Fuzzy-Set Qualitative Comparative Analysis of FinTech Ecosystem Configurations Driving Digital Economic Transformation

Digital economic transformation increasingly depends on the maturity and structural composition of national FinTech ecosystems. However, existing studies often rely on linear and single-factor models that overlook the multi-causal complexity, asymmetry, and equifinality inherent in digital ecosystems. This study applies Fuzzy-Set Qualitative Comparative Analysis (FSQCA) to a cross-national dataset covering five core FinTech ecosystem dimensions regulatory readiness, innovation capacity, digital infrastructure quality, investment depth, and consumer digital adoption across 15 countries representing advanced and emerging digital economies. Necessity analysis shows that Digital Adoption approaches necessity with a consistency score of 0.90 and coverage of 0.86, while Digital Infrastructure demonstrates near-necessary behavior with consistency of 0.88. The sufficiency analysis yields five highconsistency configurations (0.85–0.92), representing empirically observed pathways that reliably lead to high digital economic transformation. Boolean minimization produces two intermediate solution pathways: (1) a regulation–infrastructure pathway featuring strong regulatory readiness and advanced digital infrastructure as core conditions (raw coverage = 0.63; consistency = 0.91); and (2) an innovation–adoption pathway driven by high FinTech innovation capacity and strong consumer digital adoption, supported by moderate investment depth (raw coverage = 0.58; consistency = 0.89). The findings reveal that digital transformation is configurational, asymmetric, and equifinal, with different countries achieving similar transformation outcomes through distinct institutional and market arrangements. The study advances the application of FSQCA in digital economy research and provides a comparative blueprint for policymakers seeking to orchestrate effective FinTech ecosystem development.