Pathways to Performance: A Configurational Analysis of Consensus in DAOs

Abstract

Decentralized Autonomous Organizations (DAOs) represent a radical form of socio-technical systems, where rules are enforced by code and governance is conducted by a distributed network of stakeholders. A critical challenge in designing these systems is achieving consensus without centralized authority, yet how consensus ensures effective governance remains underexplored. This study investigates the design of DAO governance systems, utilizing data from 70 DAOs and applying Fuzzy Set Qualitative Comparative Analysis (fsQCA) to explore which consensus configurations lead to positive organizational outcomes. Our analysis challenges the notion of a single consensus model. Instead, we uncover 13 distinct configurations that characterize successful DAOs. Our key finding reveals a fundamental “ideation-legitimation trade-off”: successful DAOs optimize for broad participation in either the proposal (ideation) stage or the voting (legitimation) stage, but rarely both. These insights provide a nuanced framework for understanding and designing effective governance systems for DAOs.