systems research - the IDRC Digital Library - International ...

household basis on an income and expenditure sheet. Farmers were visited weekly
to collect the completed record sheets.
Seasonal surveys of crop production activities were conducted during the WS
of 1989 and the dry season (DS) of 1990. Details of household income and
expenditure were excluded from the survey.
Methods of analysis
Initial analysis was based on three farm-size categories. This did not reveal a
significant difference in mean yield or inconle-expenditure patterns among adopters
and nonadopters (Medialdia and Ranaweera 1988); therefore, further analysis was
done to compare the impact parameters between adopters and nonadopters. The
impact indicators included input use, yield and pattern of household consumption,
income, and expenditure. The partial budget technique was used to compare the
econoniic perfornlance of the t\vo groups.
Cluster ai~alysis was used to classify the adopters of the new technology
according to the level of adoption. Initially, plot-level data rather than farm-level
data were used because farmers may apply different types of technology to plots
with diverse characteristics (e.g., land tenure, Iandscilpe position, and soil texture).
However, farm-level data were subsequently used for cluster analysis.
Demographic characteristics of farmers and other farm-related inforrnation
were also recorded along with farm-level data. Variables related to the different
components of the KABSAKA technology were tabulated on a hectare basis or as a
percentage of the area where the technology was used. For ex:imple, the percentage
of the area planted using DSR was used to denote the extent to which the farmer
adopted the recommended crop establishment methods. Likewise, the percentage of
the area grown before the cut off date of the first crop and the percentage of the
area with a turnaround period of less than 16 d were used to denote the cut off date
for sowing and the turnaround period, respectively. Inputs (fertilizer, insecticide,
and herbicide) ancl yield were tabulated on a hectare basis. The VARCLUS
procedure was used to group the variables for cluster analysis. About 106 variables
were considered, but only 35 variables were used in the analysis (Table 1).
An attempt was made to combine the b;isic practices related to a conlponent
with f~rm-level characteristics, and to use these as the classifying vari~~bles for
cluster analysis. For example, for fertilizer usage as a cor-nponent technology, the
variables considered were the number of applicr~tions, the level of NPK in each
application, and the value of inputs used. Other components of the technology that
were tested were crop establishment, weed control, and turnaround period. These
components were tested on the premise that these f~rnlers could be classified
according to the level of technology adoption.