(Journal of Developmental Entrepreneurship, Oct 2002 by Kiggundu, Moses N)
Various personal demographic variables appear to differentiate successful from less successful entrepreneurs in Africa, as they do elsewhere (Kallon, 1990; Mead, 1999; Mead & Liedholm, 1998; Stewart, 1996). Earlier studies found that successful African entrepreneurs tended to be male, middle-aged, married with a number of children, and more educated that the general population. For example, Benedict (1979) found that the growth and success of family entrepreneurs was dependent upon a strong authoritarian father and a closely knit family structure, with wives and children willing to submit to the father's rule. Kallon (1990) found in Sierra Leone that, the average entrepreneur was a monogamous male, about 46.2 years old, with an average of 5.4 children, and 4.5 dependents living in his household.
More recent studies have found that female entrepreneurs experience more operational and strategic impediment to success than their male counterparts (Rutashobya, 2001). Mead and Liedholm (1998) found that male-owned firms grew faster than those owned by women. Yet other recent surveys report higher rates of female entrepreneurial participation, both as owners and employees (Frese, 2000). For example, Mead and Liedholm (1998) report female ownership participation rates of 48 percent and employees of 44 percent. This is particularly the case for the micro and small enterprises (MSEs), employing very few if any people and generating little or no income for the owners.
The predictive validity of demographic variables tends to be unstable over time, especially when studied in isolation. This may be partly due to the conceptual and measurement problems of success as a dependent variable (Van Dijk, 1995), and partly due to changing societal values and practices. Keyser, de Kruif and Frese (2000) found no significant differences in success due to age or gender among Zambian MSE owners. As predictors of success or failure, demographic variables should be studies longitudinally, and in combination with other variables to form clusters, which show up either as problems or success factors (Dia, 1996; Mead, 1999).
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