Compare methods

	Configurational Strategy Analysis (fsQCA)	Cross-Impact Analysis
Field	Strategic Management	Strategic Management
Family	Process / pipeline	Process / pipeline
Year of origin	2008	1968
Originator	Charles Ragin; Peer Fiss	Theodore Gordon & H. Hayward; Olaf Helmer
Type	Set-theoretic configurational comparative method	Conditional-probability simulation of interacting future events
Seminal source	Ragin, C. C. (2008). Redesigning Social Inquiry: Fuzzy Sets and Beyond. University of Chicago Press. ISBN: 9780226702759	Gordon, T. J., & Hayward, H. (1968). Initial experiments with the cross impact matrix method of forecasting. Futures, 1(2), 100-116.
Aliases	Fuzzy-Set QCA for Strategy, Configurational Comparative Analysis, Set-Theoretic Strategy Analysis, Equifinality Configuration Analysis	Cross-Impact Matrix Method, Cross-Impact Forecasting, Conditional-Probability Futures Analysis, Event Interaction Analysis
Related	4	4
Summary	Configurational strategy analysis applies fuzzy-set qualitative comparative analysis (fsQCA) to strategy questions, asking not which single variable drives an outcome but which combinations of conditions together produce it. The method rests on Charles Ragin's set-theoretic framework, fully developed in his 2008 book Redesigning Social Inquiry: Fuzzy Sets and Beyond, which treats causes as set-membership relations and uses Boolean logic to find the configurations of conditions that are sufficient for an outcome. Peer Fiss's 2011 Academy of Management Journal article brought the approach into mainstream strategy and organization research, showing how fuzzy sets can express organizational typologies and introducing the distinction between core and peripheral conditions. The defining premises are equifinality - several different recipes can lead to the same outcome - and causal asymmetry - the conditions for success are not the mirror image of those for failure.	Cross-impact analysis is a forecasting technique that models how a set of possible future events influence one another, so that forecasts account for the fact that real events are interdependent rather than isolated. Theodore Gordon and H. Hayward introduced the cross-impact matrix method in their 1968 Futures paper, motivated by the observation that judgmental forecasts such as Delphi estimate the likelihood of each event separately and ignore that the occurrence of one event can sharply raise or lower the odds of others. Olaf Helmer's 1977 work refined the approach, distinguishing the original correlational formulation from a causal cross-impact model and addressing the internal-consistency problems that plagued early matrices. The method specifies prior probabilities for events and conditional 'cross-impact' probabilities between them, then simulates the system to produce internally consistent joint outcomes and revised probabilities.