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

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

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

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

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

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.

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

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

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

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

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

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.

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?

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

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

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

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

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)

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

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.

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

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

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.

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

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.