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Studying temporal change using Qualitative Comparative Analysis (QCA) allows researchers to examine complex and dynamic causal pathways between configurations of time-based conditions and a desired outcome. No comprehensive QCA technique currently addresses complex temporal changes in a unified manner. To remedy these shortcomings, we introduce Growth Pattern QCA—a mixed-method technique for studying complex growth dynamics. We integrate a quantitative computational toolkit for calculating growth slopes with QCA and demonstrate it using an illustrative multiyear panel. We offer practical guidance for researchers to apply these mixed methods for analyzing and forecasting complex growth patterns in various entrepreneurship research settings. We also review existing techniques and provide a decision roadmap of time-related QCA methods for researchers to use the best option for their research objectives.
Du et al. (Sat,) studied this question.
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