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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 dataEmails/SMS/IM/Wiki/WeChat

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Interviews

Structured; Semi-structured; UnstructuredProtocols

MediatedTelephone, IM, Email, WeChat, …

Un-mediatedFace-to-face• Individual• Focus Group

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Interview ProtocolsA protocol here refers to a plan for the interview

Which topics, themes, questions you want to askHow 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 1I 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 2In 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 9The 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 usThe 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 unexpectedSome people are not comfortable being recorded, but it is OK to make notes.

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For ExampleI 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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DiariesDiaries can provide a useful subjective accountThey are normally written/kept by research subjects, who can be instructed to write down selected behaviours or impressionsFor 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 researcherVery detailed notes about everything that you do on a project

Self-reflections, questions, doubts

Schultze (2000)

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DocumentsCorporate 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 user-generated 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 companyI organise all the emails that I send to and receive from my research partnersIt 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 ExampleMay 19th, 2009 From Steve XX to RobertHi 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 startRegards, Steve

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Data Coding

Organising data so that it can be analysedLooking for patterns in data

ThematicMetaphorical

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 MetaphorsInformation is power, intelligenceOrganisation is informationSystems implementation is a war between users and developers (Keen, 1981)IS are competitive weapons (Ives and Learmonth, 1984)Choice of vendors is a minefieldIS Project goes from honeymoon to warIS is an elephant / amoebaIS 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.