An investigation into the factors affecting the growth of women-owned small and micro enterprises in Kenya : a case of selected markets in Nairobi Province
In Kenya, dominance of trade over other sectors - manufacturing, services and construction - occupy two thirds of the country's enterprises. This means that a large proportion of Micro-Small Enterprises (MSEs) is engaged in buying and selling of commodities. Women productive activities are concentrated in small-micro enterprises in such ventures as hawking, retail trade, manufacturing and periodic market trade, (Mullei, Bokea 1999). Participation of women in trade is 86 per cent, which is (20 per cent higher than men). Despite the numerical dominance of women in small-micro enterprises, there are marked gender disparities and inequalities between men and women participating in similar activities. Studies touching on problems affecting women entrepreneurs give emphasis to economic forces and fail to address adverse African traditions that inhibit women's participation in MSEs. This study investigated the factors affecting the growth of women owned micro-small enterprises. The researcher surveyed women micro-small enterprises in view of business structure, performance and constraints hindering their participation in MSEs. The objectives of the study are: (i) to determine the demographic characteristics of women operating MSEs (ii) to establish what motivates women to participate in MSEs. (iii) to determine the role played by education, training and previous jobs in making of entrepreneurs. (iv) to investigate the factors affecting the growth of women MSEs. Literature related to the study was reviewed. A survey method was adopted whereby purposive sampling method was used to select 60 women micro-small entrepreneurs from a target population of 600 women entrepreneurs from 3 markets in Nairobi province: Wakulima, Gikomba and Kangemi Harambee market which were selected using purposive sampling method. Structured and unstructured questionnaires were used to collect the data, which was analyzed using Statistical Package for social Sciences (SPSS). Simple regression and correlation was used to determine the relationship between variables.