Subcoalition Cluster Analysis: A New Method for Measuring Conflict in Organizations

Behavioral theories of organizational decision making emphasize that organizations are political coalitions. Despite considerable recent qualitative research in management and organizational theory on the role of politics in decision making and managing organizational change, quantitative research in this area has stalled. The reason for the lack of progress is not theoretical, but rather methodological; researchers lack empirical tools for understanding basic processes of coalition formation, evolution, and conflict in organizations. We introduce a novel method for modeling politics in organizations that builds on the model of intra-organizational conflict in March (1962), which we call “subcoalition cluster analysis” (sCCA). The main contribution of sCCA is that it identifies subcoalitions with consistent preferences that are in conflict without placing additional restrictions on the structure of individual preferences. We apply sCCA to two cases, Wikipedia and the Baseball Writers’ Association of America and show how leadership would benefit from conceiving of their membership as competing subcoalitions instead of individuals with idiosyncratic preference disagreement. Finally, we compare the performance of sCCA to Principal Component Analysis (PCA) and k-means clustering and demonstrate that sCCA does a better job identifying latent structure in the data when the organization consists of more subcoalitions, when individual preferences are not perfectly aligned with those of their subcoalition, and when observations are missing.