1.8. RESEARCH DESIGN AND METHODOLOGY
Research methodology refers to techniques and tools used to
gather present, process and analyze data gotten from the field. This research
was qualitative. It looked into human capital management challenges and
prospects in Rwandan MFIs.
1.8.1. Target population and sampling methods
There are in total 96 licensed MFIs as of September
15th, 2009. However, for judgmental purposes, only two were subject
to our study. IMF UNGUKA S.A. was studied because it is 100% financed by
individual shareholders. As of DUTERIMBERE IMF S.A, it was started by a
nonprofit driven organization serving women entrepreneurs, as of now, it is one
of local MFIs
which is serving, mostly women. It is interesting because it
started with funds from donors. The common denominator between them is that
they were in existence by 2006 and survived the microfinance crisis.
1.8.2. Data collection instruments
The following data collection instruments were used:
First, the study used focus groups. One focus group,
comprising 4 informants, 1 from the National Bank of Rwanda (NBR), 1 from NBR
licensed auditors, 1 former MFI manager who is currently a consultant, and 1
from Association of Microfinance of Rwanda- an association whose mandate is to
build capacity for MFIs.
This was used because time was not enough to cover many MFIs
yet there was need to have a big picture of the sector. So, people with
exposure who deal in many ways with MFIs were used for that purpose.
Secondly, semi structured interviews were used. These allowed
the interviewees greater freedom in expressing the issues that they felt were
most relevant from their own points of view, and to potentially highlight
issues not envisaged at the interview design stage. Interviews with 2 key
individuals; actually Human Resource Managers of the studied MFIs was
conducted.
Thirdly, questionnaires were designed and distributed to 2
Managing Directors and employees in MFIs and people at non managerial levels.
This was to a tune of 20 respondents per each microfinance institution sampled.
The number of respondents and specific person to collect data from was decided
on a judgmental basis.
Fourthly, literature review was used to gather secondary data.
This relied on textbooks, articles, newspapers, policy papers, speeches and
internet based sources.
Human capital management in Rwanda: Challenges and prospects
for Microfinance Institutions 1.8.3. Data presentation and
analysis tools
To ensure valid results, the data was converted and processed.
A thorough examination of questionnaires and interview responses was done to
ensure consistency, accuracy and completeness of the responses.
For a better analysis of the collected data, some techniques were
used. These are editing, coding, tabulating and statistical analysis.
Editing: This is the first task in
data processing. It is about examining errors and omissions in the collected
data and making necessary corrections. After field work was finished, gaps, and
errors in recording were corrected.
Coding: After the editing of the
data, coding was done. This was meant to summarize by classifying the different
respondents given into categories. Thorough check was done in order to detect
any coding differences and eliminate ambiguous or irrelevant cases.
Data presentation: This used different tools to
make sure that the corrected data can be presented in such a manner that it
gives meaningful information. It will use the following tools:
Tabulating: After the previous steps, data
was summarized; frequency distribution table of answers to each closed-ended
question will be done. It used statistical tables with percentages.
Statistical Analysis: The calculation of
percentages was done. This was as a number of the sample size then multiplied
by a hundred divided by the frequency of the respondents. Statistical analysis
was done almost for all tables. Summation was used as well so that conclusions
can be done after relating these findings from the field and theoretical
literature from various sources. Besides, SPSS was used to enter data, analyze
frequencies and run correlations where such analyses were needed.
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