Il contributo analizza il ruolo delle piattaforme digitali nell’evoluzione dei mercati contemporanei e le trasformazioni prodotte dall’integrazione tra Web2, Web3 e intelligenza artificiale. L’Autore esamina l’emersione di nuovi modelli economici fondati sulla gestione dei dati, sulla profilazione degli utenti e sulla crescente capacità delle piattaforme di incidere sulle scelte dei consumatori e sugli equilibri istituzionali. Emergono cosi le differenze tra i modelli regolatori adottati nell’Unione europea, negli Stati Uniti e in Cina, evidenziando il ruolo centrale delle autorità indipendenti e delle reti europee di coordinamento nella costruzione di strumenti di vigilanza, enforcement e cross-regulation. Particolare attenzione è dedicata ai settori strategici interessati dalla trasformazione digitale — trasporti, mercati finanziari, energia, cybersicurezza e contratti pubblici — nei quali l’interazione tra piattaforme, dati e intelligenza artificiale impone nuove forme di tutela dei consumatori e nuovi modelli di regolazione partecipata. The contribution analyses the role of digital platforms in the evolution of contemporary markets and the transformations generated by the interaction between Web2, Web3 and artificial intelligence. The Author examines the emergence of new economic models based on data management, user profiling and the increasing ability of platforms to influence consumer choices and institutional balances. The work explores the different regulatory approaches adopted by the European Union, the United States and China, highlighting the central role of independent authorities and European coordination networks in developing mechanisms of supervision, enforcement and cross-regulation. Particular attention is devoted to strategic sectors affected by digital transformation — including transport, financial markets, energy, cybersecurity and public procurement — where the interaction between platforms, data and artificial intelligence requires new forms of consumer protection and innovative models of participatory regulation.
Il contributo analizza l’evoluzione delle piattaforme digitali di pagamento nel passaggio dai modelli del Web2 alle prospettive del Web3, con particolare attenzione alle ricadute per i consumatori, gli operatori e le autorità di vigilanza. L’Autore ricostruisce le principali trasformazioni del settore dei pagamenti, segnato dalla convergenza tra innovazione tecnologica, nuove discipline europee, esigenze di sicurezza, contenimento delle frodi e tutela della fiducia degli utenti. Il saggio approfondisce il ruolo del nuovo pacchetto normativo europeo sui servizi di pagamento, con riferimento alla PSD3 e al Payment Services Regulation, evidenziando le criticità connesse alla responsabilità dei prestatori di servizi di pagamento, alla colpa grave dell’utente, all’educazione finanziaria e alla crescente rilevanza dei servizi tecnici abilitanti, dei digital wallet e delle BigTech. Particolare attenzione è dedicata all’euro digitale, considerato come possibile ponte tra Web2 e Web3 e come strumento per preservare il ruolo della moneta pubblica nell’ecosistema digitale. Il contributo esamina infine le stablecoins, mettendo a confronto l’approccio prudenziale europeo, fondato su MiCA, stabilità finanziaria e sovranità monetaria, con l’impostazione statunitense più orientata al mercato. In conclusione, viene sottolineata la centralità di un enforcement coerente, coordinato e multilivello, capace di bilanciare innovazione, certezza del diritto, tutela dei consumatori e stabilità del sistema dei pagamenti. The contribution analyses the evolution of digital payment platforms in the transition from Web2 models to Web3 perspectives, with particular attention to the implications for consumers, operators and supervisory authorities. The Author reconstructs the main transformations affecting the payment sector, shaped by the convergence of technological innovation, new European rules, security needs, fraud prevention and the protection of users’ trust. The essay examines the role of the new European regulatory package on payment services, with reference to PSD3 and the Payment Services Regulation, highlighting the issues related to the liability of payment service providers, the concept of gross negligence of users, financial education and the growing importance of enabling technical services, digital wallets and BigTech companies. Particular attention is devoted to the digital euro, considered as a possible bridge between Web2 and Web3 and as a tool to preserve the role of public money in the digital ecosystem. The contribution also explores stablecoins, comparing the European prudential approach, based on MiCA, financial stability and monetary sovereignty, with the more market-driven approach adopted in the United States. In conclusion, the essay emphasizes the central role of coherent, coordinated and multi-level enforcement, capable of balancing innovation, legal certainty, consumer protection and the stability of the payment system.
Non Fungible Token (NFT) Industry has been witnessing 16 million dollar trade in recent times.The following is the development of the decentralized NFT marketplace divided into three principal phases: smart contract development on the Ethereum blockchain using Solidity, creation of the frontend using React.js,Next.js,Node.js,HTML, CSS, and JavaScript, and backend development using Express.jsand MongoDB.The aim of this project is to offer a transparent and safe digital marketplace to mint, buy, and trade NFTs.The project employs ERC-721 standards for the uniqueness of tokens, Web3.js for interaction with smart contracts, and off-chain metadata storage with the help of REST APIs and MongoDB.Results indicate that the marketplace functions securely and efficiently, with seamless user interaction and successful on-chain transaction execution.Challenges related to deployment cost, metadata storage, and smart contract gas optimization were addressed during development.The final product demonstrates a fully functional, scalable, and decentralized NFT marketplace platform.
Current blockchain research and analytics tend to prioritize observable on-chain transactions, obscuring the processes through which cryptocurrencies are created, publicised, retained, and disposed of. In response, this paper considers distributed ledger technologies from records management principles in ISO 15489-1:2016. Setting off by specifying the parallels -- that is transactions as "records", crypto-asset units as "information assets", and blockchains as "aggregations" -- we introduce a seven-stage lifecycle for blockchain data. We apply the framework to Bitcoin, a fungible token, and a non-fungible token. On this basis, we argue that blockchain systems are not merely transactional infrastructures but record management systems with distinctive characteristics. We discuss how the on-chain/off-chain boundary and privacy-enhancing technologies can complicate lifecycle visibility, with particular relevance for crypto-crime research and investigation. As a meta-level framework, the lifecycle perspective enables positioning existing research, decomposing legal, regulatory, technological, and operational challenges by stage, and informing lifecycle-aware approaches to blockchain governance, analytics, and regulation.
This paper presents an open-economy macroeconomic equilibrium model for Proof-of-Stake (PoS) networks with fee-burn mechanics (EIP-1559) that formalizes the strategic interplay between a Kelly-optimizing rational institutional investor and a utility-driven retail consumer. We analyze network dynamics across two behavioral regimes. In The Unbounded Accumulation Model, the consumer purely accumulates tokens, creating an exclusive buy-side pressure that interacts with institutional portfolio rebalancing to fuel an ever-expanding speculative bubble and generate compounding excess returns for investors. Conversely, in The Utility-Consumption Model, the consumer dynamically buys and sells tokens to balance crypto wealth against real-world fiat consumption. Within this framework, we derive an explicit steady-state equilibrium price for ETH, demonstrating how token valuation anchors to a stable fundamental baseline that scales directly with network adoption while completely dissolving the institutional yield premium. Our numerical simulations show that while exogenous traditional finance (TradFi) shocks propagate through portfolio rebalancing to drive high token price volatility, network inflation remains highly stable. Furthermore, we prove that network security is insulated from institutional monopoly by counter-cyclical consumer behavior. Our findings reveal that institutional excess wealth creation in PoS ecosystems is not native to the staking protocol itself, but is strictly driven by the leveraged extraction of the retail consumer's continuous demand for transactional utility.
Strategic alliances have long required their participants to combine the certainty of formal contracts with the adaptive flexibility of relational mechanisms, and the substitutes-complements debate in alliance governance has spent decades trying to clarify how these two qualities can be combined.The recent emergence of blockchain-enabled smart contracts complicates this picture in interesting ways.This article asks how smart contracts interact with the contractual and relational governance mechanisms documented in the strategic alliance literature, what conditions shape this interaction, and what the implications are for alliance theory.Drawing on the alliance governance literature and the blockchain governance literature in roughly equal measure, the paper develops a framework that positions smart contracts as a third governance mechanism alongside contractual and relational forms, producing a hybrid arrangement termed algorithmic-relational governance.Three propositions are derived and illustrated through a case study of Walmart Canada's DL Freight platform, one of the larger production-grade smart contract deployments in a multi-party alliance setting.The findings suggest that smart contracts function primarily as governance complements rather than substitutes, that they alter alliance dynamics in ways transaction cost economics alone cannot predict, and that their effectiveness depends on deliberate architectural design choices that are themselves products of relational negotiation between alliance partners.
This paper discusses the technological development from Web 1.0 to Web 3.0, focusing on their corresponding economic models. The study begins by analyzing the Web 1.0 portal economy, followed by an in-depth exploration of the rise of the Web 2.0 platform economy and its associated challenges, including the lemon market, platform monopolies, price discrimination, and algorithmic asymmetries. To address those issues, this study elaborates on the Web 3.0 token economy and emphasizes the crucial role of decentralized technologies like blockchain in bringing new production factors and relationships. This inspires the proposal of the Decentralized Economy (DeEco), a novel user-autonomous economic model that integrates advanced Artificial Intelligence (AI) technologies with blockchain. Furthermore, the key techniques for formulating DeEco are analyzed, including Decentralized Autonomous Organizations and Operations (DAOs), Decentralized Value Systems (DVSs), Decentralized Physical Infrastructure Networks (DePIN) and digital humans. This study not only offers a co-evolutionary perspective of web technologies and economic forms but also introduces an innovative economic paradigm to support open, diverse and intelligent societies.
Decentralized Finance (DeFi) represents an emerging financial ecosystem that offers services such as lending, investing, and trading without traditional intermediaries like banks or financial institutions. Unlike conventional financial systems, users interact directly with software programs called smart contracts that encode financial logic and automate service delivery. This novel ecosystem promises transparency through public blockchain ledgers that make all transactions visible and inclusion through open access that eliminates traditional barriers to financial participation. Additionally, DeFi enables decentralized governance where users participate in protocol decision-making, and smart contracts facilitate advanced financial engineering through compositional service integration. However, despite these technical innovations, DeFi introduces significant challenges related to transaction complexity, governance concentration, and cybersecurity vulnerabilities that undermine its foundational promises. This thesis develops computational methods to systematically investigate these challenges in Decentralized Finance through empirical analysis of blockchain data. First, to address the complexity of DeFi compositions, we developed an algorithm that extracts fundamental building blocks from individual transactions, revealing recurring patterns and hidden interdependencies between financial services and assets that manual analysis cannot capture at scale. Second, we applied network analysis techniques and introduced novel measurements to examine the governance structures of decentralized applications, focusing on contributors with development and administrative roles. Our analysis revealed common voting patterns and centralized decision-making that contradict claims of decentralized governance. Third, we adapted a difference-in-differences statistical framework to quantify the economic impact of cybercrime on governance tokens, demonstrating that indirect effects on prices and trading volumes significantly exceed the direct losses suffered by immediate victims. These computational methods collectively provide the first systematic, large-scale analytical framework for empirically investigating DeFi ecosystems, revealing fundamental gaps between theoretical promises of transparency and inclusion and practical realities. The findings have significant implications for researchers, policymakers, and practitioners by establishing evidence-based approaches to measuring decentralization claims and systemic risks in blockchain-based financial systems.
Zishan Ashraf Mohammad, Nick Harkiolakis, Saman Sarbazvatan
Although there has been a massive increase in the size and complexity of the cryptocurrency ecosystem, most of the academic research into the relationship between token design parameters and the long-term value of a given token is still very much in its infancy. Most of the research in tokenomics is theoretical in nature, based upon frameworks for understanding, or is focused solely on observing a specific time frame. The authors of this paper address the above mentioned void by studying the statistically significant relationships between five on-chain tokenomic variables--transaction gas fees, total value locked (TVL), token unlocks, tokens burned, and governance concentration (as measured using the Gini coefficient) -- and the market price of Ether (ETH) during a 52 months observation window that began in August 2021 and ended in September 2025. The data for the study consisted of bi-weekly observations (n = 108) which allowed researchers to use three different analytical methods--Spearman correlation analysis, log-linear multiple regression analysis, and an error correction model (ECM) after conducting Johansen cointegration and unit root tests. A cointegrating equation among the variables was established through Johansen Trace Testing, indicating that all of these variables do indeed exhibit a long-run equilibrium relationship. The ECM revealed that the total amount of funds “locked” into smart contracts (“total value locked”) was the strongest single predictor of the price of Ether in both the long run (beta = 0.8, p < 0.001) and short run (beta = 1.18, p < 0.001) specifications. Additionally, it was found that token unlocks have a negative relationship with price (beta = −0.22, p < 0.001). Gas Fees (beta = 0.2, p = 0.021) and tokens burned (beta = 0.15, p = 0.039) had positive coefficients at the 0.01 level in the long-run specification; however, both exhibited extremely high levels of multicolinearity (Variance Inflation Factor>28,000), likely due to their technical/operational linkages under EIP-1559. Voting power did not demonstrate a statistically significant relationship to price (rho =0.143, p > 0.05).
Vladimir Kovšca, Zrinka Lacković Vincek, Suzana Keglević Kozjak
Prior research on cryptoasset valuation has largely adapted discounted cash flow (DCF) models by treating staking rewards and transaction fees as productive cash flows, while insufficiently accounting for monetary characteristics and strategic flexibility inherent to decentralized platforms. This study investigates whether such cashflow based approaches systematically undervalue Ethereum. The central hypothesis is that Ethereum’s intrinsic value cannot be adequately explained by DCF valuation alone, and that monetary premium and technological optionality constitute economically significant components of value. To examine this hypothesis, a multi-layer valuation framework is applied using network and market data from 2022–2025, combining a DCF model, a monetary premium benchmarked against gold based on relative scarcity and adoption, and a real option uplift reflecting future expansion potential. Monte Carlo simulation is employed to test the robustness of the results. The findings indicate that while DCF-based valuations remain relatively stable, total intrinsic value is highly sensitive to assumptions regarding monetary adoption and strategic optionality. These results underline the importance of layered valuation frameworks for decentralized platforms.
This conceptual paper explores the profound impact and pivotal role of information systems (IS) within the rapidly evolving landscape of Decentralized Finance (DeFi). Emerging from the advancements in blockchain technology, DeFi represents a paradigm shift in financial management, offering an ecosystem that is more inclusive, transparent, and efficient by removing centralized intermediaries through smart contracts. This paper analyzes how IS principles are fundamental to the design, management, and security of DeFi protocols, contrasting them with traditional financial systems. It delves into core DeFi applications such as Decentralized Exchanges (DEXs), lending/borrowing protocols, stablecoins, and yield farming, emphasizing their underlying IS architectures and the challenges related to user experience (UX/UI). Furthermore, the paper discusses critical IS aspects in DeFi, including security management, automation via smart contracts, blockchain-based analytics for risk management and anomaly detection, and the unique governance mechanisms through Decentralized Autonomous Organizations (DAOs). Finally, it outlines the future trajectory of DeFi, considering its integration with emerging technologies like Artificial Intelligence (AI) and Web3, and its evolving relationship with global financial systems and regulations. This work contributes to understanding the complex interplay between technology and finance, highlighting how robust information systems are indispensable for DeFi's sustained growth and its potential to reshape the digital financial ecosystem.
This online appendix accompanies the main paper of the same title. It contains thefull proofs of the propositions stated in the main paper, the multi-regime Jacobian andbifurcation analysis, the notation table, and the code-and-data documentation for theempirical execution. Section and equation references that appear in this document referto the main paper unless explicitly prefixed by OA-.
Introduction, Sports science data governance is characterized by persistent tensions between data sharing, stakeholder incentives, and regulatory constraints. These challenges are amplified by fragmented data infrastructures and competing interests among stakeholders, limiting the effective use of data in performance optimization and research. Objective, This study aims to develop and theoretically ground a decentralized autonomous organization (DAO)-based governance framework for sports science data ecosystems, focusing on how decentralized mechanisms can enhance coordination, participation, and compliance. Methodology, A multi-method research design is employed, integrating conceptual case analysis, agent-based modeling (ABM), and survey-based empirical analysis. Structural equation modeling (SEM) is used to examine the relationships between governance perceptions, incentives, and data-sharing intentions. Results, The findings indicate that DAO-based mechanisms can support more distributed and transparent data-sharing processes. Simulation results suggest that participation dynamics follow non-linear patterns, with incentive and reputation mechanisms contributing to system stabilization. Empirical results identify technical usability, perceived regulatory compliance, and incentive structures as significant predictors of stakeholder participation. Discussion, The study contributes to platform governance and institutional theory by conceptualizing a hybrid decentralized governance model for data-intensive environments. The findings highlight the importance of aligning technological design with usability and regulatory requirements. However, limitations related to model assumptions, perception-based data, and interoperability challenges remain. Future research should focus on real-world implementation and the development of standardized governance frameworks.
Capped-usage SaaS products -- LLM subscriptions such as Claude Code and ChatGPT, cloud platforms such as Vercel and Cloudflare Workers, corporate benefit platforms, identity-verification services with liability transfer -- share a structural signature with insurance products: a fixed premium decoupled from realized consumption, stochastic per-user demand with heavy-tailed severity, a non-fungible cap that resets on a fixed schedule, and a portfolio-level exposure that requires reserve adequacy under tail risk. We argue that this is not an analogy. It is the same operational problem actuarial science has been tooled for decades to address, restated with new dependent variables (tokens, bandwidth bytes, function-invocations, gym check-ins) in place of medical claims. This paper proposes a modeling framework for capped-usage SaaS pricing built from frequency-severity decomposition, premium calculation principles, and Monte Carlo reserve adequacy. We map the framework to publicly observable subscription tiers in two domains (LLM services and cloud platforms), ground it in canonical health-insurance economics (Arrow 1963; Pauly 1968; Manning et al. 1987; Brot-Goldberg et al. 2017), and demonstrate divergence from traditional unit economics through a worked example. The contribution is operational rather than theoretical: not a new theorem, but vocabulary and tools currently absent from cs.LG/stat.ML practice.
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Artificial Intelligence in Healthcare and Education
Jeong-Hyuck Park, Chanhee Park, Claudio J. Tessone, Yu Zhang
Digitalisation transforms money from distinguishable physical objects into fungible informational units. A recent theoretical framework predicts that such indistinguishable wealth obeys bosonic occupancy statistics, leading to geometric ownership distributions and enhanced inequality. Using Bitcoin blockchain data, we test this prediction on 63 UTXO denominations across 72 monthly snapshots (2018--2023). A one-parameter geometric model describes the ownership distributions, reproducing both mean holdings and their temporal evolution; Jensen--Shannon divergence values lie below $0.08$ in $99.74\%$ of cases. The inferred inverse-temperature parameter satisfies the analytic mean--temperature relation to better than $0.1\%$ in every sample -- a self-consistency test that two-parameter alternatives cannot pass -- and remains within a narrow band across eight orders of magnitude in denomination and over six years. Bitcoin UTXO ownership statistics are therefore consistent with bosonic occupancy laws, suggesting that the informational nature of electronic money may act as a structural driver of inequality in digital economies.
A non-custodial threshold instrument for Bitcoin would allow value to transfer between parties without network connectivity, fees, or custodial dependency. Digital signatures and multisignature scripts provide part of the solution, but the core benefit is lost if the issuer retains a key capable of unilateral redemption. All prior multisignature schemes have positioned the issuer at or above the spending threshold. We propose a system that inverts this: the holder receives the two keys constituting the spending threshold of a 2-of-3 multisignature script, and the issuer holds one key arithmetically below it.
Distributed ledger technology (DLT) has emerged as a transformative force in decentralized data management across e-transactions, with significant applications in the banking, finance, supply chain, and trade sectors. Recognizing its potential, governments, including Estonia and India, have implemented DLT-based e-services to enhance transparency and privacy in public administration. With numerous platforms arising/available in the DLT segment, such as Hyperledger, Ethereum, Corda, Ripple, Stellar, Dragonchain, IOTA, and Hedera, understanding interoperability mechanisms across heterogeneous platforms has become critical. This comprehensive research provides a systematic analysis of distributed ledger technology fundamentals, consensus mechanisms, smart contracts, and their applications in e-governance services. The study examines leading DLT platforms and their core features, with a specific focus on interoperability capabilities essential for seamless cross-platform integration. Through analysis of existing interoperability solutions, including trade finance platforms, central bank digital currency initiatives, and e-governance implementations, this work identifies critical challenges and evaluation criteria for DLT adoption. The research addresses three primary research questions: (1) what capabilities does DLT provide for implementing effective e-governance strategies? (2) How does interoperability influence the delivery and effectiveness of various e-governance services? (3) What is the current impact and growth trajectory of existing e-governance services providing interoperability capabilities? The primary contributions include systematic exploration of interoperability mechanisms in various DLT platforms, documentation of existing implementations across multiple countries, including Estonia, the European Union, Dubai, and India, identification of technical challenges and security considerations, and development of a future roadmap for DLT-influenced e-governance systems. The research demonstrates that effective interoperability, combined with emerging technologies such as artificial intelligence and quantum-resistant cryptography, can enable citizen-centric, transparent, and secure governance systems while maintaining regulatory compliance and data privacy.
Automated market makers (AMMs) quote prices from pool state rather than from a limit order book. AMM pools often stay close to a reference price because arbitrageurs correct profitable mispricing. A large part of decentralized finance therefore relies on a simple economic premise: once the AMM price drifts away from the reference price, arbitrage incentives push it back. This paper studies when that premise is strong enough to guarantee block-scale stability. We model the gap between the reference price and the AMM price as a stochastic tracking error, treat arbitrage as the corrective input, and place blockchain execution inside the loop through fees, discrete blocks, transaction ordering, delays, and transaction failure. The detailed execution layer is reduced to the total successful correction confirmed in each block. Under a block-level correction condition, we prove geometric ergodicity of the tracking error and obtain explicit one-step bounds that connect tracking quality to liquidity and execution quality. We also show in a constant-product example how fees, fixed execution costs, and local liquidity map into the no-trade band and the optimal corrective trade. Finally, we build empirical proxies for the theorem quantities from realized block data and use them to organize reduced and mechanism-focused simulations whose comparative statics are consistent with the theory. The contribution is to turn a basic economic intuition behind decentralized finance into a quantitative stability statement together with a tractable calibration interface.
The European Commission's April 2026 age verification framework, built on software-based Zero-Knowledge Proofs (ZKP) atop the European Digital Identity (EUDI) Wallet, fails to achieve its stated privacy guarantees due to a structural enrollment binding problem: any ZKP scheme whose trust root is a government identity credential inherits that credential's linkability at the point of issuance. This paper proposes a replacement architecture based on hardware bearer credentials — physically issued FIDO2 tokens whose identity binding is discarded immediately after issuance — combined with an anonymous hardware-handle revocation list, offline kiosk enrollment, and a self-funding economic model. The proposal is technically feasible with current production technology, financially viable at EU procurement scale, and operationally self-sustaining through a €10 citizen co-payment at issuance plus a €30 replacement fee. A cost model for national deployment using Italy as a case study demonstrates that the system requires near-zero net public expenditure. The primary novel contribution is a game-theoretic mechanism embedded in the replacement fee structure that renders secondary market trading of credentials economically irrational without requiring any surveillance of credential holders.
Résumé Au Maroc, les très petites entreprises (TPE) représentent 96 % du tissu entrepreneurial et génèrent 23 % du PIB, mais 75 à 80 % d'entre elles demeurent exclues du crédit bancaire formel. Dans ce contexte d'exclusion financière structurelle, la Finance Décentralisée (DeFi) — fondée sur les technologies blockchain et les smart contracts — se présente comme une alternative potentielle. Toutefois, son adoption par les dirigeants de TPE reste conditionnée par un ensemble de déterminants encore peu explorés dans la littérature, en particulier la confiance dans ces technologies. Cet article vise à identifier les déterminants de l'intention d'adoption de la DeFi par les TPE marocaines à travers une revue de la littérature et la proposition d'un modèle conceptuel de recherche. En s'appuyant sur le modèle UTAUT (Venkatesh et al., 2003) comme cadre théorique de référence, complété par les théories de la confiance dans les systèmes technologiques (McKnight et al., 2002 ; Pavlou, 2003 ; Zhou, 2011), cet article propose un modèle étendu intégrant cinq déterminants directs de l'intention d'adoption : la facilité d'usage perçue, l'utilité perçue, l'influence sociale, les conditions facilitatrices, et la confiance dans la technologie DeFi — algorithmi que et institutionnelle. Le genre et l'âge du dirigeant sont intégrés comme variables modératrices. Sur le plan théorique, cet article contribue à enrichir la littérature sur l'adoption des FinTech en proposant une opérationnalisation de la confiance adaptée aux spécificités de la DeFi dans un contexte d'économie émergente. Sur le plan managérial, il fournit un cadre actionnable pour les décideurs publics, les régulateurs et les concepteurs de solutions DeFi ciblant les marchés non bancarisés. Mots-clés : Finance Décentralisée (DeFi) ; UTAUT ; Confiance ; Adoption technologique ; TPE Maroc ; Inclusion financière ; Blockchain ; FinTech ; Modèle conceptuel Abstract In Morocco, micro-enterprises (TPEs) account for 96% of the entrepreneurial fabric and generate 23% of GDP, yet 75 to 80% of them remain excluded from formal bank credit. Against this backdrop of structural financial exclusion, Decentralized Finance (DeFi) — built on blockchain technologies and smart contracts — emerges as a potential alternative. However, its adoption by TPE managers remains conditional on a set of determinants that are still underexplored in the literature, particularly trust in these technologies. This paper aims to identify the determinants of DeFi adoption intention among Moroccan micro-enterprises through a literature review and the proposal of a conceptual research model. Drawing on the UTAUT model (Venkatesh et al., 2003) as the theoretical framework, complemented by trust theories in technological systems (McKnight et al., 2002; Pavlou, 2003; Zhou, 2011), this article proposes an extended model integrating five direct determinants of adoption intention: perceived ease of use, perceived usefulness, social influence, facilitating conditions, and trust in DeFi technology — algorithmic and institutional. The manager's gender and age are included as moderating variables. Theoretically, this article contributes to the FinTech adoption literature by proposing an operationalization of trust adapted to the specificities of DeFi in an emerging economy context. Managerially, it provides an actionable framework for policymakers, regulators, and DeFi solution designers targeting unbanked markets. Keywords: Decentralized Finance (DeFi); UTAUT; Trust; Technology Adoption; Micro-Enterprises Morocco; Financial Inclusion; Blockchain; FinTech; Conceptual Model
The rapid advancement of blockchain technology has given rise to Decentralized Finance (DeFi), a financial ecosystem that operates without traditional intermediaries and challenges the foundational structures of conventional banking. DeFi platforms enable peer-to-peer financial services through smart contracts, offering increased transparency, accessibility, and efficiency. This study aims to analyze the potential of DeFi to disrupt traditional banking models by examining its core mechanisms, value propositions, and structural differences from centralized financial institutions. The research seeks to assess both the opportunities and challenges posed by DeFi in reshaping financial intermediation. A qualitative analytical approach was employed, drawing on an integrative review of peer-reviewed literature, industry reports, and documented DeFi case examples. Data were analyzed through thematic synthesis to compare DeFi functionalities with traditional banking operations, focusing on governance, risk management, and financial inclusion. The findings indicate that DeFi introduces innovative financial models that reduce transaction costs, expand access to financial services, and enhance operational transparency. The study concludes that DeFi represents a transformative yet complementary force rather than a complete replacement for traditional banking. Its future impact will depend on regulatory adaptation, technological maturity, and institutional integration.
Ding Ding, Yang Li, Poh Ling Neo, Zhiyuan Wang · 5 authors
This paper develops a tractable theoretical framework to study how network participation shapes the boom–bust dynamics of non-fungible token (NFT) prices. We model NFT pricing under network effects and heterogeneous consumers, and show that prices and participation are jointly determined in equilibrium. The model implies a critical participation threshold that separates expansion from contraction regimes: above this threshold, positive feedback between participation and valuation generates self-reinforcing growth, while below it, weakening network benefits lead to contraction. We provide empirical evidence using data from the aggregate NFT market and prominent collections including Bored Ape Yacht Club (BAYC) and CryptoPunks. Reduced-form regressions show a positive association between prices and network participation, with stronger effects at the collection level than in the aggregate market. Threshold estimation further provides evidence consistent with regime-dependent dynamics, with clearer tipping behaviour in well-defined NFT communities than in the aggregate market. These findings suggest that NFT valuation is closely tied to network structure and participation dynamics. More broadly, this paper contributes a unified framework that links participation, price formation, and threshold behaviour in NFT markets.
Ignat Melnikov, Roman Vlasov, Vladimir Gorgadze, Andrey Seoev · 5 authors
Decentralized Finance (DeFi) is a rapidly evolving segment of blockchain technology that enables a transformative approach to financial services through Web3 applications. By leveraging smart contracts, DeFi allows developers to build flexible and innovative financial instruments. Among the most prominent DeFi primitives by liquidity are decentralized exchange~(DEX) swap protocols~(such as Uniswap, Curve, and Balancer) that facilitate fast token-to-token exchanges. However, new exchange mechanisms also introduce new market inefficiencies that can be systematically exploited by arbitrageurs. This paper focuses on swap protocols based on the Automated Market Maker~(AMM), where the product of reserves is preserved as an invariant. We analyze the interaction between arbitrageurs and AMM liquidity pools and develop a mathematical model grounded in empirical pool configurations. Using this model, we derive bounds on the joint revenue of liquidity providers~(LPs) and arbitrageurs, propose a method to estimate the expected number of blocks until the occurrence of Impermanent Loss~(IL), and obtain a lower bound on the pool fee required to achieve a fixed target probability of staying in the Impermanent Gain (IG) zone within a block. The proposed framework extends existing LP risk-assessment methodologies by quantifying symbiotic profitability zones, providing a principled basis for fee selection that aligns LP-arbitrageur incentives and enhances market stability.
A central question of the Ethereum ecosystem is where Maximal Extractable Value (MEV)revenue originates and to what extent it stems from harming unsuspecting users. It is acceptable if MEV arises from arbitrages between centralised and decentralised exchanges (CEX-DEX). Yet theoretical models have significantly underestimated the scale of these arbitrages, while empirical studies have highlighted their importance - though these remain conservative estimates, constrained by numerous debatable heuristic assumptions. Revisiting the theoretical model, we found that CEX-DEX arbitrages require trading volumes on the order of the total activity of major liquidity pools and yield profits comparable to MEV. Most prior AMM models utilised the Black-Scholes (BS) stochastic differential equation (SDE) - i.e., geometric Brownian motion - and assumed continuous price trajectories where asset prices move in small increments only.We argue that BS underestimates arbitrage profits by ignoring price jumps, which are precisely the points at which arbitrage opportunities tend to arise. To address this gap, we present an extended discrete-time AMM model in which the price process is the sum of a diffusive component and stochastic jumps that can have arbitrary noise distributions. Although mathematically more involved this framework allows us to employ a general discrete-time SDE and compute the stationary probability distribution via function iteration with geometric convergence. We further prove that the resulting mispricing process is an ergodic Markov chain. We implement our model in C++, collect spot prices and AMM exchange data from the Ethereum blockchain and fit the model parameters to the observed prices. The estimates derived from our model closely match empirical observations and provide a natural theoretical explanation for several fundamental questions in the blockchain ecosystem.