CONCLUSIONES Y RECOMENDACIONES

The questionnaire started with a covering letter seeking the assistance of the respondents in completing the questionnaire and at the same time, introducing the researcher as a Master’s research student, in Management in Finance and Investments (MMFI), of the

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Wits University, the topic of the research study and its aim and objective are also stated clearly. In addition to this, a covering letter from the researcher as a student as well as a letter from the ethics committee were also attached to encourage participation and to boost confidentiality.

The work adopted a structured questionnaire with closed-ended questions reflecting on the conclusion drawn from the literature review to give pre-determined answers. To ensure its reliability, the study made use of some existing studies’ questionnaire samples and guides from reputable researchers and organisations such as the United Nations Organisation (UNO), as well as some research work done locally in South Africa, among others, to act as a benchmark for the construction of data collection tools used in the study.

The research used multiple questions; response categories that required a response from Strongly Agree to Strongly Disagree on a 5-point scale was used, ranking questions which explore the importance of or preferences for certain issues were also used. All the questions in the questionnaire from section A and section B were posed in English with the assumption that all concerned, as well as the researcher, were able to interact effectively and efficiently in English. By implication, this enhanced easy communication between the researcher and the respondents.

RESEARCH DESIGN

Research design is simply the road map or a strategic blueprint for data collection, data measurement and analysis (Sekaran & Bougie, 2010). The research work adopted a quantitative survey method to execute this study. This approach allows for larger and more representative respondent samples and involves the numerical calculation of results (Creswell, 2003; Wiid & Diggines, 2009). A structured questionnaire was used as the study instrument. A survey study is a systematic way of data collection that enables the

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researcher to obtain selected respondents’ opinions, attitudes, behaviours, beliefs or answers to understand the group or population represented (Grinnell, 1997; Fowler, 2009).

The strength of this technique is that it is formal, logical and specific based in its procedure. It enabled the researcher to select a sample population without prejudice with representative units of the investigation and the population in which the investigation is going to take place (Wiid & Diggines, 2009). In addition, its data were original, obtained from a sample of the population and the content of the survey data was primarily the respondent’s own opinion on the subject matter. Most importantly, it allowed for quick data collection as the survey was done in a short time.

THE PURPOSE OF THE QUESTIONNAIRE

The reason for the adoption of the questionnaire was informed by the research design adopted, namely quantitative survey technique. With a quantitative technique, the researcher focused on facts, looked for causality, reduced phenomena to the simplest elements, formulated hypotheses and then tested them to take large samples. It is also important to say that most people are familiar with the use of a questionnaire as a measuring instrument.

TARGET POPULATION

Target population is defined as the complete group of individuals or elements that the researcher wishes to include in the sampling method and these determine sample size (Hair, et al., 2007; Sekaran & Bougie, 2010). It is defined in terms of availability of elements, time frame, geographical habitats and topic of interest. Therefore, the target population for the study comprised men and women beneficiaries of the microfinance

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institutions, leadership and staff members of the microfinance institution operating in eThekwini and surrounding areas. The target population was presumed to have an in- depth knowledge and information about the topic under investigation and general information about the operation of the MFI.

 Sampling

Sampling was used to select the respondents from each branch of the microfinance institution. Sampling is the selection of a small set from a chosen population to give a generalised result representative of that of the population (Wiid & Diggines, 2009). Sampling is encouraged because of the inability of a researcher to cover the whole population. The advantage of using a sample is that a representative sample allowed the researcher to take the information obtained from the small sample and reapply it to the total population (Ruane, 2005). In this study, the sample comprised women and men beneficiaries of the microfinance institution. A representative sample can also be seen as one that will, in all aspects, provide a true reflection of the population. It allows the researcher to gather information quickly and inexpensively.

 Sampling frame

A sample frame can be defined as a list of all the sample units available for selection at a stage of the sampling process. Therefore, the actual sample is then drawn from within the sample frame (Wiid & Diggines, 2009). According to Webb (2002), in a reliable sample frame all the elements and strata of the population are represented, including gender, age, and geography, among others. It must be up to date and there must be no duplication of entries. Its shortcomings are missing sample units, duplicate entries and foreign elements (Webb, 2002). The researcher had a variety of sampling frames that included the list of loan officers at the microfinance institutions and the list of beneficiaries from the microfinance institutions.

The limitations were taken care of as the research study made sure that all the sample units comprising the population were listed in the sample frame. In addition, duplicate

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entries were prevented as the research made use of only one sample to eliminate foreign elements.

 Sampling frame compilation

The microfinance institutions, on the other hand, were also able to list the leadership and staff members/loan officers who work with the clients directly. After the lists were compiled, the researcher was able to identify the respondents using purposive/judgement sampling method.

 Purposive/judgement sampling

This is a deliberately non-random method of sampling, whose aim is to sample a group of people or settings, with a particular characteristic, usually in qualitative research designs. The purposive sampling is also sometimes referred to as judgement sampling where respondents are selected because they have knowledge that is valuable to the research process, for instance, the MFI’s leadership (Bowling 2002). This is to ensure that the respondents who were or had participated in the microfinance institution were selected and not those who did not know anything about the topic. The researcher utilised men and women who gave informed consent and satisfied the other inclusion criteria and were then entered into the study. Since the beneficiaries had the right and opportunity to benefit from all the MFIs, the researcher took care to limit the beneficiary appearing twice as a respondent. The researcher also sought the assistance of selected staff of MFI’s in the area who had direct contact with the microfinance institutions and were knowledgeable about their operations in the area.

SAMPLE SIZE

The sample size is a specific or fixed proportion of the population (Hague, 2002). Therefore, the sample size used in this study was 100 representatives from the MFI’s and the beneficiaries. The respondents’ representation was based on an equal representative sample to include MFI’s leadership and staff members and 100 beneficiaries, both men

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and women. Therefore, the researcher selected a sample that is big enough to yield a relatively accurate estimate of the population values, but at the same time can be executed economically and practically.

To be part of the sample, the respondent had to be either a woman or man benefitting from microfinance institutions, or a credit/loan officer in the microfinance institutions operating in eThekwini and surrounding area. The respondent also had to give informed consent and ought to have participated in microfinance institutions during the period at least once. All the respondents complied with the inclusion criteria, especially the informed consent which had to be given, and those that did not consent were not forced to participate.

DATA COLLECTION METHODS

There are two types of data collection methods that could be used by researchers; these are primary and secondary data. For the purpose of this study, the researcher used only a primary source of data gathering.

 Primary data collection

Primary data refers to the field data collection done directly or indirectly by the researcher on a phenomenon or subject (Ryerson, 2010). It is data that has not been collected before (Wiid & Diggines, 2009). The researcher preferred the primary data over the secondary data source because it is best suited for the quantitative survey technique adopted for the study. Therefore, the primary data in this study comprised mainly data collected using an MS Excel-based survey questionnaire administered to the research stakeholders in eThekwini around areas.

The strengths of this method are that a wider range of data can be obtained through surveys than through observation or experimentation; quantitative data research is a lot more objective and reliable as opposed to a qualitative data approach. Most importantly,

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this method is quicker and cheaper than observation and experimentation. Its weaknesses are that validity possibility is very low and also requires special skills. Based on the strengths of the approach mentioned above, the data is good enough for the research purpose.

37 DATA ANALYSIS

According to Ghauri, et al. (2005) analytical procedures involve techniques to

conceptualise and analyse data that result in theories and findings. Sekaran and Bougie (2010) supported this position and added that three phases are involved in data analysis, namely data reduction, data display and drawing and verification.