Building Better Causal Theories: A Fuzzy Set Approach to Typologies in Organization Research
提出一种基于因果核心与外围的新理论视角，利用模糊集定性比较分析（fsQCA）研究高科技企业中的Miles和Snow类型学配置，揭示因果核心、外围和不对称性，推动中程因果理论发展。
Typologies are an important way of organizing the complex cause-effect relationships that are key building blocks of the strategy and organization literatures. Here, I develop a novel theoretical perspective on causal core and periphery, which is based on how elements of a configuration are connected to outcomes. Using data on high-technology firms, I empirically investigate configurations based on the Miles and Snow typology using fuzzy set qualitative comparative analysis (fsQCA). My findings show how the theoretical perspective developed here allows for a detailed analysis of causal core, periphery, and asymmetry, shifting the focus to midrange theories of causal processes.