Dumitrel Loghin, Shuang Liang, S. Liu, Xiong Liu · 6 authors
Zero-knowledge proofs (ZKP) are becoming a gold standard in scaling blockchains and bringing Web3 to life. At the same time, ZKP for transactions running on the Ethereum Virtual Machine require powerful servers with hundreds of CPU cores. The current zkProver implementation from Polygon is optimized for x86-64 CPUs by vectorizing key operations, such as Merkle tree building with Poseidon hashes over the Goldilocks field, with Advanced Vector Extensions (AVX and AVX512). With these optimizations, a ZKP for a batch of transactions is generated in less than two minutes. With the advent of cloud servers with ARM which are at least 10% cheaper than x86-64 servers and the implementation of ARM Scalable Vector Extension (SVE), we wonder if ARM servers can take over their x86-64 counterparts. Unfortunately, our analysis shows that current ARM CPUs are not a match for their x86-64 competitors. Graviton4 from Amazon Web Services (AWS) and Axion from Google Cloud Platform (GCP) are 1.6X and 1.4X slower compared to the latest AMD EPYC and Intel Xeon servers from AWS with AVX and AVX512, respectively, when building a Merkle tree with over four million leaves. This low performance is due to (1) smaller vector size in these ARM CPUs (128 bits versus 512 bits in AVX512) and (2) lower clock frequency. On the other hand, ARM SVE/SVE2 Instruction Set Architecture (ISA) is at least as powerful as AVX/AVX512 but more flexible. Moreover, we estimate that increasing the vector size to 512 bits will enable higher performance in ARM CPUs compared to their x86-64 counterparts while maintaining their price advantage.
The Intelligent System of Emergent Knowledge (ISEK) establishes a decentralized network where human and artificial intelligence agents collaborate as peers, forming a self-organizing cognitive ecosystem. Built on Web3 infrastructure, ISEK combines three fundamental principles: (1) a decentralized multi-agent architecture resistant to censorship, (2) symbiotic AI-human collaboration with equal participation rights, and (3) resilient self-adaptation through distributed consensus mechanisms. The system implements an innovative coordination protocol featuring a six-phase workflow (Publish, Discover, Recruit, Execute, Settle, Feedback) for dynamic task allocation, supported by robust fault tolerance and a multidimensional reputation system. Economic incentives are governed by the native $ISEK token, facilitating micropayments, governance participation, and reputation tracking, while agent sovereignty is maintained through NFT-based identity management. This synthesis of blockchain technology, artificial intelligence, and incentive engineering creates an infrastructure that actively facilitates emergent intelligence. ISEK represents a paradigm shift from conventional platforms, enabling the organic development of large-scale, decentralized cognitive systems where autonomous agents collectively evolve beyond centralized constraints.
With its potential to address persistent issues like inefficiency, fraud, and a lack of transparency, distributed ledger technology (DLT), and in particular blockchain, has become a game-changing breakthrough in the realm of international trade. With a thorough examination of its potential to revolutionize trade processes, this study examines the applications of DLT in global commerce. It starts by examining the conventional cloud-based models that predominate in global trade procedures and contrasting them with the blockchain-based approach that has been suggested. The viability and effect of blockchain technology (BCT) in this industry are evaluated by the research using both qualitative and quantitative approaches, such as data collecting, comparative analysis, and SWOT analysis. The main impediments to blockchain adoption are noted, along with suggested fixes for them. A discussion of potential future possibilities and suggestions for using blockchain technology into global trade networks round out the report. The purpose of this study is to offer theoretical understandings and useful suggestions for the successful use of blockchain technology in international trade.
This conceptual paper contributes to the nascent Web3 marketing stream via offering a novel typology of Non-Fungible Tokens (NFTs) as blockchain-enabled digital offerings. Grounded in a customer-centric approach to marketing strategy, our 2 × 2 typology suggests that NFTs vary in terms of the value on offer (i.e. value-in-use/value-in-exchange) and the strategic focus pursued by firms/creators (i.e. transactional/relational). Four main types of NFTs thus emerge: 1. Validation certificates; 2. Digital replicas; 3. Immersion enablers; and, 4. Digital upgrades. For each NFT type, we discuss their distinctive features, the opportunities they offer and their shortcomings, before detailing their strategic implications. Our typology offers researchers and practitioners who want to engage with the Web3 space a solid grounding for understanding the implications of deploying different types of NFTs from a strategic marketing perspective.
Open access
2 source records
Service and Product Innovation
Blockchain Technology Applications and Security
Consumer Behavior in Brand Consumption and Identification
This paper presents a comprehensive analysis of an enhanced asynchronous AdaBoost framework for federated learning (FL), focusing on its application across five distinct domains: computer vision on edge devices, blockchain-based model transparency, on-device mobile personalization, IoT anomaly detection, and federated healthcare diagnostics. The proposed algorithm incorporates adaptive communication scheduling and delayed weight compensation to reduce synchronization frequency and communication overhead while preserving or improving model accuracy. We examine how these innovations improve communication efficiency, scalability, convergence, and robustness in each domain. Comparative metrics including training time, communication overhead, convergence iterations, and classification accuracy are evaluated using data and estimates derived from Oghlukyan's enhanced AdaBoost framework. Empirical results show, for example, training time reductions on the order of 20-35% and communication overhead reductions of 30-40% compared to baseline AdaBoost, with convergence achieved in significantly fewer boosting rounds. Tables and charts summarize these improvements by domain. Mathematical formulations of the adaptive scheduling rule and error-driven synchronization thresholds are provided. Overall, the enhanced AdaBoost exhibits markedly improved efficiency and robustness across diverse FL scenarios, suggesting broad applicability of the approach.
Blockchain and edge computing are two instrumental paradigms of decentralized computation, driving key advancements in Smart Cities applications such as supply chain, energy and mobility. Despite their unprecedented impact on society, they remain significantly fragmented as technologies and research areas, while they share fundamental principles of distributed systems and domains of applicability. This paper introduces a novel and large-scale systematic literature review on the nexus of blockchain and edge computing with the aim to unravel a new understanding of how the interfacing of the two computing paradigms can boost innovation to provide solutions to timely but also long-standing research challenges. By collecting almost 6000 papers from 3 databases and putting under scrutiny almost 1000 papers, we build a novel taxonomy and classification consisting of 22 features with 287 attributes that we study using quantitative and machine learning methods. They cover a broad spectrum of technological, design, epistemological and sustainability aspects. Results reveal 4 distinguishing patterns of interplay between blockchain and edge computing with key determinants the public (permissionless) vs. private (permissioned) design, technology and proof of concepts. They also demonstrate the prevalence of blockchain-assisted edge computing for improving privacy and security, in particular for mobile computing applications.
In cryptocurrency markets, a key challenge for perpetual future issuers is maintaining alignment between the perpetual future price and target value. This study addresses this challenge by exploring the relationship between funding rates and perpetual future prices. Our results demonstrate that by appropriately designing funding rates, the perpetual future price can remain aligned with the target value. We develop replicating portfolios for perpetual futures, offering issuers an effective method to hedge their positions. Additionally, we provide path-dependent funding rates as a practical alternative and investigate the difference between the original and path-dependent funding rates. To achieve these results, our study employs path-dependent infinite-horizon BSDEs in conjunction with arbitrage pricing theory. Our main results are obtained by establishing the existence and uniqueness of solutions to these BSDEs and analyzing the large-time behavior of these solutions.
Manuel Jaramillo, Diego Carrión, Jorge Muñoz, Luis Tipán
This study presents a systematic bibliometric review of digital innovations in renewable energy-oriented power systems, with a focus on Blockchain, Artificial Intelligence (AI), the Internet of Things (IoT), and Data Analytics. The objective is to evaluate the research landscape, trends, and integration potential of these technologies within sustainable energy infrastructures. Peer-reviewed journal articles published between 2020 and 2025 were retrieved from Scopus using a structured search strategy. A total of 23,074 records were initially identified and filtered according to inclusion criteria based on relevance, peer-review status, and citation impact. No risk of bias assessment was applicable due to the nature of the study. The analysis employed bibliometric and keyword clustering techniques using VOSviewer and MATLAB to identify publication trends, citation patterns, and technology-specific application areas. AI emerged as the most studied domain, peaking with 1209 papers and 15,667 citations in 2024. IoT and Data Analytics followed in relevance, contributing to real-time system optimization and monitoring. Blockchain, while less frequent, is gaining traction in secure decentralized energy markets. Limitations include possible indexing delays affecting 2025 trends and the exclusion of gray literature. This study offers actionable insights for researchers and policymakers by identifying converging research fronts and recommending areas for regulatory, infrastructural, and collaborative focus. This review was not pre-registered. Funding was provided by the Universidad Politécnica Salesiana under project code 005-01-2025-02-07.
The emerging paradigm of modern vehicles as sophisticated mobile data centers generates unprecedented volumes of telemetry, sensor, and interaction data that require novel management approaches. The architectural framework addresses dual requirements of edge processing for latency-sensitive applications and cloud infrastructure for deeper analytics and model development. Vehicle-to-everything communication protocols integrate with software-defined networks and distributed ledger technologies to ensure secure, efficient data exchange across the ecosystem. Technical challenges including bandwidth constraints, data redundancy, and privacy regulations are primary motivators for solutions based on federated learning, optimized compression algorithms, and context-aware processing. Resilient vehicular data management necessitates a multi-layered approach balancing computational requirements across the edge-cloud continuum while maintaining robust security postures. These foundations enable scaling next-generation intelligent transportation systems were vehicles function as key nodes in broader smart city infrastructures.
Jun 10, 2025·Intelligent Industry Ecosystems and Manufacturing Renaissance: Designing Autonomous Production, Supply Orchestration, and Connected Retail Infrastructure
Drastic liquidity shortages dovetailing with geopolitical uncertainties have led many organizations to expedite their digital transformation initiatives, making the reinvention of the pivot of business activities — supply chains — a priority. The use of modern IT tools to automate, augment, and reinvent procurement, coupled with the trend to outsource more and more ancillary activities to third parties has led to increased interest in the automation of enablers of procurement activities. However, the answer to the question of how far this automation will go remains uncertain, leading to diverging opinions, from the expected complete commoditization of “spend categories” to the carry-over of the entirely bookable unavailability of procurement professionals. In this chapter we concentrate on the first side of the automation debate, using a specific enabler — sourcing — and a generalization of its application to show the promise of more advanced automation techniques, where the sourcing procedure takes place inside a smart contract negotiating automatically on behalf of a business participant using a variety of available agent negotiating engines.
The digital transformation of traditional finance is enabled through intelligent automation and cloud platforms. With these technologies, traditional banks and financial institutions can digitalize their products and services, transforming the banking and finance value chain along the way. Digital transformation goes beyond mere product digitization. As traditional financial institutions journey through the transformation process, they start to share their data and enable integration of back-end processes with other players in the finance ecosystem. Digital transformation leads to opening of traditional financial products through partnerships with fintech enabling easier access to financial services by suppliers, with embedded finance options. Traditional financial services such as lending and insurance underwriting become easier for customers to access through any supplier's front-end interface with integration to bank backends. Data sharing on transaction-based open finance and creditworthiness on decentralized identity with digital wallets, backed by blockchain privacy models enhances financial access for the unbanked and under-banked customers. Products are tailored to the needs of end-users through data analytics techniques and fintech partnerships.
The European Union's (EU) data strategy aims to create a single market for seamless data flow while ensuring proper governance, privacy, and data protection. In this paper, we present SEDIMARK, an EU project, that builds on this strategy by developing a fully decentralised, secure data marketplace. The goal of SEDIMARK is to build a complete toolbox that enables users to purchase and process data assets. The toolbox includes tools for data cleaning, decentralised machine learning models and secure data exchange. SEDIMARK offers users full control over data assets by enabling them to keep their data locally and thus removing the need for central servers. With customisable pipelines and tools, SEDIMARK supports a wide range of users, from novices to experts, promoting seamless collaboration and fair access to high-quality datasets across Europe. The decentralised connectivity in SEDIMARK is achieved with the use of Distributed Ledger Technology (DLT). Furthermore, SEDIMARK's architecture features a unique Connector component using Self Sovereign Identities (SSI), fostering trust and secure interactions. Transactions in SEDIMARK are stored in a Registry, a decentralised, immutable, non-repudiable and permissionless database. Together the technologies used in SEDIMARK ensure privacy, trust and data quality for secure management, sharing, and monetisation of assets in data spaces.
Alexander Grünewald, Patrick Stuckmann-Blumenstein, Patrick Keitzl, Larissa Krämer
Additive manufacturing processes such as 3D printing have seen significant progress in the industry in recent years and have become an integral part of Industry 4.0. This fourth industrial revolution is characterized by the increasing networking and automation of production systems and the use of large amounts of data. In this context, distributed ledger technologies (DLT), which include blockchain technology, offer promising opportunities to change production fundamentally. Production processes can be more secure and efficient by creating trust and transparency in data storage and eliminating dependence on centralized instances. However, the full potential of blockchain technology is often not realized due to the perceived complexity of its implementation. Overcoming this skepticism requires a better understanding of the application possibilities and, more importantly, successful practical examples demonstrating blockchain technology’s transformative power in the industry. This study explores how blockchain can be effectively integrated into additive manufacturing processes and offers a structured overview of existing blockchain-based business models within this domain. Hence, a systematic literature interview, Crunchbase review, and Workshop are performed to examine specific use cases of blockchain in additive manufacturing and analyze how these technologies interact with existing business models. In order to provide an overview of existing blockchain-based business models in the context of additive manufacturing, a taxonomy is developed in the underlying paper to identify characteristic features. The taxonomy is further demonstrated along different existing business models.
An increasing number of DeFi protocols are gaining popularity, facilitating transactions among multiple anonymous users. State Manipulation is one of the notorious attacks in DeFi smart contracts, with price variable being the most commonly exploited state variable-attackers manipulate token prices to gain illicit profits. In this paper, we propose PriceSleuth, a novel method that leverages the Large Language Model (LLM) and static analysis to detect Price Manipulation (PM) attacks proactively. PriceSleuth firstly identifies core logic function related to price calculation in DeFi contracts. Then it guides LLM to locate the price calculation code statements. Secondly, PriceSleuth performs backward dependency analysis of price variables, instructing LLM in detecting potential price manipulation. Finally, PriceSleuth utilizes propagation analysis of price variables to assist LLM in detecting whether these variables are maliciously exploited. We presented preliminary experimental results to substantiate the effectiveness of PriceSleuth . And we outline future research directions for PriceSleuth.
Within initial teacher education (ITE), there is a complex and dynamic relationship between the theoretical content delivered within university settings and the practical components experienced within schools. Strengthening the nexus between the two represents the ongoing work of teacher educators and an ongoing challenge for pre-service teachers. Extended teaching internships (e.g., of 12 months duration) provide opportunities to develop pre-service teachers’ knowledge through classroom application. These extended professional experience components are justified through how they facilitate entry into the profession and support graduate teachers’ traction within the early career phase – an outcome commonly referred to in Australian policy and public discourse as being ‘classroom-ready’. This mixed-methods research presents findings from an examination of a year-long internship. Through surveys and interviews, graduates shared their experiences and perspectives of what they gained from their involvement. Drawing on conceptual tools of community of practice and pillars of the Framework of Conditions Supporting Early Career Teacher Resilience, the analysis identified participants’ sense of belonging and employability as regular and significant outcomes of the internship. Participants reported feeling a sense of belonging to their internship school colleagues and to teaching, explaining this as an influential factor to graduate employment, early career traction and pathways that carried them beyond the early career phase. These findings have implications for the priorities and outcomes pursued through extended internships, especially during a time where employment-based internships are burgeoning. Further long-term research is needed to understand the extent of impact of extended internships on career trajectories and continuity.
The poor economic status particularly in the developing countries has resulted in limited income, scarcity of investment funds, while at the same time regulations governing project financing remain a challenge for the electricity sector. This study investigates the economic sustainability of different sources of energy to provide critical information to planners and policy makers seeking to develop an energy mix that guarantees clean and affordable electricity. Clean, efficient and affordable electricity directly and indirectly supports almost all the sustainable development goals as a vital physical input and enabler. Decentralized energy (DE), and distributed energy systems constitute power generation and storage close to the point of power need or consumption, and may or may not be connected to the distributed network. This reduces the transmission and distribution costs but leads to growth in use of local energy resources, which is an important strategy in the global sustainable energy transition. In terms of investment in clean energy, the financing for clean energy is a major concern for developing countries who play host for the close to 80 % of the global population targeting in SDP 7 targets. Therefore, economic sustainability of the energy transition is of critical importance. Decentralized generation provide numerous economic opportunities besides increasing access to clean energy for remote and off grid communities. This paper aims to develop the understanding of the relative economic value of the various energy options available for decentralized generation. The study compares the economic impacts of energy sources to help in identifying energy sources that will leave the highest positive economic impacts and limited financial cost. The findings of this study are valuable to energy and generation planners and policy makers in policy formulation and development a cost effective energy mixes. Clean, renewable, and affordable energy is a requirement for improved social, economic, and environmental health , which leads to sustainable modern energy and electricity services. The global concerns over greenhouse gas emissions and climate change as well as the need to electrify close to 750 million people with no access to reliable electricity are the main drivers of the current interest in decentralized generation. This generation offers multiple benefits like wider exploitation of local energy resources, reduced transmission and distribution costs as well as losses, higher power system resilience, higher efficiency, and democratisation of the electricity sector. However, high upfront costs and electricity costs can make decentralise generation financially unattractive to consumers and investors. The assimilation of low-cost and highly available low carbon energy sources will contribute to the attainment of the sustainable development goals particularly goal number 1 (SDG1) on poverty alleviation and goal number 7 on access to modern clean energy resources (SDG 7). The economic considerations for different decentralized energy sources was undertaken based on job creation potential, price of energy resources, levelized coat of power, demonstrate the relative economic competitiveness of energy options for decentralized power systems. The study showed that the noncombustible renewables are freely supplied by nature and hence have the lowest operation costs. By having the lowest levelized cost of power compared with fossil fuels , the renewable are more cost competitive on lifecycle basis, additionally renewables led by solar energy have the highest job creation potential. The fossil fuel sources have higher flexibility indicators like lowest ramp time and minimum run time making them ideal source of stabilizing power together with hydropower in the energy mix. Truly sustainable plans in decentralized generation should be based on real local based conditions where credible and site-specific data and information is available as opposed to the use of globalised data adopted in this study. Therefore, the findings of this study ought to be subjected to further review based on local data and realities of specific locations and countries for more reliable and accurate planning. This study demonstrated that distributed and decentralized generation is a power tool for the realisation of all the sustainable development especially in developing countries.
This chapter serves as an introduction for the different themes presented in this book. The future poses many challenges to the proper functioning of Financial Systems at the local and global levels, such as the recent pandemic, increasing levels of poverty and inequality, conflicts, climate change, which have been accelerated by recent technological developments, or high levels of market volatility. We refer to the coordinated evolution of Societal and Digital Intelligence, as well as to the functioning of the Social Brain as Financial Intelligence. Therefore, we are creating the road map to accomplish to ensure the future progress of Financial Intelligence and the proper functioning of Financial Systems via the Decentralized Trust Infrastructure for Cyberpartnerships based on Cryptographic Signatures.
Sara Alonso‐Muñoz, Rocío González Sánchez, Soraya González-Mendes, Fernando E. García‐Muiña
Purpose This paper aims to examine the relationship between the implementation of blockchain in the tourism and hospitality industry (T&HI) and its state-of-the-art. The aim is also to identify emerging research topics and gaps in this area. Design/methodology/approach A bibliometric overview is presented to examine articles from Web of Science published between 2018 and January 2024. The analysis was performed by VOSviewer software using the co-occurrence technique. Findings The results reveal the growing interest in blockchain technologies (BCT) applications in the T&HI. To reveal the conceptual structure and emerging research hotspots in this area, seven clusters were identified along with their interrelationships. This paper discusses the features and attributes of BCT mechanisms, including cryptocurrencies, distributed ledgers, smart contracts and consensus algorithms. The analysis highlights the drivers for increasing adoption and acceptance to promote smart tourism, transparency, trustworthiness and disintermediation. This paper explores the use of non-fungible tokens (NFTs) in the metaverse to promote authenticity and enhance tourists’ experiences, with emphasis on achieving cost-effectiveness and sustainability in the T&HI. In addition, key challenges are identified, with a focus on security and privacy. Practical implications This study provides timely and valuable insights concerning the application of BCT in the T&HI. It elucidates the factors that contribute to the optimal implementation of BCT, such as the collaboration between stakeholders and the key role of regulatory frameworks. Furthermore, it considers the implications for the design of new services towards enhancing sustainability and customer experiences. Originality/value This paper presents the first bibliometric analysis of the use of BCT in the T&HI. It identifies research gaps and future research avenues, which can guide further investigation in this area. This study provides valuable information for organisations, managers and academics who are considering future applications, benefits and challenges in the field of sustainability issues and technology acceptance.
DeFiisrevolutionizingthefinancialworldbyprovidingopen,approval-free,peer-to-peerwaysto transact,thankstoblockchain.DeFiallowsmorefinancialopportunitiesanddifference,butitalso presentsproblemsforAMLandcompliance due tohowitisdecentralized,usespseudonymsand is available in different countries. It describes in detail the barriers faced in DeFi within the EU duetotechnologyandregulations.ItdiscusseswhytraditionallawsareoftenunsuitableforDeFi, leading to questions about regulations, regulatory boundaries and any gaps in enforcing them. StudyingspecificcasesintheEU,thearticleexploresthejourneyofAMLregulationsandpoints out some of the obstacles inside the regulatory sphere due to swift changes in decentralized technology.Movingon,ithighlightsthatitisdifficulttoenforcethelawindecentralizednetworks. The study puts forward a group of guidelines in policy, law and technology to improve AML compliance in DeFi without hindering its advancements. For example, EU regulators may align theirrulesformemberstates,createbetterframeworksforliabilityofdecentralizedmarketactors, utilizeregtechandencourageteamworkbetweenregulators,technologistsandindustrymembers. Based on the findings, rigid and uncooperative regulations will not only fail to tackle issues in DeFibutalsoslowdowninnovation.Thus,thisarticleoffersideasforfuturediscussionsandrules on safeguarding money matters in the growing world of decentralized finance.
The security testing of Ethereum smart contracts has become increasingly important with the rise of decentralized applications (DApps) and blockchain technology. This systematic literature review (SLR) aims to provide a comprehensive overview of the state-of-the-art techniques, methodologies, tools, and challenges in the security testing of Ethereum smart contracts. By synthesizing and analyzing existing research articles, conference papers, and other relevant sources, this SLR identifies common trends, gaps, and areas for future research in this domain. The review covers various aspects of security testing, including vulnerability detection, testing frameworks, automated analysis tools, and best practices. In addition, it explores the impact of security vulnerabilities on smart contract ecosystems and proposes recommendations to improve the effectiveness and efficiency of security testing processes. This SLR serves as a valuable resource for researchers, practitioners, and developers interested in improving the security and reliability of Ethereum smart contracts.
This study seeks to offer an in-depth examination of cryptocurrency investments through the lens of Islamic law, with particular emphasis on assessing the Shariah compatibility of widely used digital assets such as Bitcoin and Ethereum. The novelty of this research lies in its systematic exploration of key issues such as the speculative nature, intrinsic value, and potential for financial harm (gharar) associated with cryptocurrencies. This study adopts a qualitative approach, drawing upon primary sources of Islamic jurisprudence namely the Quran, Hadith, and classical scholarly interpretations while also incorporating contemporary fatwas, insights from prominent Islamic finance scholars, and expert interviews to inform the analysis. The results highlight divergent viewpoints on the permissibility of cryptocurrency investments, with some scholars asserting their compliance under specific conditions, while others deem them non-compliant due to risks of speculation and uncertainty. The study concludes by proposing a set of actionable guidelines for Muslim investors, underscoring the significance of grasping the intricacies of Shariah principles in cryptocurrency investments and highlighting the necessity for continuous scholarly engagement in this evolving domain.
This paper systematically discusses the core risks (price volatility and market manipulation), investor misunderstanding, lack of regulatory framework and the double-edged effect of technological innovation. Through literature review and policy analysis, a three-dimensional regulatory framework of "risk traceability-technology enabling-cross-national collaboration" is proposed, and its effectiveness is verified based on research data. The study systematically identifies the core risks of digital currencies, including extreme price volatility, market manipulation, investor cognitive biases, regulatory gaps, and the dual-edged nature of technological innovation. Through literature review and policy analysis, a three-dimensional regulatory framework integrating "risk traceability, technology empowerment, and cross-border collaboration" is proposed. Empirical studies demonstrate that this framework significantly enhances regulatory efficiency, particularly in anti-money laundering (AML), privacy protection, and cross-border compliance. Furthermore, the dynamic sandbox regulatory model based on zero-knowledge proofs achieves a balance between fostering innovation in decentralized finance (DeFi) and mitigating systemic risks through algorithmic verification and modular design. The research underscores that investor education and international legal coordination are critical pillars for reducing market risks, while blockchain-related technological innovations require continuous optimization in security and transparency. These findings provide both theoretical and practical foundations for constructing a regulatory paradigm tailored to the unique characteristics of digital currencies.The corresponding sandbox regulatory model is proposed to provide new ideas for the regulatory level. The research results provide a theoretical basis for the optimization of digital currency regulatory policy.
Research Aims: This study aims to examine the influence of narrative, fundamental, and technical analysis on the probability of successful cryptocurrency trading in Indonesia during the 2021-2023 period. The objective is to develop a predictive model that synthesizes all three analyses to improve trading decisions in the context of Indonesia’s volatile cryptocurrency market. Design/methodology/approach: The study adopts a quantitative approach to data collection and analysis, employing statistical models to assess the impact of narrative, fundamental, and technical analysis on cryptocurrency trading success. By integrating these three analytical methods, the research aims to offer a more comprehensive understanding of how each factor contributes to trading decisions and success rates. Research Findings: The results indicate that fundamental analysis made the largest contribution to predicting successful cryptocurrency trading (23.92%), followed by narrative analysis and technical analysis, both contributing 17.94%. Among the variables analyzed, Decentralized Finance (DeFi) and Tokenomic Project were found to have the highest probability of success, at 94.20% and 90.70%, respectively. Theoretical Contribution/Originality: This research contributes to the existing literature by offering a comprehensive framework for improving cryptocurrency trading performance. The study emphasizes the integration of narrative, fundamental, and technical analyses in dealing with high market volatility and inconsistent regulation, providing valuable insights for traders, policymakers, and academic scholars. Keywords: Cryptocurrency, Trading, Narrative Analysis, Fundamental Analysis, Technical Analysis