This study aims to explore the impact of key drivers on the integration of blockchain technology implementation and green innovation practices within green supply chains. This study combines the TOE and TAM frameworks to identify six key driving factors that in the proposed model. A survey was conducted with Vietnamese enterprises, resulting in 328 valid responses from senior managers across various sectors. The PLS-SEM approach was conducted to analyze the relationships between the variables and to gain deeper insights into their interactions. The research findings highlight the significant potential of adopting blockchain and green innovation programs to enhance organizational performance. Six essential factors act as key drivers for implementing these initiatives, exerting a positive influence. Among them, Perceived Usefulness, Organizational Readiness, and Partnerships emerge as the three most influential variables within this research framework. Our research offers several valuable implications, both theoretical and practical. The structural framework model provides empirical evidence demonstrating the feasibility of achieving expected benefits for green supply chains, particularly in emerging economies such as Vietnam. Thus, these results serve as valuable references for senior managers and policy makers.
Blockchain-empowered end-edge collaborative computing is a promising technology for enhancing the timeliness and trustworthiness of Industrial Internet of Things (IIoT). However, integrating task offloading with blockchain consensus inevitably escalates resource consumption across communication, computation, and energy domains. Thus, the joint optimization of task offloading, resource allocation and blockchain consensus is very important for IIoT. This paper studies a general end-edge collaborative computing scenario with multiple end devices and multiple edge servers. We first propose a novel dynamic blockchain (DBC) scheme by developing a dynamic leader election mechanism and designing a dynamic consensus waiting time window. Then, by fully considering the constraints of multi-task size and deadline, communication bandwidth, computing frequency, battery capacity, Byzantine fault tolerant and trustworthiness, we formulate the trustworthy processing efficiency (TPE) maximization problem with respect to end-edge task division, communication and computation resource allocation, leader election and consensus waiting window. To address this problem, we transform it into a Markov decision process and design a compound reward by fully considering the penalty for computing timeout and consensus failure. After that, we propose a rotating multi-agent deep reinforcement learning (R-MADRL) algorithm tailored to the proposed DBC scheme, where an entropy-based dual-critic DRL algorithm is proposed for rotating multi-agent training and decentralized execution. Extensive experiments validate the effectiveness and superiority of the proposed DBC with R-MADRL, where three benchmark DRL algorithms and three blockchain consensus schemes are compared. The results demonstrate that R-MADRL achieves stable convergence with more than 60.32% TPE reward than other algorithms while the task timeout ratio of DBC is reduced by more than 66.49% compared with other schemes.
As consumer demand for eco-friendly products continues to grow, manufacturers are increasingly driven to enhance product greenness and disclose this information. Blockchain technology emerges as a pivotal enabler, facilitating credible communication of manufacturers’ sustainability efforts to consumers through retail platforms and influencing supply chain decisions concerning sustainability, pricing , and blockchain adoption. While existing research has extensively examined the positive moderating effect of blockchain technology on consumers’ perceived value of product greenness in retail competition or green supply chain contexts, there remains a significant gap regarding its cross-channel influence in situations of information disclosure asymmetry across retail platforms. To address this gap, we investigate the interactive dynamics of a green supply chain under asymmetric platform competition, where the incumbent platform offers blockchain services while the new platform does not. Our findings indicate that the manufacturer’s decision to adopt blockchain depends significantly on market conditions. Notably, the manufacturer’s inclination towards blockchain adoption widens for a broader range of blockchain costs when the cross-channel influence is pronounced. Moreover, the alignment of the manufacturer’s blockchain adoption strategy with the incumbent platform’s preference is not guaranteed. In scenarios where their interests diverge, joint efforts to reduce blockchain costs can be a viable strategy. Our parametric analysis further reveals that while the cross-channel influence contributes positively to enhancing product greenness and the manufacturer’s profit, it could diminish the profits of both platforms under certain conditions.
The metaverse has gradually come into the public eye and has become a hotspot in cyberspace, but it still faces many technical difficulties to be solved. Blockchain is a key component of the metaverse, enhancing the development of the metaverse by connecting the real and virtual worlds seamlessly and solving some of the difficulties faced by the metaverse. Our paper comprehensively studies the development and application of blockchain technology in the metaverse. First, there is an introduction to blockchain and the metaverse, followed by a discussion of why blockchain should be integrated into the metaverse. Second, an overview of the main blockchain technologies is provided to evaluate blockchain's role in the metaverse and the value is summarized. Third, the development of future integration of blockchain and metaverse is presented from the perspective of social life and technology. For social life, how to use blockchain in the metaverse to enhance and improve social life is discussed. Then, from the technical perspective, it discusses how blockchain shapes the metaverse. Finally, challenges associated with the integration of blockchain into metaverses are analyzed and some promising research directions and solutions are proposed.
This article explores blockchain technology's transformative role in ensuring data integrity and security across modern enterprise systems. The article examines the fundamental architecture of blockchain security, emphasizing distributed ledger technology, consensus mechanisms, and cryptographic foundations that collectively create an immutable and transparent system. The article investigation delves into core security features, including the implementation of advanced cryptographic techniques, decentralization strategies, and innovative security protocols that protect against various cyber threats. Through detailed analysis of industry applications, the article demonstrates blockchain's impact across financial services, supply chain management, healthcare, and IoT sectors, highlighting significant improvements in operational efficiency, security, and cost reduction. The article further evaluates implementation benefits, encompassing operational advantages, economic impacts, and technical improvements that organizations experience through blockchain adoption. Finally, the article addresses future implications and challenges, including technology integration hurdles, regulatory considerations, and scalability solutions, providing insights into the evolving landscape of enterprise blockchain implementation.
This comprehensive article explores the transformative impact of blockchain technology on energy trading risk management systems. The article examines how blockchain addresses critical challenges in data security, transparency, and regulatory compliance within the energy sector. Through detailed analysis of distributed ledger infrastructure, smart contract integration, and cryptographic security measures, the research demonstrates significant improvements in operational efficiency, transaction processing, and risk mitigation. The investigation encompasses automated compliance frameworks, data privacy mechanisms, and scalability solutions, highlighting how blockchain technology enhances market participation while reducing operational costs. The article also evaluates emerging technologies and industry standards, providing insights into future developments that will shape secure and efficient energy trading operations.
With the wide application of electric vehicles, smart robots and Internet of Things (IoT) devices, efficient scheduling of mobile charging systems has become an important research direction in smart energy management. However, the traditional cloud computing architecture is difficult to meet the requirements of low latency, high reliability and privacy protection, and the existing scheduling strategies still have challenges in terms of energy optimization, task balancing and dynamic adaptability. To this end, this paper proposes an intelligent mobile charging scheduling method that integrates edge computing and biomechanical modeling, constructs a biomechanical-based charging demand modeling and energy consumption analysis framework, and combines bionic optimization algorithms to achieve efficient path planning. Meanwhile, an edge computing architecture is adopted to optimize resource scheduling, and a federated learning mechanism is designed to enhance cross-domain data processing capability. To safeguard user privacy, a multi-level privacy protection mechanism is proposed, combining differential privacy, homomorphic encryption and zero-knowledge proof to ensure data security. Experimental results show that the method outperforms traditional methods in terms of task response time, energy consumption optimization, load balancing and privacy security, and can significantly improve the charging scheduling efficiency and provide effective technical support for large-scale distributed charging networks. The research results provide a theoretical basis and engineering practice reference for the application of smart charging networks, edge intelligent computing and privacy protection technology.
Blockchain is a decentralized, distributed, immutable ledger technology introduced in the late 1900s and got attention as the enabling mechanism for operating cryptocurrency transactions. Being a strong network, decentralized, immutable and almost impossible to be hacked, blockchain is the desired solution for transparency and digital security. Having multiple use cases across multiple domains, blockchain is the technology which has the potential to change the way we think of security and trust. In the last decade, the world also experienced a massive growth in the education sector with the introduction of education technology. The covid-19 pandemic forced lockdown influenced the growth of education technology. Businesses and governments experienced massive growth in the education sector globally. Incorporation of technology into education started from teaching and learning on videos calls and is now grown enough to involve artificial intelligence and machine learning. This advancement in the education industry enabled the facilities and growth but at the same time introduced new challenges and threats. The incorporation of technology also brings the threat of security, both cyber and ethical. Students and their details are exposed online, and this makes them sensitive towards cyber threats. Not only students but all the stakeholders exposed online are also sensitive towards cyber-attacks. These challenges in the education sector need to be addressed and solved. Researchers and scientists have found blockchain to be a potential solution to the challenges present in the education sector today. This paper presents a systematic review on the education technology and the potential of blockchain technology in solving the current issues in the education sector introduced through the incorporation of education technology in the last 5 years. Along with presenting the review, this paper also proposes a novel architecture of a learning management system based on blockchain and knowledge graph. The data sources explored to collect the studies for this systematic review are Complementary Index, Business Source Ultimate, eBook Index, Springer, IEEE Xplore and more. A sum of 15,855 studies were explored and screened to find a total of around 60 studies and reports to be included in this review paper. The complete process of identification, screening and selecting was a 5-step process and was done according to the PRISMA layout. The complete study is presented according to the PRISMA checklist and aims to present a clear and concise view of the current state-of-art of blockchain in education.
Propósito. Las compraventas requieren el cumplimiento de una solemnidad para su perfeccionamiento, como lo contempla el literal segundo del artículo 1857 del Código Civil. En contraste, la promesa de compraventa, si exige una solemnidad, aunque más flexible, según lo establece el numeral primero del artículo 1611 del mismo código, ya que solo se exige literalidad. Esta última será objeto de la investigación, pues puede reproducirse en un smart contract. No se trata únicamente de transcribir una promesa en un ordenador, si no que va más allá, aplicando el sistema descentralizado del Blockchain; que permite igualmente la descentralización de la información, creando así un “BackUp” automático de los metadatos que ingresemos. Metodología: Inductiva – Cualitativa de Derecho Comparado. Resultados: Colombia posee un gran potencial jurídico en tecnología e innovación, como lo demuestra su historial normativo. Desde hace décadas, leyes como la 270 de 1996 y la 527 de 1999 han sido pilares fundamentales en la construcción de una Colombia digital. Sin embargo, no fue sino hasta la llegada de una pandemia mundial que se permitió la realización de negocios, contratos y trámites judiciales a través de las nuevas tecnologías. Aún más relevante, este contexto impulsó la creación de nuevos despachos y oficinas orientados a la innovación y la integración tecnológica en la vida cotidiana del país. Conclusiones: Al automatizar las obligaciones contenidas en una promesa de compraventa, disminuiremos los riesgos de posibles errores o delitos en los contratos. Asimismo, se evitan equivocaciones involuntarias que podrían surgir en estos acuerdos.
The articles and opinions of GRUR International have frequently engaged with some of the leading issues that our legal systems are grappling with, two of which I want to explore in this short editorial focusing on the path travelled and the challenges ahead from an IP and competition law perspective. These are (possibly unsurprisingly) sustainability – including climate change – and digital and AI developments. The first part will briefly review how the two areas of law have interacted with these issues. The second part will focus on how the new era of polarisation, de-globalisation, protectionism, and nationalism, which has now been firmly ushered in with the re-election of Donald Trump in the US, will affect law and policy in these fields. It seems beyond doubt that sustainability and climate change, along with the developments around digitalisation and algorithms/AI, are among the most critical issues of our time. When exploring the issue of sustainability and especially climate, we can focus in particular on IP laws and competition laws, as each of these areas has started to grapple with specific challenges and made some progress. In the field of IP law, the role of IP and how it can foster sustainable technologies and other green innovation has become a focus of the debate. With its traditional focus, IP law has been designed with innovation incentives in mind by providing innovators with exclusive rights to their creations. This function is crucial in the green transition. The IP law framework can effectively be used in more or less unadulterated form to foster green innovation. However, given the need to rapidly scale and diffuse green technologies, a close eye needs to be kept on dissemination and in particular incentives for and costs of the dissemination of green technologies. For instance, patents related to renewable energy technologies, such as wind, solar, and bioenergy, have substantially increased over the last decade. Yet, the roll-out of these technologies on a global scale is something that deserves attention so as to ensure that they are accessible in developing nations. We have seen work in this area that has led to new proposals and the adoption of mechanisms for compulsory licensing, patent pools, and technology transfer, with WIPO’s ‘Green Platform’ being just one example in the area. Competition laws have also started to play a role in this area. Some EU Member States (and the EU itself), but equally other jurisdictions from Singapore to New Zealand, have been at the forefront, aiming to provide businesses with individual guidance and publishing general guidelines on how business activities fostering sustainability interact with competition laws. Similarly, we have seen first cases in Europe in which competition agencies pursued companies that have been restricting competition, thereby harming sustainability. For example, the European Commission pursued car makers in the AdBlue case for restricting innovation competition around better emission cleaning technologies. In some jurisdictions where there are rules on superior bargaining power, these might equally be used to foster different aspects of sustainability, ensuring that the weakest players in the market are not exploited by, e.g. powerful retailers. Overall, while (too) much still needs to be done in terms of sustainability and the climate, the fields of law covered by GRUR International have developed and adjusted their tools to play a role in addressing these challenges. The digital and AI fields are equally fields of global relevance in which we witness numerous challenges within existing legal frameworks, and GRUR International has featured many of them over the years. The role of IP has already been at the forefront of the digital transformation with questions around protection in the digital world. Yet, new frontiers are already emerging as complex questions around creations by and the creativity of AI become apparent. What protections are afforded where AI systems are trained on human-created material? How should creations made by, through or with the essential help of AI be treated? Questions around creation and inventions and subsequent ownership are crucial. How should the ownership of AI-generated art and inventions by AI be treated in applications for patents? We are seeing first attempts to regulate the space, such as the US Copyright Office’s decisions on AI-generated works. The blockchain space raises additional questions, particularly regarding digital ownership and copyright in the context of Non-Fungible Tokens (NFTs). Competition law has also seen an evolution, with questions about tech giants and the interaction with data and data protection laws becoming competition concerns. The adoption of the European Union’s Digital Markets Act (DMA) with the aim of protecting fair and contestable markets is a prime example. Other jurisdictions have also opted for the adoption of new regulatory tools that address digital markets with monopolistic tendencies. The algorithm and AI revolution further challenges the competition law framework. We have already seen a wide ranging discussion about algorithmic and AI collusion, and we are witnessing an emerging debate around abuses, market concentration and its effects in the AI domain and its AI stack, and a focus on the control of the digital value chain. The protection of innovation is a core theme in these debates. Overall, as digital and AI advances continue to transform our world, the legal frameworks have developed and will continue to have to develop to adjust to the emerging challenges, whether or not in the area of IP and competition rules. It might not be surprising that the recent years are described as a decade of increased global polarisation. Deepening social and political divides are visible all over the globe, and social media have certainly not been a moderating influence. The latest sign is the re-election of Donald Trump in the US, whose new administration is expected to push further in the direction of de-globalization. It is not farfetched to predict that the coming years will be a time characterized by even more protectionism and nationalism disrupting established global cooperation and trade. In other words, de-globalization will accelerate, thereby possibly increasing economic uncertainty and straining international relations. But what does this spell for the challenges in the sustainability and digital and AI areas discussed above? For sustainability, the new era of protectionism will have familiar consequences. On the one hand we might see a slowing of the pace of green transition and green innovation. While tariffs and other trade barriers could increase the costs for the adoption and development of green technology (e.g. rare earth minerals), the effects on green innovation work in a less direct way. On the one hand, the dissemination of green IP could be restricted due to nationalism in the form of national security restrictions. On the other hand, we might see IP law being used to protect domestic producers while harassing foreign producers and using alleged IP violations in trade disputes. In competition law, we might observe a reversal of the move towards a global consensus that competition and companies can play a role in sustainability matters. In fact, we might see the ‘anti-woke’ capitalist backlash building up steam, with antitrust rules used to harass companies that engage in ESG related matters. In other words, we could see more actions like that recently by Republican attorney generals in the US against financial investors and their climate-related actions in the coal industry. Whether such actions will ultimately be successful in court is a different question, but they might well sow doubt on the legality of corporate sustainability initiatives. This contrasts sharply with the legal certainty that many competition agencies have tried to provide to companies, and might hamper the latter’s global actions. Another avenue that might affect sustainability is national security concerns, in particular in mergers related to technology crucial for the green transition. For the digital space including algorithms and AI, the new era of protectionism will have some substantial effects. The area of digitalisation and AI is one that seems intrinsically linked to trade and competition between countries. Many countries identify this area as one of national strategic interest. The interaction between national security concerns and IP may become a crucial battleground that allows states to exclude foreign companies from any new and developing technology. Similarly, IP laws could be the tool of choice to pursue foreign companies in the digital and AI area. In the competition-law field, protectionism and nationalism might have two distinct effects. On the one hand, less harsh enforcement against dominant domestic companies, since dominant companies in the digital sphere are seen as a strategic and national security asset. At the same time, any antitrust action or regulatory action (such as e.g. the DMA) by foreign authorities against domestic tech companies will be seen as hostile and might be answered with trade retaliation. On the other hand, foreign tech companies will be seen as suspicious and worthy of antitrust scrutiny. Similarly, any merger of domestic and foreign companies in the tech area will likely face increased scrutiny. Overall, it is not without irony that the issues we are facing are becoming more globalized than ever, while de-globalisation takes hold. We can expect more heterogeneity or often even opposing approaches to the same (global) problems. Problem-solving within established (multilateral and multinational) institutions will become more difficult and possibly less influential. As a reaction, we might see a move away from formal to informal or even private cross-boundary networks for addressing global issues. For example, private standard setting organisations could gain an even greater role in addressing such issues. Yet, where such organisations face challenges, including open hostility, even such avenues for co-operation will become more difficult to maintain. In these situations, the individual legal comparativist will have an increasingly important role to play and, with it, outlets like GRUR International. The study of other systems and their solutions to problems can provide crucial insights and could be the main avenue for more global approaches to the challenges discussed here. In a de-globalized world where foreign and international measures are seen with suspicion, the comparativist has a new role. The internal critique of the existing national approach by the comparativist can be an argument for internally introduced change; the only kind of change perceived as legitimate in a de-globalized, nationalistic world.
This paper aims to assess the current state of research landscape of the role of FinTech in the digitalization of financial services through a bibliometric analysis using scientometric software (VosViewer). We analyzed a dataset of 585 documents as indexed by Scopus, published between 2015 and 2025 to generate network maps and identify emerging trends in the field. The bibliometric analysis delves into various key areas within financial services, including digital transformation, decentralized finance, artificial intelligence, and blockchain technology. The results revealed a notable rise in the publication volume throughout the years, reflecting the role of modern technologies in transforming financial systems and enhancing user experiences. Geographically, certain countries represent the highest number of publications in the field of FinTech and the digitalization of financial services such as India, China and the United States. These findings provide a foundation for researchers to foster blockchain, artificial intelligence, and decentralized finance, to drive the development and transformation of financial services.
The identification of vulnerabilities in smart contracts is necessary for ensuring their security. As a pre-trained language model, BERT has been employed in the detection of smart contract vulnerabilities, exhibiting high accuracy in tasks. However, it has certain limitations. Existing methods solely depend on features extracted from the final layer, thereby disregarding the potential contribution of features from other layers. To address these issues, this paper proposes a novel method, which is named multi-layer feature fusion (MULF). Experiments investigate the impact of utilizing features from other layers on performance improvement. To the best of our knowledge, this is the first instance of multi-layer feature sequence fusion in the field of smart contract vulnerability detection. Furthermore, there is a special type of patched contract code that contains vulnerability features which need to be studied. Therefore, to overcome the challenges posed by limited smart contract vulnerability datasets and high false positive rates, we introduce a data augmentation technique that incorporates function feature screening with those special smart contracts into the training set. To date, this method has not been reported in the literature. The experimental results demonstrate that the MULF model significantly enhances the performance of smart contract vulnerability identification compared to other models. The MULF model achieved accuracies of 98.95% for reentrancy vulnerabilities, 96.27% for timestamp dependency vulnerabilities, and 87.40% for overflow vulnerabilities, which are significantly higher than those achieved by existing methods.
As 6G networks evolve, inter-provider agreements become crucial for dynamic resource sharing and network slicing across multiple domains, requiring on-demand capacity provisioning while enabling trustworthy interaction among diverse operators. To address these challenges, we propose a blockchain-based Decentralized Application (DApp) on Ethereum that introduces four smart contracts, organized into a Preliminary Agreement Phase and an Enforcement Phase, and measures their gas usage, thereby establishing an open marketplace where service providers can list, lease, and enforce resource sharing. We present an empirical evaluation of how gas price, block size, and transaction count affect transaction processing time on the live Sepolia Ethereum testnet in a realistic setting, focusing on these distinct smart-contract phases with varying computational complexities. We first examine transaction latency as the number of users (batch size) increases, observing median latencies from 12.5 s to 23.9 s in the Preliminary Agreement Phase and 10.9 s to 24.7 s in the Enforcement Phase. Building on these initial measurements, we perform a comprehensive Kruskal-Wallis test (p < 0.001) to compare latency distributions across quintiles of gas price, block size, and transaction count. The post-hoc analyses reveal that high-volume blocks overshadow fee variations when transaction logic is more complex (effect sizes up to 0.43), whereas gas price exerts a stronger influence when the computation is lighter (effect sizes up to 0.36). Overall, 86% of transactions finalize within 30 seconds, underscoring that while designing decentralized applications, there must be a balance between contract complexity and fee strategies. The implementation of this work is publicly accessible online.
Abstract Frequent, large-scale wildfires threaten ecosystems and human livelihoods globally. To effectively quantify and attribute the antecedent conditions for wildfires, a thorough understanding of Earth system dynamics is imperative. In response, we introduce the SeasFire datacube, a meticulously curated spatiotemporal dataset tailored for global sub-seasonal to seasonal wildfire modeling via Earth observation. The SeasFire datacube consists of 59 variables including climate, vegetation, oceanic indices, and human factors. It offers 8-day temporal resolution, 0.25° spatial resolution, and covers the period from 2001 to 2021. We showcase the versatility of SeasFire for exploring the variability and seasonality of wildfire drivers, modeling causal links between ocean-climate teleconnections and wildfires, and predicting sub-seasonal wildfire patterns across multiple timescales with a Deep Learning model. We have publicly released the SeasFire datacube and appeal to Earth system scientists and Machine Learning practitioners to use it for an improved understanding and anticipation of wildfires.
The agricultural supply chain plays a crucial role in ensuring food security and sustainability. However, traditional supply chains face challenges such as lack of transparency, inefficiencies, and limited traceability, leading to fraud, food wastage, and delays. Blockchain technology has emerged as a promising solution to address these issues by providing a decentralized, immutable, and transparent ledger system. This paper explores the key attributes essential for an efficient agricultural supply chain, such as traceability, transparency, data integrity, and operational efficiency. A comprehensive survey of existing research is conducted to analyze blockchain-based solutions implemented in the agriculture sector. Various techniques, including different consensus mechanisms (such as Proof-of-Work, Proof-of-Stake, and PBFT), smart contract applications, and scalability solutions, are compared based on performance, cost, and adoption challenges. Despite its potential, blockchain faces limitations such as high transaction costs, interoperability issues, and resistance to adoption by stakeholders. Identifying these research gaps helps in refining future studies to develop a more effective and scalable blockchain framework for agricultural supply chains. This paper presents a novel perspective on blockchain-driven supply chain frameworks, highlighting their role in optimizing logistics, reducing fraud, and ensuring sustainability in global commerce. The future of blockchain-based supply chain management lies in its integration with emerging technologies such as Artificial Intelligence (AI), Internet of Things (IoT), and Big Data analytics. AI-powered analytics can enhance predictive decision-making, while IoT sensors can provide real-time monitoring of goods, improving accuracy and efficiency.
This Blockchain technology has revolutionized various industries by offering decentralized, secure, and immutable record-keeping. However, its adoption faces challenges such as scalability, energy consumption, and interoperability. As blockchain continues to evolve, researchers and developers have been working on innovative solutions to address these limitations and expand its practical applications. This paper explores recent advancements aimed at enhancing blockchain technology, focusing on key areas such as scalability solutions, energy-efficient consensus mechanisms, and interoperability protocols. It delves into techniques like sharding, Layer 2 solutions, and optimized consensus algorithms that improve transaction speed and reduce congestion. Additionally, it examines alternative consensus mechanisms like Proof-of-Stake (PoS) and Proof-of-Authority (PoA), which offer sustainability and efficiency without compromising security. Furthermore, the paper investigates interoperability solutions that enable seamless data exchange between different blockchain networks, such as atomic swaps, cross-chain communication protocols, and blockchain bridges. The study also highlights emerging trends that are set to shape the future of blockchain, including quantum-resistant cryptography, AI integration, Zero-Knowledge Proofs (ZKPs), and Blockchain-as-a-Service (BaaS). By addressing these enhancements, blockchain technology can achieve greater adoption, enabling new opportunities across various industries such as finance, supply chain, healthcare, governance, and IoT. The paper concludes with an analysis of the broader impact of blockchain innovations, emphasizing the need for continuous research and development to overcome existing barriers and unlock its full potential in modern digital infrastructure.
This paper first documents a novel herding for Altcoin, i.e., herding towards Bitcoin. Besides, constructing the proxies for flight to Bitcoin (in)attention with Google Trends and Twitter, the results reveal that flight to Bitcoin inattention strengthens the herding and flight to Bitcoin attention attenuates the herding. Subperiod analysis further reveals that the finding is more pronounced during the period before the introduction of Bitcoin futures, and the period before the outbreak of COVID-19.
This article conducts a comprehensive bibliometric analysis of 182 papers to trace the progression of research on cryptocurrency taxation. The study highlights prevailing patterns, influential contributors, and collaborative networks by utilising data from Scopus and the Web of Science Core Collection from 2002 to 2023. The findings underscore an interdisciplinary character, encompassing studies in legal frameworks, fiscal policy, economics, and technology. By employing analytical tools such as VOSviewer 1.6.20, Bibliometrix 4.0 and Microsoft Excel, the study identifies key themes and concepts focused on four main themes: international tax frameworks and regulatory variations, classification and reporting of crypto-related income, tax implications for emerging crypto segments, and issues surrounding compliance and enforcement. Tax treatment differs based on jurisdiction. Direct taxation may be levied as capital gains, income, or profit tax. Although cryptocurrency exchanges are not subject to value-added tax, intermediary services offered by platforms might incur this indirect tax. The insights generated are valuable for policymakers, scholars, and professionals aiming to comprehend the relationship between cryptocurrency and tax regulation. A limitation of the study is its exclusion of sources beyond the established timeframe. Given the fast-paced changes in cryptocurrency tax regulation, ongoing updates are crucial to capturing the full scope of this evolving field.
Until recently, digital art was perceived as something of secondary value compared to the physical artistic artifacts. One of the reasons for that being its predisposition for duplication and hence the inability to assign “original artwork” label to the digital file and represent it as a unique object on artistic market. But the rapid pace of popularization of blockchain technologies in creative communities through the use of Non-Fungible Tokens has a seeming potential to change the perception of digital art. The ERC721 standard sets a precedent for authentication and traceability of digital artworks suggesting that the old paradigm might shift, and digital art will gain value and attention comparable with traditional fine art. In this article we discuss the problematics of digital art representation on art market and the issue of digital creations’ pricing. We use photo stocks and print-on-demand platforms as an example for pre-NFTs digital art monetization. We then discuss the changes caused by Non-Fungible Token blockchain technology in the digital art market in recent years and the implications that come with the change. We then illustrate theoretical tenets with expert interview that suggest that while successful NFT projects offers publicity and profit to the creators, the level of complexity and unpredictability of results sets a high bar for entering the market.
Abstract This study investigates the digital transformation trends in the Korean fashion industry over the past decade, focusing on business models, processes, services, products, and customers. Using bibliometric and big data analyses, we examined articles from journals listed on the Korea Citation Index (KCI) from 2014 to 2023. It was revealed that the five factors are not independent but are complementary and interconnected. Keyword frequency and network analysis revealed key themes, including the increasing influence of the metaverse on business models and the significance of “recognition” in digital processes for fashion practitioners and designers. “Hanbok,” “Non-Fungible Token,” “Virtual Reality,” and “experience” were notable in services, while “COVID-19” and “3D” emerge as central product discussions. Consumer discussions highlighted “Millennials and generation Z,” “experience,” and “value.” This study provides a comprehensive overview of digital technologies in fashion, offering insights into current trends and future directions. It contributes to the theoretical understanding of digital transformation in fashion and offers practical guidance for industry professionals.
Open access
Consumer Perception and Purchasing Behavior
Consumer Behavior in Brand Consumption and Identification
Abstract Pricing dynamics and volatility are accelerating the adoption of global cryptocurrency. Despite challenges, cryptocurrencies such as Bitcoin are gaining widespread acceptance, particularly in countries with unbanked populations, the lack of bank controls, and inflation. This study investigates the global patterns of cryptocurrency adoption using Generalized Linear Models and Spatial Autoregressive Models. This research introduces a novel perspective on global cryptocurrency adoption using spatial models. Our findings reveal that cryptocurrency adoption is significantly influenced by economic instability, infrastructure availability, and spatial dynamics, with higher adoption rates in countries with limited access to traditional financial systems.
The fast development and growth of blockchain technology and cryptocurrencies, but most importantly, the fast diffusion of Ethereum, opened new chances for financial innovation but aggravated the risks of illegal activities such as money laundering. This paper discusses using machine learning techniques to detect illegal transactions over the Ethereum network. The dataset used is from Kaggle and includes a record of transaction features between Ethereum accounts; it has a high degree of class imbalance. Three machine learning models were used to classify transaction legality: Logistic Regression, Random Forest, and Extreme Gradient Boosting; this is referred to as XGBoost. Class balancing and data preprocessing are ways to improve model performance. The evaluation metrics were chosen as Accuracy and Area Under the Receiver Operating Characteristic Curve (ROC AUC). Experimental results show that the best performance of the XGBoost model was 98.52% in accuracy, while Random Forest was the best on ROC AUC, showing very strong classification capabilities. This work has shown the potentiality of machine learning in the improvement of blockchain security and provided useful lessons that might be applied to the development of scalable AML systems.
We construct liquidity-adjusted return and volatility using purposely designed liquidity metrics (liquidity jump and liquidity diffusion) that incorporate additional liquidity information. Based on these measures, we introduce a liquidity-adjusted ARMA-GARCH framework to address the limitations of traditional ARMA-GARCH models, which are not effectively in modeling illiquid assets with high liquidity variability, such as cryptocurrencies. We demonstrate that the liquidity-adjusted model improves model fit for cryptocurrencies, with greater volatility sensitivity to past shocks and reduced volatility persistence of erratic past volatility. Our model is validated by the empirical evidence that the liquidity-adjusted mean-variance (LAMV) portfolios outperform the traditional mean-variance (TMV) portfolios.