Case Study Research (Yin)

Overview

Case study research is an empirical inquiry that investigates a contemporary phenomenon in depth and within its real-life context, especially when the boundaries between phenomenon and context are not clearly evident. Yin's framework provides systematic design choices — single vs. multiple cases, holistic vs. embedded analysis — and emphasizes triangulation to strengthen construct validity.

When to Use

• Research questions are "how" or "why" questions about contemporary events
• The researcher has little or no control over behavioral events
• Contextual conditions are highly pertinent to the phenomenon of study
• Boundaries between phenomenon and context are blurred

When NOT to Use

• When frequency or incidence data is needed (use survey or experiment)
• When context is irrelevant and can be controlled (use experiment)
• When the goal is statistical generalization to a population

Assumptions

IRON LAW: Case study answers HOW and WHY questions in context — if you
need frequency or incidence data, use a survey or experiment instead.
Applying case study to "how many" or "how much" questions misuses the
methodology.

Key assumptions:

1. The case is a bounded system — define temporal, spatial, and conceptual boundaries
2. Multiple sources of evidence are essential for construct validity
3. Multiple cases follow replication logic (not sampling logic) — each case is an experiment, not a survey respondent
4. A case study protocol and database enhance reliability

Methodology

Step 1: Design the Case Study

Define the research question (how/why). Select the case type using Yin's 2x2 matrix:

| | Single Case | Multiple Case | |---|---|---| | Holistic (single unit) | Critical, unique, or revelatory case | Literal or theoretical replication | | Embedded (multiple units) | Multiple units within one case | Multiple units across cases |

Develop propositions to guide data collection.

Step 2: Collect Evidence from Multiple Sources

Gather data from at least three of six source types: documents, archival records, interviews, direct observation, participant observation, physical artifacts. Maintain a chain of evidence linking questions to data to conclusions.

Step 3: Apply Triangulation

| Triangulation Type | Description | |---|---| | Data | Multiple data sources converge on the same finding | | Investigator | Multiple researchers independently analyze the same data | | Theory | Multiple theoretical perspectives applied to the same data | | Methodological | Multiple methods (qual + quant) address the same question |

Step 4: Analyze and Report

Use pattern matching, explanation building, time-series analysis, or cross-case synthesis. Report the chain of evidence transparently.

Output Format

markdown
## Case Study Analysis: [Context]

### Research Question
- Question: [the how/why question]
- Case type: [single/multiple] x [holistic/embedded]
- Unit of analysis: [what constitutes the "case"]

### Case Selection Rationale
| Case | Rationale | Expected Pattern |
|------|-----------|-----------------|
| [name] | [why selected] | [literal/theoretical replication] |

### Evidence Matrix
| Source Type | Data Collected | Key Findings |
|------------|---------------|--------------|
| [documents/interviews/etc.] | [description] | [finding] |

### Triangulation Results
- Convergent findings: [where sources agree]
- Divergent findings: [where sources disagree]
- Explanation: [how divergence is resolved]

### Pattern Matching
- Predicted pattern: [from propositions]
- Observed pattern: [from evidence]
- Match assessment: [strong/moderate/weak]

### Conclusions
1. [Key finding with chain of evidence]
2. [Analytical generalization — how findings extend theory]

Gotchas

• Case studies generalize to THEORY (analytical generalization), not to populations (statistical generalization)
• A single-case design requires explicit justification: critical, extreme, unique, revelatory, or longitudinal
• Replication logic in multiple cases means each case must independently confirm or disconfirm a proposition
• The chain of evidence must be traceable from question to protocol to database to report
• Do NOT confuse case study with case history or case report — Yin's case study is a research strategy with formal design
• Rival explanations must be addressed explicitly, not just dismissed

References

• Yin, R. K. (2018). Case Study Research and Applications: Design and Methods (6th ed.). Sage.
• Stake, R. E. (1995). The Art of Case Study Research. Sage.
• Eisenhardt, K. M. (1989). Building theories from case study research. Academy of Management Review, 14(4), 532-550.