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December 26, 2025· Proceedings of the 2025 6th International Conference on Computer Science and Management Technology
conference-paper
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Optimizing Liquid Democracy in Product and Service DAOs: A Dual-Token Voting Power Calibration Mechanism

Authors:Jing TuYaozhi Liu

Abstract

Decentralized Autonomous Organizations (DAOs), powered by blockchain technology and smart contracts, have opened new avenues for addressing corporate governance challenges, such as effectively reducing contract risks and mitigating other organizational management issues. However, as a typical complex system that integrates both social and engineering complexities, DAOs still face problems in governance practice, including insufficient decentralization and low member participation. In particular, the liquid democracy design in their voting mechanisms-intended to allow members to flexibly switch between direct voting and delegated proxy-often leads to the phenomenon of “delegation equals abstention,” which is particularly acute in Product and Service DAOs, resulting in declining overall participation rates and excessive concentration of governance power among a few individuals. To address these challenges, this paper employs the ACP method (Artificial Systems + Computational Experiments + Parallel Execution) and proposes a dual-token governance mechanism that couples governance rights with an incentive layer. This mechanism moderately decouples governance rights from utility rights, encouraging ordinary members to shift from passive delegation to active participation in governance. At the same time, we introduce an SBT-based reputation system grounded in cumulative contributions, which dynamically constrains the upper limit of delegated receipts, thereby institutionally curbing the unchecked expansion of power by super delegates. Through case analysis combined with computational experiments, the effectiveness of this mechanism in enhancing the degree of governance decentralization and member participation is validated, providing both technical pathways and theoretical references for DAO governance optimization.

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