My data analysis is now underway. After reviewing a number of textbooks and checking out video lectures and podcasts on qualitative coding, I finally made the essential step – printed out the first interview transcript. In actual fact, this action alone was a result of deliberation as I was considering using one of the professional computer programs for qualitative data analysis known in academic circles as CAQDAS (Computer Assisted Qualitative Data Analysis Software). As tempting an option as it was, I have eventually failed to make a convincing case for using CAQDAS for my small-scale project (the fact that relevant training events at the university are all fully booked until spring didn’t help either). Yet, CAQDAS (Atlas, Nvivo and Maxqda are the most popular programs) are widely used and loudly praised for the multitude of helpful functions they offer – apart from the major purpose of effective storage, organization, management and retrieval of data, they are also useful for collecting, organizing and citing research sources, transcribing interviews, and so on. Another important advantage of CAQDAS is that they are equally helpful in working with many different types of non-numerical data other than interviews, such as images, videos, web pages, and social media sites. In short, these tools are indispensable for those analysts who are working with vast amounts of data or in large research teams and looking for the ways to facilitate and speed up the analysis process. However, learning how to operate the CAQDAS is itself a time-consuming enterprise, and it is worth weighing the possible benefits of using the software against time and efforts required to master it. Moreover, the majority of qualitative methodologists seem to agree that computer-aided analysis cannot quite replace the old-school paper and pencil method for “there is something to be said for a large area of desk or table space with multiple pages or strips of paper spread out to see the smaller pieces of the larger puzzle – a literal perspective not always possible on a computer’s monitor screen” (Saldaña, 2012, p. 22).
Inspired by the above quote (a mental image of a devoted researcher fully immersed in his data, out of touch with reality in search for the answers to the ultimate questions of life instantly emerged in my mind… is that not the ideal vision we all secretly cherish?), I too decided to go with the more traditional methods and tools – hard-copy printouts, hand-sharpened pencils, and coloured highlighters for a lot of circling, underlining and note-taking activity to be undertaken on the 42 pages of the first interview transcript. The choice of the interview to work on first also was not accidental – I deliberately started the analysis with one of my most interesting and richest cases as I expect it to generate a variety of codes, suggest helpful categories and raise some meaningful concepts and themes. This, I hope, will help me see the big picture emergent from my data and bring it upon the remaining cases to reach a clear vision of each individual life story as well as a holistic understanding of my overarching research concerns.
Finally, before starting the analysis I wanted to choose a specific coding method to guide me through the data. Saldaña’s coding manual presented a dozen of different approaches, and I felt overwhelmed and somewhat lost amidst the unfamiliar terminology and descriptions of methods many of which seemed equally suitable for my study. I have eventually decided to stick with the good old thematic analysis but elaborate it further by applying Emotion Coding, which I found to suit brilliantly both my theoretical framework and key research goals (indeed, human emotionality is one of the key concepts underpinning Margaret Archer’s understanding of how individuals attain distinct personal identities which is precisely what I aim to explore with respect to ethical consumers).
All that was left to do then is to wear my analytical lens and immerse myself into the subjects’ life stories. This is where I currently am in my research, and I will continue to record the progress of my data analysis, with all its pleasures and pains.
Saldaña, J. (2012). The coding manual for qualitative researchers (No. 14). Sage.