Building Better Causal Theories: A Fuzzy Set Approach to Typologies in Organization Research

This work develops a novel theoretical perspective on causal core and periphery, which is based on how elements of a configuration are connected to outcomes, and empirically investigates configurations based on the Miles and Snow typology using fuzzy set qualitative comparative analysis (fsQCA).

Abstract

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.