This document provides guidance on conducting qualitative research. It discusses key aspects of the research process such as developing a conceptual framework, determining what and who to study, collecting data through methods like interviews and observation, and analyzing the data through techniques such as coding and creating displays. The document emphasizes generating conclusions that consider alternative explanations and testing findings for reliability and generalizability.
2. SUMMARIZING SO FAR
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Project is hard work
But you can show skills and have fun
With enough effort you will pass!
Take responsibility
Prepares for bachelor assignment
in ‘safe’ environment (group/time limit)
Also please help us
Email first to student assistant
Initial communication in English
How’s it going?
What did you experience as most difficult?
“No man left behind”
4. More than just ‘problem definition’
A recognition that
Problems are not just ‘found’ during analysis, they’re also designed -
by you!
Your ability to solve a problem is directly affected by how well you
design it in the first place
If you can’t solve the problem, then change the problem you’re solving
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PROBLEM FRAMING
5. Designed to be actionable in the first place
Suggest what steps/tools/approach might be required to address the
problems
Use whatever language, jargon (formal or informal) makes most sense
for those involved
Exciting, compellingly worded
Upon reading it, should be a problem you want to know the answer to
Relevance at least as important as rigor
I.e., ‘usefulness’ as important as ‘precision’
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GOOD PROBLEM DEFINITIONS
6. Statements you make raise questions in the listener's mind
Fail to answer those questions—presentation perceived as incomplete
Answer questions that were not asked—presentation perceived as
redundant
Achieve a balance and credibility and impact rise dramatically
Ask only the questions you can answer, and
Answer only the questions you ask
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KEY IS BALANCE BETWEEN
QUESTIONS ASKED AND ANSWERED
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PROBLEM FRAMING SETS STARTING POINT
AND DETERMINES SCOPE
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KEY CUSTOMER PROBLEM
EXAMPLES
9. You know what you want: answer to Key Customer Problem
What did others find? Theory!
But most problems cannot be answered by use of theory alone, e.g.:
No literature available
Literature too broad
Different context (industry, country, time, etc.)
Solution: make your own ‘theory’ by empirical study
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EMPIRICAL RESEARCH DESIGN
HOW TO ANSWER KEY CUSTOMER PROBLEM?
10. Quantitative: emphasis on statistical
testing of assumptions
Qualitative: emphasis on analyzing
behaviors, events and artefacts
Design research: emphasis on
developing a useful artefact
Mixed methods
Combinations of above
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DIFFERENT DESIGNS
12. How would you measure customer demand?
Last year students did field experiment
Sell with different stories
Positive frame: prevention
Negative frame: danger
Control group: neutral
Which one sold more?
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EXAMPLE: DEMAND FOR FIRE EXTINGUISHERS
13. Methods Benefits Possible drawbacks
Quantitative Clear cut testing/
analyses; hypothesis
testing (confirm/reject)
Design needs to be perfect up
front; sample size; self-report;
causality; oversimplification
(proxies / forced answers)
Qualitative Aim to understand;
open minded
Analyses complicated; matter of
plausibility: always multiple
interpretations possible
Design You ‘deliver’ something Full cycle difficult, often only
prototype testing
Mixed methods Best of both qual and
quant
Almost double the work
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MAIN BENEFITS/ DRAWBACKS
15. Selection: which population, which respondents?
Sample: how many respondents necessary? What type of sampling?
Measurement: constructing survey instrument, use validated scales,
Databases? Self-report data / common method bias?
Collection: post or online? Dillman method?
Analysis: what type of statistics?
T-test, ANOVA, exploratory factor analysis, regression, etc.
NOIR
Highly recommended reading
Andy Field – Discovering Statistics using SPSS (Sage)
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KEY CHOICES
17. WHY QUALITATIVE RESEARCH?
Much more work than quantitative research if done well
Cost more time
Cost more effort:
more ‘messy’ process
Why bother?
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18. Qualitative Research can provide meaningful findings.
Features
Intense contact with the field
Holistic view of the context
Gather data from the inside
Isolation of certain themes
Understand account for and act on people’s behavior
Many interpretations possible
Little standardized instruments
Mostly in words
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SCIENTIFIC REASONS (MILES & HUBERMAN, 1994)
19. CASSELL & SYMON (2004)
Non-exhaustive list of 30 (!) different methods
Interviews, electronic interviews, life histories, critical incident technique,
repertory grids, cognitive mapping, twenty statements test, research
diaries, stories, pictoral representation, group methods, participant
observation, analytic induction, critical research, hermeneutic
understanding, discourse analysis, talk-in-action/conversation analysis,
attributional coding, grounded theory, template text analysis, data
matrices, preserving/sharing/reusing, documents, ethnography, case
study, soft systems, action research, co-research, future conference
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20. OWN QUALITATIVE EXPERIENCE
Semi-structured interview
(Informal) unstructured interviews
Structured interviews
Diaries
Documentary data
Group interview
(Non)participant observation
Action research
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21. Selection & sample: who do you study and why?
Measurement: which questions do you ask?
Data collection: how do you ask?
Data analyses: how do you analyze?
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RESEARCH PROCESS
22. SELECTION & SAMPLE
Who do you talk to? What about? Where to go? What do you look at?
Maximum variation or similar cases?
Selection on dependent variable
Events with system disturbing potential (Barley & Tolbert, 1997)
Multiple cases: replication and extension?
Gaining access
Snowballing
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24. MEASUREMENT
How do you ‘measure’?
Interviews (open, semi-structured, structured)
Focus groups (=small group interview)
Open survey (!)
Field study ((non-)participant observation, action research)
Documents (minutes, annual reports, manuals, protocols, etc.)
Diaries
Etc.
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25. SEMI-STRUCTURED INTERVIEWS
Most common form of qualitative research
Get a snapshot, could repeat over multiple waves
People are not familiar with you: social desirable answers
Audiotape!
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30. Contact summary sheet
• One-page document to summarize a field contact
Case analysis meetings
• Meeting with peers to discuss your research progress
Interim case summaries
• Summarizing your research progress
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SOME STRUCTURE BEFORE START
31. • Good way to analyze data (not the only way)
• Start from the data
• Difficult to see the larger picture
• Start from theory
• Difficult to find new things
• In practice always somewhere in the middle
• Other way is coding for recurring important themes over entire text
• You determine what is ‘important’
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TABLES
32. Data coding
• Assigning tags / codes to pieces of your data.
• Makes analysis easier / faster
Vignette
• Example of your research
• Narrative structure
• Exemplifies typical series of steps
Pre-structured Case
• Structure your research beforehand
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EARLY ANALYSIS STEPS
34. Clear, concise displaying data is crucial
for drawing conclusions in Qualitative
research.
Building a display format is relatively
easy
Matrix displays vs. Networks displays
• Matrix works best when focussing on
variables
• Networks show the process better
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WITHIN CASE DISPLAYS
SHOWING ONE CASE
Clear data
display
Better
conclusions
35. Main general structures
1. Partially ordered displays- Not to many ordering
2. Time-Ordered display- Ordering on time
3. Role-Ordered displays- Ordering on people’s (in-) formal roles
4. Conceptually ordered displays- Ordering on concepts / variables
Structures for explaining causality
1. Case Dynamics Matrix- Displaying a set of forces for change
2. Causal Network- Representation of important (in-) dependent variables
But: You have to test the “causal predictions” of these causal structures!
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WITHIN CASE DISPLAYS
SHOWING ONE CASE
38. Previous slides were about one case / research
We can also use this for multiple cases
• It makes our research more generalizable
• It deepens our understanding
More complex then a single case
Same categories:
1. Partially ordered displays
2. Time-Ordered display
3. Role-Ordered displays
4. Conceptually ordered displays
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CROSS-CASE DISPLAYS
SHOWING SEVERAL CASES TOGETHER
39. When explaining causality
Understand all cases
Do not plainly aggregate
your data
Avoid ‘throwing away’ data
Use both variable- and
process-oriented structures
Cluster cases in
“explanatory families”
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CROSS-CASE DISPLAYS
SHOWING SEVERAL CASES TOGETHER
41. Miles and Hubermann (1994) give a lot to take into account:
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GENERATING CONCLUSIONS AND MEANING
A LOT OF REQUIREMENTS!
Note patterns / themes Create general categories
See plausibility Use factoring
Use categories / clusters Note relations between variables
Use metaphors Find intervening variables
Use quantitative data (numbers) Build logical reasoning
Making contrasts/ comparisons Make conceptual / theoretical
coherence
Subdivide your variables
Miles & Huberman (1994) p.245-261
42. And for testing / confirming your findings
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GENERATING MEANINGFUL CONCLUSIONS
CORE ISSUES
Check for representativeness Look for negative evidence
Check researcher bias Make if-then tests
Use triangulation Be careful with causal relations
(could be spurious)
Weigh bits of evidence Replicate a finding
Check meaning of outlying data Check alternative explanations
Use extreme cases Get feedback on conclusions
Build on surprises
Miles & Huberman (1994) p.262-275
44. The way of organizing data can improve your research / report
Miles and Huberman state there are 4 categories here:
1. Is your research objective and confirmable?
2. Is your research methodology reliable / stable?
3. Do your findings make sense for this particular problem?
4. Are your findings generalizable to a larger set of problems?
Key here is to carefully document your progress and methods, so
that you connect with your ‘audiences’.
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WRAPPING UP
WHAT DID WE SEE?
46. 1. Build a conceptual framework
A graphical display of your research
2. Formulating research questions
3. Determine your case
Determine your unit of analysis
4. Sampling
Determine what you study and when
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SUMMARY RESEARCH PROCESS (1/2)
REDUCING DATA IN ADVANCE
47. 5. Instrumentation
How will you get information for
answering your questions?
6. Linking qualitative and quantitative
data (=mixed methods)
This enables:
a) Deeper analysis
b) Confirmation of qualitative data
c) New lines of thinking
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SUMMARY RESEARCH PROCESS (2/2)
REDUCING DATA IN ADVANCE