Combining Qualitative Comparative Analysis and Shapley Value Decomposition: A Novel Approach for Modeling Complex Causal Structures in Dynamic Markets

Depending on which combination of factors is used in empirical analyses, regression results lead to varying levels of significance or even insignificance and, consequently, to inconsistent results. Linear algebra and linear regression models are apparently not able to analyze complex causal structures in dynamic markets. Boolean algebra, qualitative comparative analysis (QCA) and the game theoretical-based model of the Shapley value could be more suitable for covering dynamic market structures and, consequently, for helping us to understand what significantly affects complex cause-effect relationships. Using proprietary data from the volatile motion-picture industry, we show that a segmentation and brand extension strategy are sufficient for achieving high market performance and that certain conditions (e.g., production budget, critic reviews and brand extension products) appear particularly appropriate for gaining a competitive advantage.