Factors influencing usage of new technologies in low‐income households in Kenya: the case of Nairobi

Abstract

Purpose

Use of e‐mail, the internet and mobile phones, collectively referred to as the “new technologies” in this paper, is influenced by various factors in low‐income households. These factors, which range between individual, social, economic, environmental, cultural and knowledge, have not been explored fully, particularly in low‐income households in Kenya. This paper aims to argue that access to the new technologies does not lead automatically to use thereof, since a combination of the factors determines if (and how) the technologies are used.

Design/methodology/approach

This paper uses data collected through a survey conducted in 2010, which complemented the 2007 Research ICT Africa (RIA) data. The 2010 survey focused on three clusters based in Nairobi, a subset of RIA (2007). The three clusters are Ofafa 1 (A), Umoja II (B) and Riruta Satellite (C). Data from 40 households are used. Qualitative and quantitative data were collected from the households.

Findings

Age, income, gender, education level, skills and marital status influenced usage of the new technologies in diverse ways. With innovations such as M‐Pesa, the respondents who used the technology and were confident with the usage cut across education levels. Males used the new technologies more than females did. A possible reason for this may be found in a further finding which shows that males had acquired more years of education than had females. The implication of this is that if equal education opportunities were available for all, then the usage differences would be addressed across the gender divide.

Originality/value

The paper uses the capability approach developed by Nobel laureate, Amartya Sen as the theoretical framework. A rigorous research design and methodology was used to collect and analyse the data.

Citation

Nyambura Ndung'u, M., Mwololo Waema, T. and Mitullah, W.V. (2012), "Factors influencing usage of new technologies in low‐income households in Kenya: the case of Nairobi", info, Vol. 14 No. 4, pp. 52-64. https://doi.org/10.1108/14636691211240888