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Communications of the Association for Information Systems

Author ORCID Identifier

Dix Maik Rölke: 0009-0007-6619-9760

Susanne Strahringer: 0000-0002-9465-9679

Abstract

This paper contributes to configurational research in information systems by demonstrating how Coincidence Analysis (CNA) can reveal causal structures within complex settings. CNA is a configurational comparative method for causal inference that uses a bottom-up algorithm and Boolean techniques to identify redundancy-free sufficiency and necessity relations in line with INUS/MINUS reasoning. In contrast to standard single-outcome applications (such as within QCA), CNA can handle multi-outcome structures and is therefore suited to identifying conjunctive and disjunctive dependencies, including causal chains and common-cause structures. Using an example study on new-to-market product innovation in SMEs, we show how CNA reveals a dynamic capabilities chain, linking sensing, seizing, and transforming. More specifically, the results indicate that market development is causally connected to product novelty, which in turn is linked to organizational method renewal and sustained internal R&D. Methodologically, we present a concrete, step-by-step CNA approach for IS contexts and show how issues such as boundary conditions, fragmentation, and model ambiguity can be addressed through fit-robustness analysis, sensitivity checks, and transparent reporting. As early adopters, we outline the advantages and disadvantages of CNA, common pitfalls and solutions, and consider limitations affecting our study. Our goal is to stimulate discussion within the IS community and expand its configurational toolkit.

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