A socioeconomic analysis of Ethiopian migrant entrepreneurs in South Africa
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DOIhttp://dx.doi.org/10.21511/ppm.16(2).2018.40
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Article InfoVolume 16 2018, Issue #2, pp. 449-456
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The objective of study was to assess and evaluate factors that affect entrepreneurial activities carried out by formal and informal migrant entrepreneurs from Ethiopia who conduct business operations in the nine provinces of South Africa. The study was descriptive and exploratory in nature. The design of the study was descriptive and cross-sectional. Data were collected from a stratified random sample of 3,045 migrant entrepreneurs from Ethiopia who conduct business in the nine provinces of South Africa. Stratified random sampling was used for the selection of eligible entrepreneurs. The study found that about 76% of businesses operated by migrant entrepreneurs from Ethiopia were profitable, whereas the remaining 24% of businesses were not profitable. About 32% of entrepreneurs were attracted to South Africa due to better infrastructural facilities. About 25% of entrepreneurs were attracted to South Africa due to better socioeconomic conditions. About 78% of migrant entrepreneurs had conducted business in South Africa for five years or more at the time of data collection. About 34% of businesses paid tax to the South African Revenue Service (SARS) on a regular basis. About 38% of businesses employed at least one South African in their businesses. About 85% of entrepreneurs stated that they had good working relationships with members of the various local communities in South Africa.
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JEL Classification (Paper profile tab)E24, F18, F22, G23
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References47
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Tables7
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Figures0
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- Table 1. General characteristics of migrant entrepreneurs (n = 3,045)
- Table 2. Difficulties experienced by migrant entrepreneurs (n = 3,045)
- Table 3. Level of education and access to finance (n = 3,045)
- Table 4. Perception on level of support to migrant entrepreneurs (n = 3,045)
- Table 5. Employment of local South Africans by migrant entrepreneurs (n = 3,045)
- Table 6. Top five significant two-by-two associations from cross-tab analyses (n = 3,045)
- Table 7. Results from binary logistic regression analysis (n = 3,045)
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