Yin (2003a) maintains that data analysis consists of "examining, categorizing, tabulating, testing, or otherwise recombining both quantitative and qualitative evidence to address the initial propositions of a study" According to Yin there are the following analytic strategies for case studies: 1. Relying on theoretical
Because theories are constructed in order to explain and predict and master phenomena. So, in many instances, theories are constructed as models of reality. In a research, a conceptual framework is used to outline the possible courses of action to an idea, it is an analytical tool with several variations and contexts. In developing this, you need to first select the concepts, then identify the interrelationships of each concepts, formulate the definition, and formulate the theoretical rationale. (www.southeaster.edu retrieved 2003 September).
24). According to Yin (2011, p. 307) a case study is: “A study of a particular case or set of cases, describing or explaining the events of the case(s) […]. A case study may rely on quantitative or qualitative data (or both) but usually involves some field-based data.” An important distinction within the case study methodology is to be made depending on the scope of it. The first type of case study focuses on teaching purposes and is therefore primarily used for the illustration of existing theories and concepts. The second type is the research case study.
Research philosophy Research philosophy lay down the background of how researchers understand the world, the choice of research philosophy reflect our knowledge, experiences, preconceptions, and research capability. Thus our knowledge, experiences and etc., which underpin the philosophy choice, will determine our research paradigm, strategy, design and method. (Saunders et al., 2009, p. 128-129). When Bryman describes ontology view, he introduces the objectivism and constructivism as two antithetical dimensions. (p22) However, Saunders 2009 p.119 advocates that positivism can be understood through both ontology and epistemology views.
3.1 Introduction In this chapter the coverage is on the research design and methodology, including sampling, population, establishing rigour during and after data collection, ethical considerations and data analysis. 3.2 Research Strategy This study used quantitative research strategy. According to Newman, quantitative research goes from reviewing and defining directly to developing hypotheses and collecting data. In quantitative analysis, this is called the derivation of hypotheses. “The researcher examines the literature and, based upon this process, he or she derives theoretical expectations, which become the derived hypotheses (Newman, Ridenour, & Ridenour, 1998).
RESEARCH METHODOLOGY: In this section detailed of data ,research design in ordered to test hypothesis After literature review, identifying variables and developing hypothesis and theoretical frame work this section explain what to do and how to do. Research design offers guideline to researcher to gather and analyze data in order to answer research questions (Sekaran and Bougie, 2010). Collis and Hussey (2009) identified methodology as the “overall approach to the entire process of the research study”. Research methodology is focused around the problems to be investigated in a research study and for this reason is varied according to the problems to be investigated. Research philosophy If research reflects the philosophy of positivismthen
Particularly interesting in the view of this study, is the fact that thematic analysis is firmly anchored in constructionist method which examines the ways in which events, realities, meanings, experiences and so on are the effects of a range of discourses operating within society. The study collected both qualitative and quantitative data and these were analysed differently. The quantitative data were analysed using - graphs, pie chart and tables. This was done with the Statistical Package for Social Scientist (SPSS) software. Qualitative analysis involved taking the responses from the respondents, sometimes verbatim to confirm or negate what has been observed from the other
3. Methodology 3.1 Introduction The purpose of this chapter is to outline the methods used in the gathering of data to answer the dissertation question. Limitations of the method, a description of the research tools and why it is being undertaken will be discussed. Research can be defined as “a systematic and organised effort to investigate a problem that needs a solution and encompasses the process of inquiry, investigation, examination and experimentation” (Sekaran 1992, p.4). Methodology is required to answer the research question and fulfil the objectives of the study.
Energies are engaged to systematically develop theory, but the two approaches to the research task is different. The qualitative researcher's emphasis is on the construction of the theory to agree with data, and the quantitative researcher's emphasis is on the testing of the theory to prove. The difference in approach may, in part, be due to the differences in the phenomena being studied, and the questions asked and the techniques considered appropriate for confirming or refuting the conjecture (Morse, 1996). Qualitative research requires methodological versatility; researchers have to create the knowledge fitting their research group through any of numerous strategies that depends on design, and therefore have an extensive knowledge of social science theory, to interact competently with others, and persistently focus on objective, and single-mindedly commit to research. He/she, the researcher must constantly distinguish between another's world and that of the participant researcher, and yet become close enough to the lives of another that it be both experienced and analyzed
The questions should be broad and loosely structured, following the intent of the research questions. Next, the interview questions are accompanied by a list of possible sources of data. The literature was revisited between interviews to gain a better understanding of new data. Clear conceptualizations assisted in taking definitions into the study, and combined with the other sources of data, comprised the mass of data available to study the phenomenon of interest. Thinking in metaphors, and creating simplistic models and thematic maps were essential activities in data management.