Transcript IS8004 – Seminar 2 Types of Qualitative Data And Analytical Techniques Qualitative Data Types Interviews Notes and observations Diaries Documents User-generated data Emails/SMS/IM/Wiki/WeChat.

IS8004 – Seminar 2
Types of Qualitative Data
And Analytical Techniques
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Qualitative Data Types
Interviews
Notes and observations
Diaries
Documents
User-generated data
Emails/SMS/IM/Wiki/WeChat
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Interviews
Structured; Semi-structured; Unstructured
Protocols
Mediated
Telephone, IM, Email, WeChat, …
Un-mediated
Face-to-face
• Individual
• Focus Group
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Interview Protocols
A protocol here refers to a plan for the interview
Which topics, themes, questions you want to ask
How to start? Open and closed questions?
Interview or conversation?
Free-style or very structured?
There are some similarities with surveys.
You may not get a second chance to ask, so…
How will you record the interview?
Handwritten notes? iPhone? MP3?
It is best to transcribe notes asap, or they get forgotten.
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For Example 1
I am interviewing the CEO of a hotel chain in
connection with knowledge management.
Most likely I will start off by asking the CEO to talk
about what s/he does. S/he’ll be more relaxed in this
way.
Later I can ask the questions that I am really
interested in.
Not everything that I hear will be useful – that
doesn’t matter. Not every question I ask is KM
related. We may talk about business, politics,
literature, music, hotel guests – so that it is more like
a conversation between friends.
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For Example 2
In the same company, I am talking to frontline
staff at the check-in desk.
I want to learn about the problems they face, the
solutions they create, the ways they share good
ideas.
Here my questions will be more precise – but still
I will give them a chance to say what they like.
Local information is invaluable – they know far
more than I do, so I should listen as much as
possible. I just have to keep them talking.
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Example 3
I was lucky enough to meet the GM of a local
engineering firm that is interested in KM. He is
also a CityU DBA student.
I had to get to his offices by 9
The conversation covered many topics – some of
interest to me, some to him
We needed to find a mutual basis for interactions – as
well as mutual understanding and respect
A successful partnership requires me to be very
flexible.
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Notes and Observations
In field (and lab) research, we often encounter
interesting situations
Conversations with data subjects
Watching and reflecting how people behave in different
situations
Our own internal thoughts and interpretations
These unplanned, unscripted events need to be
documented carefully – so that we can refer back
to them later.
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Notes and Observations
It is important to be aware of the ‘data’ around us
The interesting facts, happenings, people, behaviours
And to record these.
A paper notebook is most practical, unless you
want to dictate into an MP3/Smart Phone
Drawings and sketches as well as text
A camera could also be valuable
You need to be prepared for the unexpected
Some people are not comfortable being recorded, but it
is OK to make notes.
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For Example
I visit a company site.
I notice that the ‘office’ is open style – no doors,
rooms, privacy. I quickly sketch the office layout,
the location of people, teams, equipment.
I note communication patterns.
Later I ask the CEO about this unusual design
(refer to notes) and jot down his answers. I was
not expecting to acquire this information, but why
not? Can it give me an unexpected insight into the
office culture of this company?
It is all data!
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Diaries
Diaries can provide a useful subjective account
They are normally written/kept by research
subjects, who can be instructed to write down
selected behaviours or impressions
For instance, if we are investigating data privacy
violations, we could ask people in the IT
department to document each time they are asked
to release private data, together with some details
(nature of request, rank of requester, decision
taken, etc.) – in order to assess actual privacy
practices.
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Confessional Diaries
Are kept by the researcher
Very detailed notes about everything that you
do on a project
Self-reflections, questions, doubts
Schultze (2000)
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Documents
Corporate documentation is invaluable, especially in
case studies where there is a need to build up a
picture of organisational values.
Documents may include strategic plans, business
processes, standard templates, training manuals,
internal telephone books.
Documents may be paper or online (web). They may
be for internal or external use, for customers, clients,
consultants or employees.
Documents can include data that you would not think
to ask about. So reading them carefully can help you
to ask the right questions.
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For Example
On my first visit to the offices of the hotel chain I
am waiting for my appointment. There are some
company documents on the table – for visitors. In
them I learn that the group that manages the hotel
also has interests in project management for
engineering projects around the world.
Can this information inform my later interview
with the CEO?
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User-Generated Data
There are many potentially-useful forms of usergenerated data
Many of them are private and confidential, but it is
possible to access them if you ask for permission.
In my study of KS practices in Beijing, I was able to
access one month’s IM data (0.5MB) from a power
user.
We analysed that data and found that 80% was for
work purposes (i.e. not just social chatting), esp. for
knowledge sharing and coordination work.
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User-Generated Data
What other kinds of user-generated data can
you think of – and what could we do with
them?
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Researcher-Data Subject Data
Emails, IMs, SMS, etc.
Data is generated between the researcher
and the company
I organise all the emails that I send to and
receive from my research partners
It is useful to be able to look back at what I
said, or they said, a year or two ago.
Certainly, I can’t trust my memory.
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For Example
May 19th, 2009 From Steve XX to Robert
Hi Robert,
After the meeting with HQ, I have some clues to start this survey. Apart from your standard
Knowledge works there are some requirements we hope you can also include
(1) Give a speech to team members to share the importance of knowledge transfer before the
survey starts
(2) Topics to be included in your survey
(i) How do business units spread their knowledge across the team
(ii) What are the strong points of these business teams in knowledge forming, keeping &
spreading?
(iii) What are the weak points of these business teams in knowledge forming, keeping,
transferring and spreading?
(iv) How to improve the overall knowledge transferring effectiveness?
(v) Any tools and organizational suggestions to help improve the result?
(3) Provide an after survey Training to the conducted teams to summarize the survey and
highlight the key points conducted
(4) Also we should sign a NDA before we start
Regards, Steve
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Data Coding
Organising data so that it can be analysed
Looking for patterns in data
Thematic
Metaphorical
So as to identify theoretical constructs, as
well as practical examples to illustrate
existing theory.
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What Kind of Data Can Be
Coded?
Interview transcripts are a major source
Corporate documentation is possible
User generated texts are a good source,
including diaries.
There is software for qualitative data
coding/analysis, e.g. NVivo.
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What to Look For?
Patterns, themes, frequencies, repetition
Can you identify regularities or common features?
Are some themes dominant?
Are some types of metaphor used repeatedly?
Does the use of language tell us something?
Can we analyse the actual text for hidden or clear
meanings?
Compare across documents (intertextuality)
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If You Analyse the Data
Carefully
You may be able to ground a theory out of the
data
You may see a new way to organise work, people,
processes
You may identify new constructs that were not
previously reported in the literature
Qualitative case studies have been used for theory
building – where the case data supports the theory.
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In recent work, …
I contacted about 80 IS researchers to ask them
about a specific research method.
Most of them replied – in a lot of detail
Those replies need to be coded to look for key
themes
I can see 10 key themes with many examples to
illustrate.
My colleagues (2) also code the data independently
We need to reconcile our coding – reach agreement –
and then we can write up the data.
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Some Short and Simple Examples
of Metaphorical Writing
“We need to forge links with industry”
“CityU is not immune from global forces”
“We are on the edge of a new beginning”
“This requirement is a cornerstone”
“We have a large pool of graduates”
“We immerse our students in an IT-rich
environment”
“We are moving into the knowledge society”
“The university feels the pulse of the community”
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Patterns and Metaphors
We could look for certain kinds of metaphors:
Industrial, domestic, military, gentle, hard.
We could look for metaphors that everyone knows
(on the edge; forge links)
Something comfortable, reliable, gentle
Or something new as a way to express a novel
concept
Do universities really “feel the pulse”?
Do these patterns or frequencies hint at the tone of
the document, the culture, the style?
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How are Metaphors Interpreted?
Metaphors are interpreted – and
misinterpreted.
Carefully placed metaphors can help to create a
culture, a community
• “We are all members of the same team”
But use of a metaphor that people dislike can be
counter-productive
• “We live or die together”; “Freedom or death”;
• Even “we” is problematic. Who is ‘we’ and who is
not? Do you want to be one of the ‘we’?
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Application of Metaphorical Analysis
In what kind of qualitative study do you
think a metaphorical analysis of texts might
prove most illuminating?
What kind of text might be most richly
metaphorical?
Why do people use metaphors? Who uses
metaphors? When?
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Other IS Metaphors
Information is power, intelligence
Organisation is information
Systems implementation is a war between users
and developers (Keen, 1981)
IS are competitive weapons (Ives and Learmonth,
1984)
Choice of vendors is a minefield
IS Project goes from honeymoon to war
IS is an elephant / amoeba
IS project is a bowl of spaghetti
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Now … Please Look At:
Oshri, I., Fenema, P. van and Kotlarsky, J. (2008)
Knowledge Transfer in Globally Distributed
Teams: The Role of Transactive Memory,
Information Systems Journal, 18, 6, 593-616.
What kind of data was collected?
How was it analysed?
Which method(s) were adopted?
How did the data contribute to the findings?
How significant are the findings – what do we learn
from them?
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References
Keen, P.G.W. (1981) Information systems
and organizational change,
Communications of the ACM, 24, 1, 24-33.
Ives, B. and Learmonth, G.P. (1984) The
Information System as a Competitive
Weapon, Communications of the ACM, 27,
12, 1193-1201.
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