The previous chapter has highlighted the utility of borrowing concepts from different research, often advocated by problem-driven pragmatists. By using several theoretical insights as a framework, QCA becomes a suitable method that can grapple with complex relations involving conjunctural causation, but more importantly, a medium number of cases (Castellani and Hafferty, 2009: 131). QCA initially gained prominence in social science through Ragin (1987, 2008a). However, in IR generally, and conflict studies specifically, QCA has only made a few inroads (see, for example, Pinfari, 2011; van der Maat, 2011; Bretthauer, 2014b; Mello, 2014). This chapter is the first to utilise the advantages of QCA methodology to shed new light onto the issue of minor powers in asymmetric conflict with major powers. While the full presentation of QCA would be beyond the length of this chapter, the next few paragraphs provide a succinct version of the method before delving into the operationalisation and eventually the results (pathways) that will form the basis for subsequent case studies.

QCA is often mentioned as a method that bridges the gap between quantitative and qualitative approaches, and initially, it was geared towards the analysis of multiple cases in a small and intermediate-N research design (Engeli et al, 2014: 85). Two important aims of QCA became the contextualisation of explanations by gathering in-depth withincase knowledge and the capture of the complexity of cases. These are essentially qualitative features. On the other hand, QCA's quantitative appeal emerges from its treatment of cases as a series of conditions and outcomes (variables), allowing calibration using numeric indicators (Li, 2018). While quantitative studies are generally not well connected to the particularities of their cases, qualitative studies offer a very limited possibility for making generalisations (Scholvin, 2016: 54). QCA is used as a tool to reach a middle ground. Similarly, both inductive and deductive approaches to making inferences are feasible with QCA. Specifically, according to Hicks (1994), the selection of conditions and their operationalisation is based on theoretical knowledge; this is essentially a deductive step. However, conclusions based on QCA can be elaborate and interpreted, allowing researchers to formulate new theories; this is essentially an inductive step (as cited in Li, 2018).