Hee Joo Kim, Zhe Xiao, Xiaocai Zhang, Xiuju Fu · 5 authors
This survey aims to provide an up-to-date and succinct yet informative overview of the blockchain technologies for the maritime industry. We synthesize the recent advancements in blockchain development and its adoption across maritime sectors, highlighting the key blockchain use cases, including promoting maritime sustainability and optimizing maritime supply chain management through improved traceability, advancing smart shipping with automated processes and fostering collaboration among stakeholders by enhancing transparency. Through an analysis of current implementations, pilot projects, and case studies, we especially focus on identifying the challenges and barriers, reasoning on the status quo, and the opportunities and future perspectives for blockchain in maritime.
This article examines the theoretical foundations and conceptual specifics of the mechanism for adopting cryptocurrencies as a payment method in business. It discusses the definition and key features of this mechanism, along with summarizing essential recommendations for the use of cryptocurrencies and crypto assets in business payments. The cryptocurrency adoption framework is analyzed through the organizational–economic mechanism, aiming to achieve practical objectives such as cost reduction, improved access to cross–border payments, and transaction security with crypto assets. The article stresses the importance of risk analysis related to cryptocurrency use and the development of risk mitigation methods through proactive management and the application of appropriate tools. The conclusions highlight the feasibility and benefits of using an organizational–economic mechanism to incorporate crypto assets into business payment processes, ensuring efficiency and adaptability of crypto assets or other alternative payment instruments. The study’s novelty lies in its contribution to the development of a mechanism for integrating cryptocurrencies into business operations, while its theoretical value is in the synthesis and clarification of key issues related to cryptocurrency acceptance in business. The proposed concept and vision of the organizational–economic mechanism to enhance the efficiency of cryptocurrency use in business payments offer valuable insights for future research and practical implementation.
Blockchain-based technology has completely revolutionized the development of the Internet of Vehicles (IoV) framework. This has led to increasing blockchain-based Internet of Vehicles application over the last decade. However, challenges persist, including scalability, interoperability, and security issues. This paper first presents the state-of-the-art overview on IoV systems along with their applications. Then, we explore novel technologies, including blockchain-based IoV and machine learning-based IoV and highlight how the blockchain technology could be integrated with machine learning for intelligent transportation systems in the IoV ecosystem. This paper has shown the potential of machine learning integration in addressing the technical challenges in individual blockchain-based Internet of Vehicles applications.
Purpose The real estate industry is often highlighted as a significant beneficiary of blockchain-driven digital transformation (DT). This paper unravels blockchain’s role in driving rapid DT in the Finnish housing sector and its removal after market entry. Design/methodology/approach This four-year longitudinal study used 35 semi-structured interviews. Findings Blockchain was crucial in the early industry-wide DT, fostering innovation through shared value creation, delivery and capture while supporting collaboration and enhancing processes. The findings largely support blockchain’s theoretical benefits in reducing intermediaries, automating processes, minimizing errors, enhancing transparency and addressing data silos in real estate transactions. However, limitations – like the need for specialised expertise, scalability issues and centralisation tendencies emerged – ultimately outweighed the benefits, leading to blockchain abandonment. Regulatory commitment, contrary to expectations about regulatory barriers, regulatory commitment substantially boosted industry activities. While blockchain can spark transformation, maintaining momentum amid evolving market and regulatory developments may require more than blockchain alone can offer. Practical implications Blockchain can drive early-stage DT even in traditional industries like real estate, addressing issues like intermediary reliance, manual processes, inefficiencies and errors. However, it does not guarantee long-term decentralisation as initially promised and depends on off-chain governance. Originality/value This is the first empirical study on blockchain in real estate examining the drivers of a full-scale DT. It is also amongst the first to explore blockchain’s evolving role in successful industry-wide transformation based on a rare four-year study, extending insights into blockchain’s initial impact and subsequent limitations beyond the firm level.
In recent years, cryptocurrencies have become a significant element of the modern economy, attracting the attention of investors, regulators, and researchers. Despite substantial progress in understanding the factors influencing cryptocurrency pricing, many aspects remain insufficiently studied. This article provides an overview of traditional factors such as fundamental, macroeconomic, financial, behavioral, and infrastructural ones, and introduces two new groups of factors: socio-economic and market manipulators. Socioeconomic factors represent a wide range of influences determined by the state of society and the economy, significantly impacting cryptocurrency pricing. Market manipulators, on the other hand, encompass methods such as pump-and-dump schemes, insider trading, and manipulations using stablecoins, which lead to substantial price fluctuations in cryptocurrencies. The review of existing traditional factors in combination with new ones allows for a more comprehensive assessment of the dynamics of cryptocurrency pricing. The introduction of these new groups of factors underscores the need for further research to gain a fuller understanding of the pricing mechanisms in the cryptocurrency market and to develop risk management strategies. This work provides a review of existing studies and highlights gaps that require researchers’ attention.
Odunayo Akindotei, Igba Emmanuel, Babatunde Olusola Awotiwon, Adah Otakwu
Blockchain technology has garnered significant attention for its potential to revolutionize critical systems by enhancing transparency, efficiency, and data security. This review examines the integration of blockchain in three essential domains: Agile Project Management, Decentralized Finance (DeFi), and Cold Chain Management. By leveraging decentralized ledgers and smart contracts, blockchain provides a robust framework for real-time tracking, data integrity, and automated compliance, addressing long-standing challenges across these sectors. In Agile Project Management, blockchain fosters seamless collaboration and transparent decision-making, minimizing bottlenecks and improving accountability. In DeFi, blockchain strengthens security for digital transactions and identity verification while offering financial autonomy and mitigating fraud risks. Within Cold Chain Management, blockchain ensures traceability, reduces data tampering risks, and enhances visibility throughout supply chain processes, safeguarding temperature-sensitive goods. This paper evaluates existing blockchain-based applications and frameworks, identifies current limitations, and discusses future opportunities for optimizing critical systems through blockchain. The findings highlight blockchain's transformative role in driving operational efficiency, security, and data transparency across diverse applications, providing a roadmap for industries to harness its full potential in critical environments.
This paper explores the integration of blockchain technology to enhance data integrity in cloud computing environments. As data breaches and unauthorized access continue to challenge traditional cloud security measures, blockchain offers a decentralized solution that ensures tamper-proof record-keeping and accountability. By leveraging cryptographic techniques and distributed ledger technology, the proposed framework enables secure data storage, sharing, and validation processes. This study highlights key use cases, potential challenges, and the overall impact of blockchain on improving trust and reliability in cloud computing, paving the way for more robust data integrity solutions in various applications across industries.
Blockchains have sparked global interest in recent years, gaining importance as they increasingly influence technology and finance.This thesis investigates the robustness of blockchain protocols, specifically focusing on Ethereum Proof-of-Stake. We define robustness in terms of two critical properties: Safety, which ensures that the blockchain will not have permanent conflicting blocks, and Liveness, which guarantees the continuous addition of new reliable blocks.Our research addresses the gap between traditional distributed systems approaches, which classify agents as honest or Byzantine (i.e., malicious or faulty), and game-theoretic models that consider rational agents driven by incentives. We explore how incentives impact the robustness with both approaches.The thesis comprises three distinct analyses. First, we formalize the Ethereum PoS protocol, defining its properties and examining potential vulnerabilities through a distributed systems perspective. We identify that certain attacks can undermine the system's robustness. Second, we analyze the inactivity leak mechanism, a critical feature of Ethereum PoS, highlighting its role in maintaining system liveness during network disruptions but at the cost of safety. Finally, we employ game-theoretic models to study the strategies of rational validators within Ethereum PoS, identifying conditions under which these agents might deviate from the prescribed protocol to maximize their rewards.Our findings contribute to a deeper understanding of the importance of incentive mechanisms for blockchain robustness and provide insights into designing more resilient blockchain protocols.
Open access
Economic and Technological Systems Analysis
Economic and Technological Developments in Russia
Advanced Research in Systems and Signal Processing
As an emerging technology, blockchain demonstrates strong potential for applications in digital finance. As a core component of blockchain, the security and reliability of smart contracts is crucial. To ensure the high reliability of smart contracts, this study employs formal construction and verification techniques based on game theory. Initially, the profit function is defined using distortion techniques, and a game model for supply chain participation is designed. However, the equilibrium solution of the two-party game does not represent the optimal solution for the supply chain system. Therefore, the study introduces third-party participation to optimize the equilibrium solution. Finally, a probability model detection method is used to verify the constructed smart contract model. The results show that the supply chain model, analyzed through formal methods, has attributes consistent with theoretical analysis. Consequently, the research on automatic construction and verification algorithms for smart contracts based on formal verification proves to be effective and feasible in practical applications.
Christos Roumeliotis, Minas Dasygenis, Vasilis Lazaridis, Michael Dossis
The Fourth Industrial Revolution has transformed industries and supply chains by integrating advanced operations, tools, and logistics services. Despite these advancements, challenges persist, particularly in ensuring data dependability, security, and operational efficiency. Digital twins (DTs), which replicate real-world components and processes, have emerged as essential tools for enhancing predictive analytics, simulation, and product lifecycle management in Industry 4.0. However, traditional DT development relies on centralized systems, which are vulnerable to data tampering and security breaches, especially in the management of transaction logs and historical data. To address these challenges, this review provides a comprehensive analysis of the current state of integrating blockchain with DTs. Using a qualitative research methodology, including desk research, case studies, and interviews with industry experts, we analyze various blockchain-based DT applications across industries and specifically in supply chain management. The findings reveal that blockchain-enhanced DTs can significantly improve data integrity, traceability, and security, thus boosting operational efficiency and quality control in supply chains. Additionally, this study identifies key integration techniques and the role of blockchain in automating processes through smart contracts. This review provides insights into the practical implications of blockchain-based DTs, highlighting their potential to enhance the reliability and scalability of Industry 4.0 operations.
Integration of Internet of Things (IoT) and blockchain combined with the power of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) are transforming the sphere of smart industries, propagating a new era of boosted productivity, information assurance, and data-influenced deliberation. Our research looks into how these cutting-edge technologies flow together to enable smart industry breakthroughs. This offers conductive connectiveness and communication capabilities between devices and can create large pools of data, that are essential for making more informed decisions and finally, operating more sustainably. This data is then scaled and processed by the AI ML and DL algorithm to get the predictive insights; process optimization and to improve on automation. The security and immutability of data are critical in an IoT network, and this is something that blockchain technology excels at and ensures data exchanged within these networks is safe and unalterable. Thanks to recent developments in AI, ML, and DL, they can now better meet the challenges of industrial applications well beyond predictive maintenance and supply chain optimization and extend into real-time monitoring and autonomous operations. The perspective taken in this research is instead one of a practical, real-world implementations, illustrating some of the advantages as well as challenges when integrating these technologies. The results point to the enormous transformative capability of this integration and suggest a level of efficiency, security and innovation not seen before that will redefine intelligent industries today and possibly more importantly tomorrow, in effect defining the fourth industrial revolution and beyond.
This article presents a Blockchain-based solution for the management of multipolicies in insurance companies, introducing a standardized policy model to facilitate streamlined operations and enhance collaboration between entities. The model ensures uniform policy management, providing scalability and flexibility to adapt to new market demands. The solution leverages Merkle trees for secure data management, with each policy represented by an independent Merkle tree, enabling updates and additions without altering existing policies. The architecture, implemented on a private Ethereum network using Hyperledger Besu and Tessera, ensures secure and transparent transactions, robust dispute resolution, and fraud prevention mechanisms. The validation phase demonstrated the model’s efficiency in reducing data redundancy and ensuring the consistency and integrity of policy information. Additionally, the system’s technical management has been simplified, operational redundancies have been eliminated, and privacy is enhanced.
가상화폐는 일상 속 자산으로 자리 잡고 있으며, 비트코인과 이더리움의 ETF 승인은 제도권에서 받아들이기 시작한 것을 계기로 자산으로서 입지가 강화되고 있다. 우리는 가상화폐를 더 이상 단순 투자의 대상이 아닌 일상에서 화폐로 사용하거나 금과 같이 안전 자산으로 보유하고자 하는 사람들에게 주목한다. 본 연구는 기술지표와 거래 시간을 기반으로 한 가상화폐 보유 전략의 효과성을 분석하며, 이동평균선(MA, Moving Average), 볼린저 밴드(BB, Bollinger Band), 상대강도지수(RSI, Relative Strength Index) 상대강도지수(RSI, Relative Strength Index, 상품 채널 지수(CCI, Commodity Channel Index) 등 기술지표를 활용하여 백테스팅 결과를 수집한다. 우리의 접근 방법을 분석 및 평가하기 위해 매수 후 보유(Buy & Hold) 전략과 비교한다. 비트코인과 이더리움을 대상으로 보유량 증감률, 최대손실률(MDD, Maximum Draw Down), 보유기간 등을 평가한 결과, 기술지표 기반 보유 전략이 가상화폐 보유량 증가에 효과를 보였다. 거래 시간에 따라 보유 전략의 수익률의 차이를 확인하고 적합한 투자 시간을 분석했다. 이는 가상화폐 자산을 보유하면서 보유량의 증가를 원하는 투자자에게 유용한 방법 될 것이라 기대한다.
George Lăzăroiu, Tom Gedeon, Elżbieta Rogalska, Katarína Valášková · 17 authors
Research background: Generative artificial intelligence (AI) and machine learning algorithms support industrial Internet of Things (IoT)-based big data and enterprise asset management in multiphysics simulation environments by industrial big data processing, modeling, and monitoring, enabling business organizational and managerial practices. Machine learning-based decision support and edge generative AI sensing systems can reduce persistent labor shortages and job vacancies and power productivity growth and labor market dynamics, shaping career pathways and facilitating occupational transitions by skill gap identification and labor-intensive manufacturing job automation by path planning and spatial cognition algorithms, furthering theoretical implications for management sciences. Generative AI fintech, machine learning algorithms, and behavioral analytics can assist multi-layered payment and transaction processing screening with regard to authorized push payment, account takeover, and synthetic identity frauds, flagging suspicious activities and combating economic crimes by rigorous verification processes. Purpose of the article: We show that edge device management functionalities of cloud industrial IoT and virtual robotic simulation technologies configure plant production and route planning processes across cyber-physical production and industrial automation systems in multi-cloud immersive 3D environments, leading to tangible business outcomes by reinforcement learning and convolutional neural networks. Labor-augmenting automation and generative AI technologies can impact employment participation, increase wage and wealth inequality, and lead to potential job displacement and massive labor market disruptions. The deep learning capabilities of generative AI fintech in terms of adaptive behavioral analytics and credit scoring mechanisms can enhance financial transaction behaviors and algorithmic trading returns, identify fraudulent payment transactions swiftly, and improve financial forecasts, leading to customized investment recommendations and well-informed financial decisions. Methods: Machine learning-based study selection process and text mining systematic review management software and tools leveraged include Abstrackr, CADIMA, Colandr, DistillerSR, EPPI-Reviewer, JBI SUMARI, METAGEAR package for R, SluRp, and SWIFT-Active Screener. Such reference management systems are harnessed for methodologically rigorous evidence synthesis, study selection and characteristic extraction, predictive document classification, machine learning-based citation and record screening, bias assessment, article retrieval automation, and document classification and prioritization. Findings & value added: Industrial IoT and 3D augmented reality technologies can create business value by streamlining virtual product and remote asset management across extended reality-based navigation and robotic autonomous systems in smart factory environments by generative AI and machine learning algorithms, articulating business organizational level and theory of management implications. 3D simulation and operational modeling tools can execute and complete complex cognitive task-oriented and knowledge economy jobs, producing first-rate quality outputs swiftly while leading to unemployment spells, labor market disruptions, job displacement losses, and reduced earnings by machine learning clustering and spatial cognition algorithms. Generative AI decentralized finance, interoperable blockchain networks, cash flow management tools, and asset tokenization can mitigate fraud risks, enable digital fund and crypto investing servicing, and automate treasury operations by integrating real-time payment capabilities, routing and configurable workflows, and lending and payment technologies.
The article discusses the use of Ethereum blockchain technology in the Internet of Things (IoT) network for IT diagnostics of patients, which increases data security and user privacy. This integration is proving effective for storing and managing sensitive data of patients with neurological diseases. An integrated system architecture has been developed that combines the IoT network, the IPFS (InterPlanetary File System) file structure with the Ethereum blockchain to create a reliable data storage model. This system ensures efficient, secure and transparent data processing, optimizing the processes of data registration, authorization and verification. Using IPFS for decentralized file storage, along with the Ethereum blockchain to create tamper-proof medical records, provides increased efficiency, scalability and privacy. During the experiments, the process of creating and testing the system was implemented, including setting up the environment, connecting an IPFS node, programming Ethereum smart contracts, sampling voice data and storing their hashes.
The increasing complexity of modern aircraft systems necessitates advanced monitoring solutions to ensure operational safety and efficiency. Traditional aircraft health monitoring systems (AHMS) often rely on reactive maintenance strategies, detecting only visible faults while leaving underlying issues unaddressed. This gap can lead to critical failures and unplanned downtime, resulting in significant operational costs. To address this issue, this paper proposes the integration of artificial intelligence (AI) and blockchain technologies within an enhanced AHMS, utilizing the iceberg model as a conceptual framework to illustrate both visible and hidden defects. The model highlights the importance of detecting and addressing issues at the earliest possible stages, ensuring that hidden defects are identified and mitigated before they evolve into significant failures. The rationale behind this approach lies in the need for a predictive maintenance system capable of identifying and mitigating hidden risks before they escalate. Key tasks completed in this study include: a comparative analysis of the proposed system with existing monitoring solutions, the selection of AI algorithms for fault prediction, and the development of a blockchain-based infrastructure for secure, transparent data sharing. The evolution of AHMS is discussed, emphasizing the shift from traditional monitoring to advanced, predictive, and prescriptive maintenance approaches. This integrated approach demonstrates the potential to significantly improve fault detection, optimize maintenance schedules, and enhance data security across the aviation industry.
The financial markets are undergoing rapid transformations that raise fundamental questions about the effectiveness of traditional investment models and strategies. Nowadays, investment options are incomparably wider than ever before, and one of the areas of this global financial transformation is alternative investments, so the question is what might be the trends of one of these alternative investments, non-fungible tokens (NFT). The object of the study is alternative investments, such as NFTs. The article intends to reveal how NFTs might impact the valuation and trade of digital assets, as well as to identify the key advantages and risks associated with NFTs for investors and creators. The research will carry out cluster analysis of NFTs, which will help to better understand the NFT market, learn about possible prospects and developments, possible advantages and disadvantages, as well as the level of risk.
Purpose This study aims to investigate blockchain technology (BT) and its opportunities and weaknesses in Iran's tax system; it addresses the opportunities and challenges of BT when incorporated into Iran's tax system. Design/methodology/approach The statistical population consists of all the employees and managers working in tax administration, and 674 participants were selected as the sample size via Cochran sampling. The partial least square tests are used to investigate the impact of the independent variable on dependent ones. Findings The results show that BT positively affects three components of tax, including value-added tax, tax on shipping goods and income tax. BT’s advantages and opportunities positively affect these taxation types, while its threats negatively affect the opportunities and challenges in Iran’s tax system; this study provides helpful insights and develops the knowledge. Furthermore, this is among the initiatives addressing BT’s opportunities and challenges in three discriminative taxation sectors, including value-added tax, tax on shipping goods and payroll tax. Originality/value Since no study has addressed BT’s opportunities and weaknesses in Iran’s tax system, it addresses the opportunities and challenges of BT when incorporated into Iran’s tax system.
The aim of this paper is to synthesize and analyze existing evidence on interconnected sensor networks and digital urban governance in data-driven smart sustainable cities. The research topic of this systematic review is whether and to what extent smart city governance can effectively integrate the Internet of Things (IoT), Artificial Intelligence of Things (AIoT), intelligent decision algorithms based on big data technologies, and cloud computing. This is relevant since smart cities place special emphasis on the involvement of citizens in decision-making processes and sustainable urban development. To investigate the work to date, search outcome management and systematic review screening procedures were handled by PRISMA and Shiny app flow design. A quantitative literature review was carried out in June 2024 for published original and review research between 2018 and 2024. For qualitative and quantitative data management and analysis in the research review process, data extraction tools, study screening, reference management software, evidence map visualization, machine learning classifiers, and reference management software were harnessed. Dimensions and VOSviewer were deployed to explore and visualize the bibliometric data.
Chibuikem Michael Adilieme, Rotimi Boluwatife Abidoye, Chyi Lin Lee
Purpose Blockchain is an emerging digital technology proposed and trialled among different built environment professions. The technology has been proposed to introduce transparency, security and trust in property transactions. Despite this proposition, few studies have analysed the barriers and prospects in property valuation, especially in markets plagued by low transparency and a lack of stakeholder trust. Using Nigeria as a case study, this study assesses the barriers and prospects for adopting blockchain technology in property valuation. Design/methodology/approach Data was collected from 180 valuers practising in Nigeria through an online survey, and the data was analysed using mean score ranking and the chi-square (χ2) test of independence. Findings Firstly, there was a low awareness of the application of blockchain technology and an association between the number of valuation jobs executed annually and awareness of the application of blockchain technology. The most important barriers revolved around the knowledge, technical know-how of blockchain and the cost of implementing such technology. The prospects for blockchain are very high as all identified prospects were considered important, with transparency being the most crucial factor for its adoption, followed by the monitoring activities in real time and the permanence in storing records. Research limitations/implications This study's implications lie in the potential benefit of transparency identified for blockchain, which could act as a tool to introduce transparency into valuation industries that battle key issues surrounding transparency and trust. Furthermore, this study can be utilised by policymakers and property industry players in mapping strategies to adopt the beneficial use of blockchain as one among the suite of proptech tools disrupting the property valuation scene, in their practice. This also presents an opportunity to draw upon insights from this study to better prepare for using blockchain in property valuation. Originality/value This study appears to be the first to empirically assess barriers and prospects for blockchain in property valuation practice. It contributes to the literature by identifying key factors that will deter and/or promote the application of blockchain, an emerging and disruptive digital technology.
This study aims to assess the extent to which blockchain technology (BCT) may constitute an alternative to the conventional stock trading system and emphasize the changing roles of the key parties. It is expected that BCT would enhance the performance of the process across the three stages (i.e. trading, clearing and settlement within the stock exchange environment). A thorough literature review is conducted to understand the BCT performance modeling techniques and approaches (empirical and analytical) and to examine the theoretical potentials and capabilities of BCT in the financial markets. The case study and simulation methods are used to evaluate the impact of BCT implementation in optimizing the process of trading, clearing and settlement in Abu Dhabi Securities Exchange (ADX) stock-trading activities. This paper presents a simulation analysis comparing a blockchain system with a traditional trading system in the context of stock market. The simulation procedures involve modeling processes over different durations and transaction volumes, using metrics such as process time and cycle time to evaluate performance. The performance index combines these metrics with weights to ensure accurate and consistent measurements. Simulation results reveal that the blockchain system significantly outperforms the current trading system, especially at higher transaction volumes, highlighting its scalability and efficiency. A threshold of 30,000 transactions is identified as the point where blockchain’s benefits become apparent. The analysis shows that blockchain significantly elevate the process efficiency. It reduces both cycle time and process time across varying transaction volumes, maintaining consistency and reliability. Additionally, a simple simulation using the Hyperledger Fabric platform demonstrates the practical implementation of a permissioned blockchain for clearing transactions, emphasizing the system's capability to manage high transaction volumes efficiently and securely. The use of blockchain network for handling seamless transactions using pre-defined smart contracts significantly improves the performance of the stock trading processes, specifically in the clearing phase. Interestingly, the BCT system drops the need for a “third party” (i.e. stock custodian) across the three stages. At the end of the paper, we propose a thereat mitigating model for stock trading with a new blockchain system.
The article examines a new object of forensic economic examination – cryptocurrency. The author provides classic definitions of an object of forensic examination and establish the differences of cryptocurrency from the traditionally understood objects of both forensic examination in general and economic examination in particular. The main difference of cryptocurrency from other currencies and objects of investigation is its virtual nature, lack of affiliation with the material world. Two main points of view on the essence of cryptocurrency are analyzed: as a basis and tool for the development of new effective forms of payments, exchange of goods, and as an object and instrument of criminal activity. A definition of cryptocurrency is given as interpreted by the FATF – Financial Action Task Force. It is identified which issues related to the circulation of cryptocurrency can be attributed to the competence of a forensic expert-economist, and which – to the field of computer forensics. The author also describes the features of cryptocurrency that must be taken into account when considering it as an object of forensic economic examination.
Blockchain provides a decentralised, tamper-proof and trustworthy distributed database technology that is widely used in finance and economics, IoT and big data. Artificial intelligence (AI) provides a technology that can mimic human intelligence, learn autonomously and automate decision-making, which plays a major role in enhancing productivity, solving complex problems and improving decision-making. The two represent two of the major driving forces in technology today, and their integration is redefining our digital world. The aim of this paper is to explore the integration of these two technologies and the innovations, challenges, and future prospects they bring. First, we trace their history and evolution, introduce the basic characteristics of blockchain and AI, and explain in detail how they work. We then delve into the integration of blockchain and AI, highlighting their importance and significance in areas such as finance, supply chain and healthcare. We analyse the applications and implications of this integration for these areas, as well as the challenges and dilemmas faced, including issues of security, privacy, data leakage, and technical feasibility. Finally, we explore future trends and related work, highlighting the importance of global community collaboration and innovation to realize the potential of blockchain and AI.
Valentyn Bannikov, Stanislav Petko, Олександр Семенов, Олександр Журба · 5 authors
Introduction: this paper discusses and analyzes how blockchain technologies and smart contracts apply to automate assurance management processes with sustainability using a perspective model. The increase in demand for systems that are clear and secure in the automation of management processes calls for innovations such as blockchain and smart contracts. Objective: the objectives of the article are to identify the status of blockchain and smart contract adoption in many management processes; to consider the effect these technologies have on the efficiency, transparency, and sustainability of management operations.Methodology: we used regression and Markov analysis simulations to analyze the impacts of blockchain technologies on the management processes. The case study data were used to predict the long-term sustainability impacts, and simulations were carried out. Results: the regression established a positive but substantial effect of the adoption of blockchain technologies on the efficiency of management processes. 75 % of the efficiency score varies with the level of blockchain adoption. Simulations done using the Markov chain also showed that under the highest level of blockchain adoption, there is an effectivity of 90 percent where management processes would have improved and be efficient for the remaining ten years. The simulations also attested that partial adoption still offered a 70 % probability of sustained improvements.Conclusions: this paper provides strong evidence through regression analysis and Markov simulations showing the influence of these technologies. The ability of organizations to focus on innovative solutions toward sustainable management results is therefore realized