Análisis económico de las alternativas propuestas

Thematic analysis is a commonly used method for the processing of qualitative data generated from fieldwork research. Thematic analysis is able to demonstrate data in detail and deal with diverse topics through interpretation (Boyatzis, 1998). It can be applied to many forms of qualitative data collected through a variety of methods. As for this research, it was used as the data analysis technique for the semi-structure interviewing carried out in studies one, two and three. The rationale for its selection is because it allows the data to be systematically interpreted and links the separate analyses of the segments’ theme to the whole meaning of the research. In addition, in thematic analysis there exists the possibility to connect several concepts and opinions that emanate from respondents and compare these with data previously collected from other participants in different situations at different phases during the research (Miles and Huberman 1994; Gibbs 2002; Yin 2010;

Alhojailan, 2012). These features mean that thematic analysis is appropriate for this research because one of the objectives is to compare the design management practices and the perceptions of the strategic value of design between airlines that make good use of strategic design and those adopting the Silent Design approach. That is, thematic analysis facilitates the comparison a large body of diverse data which sometimes overlaps and is conflicting. Furthermore, thematic analysis allows the researcher to code and categorise the collected data into themes. Later the data can be displayed and classified according to contrasts and comparisons (Miles and Huberman, 1994).

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Outline of the Data analysis Procedure

After the data collection was completed for each study, sequentially, the researcher analysed the data collected to build upon the findings of each previous study to develop an evolutionary prototype of the conceptual framework. As already explained the qualitative data analysis covered in study one the customer semi-structured interviews (see Section 3.6.1.2). In study two and three the interviews with design experts and Saudia Airlines employees (see Sections 3.6.2 and 3.6.3) produced qualitative information. For each of these stages of the study, the researcher adapted Creswell’s (2014) proposed thematic process:

1. Arranging and preparing the data for analysis 2. Reading through the raw data

3. Coding to breakdown, simplify and organise the data into relevant categories

4. Using the coding process to create a description of the categories or theme for analysis 5. Representing sub-themes and themes with different techniques, as follows: quotations, narrative texts, a process model, figures and tabulating the differences and similarities to clarify their relationships

6. Interpreting the findings of the research

The Thematic Process Applied to the Qualitative Data

Firstly, the process of organising and preparing the data for analysis was carried out after the researcher had transcribed the recorded interview data. Secondly, she read through the raw data. It was important to read the data repeatedly and re-visit it many times to grasp clearly the narratives of the interviewees before starting the coding. Thirdly, she used coding to breakdown, simplify and organise the data into relevant categories. This stage involved the initial unearthing of common words, which were identified as codes. The small unit of data, which is known as a ‘code’ is ‘most often a word or short phrase that symbolically assigns a summative, salient, essence-capturing, and/or evocative attribute for language based or visual data’ (Saldana, 2013). The coding process can be done with a software program or manually and in this study, the software, MaxQDA, was used to systematically select and simplify the codes that were similar (see Figure 3.10).

Figure 3.10 MaxQDA software use to organise the initial codes. Source: Researcher.

Next the coding process was employed to create a description of the categories or themes for analysis. A coding and grouping of data were complete, a long list of different codes was produced. In this stage the researcher used affinity maps as a visual tool to focus on the broader level of themes by sorting the different codes into potential themes (see Figure 3.11, Appendix C1 and D1)

Figure 3.11 Affinity maps done by the researcher. Source: Researcher.

The affinity maps of the data were reviewed to ensure they were satisfactorily in depth and had full coverage. The themes prepared for the analysis were modified and some were further refined to ensure that they captured the essence of what each was about and the features of the data each theme covered for the data for each study. As a result, a collection of themes and sub-themes were produced. Creswell (2014) recommends the demonstration of the sub-themes and themes with different techniques, as follows:

quotations, narrative texts, figures and tabulating the differences and similarities to clarify

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their relationships and associated complexities (Miles and Huberman 1994; Gibbs 2002;

Yin 2010; Alhojailan, 2012) The advantage of employing various data display techniques is that it can make descriptions of comparisons and similarities more well defined. In this research the researcher used the technique of tabulating the data. Table 3.5 illustrates one example of tabulating the data in this study, for study two for design experts, the table includes the key theme organisational mind-set and lists the nine sub-themes.

Table 3.5 Study Two for design experts, the key theme for organisational mind-set and the nine sub-themes.

Key themes Sub-themes

1.Organisational mind-set

1.1 Appreciation of both strategic and operational contributions of design.

1.2 Support and investment for overall design agendas from senior management

1.3 Strong ambition for Design

1.4 Positive attitude toward change

1.5 Importance of innovation in airlines

1.6 Respect for Design

1.7 Monitoring competitors

1.8 Importance of customer experience and design contributions

1.9 Design as an essential part of business

Furthermore, the researcher then evaluated the themes to make sure that the themes represented the overall text (Miles and Huberman, 1994; Alhojailan, 2012). All the themes were evaluated and quotations that offer evidence, support and validate interpretations (Miles and Huberman, 1994; Gibbs, 2002) were noted. Ensuring the reliability and validity of the analysis will be explained in detail in the next section. By applying the data display technique of tabulating the data the researcher organised (see Appendix B, C and D) and framed the information so that she was able to make links, compare the data and

move towards the final stage of analysis (Miles and Huberman, 1994; Gibbs, 2002;

Alhojailan, 2012). Finally, the last stage of the data analysis process for each of the three studies involved interpreting the findings. The findings were linked by displaying and organising the ideas and thoughts into the evolutionary prototype framework that was presented at the end of each chapter (see Chapters 04, 05 and 06) for each study. This was developed by creating coherent results and drawing structure from the data.

Ensuring the Reliability and Validity of the Analysis

The researcher involved an outside reviewer in the early stage to evaluate the themes that had been identified (see Figure 3.12). The purpose of the outside reviewer was to examine whether or not the themes were compatible with the whole text. An independent reviewer also helps to give more feedback regarding the identified themes from an outside perspective to compare the feedback of the reviewers to build reliability. The outside reviewer was Dr Busayawan Lam and the independent reviewer was Dr Ray Holland, who are experts in the area of design and design management field, which is the area of this study. The key reason for this according to Hosmer (2008, p.52) is to ‘build reliability in theme analysis coding.’ Afterwards the researcher can identify any conflicts regarding the themes or codes that had been added or removed by both the outside and independent reviewers (Miles and Huberman, 1994; Hosmer, 2008; Alhojailan, 2012) (see Appendix B2, B4, C2 and D2).

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Figure 3.12 An example of the corrections of one of the reviewers for the qualitative analysis. Source:

Researcher.