Validity and reliability of data are important if the research is to fulfil its objectives. Validity refers to ‘an estimate of the accuracy of an instrument or of the study results’(Peat et al., 2001, p.105). In other words, do the questions in a questionnaire meas ure what they are intended to measure? There are many types of validity that a researcher must take into consideration, including external validity, internal validity etc. Reliability refers to ‘the degree to which a measure of a concept is stable’ (Bryman, 2008, p. 698). This implies that the same results must be obtained if the question is put to the same respondent at different times, provided that there are no changes in the facts about the subject (Proctor, 2005, Silverman, 2005).
5.11.1 Data Quality and Reliability of Quantitative Analysis
In a research study, data validity and reliability are important to ensure that interpretation and conclusion of the research are accomplished. In a survey, pilot testing of the questionnaire is the best technique or tool to overcome validity and reliability issues (de Vaus, 1990, Bryman and Bell, 2003). To ensure validity and reliability of the questionnaire, the researcher was careful with the wording of the questionnaire, particularly the Thai version. Pilot testing and comments from experts gave the researcher the chance to revise the questionnaire. Furthermore, the research assistants were trained to ensure that they fully understood the contents and what each question was intended to measure. Cronbach’s Alpha test was employed to test internal consistency of itemised types and Likert scales. The results show that the Cronbach’s Alpha coefficient for the respondents
129 groups was .828. This is higher than 0.7 which is suggested by most researchers (de Vaus, 1990, Pallant, 2004).
5.11.2 Data Quality and Reliability of Qualitative Analysis
The researcher ensured validity of the data by using careful wording during the interview and attempting to find another case to test the main provisional themes and sub-themes. This is referred to as the constant comparative method (Silverman, 2005). The number of interviewees, which was forty, was sufficient to identify the repeated themes. Reliability can be ensured by tape-recorded interactions (Silverman, 2005). The researcher made notes of relevant reactions by the interviewees during the interview sessions and ensured that the notes were available when transcribing the interview records. Silences and rephrasing, for instance, were recorded in the notes. These notes were also referred to in the coding process using NVivo.
5.12 CONCLUSION
This chapter has thoroughly discussed the research framework and methodology employed in this research. Firstly, it describes the research framework and questions developed in order to meet the research objectives. The research design and research strategy are then discussed. The research adopts a combination of quantitative and qualitative methods in which primary data are collected through a questionnaire-based survey and semi-structured interview. Additionally, secondary data are also used in the analysis in order to meet the research objective on outreach and sustainability of Islamic microfinance programmes. This is followed by a discussion on instrument design, sampling process, pilot testing, data collection, data quality and reliability, and data analysis in which non-parametric techniques are preferred. Based on the research design and planning, the collected data are found to be appropriate for statistical analysis, which is illustrated in detail in the next chapters.
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Chapter 6
EXPLORING DEMAND FOR ISLAMIC MICROFINANCE
6.1 INTRODUCTION
From this chapter onwards, this study will describe the empirical findings and analyse the research findings of the questionnaire and interviews based on the data collected from the fieldwork in Thailand and the secondary data as defined in the research methodology chapter (Chapter 5). This chapter, in particular, will present and discuss the questionnaire’s items that assess the demand for Islamic microfinance services. It covers the first objective: to identify the factors affecting the demand for IsMF services. This includes a descriptive analysis which will provide readers with some insight into the data and characteristics of the respondents’ profiles, and an inferential analysis which gives a comparative analysis of various identified groups such as gender, age, and education. The results will give useful information on the financial behaviours and needs of IsMFIs’ clients which is crucial for effective microfinance programmes. The data were analysed using SPSS software which is often utilised in social science research in which questionnaire-based surveys are adopted. Descriptive analysis tools employed in this chapter consist of frequency distribution, mean, and standard deviation. As for inferential analysis tools, this chapter employs statistical tools for non-parametric data analysis, including Mann-Whitney U-Test, Kruskal-Wallis Test, cross-tabulation, and logistic regression.
This chapter is divided into three key parts for the analysis. The first part (Sections 6.2, 6.3, and 6.4) describes respondents’ profiles, their characteristics, and their households’ characteristics. It provides an introductory analysis for further analysis in the subsequent sections. The second part (Sections 6.5, 6.6, 6.7, 6.8, and 6.9) focuses on the respondents’ relationship with IsMFIs, ranging from the services they use, purposes of micro- financing, use of conventional financial institutions, their engagement in SMEs, and patronage factors and ranking order of Islamic microfinance services in key events. The third part (Section 6.10, and 6.11) explores various groups of respondents who frequently demand Islamic microfinance services, and predictors of the likelihood of them using these services. This chapter concludes with a summary of the overall analysis and findings.
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