Modular DAOs for community-based resilience: a blockchain architecture for critical infrastructure funding
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Author(s)
Levinson, Augustus
Mulligan, Catherine
Ozdemir-Sonmez, Ferda
Knottenbelt, William
Type
Journal Article
Abstract
Critical infrastructure systems in many countries face persistent financing and delivery challenges, including delayed disbursement, limited transparency, and constrained local participation. While blockchain-based systems have been proposed as alternatives, existing work primarily evaluates their technical properties rather than their ability to support resilience under disruption. This paper introduces Community-Based Resilience (CBR) as a framework for evaluating blockchain-enabled infrastructure financing. We propose a modular architecture based on decentralised autonomous organisations (DAOs) that enables project-level fundraising, tokenised ownership, and programmable governance through smart contracts on Ethereum-compatible networks. The system is implemented in Solidity and evaluated through static security analysis, gas-cost benchmarking across Ethereum and Layer-2 rollups, and an illustrative discrete-event simulation of fund reallocation under shock. The simulation is not calibrated to a deployed field system; rather, it is used to explore how governance latency and modular reallocation assumptions affect service-continuity metrics under a stylised scenario. Under those assumptions, DAO-based governance produces lower cumulative service loss than a donor-funded baseline, illustrating the design intent rather than validating field performance. The paper contributes a CBR-based evaluation framework, a modular DAO architecture, and a resilience-oriented methodology for assessing infrastructure systems under disruption.
Date Issued
2026-08-08
Date Acceptance
2026-07-11
Citation
Blockchain: Research and Applications, 2026
ISSN
2096-7209
Publisher
Elsevier BV
Start Page
100544
End Page
100544
Journal / Book Title
Blockchain: Research and Applications
Copyright Statement
©2026 Published by Elsevier Ltd on behalf of Zhejiang University Press. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)
Publication Status
Published online
Article Number
100544
Date Publish Online
2026-08-08
