This
exploratory study assessed attitudes and perceptions of smallholder farmers
towards agricultural technologies in Kakamega County, Kenya. Through a mixed-methods
sequential design, the study evaluated the key variables predicting farmer
adoption of agricultural innovations. While social sciences provide a clear human-driven pattern explaining the
process of choices and behaviors regarding technology use, there is still little
clarity on the influences of adoption decisions among smallholder farmers in
rural Kenya. Using the diffusion of
innovations theory, the study explored the attitudes and perceptions of
smallholder farmers toward technology adoption in seven sub-counties of
Kakamega County (Lurambi, Ikolomani, Shinyalu, Mumias East (Shianda), Malava
Butere, and Khwisero). The study design utilized a quantitative survey of 245
smallholder heads of households, followed by focus group discussions to further
probe attitudes, values and practices that could influence technology adoption.
The survey questionnaire tested two hypotheses: (H1) socio-demographic
characteristics are related to agricultural technology adoption; and, (H2)
farmer access to extension services was related to agricultural technology
adoption. A binary logistic regression model was used to quantitatively
estimate socio-demographic variables presumed to influence the adoption of agricultural innovations.
Subsequently, four informal focus group discussions of 28 discussants was
conducted across representative sub-counties (Lurambi, Shianda, Malava and
Ikolomani), to elicit an in-depth understanding of farmers’ perspectives on
technology adoption. The focus group
participants included farmers recruited from among survey participants. The qualitative research instrument sought to
answer three questions, (RQ1) what are farmer attitudes and perceptions towards
agricultural technologies; (RQ2) what socio-cultural values influence farmers’
choice of agricultural technologies; and, (RQ3) what sources do farmers use for
obtaining information on agricultural technology? Quantitative results included
a principal component analysis (PCA) in which 14 attitudes questions were
reduced to five conceptual clusters. These clusters included: challenges in
accessing modern agricultural technologies (explained 19.09% of the total
variance); effectiveness of agricultural technologies (11.88%); enjoyment of
agricultural technologies (10.02%); social influence in use of technology
(9.47%); and experience with agricultural technologies (8.13%). A logistic
regression model indicated that independently age (.07), education (.10), and
off-farm income (.08) were significantly associated with adoption of technology
at the 90% confidence level when controlling for all other variables in the
model. However, agricultural
extension (.42) was not a significant predictor of agricultural technology
adoption in this model. Qualitative results provided rich insights which
enhanced findings from the survey data. Key
insights in the thematic analysis included: farmers’ ambivalence about
agricultural technologies; lack of trust in agricultural agents; low levels of
agricultural technology knowledge; extension services as the main source of information
dissemination to farmers; predominance of gender in determining agricultural
technology adoption; and gender inequity in agricultural decision-making. In
conclusion, the study results suggested that a mixed-methods approach was valuable in probing the
nuances of farmers’ perceptions of agricultural extension and technology
adoption among smallholder farmers. The results supported the following
recommendations: the agricultural extension efforts could be more effectively
structured in order to support the dissemination of agricultural information;
the issue of gender should be adequately addressed by engaging male and female
in collaborative agricultural efforts to help break the barrier of gender
inequity; and future research would benefit from disaggregating public and
private extension services as a more robust method for determining their
individual effects in the promotion of agricultural innovations among
smallholder farmers.