In traditional banking, repeated deposit-and-lend cycles let a single dollar of reserves support multiple dollars of claims. Decentralized finance produces an analogous structure with tokens. Constructing a Token Graph of 10,200 tokens across 200 blockchains, this paper maps the resulting hierarchy and shows that, by late 2025, each dollar of base assets supports $4.7 of total claims. An embedded yield correction disentangles two channels that raw data conflates: a compositional channel, where lending protocols concentrate in deeper tiers and mechanically raise average yields; and a liquidity channel, where each derivation step reduces secondary-market depth and depresses yields in liquidity-sensitive pools. The liquidity channel concentrates in DEX pools and vanishes in lending pools. A yield decomposition shows that the tier gradient operates entirely through fundamental protocol yields, not incentive-token emissions; quantile regressions reveal that the structural associations concentrate in the upper tail of the yield distribution, with near-zero effects at the median. These findings reframe DeFi's "double counting" as a structural risk question and identify liquidity fragmentation as the primary mechanism associated with yield variation across the token hierarchy.
Rarity is a key determinant of value in non-fungible token markets, yet its measurement remains fragmented, opaque, and theoretically underdeveloped. We analyse the statistical and combinatorial rarity metrics used by major platforms and show that most reduce to transformations of the Pythagorean means. The widely-used OpenRarity metric produces rankings identical to the geometric mean of attribute frequencies and is therefore not a new methodology. However, this approach admits a coherent probabilistic interpretation only under the assumption of trait independence. Alternative arithmetic- and harmonic-mean metrics lack theoretical justification, while the Jaccard distance is structurally biased when metadata omit missing traits. When metadata are standardised appropriately, Jaccard-based rankings are identical to the arithmetic mean ranks. These findings explain pervasive inconsistencies in rarity rankings and help explain the weak empirical relationship between price and rarity. We propose a standardised, theoretically grounded framework for rarity measurement that accommodates dependence structures and corrects metadata bias.
Decentralized Autonomous Organizations (DAOs) face a fundamental decentralization paradox: the characteristics that make them theoretically superior to existing hierarchical structures simultaneously undermine their practical effectiveness. This thesis investigates whether and how this paradox can be addressed through a multi-level analysis that encompasses price stability, market performance, and philanthropic implications. In doing so, this thesis aims to provide critical insights into DAOs, which are considered a new form of digital enterprise that facilitates collective action in managing digital commons. The thesis comprises three interconnected essays, each underpinned by a specific research question.<br><br>The first essay investigates how non-traditional performance indicators impact DAO volatility. Unlike some DAOs, which issue decentralized stablecoins to maintain stable token prices, most DAOs are built on a native token basis, whose value depends entirely on the effectiveness of governance and the protocolâÂÂs future adoption. This means their prices are more exposed to speculative trading, making volatility a central concern for these DAOs. Under these circumstances, native DAOs that are not built on a stable mechanism must rely on relevant performance indicators to assess token price stability from an investment perspective. However, non-traditional performance indicators, such as social media and wealth inequality, are not typically included when measuring the riskiness of crypto assets. Based on several econometric models and robustness checks (e.g., MM-type, GMM, and entropy balancing), the findings show that both social media dominance and wealth inequality significantly reduce DAO volatility. Drawing on herding behavior and equity theories, the concepts of digital elites and stability pacts demonstrate that strategic recentralization enhances price stability and enables the development of novel DAO risk assessment frameworks. This essay recognizes the relevance of social media dominance and wealth inequality as non-traditional performance indicators for predicting DAO volatility and can help establish a risk assessment framework that crypto investors can rely on when making informed decisions. <br><br>The second essay examines the impact of ownership concentration and duration on the performance of DAO markets. Using several econometric models and robustness checks (e.g., GLS, GMM, and PSM), the findings reveal a positive and significant impact of ownership concentration and duration across categories on DAO market performance. Furthermore, the findings indicate that the average ownership duration has a significant positive impact, whereas ownership concentration has a significant negative impact on DAO market performance. Drawing on participatory governance and social exchange theories, this essay proposes an optimal governance equilibrium model to enhance and sustain DAO market performance. Overall, this essay offers novel insights into how the token-holdersâ commitment mitigates decentralization's operational inefficiencies.<br><br>The third essay examines the application of DAOs in the charity sector and aims to deepen the understanding of crypto donors' perceptions of this technology. Improving transparency and trust in the charity sector is crucial, as donors increasingly seek new ways to monitor and verify their contributions. Specifically, this essay examines Maxity, the world's first Web3 Social Impact protocol that contributes to the 17 UN SDGs. By adopting a netnography approach and using UMAP, HDBSCAN, and BERTopic â three unsupervised machine learning models â this essay identified four latent dimensions related to DAO-based charitable activities. These findings reveal how donors perceive DAO as an effective channel for contributing to charitable causes, enabling greater transparency, faster donation delivery, cost-effectiveness, and increased trustworthiness. Furthermore, the concept of sociotechnical governance was introduced to theorize how DAO-enabled NFTs reshape institutional trust and refine traditional charity governance paradigms. This essay contributes to the expanding discussion on DAOs as an innovative channel for organizing and responding rapidly to humanitarian crises.
This paper investigates how blockchain consensus mechanisms and market mechanisms of liquidity provision affect price bubble formation in cryptocurrency markets. Specifically, we compare Proof-of-Work (PoW) and Proof-of-Stake (PoS) under two trading environments: a Limit Order Market (LOM) and an Automated Market Maker (AMM). We conduct a controlled laboratory experiment following a 2Ă2 between-subject design, generating four treatments: PoW-LOM, PoW-AMM, PoS-LOM, and PoS-AMM. Market outcomes are evaluated using standard bubble measures, including RD, RAD, RDMAX, AMPLITUDE, and CRASH. The results show that AMM-based markets exhibit weaker bubble dynamics than LOM-based markets, with lower mispricing, smaller peak overvaluation, and less severe crashes. By contrast, the results do not support the hypothesis that bubble formation is lower under PoS than under PoW. Instead, in the experimental setting, PoS treatments display stronger bubble patterns than PoW treatments. Overall, our results show that the institutional design of cryptocurrency markets plays an important role in shaping speculative price dynamics and market stability.
Blockchain oracles combine, within a single arrangement, activities that traditional finance assigns to distinct and in part regulated entities. We develop a four-stage oracle data lifecycle framework, covering sourcing, collection and reporting, aggregation, and delivery and consumption, and compare each stage with its counterpart in traditional wholesale data markets. In traditional markets, safeguards attach at the regulated start and end points of that lifecycle, and liability for mispricing rests on identifiable contractual parties. In DeFi, no regulated end-point exists: smart contracts execute on oracle prices automatically and irreversibly, and end-users bear mispricing risk without redress. Distinguishing control-based from supply-based regulatory hooks, we classify oracles as suppliers to DeFi arrangements. Because the risks accompanying the same activities differ, transplanting benchmark regulation would be disproportionate. We identify three paths forward: DeFi literacy, public-permissioned oracle networks, and regulated benchmark administrators publishing on-chain.
Decentralized finance (DeFi) promises cheaper, faster and more accessible financial services by replacing traditional regulated intermediaries with software protocols and smart contracts. But removing those intermediaries also removes the practical chokepoints for implementing modern financial regulation: customer identification and screening, disclosure, recordkeeping, operational safeguards and incident reporting. This paper argues that the core compliance challenge in DeFi is therefore a governance problem: regulators should focus less on DeFiâs underlying computer code and more on the control points where compliance duties could realistically be assigned, supervised and enforced. Identifying those control points could be challenging, however, because DeFi responsibilities are dispersed across software developers, governance structures, parties that interface with investors and third-party service providers. To address that challenge, the paper proposes a layered regulatory strategy comprising four complementary approaches: identifying and regulating gateway intermediaries that facilitate access to DeFi services; prescribing the compliance obligations those intermediaries should assume; establishing targeted governance standards for smart contracts and the oracle and data inputs on which they depend; and applying shadow-banking-type safeguards to constrain spillover channels between DeFi and the traditional financial system. No single approach would be sufficient on its own; their combined effect would reconstruct, at workable control points, the most critical accountability and oversight functions that DeFi displaces. Properly designed and implemented, this strategy could help to preserve DeFiâs efficiency benefits while cost-effectively restoring regulatory protection and accountability.
The intermediated holding of investment securities through tiered custody chains undermines the rights of investors. Distributed ledger technology offers potential solutions through direct investor-issuer connections, but emerging regulatory frameworks paradoxically recreate intermediation while providing weaker safeguards than for traditional securities. This article examines how current legal approaches to tokenised securities risk creating worse outcomes for investors, particularly retail participants.
Tobias Kranz, Vincent Schaaf, Tobias Guggenberger, Jens StrĂźker
Decentralized Finance (DeFi) promises to lay ground for a more open financial system enabled by blockchain technology. Therein, stablecoins have recently gained momentum as regulated and trusted payment instruments, increasingly adopted for cross-border transactions and supported by initiatives such as the GENIUS Act in the U.S. and the European MiCAR framework. While stablecoins create the foundation of trust for linking DeFi with traditional finance, the ecosystem still depends heavily on cryptocurrency markets due to limited real-world asset integration. Existing research largely focuses on traditional securities and tradable assets, but scant attention has been paid to one of the worldâs largest asset classes, real estate. To address this gap, we propose a framework for the tokenization of real estate for integration into the DeFi ecosystem. Using the Design Science Research (DSR) approach, we construct and evaluate our framework through expert interviews and smart contract simulations. The simulations validate technical feasibility and demonstrate efficiency gains, with batch transfers reducing transaction costs for portfolio purchases. Building on these evaluations, we derive design principles for the nascent field of real-world asset tokenization. These principles highlight the importance of covering the entire product range, pursuing end-to-end compliance, leveraging token standards for interoperability, and extending their functionality for efficiency and scalability. By combining regulatory, organizational, and technical perspectives, our work advances design knowledge for compliant integration of real-world assets into DeFi.
Dec 23, 2025¡Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
Tejas Kotha, Kushagra Bhatnagar, Leona Chandra Kruse, Matti Rossi
NFTs (non-fungible tokens) promised the interaction of artists/creators directly with their collectors without the need for any intermediaries, but the realisation was quick that such a technology, instead of getting rid of intermediaries, reintroduced new intermediaries in the form of NFT marketplaces. These marketplaces exhibit diverse features and cater to different user groups. A wide array of governance strategies, such as curation and gatekeeping, are used to steer creativity and interactions in the marketplace, informed by the marketplace's strategy. We examined this diversity by identifying the 'ideal types' of marketplaces based on these strategies alongside the motivations of the creators to make sense of the growing NFT market and constructed a typology that distinguishes four kinds of NFT marketplaces: Avant-garde, Canonical, Mass Culture, and Coterie. The article also offers practical implications for creators and collectors looking to make informed choices when deciding to participate in a particular marketplace.
This paper examines the strategic behavior of rational actors in the TON blockchain, focusing on their responses to slashing mechanisms in a proof-of-stake (PoS) environment. Slashing introduces financial penalties for behavior that threatens network integrity, addressing the nothing-at-stake problem, where validators in PoS systems can support multiple chains at no cost. Although slashing is intended to deter malicious behavior by Byzantine actors, it also affects rational validators by altering their expected returns. Using a game-theoretic model inspired by the BAR framework, this study examines how rational, utility-maximizing validators weigh the risks and rewards of violating or enforcing slashing mechanisms in the presence of potentially Byzantine actors when penalty enforcement is uncertain. Located at the intersection of game theory and distributed systems, this research sheds light on compliance and deviation dynamics in PoS networks, contributing to a deeper understanding of incentive alignment in blockchain governance.
The thesis deals with the development of a decentralized Ethereum-based application for purchasing, selling and playing music. The goal of the application is to demonstrate the use of a blockchain-based platform that can replace corporate intermediaries.
One of the main Web3 applications is Non-Fungible Tokens, blockchain-based certificates to keep track of the ownership of unique digital or physical assets. Nowadays, there is no standard method to evaluate an NFT, and only for a trait-based collection can we rely on the rarity score, which estimates the scarcity of the traits of the NFT. However, rarity is unsuitable for describing the price of a token in a volatile market, and it is not a good price indicator because a tokenâs price is strictly related to external unpredictable events and the interest people have in specific assets. In this paper, we propose an evaluation model called The Popularity Model , that aims to evaluate NFTs based on marketability The Popularity Model is based on a set of indices which define a dynamic, socioeconomic indicator, with an antifraud system. We formalised and compared our popularity model and the rarity score to show their differences. Finally, we propose two applicable use cases in which the popularity index can be applied. The experiments show and confirm the utility and efficacy of the proposed evaluation model.
The user-ownership model of Web3 commerce is widely viewed as a potential paradigm shift for the digital economy, yet its macroeconomic implications remain under-quantified within a unified, dynamic, and parameterized framework. This paper develops a tractable dynamic macroeconomic model of a âwealth flywheelâ featuring two feedback channels. The income loop operates through profit-backed user rebates that raise income-equivalent purchasing capacity and stimulate consumption. The asset loop operates through consumption-driven profit and valuation growth, which expands household wealth under user ownership and feeds back into consumption via wealth effects. In a static setting, the paper derives a closed-form consumption multiplier and a corresponding stability condition. Aggregate consumption responds proportionally to an exogenous income impulse, and the system is stable if the combined strength of rebate-induced consumption feedback and wealth-effect amplification remains below unity. The static mechanism is then embedded into a global multi-period simulation framework with time-varying Web3 penetration, finite-horizon household deposit reallocation into consumption, and endogenous valuation paths. Using illustrative parameterizations, the paper simulates trajectories for global real GDP, equity market capitalization, household wealth, and inflation under neutral and aggressive adoption scenarios. The analysis further examines distributional implications when capitalization gains are directed toward user cohorts with higher marginal propensities to consume. The framework provides a parsimonious diagnostic for stability in mechanism design and contributes to macro-prudential discussions of self-reinforcing growth dynamics. Importantly, the analysis abstracts from collateralized borrowing, leverage, rehypothecation, and other financial intermediation channels. All amplification effects in the model arise from ownership structure and wealth effects rather than from credit-driven financial accelerators.
Ankenbrand, Thomas, Bieri, Denis, Ferrazzini, Stefano, Hoehener, Johannes
Tokenised money encompasses a broad range of digital monetary instruments issued on distributed ledger technology, including Central Bank Digital Currencys (CBDCs), deposit tokens, stablecoins, and decentralised protocol-based designs. Despite their shared monetary function, these instruments differ markedly in issuer structure, collateralisation, stability mechanisms, governance, and technological embedding, creating conceptual ambiguity. This paper proposes a concise taxonomy spanning twelve key design dimensions, offering a systematic framework for comparing heterogeneous forms of tokenised money. The taxonomy clarifies how different design choices shape monetary properties, risks, and policy implications, supporting clearer analysis and dialogue across academia, industry, and regulation.
Despite the recognition of Blockchain Technologyâs disruptive potential, there is ongoing debate about its ontological and axiomatic foundations. This study develops a theoretical framework to explain the underline structural principles of blockchain technology through the lens of Arthurâs theory of technology, and the framework is developed through adopting Narrative Literature Review. By integrating conceptual analysis with a structural examination of Ethereum, this study reveals that blockchain technology is not a single invention but a composite technological system developed through recursive interactions among sub-technologies. The proposed framework identifies three interrelated structural patternsâthe Combinatorial Pattern of Components elucidating blockchain technologyâs structural ontology, the Capturing Pattern of Algorithms revealing the operational source of its innovation, and the Recursive Pattern of Technologies characterizing its inner logical structure of componentsâthat together explain blockchain technologyâs generative and evolving nature. The study extends Arthurâs theory by clarifying the âtechnology within technologyâ dynamic that underlies blockchain technology innovation. The Ethereum case confirms the frameworkâs applicability and generalizability, showing that blockchain systems, despite their diversity, share a consistent structural logic. Beyond its theoretical contribution, the framework offers practical guidance for sustainable technological innovation. It provides analytical support for designing blockchain-based applicationsâ architectures that enhance transparency, efficiency, and adaptability, contributing to the sustainable evolution of digital technologies.
This paper challenges the prevailing assumption in Central Bank Digital Currency (CBDC) design that comprehensive transaction surveillance is necessary for financial stability and crime prevention. We propose an alternative privacy-preserving architecture that achieves equivalent or superior fraud detection through mechanism design rather than identity monitoring. Key contributions: Separation of pattern detection from identity: Transaction graph analysis identifies structural anomalies without accessing participant identities Transaction-level intervention: Suspicious activity flags individual transactions, not accounts or users Opt-in deanonymization: Identity revelation is always voluntary; users may abandon flagged transactions without consequence Architectural enforcement: Privacy guarantees are structural, not policy-dependent The framework inverts the burden of proof in financial surveillance. Rather than requiring users to demonstrate legitimacy, it requires the system to demonstrate suspicionâand even then, users retain the option to walk away. This creates a game-theoretic deterrent where illicit actors cannot complete transactions, while legitimate users experience minimal friction. We demonstrate that privacy-preserving CBDC architecture is technically feasible using established cryptographic primitives (zero-knowledge proofs, secure multi-party computation, threshold cryptography) and that the choice to implement surveillance infrastructure represents a policy decision rather than technical necessity. Part of the Adversarial Systems Research program investigating friction dynamics in complex systems where competing interests generate structural conflict.
Ethereum, as a leading blockchain platform, experiences high variability in transaction fees due to network congestion, gas bidding, and computational complexity. This study analyzes 10,000 Ethereum transactions to identify key factors influencing transaction fees, block density, and staking mechanisms. The results show that transaction fees vary significantly, with an average of 0.1826 ETH and a standard deviation of 0.2381 ETH, indicating substantial fluctuations. A strong positive correlation (r = 0.72) between transaction size and transaction fee confirms that larger transactions incur higher costs due to increased computational demand. Time-series analysis reveals periodic spikes in gas fees, aligning with network congestion patterns. Block density averages 1718.8% (std = 501.01%), showing that some blocks are highly congested while others are underutilized. An Isolation Forest anomaly detection model identifies 3.4% of transactions as outliers, exhibiting unusually high gas fees, which may be caused by priority-based bidding, inefficient smart contract execution, or potential fee manipulation. Further analysis demonstrates that Coin Age and Stake Reward significantly influence transaction success rates. Transactions with older coins show a 7.8% higher success rate, indicating that validators may prioritize transactions with greater historical weight. Additionally, Stake Reward positively affects the Block Generation Rate (p < 0.05), confirming its role in securing the network and optimizing transaction processing. These findings provide valuable insights for Ethereum users, developers, and validators to optimize gas fees, transaction timing, and staking incentives. While this study offers critical observations, future research should focus on real-time gas fee monitoring, deep learning-based congestion forecasting, and the impact of Layer-2 scaling solutions. Understanding Ethereumâs Proof-of-Stake (PoS) dynamics will be essential for ensuring fair transaction processing, reducing gas fees, and improving blockchain efficiency.
Ledger-native payment systems introduce a radically new interaction paradigm at the point of sale. Rather than relying on legacy card-based processing networks, these systems enable merchant devices and user devices to collaboratively perform the construction, authorization, signing, and broadcasting of a transaction directly to a digital ledger. Once biometric authentication is performed on the userâs device, the remaining steps of the payment flow may be distributed flexibly between the devices. This shift allows the point-of-sale environment to evolve into an expressive, adaptive, and deeply interactive interface layer. This white paper presents a comprehensive exploration of the experiential landscape surrounding ledger-native payments, mapping the full set of user-experience, sensory, identity, environmental, and data-driven capabilities that emerge once retail transactions operate directly on a cryptographic substrate. The document is fully self-contained and articulates the future UX domain rather than any specific implementation.
Abstract We present a spatial analysis of Bitcoin-accepting merchants using BTC Map, a global crowdsourced dataset built on OpenStreetMap, to provide ground-level evidence on Bitcoinâs payment ecosystem. While prior research emphasizes macroeconomic drivers, our analysis of approximately 11,000 merchants shows that local adoption is more strongly shaped by community dynamics and sectoral niches. Acknowledging quality variance in crowdsourced data, we focus on verified regional clusters. We find a global concentration of adoption in the hospitality sector, localised clusters driven by grassroots initiatives rather than national policy and significant presence in alternative healthcare and IT services. These findings highlight the limits of top-down interventions such as El Salvadorâs legal tender law and underscore the role of social networks in sustaining adoption. By contrasting spatial micro-level evidence with national studies, this work positions merchant data as a key lens for understanding Bitcoinâs evolving role as a medium of exchange.
This study explores Bitcoin's value formation through the Granular Interaction Thinking Theory-Value Theory (GITT-VT). Rather than stemming from material utility or cash flows, Bitcoin's value arises from informational attributes and interactions of multiple factors, including cryptographic order, decentralization-enabled autonomy, trust embedded in the consensus mechanism, and socio-narrative coherence that reduce entropy within decentralized value-exchange processes. To empirically assess this perspective, a Bayesian linear model was estimated using daily data from 2022 to 2025, operationalizing four informational value dimensions: Store-of-Value (SOV), Autonomy (AUT), Social-Signal Value (SSV), and Hedonic-Sentiment Value (HSV). Results indicate that only SSV exerts a highly credible positive effect on next-day returns, highlighting the dominant role of high-entropy social information in short-term pricing dynamics. In contrast, SOV and AUT show moderately reliable positive associations, reflecting their roles as low-entropy structural anchors of long-term value. HSV displays no credible predictive effect. The study advances interdisciplinary value theory and demonstrates Bitcoin as a dual-layer entropy-regulating socio-technological ecosystem. The findings offer implications for digital asset valuation, investment education, and future research on entropy dynamics across non-cash-flow digital assets.
R. Li, Srisht Fateh Singh, Andreas Park, Andreas Veneris
This paper presents a securities tokenization solution that brings the accessibility, transparency, efficiency, and innovation of blockchain and decentralized finance to real-world securities. Tokenization in principle seems straightforwardâan intermediary holds assets and issues 1:1 tokensâbut decentralized finance applications (DeFi) introduce significant complications. Even basic DeFi mechanisms, such as liquidity pools, pose challenges for tokenizing stocks and bonds because when assets are pooled in smart contracts, ownership becomes unclear, hindering asset owners to access their entitlements, such as dividends, coupons, or voting rights. Existing solutions often fail to address these challenges and are typically limited to specific security types. Our solution, by contrast, generalizes to any security and any holding rights through fungible tokens and using separate smart contracts for shareholders to redeem their entitlements. To address the decentralized ownership issue, our solution employs off-chain accounting with additional logic for liquidity pools. We implement this on Ethereum, demonstrating that it is 27% cheaper in gas costs than current alternatives. We also analyze the liquidity logic of over 90% of Ethereum's liquidity pools, confirming compatibility with our solution. Finally, we demonstrate its use for dividend-paying stocks, common stock, mergers, and coupon-paying bonds.
This dissertation examines the evolving market microstructure of digital assets, focusing on transaction costs, liquidity provision returns, and the development of innovative exchange mechanisms. In three essays, the research provides empirical evidence on digital asset trading in both traditional and emerging decentralized market architectures. Each essay addresses previously unresolved questions, offering valuable insights for researchers, practitioners, and regulators to better understand and manage the benefits, costs, and risks of trading in digital asset markets.The first essay examines the cost of trading across digital assets in traditional centralized limit-order-book exchanges and a nascent, decentralized market architecture: the Automated Market Maker. By employing a novel methodology the study extends prior research that relies on less detailed, low-frequency information. The findings reveal transaction cost advantages for Automated Market Makers with remarkable stability across varying levels of market volatility, trading volume, and market capitalization. These results offer practical insights into execution venue selection and market design considerations.The second essay explores the evolution of Automated Market Makers, using the introduction of a new generation of these exchange architectures as a case study. In addition to documenting their technical advancements, the research shows that asset pairs migrate to the new Automated-Market-Maker models based on asset-specific fundamentals. The study makes key contributions through two experimental setups, demonstrating that reductions in inventory costs and the introduction of flexible fee tiers deliver welfare benefits for both liquidity demanders and providers. These findings enrich the broader discussion on market design and highlight the potential for innovative mechanisms to enhance efficiency in both decentralized and traditional financial systems.The third essay sheds light on liquidity provision in Automated Market Makers. Leveraging granular profitability data, the study finds that a small subset of liquidity providers dominate liquidity provision. These sophisticated agents achieve significantly higher absolute and relative profits compared to retail participants, while demonstrating a high level of skill. The emergence of these de-facto intermediaries challenges the decentralized finance ethos of disintermediation, highlighting that liquidity provision, even in decentralized markets, remains dominated by specialists. Understanding the composition of participants in these nascent markets is not only crucial for practitioners but also regulators, enabling them to develop targeted and effective policies that promote fair and competitive market environments.
David DavĂł, Javier Arroyo, Samer Hassan, Silvia Semenzin
Despite the hype and scandals around blockchain, there are valuable applications beyond finance, such as decentralized autonomous organizations (DAOs). DAOs are self-governed online communities where users vote and manage budgets transparently. In under a decade, DAOs have evolved from theory to managing billions of dollars. Blockchain enthusiasts launched DAO platforms like our case study, âDAOstackâ, promising large-scale collaboration and quickly securing millions in funding. Today, we can critically evaluate to what extent the platform followed up on its promises. In this work, we analyze DAOstack using a mixed-methods approach combining quantitative and qualitative data. In particular, we quantitatively examined its 92 organizations in terms of size, lifespan, activity, power concentration, and the effectiveness of its governance model. We also interviewed in-depth 6 DAOstack core users to delve deep into their experiences using the platform. Our analysis shows that DAOstack mainly hosted small, short-lived DAOs, with some exceptions. Its governance model was functional, but the economic incentives underpinning it were ineffective. The analysis of the interviews reveals interesting aspects such as the power imbalances due to token ownership and reputation, and that the voting system, though innovative, was affected by issues of cost and complexity. We conclude by discussing the challenges these platforms face and advocating for a multidisciplinary experimental approach for future DAO designers.