McCormick+Schmitz Handbook for value chain research on - PACA

The coding of open-ended questions requires more attention and <strong>research</strong>er involvement.
Unless the survey is so large as to make this impractical, it is usual <strong>for</strong> all open-ended
responses to be listed. The <strong>research</strong>er then reviews the list and prepares a set of
categories. The categories depend to a large extent on the purpose of the study and of the
particular question. A question soliciting reasons <strong>for</strong> using a particular supplier may, <strong>for</strong>
example, in one context have responses reduced to only two categories (economic reasons
and social reasons) while in another, up to ten categories might be needed. Given that
today’s computer programmes make it fairly easy to collapse many categories into a few,
it is probably better to have too many rather than too few, at least at the initial stages of
analysis.
A.5.4 Data analysis
Data analysis is the process of bringing order, structure and meaning to the mass of
in<strong>for</strong>mation collected. In many ways, the quantitative analysis of data resulting from the
survey questionnaire is the easiest. Once the data have been entered into the computer and
the resulting data files checked <strong>for</strong> errors - a process called ‘data cleaning’ - you are ready
<strong>for</strong> the first level of analysis. This involves producing frequency distributions of all of the
variables. The review of the first printout of frequencies often reveals a few more data
problems that require cleaning. When these have been taken care of, you can move on to
the next level of analysis, which usually consists of a set of cross tabulations and analyses
of mean <strong>value</strong>s. In a <strong>value</strong> <strong>chain</strong> study, <strong>for</strong> example, you might base this analysis on the
destination of firms’ exports. You might want to examine key variables such as the
numbers of homeworkers, pay levels, benefits offered, and homeworker complaints <strong>for</strong>
firms exporting mainly to the US, compared with those exporting to Europe and other
destinations. To do this well, you will either need a fair knowledge of statistics or a
competent data analyst who has this knowledge.
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