Using fuzzy-set qualitative comparative analysis for a finer-grained understanding of entrepreneurship

•FsQCA allows incorporation of asymmetric data, outliers, asymmetric relationships, interdependent conjunctural causation, and equifinality.•FsQCA reveals patterns within the data that are left hidden by traditional methods, and it accommodates data that traditional methods cannot.•The fsQCA method is outlined in the entrepreneurship context to highlight the contribution this analytical tool can make to developing entrepreneurship theory.•Replication of a prior symmetric study using the fsQCA method demonstrates the finer-grained information that this analytical tool can reveal.•A detailed future research agenda for the application of fsQCA method to a wide range of micro and macro entrepreneurial topics. Entrepreneurship theory has largely been developed and tested using symmetrical correlational methods, effectively describing the sample-average respondent and subsuming individual differences. Such methods necessarily limit investigation of asymmetries that are evident in entrepreneurship, and provide only a single explanation that belies the multiple pathways to entrepreneurship observed in practice. This paper employs a case-based approach—fuzzy-set Qualitative Comparative Analysis (fsQCA)—to identify configurations of antecedent attributes of individuals in groups within samples, thereby revealing asymmetries and multiple entrepreneurial pathways that are otherwise hidden in the data. We explain the application of fsQCA to reveal these common issues in entrepreneurship; demonstrate how fsQCA complements correlational methods and offers finer-grained understanding of individual entrepreneurial behavior; and offer a comprehensive research agenda to build new entrepreneurship theory.