This study aims to explain the configurational research approach in comparison with a traditional correlation-based research approach and show how it enables researchers to build an appropriate theory for complex business phenomena. A configurational approach views a case as a combination of interdependent elements and allows researchers to explain how the elements work together and combine to produce the outcome of interest (conjunction), not just into a single configuration but multiple configurations (equifinality), and an element causally related in one configuration may be unrelated or even inversely related in another (asymmetry). As a matching configurational method, qualitative comparative analysis (QCA) has been increasingly used by studies in diverse disciplines as a main research approach for both deductive theory testing and inductive theory building. Rather than focusing on the linear net-effect of independent variables on the outcome of interest, QCA enables researchers to investigate the complex interdependencies among all elements and empirically analyze how they simultaneously combine into multiple configurations to achieve the outcome. This study provides detailed guidelines for applying QCA step-by-step with an illustrative example. By doing so, this study intends to help researchers understand the unique problems of causal complexity and build a configuration theory with QCA to explain causal mechanisms that could not be well captured with a traditional correlational approach.