Social Learning in Decentralized Autonomous Organizations (DAOs)

Abstract

We document social learning in the form of information cascades in proposals put up for vote in decentralized autonomous organizations (DAOs). Exploring hand-collected data covering 19,450,710 votes from 924,095 unique voters in 3,317 DAO governance proposals, we identify economically strong information cascades that run from influential through early to late voters. Several contextual factors impede social learning in DAOs, including the presence of cybercriminals in the DAO community and market sentiment, while the decentralization of token ownership is an important prerequisite for information cascades to unfold. Finally, we establish a link between the potency of information cascades and the financial performance of DAOs. Stronger information cascades are associated with higher market capitalization, trading volume, and abnormal cryptocurrency token returns. Overall, our study shows how decentralized digital communities coordinate to create economic value in entrepreneurial settings.

Keywords: Social learning, information cascades, decentralized autonomous organization (DAO)