Governance through Reputation: An Inventory of Reputation Systems in Decentralized Autonomous Organizations (DAOs)
The study is an exploratory, qualitative analysis aimed at inductively gaining insight into the diverse practices and forms of reputation-based governance within DAOs. The research design involved selecting a diverse sample of 10 DAOs and systematically coding and analyzing their white papers. The coding process focused on identifying inputs (methods for earning reputation) and outputs (applications of reputation), with the input-output typology emerging inductively from the data. Through this analysis, we uncovered a total of 9 inputs and 5 outputs, as well as the relationships between them, which helped us map out how reputation is strategically used to govern behavior and foster cooperation within DAOs.
Drawing on our inductive analysis, we propose a typology of reputation management approaches, organized around two core criteria: (1) the type of contribution being assessed (contribution-based vs. community participation-based rewards) and (2) the method of assessment (automatic tracking vs. peer evaluation). The resulting four ideal-typical reputation governance models reflect different views of social control in DAOs, balancing objectivity, subjectivity, individual performance, and community cohesion.
Our analysis of the complexities of reputation-based governance contributes to deepening our understanding of democratic participation in digital commons, exploring the current range of practical solutions for fostering trust, cooperation, and inclusion.