Table 1 Comparison of the key features... | Emerald Publishing

Table 1

Comparison of the key features of case studies, fsQCA and experiments

	Case studies	fsQCA	Experiments
Stage of theory development	Theory building (Exploration)	Theory building (Exploration)	Theory testing
Types of data	Qualitative data	“Quantified” qualitative and quantitative data	Quantitative data
Unit of analysis	Cases (usually of firms, but also individuals or organizational units)	Cases (usually of firms, but also individuals or organizational units)	Usually individuals, but also firms or organizational units
Sample size	Small N (10 or less)	Medium or large N	Depends on the experimental design; minimum of 30 per studied condition
Mathematical foundation	None	Set relations	Usually frequentist statistics (alternatively Bayesian)
Analytical logic	Inductive	Inductive	Deductive
Nature of causality	Observed sequence of phenomena (weak form of causality)	Complex causal patterns (medium form of causality)	Intervention-based causality (strong form of causality)
Role of theory	Interpretation of empirical findings to support proposition development	Identification of the relevant conditions to be included in the analytical procedure and interpretation of the identified configurations	Hypothesis development
Intended outcome	Formation of propositions	Specification of cause–effect relationships that result in equifinal paths to an intended outcome	Specification of cause–effect relationships

	Case studies	fsQCA	Experiments
Stage of theory development	Theory building (Exploration)	Theory building (Exploration)	Theory testing
Types of data	Qualitative data	“Quantified” qualitative and quantitative data	Quantitative data
Unit of analysis	Cases (usually of firms, but also individuals or organizational units)	Cases (usually of firms, but also individuals or organizational units)	Usually individuals, but also firms or organizational units
Sample size	Small N (10 or less)	Medium or large N	Depends on the experimental design; minimum of 30 per studied condition
Mathematical foundation	None	Set relations	Usually frequentist statistics (alternatively Bayesian)
Analytical logic	Inductive	Inductive	Deductive
Nature of causality	Observed sequence of phenomena (weak form of causality)	Complex causal patterns (medium form of causality)	Intervention-based causality (strong form of causality)
Role of theory	Interpretation of empirical findings to support proposition development	Identification of the relevant conditions to be included in the analytical procedure and interpretation of the identified configurations	Hypothesis development
Intended outcome	Formation of propositions	Specification of cause–effect relationships that result in equifinal paths to an intended outcome	Specification of cause–effect relationships