• Agent-based modeling can be used to study the sociotechnical dynamics associated with technology implementation. • Ethereum’s ERC-721protocol can be leveraged to facilitate reducing the prevalence of counterfeit electronic parts. • Widespread adoption of blockchain is required to reduce the flow of counterfeit electronic parts. • Adoption is sensitive to the direct and indirect cost associated with blockchain implementation. • Integerating blockchain with business practice verification can reduces its cost, leading to an increase in adoption. Safety-critical, mission-critical, and infrastructure-critical systems (e.g., aerospace, transportation, defense, and power generation) are forced to source parts over exceptionally long periods of time from a supply chain that they do not control. Such systems are exposed to the dual risks of the impacts of system failure and the exposure to an unauthorized electronics marketplace over decades. Therefore, critical systems operators, manufacturers, and sustainers, must implement policies and technologies to reduce the risk of obtaining counterfeit parts. Blockchain technology, as a distributed ledger platform, has shown promise for resolving the issues associated with a lack of trust, transparency in peer-to-peer transactional networks, and compromised supply chains. There are opportunities to apply blockchain for supply chain concepts to mitigate the risks associated with part authenticity in the electronic part supply chain. This paper introduces a supply-chain blockchain framework resilient to aging (e.g., the loss of involvement of the original component manufacture and its authorized distributors, and loss of part transaction history). An agent-based model is introduced as a novel platform to test the impact of the proposed blockchain framework on supply-chain parties as well as the prevalence of counterfeits in the electronics supply chain. The model can validate the proposed protocol over the entire life cycle of a part (i.e., from active production to discontinuance and beyond) and predict the parties’ adoption rates, and changes in the prevalence of counterfeit parts. Application of the model to a public participation blockchain based on Ethereum ERC- 721 protocols indicates that the participation level of independent distributors directly affects the efficacy of blockchain in the prevention of transactions containing counterfeit parts. A proposed certification-based blockchain participation approach can be effective if certifications require large enough test accuracy limits and high previous owner certification thresholds.
Muhammad Firdaus, Harashta Tatimma Larasati, Kyung Hyune-Rhee
Healthcare data is often fragmented across various institutions due to its highly sensitive and private nature. In this sense, hospitals and clinics maintain electronic health records (EHRs) independently; hence, valuable data is siloed within individual organizations, preventing comprehensive analysis that could benefit from diverse data sources. Federated learning (FL) addresses these challenges by enabling the training of a shared global model using data distributed across multiple institutions without moving the data from its source. By leveraging FL, healthcare institutions can combine their data assets to improve predictive analytics, personalized medicine, and overall healthcare outcomes, ultimately benefiting patients and the healthcare system. However, the current FL model with a central server presents several challenges within healthcare, including the risk of malicious attacks, regulatory compliance, and privacy vulnerabilities. To overcome these issues, this paper introduces the FL framework with blockchain and homomorphic encryption (HE). Our framework aims to minimize the role of the central server, enable collaborative model training across healthcare organizations, and enhance data security and privacy. In this sense, blockchain ensures the integrity and transparency of the process, while homomorphic encryption ensures that the data remains private. This framework can potentially enable institutions to enrich medical knowledge while securely keeping patient data collaboratively and facilitating healthcare analytics in practical settings.
Financial data analytics has become a critical tool for businesses seeking to drive growth, enhance fraud prevention, and mitigate risks in dynamic markets. By leveraging large datasets, advanced algorithms, and real-time analytics, organizations can make more informed financial decisions, improve operational efficiency, and enhance compliance with regulatory frameworks. This review explores how financial data analytics contributes to business growth by improving revenue forecasting, identifying market trends, and optimizing financial planning. Companies can leverage predictive models and artificial intelligence to gain competitive advantages through better risk assessment and investment decision-making. Fraud prevention is another key area where financial data analytics plays a transformative role. Machine learning algorithms, anomaly detection systems, and real-time transaction monitoring help identify and prevent fraudulent activities before they cause significant financial losses. Businesses and financial institutions can use automated risk-scoring models to strengthen security in banking, payments, and investment transactions. Risk mitigation in financial markets is also enhanced through data analytics. By employing predictive modeling, scenario analysis, and stress testing, businesses can assess potential market fluctuations and develop strategies to minimize financial exposure. Moreover, analytics-driven regulatory compliance mechanisms improve transparency and reporting, ensuring adherence to legal and industry standards. Despite its advantages, financial data analytics faces challenges such as data privacy concerns, integration with legacy systems, and the need for skilled professionals. However, emerging technologies, including blockchain, AI, and decentralized finance (DeFi), present new opportunities for strengthening financial security and business resilience. This review concludes that financial data analytics is a vital asset for modern businesses, offering strategic insights that drive profitability, enhance fraud detection, and strengthen risk management. Companies must continue to invest in data-driven solutions to stay competitive in an increasingly digital financial landscape. Keywords: Financial data, Business growth, Fraud prevention, Markets.
Abstract The convergence of artificial intelligence (AI) and blockchain technology is transforming the creative economy by enabling secure, transparent, and decentralized innovation in digital content creation, intellectual property management, and monetization. Traditional creative industries are often constrained by centralized platforms, opaque copyright enforcement, and unfair revenue distribution, which limit the autonomy and financial benefits of creators. By leveraging blockchain’s immutable ledger, smart contracts, and non-fungible tokens (NFTs), digital assets can be authenticated, tokenized, and securely traded, ensuring ownership verification and automated royalty distribution. Simultaneously, AI-driven tools such as generative adversarial networks (GANs), neural networks, and natural language processing (NLP) models facilitate content generation, curation, and adaptive recommendations, enhancing creative workflows and fostering new artistic possibilities. This research report explores the synergies between AI and blockchain in the decentralized creative economy, analyzing their impact on digital rights protection, NFT marketplaces, decentralized publishing, AI-assisted music composition, and smart licensing models. Furthermore, it examines regulatory challenges, ethical considerations, and scalability limitations that need to be addressed for mainstream adoption. By integrating AI-powered automation with blockchain’s decentralized infrastructure, this study outlines a sustainable roadmap for secure, fair, and transparent digital creativity in the Web3 era. Keywords AI-powered creativity, blockchain-based digital ownership, decentralized innovation, generative AI, smart contracts, non-fungible tokens (NFTs), digital content authentication, AI-driven content generation, decentralized autonomous organizations (DAOs), intellectual property management, AI in art and music, Web3 creativity, tokenized digital assets, secure content monetization, ethical AI in blockchain, AI-assisted copyright protection, decentralized publishing, AI-powered music composition, blockchain scalability, AI for digital rights management.
Paula Ungureanu, Francesca Bellesia, Carlotta Cochis
This study investigates an emblematic case of innovation failure in blockchains as to understand how turbulent episodes of innovation failure shape the socio-technical organization of digital ecosystems. The Decentralized Autonomous Organization ( The DAO ) was an alternative model of organizational governance based on the Ethereum blockchain which registered one of the biggest successes in crowdfunding history and fell victim to one of the biggest hacks of the crypto world. Our empirical qualitative study combines interviews, archival and social media data to develop a grounded theory on how innovation failure was framed and dealt with in the Ethereum ecosystem. Our findings highlight the key role of blaming processes following innovation failures in digital ecosystems. Building on blame theory, we theorize about the interplay between human and technological blaming, and document a process called multi-distributed blaming whereby actors circle between multiple blames to an ecosystem's human and technological components, with multi-level (i.e., organizational and technological) consequences for the ecosystem. By adopting a socio-technical perspective, our findings contribute to blame theories, to the literature on digital ecosystems and to the scant research on blockchain organization. • We study The DAO blockchain experiment as a case of failure in digital ecosystems • We show the interplay between organizational and technological ecosystems’ elements • We introduce a multi-distributed blaming process in complex digital ecosystems • We show how blaming processes shape the consequences of an innovation failure • We show the consequences for the ecosystem’s organizational and technological players
Ebtihal Abdulrahman, Suhair Alshehri, Ali Alzubaidy, Asma Cherif
Recently, the Internet of Things (IoT) environment has become increasingly fertile for malicious users to break the security and privacy of IoT users. Access control is a paramount necessity to forestall illicit access. Traditional access control mechanisms are designed and managed in a centralized manner, thus rendering them unfit for decentralized IoT systems. To address the distributed IoT environment, blockchain is viewed as a promising decentralised data management technology. In this thesis, we investigate the state-of-art works in the domain of distributed blockchain-based access control. We establish the most important requirements and assess related works against them. We propose a Distributed Blockchain and Attribute-based Access Control model for IoT entitled (DBC-ABAC) that merges blockchain technology with the attribute-based access control model. A proof-of-concept implementation is presented using Hyperledger Fabric. To validate performance, we experimentally evaluate and compare our work with other recent works using Hyperledger Caliper tool. Results indicate that the proposed model surpasses other works in terms of latency and throughput with considerable efficiency.
Robert Ghrist, Julian Gould, Miguel Lopez, Hans Riess
Modern financial networks involve complex obligations that transcend simple monetary debts: multiple currencies, prioritized claims, supply chain dependencies, and more. We present a mathematical framework that unifies and extends these scenarios by recasting the classical Eisenberg-Noe model of financial clearing in terms of lattice liability networks. Each node in the network carries a complete lattice of possible states, while edges encode nominal liabilities. Our framework generalizes the scalar-valued clearing vectors of the classical model to lattice-valued clearing sections, preserving the elegant fixed-point structure while dramatically expanding its descriptive power. Our main theorem establishes that such networks possess clearing sections that themselves form a complete lattice under the product order. This structure theorem enables tractable analysis of equilibria in diverse domains, including multi-currency financial systems, decentralized finance with automated market makers, supply chains with resource transformation, and permission networks with complex authorization structures. We further extend our framework to chain-complete lattices for term structure models and multivalued mappings for complex negotiation systems. Our results demonstrate how lattice theory provides a natural language for understanding complex network dynamics across multiple domains, creating a unified mathematical foundation for analyzing systemic risk, resource allocation, and network stability.
Ali Bukhtiar, Hafiz Abdul Rehman Saleem, Asif Iqbal, Muhammad Younas · 5 authors
The development of blockchain technology and its affiliated cryptocurrencies quickly changed the outlook for numerous industries; the most recent, however is that of the smart contract, a self-executing digital agreement whose terms of contract are followed by automatic execution on specific conditions. Yet, despite the huge potential to transform the way transactions are conducted, implementing smart contracts within blockchain and cryptocurrency systems faces a host of legal issues. The research discussed the core legal issues of smart contracts, primarily being a lack of clarity concerning the regulatory framework, lack of clear regulation of enforcement in the traditional legal system, and issues with dispute and accountability. In the same context, the article takes the reader on a journey about the intricacies involved in understanding party intent when using smart contracts. The coding of the contracts might not always capture all the nuances within an agreement. Moreover, certain issues such as the anonymity of a blockchain system, further add the complexity to define the parties at fault in breach or fraud circumstances. This study aims at understanding the junction of law and technology, to identify key barriers that need to be addressed so that smart contracts can be appropriately used in the blockchain and cryptocurrency ecosystem. This research will deliver findings on the adaptation of new digital technologies with legal frameworks for accommodating these newer digital technologies. Recommendations will then be given on how to overcome the problems that are present with the current technology.
Abstract Forecasting cryptocurrencies as a financial issue is crucial as it provides investors with possible financial benefits. A slight improvement in forecasting performance can lead to increased profitability; Therefore, obtaining a realistic forecast is very important for investors. Bitcoin, frequently mentioned in recent due to its volatility and chaotic behavior, has become an investment tool, especially during and after the COVID-19 pandemic. In this study, selected ML techniques were investigated for predicting cryptocurrency movements by using technical indicator-based data sets and measuring the applicability of the techniques to cryptocurrencies that do not have sufficient historical data. In order to measure the effect of data size, Bitcoin’s last 1 year and 7 years of data were used. Following the related literature, Google trends and the number of tweets were used as input features, in addition to the most commonly used twelve technical indicators. Random Forest, K-Nearest Neighbors, Extreme Gradient Boosting (XGBoost-XGB), Support Vector Machine (SVM), Naive Bayes (NB), Artificial Neural Networks (ANN), and Long-Short-Term Memory (LSTM) network were optimized for best results. Accuracy, F1, and area under the ROC curve values were used to compare the model performance. For continuous data, ANN and SVM performed the best with the highest accuracy and outperformed the other ML models for complete and reduced sets. LSTM reached the best accuracy for trend data, but SVM, NB, and XGB models showed similar performance. The research shows that some indicators significantly affect prediction performance, and the data discretization process also improved the model’s accuracy. While the number of samples affects the results of many ML models, correctly optimized and fine-tuned models may also give excellent results even with less data.
The preservation and restoration of cultural heritage has acquired increasing attention in recent years since it has priceless value from both historical and touristic points of view. However, this activity requires considerable funds to be carried out, and frequently, such costs cannot rely entirely on public sources. At the same time, crowdfunding platforms are becoming a widely recognized way to collect funds and finance projects. Indeed, in the literature, some attempts have been made to use crowdfunding platforms to support renovation and restoration projects for cultural heritage items. Even if the benefits of their use in general, particularly for cultural heritage, are widely recognized, skepticism remains regarding transparency, reliability, and trustworthiness. In this regard, the emerging blockchain technology could represent an innovative solution for promoting and guaranteeing such properties through the entire crowdfunding process. However, existing solutions based on the direct use of cryptocurrencies for collecting funds have encountered users' fear and reluctance due to their novelty and the absence of clear and complete regulation by governments. For this reason, in this paper, we propose a solution that is not based on using cryptocurrencies but concentrates on the immutability, traceability, and trustworthiness properties that blockchain offers. To do so, an integrated solution is proposed that combines traditional platforms with a set of smart contracts and a Decentralized Application (dApp), allowing the immutable storage of information inside the blockchain and their subsequent validation by the donors.
Ezinne C Chukwuma-Eke, Olakojo Yusuff Ogunsola, Ngozi Joan Isibor
Access to affordable and reliable energy remains a significant challenge for underserved communities, particularly in developing regions. Financial constraints, lack of investment, and inadequate policy frameworks hinder the widespread adoption of modern energy solutions. This paper explores the role of financial inclusion strategies, driven by technology and policy interventions, in improving energy access for marginalized populations. By integrating digital financial services, decentralized energy systems, and innovative policy measures, this study proposes a comprehensive framework to bridge the energy gap. The proposed framework focuses on leveraging financial technology (FinTech), mobile banking, and blockchain-based microfinancing to enhance accessibility to clean energy solutions. Digital payment platforms and mobile-based credit scoring models facilitate microloans for renewable energy adoption, empowering low-income households and small enterprises. Blockchain technology ensures transparency, security, and accountability in financial transactions, reducing the risks of fraud and inefficiencies in energy financing. Policy interventions play a crucial role in fostering financial inclusion and energy accessibility. Targeted subsidies, regulatory reforms, and public-private partnerships are essential for creating an enabling environment. Governments and financial institutions must collaborate to design policies that incentivize investment in decentralized energy projects, such as mini-grids and off-grid solar solutions. Additionally, carbon credit markets and green bonds can provide sustainable financing mechanisms for long-term energy development. A case study analysis highlights successful implementations of technology-driven financial inclusion models in regions with limited energy access. Results demonstrate that integrating mobile financial services and decentralized energy solutions leads to increased energy affordability, economic empowerment, and improved quality of life. The findings underscore the need for a multi-stakeholder approach, combining technological innovation, policy support, and community engagement to drive sustainable energy inclusion. This study contributes to the discourse on financial inclusion and energy sustainability by proposing a data-driven and policy-oriented approach. Future research should explore the scalability of digital financial services in emerging markets and the long-term impact of financial inclusion strategies on energy equity.
Mrs. V. Deepapriya, C. Sathana, J. Rishwana Begam, V Rohini · 6 authors
Ensuring robust image security in cloud environments is a critical challenge due to risks such as unauthorized access, data tampering, and privacy breaches. This study introduces a Blockchain-based Secure Image Encryption (BC-SIE) method using Chebyshev Polynomial Fostered Hierarchical Auto-Associative Polynomial Convolutional Neural Network (CPHAPCNN) to enhance security, integrity, and high-fidelity image reconstruction. During encryption, the input image is divided into two unpredictable cryptographic shares, represented by black dot patterns, rendering them meaningless individually and preventing unauthorized access. These shares are then secured on a blockchain using an optimized BLAKE2b hashing algorithm, providing efficient and collision-resistant storage. Furthermore, the Chebyshev polynomial-based encryption strengthens security by introducing pixel scrambling, which makes the method resistant to cryptographic attacks. For decryption, the shares are recombined to reconstruct the image, but this introduces noise, impacting image quality. To mitigate this, a Hierarchical Auto-Associative Polynomial Convolutional Neural Network (HAPCNN) is utilized to reduce noise and preserve image details, ensuring near-lossless recovery. The performance of the BC-SIE-CPHAPCNN framework is evaluated using various metrics, including processing time, correlation coefficient, entropy, peak signal-to-noise ratio (PSNR: 28.44 dB), and mean square error (MSE). The results demonstrate superior encryption security and image reconstruction accuracy, with an updated computed SSIM accuracy of 91.75%. Additionally, the Delegated Proof of Stake (DT-DPoS) blockchain consensus mechanism enhances both security and scalability. Experimental evaluations confirm that this approach outperforms existing methods, making it ideal for cloud storage, medical imaging, and secure surveillance systems.
“Değiştirilemez ve benzersiz varlıklar” şeklinde ifade edilen NFT’ler (Non-Fungible Token), kripto para teknolojisinin bir uzantısı olarak doğmuş olmasına rağmen kısa süre içerisinde sanat ve estetik konularıyla iç içe geçmiştir. Dijital sanatın bir göstergesi olan NFT’ler, sadece estetik ve etik açıdan değil, aynı zamanda orijinallik, koleksiyonerlik ve ticarileşme gibi pek çok açıdan incelenmeye değer bir konudur. Yapay zekâ destekli algoritmaların etken bir faktör olarak NFT’lerde yer alması, sanatçının rolünü birçok açıdan dönüştürmüştür. Bunun yanı sıra sanat eserlerinin mülkiyetinin dijitalleşmesi, eserden beklentilerin de değişmesine sebep olmuştur. Bu değişimde NFT’ler üzerinden sanatın ticarî bir meta hâline getirilmesinin büyük bir etkisi bulunmaktadır. Yapay zekâ desteğiyle üretilen sanat eserlerinin, yine yapay zekâ tarafından manipüle edilerek para piyasalarını kontrol altına alabilmesi pek çok spekülasyona yol açsa da Refik Anadol, Murat Pak, Selçuk Erdem, Cem Yılmaz gibi bazı öncü Türk NFT sanatçıları küresel ölçekte yeni bir sanat zemini oluşturmuştur. Bu çalışmada yapay zekâ ile desteklenen NFT’lerin sanat dünyasındaki yeri, Türk NFT sanatçıları örnekleminde değerlendirilecektir. Aynı zamanda sanatın doğuşundan kitlelere uzanan yolda yapay zekânın etkisi ve önemi ile yaratıcılık ve orijinallik kavramlarının nasıl değişime uğradığı tartışılacak, NFT’lerin sanatı yayma gücü ve potansiyeli irdelenirken, dijital teknolojilerin sanatçı ve sanatın alımlayıcısı arasındaki yeni ve doğrudan ilişkiyi nasıl dönüştürdüğü üzerinde de durulacaktır.
Kode Lakshmi Durga Sindhujasri, Kaduputla Manogna, Sutrayeth Hari Yuktha Nanda, Baligiri Thandava Krishna · 5 authors
Abstract: Elections play a fundamental role in any democratic system, and ensuring their integrity is of utmost importance. Traditional voting methods, such as paper ballots and Electronic Voting Machines (EVMs), suffer from various limitations, including security vulnerabilities, vote tampering, low voter turnout, delays in result processing, and a lack of transparency. Digital voting solutions offer convenience but raise concerns regarding data security and susceptibility to cyber threats. Blockchain technology presents a promising solution to these challenges by providing a decentralized, transparent, and tamperproof framework for conducting elections. As a distributed ledger system, blockchain records transactions in an immutable and verifiable manner, ensuring the integrity of votes. Key features such as decentralization, cryptographic security, transparency, and anonymity make blockchain a robust choice for secure e-voting. In this paper, we propose and implement a blockchainbased e-voting system using Ethereum smart contracts and Web3.js. Our system enforces single-use voting credentials, preventing duplicate votes, and leverages gas fees to mitigate fraudulent voting attempts. Additionally, we develop a web-based application that demonstrates the practical implementation of blockchain voting, discussing its advantages, challenges, and limitations in real-world scenarios
Open access
Internet Traffic Analysis and Secure E-voting
Advanced Steganography and Watermarking Techniques
Costase Ndayishimiye, Richard Nduwayezu, Christoph Sowada, Katarzyna Dubas‐Jakóbczyk
Results-based healthcare financing policies have been adopted in countries worldwide, including those with limited resources. We conducted a retrospective, semistructured interview study to evaluate healthcare providers' experiences with Rwanda's performance-based financing (PBF) policy and the factors influencing its implementation. Guided by the health policy evaluation model-context, content, process, and actors-as a deductive framework supplemented by inductive coding, we analysed data from 21 participants (doctors, n = 13; nurses, n = 5; midwives, n = 3). Providers described PBF as a key motivator, supplementing incomes, increasing accountability, and fostering teamwork to meet performance targets. PBF was credited with improving patient outcomes, particularly in incentivized services; however, concerns arose regarding disparities in service prioritization. Key facilitators of and barriers to the implementation of PBF were identified, providing insights into its operational dynamics. Strong political commitment and integration into national strategies, such as Imihigo, along with decentralization through district steering committees, were key contextual enablers, enhancing the program's flexibility and alignment with local priorities. The content factors centred on a two-tiered contracting system, combining national accreditation processes with individual performance incentives. Process factors supporting PBF were characterized by decentralized evaluations, audits, and multilevel communication, which collectively bolstered accountability mechanisms. The engagement and capacity of stakeholders were highlighted as crucial to the success of PBF. Nonetheless, significant barriers, such as payment delays, manual documentation, untimely evaluations, insufficient training, limited provider participation in decision-making, and the exclusion of patients as stakeholders, were identified. These findings offer practical recommendations for policymakers aiming to improve or adapt provider payment mechanisms in similar contexts.
Abstract Blockchain-based emerging technologies such as decentralized finance (DeFi), cryptocurrencies, tokens, and smart contracts have introduced innovative frameworks for resource allocation and economic interactions. Ethereum, as the major technical network foundation of DeFi and tokenized assets, is becoming increasingly pivotal in facilitating an extension and alternative to traditional finance for many stakeholders, including those who are “unbanked”. Moreover, the recent transition of Ethereum from a proof-of-work (PoW) mechanism to a proof-of-stake (PoS) consensus mechanism and the Shanghai upgrade may significantly impact Ether (ETH) distribution. However, the status quo and dynamics of wealth distribution, especially after these changes in governance structure, remain unclear. By utilizing a rich dataset spanning the entire Ethereum history from July 2015 to December 2024, we analyze the balances across address groups of different sizes and the role of key economic activities and infrastructure components within Ethereum, such as exchanges, DeFi platforms, and staking. To provide detailed insights into ETH’s distributional equality, our approach combines descriptive, longitudinal, and causal inference analyses; a complete enumeration of more than 98 million unique wallet addresses; and novel on-chain analysis. Our findings show a substantial concentration of ETH within a small fraction of addresses, with approximately 0.3% of wallets holding nearly 95% of the total supply, despite the majority of wallets holding less than 0.1% ETH. However, the ETH distribution broadly resembles wealth distributions in traditional economies, with a log-normal body and Pareto-like tails. We assert that previous studies have overstated the concentration of ETH. Additionally, our dynamic analysis reveals a nuanced trend toward less concentration over time, driven by market cycles, increasing staking participation, and reinvestment in DeFi. These results challenge the notion of pervasive centralization. This study contributes to a deeper understanding of the current ETH distribution and its evolution over time. Therefore, this work provides an objective, data-driven basis for the ongoing discussion on wealth (in)equality in blockchain-based ecosystems, particularly in DeFi.
Taylor Lundy, Narun Raman, Scott Duke Kominers, Kevin Leyton‐Brown
Conspicuous consumption occurs when a consumer derives value from a good based on its social meaning as a signal of wealth, taste, and/or community affiliation. Common conspicuous goods include designer footwear, country club memberships, and artwork; conspicuous goods also exist in the digital sphere, with non-fungible tokens (NFTs) as a prominent example. The NFT market merits deeper study for two key reasons: first, it is poorly understood relative to its economic scale; and second, it is unusually amenable to analysis because NFT transactions are publicly available on the blockchain, making them useful as a test bed for conspicuous consumption dynamics. This paper introduces a model that incorporates two previously identified elements of conspicuous consumption: the \emph{bandwagon effect} (goods increase in value as they become more popular) and the \emph{snob effect} (goods increase in value as they become rarer). Our model resolves the apparent tension between these two effects, exhibiting net complementarity between others' and one's own conspicuous consumption. We also introduce a novel dataset combining NFT transactions with embeddings of the corresponding NFT images computed using an off-the-shelf vision transformer architecture. We use our dataset to validate the model, showing that the bandwagon effect raises an NFT collection's value as more consumers join, while the snob effect drives consumers to seek rarer NFTs within a given collection.
Open access
2 source records
Consumer Behavior in Brand Consumption and Identification
Decentralization is understood both by professionals in the blockchain industry and general users as a core design goal of permissionless ledgers. However, its meaning is far from universally agreed, and often it is easier to get opinions on what it is not, rather than what it is. In this paper, we solicit definitions of 'decentralization' and 'decentralization theatre' from blockchain node operators. Key to a definition is asking about effective decentralization strategies, as well as those that are ineffective. Malicious, deceptive, or incompetent strategies are commonly referred to by the term 'decentralization theatre.' Finally, we ask what is being decentralized. Via thematic analysis of interview transcripts, we find that most operators conceive of decentralization as existing broadly on a technical and a governance axis. This informs a two-axis model: network topology and governance topology, or the structure of decision-making power. Our key finding is that `decentralization' alone does not affect ledger immutability or systemic robustness.
The evaluation of smart contract reputability is essential to foster trust in decentralized ecosystems. However, existing methods that rely solely on code analysis or transactional data, offer limited insight into evolving trustworthiness. We propose a multimodal data fusion framework that integrates code features with transactional data to enhance reputability prediction. Our framework initially focuses on AI-based code analysis, utilizing GAN-augmented opcode embeddings to address class imbalance, achieving 97.67% accuracy and a recall of 0.942 in detecting illicit contracts, surpassing traditional oversampling methods. This forms the crux of a reputability-centric fusion strategy, where combining code and transactional data improves recall by 7.25% over single-source models, demonstrating robust performance across validation sets. By providing a holistic view of smart contract behaviour, our approach enhances the model's ability to assess reputability, identify fraudulent activities, and predict anomalous patterns. These capabilities contribute to more accurate reputability assessments, proactive risk mitigation, and enhanced blockchain security.
Aakanksha Bedi, J. Ramprabhakar, R. Anand, Veerpratap Meena · 5 authors
Energy is the basic prerequisite of any industry, but global warming, climate change, and pollution are increasing due to digitization and industrialization. Rising electricity demand, combined with the integration of electric vehicles, has made it increasingly challenging to rely solely on conventional centralized power systems. To meet this current changing energy scenario, it becomes essential to introduce green energy into conventional power systems and allow bi-directional energy flow. Microgrids, smart grids, and virtual power plants will play an important role in making this massive shift from a centralized system to a decentralized power system. A virtual power plant is a cloud-based energy system incorporating various microgrids, energy storage, distributed energy resources, and weather forecasting. Since this system is virtual, it could lead to cyber threats. To the best of the authors’ knowledge, this review article complies with recent data from ten major research libraries, offering consolidated insights into the virtual power plant (VPP) framework that will enhance customer participation and encourage them to become prosumers. Additionally, a blockchain-based VPP framework is presented along with two very prominent scenarios of blockchain-based distributed VPP involving P2P transactions and NW trading discussed for building futuristic NZEGs aimed at reducing carbon footprints and providing a foundation for future net-zero energy grids (NZEZs).
Javier Parra-Domínguez, Laura Sanz Martín, Germán López‐Pérez, José Luis Zafra Gómez
Purpose The purpose of this study is to explore the disruptive potential of blockchain technology in the field of accounting. By conducting a systematic review and bibliometric analysis, the research aims to identify key clusters and trends that illustrate how blockchain can transform traditional accounting practices. This includes improving transparency, enhancing data security, automating processes and integrating emerging technologies such as artificial intelligence. This study also seeks to highlight current research gaps, challenges in practical implementation and the future impact of blockchain on governance and financial systems. Design/methodology/approach This study uses two main methodologies: a systematic literature review and bibliometric analysis. The systematic review follows the PRISMA 2020 guidelines to identify and analyze relevant articles from Scopus, Web of Science and EBSCO databases, using specific search equations related to blockchain and accounting. A bibliometric analysis was conducted using VOSviewer to identify key clusters and trends within the collected literature. Clustering techniques, such as exploratory factor analysis, were applied to explore the relationships among documents, keywords and authors, providing insights into the evolution of blockchain’s impact on accounting practices. Findings The results of this study reveal four primary clusters in the intersection of blockchain and accounting: CryptoLedger Accounting Network, TransparentChain Trust Framework, IntelliLedger Accounting Tech and DigiGov Ledger Insights. These clusters highlight key areas where blockchain technology is transforming accounting practices, such as enhancing transparency and trust in supply chains, integrating artificial intelligence for accounting automation and improving data security. The bibliometric analysis also identified emerging trends, including the increasing relevance of smart contracts, the challenges of integrating blockchain with existing systems and the need for updated regulatory frameworks. Practical implications In this sense, this paper presents several theoretical and practical implications, as well as identifying possible limitations and gaps in current knowledge, providing new opportunities for the establishment of future lines of research, such as robust regulatory frameworks, privacy and security considerations, and the practical implementation of blockchain solutions in real-world accounting scenarios. Originality/value This study provides a unique contribution by synthesizing the disruptive impact of blockchain technology on accounting through a combination of systematic literature review and bibliometric analysis. By identifying four distinct research clusters, this paper offers fresh insights into how blockchain integrates with accounting practices, particularly in transparency, automation and security. It also highlights emerging challenges and research gaps, such as regulatory frameworks and practical implementation. The originality lies in the comprehensive exploration of blockchain’s multifaceted role in modernizing accounting, offering valuable guidance for both academics and practitioners navigating this evolving field.
Aditya R. Malhotra1, Kavya S. Ahuja2, Vihaan P. Bansal3, Tanvi R. Kapoor4
The integration of blockchain technology, particularly Bitcoin-inspired decentralized protocols, into smart grid systems offers innovative solutions for energy management, security, and peer-to-peer (P2P) energy trading. Traditional centralized grids face challenges including inefficiencies, security vulnerabilities, and lack of real-time transactional transparency. By leveraging Bitcoin-like blockchain mechanisms, smart grids can facilitate secure, automated, and auditable energy transactions between distributed producers and consumers. This paper explores the design principles of Bitcoin-enabled smart grids, including consensus protocols, cryptographic transaction verification, and integration with IoT-based energy meters. It also examines case studies and simulation models demonstrating the potential for reduced energy losses, enhanced security, and decentralized grid optimization. Finally, challenges related to scalability, transaction speed, and energy consumption of blockchain networks are discussed, highlighting directions for future research in sustainable and efficient decentralized energy systems.
Xiangyu Bai, Jiali Hu, Xianming Liu, Yaqin Deng · 6 authors
The purpose of this paper is to discuss the design and implementation of the upgrade of encryption technology of the Grand Canal digital document system based on blockchain technology. Based on the core technologies of blockchain's distributed ledger, smart contract and encryption algorithm, this study proposes a novel upgrade scheme for the Grand Canal digital document system. The scheme realizes the non-tampering and full traceability of document data by constructing a decentralized document storage architecture, and optimizes the document management process by using smart contract technology and asymmetric encryption algorithm to ensure the security of document transmission and storage. As a modern technology with strong confidentiality and security, blockchain is extremely important for data protection, and is of great practical significance for promoting the digital inheritance and innovative development of the cultural heritage of the Grand Canal.
The evolution from Web 2.0 to Web 3.0 represents a paradigm shift in internet technology, with a focus on decentralization, user control, and improved security. While Web 2.0 facilitated social networking, cloud computing, and engaging content, it came at the cost of data privacy issues, central control, and digital monopolies. Web 3.0 is based on blockchain, artificial intelligence, smart contracts, and decentralized finance (DeFi) to build a trustless, peer-to-peer digital world that is focused on user ownership and security. This research assesses the fundamental features of Web 3.0, such as decentralized applications (dApps), digital identity systems, and interoperability solutions, in addition to analyzing the adoption challenges, such as scalability, regulatory ambiguity, and usability obstacles. Through decentralized finance case studies, social media, gaming, and data storage, the paper showcases the advantages and challenges of Web 3.0 integration with current digital infrastructures. Future directions point toward developments in Layer 2 scaling, privacy technologies, and cross-chain interoperability to make Web 3.0 more mainstream and sustainable. Though there are challenges, Web 3.0 can reshape finance, governance, and online interactions, leading to a decentralized, user-owned internet.