1. Designing Case Studies
Grupp 2
Jukka Mäki-Turja, Johan Andersson, Joel Huselius

2. Case Studies from Chapter 1
A case study is an empirical inquiry that
Investigates a contemporary phenomenon within its real-life context, especially when
the boundaries between phenomenon and context are not cleraly evident
When to use a CS?
Many more variables of interest than data points
Relies of multiple sources of evidence
Benefits from prior theoretic propositions, guiding data collection and analysis.
In answering ”how” and ”why” questions

3. Outline – Research Design
What is a Research Design?
The role of Theory
Criteria for high quality research design
Single vs. Multiple case design
Conclusion and Advice

4. What is a Research Design
Research Design is a difficult part of doing Case Studies
No roadmaps exists…
Logical plan to go from A to B
A = initial set of question to be answered
B = conclusions of study
Logical, not a logistical problem!
Research design can be seen as a blueprint of research
What question to study?
What data are relevant?
What data to collect?
How to analyze the results?
Case studies require its own research design
Not a special case of, e.g., experiment.

5. 5 Components of Research Design
Questions
Propositions
Unit of analysis
Linking data to propositions
Criteria for interpreting the findings

6. Questions and Propositions
The high level questions of the Case Study.
Case studies suitable for ”how” and ”why” questions.
Propositions
Possible (partial) answers (a.k.a hypotheses)
Directs attentions on what to examine in the study
More concrete than questions
Forces the study in the “right” direction
In exploratory studies - no propositions
State purpose instead

7. Unit of Analysis What is the ”case”?
An individual?
A decision?
A program?
Relates to research questions and proposition
Without clear propositions, one might be tempted to cover “everything”.
Non-favoring research questions – too vague or too numerous
Different units of analysis requires different research design and data collection strategy.

8. Linking data to propositions
Least well developed
Pattern Matching
Identify effects/no effects patterns
Which pattern matches best?
”effects” pattern
”no effects” pattern
Observation

9. The criteria for Interpreting the findings
How close does a match have do be in order to be considered a match?
No general solution…
Hope that patterns of rival propositions are sufficiently constrasting

10. Outline – Research Design
What is a Research Design?
The role of Theory
Criteria for high quality
Single vs. Multiple case design
Conclusion and Advice

11. The Role of Theory
Covering these 5 aspects force you to begin constructing a preliminary theory.
Important to have a theoretical framework providing guidance
Existing work
Analytical vs. Statistical generalisation
Replication

12. Criteria for high quality
Judging the quality of Research Design
Four tests
Construct Validity
Internal Validity
External Validity
Reliability

13. Construct Validity
”Establishing correct operational measures for the concepts being studied”
Case studies are often criticized that subjective judgement is used collecting data.
To meet Construct Validity, e.g.
Select the specific type of changes that are to be studied.
Demonstrate that the selected measures of these changes do indeed reflect the specific type of change that have been selected.

14. Internal Validity
“Establishing a causal relationship, whereby certain conditions are shown to lead to other conditions, as distinguished from spurious relationships”
For explanatory or causal studies only.
Inferring theory
Study x leads to y
What happens if unknown z affects y?

15. External Validity
”Establishing the domain to which a studies findings can be generalized”
Critics state that single cases offer a poor basis for generalization.
Analytical generalization rather than statistical
Generalization by replication
Replication logic same as for experiments

16. Reliability
”Demonstrating that the operations of a study can be repeated with the same results”
The goal of reliability is to minimize the errors and biases in a study.
Case study protocols to document
General approach: conduct research ”as if someone were always looking over your shoulder”
compare with accounting

17. Tests Tactics Phase Construct Validity Multiple sources of evidence
Establish chain of evidence
Review draft CS report
Data collection
Composition
Internal Validity
Pattern matching
Explanation building
Adress rival explanations
Use logic models
Data analysis
External Validity
Use theory in single-case studies
Use replication logic in multiple case
Research design
Reliability
Use case study protocols
Develop case study database

18. Case Study Designs Single vs. Multiple case Embedded vs. Holistic
Single case appropriate in certain conditions
Multiple case design better in general
Embedded vs. Holistic
Holistic = one unit of analysis
Emdedded = several units of analysis

19. Basic types of Designs Context Case Context Case Single-case Designs
Multiple-case Designs
Context
Case
Context
Case
Holistic
(single unit
of analysis)
Context
Case
Embedded
Unit of
Analysis 1
Analysis 2
Context
Case U1 U2
Embedded
(multiple units
of analysis)

20. Single-case Design Five rationales
Critical case: clear set of propositions
Extreme/unique case
Representative/typical case
Revelatory case
Previously inaccessible phenomena
Longitudinal case
Same things at different points in time
Assumes that conditions changes over time
As a pilot case for multiple case studies
Not considered as a case study of its own

21. Embedded vs. Holistic Designs
When no logical subunits can be identified.
study might be conducted on a too abstract level
Research question slippage
Embedded design
Avoids slippage
Extensive analysis
Might focus too much on subunits, loses higher level (holuistic) aspects.

22. Multiple-case Designs
More robust results and compelling arguments
Require more resources
Replication rather than ”sampling” logic
Each case can be holistic or embedded

23. Replication vs. Sampling logic
Replication – analytical generalization
Analogous to that used in multiple experiments
Goal is to duplicate results from previous work
Convergent evidence is saught
”Sampling”– statistical
Analogous to that used in surveys
Goal is to gather general information from large amounts of data

24. Literal vs. Theoretical Replication
Literal replication
Similar results
Theoretical replication
Contrasting results for predictable reasons
If cases are contradictory initial proposition must be revised
Without redesign, you can be accused of distorting or ignoring the discovery to accommodate your design.
A prerequisite of successful replication is a rich theoretical framework
Number of cases is very fuzzy.

25. Rationale for a multiple case design
Comes from understanding theoretical and literal replication
Simplest multiple case design
Literal replication among two cases
More complicated multiple case design
Theoretical replication between different types of conditions
Literal replication within each type of condition

26. Conclusion and Advice
When you have a choice (and resources) choose multiple case design
Two cases is significatly better than a single one – allows for replication.
Drastical improvment of generalizability
Theoretical replication even stronger argument
Avoids critisism and skepticism
If you use single case
prepare to make an extremly strong argument in justifying your choice of case.