Non-Fungible Tokens (NFTs) have emerged as a new organizational layer of digital exchange, raising questions about how participation, concentration, and community formation are structured within on-chain markets. Understanding whether these structures differ systematically across blockchain ecosystems with distinct asset orientations requires examining ecosystem-level interaction patterns. Most studies focus on specific collections or single platforms, offering limited insight into how connectivity, concentration, and community structure vary across markets with different NFT use cases. This study compares Ethereum and Polygon, two major NFT platforms with distinct dominant asset orientations (investment-oriented vs utility-oriented), to examine how their transaction networks differ at the ecosystem level. Using 3.9 million NFT transactions from May 2022 to May 2024, we apply network analysis to assess connectivity, centralization, community structure, and temporal dynamics. The findings show highly skewed interaction patterns in both ecosystems, with a small subset of addresses accounting for a disproportionate share of activity. Polygon networks exhibit higher modular segmentation and sharper upper-tail dominance, with communities aligning near-perfectly with application-specific boundaries, whereas Ethereum networks display comparatively more integrated, crosscollection interaction structure. These contrasts are interpreted as ecosystem-level structural patterns conditional on each chain's market composition and dominant NFT use cases, offering socio-technical insights into how participation concentrates and communities form across blockchain-based digital markets.
Non-fungible token (NFT) marketplaces are the main venues for NFT transactions. In recent years, these platforms have introduced ”Sweeping,” a bulk purchasing feature intended to improve the buying experience and enhance market liquidity. Although this feature offers clear benefits, such as simplifying the purchase of multiple NFTs and reducing gas fees, its actual effects on market dynamics remain underexplored. This study examines how the bulk purchasing feature affects two key dimensions of the NFT market, liquidity and speculation. Using a comprehensive dataset of Ethereum on-chain NFT transactions, NFT collection characteristics, and Twitter data, we adopt a rigorous identification strategy that combines Propensity Score Matching (PSM) with Difference-in-Differences (DID) estimation to identify causal effects. We find that the bulk purchasing feature significantly increases both liquidity (measured by transaction volume and sales count) and speculation (measured by price volatility and turnover rate) at the collection level. These results are consistent with Transaction Cost Economics (TCE). We also find heterogeneous effects. Collections with higher economic and social value experience larger gains in liquidity. In contrast, the effect on speculation remains similar across collections with different value attributes. These findings offer decision support for NFT marketplace operators seeking to design and implement bulk trading mechanisms.
João Pires da Cruz, Daniel Costa, Pedro Granate, Armando Teixeira · 6 authors
We study the formation and evolution of trading networks in non-fungible token (NFT) markets using transaction-level data from two major collections, Bored Ape Yacht Club (BAYC) and Azuki. We introduce a simple transaction-based clustering rule that identifies dynamically evolving trading networks formed by buyer-seller interactions. These networks correspond to persistent trading structures linking wallets through sequences of transactions. We document three main empirical regularities. First, trading networks emerge endogenously and exhibit heavy-tailed size distributions consistent with preferential attachment dynamics. Second, the internal connectivity of large networks displays scale-free degree distributions characteristic of growing trading systems. Third, the lifetime of trading networks follows approximately exponential statistics, indicating a memoryless extinction process. These findings suggest that NFT markets are organized around evolving clusters of trading relationships rather than isolated transactions. The results replicate across collections, indicating that trading network formation is a robust structural feature of NFT markets. Our findings provide new evidence on the microstructure of digital asset markets and the mechanisms governing the formation and persistence of trading relationships.
Jun Young Byun, Yosep Na, Daehyun Kim, Hyun Ho Jeon · 6 authors
This paper examines whether on-chain factors derived from Ethereum blockchain data contain pricing information beyond established cryptocurrency risk factors. We construct 27 on-chain factors across four dimensions (network activity, scale-adjusted activity, valuation ratios, and token distribution) for 122 Ethereum-based tokens from July 2020 to August 2025, and evaluate them against 26 benchmark factors spanning size, momentum, volume, and volatility using a double-selection LASSO framework, complemented by portfolio sorts and three-factor regressions. Eight on-chain factors are significant in the cross-sectional pricing test, with the strongest evidence concentrated in scale-adjusted activity and token distribution. Transaction count to network value is the only factor that remains significant in the cross-sectional pricing test, portfolio sorts, and three-factor regressions. In contrast, valuation ratios based on market-to-realized values do not survive as independent sources of abnormal return once momentum is taken into account, reflecting the mechanical overlap between recent price appreciation and slowly adjusting realized values. Token-distribution factors, particularly small-holder share and centralized exchange share, generate the most robust abnormal returns and remain economically meaningful under equal-weighted construction and conservative transaction-cost assumptions. Subperiod analysis further reveals a change in on-chain pricing power: scale-adjusted activity factors are stronger earlier in the sample, whereas distribution-based factors become more important over time. Overall, the results show that blockchain-native information, especially holder distribution, captures a distinct dimension of cryptocurrency asset pricing.
Battery energy storage sits at the centre of Europe’s low-carbon transition, yet financing these assets remains fraught with uncertainty. This thesis asks a pointed question: how do market volatility, shifting regulations, and the threat of asset stranding jointly shape the ability of investors to fund centralised and decentralised storage projects in Germany and Sweden? Drawing on a comparative case study rooted in pragmatist thinking, the analysis pairs discounted cash flow modelling with a careful reading of policy documents, regulatory rulings, and industry commentary. All market data, wholesale electricity prices from ENTSO-E, ancillary-service auction results from national grid operators, cover the period 2019-2024 and are publicly accessible. What emerges is a stark contrast. German centralised battery energy storage systems (BESS) projects carry the heaviest risk burden: frequency containment reserve (FCR) market saturation, confirmed grid-fee hikes, and a massive connection-queue backlog combine to push the internal rate of return from 11.5% down to 2.8% under stress, rendering projects economically unviable. Swedish centralised projects fare better for now, though their dependence on a handful of ancillary-service markets introduces a concentration risk that warrants close monitoring. Across both countries, decentralised storage proves more financially resilient, revenue diversification across retail savings, frequency markets, and peak shaving translates into lower risk premiums and more favourable debt terms, even where headline returns are lower. Monte Carlo simulations confirm that investment feasibility is highly sensitive to revenue cannibalisation and policy shocks. Theoretically, the study extends asset stranding literature by demonstrating that stranding risk in modern storage infrastructure is fundamentally revenue-driven rather than technologically deterministic, with regulatory interventions capable of eroding cash flows as rapidly as market saturation. From a policy perspective, the findings underscore the urgent need for regulatory clarity on grid tariff structures in Germany, the development of a coherent national storage strategy in Sweden, and the effective implementation of the EU Storage Infrastructure Act. For market participants, the analysis establishes that decentralised, revenue-diversified storage configurations offer a more robust risk-return profile, lowering hurdle rates and facilitating capital allocation in Europe’s evolving flexibility markets.
Abstract Around three-quarters of Bitcoin transactions occur off-chain. While most empirical studies focus exclusively on on-chain transactions, only few papers analyse off-chain transactions. The empirical evidence of Bitcoin market considering both types of trading strategies remains limited. This paper is one of the first to present an empirical analysis of both on- and off-chain demand and supply-side factors and their short- and long-run relationship with the Bitcoin price. Employing the ARDL approach with daily data from 2019 to 2024, we demonstrate a differentiated contribution of on-chain and off-chain drivers to the Bitcoin price. In the long-run, off-chain demand pressures have a significant relationship with the Bitcoin price. In the short-run, both off-chain demand and supply factors are statistically significantly related to the Bitcoin price. The relationship between blockchain transactions and the Bitcoin price is also present, albeit likely operating through a different channel than off-chain trades. These findings confirm the dual nature of the Bitcoin market, in which price movements are related to both market fundamentals and speculative considerations captured by on- and off-chain trades, respectively.
The tokenization of real-world assets (RWAs) has emerged as a transformative application of blockchain technology, with market projections estimating trillions of dollars in tokenized assets within the coming decade. However, a fundamental challenge remains unaddressed: physical assets such as precious metals, stored commodities, and warehoused goods incur structural negative carry -- custody, insurance, and audit costs that accumulate over time. While existing tokenization models have successfully established the market for digital gold and treasuries, they typically manage operational costs at the issuer level. The FRS introduces a framework to bring these economics directly on-chain, avoiding mechanisms such as token rebasing that compromise fungibility and composability with decentralized finance (DeFi) protocols. This paper proposes the Fungible Reserve Standard (FRS), a deterministic token design framework that encodes carrying costs transparently into on-chain logic. The FRS introduces an asset-per-token variable q(t) that decreases according to a predefined annualized carrying cost rate, coupled with a supply reconciliation mechanism that preserves holder balances and ERC-20 composability. While mathematically inspired by the daily expense ratio accrual in traditional asset management -- which often embed centralized profit margins -- the FRS design specifically encodes actual operational carrying costs to provide pure institutional-grade accounting clarity without compromising DeFi compatibility. The framework is asset-agnostic and applicable to any real-world asset with positive, predictable holding costs.
The dissertation studies how privacy and trust are shaped by digital technologies: how individuals value privacy over personal data, how AI alters trust and disclosure, and how decentralised blockchains can sustainably replace trusted intermediaries. Chapter 1 argues that the 'privacy paradox' --- that individuals claim to value privacy, yet readily disclose personal data --- arises because privacy is treated as monolithic, when it is multidimensional. I develop a framework that distinguishes voluntary disclosure from involuntary data diffusion, reconciling the paradox by showing that disclosures reflect contextual trade-offs. Using a discrete choice experiment, I provide estimates of privacy valuations across both institutional and social contexts. I find that privacy has substantial value when exposure results in harmful consequences, such as socially revealing data reaching close contacts. I also document an AI privacy puzzle: individuals are less concerned about privacy from AI assistants than from the firms that develop them. Chapter 2 examines this AI privacy puzzle. Using a survey experiment, I replicate the finding from Chapter 1 specifically for firms in the AI industry, highlighting the privacy gap that arises despite the clear product--firm relationship. An information treatment that explicitly links AI assistants to their firms increases concern about both, but does not significantly reduce this gap. Instead, the gap also reflects the anthropomorphic features of AI assistants, aversion to the commercial nature of firms, and the trust and perceived control consumers attach to each. However, when respondents evaluate real-world AI assistant--firm pairs, brand familiarity is the strongest predictor of where privacy concern is attributed. Chapter 3 considers decentralised trust in blockchain systems, in which consensus mechanisms replace trusted intermediaries. I propose a 'proof of quiet quitting' consensus mechanism that reduces the excessive energy consumption of proof of work while retaining the decentralisation that proof of stake can compromise. By introducing a participation lottery with unrestricted entry and an endogenous cutoff, the mechanism separates maximum effort capacity from the probability of winning, inducing participants to exert no more than the minimum effort required in equilibrium.
Patrick Woitschig, Ruting Wang, Wolfgang Karl Härdle
Blockchain networks have raised growing public concerns due to their substantial electricity consumption. The transition from Proof-of-Work (PoW) to Proof-of-Stake (PoS) on the Ethereum network is widely regarded as a landmark event in reducing blockchain energy use, with prior studies commonly reporting energy savings exceeding 99%. However, existing estimates vary substantially because of the strong assumptions embedded in the dominant top-down and bottom-up approaches. The top-down approach assumes that miners' electricity costs are closely tied to mining revenue under market equilibrium, whereas the bottom-up approach relies on the assumed average efficiency of the mining fleet, which is unobservable and highly sensitive to assumptions regarding hardware composition and utilization. "The Merge'' provides an observable profitability-based sorting mechanism that helps identify the efficiency distribution of mining hardware. By observing which miners could profitably migrate to Ethereum Classic after "The Merge'', we infer the efficiency threshold of economically viable machines and reconstruct the pre-Merge mining fleet more realistically. Using this framework, we estimate Ethereum's pre-Merge PoW electricity demand at 2.98 GW. The Ethereum Classic midpoint residual post-Merge PoW demand of 0.099 GW implies net electricity savings of 96.67%; including the broader Ethash-family residual yields savings of approximately 93.7-96.3%. To further investigate the determinants of estimation divergence, we estimate a VAR model and find that fluctuations in Ethereum prices significantly affect mining equilibrium and implied energy consumption. Overall, the paper provides a transparent, behaviorally grounded framework for estimating blockchain electricity use and offers refined evidence on the energy implications of consensus-mechanism design.
Abstract This chapter reviews and contributes to the debate concerning the fiduciary duties of network participants of blockchain systems, with a focus on software developers and decentralized autonomous organization (DAO) members. After briefly introducing the concept of fiduciary duties in the UK and the US, the chapter surveys the early academic debates on the fiduciary status of core developers. It then turns to an analysis of the main case law in England and California relating to fiduciary duties in this space, before arguing that the imposition of implicit fiduciary duties could lead to unjust outcomes, deter participation in blockchain systems, and stifle innovation. Instead, the remainder of the chapter contends that pursuing co-regulatory efforts which are grounded in the principle of regulatory equivalence, such as the adoption of the COALA DAO Model Law, will secure the public policy objectives of imposing fiduciary duties, without sacrificing the distinctive features of blockchain networks.
<b>Maximal Extractable Value (MEV)</b> has evolved from a theoretical artifact of transparent transaction ordering into a dominant economic force shaping Proof-of-Stake (PoS) blockchain ecosystems. While early research framed MEV as an unavoidable but competitive phenomenon, recent infrastructure developments—particularly MEV relays, aggregators, and proposer-builder separation (PBS)—have enabled the consolidation of extractive power into coordinated intermediary groups. This paper introduces <b><i>MEV Aggregator Drift</i></b>, a structural phenomenon in which MEV extraction progressively centralizes into opaque, off-chain coordination clusters <b><i>(“collusion packs”)</i></b> that undermine validator neutrality, distort protocol incentives, and introduce cartel-like dynamics without explicit on-chain collusion. We analyze the economic drivers, execution mechanisms, and systemic risks of MEV collusion across PoS and DeFi systems, and argue that existing mitigations focus on efficiency while neglecting enforceable neutrality. Finally, we outline mitigation requirements centered on validator accountability, behavioral monitoring, and transaction ordering attestation.
Jan 1, 2026·Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
Blockchain, originally developed to solve the double-spending problem in digital currencies like Bitcoin, has evolved into a foundational technology with broad applications across public and private sectors.Its key features-immutability, decentralized trust, and cryptographic security-enable authenticated data sharing without the need for a central authority.This is particularly valuable in systems like supply chains, where participants may not know or trust each other.Smart contracts further enhance blockchain's utility by automating agreements through code, reducing uncertainty and fostering trust among stakeholders.The rise of the decentralized web, combined with emerging technologies like IoT, AI, and AR/VR, signals a wave of disruptive innovation whose full impact is yet to be seen.Given the rapid pace of development, academic research is essential to understand and guide blockchain's evolution.Conferences are especially important for timely knowledge dissemination, as they can keep up with the fast-moving nature of the field better than traditional journals.This mini-track builds on a series of successful sessions from HICSS conferences (HICSS-51 through HICSS-58), which have focused on blockchain's impact in areas such as fintech, transformation, and innovation.Over the years, it has served as a valuable forum for exploring blockchain technology and its implications for process improvement and innovation.For the current edition, six accepted papers contribute to expanding the academic understanding and supporting broader adoption of blockchain solutions.The first paper, "Playing Strategic Games in The Open Network (TON): Analyzing the Robustness of Proof-of-Stake Slashing Incentives", by Sascha Hgele, analyzes how rational validators in the TON blockchain respond to slashing penalties in a proof-of-stake system.Using a game-theoretic model, it reveals that when penalty enforcement is uncertain, validators strategically weigh risks and rewards, which impacts
The convergence of fundamental blockchain technology with the Ethereum network has ushered in a new era of decentralized innovation, moving beyond simple cryptocurrency transactions to a programmable, trustless ecosystem. By introducing smart contracts—self-executing, automated agreements—and the Ethereum Virtual Machine (EVM), Ethereum acts as a decentralized \\\"world computer\\\" that allows for the creation of decentralized applications (dApps) across numerous sectors, including finance, healthcare, and supply chain management. In recent years, blockchain technology has gained significant attention for its potential in various domains. However, the lack of interoperability between different blockchain platforms poses a significant challenge in meeting the demands of the modern world. To address this issue, our research focuses on unlocking blockchain interconnectivity through smart contract-driven cross-chain communication. We aim to contribute to the development of a model that enhances the functionality and usability of blockchain technology. To achieve interoperability, we explore various options and leverage the power of smart contracts.
On January 10, 2024 (July 23rd, 2024), the Commission approved the listing of eleven (eight) bitcoin-based (Ethereum-based) exchange-traded products (ETPs) in NYSE Arca, Nasdaq and Cboe BZX. Using these approvals as a natural experiment, we employ a program evaluation framework to study the impact of the introduction of crypto-based ETPs on the liquidity of spot bitcoin/Ethereum markets in crypto trading platforms. We use the most recently available blockchain data supplied by Kaiko. The estimation strategy identifies that while the level of liquidity has not changed, that the time series trading pattern has, and that successive returns are more (less) related. However, though returns are on average more correlated we find that the returns in the bitcoin and Ethereum spot market overall show improvements after the introduction of these ETPs globally as compared to before. The findings further shed light on the workings of different aspects of crypto asset markets.
We study the role of liquid staking and how it affects the interaction between issuance policy, economic productivity, and security in proof-of-stake blockchains, with a focus on the role of liquid staking. In a dynamic macro-finance framework, we show that issuance redistributes resources from productive on-chain activity to validators, which effectively acts as a tax on productive capital. This mechanism generates a Laffer-curve-type tradeoff: beyond an interior optimum, higher issuance weakens the productive base that finances security and reduces staking rewards. We then introduce liquid staking, which allows users to earn staking rewards while retaining liquidity for productive use. Liquid staking collapses the traditional tradeoff between staking and DeFi. When liquid staking tokens (LSTs) closely substitute for the native asset and benefit from strategic complementarities, issuance reallocates productive activity toward LSTs, compresses the feasible policy space, and can render issuance and slashing ineffective as policy instruments.
Este estudo analisa a arquitetura da interoperabilidade no ecossistema <b>Ethereum</b>, investigando como a padronização de interfaces e os mecanismos de comunicação entre contratos sustentam a natureza compostável da <b>Web3</b>. A pesquisa detalha a evolução dos padrões de tokens, partindo do <b>ERC-20</b> para ativos fungíveis, passando pelo <b>ERC-721</b> para ativos não-fungíveis (NFTs), até o advento do <b>ERC-1155</b>, que permite a gestão multi-token em um único contrato, otimizando custos de transação (<i>gas</i>).Além dos padrões, o texto explora os mecanismos de comunicação <i>cross-contract</i>, como o delegatecall, essenciais para a criação de sistemas modulares e contratos atualizáveis. No entanto, a obra ressalta que a interoperabilidade amplia a superfície de ataque, destacando a vulnerabilidade de <b>reentrância</b> e a importância do padrão <i>Checks-Effects-Interactions</i> para mitigar riscos financeiros. Por fim, o trabalho discute fronteiras emergentes, como o padrão <b>ERC-6551</b> (tokens vinculados a contas) e a necessidade de soluções seguras para a interoperabilidade entre diferentes blockchains (<i>cross-chain</i>).<br>
This paper introduces the Blockchain First-Principles Analysis (BFPA) framework, a novel methodology for the epistemic evaluation of distributed ledger systems. Unlike conventional blockchain assessment approaches that rely on performance metrics, tokenomics, or decentralization indices, BFPA constructs a rigorous derivation chain from physical laws and cryptographic assumptions through an action axiom to concrete protocol design decisions. The framework systematically identifies structural failure points by testing whether each design choice is derivable from foundational axioms or represents an ad hoc decision vulnerable to obsolescence. The framework introduces several analytical innovations: (i) a four-level axiom hierarchy anchoring evaluation in physics, cryptography, praxeology, and social consensus; (ii) a Nash equilibrium gate mechanism for social layer stability; (iii) a four-stage stability profile progressing from Nash equilibrium through evolutionarily stable strategies and lock-in to self-referential feedback; (iv) a lock-in typology distinguishing design-emergent, ecosystem-emergent, corporate-imposed, and regulatory-granted lock-in; and (v) a network effect genesis model identifying five necessary conditions for spontaneous adoption without marketing. We apply the framework systematically to eight major blockchain systems: Bitcoin, Ethereum, Solana, Monero, XRP, Polkadot, Tezos, and BNB Chain. The analysis reveals that epistemic design quality alone correlates weakly with market price and adoption. Lock-in type and network effect genesis conditions are substantially stronger predictors. This finding provides a principled explanation for two empirical puzzles: the Tezos Paradox (superior governance design, declining price) and the Monero Paradox (strong epistemic foundations, stagnant adoption). The framework provides a falsifiable, non-speculative methodology for institutional evaluation of blockchain systems as coordination mechanisms.
In late 2025 the Central Bank of Brazil (BCB) discontinued the Hyperledger Besu pilot platform of its DREX permissioned-CBDC programme and signalled a redesign of the next phase, while the broader DREX initiative remained under development. Throughout the documented pilot, consensus authority stayed within six BCB-operated nodes running QBFT, while the sixteen institutional participants operated non-validating nodes. We therefore approach the DREX experience not as a failed governance experiment by institutional validators but as a motivating case for a broader question: under what conditions could institutional participants of heterogeneous type be safely promoted to validators in a future distributed phase of a permissioned CBDC? We develop an action-incentive-compatibility condition for the permissioned-CBDC setting under parametric type heterogeneity (BAIC): an incentive condition stated on validators' actions rather than on reported types, designed against the regulator's distributional knowledge of validator types. (We retain the Bayesian label for the design-against-distribution object; under the present calibration the expectation over other validators' types is degenerate, a point we make explicit in Section 5.3.) A four-archetype typology of candidate validators systemic banks, mid-tier banks and cooperatives, authorised ntechs, and registry institutions characterises the heterogeneity any future distributed phase would need to discipline. Privacy law enters as a lower bound on the false-positive rate of any admissible monitoring signal, generating a privacysustainability frontier we characterise analytically. A Quadruple Alignment result gives sucient conditions for systemic integrity on four levels consensus protocol, individual BAIC, validator-list composition, and regulatory feasibility of the required monitoring with explicit hypotheses for necessity. The composition condition is stated in a synchronised form consistent with the timing of the coalitional game: a coalition of eective per-member gain at most G max is deterred for archetype k when G max ≤ D k , where D k is the discounted per-member deterrence threshold that accounts for both detection and the honest path's own false-positive exposure. Under a parametrisation disciplined by institutional facts, only systemic banks satisfy the synchronised composition certicate; mid-tier banks fail it by a non-trivial margin under pilot monitoring, and are not jointly admissible with systemic banks at the legal privacy oor; ntechs and registry institutions exhibit a decit that persists under any isolated reduction in the false-positive rate within the maintained parameterisation it is not closed by better monitoring alone. The reported centralised reorientation of DREX, which the model represents as a counterfactual low-false-positive benchmark for a distributed network, leaves the ntech and registry decit untouched, because it lies in the archetypes' utility fundamentals rather than in monitoring precision; closing it would require changing those fundamentals (mandate, reputational stake, accessible gains, or voting rights), not merely the signal.
This paper examines the Virtuals Protocol as a case study in economic innovation enabled by autonomous AI agents. It analyzes how the protocol establishes a comprehensive infrastructure that combines tokenized ownership, decentralized governance, and standardized coordination to support agent-based economic organization. Drawing on transaction cost economics and network economics, the study shows how the protocol reduces coordination costs and amplifies network effects through agent specialization and composability. The concept of Autonomous Agent Organizations (AAOs) is introduced as a functional subclass of Decentralized Autonomous Organizations (DAOs), distinguished by their greater economic autonomy and composable inter-agent collaboration. AAOs represent a novel form of economic organization that transcends traditional boundaries between firms, markets, and platforms. The findings offer theoretical contributions to economic organization theory and practical implications for platform design, governance, and regulatory development. As AI agents become an increasingly prevalent aspect of economic activity, the Virtuals Protocol provides a model for scalable, adaptive, and inclusive economic coordination.
This paper introduces DNET (Dual Network Exchange Technology), an interface architecture that unifies Settlement, Exchange, and Record generation into a single transaction structure for digital payments. Modern payment systems often treat exchange and settlement as separate backend processes, leading to fragmented identifiers, inconsistent idempotency behavior, and operational divergence across implementations. DNET resolves these issues by binding Payment Intent, Exchange Decision, and Settlement Outcome under a single TxID, enabling atomic SER‑coupling across Web2 and Web3 environments. The architecture provides a protocol‑level foundation for multi‑asset payments, ensuring traceability, auditability, and interoperability while reducing operational complexity. This work positions DNET as an OS‑layer interface for value transfer, offering a structural standard for future financial infrastructure.
There have been various attempts at token standards on numerous blockchain platforms today to fundamentally change the way assets are traded in the traditional capital markets, but there is a lack of research and resolution on regulatory issues that become the common foundation for interoperability and reusable standards. Our proposal, Regulatory Compliance Protocol (RCP), is based on the regulations and reports of 15 global financial institutions and standardizes recommendations and guidelines involving the overall asset tokenization of TradFi and DeFi into five regulatory groups: Traceability, Privacy, Enforceability, Finality and Tokenizability, compiling them into 31 items and presenting a benchmark for technology and standards as an underlying protocol. To review the legality and effectiveness of RCP, it was validated based on three tokenization and trading scenarios, and by benchmarking existing asset-tokenization standards (ERC-20, ERC-7943, ERC-1400, and ERC-3643) against RCP, it makes explicit which regulatory requirements each standard addresses at the token level and which remain inherently off-chain.
Real-world asset (RWA) tokenization has emerged as a prominent application of blockchain technology, enabling off-chain financial and non-financial assets to be represented through blockchain-based instruments. However, deployed RWA systems remain difficult to compare because legal claims, custody arrangements, token mechanics, verification processes, and on-chain integrations are often described separately. This paper develops a systems-level taxonomy of RWA tokenization to classify how off-chain assets are legally, economically, and technically represented on-chain. Following an iterative taxonomy-development method, we organize twenty-three dimensions into five components: governance, asset structure, token properties, distributed ledger technology, and economy. We apply the taxonomy to twenty major RWA systems selected by market capitalization and compare their design choices across asset classes and implementation models. The classification shows that current RWA tokenization is predominantly implemented through hybrid architectures: blockchain tokens support representation, transfer control, redemption workflows, pricing, and composability, while core legal guarantees remain anchored in off-chain legal wrappers, custodial arrangements, compliance processes, and verification mechanisms. The analysis also reveals recurring documentation gaps concerning voting rights, dispute forums, burn mechanics, supply constraints, and reserve verification. Overall, the taxonomy provides a structured basis for comparing RWA systems, identifying design patterns and limitations, and supporting future research on blockchain-based financial infrastructure.