Analyzing the data

The data analysis stage started concurrently with the interview process once a sufficient amount of data had been collected, specifically after having com-pleted four full interviews. My initial approach to analysis was heavily in-spired from grounded theory (Strauss & Corbin 1994). The main features of grounded theory are outlined by Bryman (2012), however, there are many facets not covered. Due to time constraints of this thesis, I could not feasi-bly apply grounded theory in its full capacity, but instead rested on its core tools which are theoretical sampling, coding, theoretical saturation, and con-stant comparison (Bryman 2012). I applied all of them to varying extents, except for theoretical sampling which seemed to require more expertise in theory building skills than I perceived I had during the interview process.

Nevertheless, my purposive sampling strategy seemed to have reasonably as-sured avoiding theoretical oversaturation anyways, which is the main point of theoretical sampling.

As recommended by Bryman (2012), I started the coding process by first reading through the transcripts with a fresh mind and jotting down a few notes. Following that, the coding process continued and generally involved

“a movement from generating codes that stay close to the data to more se-lective and abstract ways of conceptualizing the phenomenon of interest”

(Bryman 2012, p.570). Initially, coding was performed nearly sentence by sentence in an attempt to stay close to the data, however, after struggling to make sense of hundreds of codes, I restarted using some higher level concepts inspired by this initial coding process. Aside from the challenges of dealing with large numbers of codes, it was also difficult to develop meaningful con-cepts that fit the research question. Many coding iterations were required to develop a smaller set of codes which reasonably fit the research question and data. Although I often felt that I was going in circles during this process, I eventually discovered this was likely the grounded theory process of constant comparison that Bryman (2012) had referred to.

The process of developing a final set of codes and organizing them into larger categories generally resembled the approach by Gioia et al. (2013).

Parts of the transcripts were assigned a code, and these codes in turn linked to

32 CHAPTER 3. METHOD a larger overall category. This approach helped to manage the large amounts of qualitative data collected. A few examples of how the raw empirical data was transformed into codes, and subsequently categories, is illustrated in Figure 3.1.

Figure 3.1: Examples of coding structure

The majority of this intensively iterative coding process was performed during analysis of the first four interviews. After that point, I used the con-cepts developed to date to thematically code (Bryman 2012) the remaining interview data as it was collected. Essentially, the empirical data collected from the final three interviews was coded strictly using the set of codes refined during analysis of the first four interviews. This was a more efficient way to process the remaining data which was necessary considering the time con-straints. Unfortunately, it also represented a departure from the principles

3.2. RESEARCH METHOD 33 of grounded theory. On the other hand, about 40% of the qualitative data benefited from the detailed coding process which could have been enough to theoretically saturate the main underlying themes of the topic. Nevertheless, this remains a potential weakness of the research methodology imposed by realistic time constraints.

The software NVivo 12 was utilized throughout the analysis phase, which I generally found to be a useful and efficient tool. The process of learning the software was relatively smooth, although my experiments with some of the more advanced features (e.g. automatic coding) either failed in technique or the features themselves proved to not be considerably useful. For example, the automatic coding tool generated a set of codes that did not seem intu-itively connected or reflective of the main themes I had envisioned through conducting the interviews. Nevertheless, the software properly served its main purpose which was to assist in organizing the complex web of codes and transcripts inherent in the analysis phase. I predominantly used the software to keep track of different versions of coding sets, all of which I manually coded myself.

The concepts developed during the analysis stage ultimately ended up shaping the structure of Chapter 4 (Empirical data). The third level sec-tions in that chapter represent the concepts developed, and the second level sections represent the categories that the concepts were organized into (e.g.

contextual factors, individual factors, etc.). Organizing the chapter in this fashion facilitated presenting the empirical data because all of the relevant points could be easily accessed through NVivo 12 during the writing pro-cess. Furthermore, the process of writing out the empirical data inherently involved comparing data between individuals and between case firms, which ultimately inspired the propositions and supporting theory introduced in Chapter 2 (Theoretical background). As mentioned in Chapter 2 (Theoretical background), the structure of that chapter is based on an adaption of an ex-isting telework model rather than the empirical categories developed through the coding process, although they are fairly similar.

The process of analyzing propositions generally involved searching the available data from Chapter 4 (Empirical data) for supportive and contrary points. For each proposition, the empirical data was organized based on whether it supports the proposition, disproves it, or has no impact. This provided a clear overview for assessing each proposition, and enabled writing an engaging analysis. In addition, it is worth mentioning that some iter-ation was involved as the impliciter-ations of the results on theory was being rationalized, which in some cases required returning to the empirical chapter to present additional data related to a nuanced theoretical point. Overall, I attempted to maintain a balanced analysis and discussion by constantly

34 CHAPTER 3. METHOD challenging both sides of an argument and finding rivalry explanations (Yin 2009). Hopefully this reduced bias in the research, however, it is impossible to completely remove bias due to the nature of social research.

The research strategy, design, and methods employed in this thesis have now been explained, and the next section aims to evaluate the quality of this research setup.