This study examines the impact of the coronavirus disease 2019 (COVID-19) pandemic on market efficiency by analyzing three time series -- price returns, absolute returns, and volatility increments -- in stock (Deutscher Aktienindex, Nikkei 225, Shanghai Stock Exchange (SSE), and Volatility Index) and cryptocurrency (Bitcoin and Ethereum) markets. The effect is found to vary by asset class and market. In the stock market, while the pandemic did not influence the Hurst exponent of volatility increments, it affected that of returns and absolute returns (except in the SSE, where returns remained unaffected). In the cryptocurrency market, the pandemic did not alter the Hurst exponent for any time series but influenced the strength of multifractality in returns and absolute returns. Some Hurst exponent time series exhibited a gradual decline over time, complicating the assessment of pandemic-related effects. Consequently, segmented analyses by pandemic periods may erroneously suggest an impact, warranting caution in period-based studies.
Mansur Masama Aliyu, Niclas Kannengießer, Ali Sunyaev
The blockchain trilemma highlights the difficulty of simultaneously achieving a high degree of decentralization (DoD), scalability, and security in blockchain systems. While numerous constructs and metrics have been proposed to analyze these subconcepts, existing guidance is fragmented and inconsistent, limiting comparability across studies. This lack of clarity hinders practitioners in identifying Pareto-optimal blockchain system designs that meet common non-functional requirements. We systematically reviewed literature on the blockchain trilemma and blockchain benchmarks to synthesize constructs and their operationalizations through metrics to analyze the trilemma's subconcepts. We identified 12 constructs, operationalized through 15 metrics, that capture DoD, scalability, and security. We explain how these constructs apply across different blockchain systems and provide a structured overview that supports benchmarking and blockchain system design. Beyond blockchain, the findings offer insights for distributed database systems that rely on consensus and state machine replication. This work contributes a harmonized foundation for quantitative analyses of the blockchain trilemma, guiding both researchers in developing analysis approaches and practitioners in evaluating real-world systems.
ABSTRACT The introduction of digital money such as Bitcoin, and the underlying blockchain and distributed ledger technology, created huge interest. The developments have posed the possibility of major implications for the financial system and potentially the whole economy. This article tackles the topic of a central bank ought to issue digital money for widespread use. Defines a benchmark central bank digital currency with characteristics like cash.The implications of such a digital currency are analyzed, with particular attention to central bank title, monetary policy, the banking system, financial stability, and payment. This Study delivers a CBDC that is considerably different from the accepted digital currency is assessed. However, their successful incorporation requires careful consideration of a multitude of issues, not to mention rewarding and balancing risks, to establish firm foundations that minimize these risks and take advantage of CBDCs’ potential to drive a more equal and efficient financial system.
ABSTRACT This article explores the critical importance of traceability and accountability within modern supply chains, and how blockchain technology provides innovative solutions to enhance transparency and trust. Drawing upon literature, case studies, and emerging practices, the study identifies the transformative potential of distributed ledger technology (DLT) in tackling issues such as product authenticity, fraud, and ethical sourcing. As supply chains become increasingly complex, blockchain emerges as a decentralized mechanism to record, verify, and share immutable transaction data across all stakeholders, ensuring end-to-end visibility.
Decentralized Finance (DeFi) remains a complex domain, difficult for newcomers to grasp due to abstract mechanisms like liquidity pools, decentralized exchanges (DEXs), and asset swapping. This paper proposes Black Doge — a multichain digital asset — as a form of "digital stationery" for students to practically learn DeFi concepts. Black Doge, existing across multiple blockchain networks, can simulate real-world DeFi activities in a controlled educational environment. We explore the significance of this approach, its impact on student learning, future blockchain adoption, DEX usability, and broader blockchain ecosystem development.
The quest for wealth has been a constant in human civilization. Ancient Indian mythology, through symbols such as Kamadhenu — the wish-fulfilling divine cow — and philosophical ideas like Soul Contracts, explored the dynamics of material abundance and spiritual growth. In modern times, the emergence of decentralized finance (DeFi) and centralized finance (CeFi) systems mirrors these ancient philosophies in unexpected ways. This paper explores the intersections between ancient and modern ideas about wealth, drawing connections between Kamadhenu and DeFi (as models of self-generating, permissionless abundance), and between Soul Contracts and CeFi (as models involving agreements, authority, and structured dependence). Through detailed narrative analysis, philosophical interpretation, and case studies in finance, the paper argues that understanding ancient wisdom can provide meaningful insights for navigating the complex economic realities of the 21st century.
The integration of machine learning (ML) in healthcare has unlocked transformative potential in disease prediction, personalized treatment, medical imaging, remote patient monitoring, and genomic data analysis. However, the sensitive nature of medical data introduces critical concerns regarding patient privacy, data security, and regulatory compliance. This chapter presents a comprehensive overview of privacy-preserving machine learning approaches tailored for healthcare applications, with a focus on technical frameworks, real-time implementations, and regulatory alignment. It explores the use of advanced techniques such as federated learning, differential privacy, homomorphic encryption, and zero-knowledge proofs to safeguard patient information while maintaining model utility. The chapter also addresses domain-specific challenges in processing real-time health data streams and implementing privacy-aware algorithms in resource-constrained environments. By bridging the gap between technical innovation and clinical applicability, this work emphasizes the importance of secure, scalable, and ethically aligned ML solutions in modern healthcare ecosystems. The discussion was contextualized within current legal frameworks and highlights future directions for research and implementation to ensure trust, transparency, and resilience in data-driven medical systems.
In recent years, cryptocurrencies have attracted growing attention from both private investors and institutions. Among them, Bitcoin stands out for its impressive volatility and widespread influence. This paper explores the predictability of Bitcoin's price movements, drawing a parallel with traditional financial markets. We examine whether the cryptocurrency market operates under the efficient market hypothesis (EMH) or if inefficiencies still allow opportunities for arbitrage. Our methodology combines theoretical reviews, empirical analyses, machine learning approaches, and time series modeling to assess the extent to which Bitcoin's price can be predicted. We find that while, in general, the Bitcoin market tends toward efficiency, specific conditions, including information asymmetries and behavioral anomalies, occasionally create exploitable inefficiencies. However, these opportunities remain difficult to systematically identify and leverage. Our findings have implications for both investors and policymakers, particularly regarding the regulation of cryptocurrency brokers and derivatives markets.
Chiara Oldani, Giovanni S. F. Bruno, Marcello Signorelli
This paper investigates the existence of bubbles in the daily prices of the most popular cryptocurrencies, Bitcoin (BTC), Ether (ETH), and Ripple (XRP), employing the recursive methods of Phillips et al. (2015) and Phillips et al. (2011) for testing and date-stamping episodes of exuberant behaviour over a period spanning seven years (2018–2024), including the COVID-19 pandemic crisis (2020–2021). The critical values of the tests are computed through the composite wild bootstrap technique by Phillips and Shi (2020) to make them robust to time-varying unconditional heteroscedasticity and the multiplicity issue in recursive tests. Results indicate that the prices of the most popular cryptocurrencies traded on decentralized ledgers, BTC and ETH, exhibited multiple episodes of exuberant behaviour, unambiguously for BTC and depending on the tests for ETH. Bubbles detected in the prices of BTC were due to the halving of the crypto, to market exuberance and to the pandemic crisis; bubbles detected on ETH prices were due to the launch of NFTs on the Ethereum blockchain, and to the change in investors’ expectations (from exuberant to pessimistic); the change in the stance of monetary policy burst the bubbles of BTC and ETH prices in 2024. No test supports the exuberance of XRP that is traded on a centralized ledger; weekly data confirm the absence of multiple bubbles. By looking at the presence of bubbles in these different digital ecosystems, we also consider how the technological differences can impact, possibly asymmetrically, bubbles' formation.
This study introduces a novel hybrid stochastic modeling framework for simulating Ethereum price dynamics by integrating Poisson and Gaussian processes. The model captures both abrupt price jumps, modeled using a Poisson process, and continuous price variations, represented by a Gaussian process. Our analysis reveals that significant price fluctuations occur approximately every 4.33 days, with an average daily return of 0.0041 and an annualized volatility of 0.8631, underscoring the extreme volatility inherent in Ethereum’s market behavior. By combining these processes, the model effectively encapsulates the intrinsic price patterns of Ethereum, including persistent oscillations and sudden surges. Simulations of future price trajectories demonstrate the model’s efficacy in replicating real world Ethereum price dynamics, offering valuable insights for traders and analysts in devising risk management strategies and making informed decisions in highly volatile cryptocurrency markets. The findings highlight the importance of hybrid models in addressing the unique challenges of modeling Ethereum’s price behavior.
Blockchains rely on economic incentives to ensure secure and decentralised operation, making incentive compatibility a core design concern. However, protocols are rarely deployed in isolation. Applications interact with the underlying consensus and network layers, and multiple protocols may run concurrently on the same chain. These interactions give rise to complex incentive dynamics that traditional, isolated analyses often fail to capture. We propose the first compositional game-theoretic framework for blockchain protocols. Our model represents blockchain protocols as interacting games across the application, network, and consensus layers. It enables formal reasoning about incentive compatibility under composition by introducing two key abstractions: the cross-layer game, which models how strategies in one layer influence others, and cross-application composition, which captures how application protocols interact concurrently through shared infrastructure. We illustrate our framework through case studies on Hashed Timelock Contracts (HTLCs), Layer-2 protocols, and Maximal Extractable Value (MEV) showing how compositional analysis reveals new subtle incentive vulnerabilities and supports modular security proofs. Also, by introduction of a novel rational miner model, we derive new conditions for the robustness of timelocks to bribing attacks.
Solana is an emerging blockchain platform, recognized for its high throughput and low transaction costs, positioning it as a preferred infrastructure for Decentralized Finance (DeFi), Non-Fungible Tokens (NFTs), and other Web 3.0 applications. In the Solana ecosystem, transaction initiators submit various instructions to interact with a diverse range of Solana smart contracts, among which are decentralized exchanges (DEXs) that utilize automated market makers (AMMs), allowing users to trade cryptocurrencies directly on the blockchain without the need for intermediaries. Despite the high throughput and low transaction costs of Solana, the advantages have exposed Solana to bot spamming for financial exploitation, resulting in the prevalence of failed transactions and network congestion. Prior work on Solana has mainly focused on the evaluation of the performance of the Solana blockchain, particularly scalability and transaction throughput, as well as on the improvement of smart contract security, leaving a gap in understanding the characteristics and implications of failed transactions on Solana. To address this gap, we conducted a large-scale empirical study of failed transactions on Solana, using a curated dataset of over 1.5 billion failed transactions across more than 72 million blocks. Specifically, we first characterized the failed transactions in terms of their initiators, failure-triggering programs, and temporal patterns, and compared their block positions and transaction costs with those of successful transactions. We then categorized the failed transactions by the error messages in their error logs, and investigated how specific programs and transaction initiators are associated with these errors. We find that transaction failure rates on Solana exhibit recurring daily patterns, and demonstrate a strong positive correlation with the volume of failed transactions, with bots on Solana experiencing a high transaction failure rate of 58.43%. We identify ten distinct error types in the error logs of failed transactions, with price or profit not met and invalid status errors accounting for 67.18% of all failed transactions. AMMs primarily experience invalid status errors among failed transactions, while DEX aggregators are more commonly affected by price or profit not met errors. Among transaction initiators, bots encounter a broader range of errors due to their high-frequency trading and complex interactions with smart contracts. In contrast, human users experience a more limited range of errors. Based on our findings, we provide recommendations to mitigate transaction failures on Solana and outline future research directions.
• Blockchain enhances security, efficiency, transparency and trust in maritime sector. • Five research clusters identified including secure data sharing and IoT integration. • Key adoption barriers: scalability, interoperability, standards and legal frameworks. • Publication trend shows growing interest in maritime blockchain applications since 2018. • China, Singapore and their institutions are leading research in this domain. This paper presents systematic literature review with bibliometric analysis that aims at studying and identifying potential uses of blockchain technology in the context of Maritime Single Window and Port Community Systems. The research aims to examine the state of development of the blockchain technology, to determine the trends of the industry and to analyze the prevalent strengths and weaknesses of the industry. Through analyzing 51 peer-reviewed articles from Scopus and Web of Science (between 2013 and 2023), it is possible to state that the rate of scholars’ engaging with the topic has risen significantly since 2018 within the countries in Asia, especially China, Singapore, and other countries. Our mapping outlines five major streams of research: security and sharing of data in ports and port innovation; behavioral analysis of decentralized technologies in smart ports; factors leading to success of blockchains; effects of blockchains on container shipping; and integration of blockchains with IoT and supply chain management. The review highlights how blockchain can improve security, increase the performance of procedures, guarantee signature and credibility, and build trust, which are fundamental for growth in the maritime sectors. However, the study identifies several main implementation challenges, namely, scale-up features, interoperability, open-endedness, institutional implications, and variable management. As a result, we offer suggestions to the practitioners, policymakers, and scholars on how best to go about the adoption and implementation of blockchain in the maritime industry. Further research in the form of implementation studies, case, legal, and probes on how Blockchain interacts with other emerging technologies is recommended in the study. Namely, they establish foundational domains and define further methodology for subsequent studies and advancement related to blockchain enablement of maritime industries.
Economic theory has long been governed by the principle of scarcity—an assumption that shapes the allocation of resources in virtually all historical economic systems. From classical economics, as articulated by Adam Smith in The Wealth of Nations (1776), to the critiques of capitalist frameworks offered by Karl Marx in Das Kapital (1867), scarcity has been the foundational pillar upon which economies have been constructed. Even in the 20th and 21st centuries, the models of Keynesian economics (Keynes, 1936) and neoliberal capitalism (Friedman, 1962) maintain that resource allocation is predicated on the limits imposed by scarcity, whether that scarcity is natural, human, or financial. However, the technological and systemic advances of the 21st century have begun to challenge this assumption, which, despite its dominance, no longer reflects the evolving nature of global economies. In the era of digital technologies, artificial intelligence (AI), and quantum computing, scarcity is increasingly being replaced by a new set of possibilities—an emergent paradigm defined by abundance and infinite scalability. Quantum computing offers the potential for processing power so vast that it could redefine the very nature of problem-solving. Simultaneously, AI-driven automation and digital decentralization are dismantling traditional models of labor, resource management, and value creation (Brynjolfsson & McAfee, 2014). Moreover, advancements in nanotechnology and synthetic biology could soon facilitate material abundance in previously unimaginable ways, fundamentally undermining traditional economic concerns about finite resources (Drexler, 2013). Blockchain technology, with its promise of decentralized finance (DeFi), is already challenging the very nature of money, while new models of governance enabled by AI and multi-agent systems are rethinking the need for centralized economic management (Helbing, 2015). This transformation signals the birth of a new economic model, one that transcends traditional notions of scarcity—what we term the Infinity Economy. The Infinity Economy represents a departure from existing paradigms of capitalism, socialism, and even post-capitalism (Piketty, 2014). It proposes a complete reimagining of how value is produced, exchanged, and distributed in a world increasingly defined by technological abundance. Rather than extending existing economic systems, the Infinity Economy seeks to eliminate the very foundations of economic thought—namely, scarcity and limited resource allocation—ushering in an era where value and wealth are no longer bound by finite constraints.
Cross-border payments face persistent challenges in today's global economy, characterized by high costs, lengthy processing times, and operational inefficiencies within traditional correspondent banking models. The emergence of blockchain technology offers a transformative solution to these long-standing issues through its distributed ledger architecture, smart contracts, and innovative consensus mechanisms. By eliminating intermediaries and automating processes, blockchain implementation in cross-border payments demonstrates the potential to revolutionize international money transfers by reducing transaction times, lowering costs, and enhancing transparency. The technology's inherent features address critical pain points in current systems while providing robust security measures and improved auditability, particularly benefiting developing economies and regions with limited banking infrastructure.
This study integrates blockchain technology into smart agriculture to enhance its productivity and sustainability. By combining blockchain with remote sensing, artificial intelligence (AI), and the Internet of Things (IoT), a Human-Cyber-Physical System (H-CPS) architecture tailored for agricultural applications is proposed. It supports real-time crop management, data-driven decision-making, and transparent trading of agricultural products. A semantic-based blockchain framework is introduced to address challenges in data management and AI model integration, optimizing production, improving traceability, reducing costs, and enhancing financial security. This framework directly addresses real-world agricultural challenges, such as optimized irrigation, improved crop breeding efficiency, and enhanced supply chain transparency. These innovations provide practical solutions for modern agriculture, contributing to sustainable development and global food security. Further research and collaboration are encouraged to unlock its full potential in transforming agricultural practices.
The evolution of supply chain finance has entered a transformative phase driven by data analytics, artificial intelligence, and digital technologies. This article examines how these innovations are reshaping financial relationships between buyers, suppliers, and financial institutions in supply chains worldwide. It explores the core data technologies revolutionizing supply chain finance, including ERP integration, advanced analytics, and automated financing platforms. The article further investigates how artificial intelligence and machine learning applications enhance credit risk assessment, enable dynamic pricing models, improve fraud detection, and streamline document processing through natural language processing. Additionally, it analyzes the impact of blockchain and distributed ledger technologies in automating payments through smart contracts, expanding access to financing through tokenization, and providing end-to-end traceability. While highlighting the significant benefits of these technologies, the article also addresses implementation challenges related to data quality, system integration, and change management requirements, offering insights for organizations seeking to optimize their supply chain finance operations in an increasingly digital ecosystem.
Blockchain has been broadly practiced in different markets. It is decentralized, unchangeable, and transparent. Our essay summarizes its practices in three key industries including finance, healthcare, as well as supply chain management. In the former, it benefits efficiency in payment and settlement, preventing greenwashing and optimizing carbon trading. In the middle, it helps in digital health check management, clinical trial transparency, and insurance claim simplification. Blockchain also brings product traceability and multi-party collaboration, while facilitating managing flow. Our work uncovered the common obstacles blockchain practices confronted. Future direction standing on newest research heats and multi-subjects are identified. Hopefully, we can plant theoretical bases and practical guidance in blockchain's coming development and general practices.
Ana Fabiola Zamora Vázquez, Francisco Xavier Ávila-Cárdenas, María Caridad Rojas Valdivieso, Juan Bautista Solís Muñoz
This study analyzed the production and commercialization of toquilla straw hats in the Nazón parish, with the objective of assessing the feasibility of establishing an association of toquilla straw weavers in the area, evaluating its potential benefits, challenges, and the applicable legal framework. It was identified that this activity constitutes one of the main sources of income for approximately 25 to 30 families, and represents a key component of the community’s intangible cultural heritage. However, it was found that most weavers sell their products at low prices (less than $10 per hat), mainly due to the involvement of intermediaries and limited access to more profitable markets. Furthermore, 70.6% of the artisans have not received any formal training, which restricts their ability to innovate and improve the marketing of their products. The research employed a mixed-methods approach, combining qualitative and quantitative techniques. Surveys were administered to 17 out of 20 selected women, who expressed interest in joining a formal association. Data collection was primarily based on first-hand sources, including the testimony of the President of the Rural Parish Decentralized Autonomous Government of Nazón, and was complemented by secondary information regarding relevant regulations and prior studies. Among the most relevant findings was the low participation of young people in this artisanal activity, which poses a threat to its generational continuity. Notably, 100% of the respondents indicated their willingness to be part of a formal organization. The study concludes that the formalization of a weavers’ association, accompanied by training processes, access to technology, and digital marketing strategies, represents a viable solution to ensure both the economic and cultural sustainability of this traditional craft.
This article examines the intersection between non-fungible tokens (NFTs) and copyright within the realm of digital intellectual property. NFTs represent a disruptive technology that challenges traditional notions of ownership and authenticity, raising new legal and ethical questions. The study analyzes how this technology impacts the creation, distribution, and commercialization of digital works, and evaluates the challenges current copyright laws face when applied to this new environment, including issues such as ownership, reproduction, and derivative works. It also explores the role of smart contracts associated with NFTs and their potential to automate the management of rights and royalties. The article highlights risks such as plagiarism and forgery in the digital space and proposes both legal and technological solutions. Through case studies and emerging trends, it suggests how legislation may evolve to adapt to the NFT era. Finally, it offers practical recommendations for creators, platforms, and policymakers to navigate this new digital frontier.
The focus of this work is to map the value and production chains of Aviation Kerosene Fuel (AKF), with particular attention to the points where decarbonization actions are being implemented and monitored.To do so, we propose the use of blockchain technology, which allows the creation of an immutable record of production and value chains for this fuel.This approach provides transparency throughout the process -from production to fueling aircraft -by ensuring the traceability of AKF's origin and its compliance with safety regulations.As a major contribution, the study proposes the tokenization of attributes related to decarbonization through NFTs (Non-Fungible Tokens), that could serve as evidence tools for end customers and even be traded in a secondary market.The decentralized and immutable nature of a Distributed Ledger Technology (DLT) not only enhances the management of metrics associated with the energy transition but also minimizes the risk of fraud, enabling the automation of transactions through smart contracts.
This investigation evaluates blockchain’s dichotomous effects on auditing through systematic literature synthesis and comparative case studies of Big Four accounting firms. Empirical evidence demonstrates that distributed ledger technology enhances audit efficacy through automated transaction authentication (exemplified by PwC’s 90% temporal reduction in reconciliation protocols) and machine learning-powered anomaly detection algorithms, enabling comprehensive audit sampling and continuous monitoring capabilities. Persistent technical risks remain, notably 51% consensus vulnerabilities, self-executing contract exposures, and throughput constraints in decentralized architectures, which collectively compromise system integrity. Furthermore, regulatory lacunae in cross-jurisdictional compliance frameworks and practitioners' competency deficits in cryptographic validation techniques substantially impede technological assimilation. The analysis substantiates three critical imperatives: (1) harmonized regulatory frameworks with Turing-complete compliance protocols, (2) cross-disciplinary human capital development initiatives, and (3) applied research on heterogeneous system interoperability. Strategic mitigation of these implementation barriers could transition auditing toward cryptographic trust ecosystems, contingent upon synergistic collaboration between regulatory bodies establishing adaptive governance models, corporate entities developing hybrid audit architectures, and academic institutions advancing validation methodologies.