Interview Data

4.3.1 Data Analysis Procedure

A systematic procedure was formalised before analysis of the data took place. This approach was taken in order to guide the research down a path of rigorous methodology, with the aim of achieving the research goals of this project. By adopting a pre-ordained methodology, assurances can be made that:

- Each data set is treated in the same manner.

- The focus of the analysis lies on the appropriate aspects of the data, relevant to the

research goals.

- The extracted themes are appropriate to the scope of the research project.

Open-ended interviewing techniques elicit a large quantity of data which will include in it elements that are highly relevant to the subject, but also elements of lesser interest and even those irrelevant to the focus area. A good analysis should have provision for identifying the relevant portions of the data and dealing with them appropriately, but also a method of screening those elements of lesser relevance to ensure that an important connection is not overlooked or lost during codification.

With this in mind the strategy for data analysis was formed, using the recommendations of Yin (2009) as the primary reference. The most preferred strategy is one that relies on the original objectives and theoretical propositions that were set out at the beginning of the research project. The extraction of meaning from the data must be guided by the same factors that provided the impetus for the initial data gathering phase. Therefore the codification of data was orchestrated to expose those elements that have appropriate relevance.

In addition to this, a descriptive approach was utilised as much of this research project is performed under descriptive case study methodology. The definitions and delimitations of scope (section 1.5) serve to outline the focus and depth of the cases, and provide the theory of

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what is important to describe when performing the research. This “descriptive theory” is the criteria by which the data is analysed in a descriptive case study (Yin, 2003).

Fig. 3 presents the procedure by which the data was handled and the aforementioned strategies applied. DISCUSSION ANALYSIS CODIFICATION Transcription of interview data

Cross case analysis Compare findings between cases, develop list of overall prominent

themes

Contrast respondents views on overall themes and sub-themes, areas of agreement/disagreement Summarize

to a simpler level of detail

Identify major themes, key points and comments within each

interview Analyse each respondent’s view on themes. Build theory from responses

Cross reference with computer analysis

Discussion on reasons for agreement/disagreement – relate

to individual context of each enterprise, and also to overall

product development space

Iterate

Figure 3 Data Analysis Procedure Source: Developed for this research

The first step was to transcribe the interview data. All interviews had been recorded so that every comment could be fully captured, and sentiment retained for later reference. Verbatim transcription is not necessary in this instance, nor is it preferable as human speech contains many features that are not directly codifiable. Figures of speech, colloquialisms, and

hyperbole, for example, make literal extraction less desirable, as well as implied content that requires the listener to fill in the gaps by subconsciously analysing the speakers tone, body language and other natural communication traits. The data was therefore put into text through careful extraction of meaning from the interview recordings. The respondents wording was retained preferentially, but where necessary their intentions were conveyed through terminology of the type that is commonly used in Product Development literature. By iteratively summarizing the raw interview data as described during codification, there is opportunity to identify and capture the pertinent elements whilst reducing the volume of information to an observable size. Thus the full content of the data is reviewed, and the relevant themes are distilled from raw data down to a form that is appropriate for theory building within an exploratory study.

The main analysis itself began with the identification of the major themes that emerge from each interview, consisting of the key points and supporting comments that the entrepreneurs

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offered. Initial theory building was then carried out on the individual results of each case. The themes of each case are then brought together and a cross-case analysis is undertaken, which begins with overall themes being developed from the data of all cases combined. The findings are cross-referenced with those generated by computer software analysis, to provide further screening for relevant items. Analysis is then undertaken which contrasts the overall emergent themes with those of the individual cases, and areas of agreement or disagreement between cases. Finally, the connections that have been identified are discussed with reference to the companies, the environment and situation they operate in, and how the results relate to product development theory. The summarised data from each case is shown in section 4.6.2, and discussion resulting from this analysis is offered in section 4.7.