Decentralized Autonomous Organizations (DAOs): Modeling and Analysis of Voting Decentralization Performance

The development of blockchain technology and the emergence of Web3 have given rise to a new paradigm known as Decentralized Autonomous Organizations (DAOs), online communities jointly owned and managed by members working for the same interests. Voting is the primary decision-making method within DAOs aligning with the decentralization philosophy. However, existing DAO voting mechanisms often exhibit a strong tendency toward centralized control, contradicting DAOs’ pursuit of decentralization. In the absence of a decentralization standard, we define the decentralization coefficient as a novel metric to evaluate the overall decentralization performance of DAO voting mechanisms quantitatively by establishing the first stochastic process model for the DAO voting process. By analyzing and simulating four typical voting mechanisms, we uncover that quorum and voting power thresholds, often thought to improve voting performance, may negatively impact decentralization. Additionally, the study analyzes the impact of three main factors, including voting power distribution, participation rate, and voting process, on decentralization. The findings highlight that decentralization is shaped by the interplay between these factors, rather than merely by adopting specific voting rules. This study provides a quantitative benchmark for future research and offers practical guidance for DAO designers, emphasizing the need to prioritize inclusive participation over additional voting conditions.

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Publication Details

Journal
Blockchain Research and Applications
Published
2026-01-01
DOI
https://doi.org/10.1016/j.bcra.2025.100437
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
0.00
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article

Decentralized Autonomous Organizations (DAOs): Modeling and Analysis of Voting Decentralization Performance

Yixuan Fan, Lei Zhang, Xinyi Lin, Yang Fang et al.
Blockchain Research and Applications
Blockchain Technology Applications and Security
article

Decentralized Autonomous Organizations (DAOs): Modeling and Analysis of Voting Decentralization Performance

Yixuan Fan, Lei Zhang, Xinyi Lin, Yang Fang, Yao Sun
article en

Abstract

The development of blockchain technology and the emergence of Web3 have given rise to a new paradigm known as Decentralized Autonomous Organizations (DAOs), online communities jointly owned and managed by members working for the same interests. Voting is the primary decision-making method within DAOs aligning with the decentralization philosophy. However, existing DAO voting mechanisms often exhibit a strong tendency toward centralized control, contradicting DAOs’ pursuit of decentralization. In the absence of a decentralization standard, we define the decentralization coefficient as a novel metric to evaluate the overall decentralization performance of DAO voting mechanisms quantitatively by establishing the first stochastic process model for the DAO voting process. By analyzing and simulating four typical voting mechanisms, we uncover that quorum and voting power thresholds, often thought to improve voting performance, may negatively impact decentralization. Additionally, the study analyzes the impact of three main factors, including voting power distribution, participation rate, and voting process, on decentralization. The findings highlight that decentralization is shaped by the interplay between these factors, rather than merely by adopting specific voting rules. This study provides a quantitative benchmark for future research and offers practical guidance for DAO designers, emphasizing the need to prioritize inclusive participation over additional voting conditions.

Blockchain Research and Applications
University of Glasgow (GB), University of Westminster (GB)
Peace, Justice and strong institutions
Openalex Percentile: Top 98%
Blockchain Technology Applications and Security
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Decentralized Autonomous Organizations (DAOs): Modeling and Analysis of Voting Decentralization Performance — Yixuan Fan, Lei Zhang, et al. · Blockchain Research and Applications (2026) | TGRS Research Map | TGRS