Analysing the Governance and Coordination Properties of DAOs Managing Physical Assets

Level: BA/MA
Responsible person: Parminder Kaur Makode
Keywords:  DAO, Conceptual Framework, Design Science 

1. Introduction  

Decentralised Autonomous Organisations (DAOs) are blockchain-based collectives that coordinate ownership, decision-making, and resource allocation through smart contracts and token-based voting. While many DAOs exist purely in digital ecosystems, a growing class of physical-asset DAOs governs tangible real-world assets such as real estate, sports clubs, co-living spaces, and infrastructure networks. These entities merge on-chain transparency with off-chain legal and operational responsibilities, creating hybrid governance systems. 
This project aims to systematically analyse how DAOs managing physical assets coordinate participation, manage resources, and maintain decentralisation using publicly available data from platforms such as DeepDAO, Snapshot, Tally, and Messari. 

2. Project Description 

This master project/theses aims to construct and analyse a comprehensive dataset of DAOs managing real-world assets by integrating governance data from DeepDAO, Snapshot, Tally, Messari, and official DAO forums. 
The student will evaluate participation, decision-making, and power-concentration patterns and identify why some DAOs succeed or fail in governing tangible assets. 

Key research directions include: 

Comparative analysis of governance metrics across 20–50 physical-asset DAOs. 

Investigation of failed or inactive DAOs. 

Correlation between governance concentration (e.g., token Gini, delegate dominance) and proposal throughput or pass rates. 

3. Expected Analyses 

The project will analyse multiple governance and participation metrics from both on-chain and off-chain sources. It will measure participation (average voters per proposal, unique voters, proposers, and retention) and concentration (token Gini coefficient, top-10 holder share, delegate concentration). Governance performance will be assessed through proposal throughput, pass rate, and decision latency. The study will also track disputes and governance incidents such as contested proposals, vetoes, or forks, and identify the resolution mechanisms used (e.g., Kleros, Snapshot veto). In addition, community behaviour will be examined through forum participation, sentiment, and topic clustering, while failure or decline will be evaluated based on changes in voter turnout, treasury activity, and possible legal or operational causes of dissolution. 

4. Skills Required 

Basic proficiency in Python or R for data analysis and visualization (pandas, matplotlib, seaborn). 

Experience with data collection and cleaning, including working with APIs (Snapshot, Tally, DeepDAO) and large datasets. 

Ability to handle and analyse big data, ensuring reproducible and efficient processing of governance and voting records. 

Familiarity with blockchain data platforms (DeepDAO, Snapshot API, Messari) and DAO governance dashboards. 

Understanding of DAO governance concepts and basic knowledge of smart contracts or token-based voting systems. 

5. References 

1. Blum, M., Crimi, N., Emmenegger, P., Spychiger, F., & Tessone, C. J. (2025). Governance and Maintenance for DAOs With Physical Assets–The Case of No1s1. Blockchain: Research and Applications, 100357. 

2. Spychiger, F., Makode, P. K., Küng, L., & Tessone, C. J. (2024, July). Governance and maintenance for a DAO with physical assets-an agent-based Model. In 2024 IEEE international conference on omni-layer intelligent systems (COINS) (pp. 1-6). IEEE. 

3. Lustenberger, M., Spychiger, F., Küng, L., & Martignoni, J. (2025). DAOs as property owners: a conceptual exploration from the perspective of organizational system theory. Journal of Organization Design, 1-17. 

4. Hunhevicz, J. J., Wang, H., Hess, L., & Hall, D. (2021). no1s1–a blockchain-based DAO prototype for autonomous space. In proceedings of the 2021 european Conference on Computing in Construction (Vol. 2, pp. 27-33). University College Dublin