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Doing case study research

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  1. Doing case study research Paul ‘t Hart Political Science, RSSS, ANU USG, Utrecht University

  2. Case studies: A Brief Introduction • Characteristics? • When to use? • Challenges, problems? • Strategies

  3. Characteristics of case studies (I) • Research strategy, not research method • Commonly, but not exclusively, used by interpretive researchers and process-oriented positivists • Yields `knowing much about a little’

  4. Characteristics of case studies (II) • Single and multiple case studies • Explorative/heuristic vs validating/testing uses of case studies • Crucial case studies • Comparative case designs

  5. Case study designs in context Continuum: Case study  Comparative research -> Survey research ->Experimental research Key factors:Key implications: Number of variables Different generalization potential Number of observations Different ability to absorb real- world complexity Control over context Different balance scope/depth of knowledge

  6. When to undertake case study research? • When you investigate a phenomenon that cannot be manipulated/simulated • When you investigate a unique/rare phenomenon • When knowledge of context is essential to grasp/explain the phenomenon • When knowledge of process is essential to grasp/explain the phenomenon • When social constructions of actors must be charted/compared/contrasted

  7. When to undertake comparative case research? • Research question requires real-world observation • Theory contains many/complex variables • Researcher wants: • To compare particular units/populations intrinsically • To produce empirical generalizations

  8. Challenges in case study research: design (I) • Case demarcation: • What is a case, what is context? • What is unit of observation? • Case selection/comparison: • Which logic of selection/comparison? • How to ensure comparability? • How to account for observed congruence/variation?

  9. Comparative Case Selection Strategies Selection on dependent variable: - MDCD: accounting for unexpected differences in outcomes • MSCD: accounting for unexpected similarities in outcomes Selection on independent variable(s): • MDCD: testing if expected differences materialize • MSCD: testing if expected similarities materialize

  10. Challenges in case study research: design (II) • Case description: • How to deliver on promise of `in-depth’ study? • How to focus: when do you know enough? • How to deal with factual gaps and contradictions? • Case analysis: • How to balance between reconstruction / description and analysis / interpretation? • How to ensure validity/reliability – interpretive persuasiveness? • From case(s) to theory: inference, `generalization’

  11. Sensible description and analysis in a case study George and Bennett: • Focused comparison (G&B, ch 3-6) • Process tracing (G&B, ch 10)

  12. Bad case study research: traps to avoid • Methodological laziness • Unstructured ‘trips to the field’ • Accidental/ill-considered case selection • Analysis as `just presenting the facts’ or `just telling the/a story’ • Lack of rigor in reporting • Boringness: details overkill • Unstructuredness: not question-driven, not concepts-driven • Unevenness: in source use, in coverage of context/process • Unwarranted empirical generalizations

  13. Doing good case study research: Tips • Don’t assume it is the easy option; don’t do it because you are ‘afraid of numbers’ • Don’t do it before you have seriously considered alternatives • Consider your ontological/epistemological position, and derive your case-study aims/approach accordingly • Be rigorous: set and follow rules in data collection, recording, interpretation • ‘Triangulate’ methods/sources within the case design framework • Think – and act – comparatively: even in N=1 setting you can increase number of observations • Read, re-read George/Bennett; read it again; then apply its lessons