In this research, data analysis is categorised into separate techniques; secondary data analysis, multiple- case study analysis and realistic evaluation analysis.
5.9.1 Secondary Data Analysis
The information gathered from the secondary data collection will be the subject of document analysis. Therefore, information from the secondary sources will be conceptualised, coded and categorised accordingly. Following Pole & Lampard (2002:p15), the literature will be assessed by going through a process of indexing and coding, and from there be categorised under separate grouping; the essential literature which is likely to be the central point of the research; the important literature which includes the references that might not be the central theme of study; the relevant literature that is expected to be utilised during the process of study; the supporting literature which may be related to the study; and the irrelevant literature which may not be relevant to the research. In this approach, the document analysis approach is not only conducted for the literature review, but also throughout the empirical work.
In a qualitative design research, case study method was chosen as a research strategy. The research intends to benchmark the performance of programmes. Using the conceptual framework outlined in Figure 5.7 above, two UK case studies were selected, for examples, National Park A and National Park B. Both parks are equivalent in terms of national scale. Park A is the main subject, while Park B becomes the comparative measure (or benchmarking partner). Additionally, Park B must be of an exemplar or demonstrates best practice in terms of programme delivery, in order to ensure that Park A can gain lessons from its practice. The evaluation process is divided into two parts; Stage 1 is designed to benchmark case studies in terms of its performance and practice, while Stage 2 is designed to benchmark both case studies using the realistic evaluation
In Stage 1: The first process is to study both parks separately and classify the information of both case studies according to the CMO configurations, so as to enable the efficiency of realistic evaluation to be performed during the assessment. The second step is to benchmark the performance of Park A against Park B. The outcome of this process is then used in Stage 2.
In Stage 2: Results from the benchmarking exercise in Stage 1 are then re-analysed using the CMO configurations (Realistic Evaluation). Findings from Stage 1 are compared between Park A and Park B. Recommendations for this evaluation process are separated into two; (1) Specific recommendations in terms of programme delivery for urban regeneration initiatives delivered through national parks; and (2) Recommendations on the application of benchmarking and realistic evaluation as a combined tool in assessing the performance of national parks.
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In the case of multiple-case study, since the study involves in-depth interviews, therefore it is proposed that the analysis of data will use the technique of transcribing the interviews (see McQueen and Knussen (2002). Since there were surveys involving questionnaires, therefore, the use of computer software to analyse the data is seen as an important tool. In general, the information is coded, and categorised according to topics, then analysed.
For comparative examination, this research applies the comparative method as a methodology of comparative analysis. Adhering to Warwick and Osherson (1973:p51) “the comparative method is a substitute for experimentation, and is employed in the analysis of historical data, the number of cases of which is too small to permit statistical manipulation”. This method is most often required in the comparative analysis of national units, which are few, but it may also be used in comparing regions, cities, communities, and other sub-national units. Because of the restricted number of cases, the investigator relies on systematic comparative illustration.
In response to that, the study therefore formulated rationalisations by having logical control of parameters and operative variables. The approach was to analyse the data through positive and negative, whereby positive comparative method will be in the form of “identifying the similarities in independent variables associated with a common outcome, while negative comparative method will include the identification of variables associated with divergent outcomes” (Warwick & Osherson, 1973: 52).
In relation to data analysis for the interviews, the research adopts the suggestion provided by Cresswell (2009:p185) which the researcher finds practical and pragmatic (see Figure 5.9 below). From the illustration (Figure 5.9), it is observed that the primary data are organised accordingly and placed under the coding system. The structure suggested that any forms of primary data including transcripts, or notes and images can be analysed through the same process. The procedures are carried out in sequence which starts by arranging the raw data and reviewing all the information acquired. The following task is to classify the data into a coding system, either by separate topics or subjects. From there, the groups are combined and assessed according to their correlation, and finally, to translate the results by means of specific themes or descriptions. However, during the process, Creswell also advocated the process of confirming the precision of the information. This was highlighted in the course of assembling the raw data and at the end of the analysing upon obtaining the findings. It was then decided that this systematic approach be adopted for the research.
Since the research also involved interviews, the research utilised the NVivo Software to manage and analyse the data. The function of this software enables the qualitative data to be categorised into separate
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themes and patterns. This is also known as coding as it abbreviates the immensity of data into manageable sets of data (Coffey and Atkinson, 1996). To Burns (2000:p432), “the first stage in analysing the interview data is coding”. An advantage of coding is that it reduces the data into more focused data in accordance with the research purpose. Coffey and Atkinson (1996:p35) claim this as “data-reduction task” and elaborated that “Segmenting and coding the data in that particular way would at least allow us to characterise what each stretch of the interview was about in terms of general thematic content, in this instance relating directly to the topics of the interview elicitations and responses”. Interestingly, Coffey and Atkinson (1996) argued and stresses the technique of coding for social science field is as important as other disciplines even when many thought that that coding is meant for quantitative data:
“It would be as much a mistake to think that coding is an activity that is universally understood across the qualitative (or indeed quantitative) research spectrum. Rather, the term coding encompasses a variety of approaches to and ways of organizing qualitative data” (Coffey and Atkinson, 1996:p26-27).
Additionally, Coffey and Atkinson (1996:p29) added:
“Coding qualitative data differs from quantitative analysis, for we are not merely counting. Rather, we are attacking codes as a way of identifying and reordering data, allowing the data to be thought about in new and different ways. Coding is the mechanics of a more subtle process of having ideas and using concepts about the data”.
It is therefore determined that, the interviews’ transcriptions were classified into different themes and common ideas, as well as similarities and differences. This researcher felt that the coding tool provided by NVivo is very useful and the approach itself is essential as the process facilitates the research with main ideas and their interpretation, as well as aiding the concluding part.
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Figure 5.9: Data Analysis in Qualitative Research Source: Extracted from Creswell (2009:p185)
5.9.3 The Realistic Evaluation Analysis
As elaborated in Chapter Four, the realistic evaluation uses the CMO configurations to assess a programme. This framework justifies the context, mechanisms and outcomes of a programme through its exploration of relationships and causal effects. The way it is analysed is through descriptive and explanatory technique. The ‘CMO configurations’ in this sense is already a tool of analysis.