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ABSTRACT<br />

The purpose <strong>of</strong> this study was to investigate and identify ICTs that<br />

provide access to information, enhance quality <strong>of</strong> life, and improve the<br />

economic standards <strong>of</strong> rural women by conceptualizing a model for the<br />

development, management, exploitation and use <strong>of</strong> ICTs in an African<br />

rural environment. In order to obtain data from the respondents, two<br />

research methods were utilized, namely the case study and survey<br />

research. In the former, data was collected from key informants in<br />

organizations that work with ICTs and rural women. Using frame lists<br />

from both South Africa and Kenya, a total <strong>of</strong> four organizations were<br />

purposefully selected, i.e. Womensnet and the National Community<br />

Radio Forum (NCRF) in South Africa, and AfriAfya and the Arid Lands<br />

Information Network (AUN-EA) in Kenya. The survey research method<br />

was used to interview women aged between 16 and 60 years. 400<br />

respondents formed the sampling size, randomly selected from census<br />

household data. Survey data in Kenya was obtained from the sub­<br />

divisions <strong>of</strong> the Kaplamai Division in Trans-Nzoia district, namely:<br />

Kimoson, Sinyerere, Sitatunga and Makutano. The sample frame<br />

included: small-scale traders (68; 34%); housewives (29; 14.5%);<br />

educators/teachers (27; 13.5); farmers (26; 13.0); students (11;<br />

5.5%); domestic workers (10; 5.0%); preachers (10; 5.0%); farm<br />

workers (6; 3.0%); large-scale entrepreneurs (5; 2.5%); nurses (4;<br />

2.0%); clerical workers (2; 1.0%); and community development<br />

workers (2; 1.0%).<br />

In South Africa, a similar sample frame included: small-scale traders<br />

(58; 29.0%); housewives/homemakers (48; 24.0%); farm employees<br />

(25; 12.5%); domestic workers (18; 9.0%); educators/teachers (16;<br />

8.0%); students (15; 7.5%); entrepreneurs managing large-scale<br />

enterprises (3; 1.5%); clerical workers (9; 4.5%); community<br />

development workers (6; 3.0%); and two preachers (2; 1.0%).<br />

Sampling data was obtained from census household data belonging to

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