Decentralized autonomous organization in built environments: applications, potential and limitations

Reachsak Ly & Alireza Shojaei

Information Systems and e-Business Management2025https://doi.org/10.1007/s10257-025-00699-1article
AJG 2ABDC B
Weight
0.41

Abstract

Abstracts The operations of built environment-related sectors are often run on centralized organizational structures. This centralized approach could lead to operational challenges that restrict efficiency, hinder transparency, and misalign with the community’s interests. The emergence of decentralized autonomous organization (DAO) presents a promising avenue for addressing these issues by leveraging blockchain technology and decentralized governance models. This paper presents a review of DAO, examining its existing applications, limitations, and potential use cases in the built environment. Seven categories of DAO applications in the built environment were identified and discussed. The study also explores DAO’s fundamentals, including its governance characteristics, operational mechanism, limitations and technical implementation, and corresponding challenges. Finally, this study highlights three potential areas in the built environment for future DAO use cases. This article serves as an essential reference for future academics, professionals, and policy regulators interested in learning more about the integrations of DAO in the built environment.

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https://doi.org/https://doi.org/10.1007/s10257-025-00699-1

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@article{reachsak2025,
  title        = {{Decentralized autonomous organization in built environments: applications, potential and limitations}},
  author       = {Reachsak Ly & Alireza Shojaei},
  journal      = {Information Systems and e-Business Management},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1007/s10257-025-00699-1},
}

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Evidence weight

0.41

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.25 × 0.4 = 0.10
M · momentum0.55 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.