This final section in the methodology chapter describes how the data from interviews and relevant documents were analysed.
4.6.1 Step 1 – Screening the data
Familiarisation with the case study is an essential precursor to the construction of explanations for changes in commercialisation practice. First, I examined whether learning took place at all in the particular case. I analysed whether (1) commercialisation staff learned through interactions with members of their internal community of practice, (2) whether they learned from their NOPs, and (3) whether they learned through interactions with other kinds of professionals, such as researchers, patent agents, consultants, etc. The presence or absence of learning is reported for each case. Second, I identified all changes in commercialisation practice reported by interviewees. Third, I explored the strategic practices of management in each case.
This initial stage of case study analysis was completed with the help of NVivo, a computer assisted tool for qualitative data analysis. The tool was used to code and categorise textual data collected in the semi-structured interviews and in relevant documents. The guidelines provided by Bazeley (2007) were followed to make the best use of the tool. An initial set of codes reflecting theoretical concepts (learning in COPs, NOPs, across COPS, strategic practices of management, commercialisation practice and changes in practice) was created. In the course of the analysis, more precise codes were created.
4.6.2 Step 2 – Explanation building
Yin argues that “to ‘explain’ a phenomenon is to stipulate a presumed set of causal links about it, or ‘how’ and ‘why’ something happened” (Yin, 2009: 141). Yin (2009) suggests that the pattern matching technique is one of the most desirable techniques for case study analysis and recognises the ‘explanation building’ technique as a special type of pattern matching. The ‘explanation building’ technique is appropriate when the explanation of the phenomenon is built upon some theoretically significant propositions, but the final explanation is not fully stipulated at the beginning of the study.
This technique is suitable for the present study since I have made some theoretical proposition for explanations of how and why changes in commercialisation practice come about, and also argued that the final explanation of changes may be more complex than my initial propositions would suggest. In particular, I proposed that learning in
COPs and NOPs initiated by COP members leads to incremental changes in performance of existing work activities (in ‘the how’ and ‘the what’). I have argued also that radical changes in what activities are performed result from learning in COPs and across COPs spontaneously initiated by COP members or from learning in COPs instigated by management. These propositions were derived from previous empirical studies. Common sense dictates that management may also play a role in triggering and shaping situated learning that leads to incremental changes and radical changes in how.
Thus, while my analysis is based on some theoretically sound propositions, I develop a final explanation of changes in practice through an iterative process of ‘explanation building’.
Yin (2009) explains that explanation building comprises the following iterative steps:
“Making an initial theoretical statement or an initial proposition about policy or social behaviour
Comparing the findings of an initial case against such a statement or proposition
Revising the statement or proposition
Comparing other details of the case against the revision
Comparing the revision to the facts of a second, third, or more cases
Repeating this process as many times as is needed.” (Yin, 2009: 143, emphases in the original)
This iterative process, which increases the internal validity of the study, was adopted for the analysis of the six case studies. At the end of each case study, a number of hypotheses about how and why changes in practice occurred were generated, and tested in the succeeding case study. This data analysis method follows the logic of
‘falsification’ advocated by Karl Popper as the most rigorous test to which scientific propositions can be subjected (Flyvbjerg, 2011). “If just one observation does not fit with the proposition, it is considered not valid generally and must therefore be either revised or rejected” (Flyvbjerg, 2011: 305). Cases A and B, where I expected to observe radical changes in practice, were analysed first, followed by Cases E and F, where I expected to observe mainly incremental changes. Finally, Cases C and D, where I expected radical and incremental changes, but in different aspects of commercialisation practice, were examined. The cases are not presented in this order, however; their ordering is aimed at highlighting certain similarities and differences across the cases.
This stage of case study analysis also exploited the NVivo software, and was aimed at creating links between changes in practice and their explanations. The software
helped to organise the empirical evidence illustrating how and why changes in practice occurred in each case.
4.6.3 Step 3 – Cross-case comparison
The last step in the analysis was cross case-study synthesis. In accordance with Yin’s (2009) recommendations, each case study was treated as a separate study and the cross-case comparison was aimed at aggregating the findings from all six cross-cases. These findings were combined in order to answer the research questions and to advance our theoretical understanding of the role of situated learning and strategic practices of management in bringing about changes in work practices. I looked across cases to explore whether alternative explanations of changes in practice (see Section 4.3.3) were more compelling than the explanations proposed by the theoretical framework.
5 Institutional context for commercialisation of academic research
In Section 4.3.3 I argued that work practices may be shaped by the institutional context in which organisations operate rather than by situated learning. In order to explore this alternative explanation of changes in KTO’s commercialisation practice, Chapter 5 looks at changes in government policies for university-industry knowledge transfer in the UK, with a particular focus on the first decade of 2000.