Qualitative comparative analysis (QCA) comprises logic-based methods for describing phenomena, for developing concepts or theories about causal relationships, or for testing theories. In-depth comparison of relatively few cases allows fine-grained and context-sensitive attention to causal mechanisms and process dynamics, crucial for description and theory development. For theory testing, in contrast, a small number of observations constrains the imposition of comparative control and narrows the basis for generalization beyond cases. Comparativists seek to overcome these challenges by selecting cases strategically, enhancing case diversity, and formalizing the comparison. The present trend towards a stronger comparative element in studies of global environmental governance supports cumulative research by requiring common variable definitions, greater operational specificity, better tools for context-sensitive analysis, and concepts and causal propositions capable of ‘travelling’ across issue- and spatial boundaries. A set theory-based, formalized QCA variety outlined in this article is particularly strong in identifying combinations of factors associated with a particular outcome when numbers of observations are small to intermediate.