Creating environmentally friendly office spaces

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Case 13e: Creating environmentally friendly office spaces
Catherine Cassell, University of Leeds and Bill Lee, University of Sheffield
Stephanie is a part-time student conducting a Masters in Management at a UK
university. Stephanie’s research project is focused upon how organisations can
make their office spaces more environmentally friendly, and what the barriers to that
process are. As a committed green activist, Stephanie has relished the chance to
investigate this issue in two separate international locations. One of these is her own
organisation which is a branch of a large multi-national bank, and the other is in a
New Zealand government office where she had the opportunity to interview staff
when she was in Wellington on vacation. Stephanie decided she wanted to do two
comparative case studies of how the different organisations approached
environmental issues so her data comes from a range of different sources. She has
interviewed and audio recorded 10 employees at each of the different locations
about their views and transcribed these interviews. She has also collected
documents that relate to the different company policies and practices regarding
environmental issues. Furthermore she has spent a week conducting participant
observation in both offices on the everyday practices around recycling and other
environmentally friendly practices. As part of this she has made extensive field notes
in her research diary.
This is the first time that Stephanie has conducted any qualitative data analysis and
she is concerned to find an appropriate method that will enable her to draw upon the
three different sources of data she has across the two case studies. Initially it all
seemed a bit bewildering and she was unsure where to start. In her research
methods lectures her tutor had talked about three different types of qualitative data
analysis as examples of the variety of data analytic processes available. These were
content analysis; narrative analysis; and thematic analysis using templates; but
Stephanie was unsure about which of these would be appropriate in her case.
Initially Stephanie considered how she could use content analysis for this data. She
thought about how she could draw up a codebook and the initial terms that she could
use. Words and phrases such as recycling and turning off lights were typical of the
phrases that could go in the codebook. She could then go through her interview
transcripts, documents and research diary to see precisely how many times each of
these words was used. Stephanie designed what she thought was an appropriate
codebook, but after coding a couple of interviews, she began to worry about
precisely what this kind of analysis would give her. Specifically she had two
concerns. One was that it might simplify the complex data that she had, in that
everything would be reduced to counting terms rather than addressing meanings
about issues. Secondly, she felt that she would lose some of the sense of passion
and commitment that came through in the interviews when people talked about
environmental issues. This was particularly true in her experience of the New
Zealand interviewees.
Given these concerns Stephanie then considered how an analysis of the narratives
in the data may be helpful. In reading and re-reading her data she had been
interested to see that there were some underlying narratives that came through
particularly in the interviews and the documents. One of these was the way in which
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interviewees would draw upon the consequences of climate change in how they
talked about their own environmentally friendly practices. There was also an ongoing
reference to being part of some collective or community that has some form of
shared responsibility for the environment. Stephanie felt that the use of narrative
analysis might particularly enable her to identify this shared sense of what
environmentally friendly practices were about. However, despite being potentially
useful she had two concerns about going down the narrative analysis route. One
was that she wasn’t sure how the data from her own research dairies could be used
in this kind of approach. Where would it fit? Her observations had focused upon
practices, rather than what people talked about. Secondly, Stephanie wasn’t sure
how this kind of narrative analysis would help to address her research question. A
narrative analysis couldn’t comprehensively address the question of the various
barriers that might exist in both the organisations.
Eventually Stephanie settled upon a template analysis for the analytic process.
Firstly, she designed a set of themes for the template. She then coded the interview
data into those themes in line with the processes of template analysis (King, 2004).
As part of this process Stephanie soon realised that not every piece of data could
clearly be fitted into one theme or another, and in some places she had to create a
new theme or splice two sub-themes together to accommodate new data. Therefore
at the end of the interview coding process she was surprised that the template
structure was somewhat different than it was when she originally started. She then
remembered her tutor’s advice that she should keep a copy of the original template
and the revised template so that she could account for changes she had made along
the way. These were, after all, important analytic decisions. Stephanie was surprised
how easy it was to then code the data from the participant observation and her
research diary into the same template. She was pleased that this process meant that
she could see all the data from the different research methods under the different
themes in the template. So, for example, the data on what people said in interviews
about paper recycling; what the company policy was about paper recycling; and
observations on what people did about paper recycling, were all in the same part of
the template.
Although Stephanie felt a great sense of satisfaction once all the data had been
coded, she realised that there was still quite a lot of work left to be done and that the
processes of interpretation were only just beginning. She studied her template
carefully to see what patterns there were within the various themes and what
conclusions she could make. However, there was a nagging doubt in her mind that in
coding all of the data into the same template she had somehow lost sense of how to
identify differences between the two organisations in their practices. Thinking about
this she decided that interpreting the data from the full template would help her
answer her overall research questions, but in order to be able to evaluate potentially
subtle differences between approaches in the two countries she might also have to
have to separate the UK and New Zealand data and have two identical templates,
one containing the UK data and one containing the New Zealand data. After
constructing these templates Stephanie felt more confident about summarising the
different approaches that the two separate organisations took towards the greening
of office space, and the underlying differences between the two countries that might
underpin this. Stephanie now felt more confident that as well as addressing her
research questions she had something interesting to say from her international
comparisons.
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Questions
1. Did Stephanie organise her template analysis to make best use of her data?
Could she have organiszed the template analysis differently?
2. We know that Stephanie conducted research in her own organisation and that
she is a committed green activist. Should she have taken these issues into
account as part of the analytic process and if so, in what ways?
3. What other forms of qualitative data analysis could Stephanie have used and
how would these have enabled her to address her research questions?
References and further reading
Cassell, C.M. and Symon, G. (2004). Essential guide to qualitative methods in
organizational research. London: Sage.
King, N. (2004). Templates in the thematic analysis of text. In C.M. Cassell and G.
Symon (Eds.) Essential guide to qualitative methods in organizational research.
London: Sage.
Miles, M.B. and Huberman, A.M. (1994). Qualitative data analysis: an expanded
sourcebook. Thousand Oakes: Sage. 2nd edition.
Nadin, S. and Cassell, C.M. (2004). Matrices analysis. In C.M. Cassell and G.Symon
(Eds.) Essential guide to qualitative methods in organizational research. London:
Sage.