Objective: This study aims to comprehensively analyze the transformative potential of asset tokenization for Micro, Small, and Medium Enterprises (MSMEs) within the Decentralized Finance (DeFi) ecosystem, with a focus on opportunities, risks, and the hybrid governance architecture required. Research Design & Methods: This study uses a qualitative approach, combining a systematic literature review and case studies with thematic content analysis of secondary data from credible sources to identify patterns and key themes. Findings: Findings show that tokenization of MSME assets offers significant opportunities, such as broader and faster access to funding through fractionalization of ownership, increased asset liquidity, operational efficiency, and enhanced transparency and security. However, this implementation is accompanied by various risks, including smart contract vulnerabilities, cyber attacks, blockchain scalability challenges, regulatory uncertainty, market volatility, and operational risks related to reliance on off-chain third parties. A hybrid governance architecture that integrates on-chain and off-chain elements is essential to mitigate these risks. Implications & Recommendations: This study indicates that tokenization can be an essential bridge for MSMEs to enter the global digital economy, but it requires improved digital literacy and technological readiness. For investors, it offers new diversification opportunities with inherent risks. Policy recommendations include adaptive regulation, simplified compliance, digital education, infrastructure strengthening, utilization of regulatory sandboxes, and cross-sector collaboration and standardization. Contribution & Value Added: This study presents a comprehensive framework for tokenizing MSME assets, offering practical guidance for various stakeholders to promote financial inclusion and equitable economic growth.
The aim of the study was to conduct a comprehensive comparison of selected popular cryptocurrencies, such as Bitcoin, Ethereum, XRP, Cardano, and Litecoin. The analysis was carried out in terms of technological categories, scalability, as well as security and privacy. In addition, the development prospects of selected cryptocurrencies were assessed.The research showed that despite its slow transaction speed and scalability issues, Bitcoin is the most widely accepted cryptocurrency as a form of payment, while XRP, which has the fastest transaction speed, is not as widely chosen and supported as a payment method. In terms of everyday applications, Ethereum is the best choice due to its ability to automate many business processes. Most cryptocurrencies are decentralized, which is the foundation of their existence and functioning. Bitcoin, Litecoin, and Cardano place considerable emphasis on this, while there is much debate about the actual decentralization of XRP due to their affiliation with Ripple Labs. An analysis of price stability and volatility has shown that a large proportion of cryptocurrencies are dependent on Bitcoin's market position, which gives an idea of how important it is as a resource. In terms of potential future applications, each of the cryptocurrencies studied can be used as a means of payment, but Bitcoin and Ethereum have the potential to find general use. In addition, they are seen by investors as the safest investment option due to the constant improvements and updates.Analysis in terms of selected factors, including technology, privacy, stability, and price volatility, allowed us to determine the relationship between these factors and the development prospects of the given cryptocurrencies. Bitcoin and Ethereum are the most popular currencies due to their price, and investors often treat them as long-term investments with high growth potential. XRP, Cardano, and Litecoin are less commonly used due to their high dependence on Bitcoin and low growth potential compared to other cryptocurrencies.
Teodora Maria Suciu, Nicoleta Verejan, Adela Socol
The accelerated development of digital technologies and cryptocurrencies in latest years has been accompanied by an exponential raise in related scientific literature. This study conducts a bibliometric analysis based on the VOSviewer software for documents indexed in the Web of Science Core Collection from 2015-2024, focusing on the evolution of research topics in the field of cryptocurrencies. The analysis employs co-occurrence mapping of the main research topics related to cryptocurrencies. The results highlight a high degree of thematic diversification, organized into five major clusters with the following directions: cryptocurrency markets and financial performance, digital assets and technological foundations, blockchain infrastructure and governance, emerging applications and risks, general cryptocurrency concepts and operational aspects. This research contributes to the knowledge by offering a comprehensive and structured overview of cryptocurrency-related literature streams, providing valuable insights for scholars, policymakers and industry stakeholders seeking to understand the trajectory and future potential of cryptocurrency-related research.
Mario Fernando Herrera Venegas, Martín Wilson Lozano Rivera, Johanna Yadira Zambrano Solórzano
This study develops and empirically validates a budget reform model aimed at enhancing the national transplant system in Ecuador. Employing an applied, cross-sectional quantitative design, data were collected from 109 employees of the National Institute of Donation and Transplantation of Organs, Tissues, and Cells (INDOT) through validated instruments assessing budgetary reform dimensions and transplant activity. Ordinal logistic regression and model-fit tests confirmed a statistically significant relationship (χ², Wald; p<0.05), with a pseudo-R² (Nagelkerke ≈0.997). Results reveal that public underfunding, limited earmarked revenues, and rigid execution rules critically restrict the efficiency and sustainability of transplant programs. Descriptive findings also identified advisory, substantive, and decentralized management processes as institutional bottlenecks. Building on these results, the paper proposes a legislative framework to establish a public trust fund, fed by service fees and fiscal transfers, ensuring transparent, predictable, and decentralized financing for transplantation. The proposed model provides a replicable policy instrument for countries facing fiscal constraints, offering practical strategies to strengthen governance, financial sustainability, and access to organ transplantation services.
Network Systems, AT&T, United States, Amar Gurajapu, Vardhan Garimella, United States Intellibus
ABSTRACT: Distributed cloud services across multiple providers demand consistent identity verification and policy enforcement. Centralized IAM and policy managers introduce single points of failure, limited auditability, and latency. We propose BC-IdPol, a blockchain-based framework that stores identities and governance policies on a permissioned ledger. Smart contracts enforce registration, authentication, and policy retrieval. Off-chain cloud agents query the chain for runtime decisions. In experiments over a three-cloud prototype (Azure, AWS, GCP) on Hyperledger Fabric, BC- IdPol achieved: 99.9 % tamper-resistance (vs. 0 % baseline) 45 ms median identity lookup latency (vs. 18 ms centralized API) 60 ms median policy fetch time (vs. 20 ms baseline) 1,800 req/sec enforcement throughput (vs. 2,200 req/sec) We detail architecture, smart-contract design, mermaid diagrams, evaluation results, limitations, and future work.
Eka Lia Febrianti, Agus Suryadi, Ilwan Syafrinal, Andhika Andhika
Abstract: The global transition towards sustainable food systems faces significant challenges in vegetarian food supply chains, including transparency issues, distribution inefficiencies, and quality verification problems. This research proposes VegeChain development, a decentralized marketplace ecosystem based on smart contracts designed to transform vegetarian food supply chains and accelerate Meatless, Balanced, Green (MBG) program adoption. Using mixed-method methodology integrating blockchain system design, stakeholder analysis, and economic simulation, this research develops a comprehensive technology framework combining blockchain transparency, smart contract automation, and sustainable tokenomics with novel mathematical models. The system implements dynamic pricing algorithms based on Automated Market Maker (AMM) mechanisms, multi-objective optimization for supply chain efficiency, and reputation-based consensus protocols. Simulation results demonstrate that VegeChain implementation can improve supply chain efficiency by 35%, reduce food waste by 28%, and increase consumer trust by 42% measured through validated stakeholder satisfaction surveys (n=456) using 5-point Likert scales with statistical significance p<0.001. Technical innovations include Byzantine Fault Tolerant consensus with 99.9% reliability, gas optimization achieving 67% cost reduction, and real-time quality verification algorithms with 98.7% accuracy. Keywords: smart contracts; supply chain optimization; automated market makers; blockchain technology; sustainable tokenomics
This study analyzes the time-varying interactions among assets in the digital financial asset market. Within the scope of the study, 1,820 daily observations from the 2020–2025 period for Ethereum, Ripple, Binance Coin, Cardano, Stellar, IOTA, Stacks, and Chainlink are examined using the Generalized R² method proposed by Balli et al. (2023). This approach reveals both contemporaneous and lagged interconnectedness between assets, thereby enabling an understanding of how dynamic relationships evolve over time. The results indicate that market interconnectedness is not stable over time and that the transmission of shocks tends to intensify particularly during periods of uncertainty. The findings show that Ethereum maintained a central role throughout the analysis period, while Cardano, STX, LINK, and IOTA were more exposed to shocks. These results underscore the necessity of policy frameworks that address not only individual asset risks but also contagion risks to promote market stability. From an investor’s perspective, it is recommended that portfolio compositions consider both contemporaneous and lagged effects.
The Internet of Things (IoT) has made secure and reliable data communication more difficult due to its dynamic topologies, energy constrictions, and intelligent and sophisticated adversaries.To address these difficulties in IoT networks, we propose G-TrustChain, an integrated hybrid framework based on Graph Neural Networks (GNNs) for intelligent and dynamic routing and a light Blockchain for distributed trust.G-TrustChain makes use of node-level parameters including latency, remaining energy, and behavioural trust scores derived from a Graph Attention Network (GAT) for routing paths.A lightweight Directed Acyclic Graph (DAG)-structure Blockchain maintains trust scores with a distributed, scalable, and tamper-proof ledger that minimizes dependency on a centralized authority.Experimentation is done for 10,000 rounds, G-TrustChain demonstrated superior routing performance to other protocols such as Trust-based Routing, BBTR, and ROUTENET.It is achieving 95.6% packet delivery ratio, 91.2% detection rate of attacks, and energy consumption as low as 0.0110 J/bit.Also achieving more accurate and reliable trust scores despite energy constraints and higher/extensive attacks.These outcomes demonstrated G-TrustChain provides energy-efficient, secure, and intelligent data communication for the next generation of IoT networks.
Advances in differential equations and control theory are reshaping how secure, efficient medical data-exchange systems are designed. In parallel, blockchain offers decentralized trust, cryptographic integrity, and auditable access control for healthcare networks. Yet the choice of storage and transmission architecture strongly affects scalability, latency, privacy, and cost. This work investigates how mathematical modeling via differential equations and modern control processes can be coupled with blockchain to strengthen security and interoperability across distributed healthcare systems. We comparatively examine three deployment models: (1) on-chain storage, (2) off-chain, cloud-backed storage with blockchain access control, and (3) local institutional storage integrated with federated learning. On-chain designs maximize transparency and tamper-resistance but incur substantial computation and storage overhead. Off-chain approaches improve scalability while retaining verifiable control through the ledger. Local storage with federated learning safeguards patient privacy by keeping raw data within institutions and sharing only encrypted updates or proofs on chain. Persistent challenges include storage bloat, network delays, heterogeneous regulations, and evolving attack surfaces. To address these issues, we outline optimization strategies grounded in system dynamics stability analysis, resource allocation, and control-oriented tuning to balance throughput, privacy, and reliability. The study synthesizes theoretical insights with implementation considerations, offering a unified perspective on building resilient, performant, and privacy-preserving medical data-exchange frameworks that leverage blockchain under mathematically principled control.
Abstract: Authoritarian governments worldwide are increasingly using financial repression to disable their challengers. By surveilling and freezing bank accounts, they can stop democratic opposition in its tracks. At the same time, human rights groups from Nigeria to Russia to Hong Kong are turning to Bitcoin—a censorship-resistant digital currency that can be used without tying one's transactions to one's personal information—to receive donations, run payroll, and keep their operations going, even if dictators want them to stop.
Artificial intelligence (AI) is increasingly central to solving complex societal, economic, and scientific problems, yet prevailing models remain constrained by their opacity, vulnerability to adversarial inputs, and reliance on centralized infrastructures. These limitations underscore the urgent need for approaches that combine the adaptability of neural networks with the interpretability and rule-based precision of symbolic systems. At the same time, decentralization has emerged as a critical paradigm for enhancing trust, resilience, and accountability in intelligent systems. Together, these threads converge on the concept of decentralized neuro-symbolic cognitive systems, which integrate distributed inference, symbolic reasoning, and governance mechanisms to create secure and transparent frameworks for machine intelligence. This article presents a comprehensive methodology for the design and operation of such systems, advancing beyond conventional hybrid AI by embedding causal intent routing, federated cognitive capsules, encrypted episodic memory, and immutable epistemic ledgers. These elements are supported by governance innovations such as the NeuroConstitution™, which enables tokenized, evolvable norms and ensures accountability through transparent dispute resolution. The framework is evaluated across key application domains, including healthcare, finance, governance, and climate modeling, with comparative benchmarks demonstrating gains in robustness, interpretability, and systemic trust. By uniting symbolic reasoning, neural inference, and decentralized governance, this research outlines a pathway toward AI systems that are not only technically powerful but also socially aligned and ethically defensible. The article concludes that decentralized neuro-symbolic architectures provide a sustainable foundation for advancing trustworthy AI capable of supporting critical infrastructures and decision-making in a rapidly evolving world.
This study investigates how market capitalization, price volatility, and behavioral biases affect decisions to buy cryptocurrencies. Because of its decentralized structure and extreme volatility, the cryptocurrency market frequently affects investment choices through psychological elements, including loss aversion, overconfidence, and herd mentality. This study uses a quantitative methodology to analyze data from the nine most traded cryptocurrencies using independent t-tests, multiple linear regression, and simple linear regression. According to the study's findings, decisions to buy cryptocurrencies are significantly positively influenced by herd behavior and overconfidence, as shown by high volatility, but not significantly by loss aversion. Furthermore, it has been demonstrated that price volatility significantly affects herd behavior, meaning that investors are influenced to follow the majority lead when prices fluctuate significantly. However, the degree of herd behavior is not affected by market capitalization, suggesting that psychological elements like herd behavior are more impacted by general market conditions than by market capitalization size. These results highlight how crucial it is to comprehend the psychological aspects of cryptocurrency market decision-making, since doing so can offer a better understanding of investor behavior and the workings of this extremely unpredictable market.
The purpose of this article is to study the peculiarities of the functioning of Ukraine's public finance system under martial law, identify key challenges associated with high levels of economic and social uncertainty, and justify possible ways of adapting budgetary and financial policy to ensure the sustainability, balance, and efficiency of public resource management. The article analyzes the current state of public finances in Ukraine under martial law, describes the main trends in the formation of revenues and expenditures of the state budget, the impact of military actions on the tax system, interbudgetary relations, and financial decentralization. It identifies the main challenges facing the state's financial system, including a sharp increase in military and social spending, a reduction in budget revenues due to a decline in economic activity, a growing budget deficit, and the need for external financing. Particular attention is paid to the role of international financial assistance in maintaining macroeconomic stability, ensuring the solvency of the state, and financing critically important sectors of the economy. The problems of effective public finance management during wartime are highlighted, in particular the issues of transparency of budgetary processes, targeted use of funds, risks of corruption, and restrictions in the area of financial control. Directions for improving public finance management mechanisms in conditions of uncertainty are substantiated, including the digitization of financial processes, strengthening anti-crisis planning, optimizing budget expenditures, improving the effectiveness of financial control, and developing strategic forecasting. Recommendations are proposed to improve the country's financial stability in the medium and long term, which include aligning domestic financial capabilities with external support, improving the efficiency of budget resource use, developing effective public debt management mechanisms, and enhancing financial security as a component of national stability.
Introduction: The rapid development of financial technology (fintech) and blockchain has brought a major transformation in the global industry, including in the Islamic finance sector. However, integrating fintech and blockchain with Sharia principles remains a challenge and has not been studied systematically. This research aims to map and analyze the development of research related to Fintech, Blockchain, and Islamic finance, identifying trends, research gaps, and future development directions. Methods: This study employed a qualitative research method with a Systematic Literature Review approach, utilizing a model prism. The data source for this study consisted of published articles obtained from Scopus and Emerald. The study's results showed that 30 articles, published in Scopus and Emerald, were published between 2015 and 2024. Results: Based on the findings obtained, it is evident that blockchain technology, fintech, and digital innovation have significant potential in enhancing the efficiency, transparency, and inclusivity of Islamic finance, particularly through applications in zakat, waqf, sukuk, and crowdfunding. Despite regulatory and collaboration challenges, these technologies have been able to eradicate poverty, support economic development, and expand access to finance, including in non-Muslim countries. Technology adoption is also influenced by religiosity factors and perception of benefits, confirming the need for global regulatory and standard support to maximize its benefits. Conclusion and Suggestion: The reviewed studies suggest that blockchain technology has significant potential to strengthen trust and compliance with Shariah by enabling smart contracts, decentralized financial products, and transparent auditing mechanisms. Moreover, fintech solutions can expand financial inclusion in Muslim-majority countries and beyond, especially for the unbanked population. However, challenges remain in terms of regulatory frameworks, Shariah standardization, scalability of blockchain applications, and the readiness of financial institutions and customers to adopt these innovations. In conclusion, while fintech and blockchain present strong prospects for advancing Islamic finance, further research and practical implementation are required to fully realize their potential in providing Shariah-compliant, inclusive, and sustainable financial services.
Atul Kumar Singh, Nishanth Rao Dugyala, Farzad Pour Rahimian, Faris Elghaish · 5 authors
Existing ESG reporting tools in construction organizations often lack transparency and accountability, presenting significant challenges in effectively managing and reporting ESG data. This research addresses the gap in current reporting practices by proposing and validating a hybrid blockchain solution aimed at enhancing ESG reporting in the Architecture, Engineering, and Construction (AEC) industry. The primary objective is to develop a blockchain-based solution that automates ESG reporting, addressing issues such as data fragmentation, lack of verification, and inefficiencies. Adopting a design science approach, the study develops a conceptual framework that combines Ethereum and Hyperledger Fabric to create a hybrid blockchain model for the prototype. The comprehensive literature review highlights key challenges in ESG practices and emphasizes the potential of blockchain technology to overcome these barriers. The findings show that the hybrid blockchain model successfully automates the ESG reporting process, ensuring transparency, immutability, and accountability. The prototype, validated through a case study involving two construction organizations, demonstrates the feasibility of combining Ethereum and Hyperledger Fabric to manage ESG data, reducing errors, preventing manipulation, and enabling real-time reporting. This research enriches the theoretical understanding of blockchain applications in ESG practices. It provides practical implications by offering a tangible, blockchain-based solution that ensures transparent, reliable, and accountable ESG reporting in the construction industry, ultimately contributing to more sustainable practices.
The current study undertakes a bibliometric examination to analyze the emerging intersection of green finance and environmental monitoring, two critical areas that are driving the global agenda for sustainability. Based on evidence from the Scopus database and visualization using VOSviewer, the study investigates 20 years of scholarly articles to identify major authors, institutions, countries, and thematic groups. The findings of the research pinpoint a discernible chronological development—early research into pollution detection and environmental monitoring systems giving way to subsequent emphasis on financial tools such as green bonds, sustainable development investments, and decentralized finance. Keyword co-occurrence and overlay visualization show how environmentally pertinent data increasingly is being made part of financial decision-making and policy-making. In addition, the study reveals Chinese, American, Indian, and certain European country regional leadership in terming the story. Findings reveal theoretical and empirical contributions through the convergence of environmental science and financial innovation, as well as discovering limitations towards database scope and metrics by citation. Lastly, the study provides a strategic model for scholars, investors, and policymakers seeking to align environmental intelligence with sustainable finance practice.
Fernando Hose, Florika Censaka, Ricky Andrian Wijaya, Jennifer · 6 authors
Perkembangan era digital meningkatkan risiko terhadap identitas digital dan privasi data, sehingga dibutuhkan mekanisme keamanan yang lebih adaptif. Zero-Trust Architecture (ZTA) hadir dengan prinsip “never trust, always verify”, sementara blockchain menawarkan sistem desentralisasi yang transparan dan tahan manipulasi. Kajian ini bertujuan menganalisis peran blockchain dalam memperkuat ZTA, khususnya pada aspek autentikasi dan pengelolaan identitas. Melalui pendekatan kualitatif berbasis studi kasus dengan analisis literatur dan dokumen, hasil menunjukkan bahwa penerapan Decentralized Identifiers (DID) dan Self-Sovereign Identity (SSI) memungkinkan pengguna mengendalikan data pribadi, serta memperkuat auditabilitas, verifikasi berlapis, dan privasi melalui smart contract serta zero-knowledge proofs. Namun, integrasi blockchain-ZTA masih menghadapi tantangan berupa skalabilitas, manajemen kunci, dan kepatuhan regulasi. Oleh karena itu, diperlukan pendekatan hybrid dan regulasi yang adaptif agar integrasi ini dapat menjadi fondasi keamanan digital yang andal dan berkelanjutan.
This analytical review examines Pakistan's dual-path approach to digital finance by assessing the policy tension between decentralized cryptocurrencies (CC) and a Central Bank Digital Currency (CBDC). Through a comprehensive analysis of grey literature and policy documents, the study identifies a significant ideological struggle between risk-averse financial institutions and a pro-innovative government faction. Our findings reveal that this conflict has led to a pragmatic, dual-track strategy: the formalization of the CC market via the Virtual Assets Ordinance 2025 and the parallel development of a state-controlled CBDC. The research quantifies the scale of the informal CC economy, estimating it involves 15-20 million Pakistanis and holds the potential to unlock $20-25 billion in dormant assets for the formal economy. Concurrently, the Digital Pakistani Rupee (CBDC) is projected to reduce the substantial direct costs of cash, estimated at Rs76 billion annually, and enhance financial inclusion for approximately 100 million unbanked adults. The study concludes that for this dual strategy to succeed, Pakistan must prioritize policy harmonization, a privacy-centric CBDC design, and a streamlined regulatory framework for virtual assets. This case offers critical lessons for developing nations navigating the trade-offs between financial innovation, stability, and inclusion
Maruf Farhan, Usman Butt, Rejwan Bin Sulaiman, Mansour Naser Alraja
The widespread circulation of digital misinformation exposes a critical shortcoming in prevailing detection strategies, namely, the absence of robust mechanisms to confirm the origin and authenticity of online content. This study addresses this by introducing VeriTrust, a conceptual and provenance-centric framework designed to establish content-level trust by integrating Self-Sovereign Identity (SSI), blockchain-based anchoring, and AI-assisted decentralized verification. The proposed system is designed to operate through three key components: (1) issuing Decentralized Identifiers (DIDs) and Verifiable Credentials (VCs) through Hyperledger Aries and Indy; (2) anchoring cryptographic hashes of content metadata to an Ethereum-compatible blockchain using Merkle trees and smart contracts; and (3) enabling a community-led verification model enhanced by federated learning with future extensibility toward zero-knowledge proof techniques. Theoretical projections, derived from established performance benchmarks, suggest the framework offers low latency and high scalability for content anchoring and minimal on-chain transaction fees. It also prioritizes user privacy by ensuring no on-chain exposure of personal data. VeriTrust redefines misinformation mitigation by shifting from reactive content-based classification to proactive provenance-based verification, forming a verifiable link between digital content and its creator. VeriTrust, while currently at the conceptual and theoretical validation stage, holds promise for enhancing transparency, accountability, and resilience against misinformation attacks across journalism, academia, and online platforms.
In this study, an ensemble neural network (ENN) for Ethereum time series prediction was optimized using particle swarm optimization and genetic algorithms. Additionally, Type-1, Type-2, and Type-3 fuzzy inference systems, of both Mamdani and Sugeno types, were designed for achieving the prediction. The integration performed with these fuzzy systems is achieved by utilizing the results from optimizing the ENN with each optimization algorithm. In this case, the Ethereum data is the series being used for testing the proposal. This approach aims to minimize prediction error by combining the responses of the ENN with Type-1, Type-2, and Type-3 fuzzy systems, each consisting of five inputs and consequently 32 fuzzy rules are utilized. The results show that the Type-1, Type-2, and Type-3 fuzzy system approach yields an accurate prediction of the Ethereum series, as further validated by statistical tests on the results of the fuzzy systems.