The financial sustainability of small and medium-sized enterprises (SMEs) has become increasingly important in the context of economic volatility, technological disruption, and growing sustainability demands. However, existing studies remain fragmented and often examine financial, organizational, technological, and environmental factors in isolation. This study systematically reviews 49 articles indexed in the Scopus and Web of Science databases published between 2014 and 2026 to identify the dominant determinants, thematic patterns, and conceptual structure of financial sustainability in SMEs. Using the PRISMA protocol and NVivo-based bibliometric and thematic analyses, this study examines publication trends, geographic distribution, lexical structures, and thematic relationships across the literature. The results show that research is concentrated primarily in Asia and Europe, reflecting increasing scholarly attention to financial literacy, governance quality, resilience, digital transformation, FinTech adoption, ESG practices, and green finance. Thematic synthesis reveals three interconnected pillars—Internal Capability, Adaptive Resilience, and Digital–Green Transformation—which collectively form an architecture of endurance framework that explains how SMEs maintain financial viability under conditions of uncertainty and change. This framework advances prior reviews by integrating organizational capability, resilience-building mechanisms, and sustainability-oriented transformation into a unified model of financial sustainability for SMEs. Practically, the findings highlight the importance of strengthening financial literacy, governance quality, risk management capability, digital adoption, and sustainability-oriented financing, while emphasizing the role of policy support and financial inclusion in fostering SME resilience. Future research should further explore the implications of generative artificial intelligence, blockchain-based finance, and decentralized finance (DeFi) on SME financial sustainability.
This research provides an in-depth evaluation of current academic studies and advancements in the fields of cryptocurrencies, financial technology, blockchain-based decentralized finance (DeFi), stablecoins, state-owned digital currencies, and Central Bank Digital Currencies (CBDCs). The rapidly evolving Fintech environment, as well as the growing significance of DeFi, Bitcoin, and CBDCs, are critical in the current financial landscape. The study delves into several areas of the Fintech development, such as the overall Fintech experience, digital banking tools, payment methods, and Fintech-based lending practices. It also provides insight into the current status of CBDC programs and pilot projects in different countries. Furthermore, the study looks into how the emergence of cryptocurrencies, Fintech, and DeFi on the blockchain has resulted in revolutionary changes inside industrialized nations such as the United States, China, Japan, and several European countries. It also discusses the wide-ranging implications of these changes for financial stability, security, and regulatory measures. This comprehensive analysis provides valuable insights into the current financial landscape and its potential future directions.
The growing popularity of smart contracts on blockchain platforms in recent years has made the development of reliable verification techniques that ensure code is both logically correct and secure an urgent priority. One of the most effective methods adopted by existing tools is formal verification. This thesis addresses the problem of smart contract verification, particularly focusing on those developed for the Ethereum platform. It concentrates on using Constrained Horn Clauses (CHCs) as an intermediate formalism for representing and analysing program properties. Various verification tools were analysed and compared during the course of the work, particularly those based on CHCs, to identify practical limitations, methodological gaps, and opportunities for improvement. Based on this analysis, new tools and optimisations were designed and developed. On the one hand, we implemented CHCViz, a visualisation system that assists auditors and developers in inspecting and understanding CHCs generated by existing tools, such as SolCMC. On the other hand, a verifier for Yul code was built from scratch to extend the applicability of formal verification via CHCs to the recently released intermediate code from the Ethereum foundation.
Anas Azenzoul, Nacer MAHOUAT, Ouissale El Gharbaoui, Jihane Tayazime · 6 authors
Tax systems worldwide face a compliance gap that OECD data places at USD 100–240 billion annually in corporate avoidance alone, before accounting for the shadow economy and crypto-asset transactions. FinTech mandatory e-invoicing, real-time transaction matching, and machine-learning audit selection is narrowing the informational conditions that enable evasion, while simultaneously introducing governance risks: opaque algorithmic audit targeting, contested blockchain forensic evidence, and the surveillance potential of programmable money. This article presents a PRISMA 2020 systematic literature review of 59 peer-reviewed articles (Scopus, Web of Science, and ScienceDirect), complemented by IRAMUTEQ lexicometric analysis and an extension of the Allingham Sandmo compliance model to incorporate algorithmic detection probabilities, bomb-crater belief dynamics, and Zero-Knowledge Proof verification. Four thematic clusters emerge: tax compliance behaviour and FinTech adoption (19.92%), digital transformation and corporate performance (35.34%), bibliometric and emerging-technology research (16.54%), and cryptocurrency markets and regulatory challenges (28.20%). Across them, FinTech reduces evasion where institutional and technical conditions allow but generates distributional, evidentiary, and constitutional risks that existing legal frameworks have yet to resolve. In response, we propose the Techno-Legal Due Process Framework (TLDPF) three pillars (Techno-Proportionality, Cryptographic Burden of Proof, and Algorithmic Constitutionalism) grounded in EU/OECD constitutional doctrine as a normative design proposal awaiting empirical validation.
One of the domains that is seeing a rapid transformation in its dimensions as a result of the proliferation of new technologies across the globe is finance. As a component of the conventional financial system, Islamic finance is required to keep pace with the development of technology to make the most of the opportunities presented by developing technologies in the process of bringing Shariah-compliant products that are suitable for Muslims in particular and for mankind in general. Musharakah, Mudarabah, and Murabahah are the three models that serve as the basis for the essential foundations of Islamic commercial law. Specifically, the Mudarabah, Musharakah, and Murabaha contracts are the ones that are investigated in this chapter as they pertain to the implementation of blockchain technology in Islamic commercial transactions. An introduction to blockchain and its various varieties, characteristics, and functions is presented at the beginning of the chapter. Following this, the chapter sheds light on the primary Islamic commercial contracts (mudarabah, musharakah, and murabahah) and their requirements, as well as their functioning, respectively. The chapter then moves on to its primary thesis, which is a comprehensive discussion of how blockchain technology can be used in the three Islamic commercial contracts that are being examined. The problems that Islamic finance specialists will need to overcome to properly incorporate blockchain technology in Islamic commercial contracts are discussed in the final section of the chapter.
Blockchain consolidated as a disruptive technology across various domains and gained widespread adoption in the last decade. It enforces data integrity and traceability by storing data in an immutable chain of blocks, each linked to the previous one with a cryptographic hash value. Smart contracts enable decentralized applications by enforcing logic directly on the blockchain, eliminating the need for trusted intermediaries or central authorities. Despite their rapid adoption, immutability makes their development and maintenance particularly challenging, and current approaches provide limited support for continuous assurance after deployment. Existing research focused on security vulnerabilities and protocol design, with limited attention to lifecycle management, post-deployment maintenance, and empirical characterization of development practices. These characteristics require novel approaches that enable smart contracts to be observed, tested, and evolved without violating the constraints imposed on the chain. In this context, Digital Twin offers a promising paradigm for mirroring and analyzing smart contract behavior in a controlled, off-chain environment. Engineering the development process for smart contracts will help developers reduce errors and improve the lifecycle in blockchain-based applications. This thesis investigates how to support the continuous monitoring, testing, and controlled evolution of smart contracts throughout their lifecycle. The thesis introduces SmartCoach, a framework inspired by the Digital Twin paradigm that establishes a synchronized virtual counterpart of smart contracts. SmartCoach monitors deployed contracts, mirrors their state and behavior, executes test scenarios in a virtual environment, and supports controlled evolution through proxy- based upgrade mechanisms. By integrating existing tools for static and dynamic analysis, SmartCoach helps developers identify vulnerabilities, validate fixes, and safely evolve contracts. To address the lack of large-scale empirical evidence on how smart contracts are actually designed in practice, the thesis also presents a comprehensive study of micro patterns in Solidity smart contracts, grounded in the observation that recurring coding idioms influence structure, security, and maintainability. Using a custom detection pipeline, more than two million verified contracts across eight different EVM- compatible blockchains were analyzed. The study identifies the prevalence, co-occurrence, and evolution of micro patterns, providing a vocabulary for understanding structural properties of decentralized codebases. Together, the proposed framework and empirical findings bridge the gap between software engineering and blockchain research. They demonstrate how lifecycle-aware engineering approaches and data-driven insights can improve the reliability and maintainability of smart contracts. The thesis also discusses limitations and open challenges, including the development of fully autonomous contract evolution and the validation of detection precision, outlining directions toward more robust, maintainable, and future-proof smart contract ecosystems.
Terrorist financing is a major fuel for political violence and extremist operations in the world. The increasing advancement of digital technologies, cryptocurrencies, crowdfunding platforms, and social media has significantly transformed how extremist groups raise, transfer, and conceal funds, yet little has been done to examine the broader digital transformation of terrorist financing and its implications for the United States. This scoping review examined evolving trends, financing strategies, and operational challenges associated with terrorist financing networks and assessed their implications for the United States counterterrorism agenda. Following the Arksey and O’Malley guidelines for scoping reviews, relevant studies were identified through systematic database searches and screened using predefined inclusion and exclusion criteria. Ten studies were selected and analyzed thematically. The findings underscored four major themes: the digitalization of terrorist financing, the fusion of lawful and unlawful funding mediums, administrative and institutional weaknesses, and the growing need for collaborative and intelligence-driven disruption strategies. The review found that extremist financing increasingly operates within ordinary digital and financial ecosystems, making detection more difficult for regulators, financial institutions, and law enforcement agencies. The study concludes that terrorist financing has become more decentralized, adaptive, and technologically sophisticated than many existing counterterrorism frameworks are prepared to address. Hence, strengthening United States national security will require a more proactive digital financial monitoring, sophisticated regulatory systems, and stronger inter-sectoral collaborations to disrupt evolving extremist financing networks before they escalate into acts of violence.
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Terrorism, Counterterrorism, and Political Violence
Background: Indonesia’s simultaneous regional elections (Pilkada serentak) constitute a key component of post-Reformasi decentralization. While designed to strengthen democratic local governance, recent fiscal rationalization policies have increased central control over election financing, raising concerns about their impact on substantive democratic representation. Objectives: This study examines whether fiscal rationalization in Pilkada implementation supports or undermines constitutional principles of democratic, participatory, and accountable local government. It analyzes the constitutional framework of Pilkada, identifies key fiscal rationalization mechanisms, and evaluates their effects on local political representation. Methods: A qualitative normative empirical approach was employed. Normative analysis examined the 1945 Constitution, electoral and regional governance laws, fiscal decentralization regulations, and Constitutional Court decisions. Empirical analysis was conducted through comparative case studies of regional election budget management. Results: Four major mechanisms were identified: NPHD budget revisions, APBD burden-shifting, compressed electoral timelines, and intensified central fiscal steering under Law No. 1 of 2022. These mechanisms reduced electoral capacity, limited voter-candidate engagement, and disproportionately affected less-resourced regions. Although elections formally complied with constitutional requirements, substantive representation was weakened, creating a persistent gap between procedural legality and democratic quality. Conclusion: Fiscal rationalization has strengthened formal compliance but constrained substantive democratic representation. Greater fiscal stability and regional autonomy are needed to ensure competitive, equitable, and accountable local elections. Keywords: fiscal rationalization; Pilkada serentak; constitutional compliance; democratic representation; decentralization.
Smart contracts deployed on blockchain platforms are immutable once deployed, making correctness and security critical concerns that have led to substantial financial losses due to vulnerabilities. A significant proportion of these vulnerabilities stem from human-written code rather than blockchain infrastructure or cryptographic primitives. This observation motivates a paradigm shift from manual code development to model-driven approaches that generate semantically correct smart contracts from formal specifications. This thesis presents EDAM (Enhanced Data-Aware Machines), a behavioural model for specifying smart contracts that balances expressiveness with tractability. The framework extends traditional data-aware finite state machines [3] with essential features for a wide range of smart contract applications: dynamic role-based access control enabling runtime role assignment and revocation, participant management supporting unbounded and varying participants, and explicit modelling of inter-contract interactions through call tries with success and failure handling. The formal semantics of EDAM are grounded in established techniques from behavioural type theory, process calculi, and finite state machine theory, enabling rigorous reasoning about contract behaviour. The thesis contributes a comprehensive toolchain that integrates modelling, code genera- tion, test generation, and validation in a unified methodology. We develop a code generation engine that automatically produces Solidity smart contracts from EDAM specifications. The generated code faithfully implements the formal model, ensuring that the behaviour established at the model level is preserved in the executable code. The code generation process uses an intermediate JavaScript Object Notation (JSON) representation, which enables platform-agnostic code generation with ongoing extensions to support additional blockchain platforms such as Aptos. We present an automated test generation methodology that produces executable test suites from EDAM specifications. The approach combines symbolic trace generation using the formal semantics implemented in OCaml with randomized exploration of the Finite State Machine (FSM) network, enabling concrete trace derivation through random value assignment and Satisfiability Modulo Theories (SMT) constraint solving. This methodology systematically explores the state space to generate traces that exercise transitions, guards, and role constraints, producing executable test suites for standard testing frameworks such as Hardhat. The process is fully automated and can be integrated into the development workflow. Our evaluation demonstrates the expressiveness and practicality of the approach through a diverse benchmark of smart contracts, including contracts from the Azure repository [148], standard token contracts (Ethereum Request for Comments 20 (Token Standard) (ERC20)), Decentralized Finance (DeFi) protocols (Automated Market Makers (AMMs)), and multi- coordinator systems. The evaluation demonstrates expressiveness through the modelling of essential features, showing that the approach is able to model a wide range of smart contract features. The validation methodology employs a multi-faceted approach that combines code coverage analysis, mutation testing to validate the correctness of the generated code and the effectiveness of the test suites, and cross-validation by applying the generated tests to other established implementations. This cross-validation approach shows that our generated test suites are applicable to validate existing smart contract implementations, providing evidence of the quality and correctness of both the generated code and the testing methodology. The results empirically indicate that our model-driven approach produces contracts and test suites that preserve the structure and semantics of the formal model and can be applied to validate existing smart contract implementations. Unlike existing approaches that address isolated phases of the development lifecycle, EDAM provides an integrated toolchain that ensures consistency between specifications, vii generated code, and test suites. The framework shows that behavioural types provide a solid foundation for smart contract modelling and verification, enabling the development of unified frameworks that integrate modelling, code generation, test generation, and val- idation. Although our implementation targets blockchain platforms, the methodology is platform-agnostic and may generalise to other service-oriented and distributed architectures. The results show that model-driven approaches can produce high-quality smart contracts and comprehensive test suites, contributing to the advancement of secure smart contract development practices.
This short position paper suggests there may be greater deception and influence of an attacker’s perceptions of a fictional ‘Agentic AI Army’ swarm of LLM sock puppet network defenders than deploying real LLM agent swarms. We model a counterintuitive industry approach integrating Whaley’s lesser-known Theory of Outs and “turnabout” deception techniques to encourage a human or LLM attacker’s discovery of deception on an industry network. While we recognize that the knowledge of real or imagined deception can deter an attacker, we also recognize that attackers may demonstrate greater confidence on a network after discovering what appears to be deception artifacts. We visualize how ‘noisy’ LLM sock puppets inside of a network that prompt optimized query returns on their content and placement on the network could draw attackers to later stage deception functions and effects and enhanced defender alerting and analysis on human or LLM attacker interaction with those deception functions. We find in anecdotal operational research that highlighting ‘noisy’ sock puppet content enhances high-fidelity detection. We frame these findings using this integrated industry model in the context of LLM swarm narratives for deception. There has been an increasing concentration on swarming as a military technique and military strategy, as modern military conflicts continue to adapt to irregular warfare environments. The renewed concentration on developing and integrating swarm intelligence with LLM agents continues to face limitations, in terms of simulating natural swarm behaviors and operating autonomously as part of a decentralized model. This short position paper proposes a more immediate deception and influence effect, namely projecting fictional LLM swarm narratives suggesting there is an ‘Agentic AI Army’ assisting human defenders. We use organizational perception management as a design framework to visualize a deception and influence narrative communicating this fictional narrative using ‘noisy’ LLM sock puppets and our integrated model of Whaley’s Theory of Outs and “turnabout” deception techniques.
This paper investigates Ethereum-based smart contracts as a decentralized cybersecurity governance layer for Electronic Medical Records (EMRs). It addresses challenge of fragmented healthcare data silos and strict compliance requirements for electronic protected health information (ePHI), such as HIPAA and GDPR by analyzing how blockchain technology enables explicit, patient-centric access control. Current legacy systems often centralize authorization, creating vulnerablilities. Through topic analysis and a Solidity-based Proof of Concept (PoC), the study demonstrates a hybrid architecture that uses on-chain execution for permission management while storing sensitive clinical data off-chain. The PoC shows how immutable ledger entries enforce least-privilege principles, block unauthorized queries, and provide tamper-evident auditability. The architecture’s trade-offs between enhanced accountability, patient sovereignty, and practical limitations in scalability, governance, and costs are assessed. It concludes that while blockchain offers a robust trust layer, integration with off-chain interoperability standards remains essential for clinical adoption.
This paper underscores the vital role of blockchain technology in Industry 4.0, aiming to inspire researchers and industry professionals to recognize its transformative potential in creating decentralized, automated, and data-driven industrial settings. It explains core concepts, components, and varieties of blockchain systems, and assesses their uses across various sectors. The research delves into security and privacy issues, particularly relating to Ethereum platforms and smart contracts. It meticulously details common vulnerabilities of smart contracts and their implications for industrial systems. A critical comparison of existing vulnerability-detection techniques reveals current limitations. The paper also investigates the potential of artificial intelligence to enhance security analysis in blockchain contexts, systematically reviewing machine learning and deep learning strategies for identifying smart contract issues. A novel detection framework is introduced and tested against real-world datasets, showing improved accuracy and robustness compared to traditional methods. Ultimately, the paper aims to foster the development of secure and trustworthy blockchain infrastructure for applications in Industry 4.0.
Blockchains are distributed ledgers that let mutually distrustful parties agree on an append-only transaction history without relying on a central authority. By combining cryptographic hashing, digital signatures, and consensus mechanisms, blockchains provide tamper evidence, auditability, and agreement among nodes. Modern blockchain systems significantly vary in consensus design (e.g., Proof of Work, Proof of Stake, Proof of Author- ity, and Byzantine Fault Tolerance mechanisms), access model (open vs. permissioned), and execution layers (from simple asset transfers to expressive smart-contract virtual machines). The related architectural choices shape decentralization, fault tolerance, and the attainable latency-throughput envelope. As blockchain deployments expand to payments, tokenization, decentralized finance, supply chain traceability, and digital identities, comparing these systems has become an urgent necessity. Unfortunately, rigorous blockchain evaluation remains difficult. On the one hand, measurements are confounded by fluctuating network conditions, heterogeneous infrastructures, and rapidly evolving software. On the other hand, results are too often collapsed to a single number (such as transactions per second) without dispersion or methodological details; economic assessments of crypto-assets lack a unified and interpretable index that captures the balance of core economic parameters and their trade-offs (usage, liquidity, stability, and security) rather than market price sentiment; and experimental studies rarely address the dimensions of experimental repeatability (same setup, same results) and performance predictability (stable expectation). The consequence is an evidence gap: how to assess and compare the efficiency of blockchains – spanning performance, energy, economics, and result stability – in different scenarios? This dissertation aims at reducing this gap with a coherent yet modular approach that combines topology-controlled benchmarking with an orthogonal, entropy-based economic analysis, delivering four contributions. First, it introduces Lilith, a system-agnostic benchmarking framework that couples workload generation with network emulation to run controlled, repeatable experiments under explicit overlay topologies (i.e., the logical peer- to-peer connectivity graphs) and link properties such as latency, bandwidth, and packet loss. Lilith orchestrates deterministic deployments (pinned artifacts, controlled boot order, and CPU core pinning and memory binding), integrates power probes, and provides a uniform client interface; this underpins a comparison based on typical performance metrics. Second, Lilith is employed to quantify blockchain energy consumption under realistic conditions. Third, Lilith is adopted for a network-controlled, multi-run measurement campaign to produce a public dataset. By combining dispersion metrics (e.g., worst-case deviation) with analysis of variance and intraclass correlation, we quantify run-to-run variability and performance predictability across blockchains, topologies, workloads, and node-set sizes. Fourth, in addition to Lilith, the dissertation introduces the Entropy Balance index (EB-index), which aggregates heterogeneous on-chain indicators into a single, interpretable score of economic efficiency. ii As for the first three contributions, we set up the experimental baseline by considering five network topologies (fat-tree, full mesh, hypercube, scale-free, torus) and five industry- grade blockchains (Algorand, Diem, Ethereum Clique, Quorum IBFT, Solana), exercised with transfer transactions and smart-contract workloads (DDoS, FIFA, GAFAM, gaming, PayPal, VISA) across two node-set sizes (10 and 40). In the performance study, the network topology emerges as the primary factor de- termining throughput and latency. Full mesh, hypercube, and torus deliver higher performance under heavy load. The performance of Algorand and Diem is stable with respect to topology changes, while Ethereum is less sensitive but remains slower. In the energy study, fat-tree and full mesh turn out to be the most energy-efficient topologies, especially at high load. Algorand and Diem exhibit the lowest energy per transaction, Ethereum Clique the highest across topologies; Quorum IBFT and Solana become costlier as workload intensity and network size increase. The experimental repeatability and performance predictability study shows low per- formance variance (transactions per second, block latency, energy consumption) for Algorand and Diem and pronounced sensitivity for Solana and Quorum IBFT, especially as workloads, node-set size, and geo-latency conditions vary. The released dataset and the accompanying analysis templates, which are based on clusters instead of public-cloud testing, enable thorough checks that go beyond point estimates by quantifying dispersion and confidence in comparative results. Finally, in the economic study, the EB-index aggregates heterogeneous on-chain indicators – such as user activity (transactions, active addresses), token distribution (balance concentration), and supply turnover/velocity – by using the normalized Shannon entropy and its weighted Beliş-Guiaşu variant. When applied to the capitalization-based leading crypto-assets Bitcoin, Ethereum, Ripple, USD Coin, Dogecoin, and Cardano, the EB-index separates volume-driven bursts from structurally balanced ecosystems and reveals differences that price, total value locked, or raw activity may blur. Overall, this dissertation delivers a topology-aware blockchain benchmarking frame- work, empirical evidence that network structure materially affects performance and energy, a public multi-run dataset together with analysis templates that promote experimental repeatability and performance predictability, and an entropy-based index for assessing economic efficiency.
Gefei Tan, Adria Gascon, Sarah Meiklejohn, Mariana Raykova
In machine learning, model certification has been identified as an important method for gaining assurance about a model's trustworthiness and quality. A model's quality is largely determined by its ability to generalize, i.e., to perform well on data beyond what it was trained on. It is not possible to certify generalization directly, however, as it depends on unknown data and is not directly measurable. Proxies such as test accuracy can be misleading when the training process is perturbed (intentionally or accidentally), and metrics such as sharpness -- which has an empirically supported link to generalization -- are computationally expensive and can also serve as unreliable signals when training deviates from a prescribed procedure. In this work, we propose directional sharpness, a metric designed to efficiently and reliably indicate generalization despite potential training deviations. We provide empirical and analytical evidence that directional sharpness (1) correlates more strongly with generalization than existing metrics and (2) identifies models with poor generalization more reliably than existing metrics. Furthermore, directional sharpness is efficiently computable in model auditing settings, where the verifier has access to training data, and via zero-knowledge proofs that certify quality without revealing training data.
The increasing adoption of decentralised technologies, such as blockchain, is reshaping the way distributed systems are used and, in particular, how digital and physical resources are represented and managed. While tokenisation techniques have enabled the representation of unique and verifiable artefacts on the blockchain, Non-Fungible Tokens (NFTs), the most popular standards used to encode them still provide limited support for those resources that need to change over time. Updates to their content are handled through poorly structured, weakly regulated, and often opaque mechanisms, making it difficult to model assets whose lifecycle requires controlled modifications, and verifiable state transitions. This thesis addresses these limitations and introduces a conceptual and operational framework for the structured, controlled, and traceable man- agement of asset mutability within blockchain-based ecosystems running on Ethereum-compatible platforms. The proposed approach formalises the mu- tability of asset attributes, defines an explicit model for updates, and inte- grates on-chain authorisation mechanisms to ensure that every modification, every transfer and every minting operation is performed in accordance with predefined policies and in a permanently verifiable manner. The thesis defines update-control rules, more fine-grained metadata rep- resentations, and coordination schemes that enable creators, owners, and authorised actors to collaborate safely on the modification of a resource. The validity of the framework is assessed through the application of real use cases and simulation tools that analyse performance, costs, and behavioural properties, as well as the long-term sustainability in the blockchain across different scenarios. The results show that a more precise and structured treatment of muta- bility significantly enhances the expressiveness, reliability, applicability, and, iii most importantly, the intrinsic value of blockchain-based asset representa- tions. This provides a more realistic and flexible management of the lifecycle of digital resources, while opening new directions towards future develop- ments in areas such as decentralised identity, cross-chain interoperability, and distributed collaborative systems.
Mariachiara Restuccia, Achilleas Boukis, Charles Hofacker, Fulya Açikgöz
Non-Fungible Tokens (NFTs) have become part of the product portfolios of many brands, ranging from individual creators to established firms. Yet, we currently have a limited understanding of how NFTs should be designed, launched, and managed effectively over their lifecycle journey. To fill this gap, we explore the distinctive lifecycle of this novel digital product category. Rather than focusing on the macro-view of the product lifecycle at the aggregate product category level (e.g., introduction, growth, maturity, and decline), our work offers a micro-view of the lifecycle at the individual NFT level, focusing on the relevant decisions to be made and activities to be performed by a creator or a firm. Drawing on the product lifecycle management literature and field exemplars, our proposed NFT lifecycle consists of three main stages: 1. Inception (featuring content creation, minting, and dropping), 2. Circulation (involving experience, trade, and commercial exploitation), and 3. Termination (including timed expiration, regeneration, and retirement decisions). Our conceptual work contributes to the emerging literature on blockchain assets by developing an original and integrative lifecycle framework. It also offers marketers actionable insights into how to manage each of the different lifecycle stages of a decentralized digital offering like NFTs, broadening the focus from short-term activities (e.g., Inception and Circulation) to the long-term ones (e.g., Termination).
Fariq Wastu Nuzlul Qurani, R. Eriska Ginalita Dwi Putri
Perkembangan teknologi Blockchain telah menghasilkan inovasi baru berupa Non-Fungible Token (NFT), yang memungkinkan karya digital diperdagangkan sebagai aset digital yang unik dalam ekosistem berbasis Blockchain. Kehadiran NFT membuka peluang ekonomi baru bagi para kreator digital untuk memonetisasi karya mereka secara lebih luas. Akan tetapi, praktik minting dan perdagangan NFT juga memunculkan masalah hukum, terutama terkait pelanggaran hak cipta pada karya digital yang dimanfaatkan tanpa persetujuan dari penciptanya. Studi ini bertujuan untuk mengkaji jenis perlindungan hukum yang bersifat represif bagi para pencipta digital dari duplikasi karya dalam ekosistem NFT serta pertanggungjawaban hukum bagi pelanggaran hak cipta. Metode yuridis normatif digunakan dengan pendekatan perundang-undangan, konseptual dan kasus. Penelitian ini menunjukkan, bahwa pelanggaran hak cipta dalam ekosistem NFT biasanya terjadi melalui penggunaan dan pengubahan karya digital menjadi NFT tanpa persetujuan dari pencipta aslinya. Perlindungan hukum represif terhadap pelanggaran ini dapat diambil melalui jalur perdata yaitu tuntutan ganti rugi dan penghapusan NFT yang melanggar hak cipta, serta melalui jalur pidana berdasarkan UUHC Nomor 28 Tahun 2014. Dengan demikian, penegakan hukum masih menghadapi tantangan karena sifat desentralisasi teknologi Blockchain dan kurangnya regulasi khusus terkait NFT di Indonesia.
This PhD thesis examines risks, opportunities and socio-technical innovation in blockchain-based financial systems, combining network analysis, empirical market data, and institutional analysis. As the crypto ecosystem and decentralized financial infrastructures continue to expand and interact with traditional monetary systems, understanding how risk propagates across assets, platforms, and institutional designs has become increasingly important for market participants and policymakers. The first two chapters focus on systemic risk in crypto assets (cryptocurrencies and stablecoins) using a network-based approach. The first paper analyzes major crypto assets and constructs dynamic networks based on return co-movements to study the evolution of interconnectedness and contagion risk over time. Network centrality measures (degree, closeness, betweenness, and eigenvector) are used to identify systemically important nodes (cryptocurrencies and stablecoins) and to assess how these measures affect their systemic risk contributions, particularly during market stress episodes. Results showed that the systemic risk contribution of crypto assets decreases over time as their connectedness in the system increases. This impact is more pronounced for cryptocurrencies than for centrally issued, managed, and governed stablecoins. Our findings suggest that pure network interconnectedness plays a diminished role in tail risk propagation in the crypto market. The second paper extends this framework to token pairs traded on centralized and decentralized exchanges (CEXs and DEXs), allowing for a comparison of market structure and risk transmission across trading platforms. By incorporating data from CEXs and DEXs, this chapter highlights differences in network topology and the role of liquidity concentration in shaping systemic risk. Results showed that centrality values significantly impact systemic risk contribution of token pairs listed on centralized exchanges. Conversely, insignificant results were found for all token pairs traded on decentralized exchanges. The token pairs on centralized exchanges exhibited a negative association with centrality values, consistent with the findings reported in the first paper. These findings imply that systemic risk in cryptocurrency markets is not solely driven by interconnectedness, but by how that interconnectedness is structured. In particular, the negative relationship between centrality and systemic risk suggests that higher network integration, supported by transparency and decentralized architectures, may enhance risk sharing and reduce systemic vulnerability. These results highlight the potential of blockchain based financial systems to contribute to more resilient, efficient, and inclusive financial ecosystems, while also offering new insights for the design of risk management and regulatory frameworks. The third paper shifts the focus from market level risk to protocol level risk management in leading Decentralized Finance (DeFi) lending platforms. It examines the determinants of liquidation events and evaluates the effectiveness of protocol design features as risk management tools. Exploiting the transition from earlier to newer protocol versions across different blockchain layers, the empirical analysis employs panel fixed effect regression models to assess how changes in risk control measures 3 affect liquidation dynamics and protocol’s performance. The findings emphasize that protocol level design choices play a critical role in mitigating risk beyond asset price volatility alone. The architectural evolution from v2 to v3, characterized by granular risk parameters, isolation modes, and enhanced risk management mechanisms has systematically improved protocol resilience, with liquidations in v3 serving as positive signals of stability rather than distress. The fourth paper broadens the scope of the thesis by examining blockchain based complementary currencies in comparison with traditional complementary currency systems, with a particular focus on their potential role in universal basic income schemes. It investigates the socio-technical evolution of Complementary Currencies for Basic Income using a data-driven approach to different case studies (Fiat and Blockchain based models). It highlights how technological choices influence scalability, transparency, and risk exposure in social and monetary innovations by employing mix method approach. Finally, based on the trade-offs of each system, a hybrid model for UBI is proposed for financial inclusion and poverty elimination. Taken together, the four papers provide an integrated perspective on risks and opportunities in emerging financial ecosystems, spanning asset markets, trading infrastructure, decentralized protocols, and alternative monetary arrangements. Overall, the results suggest that the core features of blockchain based markets, e.g., decentralization, transparency, accessibility, low transaction costs and automated risk management, are not merely technological innovations but may serve as mechanisms for improving system resilience and inclusive financial architectures. This thesis also contributes to the literature by demonstrating how network structures and institutional design jointly shape systemic risk and resilience in DeFi, offering insights relevant for researchers, protocol designers, and policymakers navigating the evolving digital financial landscape.
Web3 promises to rebuild the Internet on decentralised foundations, yet it inherits its predecessors’ familiar tensions between autonomy, coordination, and institutional legitimacy. This chapter analyses how decentralisation redistributes power while creating new risks of harm and recentralisation. It then considers what it would mean to govern these infrastructures with an ethic of compassion attuned to human vulnerability and structural power.
We introduce \textit{OptChain}, a permissionless blockchain state machine replication (SMR) protocol that achieves optimal throughput. We first establish a theoretical upper bound on the throughput of any SMR protocol under a fixed error probability, and OptChain is the first protocol to approach this limit. Conceptually, OptChain is a sharding protocol that optimizes both vertical and horizontal scalability. Vertically, we introduce \textit{Shardis}, a novel permissionless verifiable information dispersal mechanism that maximizes intra-shard throughput to its physical limit, determined by the fastest node's bandwidth within each shard. Horizontally, we propose \textit{diffusion mining}, which ensures security as long as each shard includes at least one honest node, thereby allowing for the maximum number of shards. We provide a formal security and efficiency analysis, demonstrating that OptChain approaches the established upper bound while maintaining robust security. Finally, we implement a full prototype of OptChain and deploy it on AWS EC2 nodes across various regions. Experimental results indicate that OptChain outperforms state-of-the-art permissionless protocols and closely approaches the theoretical optimal throughput.
Mohammed Benseddik, Benjamin Kraner, Claudio J. Tessone
Ethereum's beacon chain hosts over 920,000 active validators, a number inflated by the legacy 32 ETH stake cap. The Pectra upgrade (May 2025) addresses this by introducing 0x02 compounding validators, raising the maximum stake per validator from 32 to 2,048 ETH and enabling automatic reward reinvestment. This paper examines how compounding affects consensus-layer rewards, whether higher balances provide execution-layer advantages, and whether the APR uplift justifies migration for different staker types. We analyse adoption patterns across solo stakers and staking providers, investigate the role of consolidation (merging multiple 32 ETH validators into one) in early migration, and identify barriers slowing the transition. Through simulation, we find that compounding provides roughly +5% relative consensus-layer APR uplift for small balances, diminishing to under 1% for large staking providers. Empirical analysis of all active beacon chain validators shows 0x02 validators achieving modestly higher median CL APR. Solo stakers show higher relative adoption but face operational barriers, whilst providers cite infrastructure costs and protocol constraints. The results suggest that without improved reward accessibility and stronger economic incentives, 0x02 migration will remain gradual despite its network efficiency benefits.