Explainer · Plain-language

What Is a Case Study? Research Method Explained | CASRAI

A case study is an in-depth, intensive investigation of a single individual, group, event, organisation or phenomenon within its real-world context. It is one of the most widely used qualitative research strategies across the social sciences, medicine, law, business, and education.

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Yin’s definition and types of case study

Robert Yin’s (2018) influential definition describes a case study as an empirical method that "investigates a contemporary phenomenon in depth and within its real-world context, especially when the boundaries between phenomenon and context may not be clearly evident." Yin distinguishes six types across two dimensions. By purpose: descriptive (documents the phenomenon), exploratory (generates hypotheses), and explanatory (tests causal links). By scope: intrinsic (the case matters in itself), instrumental (the case illuminates a broader issue), and collective (multiple cases studied together to build theory). These typologies help researchers select the most appropriate design and articulate what kind of knowledge the study can produce.

Data sources in case study research

Case study research draws on multiple sources of evidence to achieve convergence — a practice Yin calls "triangulation of evidence." Common sources include semi-structured interviews, participant and non-participant observation, primary documents (meeting minutes, reports, correspondence), archival records, physical artefacts, and audio-visual material. The use of multiple sources is a methodological strength: findings that hold across different types of evidence are more credible than those resting on a single source. A case study database and a clear chain of evidence are recommended to ensure auditability and transparency.

Strengths and limitations

Case studies offer exceptional contextual richness, are well-suited to theory-building, and provide access to rare or unusual phenomena. Oliver Sacks’ neurological case studies, Freud’s case of Dora, and the Harvard Business School MBA case method all illustrate how deeply illuminating single cases can be. The primary limitation is low external generalisability: findings from one case cannot automatically be extended to a population. Yin distinguishes statistical generalisation (extending to a population) from analytical generalisation (extending to a theory) and argues that case studies target the latter. Researcher bias and the time-intensive nature of data collection are additional challenges.

Multiple-case and comparative designs

When more than one case is examined, researchers use a multiple-case or cross-case design. This is analogous to running multiple experiments: each case is studied on its own terms, and then patterns are compared across cases (replication logic). Literal replication means several cases are expected to yield similar results; theoretical replication means cases are chosen to predict contrasting results for specifiable reasons. Multiple-case designs strengthen generalisability to theory but require significantly greater resources. They are increasingly common in education research, policy evaluation, and organisational studies.

Key facts

At a glance

Definition: In-depth investigation of a single phenomenon in its real-world context
Theorist: Robert Yin (2018) — the definitive methodology text
Types: Descriptive, exploratory, explanatory; intrinsic, instrumental, collective
Data sources: Interviews, documents, observations, artefacts (triangulated)
Strength: Contextual richness, theory-building, access to rare phenomena
Limitation: Low statistical generalisability; targets analytical generalisation instead
Disciplines: Medicine (clinical case report), law, business (Harvard MBA method), psychology

Common misconceptions

What people often get wrong

Often heard: A case study can only use qualitative data.

Actually: No — case studies can incorporate quantitative data alongside qualitative sources. Yin explicitly includes numerical data as a legitimate source of evidence within a case study design.

Often heard: Case studies cannot generalise.

Actually: Partly true — case studies cannot generalise statistically to populations, but Yin argues they achieve analytical generalisation: testing or extending theoretical propositions, which is a different and legitimate form of knowledge.

Often heard: A case study is an easy research method requiring little rigour.

Actually: No — rigorous case study research requires a clearly bounded case, a systematic protocol, multiple evidence sources, a case study database, and a transparent chain of evidence.

Going deeper