: 89 (39.04%)
|Proof of current tax submission to SARS seen by data collector during survey||Yes: 62 (27.19%)
No: 166 (72.81%)
Table 3 shows a frequency distribution for the provinces of operation of the 228 women entrepreneurs who were selected for the study. The table shows that about 32% of women entrepreneurs were based in Gauteng Province. About 14% of them were based in the Western Cape. The percentage of entrepreneurs in KwaZulu-Natal was about 18%.
|Table 3 Province of Business Operation of Women Entrepreneurs (n=228)|
|Characteristic||Number of respondents and percentage|
|Province of business operation||Eastern Cape: 13 (5.70%)
Free State: 16 (7.02%)
Gauteng: 72 (31.58%)
KwaZulu-Natal: 41 (17.98%)
Limpopo: 14 (6.14%)
Mpumalanga: 17 (7.46%)
Northern Cape: 8 (3.51%)
North-West: 14 (6.14%)
Western Cape: 33 (14.47%)
Table 4 shows that about 13% of respondents started business by using their own savings. About 21% of them started business by using money from their friends or family. About 52% of them did so by using money raised from social capital schemes. About 8% of them did so by using donations. About 13% of respondents had applied for at least one business loan from a commercial bank. About 41% of respondents had applied for at least one business loan from a microfinance agency. About 71% of respondents had applied for a business loan from a social capital scheme.
|Table 4 Province of Business Operation (n=228)|
|Variable of study||Number and percentage|
|Source of start-up capital||Own savings: 29 (12.72%)
Friends or family: 48 (21.05%)
Social capital scheme: 119 (52.19%)
Donation: 18 (7.89%)
Others: 14 (6.14%)
|Past experience of applying for a business loan from a commercial bank||Yes: 29 (12.72%)
No: 199 (87.28%)
|Past experience of applying for a business loan from a microfinance agency||Yes: 94 (41.23%)
No: 134 (58.77%)
|Past experience of applying for a business loan from a social capital association||Yes: 161 (70.61%)
No: 67 (29.39%)
|Outcome of application for a business loan at a formal commercial bank||Positive: 5 (17.24%)
Negative: 24 (82.76%)
|Outcome of application for a business loan at a microfinance agency||Positive: 36 (38.30%)
Negative: 58 (61.70%)
|Outcome of application for a business loan at a social capital association||Positive: 144 (89.44%)
Negative: 17 (10.56%)
Table 5 shows that about 23% of respondents had experienced problems related to immigration permits in the past. About 17% of respondents had had trouble in opening up bank accounts at commercial banks. About 6% of them had experienced problems related to renting premises for business operation. About 5% of them had experienced language-related problems. Trade license related problems were experienced by less than 3% of respondents.
|Table 5 Difficulties Experienced by Women Entrepreneurs (n=228)|
|Major difficulties||Number (Percentage)|
|Problems related to immigration permits||53 (23.25%)|
|Collection of debt from customers||42 (18.42%)|
|Difficulty in opening up a bank account||38 (16.67%)|
|Rental problems||14 (6.14%)|
|Language related problems||12 (5.26%)|
|Storage room for merchandise||10 (4.39%)|
|Theft of goods||9 (3.95%)|
|Cultural problems||8 (3.51%)|
|Labour related problems||8 (3.51%)|
|Transportation problems||7 (3.07%)|
|Tax assessment problems||7 (3.07%)|
|Trade license related problems||6 (2.63%)|
|Driver's license related problems||6 (2.63%)|
|Security related problems||5 (2.19%)|
|Violent attack by robbers or thugs||3 (1.32%)|
Table 6 shows that about 93% of respondents had a positive perception about the level of support provided to them by members of local communities. About 94% of them took pride in the entrepreneurial activities they carried out in order to earn a living. About 95% of respondents had good working relationships with members of their local communities.
|Table 6 Perception Held by Women Entrepreneurs (n=228)|
|Perception held by women entrepreneurs||Number and percentage|
|Perception on the level of support from local community members|| Positive: 211 (92.54%)
Negative: 17 (7.46%)
|Taking pride in providing entrepreneurial services|| Yes: 214 (93.86%)
No: 14 (6.14%)
|Assessment of perception on the state of working relationship with members of local communities|| Positive: 217 (95.18%)
Negative: 11 (4.82%)
Table 7 shows results obtained from Pearson’s chi-square tests of associations that identify 6 factors that are significantly associated with profitability in businesses.
|Table 7 Determinants of Profitability in Businesses (n=228)|
|Factors that affect profitability in businesses||Observed chi-square value||P-value|
|Level of entrepreneurial skills||13.0259||0.0000|
|Ability to raise business loans from social capital associations||11.4126||0.0000|
|Ability to order merchandise in bulk on credit from wholesale suppliers||9.3615||0.0000|
|Level of formal education||3.6371||0.0000|
Discriminant analysis (Tibshirani et al., 2015) was used for constructing a predictive model of profitability of business based on the socioeconomic characteristics of the 228 women entrepreneurs in the study. The procedure generated a linear discriminant function for distinguishing profitable businesses from non-profitable businesses. The equation of the linear discriminant function (D) is given as follows:
D = a(ES) + b(SC) + c(OM) … (1)
Y =Profitability of business (Yes, No)
ES =Entrepreneurial skills by the standards of Bell (2016)
SC =Social capital participation for raising loan needed for business operation
OM =Ordering merchandise in bulk on credit from wholesale suppliers
The 3 predictor variables shown in Equation (1) were measured in standardised and validated percentage scores. The constants a, b and c are regression coefficients estimated from discriminant analysis. In cases where the regression coefficients a, b and c are useful for discriminating between the 2 categories of the dependent variable of study (profitability of businesses), values of the discriminant function D vary significantly depending on the 2 possible values of the dependent variable of study (profitable and non-profitable businesses). Stepwise discriminant analysis was used for identifying and quantifying the most influential predictor variables. For each canonical discriminant function, Eigen values and percentage of variance, Wilk’s lambda chi-square statistics and P-values were estimated. It was assumed that group membership is mutually exclusive and collectively exhaustive. Individual respondents who were selected for the study are assumed to be independent of each other. The predictor variable was assumed to follow a multivariate normal distribution. Within-group variance-covariance matrices were assumed to be equal across groups.
Table 8 shows standardised mean scores for the 3 predictors of profitability in the 228 businesses in the study for 3 categories of businesses (169 profitable businesses, 59 non-profitable businesses, and all 228 businesses). It can be seen from the table that the mean scores of the 3 predictor variables vary significantly.
|Table 8 Standardized Mean Scores of Predictor Variables (n=228)|
|Predictors of profitability of businesses||Profitable businesses (n=169)||Non-profitable businesses (n=59)||All businesses (n=228)|
|Level of entrepreneurial skills||35.09||29.37||32.29|
| Ability to raise business loans from
social capital associations
| Ability to order merchandise in bulk
on credit from wholesale suppliers
Table 9 shows a table of estimates obtained from discriminant analysis for the 3 key predictor variables of study. It can be seen from the table that the magnitude of the estimated canonical correlation coefficient is equal to 0.8118>0.75. This figure is a measure of explained variation. That is, the 3 predictor variables jointly account for 81.18% of the total variation in profitability. The magnitude of the Eigen value is 2.3924>1. The P-value from the F-test is equal to 0.0000<0.05.
|Table 9 Estimates Obtained from Discriminant Analysis (n=228)|
|Pairs of predictor variables||Correlation coefficient|
|Canonical correlation coefficient||0.8118|
|Calculated value of F-statistic with degrees of freedom 3 and 224||152.48|
|P-value for F-test||0.0000|
Table 10 shows standardized canonical discriminant function coefficients for the 3 predictor variables of study.
|Table 10 Standardized Canonical Discriminant Function Coefficients (n=228)|
|Predictor variables||Standardized canonical discriminant function coefficients|
|Level of entrepreneurial skills||0.64|
| Ability to raise business loans from
social capital associations
| Ability to order merchandise in bulk
on credit from wholesale suppliers
Table 11 shows comparative result estimated from logit analysis for the 3 predictor variables of study.
|Table 11 Odds Ratios Estimated from Ordered Logit Analysis (n=228)|
|Variable||P-value||Odds Ratio||95% C. I.|
|Level of entrepreneurial skills||0.000||3.51||(2.51, 6.93)|
|Ability to raise business loans from social capital associations||0.000||2.93||(1.89, 5.73)|
|Ability to order merchandise in
bulk on credit from wholesale
The survey was conducted by collecting information from 228 entrepreneurs of Ethiopian origin living and working in South Africa. About 13% of entrepreneurs started business operation by using their own savings. About 21% of them started business operation by using money raised from friends or family. About 52% of them started business operation by using money raised from social capital schemes. About 8% of them started business operation by using donated money.
About 74% of businesses were profitable. About 79% of entrepreneurs possessed adequate entrepreneurial skills by the standards of Bell (2016). About 72% of entrepreneurs possessed adequate marketing skills by the standards of Wedel and Kannan (2016). About 51% of entrepreneurs possessed adequate networking skills by the standards of Bone (2017). About 73% of respondents were formal migrants, whereas about 27% of them were informal migrants. About 36% of respondents owned the businesses they operated, whereas about 64% of them were employee managers. About 71% of respondents had an experience of raising money needed for business operation from social capital associations. About 44% of respondents were capable of ordering merchandise in bulk on credit from wholesale suppliers.
Similar results were obtained from discriminant analysis and ordered logit analysis. The study has shown that profitability was influenced by level of entrepreneurial skills, the ability to raise business loans from social capital associations, and the ability to order merchandise in bulk on credit. Results obtained from the study are similar to those reported by Akanle et al. (2016); Molla et al. (2015). The study has shown the significant association between profitability and raising loan from social capital schemes. About 71% of respondents raised loan money from social capital schemes. The study has shown the relative importance of ordering merchandise in bulk on credit from wholesale suppliers. About 44% of respondents ordered merchandise in bulk on credit from wholesale suppliers. These findings are similar to those reported by Reda (2018).
1. Migrant entrepreneurs should do their best to acquire formal education on entrepreneurial, marketing and networking skills before migrating to South African cities and townships for conducting business operation, as has been suggested by Mersha & Ayenew (2017).
2. Young Ethiopians who intend to pursue entrepreneurship in South Africa must acquire basic education on entrepreneurship, bookkeeping, auditing and writing up business plans. They should also obtain work permits through the South African Embassy in Addis Ababa as a means of minimising the loss of valuable time and resources at a later stage, as has been suggested by Mutoko & Kapunda (2017).
3. Businesses that are operated by women entrepreneurs are vulnerable to lack of socioeconomic stability. Migrant entrepreneurs could benefit from formal agreements and collaborations between Ethiopia and South Africa. More research is needed to identify a framework that could be used for promoting migrant entrepreneurship between the two countries.