160 likes | 176 Views
In this lecture, Geoff Walsham discusses techniques for analyzing qualitative data, legitimizing analytical approaches, constructing contributions, and generalizing from interpretive studies.
E N D
Analysis and Contribution Geoff Walsham Lecture 4 of Course on Interpretive Research in IS - Oslo University
Contents of Lecture 4 • Impressions and themes • Analyzing all your data • Qualitative data analysis techniques • Legitimising your approach • Constructing a contribution • Generalising from interpretive studies
Impressions In addition to field notes, I normally write a personal comment on the interview and the interviewee. Here is one from my colleague Michael Barrett: ‘The meeting started off on a very cool note with X being frank and open with me about his feelings on our meeting. He kept on repeating … that he had to protect his staff from numerous requests made of them from the centre and regions (me being one of them). He was a friend of Y (my contact) but ….
Themes I also generate sets of initial themes from my field notes as a basis for reflection, theorising, and interaction with my co-researchers (if any)
Brazil Country Office - Some Themes Background • Internal comms department of 4 people • External comms handled by PR agency The software package • Little use of anything locally • Except for head office intern - to see what is happening back at HQ Functionality issues • Slow • Messy interface/would like to customise Organizational changes • None as yet • Not clear what are expectations on the local office • HQ ignores Latin America (markets too small)
Analyzing All Your Data • Best tool for analysis is your own mind and that of others • So read your data carefully and then read it again • Make data/theory links as discussed earlier • Try your ideas on others through working papers, conversations, seminars
Qualitative Data Analysis Techniques(e.g. Nudist) • Method for linking themes to specific pieces of text in your notes and transcripts • But very time consuming (displacement activity?) • Doesn’t replace the need for thought • And can tend to ‘lock you in’ to one way of looking at the data
A Warning about Klein and Myers (1999) • Certainly valuable to think about your work in relation to the principles • But ‘a particular study could illustrate all of our suggested principles and still not come up with interesting results’ • Don’t merely say: ‘I have applied the principles’ • Do say: ‘Here are my interesting results’
Constructing a Contribution • Who is your audience (or audiences) • To what literature are you aiming to contribute? • What do you claim to offer that is new to the audience and the literature? • How should others use your work?
Example: Klein and Myers (1999) • Key audience: interpretive researchers wanting to reflect on their approach and defend their work • Literature: interpretive work in IS • Claim to offer: Set of principles (based on hermeneutics/pheneomenology) • Use by others: ‘In fact, authors may find it useful to refer to the principles when their work is submitted for peer review’ (87-88)
Generalizing from Interpretive Studies(Walsham 1995) • Development of concepts • Generation of theory • Drawing of specific implications • Contribution of rich insight
Development of Concepts • Zuboff (1988) - concept of ‘informate’ • Walsham (2004) - concept of knowledge communities: ‘are a complex network of sense-readers and sense-givers, taking action, reflecting on it, making representations based on their tacit knowing, ‘reading’ others’ representations, and taking further action in turn’
Generation of Theory • Theories of organizational consequences of IT - Orlikowski and Robey (1991), Jones and Nandhakumar (1993) • Walsham (2004): A basic model of communication with a sociological complement
Drawing of Specific Implications • Relationship between design and development and business strategy - Walsham and Waema (1994) • Walsham (2004): on incentives and disincentives for knowledge ‘sharing’; on forms of representation etc.
Contribution of Rich Insight • Suchman (1987) - limits of machine intelligence; differences between plans and prcatical actions • Walsham (2004) - weaknesses of the ‘knowledge as object’ literature; deep meaning of tacit knowledge