9 pages., via online journal., Mobile apps such as social media have friendly attributes and unbiased usage across gender and age; and have become one of the most promising channels for dissemination of agricultural information. The current sources of agricultural information available to farmers do not allow a two-way flow of information and instant feedback. The information disseminated using such channels are generally not customized to specific farmers’ needs. Despite the availability of various mobile apps providing agricultural information, the adoption rate is too minimal. The aim of this study was to determine the usability attributes of social media influencing its adoption and use. A semi-structured questionnaire was used to collect data from a sample of 149 respondents. The respondents were selected through purposive sampling technique from a population comprising of farmers, extension staff, lecturers and students enrolled in agricultural courses participating in the Farm Attachment Program of Egerton University. Data collected was analysed using Statistical Packages for Social Sciences (SPSS) and probit regression was used to analyse expected probability of social media adoption. The findings indicate that the main usability attributes of social media are Ease of use, usefulness, credibility, flexibility and Internet availability. Mobile apps being used to disseminate agricultural information should incorporate some of the usability attributes that have significantly influenced the adoption and use of social media to enhance its uptake and use.
Agricultural Communications Documentation Center, Funk Library, University of Illinois Document Number: D11075
Notes:
Pages 131-132 in Penelope Muse Abernathy, Saving community journalism: the path to profitability. University of North Carolina Press, Chapel Hill. 254 pages., Describes use of a data mapping application called OpenBlock by rural and other community newspapers to enhance their reporting on public issues by providing context and analysis in government data.
