Questionnaire

Questionnaires are a survey technique that is used to collect data in which individuals are asked to respond to the same set of questions in a predetermined order Saunders et al., 2009:360). It is considered a powerful tool which is able to yield the maximum amount of information in the most efficient way (Gummesson, 1991). The advantages of a questionnaire include that they need less skill and are less sensitive to administer than face-to-face methods of data collection (Saunders et al., 2007).

Gummesson (1991) suggests that it is enough to use only questionnaires as the data collection method although is often better that it be linked to other methods in a multiple–method research design. For instance, a questionnaire used alongside a semi- structured interview to contextualise individual perspectives. Questionnaires need to be completed by participants either by themselves or with a guiding hand (Glăveanu, 2008). Unlike interviews, questions in a questionnaire must not stray from the schedule.

Saunders et al. (2007) views that questionnaires work best when questions are standard and are suitable for use in explanatory and descriptive research designs. Descriptive research that discovers attitudes and opinions through questionnaires are useful for identifying the variability of phenomena while questionnaires in explanatory or analytical research are useful for examining correlation relationships. According to Saunders et al. (2007), however, questionnaires see limited use in exploratory research or when there are large amounts of open-ended questions. He consider it as a less useful instrument for the study of processes due to the rendering of cross sectional data as happening at one point in time rather than perceiving the social reality as a process.

Since this research is also an exploratory and descriptive research in terms of its design, the questionnaire is considered as one of the main research methods in collecting the required qualitative data (in the form of opinions and perceptions) to respond to the identified research questions.

Page 91

It should be noted that there were difficulties in getting responses from the sampled banks’ employees through questionnaires due to reasons such as confidentially, time constraints, unwillingness, etc. Apart from this, due to budget constraints, convenience, easy access, the method being flexible and hassle-free, and freedom (no obligations imposed on respondent) an unobtrusive method of disclosure analysis is chosen.

To ensure that the sample is representative, there are certain techniques to be considered such as the when, type, and choice of questionnaire. The type of questionnaire will affect the number of people responding to the questionnaire. For instance, interviewer-administered questions will usually have a higher response rate than self-administered questionnaires. The size of the sample and the way the sample is selected affects the credibility or the confidence of the collected data as well as to what extent their responses can be generalized. Furthermore, longer questionnaires are normally used in a structured interview. In essence, the choice of questions in the questionnaire will have to be aligned with the research questions and objectives of the study.

4.5.1.2. Sampling

Questionnaires need to be precisely designed to be able to provide answers to the research question. This is because it almost impossible for a researcher to collect data a second time as it may be difficult to find the same respondents again, especially if they are anonymous.

Sampling is used in research to determine the characteristics of a population as it is usually impossible to use the whole population as a sample (Stangor, 2011). This makes it difficult to determine the true characteristics of the population (Stangor, 2011). In evaluating research, Black (2002) lists several groups of participants to be chosen for participation in a study: a whole population, a randomly selected sample, a purposely selected sample from a population, or volunteers and unspecified groups. There can also be combinations of groups to select the participants from.

In exploring the uniformity or diversity of the frameworks adopted by IBs, the study utilises a sampling approach to collect data on CG and RM-related matters. It uses a combination of randomly selected groups as well as a purposely selected group

Page 92

sample. This is because the random samples are the ones from the operations level who can provide data pertaining to the implementation of corporate governance and risk management practices. The purposely selected samples, on the other hand, are the individuals who are in between the levels of senior management and the board of directors as they are expected to be able to provide data specifically on policy matters vis-à-vis the ones that deal in the operation aspects.

Sampling can be done either through probability sampling or non-probability sampling. In probability sampling, everyone in the population has a known chance of being included (Stangor, 2011). Probability sampling is more likely to be representative. However, samples may only become truly representative if two conditions are met. Firstly, there must be more sampling frames that list the entire population of interest and secondly all the selected individuals must then be sampled (Stangor, 2011). If these conditions are not met it will lead to a sample bias (Stangor, 2011). The probability methods can be classified into: simple random, systematic random, stratified, and cluster sampling while non-probability sampling includes snowball sampling and convenience sampling (Stangor, 2011).

In non-probability sampling, the sample frame does not exist. The snowball sampling of a non-probability sample is used when it is difficult to reach members of the population. Even if a complete sample frame is available, if all members of the random sample frame do not participate, it risks creating a sampling bias. Other types of non-probability sampling include: quotas, self-selection, convenience, and purposive sampling (Saunders et al., 2009:236). However, purposive or judgemental sampling requires judgement in selecting cases that can best provide answers to the research questions (Saunders et al., 2009:237). Thus, even though this sampling runs the risk of not being representative, it benefits by being able to focus on key themes as it selects cases depending upon its research questions. It thus allows for homogeneous sampling when the survey is focused on a group in which all sample members are similar. This provides an in-depth analysis of the issues.

This study uses the non-probability sample of purposive sampling. Ideally the whole population of IBs could best be used to examine the CG-RM relationship. However, this is not possible hence the research uses purposive sampling in order to be able to reach potential respondents in an efficient manner. In this case the sampling is chosen

Page 93

regardless of its location but fully based on the judgment of whether the sample is a financial institution that provides Islamic products and whether the individual respondents are well aware of the CG and RM issues in their respective IBs. Thus, he/she should be able to provide answers for the research questions. Therefore, questionnaires were sent to the relevant departments in a number of IBs who were identified through different sources as the best people who were able to respond.